Sample records for average relative errors
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Estimation of open water evaporation using land-based meteorological data
NASA Astrophysics Data System (ADS)
Li, Fawen; Zhao, Yong
2017-10-01
Water surface evaporation is an important process in the hydrologic and energy cycles. Accurate simulation of water evaporation is important for the evaluation of water resources. In this paper, using meteorological data from the Aixinzhuang reservoir, the main factors affecting water surface evaporation were determined by the principal component analysis method. To illustrate the influence of these factors on water surface evaporation, the paper first adopted the Dalton model to simulate water surface evaporation. The results showed that the simulation precision was poor for the peak value zone. To improve the model simulation's precision, a modified Dalton model considering relative humidity was proposed. The results show that the 10-day average relative error is 17.2%, assessed as qualified; the monthly average relative error is 12.5%, assessed as qualified; and the yearly average relative error is 3.4%, assessed as excellent. To validate its applicability, the meteorological data of Kuancheng station in the Luan River basin were selected to test the modified model. The results show that the 10-day average relative error is 15.4%, assessed as qualified; the monthly average relative error is 13.3%, assessed as qualified; and the yearly average relative error is 6.0%, assessed as good. These results showed that the modified model had good applicability and versatility. The research results can provide technical support for the calculation of water surface evaporation in northern China or similar regions.
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Masked and unmasked error-related potentials during continuous control and feedback
NASA Astrophysics Data System (ADS)
Lopes Dias, Catarina; Sburlea, Andreea I.; Müller-Putz, Gernot R.
2018-06-01
The detection of error-related potentials (ErrPs) in tasks with discrete feedback is well established in the brain–computer interface (BCI) field. However, the decoding of ErrPs in tasks with continuous feedback is still in its early stages. Objective. We developed a task in which subjects have continuous control of a cursor’s position by means of a joystick. The cursor’s position was shown to the participants in two different modalities of continuous feedback: normal and jittered. The jittered feedback was created to mimic the instability that could exist if participants controlled the trajectory directly with brain signals. Approach. This paper studies the electroencephalographic (EEG)—measurable signatures caused by a loss of control over the cursor’s trajectory, causing a target miss. Main results. In both feedback modalities, time-locked potentials revealed the typical frontal-central components of error-related potentials. Errors occurring during the jittered feedback (masked errors) were delayed in comparison to errors occurring during normal feedback (unmasked errors). Masked errors displayed lower peak amplitudes than unmasked errors. Time-locked classification analysis allowed a good distinction between correct and error classes (average Cohen-, average TPR = 81.8% and average TNR = 96.4%). Time-locked classification analysis between masked error and unmasked error classes revealed results at chance level (average Cohen-, average TPR = 60.9% and average TNR = 58.3%). Afterwards, we performed asynchronous detection of ErrPs, combining both masked and unmasked trials. The asynchronous detection of ErrPs in a simulated online scenario resulted in an average TNR of 84.0% and in an average TPR of 64.9%. Significance. The time-locked classification results suggest that the masked and unmasked errors were indistinguishable in terms of classification. The asynchronous classification results suggest that the feedback modality did not hinder the asynchronous detection of ErrPs.
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Use of scan overlap redundancy to enhance multispectral aircraft scanner data
NASA Technical Reports Server (NTRS)
Lindenlaub, J. C.; Keat, J.
1973-01-01
Two criteria were suggested for optimizing the resolution error versus signal-to-noise-ratio tradeoff. The first criterion uses equal weighting coefficients and chooses n, the number of lines averaged, so as to make the average resolution error equal to the noise error. The second criterion adjusts both the number and relative sizes of the weighting coefficients so as to minimize the total error (resolution error plus noise error). The optimum set of coefficients depends upon the geometry of the resolution element, the number of redundant scan lines, the scan line increment, and the original signal-to-noise ratio of the channel. Programs were developed to find the optimum number and relative weights of the averaging coefficients. A working definition of signal-to-noise ratio was given and used to try line averaging on a typical set of data. Line averaging was evaluated only with respect to its effect on classification accuracy.
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Passive quantum error correction of linear optics networks through error averaging
NASA Astrophysics Data System (ADS)
Marshman, Ryan J.; Lund, Austin P.; Rohde, Peter P.; Ralph, Timothy C.
2018-02-01
We propose and investigate a method of error detection and noise correction for bosonic linear networks using a method of unitary averaging. The proposed error averaging does not rely on ancillary photons or control and feedforward correction circuits, remaining entirely passive in its operation. We construct a general mathematical framework for this technique and then give a series of proof of principle examples including numerical analysis. Two methods for the construction of averaging are then compared to determine the most effective manner of implementation and probe the related error thresholds. Finally we discuss some of the potential uses of this scheme.
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Sensitivity analysis of Jacobian determinant used in treatment planning for lung cancer
NASA Astrophysics Data System (ADS)
Shao, Wei; Gerard, Sarah E.; Pan, Yue; Patton, Taylor J.; Reinhardt, Joseph M.; Durumeric, Oguz C.; Bayouth, John E.; Christensen, Gary E.
2018-03-01
Four-dimensional computed tomography (4DCT) is regularly used to visualize tumor motion in radiation therapy for lung cancer. These 4DCT images can be analyzed to estimate local ventilation by finding a dense correspondence map between the end inhalation and the end exhalation CT image volumes using deformable image registration. Lung regions with ventilation values above a threshold are labeled as regions of high pulmonary function and are avoided when possible in the radiation plan. This paper investigates a sensitivity analysis of the relative Jacobian error to small registration errors. We present a linear approximation of the relative Jacobian error. Next, we give a formula for the sensitivity of the relative Jacobian error with respect to the Jacobian of perturbation displacement field. Preliminary sensitivity analysis results are presented using 4DCT scans from 10 individuals. For each subject, we generated 6400 random smooth biologically plausible perturbation vector fields using a cubic B-spline model. We showed that the correlation between the Jacobian determinant and the Frobenius norm of the sensitivity matrix is close to -1, which implies that the relative Jacobian error in high-functional regions is less sensitive to noise. We also showed that small displacement errors on the average of 0.53 mm may lead to a 10% relative change in Jacobian determinant. We finally showed that the average relative Jacobian error and the sensitivity of the system for all subjects are positively correlated (close to +1), i.e. regions with high sensitivity has more error in Jacobian determinant on average.
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Method of estimating natural recharge to the Edwards Aquifer in the San Antonio area, Texas
Puente, Celso
1978-01-01
The principal errors in the estimates of annual recharge are related to errors in estimating runoff in ungaged areas, which represent about 30 percent of the infiltration area. The estimated long-term average annual recharge in each basin, however, is probably representative of the actual recharge because the averaging procedure tends to cancel out the major errors.
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Preston, Jonathan L; Hull, Margaret; Edwards, Mary Louise
2013-05-01
To determine if speech error patterns in preschoolers with speech sound disorders (SSDs) predict articulation and phonological awareness (PA) outcomes almost 4 years later. Twenty-five children with histories of preschool SSDs (and normal receptive language) were tested at an average age of 4;6 (years;months) and were followed up at age 8;3. The frequency of occurrence of preschool distortion errors, typical substitution and syllable structure errors, and atypical substitution and syllable structure errors was used to predict later speech sound production, PA, and literacy outcomes. Group averages revealed below-average school-age articulation scores and low-average PA but age-appropriate reading and spelling. Preschool speech error patterns were related to school-age outcomes. Children for whom >10% of their speech sound errors were atypical had lower PA and literacy scores at school age than children who produced <10% atypical errors. Preschoolers who produced more distortion errors were likely to have lower school-age articulation scores than preschoolers who produced fewer distortion errors. Different preschool speech error patterns predict different school-age clinical outcomes. Many atypical speech sound errors in preschoolers may be indicative of weak phonological representations, leading to long-term PA weaknesses. Preschoolers' distortions may be resistant to change over time, leading to persisting speech sound production problems.
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Preston, Jonathan L.; Hull, Margaret; Edwards, Mary Louise
2012-01-01
Purpose To determine if speech error patterns in preschoolers with speech sound disorders (SSDs) predict articulation and phonological awareness (PA) outcomes almost four years later. Method Twenty-five children with histories of preschool SSDs (and normal receptive language) were tested at an average age of 4;6 and followed up at 8;3. The frequency of occurrence of preschool distortion errors, typical substitution and syllable structure errors, and atypical substitution and syllable structure errors were used to predict later speech sound production, PA, and literacy outcomes. Results Group averages revealed below-average school-age articulation scores and low-average PA, but age-appropriate reading and spelling. Preschool speech error patterns were related to school-age outcomes. Children for whom more than 10% of their speech sound errors were atypical had lower PA and literacy scores at school-age than children who produced fewer than 10% atypical errors. Preschoolers who produced more distortion errors were likely to have lower school-age articulation scores. Conclusions Different preschool speech error patterns predict different school-age clinical outcomes. Many atypical speech sound errors in preschool may be indicative of weak phonological representations, leading to long-term PA weaknesses. Preschool distortions may be resistant to change over time, leading to persisting speech sound production problems. PMID:23184137
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Spüler, Martin; Rosenstiel, Wolfgang; Bogdan, Martin
2012-01-01
The goal of a Brain-Computer Interface (BCI) is to control a computer by pure brain activity. Recently, BCIs based on code-modulated visual evoked potentials (c-VEPs) have shown great potential to establish high-performance communication. In this paper we present a c-VEP BCI that uses online adaptation of the classifier to reduce calibration time and increase performance. We compare two different approaches for online adaptation of the system: an unsupervised method and a method that uses the detection of error-related potentials. Both approaches were tested in an online study, in which an average accuracy of 96% was achieved with adaptation based on error-related potentials. This accuracy corresponds to an average information transfer rate of 144 bit/min, which is the highest bitrate reported so far for a non-invasive BCI. In a free-spelling mode, the subjects were able to write with an average of 21.3 error-free letters per minute, which shows the feasibility of the BCI system in a normal-use scenario. In addition we show that a calibration of the BCI system solely based on the detection of error-related potentials is possible, without knowing the true class labels.
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Performance of some numerical Laplace inversion methods on American put option formula
NASA Astrophysics Data System (ADS)
Octaviano, I.; Yuniar, A. R.; Anisa, L.; Surjanto, S. D.; Putri, E. R. M.
2018-03-01
Numerical inversion approaches of Laplace transform is used to obtain a semianalytic solution. Some of the mathematical inversion methods such as Durbin-Crump, Widder, and Papoulis can be used to calculate American put options through the optimal exercise price in the Laplace space. The comparison of methods on some simple functions is aimed to know the accuracy and parameters which used in the calculation of American put options. The result obtained is the performance of each method regarding accuracy and computational speed. The Durbin-Crump method has an average error relative of 2.006e-004 with computational speed of 0.04871 seconds, the Widder method has an average error relative of 0.0048 with computational speed of 3.100181 seconds, and the Papoulis method has an average error relative of 9.8558e-004 with computational speed of 0.020793 seconds.
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Methods for estimating flood frequency in Montana based on data through water year 1998
Parrett, Charles; Johnson, Dave R.
2004-01-01
Annual peak discharges having recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years (T-year floods) were determined for 660 gaged sites in Montana and in adjacent areas of Idaho, Wyoming, and Canada, based on data through water year 1998. The updated flood-frequency information was subsequently used in regression analyses, either ordinary or generalized least squares, to develop equations relating T-year floods to various basin and climatic characteristics, equations relating T-year floods to active-channel width, and equations relating T-year floods to bankfull width. The equations can be used to estimate flood frequency at ungaged sites. Montana was divided into eight regions, within which flood characteristics were considered to be reasonably homogeneous, and the three sets of regression equations were developed for each region. A measure of the overall reliability of the regression equations is the average standard error of prediction. The average standard errors of prediction for the equations based on basin and climatic characteristics ranged from 37.4 percent to 134.1 percent. Average standard errors of prediction for the equations based on active-channel width ranged from 57.2 percent to 141.3 percent. Average standard errors of prediction for the equations based on bankfull width ranged from 63.1 percent to 155.5 percent. In most regions, the equations based on basin and climatic characteristics generally had smaller average standard errors of prediction than equations based on active-channel or bankfull width. An exception was the Southeast Plains Region, where all equations based on active-channel width had smaller average standard errors of prediction than equations based on basin and climatic characteristics or bankfull width. Methods for weighting estimates derived from the basin- and climatic-characteristic equations and the channel-width equations also were developed. The weights were based on the cross correlation of residuals from the different methods and the average standard errors of prediction. When all three methods were combined, the average standard errors of prediction ranged from 37.4 percent to 120.2 percent. Weighting of estimates reduced the standard errors of prediction for all T-year flood estimates in four regions, reduced the standard errors of prediction for some T-year flood estimates in two regions, and provided no reduction in average standard error of prediction in two regions. A computer program for solving the regression equations, weighting estimates, and determining reliability of individual estimates was developed and placed on the USGS Montana District World Wide Web page. A new regression method, termed Region of Influence regression, also was tested. Test results indicated that the Region of Influence method was not as reliable as the regional equations based on generalized least squares regression. Two additional methods for estimating flood frequency at ungaged sites located on the same streams as gaged sites also are described. The first method, based on a drainage-area-ratio adjustment, is intended for use on streams where the ungaged site of interest is located near a gaged site. The second method, based on interpolation between gaged sites, is intended for use on streams that have two or more streamflow-gaging stations.
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NASA Astrophysics Data System (ADS)
Li, Xiongwei; Wang, Zhe; Lui, Siu-Lung; Fu, Yangting; Li, Zheng; Liu, Jianming; Ni, Weidou
2013-10-01
A bottleneck of the wide commercial application of laser-induced breakdown spectroscopy (LIBS) technology is its relatively high measurement uncertainty. A partial least squares (PLS) based normalization method was proposed to improve pulse-to-pulse measurement precision for LIBS based on our previous spectrum standardization method. The proposed model utilized multi-line spectral information of the measured element and characterized the signal fluctuations due to the variation of plasma characteristic parameters (plasma temperature, electron number density, and total number density) for signal uncertainty reduction. The model was validated by the application of copper concentration prediction in 29 brass alloy samples. The results demonstrated an improvement on both measurement precision and accuracy over the generally applied normalization as well as our previously proposed simplified spectrum standardization method. The average relative standard deviation (RSD), average of the standard error (error bar), the coefficient of determination (R2), the root-mean-square error of prediction (RMSEP), and average value of the maximum relative error (MRE) were 1.80%, 0.23%, 0.992, 1.30%, and 5.23%, respectively, while those for the generally applied spectral area normalization were 3.72%, 0.71%, 0.973, 1.98%, and 14.92%, respectively.
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Errors in Multi-Digit Arithmetic and Behavioral Inattention in Children With Math Difficulties
Raghubar, Kimberly; Cirino, Paul; Barnes, Marcia; Ewing-Cobbs, Linda; Fletcher, Jack; Fuchs, Lynn
2009-01-01
Errors in written multi-digit computation were investigated in children with math difficulties. Third-and fourth-grade children (n = 291) with coexisting math and reading difficulties, math difficulties, reading difficulties, or no learning difficulties were compared. A second analysis compared those with severe math learning difficulties, low average achievement in math, and no learning difficulties. Math fact errors were related to the severity of the math difficulties, not to reading status. Contrary to predictions, children with poorer reading, regardless of math achievement, committed more visually based errors. Operation switch errors were not systematically related to group membership. Teacher ratings of behavioral inattention were related to accuracy, math fact errors, and procedural bugs. The findings are discussed with respect to hypotheses about the cognitive origins of arithmetic errors and in relation to current discussions about how to conceptualize math disabilities. PMID:19380494
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Field Comparison between Sling Psychrometer and Meteorological Measuring Set AN/TMQ-22
the ML-224 Sling Psychrometer . From a series of independent tests designed to minimize error it was concluded that the AN/TMQ-22 yielded a more accurate...dew point reading. The average relative humidity error using the sling psychrometer was +9% while the AN/TMQ-22 had a plus or minus 2% error. Even with cautious measurement the sling yielded a +4% error.
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Mobarakabadi, Sedigheh Sedigh; Ebrahimipour, Hosein; Najar, Ali Vafaie; Janghorban, Roksana; Azarkish, Fatemeh
2017-03-01
Patient's safety is one of the main objective in healthcare services; however medical errors are a prevalent potential occurrence for the patients in treatment systems. Medical errors lead to an increase in mortality rate of the patients and challenges such as prolonging of the inpatient period in the hospitals and increased cost. Controlling the medical errors is very important, because these errors besides being costly, threaten the patient's safety. To evaluate the attitudes of nurses and midwives toward the causes and rates of medical errors reporting. It was a cross-sectional observational study. The study population was 140 midwives and nurses employed in Mashhad Public Hospitals. The data collection was done through Goldstone 2001 revised questionnaire. SPSS 11.5 software was used for data analysis. To analyze data, descriptive and inferential analytic statistics were used. Standard deviation and relative frequency distribution, descriptive statistics were used for calculation of the mean and the results were adjusted as tables and charts. Chi-square test was used for the inferential analysis of the data. Most of midwives and nurses (39.4%) were in age range of 25 to 34 years and the lowest percentage (2.2%) were in age range of 55-59 years. The highest average of medical errors was related to employees with three-four years of work experience, while the lowest average was related to those with one-two years of work experience. The highest average of medical errors was during the evening shift, while the lowest were during the night shift. Three main causes of medical errors were considered: illegibile physician prescription orders, similarity of names in different drugs and nurse fatigueness. The most important causes for medical errors from the viewpoints of nurses and midwives are illegible physician's order, drug name similarity with other drugs, nurse's fatigueness and damaged label or packaging of the drug, respectively. Head nurse feedback, peer feedback, fear of punishment or job loss were considered as reasons for under reporting of medical errors. This research demonstrates the need for greater attention to be paid to the causes of medical errors.
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Accuracy of acoustic velocity metering systems for measurement of low velocity in open channels
Laenen, Antonius; Curtis, R. E.
1989-01-01
Acoustic velocity meter (AVM) accuracy depends on equipment limitations, the accuracy of acoustic-path length and angle determination, and the stability of the mean velocity to acoustic-path velocity relation. Equipment limitations depend on path length and angle, transducer frequency, timing oscillator frequency, and signal-detection scheme. Typically, the velocity error from this source is about +or-1 to +or-10 mms/sec. Error in acoustic-path angle or length will result in a proportional measurement bias. Typically, an angle error of one degree will result in a velocity error of 2%, and a path-length error of one meter in 100 meter will result in an error of 1%. Ray bending (signal refraction) depends on path length and density gradients present in the stream. Any deviation from a straight acoustic path between transducer will change the unique relation between path velocity and mean velocity. These deviations will then introduce error in the mean velocity computation. Typically, for a 200-meter path length, the resultant error is less than one percent, but for a 1,000 meter path length, the error can be greater than 10%. Recent laboratory and field tests have substantiated assumptions of equipment limitations. Tow-tank tests of an AVM system with a 4.69-meter path length yielded an average standard deviation error of 9.3 mms/sec, and the field tests of an AVM system with a 20.5-meter path length yielded an average standard deviation error of a 4 mms/sec. (USGS)
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Mendiburu, Andrés Z; de Carvalho, João A; Coronado, Christian R
2015-03-21
Estimation of the lower flammability limits of C-H compounds at 25 °C and 1 atm; at moderate temperatures and in presence of diluent was the objective of this study. A set of 120 C-H compounds was divided into a correlation set and a prediction set of 60 compounds each. The absolute average relative error for the total set was 7.89%; for the correlation set, it was 6.09%; and for the prediction set it was 9.68%. However, it was shown that by considering different sources of experimental data the values were reduced to 6.5% for the prediction set and to 6.29% for the total set. The method showed consistency with Le Chatelier's law for binary mixtures of C-H compounds. When tested for a temperature range from 5 °C to 100 °C, the absolute average relative errors were 2.41% for methane; 4.78% for propane; 0.29% for iso-butane and 3.86% for propylene. When nitrogen was added, the absolute average relative errors were 2.48% for methane; 5.13% for propane; 0.11% for iso-butane and 0.15% for propylene. When carbon dioxide was added, the absolute relative errors were 1.80% for methane; 5.38% for propane; 0.86% for iso-butane and 1.06% for propylene. Copyright © 2014 Elsevier B.V. All rights reserved.
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NASA Astrophysics Data System (ADS)
Gryaznov, D.; Fleig, J.; Maier, J.
2008-03-01
Whipple's solution of the problem of grain boundary diffusion and Le Claire's relation, which is often used to determine grain boundary diffusion coefficients, are examined for a broad range of ratios of grain boundary to bulk diffusivities Δ and diffusion times t. Different reasons leading to errors in determining the grain boundary diffusivity (DGB) when using Le Claire's relation are discussed. It is shown that nonlinearities of the diffusion profiles in lnCav-y6/5 plots and deviations from "Le Claire's constant" (-0.78) are the major error sources (Cav=averaged concentration, y =coordinate in diffusion direction). An improved relation (replacing Le Claire's constant) is suggested for analyzing diffusion profiles particularly suited for small diffusion lengths (short times) as often required in diffusion experiments on nanocrystalline materials.
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Early math and reading achievement are associated with the error positivity.
Kim, Matthew H; Grammer, Jennie K; Marulis, Loren M; Carrasco, Melisa; Morrison, Frederick J; Gehring, William J
2016-12-01
Executive functioning (EF) and motivation are associated with academic achievement and error-related ERPs. The present study explores whether early academic skills predict variability in the error-related negativity (ERN) and error positivity (Pe). Data from 113 three- to seven-year-old children in a Go/No-Go task revealed that stronger early reading and math skills predicted a larger Pe. Closer examination revealed that this relation was quadratic and significant for children performing at or near grade level, but not significant for above-average achievers. Early academics did not predict the ERN. These findings suggest that the Pe - which reflects individual differences in motivational processes as well as attention - may be associated with early academic achievement. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
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Topographic analysis of individual activation patterns in medial frontal cortex in schizophrenia
Stern, Emily R.; Welsh, Robert C.; Fitzgerald, Kate D.; Taylor, Stephan F.
2009-01-01
Individual variability in the location of neural activations poses a unique problem for neuroimaging studies employing group averaging techniques to investigate the neural bases of cognitive and emotional functions. This may be especially challenging for studies examining patient groups, which often have limited sample sizes and increased intersubject variability. In particular, medial frontal cortex (MFC) dysfunction is thought to underlie performance monitoring dysfunction among patients with previous studies using group averaging to have yielded conflicting results. schizophrenia, yet compare schizophrenic patients to controls To examine individual activations in MFC associated with two aspects of performance monitoring, interference and error processing, functional magnetic resonance imaging (fMRI) data were acquired while 17 patients with schizophrenia and 21 healthy controls performed an event-related version of the multi-source interference task. Comparisons of averaged data revealed few differences between the groups. By contrast, topographic analysis of individual activations for errors showed that control subjects exhibited activations spanning across both posterior and anterior regions of MFC while patients primarily activated posterior MFC, possibly reflecting an impaired emotional response to errors in schizophrenia. This discrepancy between topographic and group-averaged results may be due to the significant dispersion among individual activations, particularly among healthy controls, highlighting the importance of considering intersubject variability when interpreting the medial frontal response to error commission. PMID:18819107
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Efficient Measurement of Quantum Gate Error by Interleaved Randomized Benchmarking
NASA Astrophysics Data System (ADS)
Magesan, Easwar; Gambetta, Jay M.; Johnson, B. R.; Ryan, Colm A.; Chow, Jerry M.; Merkel, Seth T.; da Silva, Marcus P.; Keefe, George A.; Rothwell, Mary B.; Ohki, Thomas A.; Ketchen, Mark B.; Steffen, M.
2012-08-01
We describe a scalable experimental protocol for estimating the average error of individual quantum computational gates. This protocol consists of interleaving random Clifford gates between the gate of interest and provides an estimate as well as theoretical bounds for the average error of the gate under test, so long as the average noise variation over all Clifford gates is small. This technique takes into account both state preparation and measurement errors and is scalable in the number of qubits. We apply this protocol to a superconducting qubit system and find a bounded average error of 0.003 [0,0.016] for the single-qubit gates Xπ/2 and Yπ/2. These bounded values provide better estimates of the average error than those extracted via quantum process tomography.
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Error rate of automated calculation for wound surface area using a digital photography.
Yang, S; Park, J; Lee, H; Lee, J B; Lee, B U; Oh, B H
2018-02-01
Although measuring would size using digital photography is a quick and simple method to evaluate the skin wound, the possible compatibility of it has not been fully validated. To investigate the error rate of our newly developed wound surface area calculation using digital photography. Using a smartphone and a digital single lens reflex (DSLR) camera, four photographs of various sized wounds (diameter: 0.5-3.5 cm) were taken from the facial skin model in company with color patches. The quantitative values of wound areas were automatically calculated. The relative error (RE) of this method with regard to wound sizes and types of camera was analyzed. RE of individual calculated area was from 0.0329% (DSLR, diameter 1.0 cm) to 23.7166% (smartphone, diameter 2.0 cm). In spite of the correction of lens curvature, smartphone has significantly higher error rate than DSLR camera (3.9431±2.9772 vs 8.1303±4.8236). However, in cases of wound diameter below than 3 cm, REs of average values of four photographs were below than 5%. In addition, there was no difference in the average value of wound area taken by smartphone and DSLR camera in those cases. For the follow-up of small skin defect (diameter: <3 cm), our newly developed automated wound area calculation method is able to be applied to the plenty of photographs, and the average values of them are a relatively useful index of wound healing with acceptable error rate. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
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Geometrical correction factors for heat flux meters
NASA Technical Reports Server (NTRS)
Baumeister, K. J.; Papell, S. S.
1974-01-01
General formulas are derived for determining gage averaging errors of strip-type heat flux meters used in the measurement of one-dimensional heat flux distributions. The local averaging error e(x) is defined as the difference between the measured value of the heat flux and the local value which occurs at the center of the gage. In terms of e(x), a correction procedure is presented which allows a better estimate for the true value of the local heat flux. For many practical problems, it is possible to use relatively large gages to obtain acceptable heat flux measurements.
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Jensen, Jonas; Olesen, Jacob Bjerring; Stuart, Matthias Bo; Hansen, Peter Møller; Nielsen, Michael Bachmann; Jensen, Jørgen Arendt
2016-08-01
A method for vector velocity volume flow estimation is presented, along with an investigation of its sources of error and correction of actual volume flow measurements. Volume flow errors are quantified theoretically by numerical modeling, through flow phantom measurements, and studied in vivo. This paper investigates errors from estimating volumetric flow using a commercial ultrasound scanner and the common assumptions made in the literature. The theoretical model shows, e.g. that volume flow is underestimated by 15%, when the scan plane is off-axis with the vessel center by 28% of the vessel radius. The error sources were also studied in vivo under realistic clinical conditions, and the theoretical results were applied for correcting the volume flow errors. Twenty dialysis patients with arteriovenous fistulas were scanned to obtain vector flow maps of fistulas. When fitting an ellipsis to cross-sectional scans of the fistulas, the major axis was on average 10.2mm, which is 8.6% larger than the minor axis. The ultrasound beam was on average 1.5mm from the vessel center, corresponding to 28% of the semi-major axis in an average fistula. Estimating volume flow with an elliptical, rather than circular, vessel area and correcting the ultrasound beam for being off-axis, gave a significant (p=0.008) reduction in error from 31.2% to 24.3%. The error is relative to the Ultrasound Dilution Technique, which is considered the gold standard for volume flow estimation for dialysis patients. The study shows the importance of correcting for volume flow errors, which are often made in clinical practice. Copyright © 2016 Elsevier B.V. All rights reserved.
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Error analysis of 3D-PTV through unsteady interfaces
NASA Astrophysics Data System (ADS)
Akutina, Yulia; Mydlarski, Laurent; Gaskin, Susan; Eiff, Olivier
2018-03-01
The feasibility of stereoscopic flow measurements through an unsteady optical interface is investigated. Position errors produced by a wavy optical surface are determined analytically, as are the optimal viewing angles of the cameras to minimize such errors. Two methods of measuring the resulting velocity errors are proposed. These methods are applied to 3D particle tracking velocimetry (3D-PTV) data obtained through the free surface of a water flow within a cavity adjacent to a shallow channel. The experiments were performed using two sets of conditions, one having no strong surface perturbations, and the other exhibiting surface gravity waves. In the latter case, the amplitude of the gravity waves was 6% of the water depth, resulting in water surface inclinations of about 0.2°. (The water depth is used herein as a relevant length scale, because the measurements are performed in the entire water column. In a more general case, the relevant scale is the maximum distance from the interface to the measurement plane, H, which here is the same as the water depth.) It was found that the contribution of the waves to the overall measurement error is low. The absolute position errors of the system were moderate (1.2% of H). However, given that the velocity is calculated from the relative displacement of a particle between two frames, the errors in the measured water velocities were reasonably small, because the error in the velocity is the relative position error over the average displacement distance. The relative position error was measured to be 0.04% of H, resulting in small velocity errors of 0.3% of the free-stream velocity (equivalent to 1.1% of the average velocity in the domain). It is concluded that even though the absolute positions to which the velocity vectors are assigned is distorted by the unsteady interface, the magnitude of the velocity vectors themselves remains accurate as long as the waves are slowly varying (have low curvature). The stronger the disturbances on the interface are (high amplitude, short wave length), the smaller is the distance from the interface at which the measurements can be performed.
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Anandakrishnan, Ramu; Onufriev, Alexey
2008-03-01
In statistical mechanics, the equilibrium properties of a physical system of particles can be calculated as the statistical average over accessible microstates of the system. In general, these calculations are computationally intractable since they involve summations over an exponentially large number of microstates. Clustering algorithms are one of the methods used to numerically approximate these sums. The most basic clustering algorithms first sub-divide the system into a set of smaller subsets (clusters). Then, interactions between particles within each cluster are treated exactly, while all interactions between different clusters are ignored. These smaller clusters have far fewer microstates, making the summation over these microstates, tractable. These algorithms have been previously used for biomolecular computations, but remain relatively unexplored in this context. Presented here, is a theoretical analysis of the error and computational complexity for the two most basic clustering algorithms that were previously applied in the context of biomolecular electrostatics. We derive a tight, computationally inexpensive, error bound for the equilibrium state of a particle computed via these clustering algorithms. For some practical applications, it is the root mean square error, which can be significantly lower than the error bound, that may be more important. We how that there is a strong empirical relationship between error bound and root mean square error, suggesting that the error bound could be used as a computationally inexpensive metric for predicting the accuracy of clustering algorithms for practical applications. An example of error analysis for such an application-computation of average charge of ionizable amino-acids in proteins-is given, demonstrating that the clustering algorithm can be accurate enough for practical purposes.
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Statistics of the radiated field of a space-to-earth microwave power transfer system
NASA Technical Reports Server (NTRS)
Stevens, G. H.; Leininger, G.
1976-01-01
Statistics such as average power density pattern, variance of the power density pattern and variance of the beam pointing error are related to hardware parameters such as transmitter rms phase error and rms amplitude error. Also a limitation on spectral width of the phase reference for phase control was established. A 1 km diameter transmitter appears feasible provided the total rms insertion phase errors of the phase control modules does not exceed 10 deg, amplitude errors do not exceed 10% rms, and the phase reference spectral width does not exceed approximately 3 kHz. With these conditions the expected radiation pattern is virtually the same as the error free pattern, and the rms beam pointing error would be insignificant (approximately 10 meters).
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Instrument Pointing Capabilities: Past, Present, and Future
NASA Technical Reports Server (NTRS)
Blackmore, Lars; Murray, Emmanuell; Scharf, Daniel P.; Aung, Mimi; Bayard, David; Brugarolas, Paul; Hadaegh, Fred; Lee, Allan; Milman, Mark; Sirlin, Sam;
2011-01-01
This paper surveys the instrument pointing capabilities of past, present and future space telescopes and interferometers. As an important aspect of this survey, we present a taxonomy for "apples-to-apples" comparisons of pointing performances. First, pointing errors are defined relative to either an inertial frame or a celestial target. Pointing error can then be further sub-divided into DC, that is, steady state, and AC components. We refer to the magnitude of the DC error relative to the inertial frame as absolute pointing accuracy, and we refer to the magnitude of the DC error relative to a celestial target as relative pointing accuracy. The magnitude of the AC error is referred to as pointing stability. While an AC/DC partition is not new, we leverage previous work by some of the authors to quantitatively clarify and compare varying definitions of jitter and time window averages. With this taxonomy and for sixteen past, present, and future missions, pointing accuracies and stabilities, both required and achieved, are presented. In addition, we describe the attitude control technologies used to and, for future missions, planned to achieve these pointing performances.
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Do alcohol excise taxes affect traffic accidents? Evidence from Estonia.
Saar, Indrek
2015-01-01
This article examines the association between alcohol excise tax rates and alcohol-related traffic accidents in Estonia. Monthly time series of traffic accidents involving drunken motor vehicle drivers from 1998 through 2013 were regressed on real average alcohol excise tax rates while controlling for changes in economic conditions and the traffic environment. Specifically, regression models with autoregressive integrated moving average (ARIMA) errors were estimated in order to deal with serial correlation in residuals. Counterfactual models were also estimated in order to check the robustness of the results, using the level of non-alcohol-related traffic accidents as a dependent variable. A statistically significant (P <.01) strong negative relationship between the real average alcohol excise tax rate and alcohol-related traffic accidents was disclosed under alternative model specifications. For instance, the regression model with ARIMA (0, 1, 1)(0, 1, 1) errors revealed that a 1-unit increase in the tax rate is associated with a 1.6% decrease in the level of accidents per 100,000 population involving drunk motor vehicle drivers. No similar association was found in the cases of counterfactual models for non-alcohol-related traffic accidents. This article indicates that the level of alcohol-related traffic accidents in Estonia has been affected by changes in real average alcohol excise taxes during the period 1998-2013. Therefore, in addition to other measures, the use of alcohol taxation is warranted as a policy instrument in tackling alcohol-related traffic accidents.
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NASA Astrophysics Data System (ADS)
Shan, Y.; Eric, W.; Gao, L.; Zhao, T.; Yin, Y.
2015-12-01
In this study, we have evaluated the performance of size distribution functions (SDF) with 2- and 3-moments in fitting the observed size distribution of rain droplets at three different heights. The goal is to improve the microphysics schemes in meso-scale models, such as Weather Research and Forecast (WRF). Rain droplets were observed during eight periods of different rain types at three stations on the Yellow Mountain in East China. The SDF in this study were M-P distribution with a fixed shape parameter in Gamma SDF(FSP). Where the Gamma SDFs were obtained with three diagnosis methods with the shape parameters based on Milbrandt (2010; denoted DSPM10), Milbrandt (2005; denoted DSPM05) and Seifert (2008; denoted DSPS08) for solving the shape parameter(SSP) and Lognormal SDF. Based on the preliminary experiments, three ensemble methods deciding Gamma SDF was also developed and assessed. The magnitude of average relative error caused by applying a FSP was 10-2 for fitting 0-order moment of the observed rain droplet distribution, and the magnitude of average relative error changed to 10-1 and 100 respectively for 1-4 order moments and 5-6 order moments. To different extent, DSPM10, DSPM05, DSPS08, SSP and ensemble methods could improve fitting accuracies for 0-6 order moments, especially the one coupling SSP and DSPS08 methods, which provided a average relative error 6.46% for 1-4 order moments and 11.90% for 5-6 order moments, respectively. The relative error of fitting three moments using the Lognormal SDF was much larger than that of Gamma SDF. The threshold value of shape parameter ranged from 0 to 8, because values beyond this range could cause overflow in the calculation. When average diameter of rain droplets was less than 2mm, the possibility of unavailable shape parameter value(USPV) increased with a decreasing droplet size. There was strong sensitivity of moment group in fitting accuracy. When ensemble method coupling SSP and DSPS08 was used, a better fit to 1-3-5 moments of the SDF was possible compared to fitting the 0-3-6 moment group.
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On the Probability of Error and Stochastic Resonance in Discrete Memoryless Channels
2013-12-01
Information - Driven Doppler Shift Estimation and Compensation Methods for Underwater Wireless Sensor Networks ”, which is to analyze and develop... underwater wireless sensor networks . We formulated an analytic relationship that relates the average probability of error to the systems parameters, the...thesis, we studied the performance of Discrete Memoryless Channels (DMC), arising in the context of cooperative underwater wireless sensor networks
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Rate, causes and reporting of medication errors in Jordan: nurses' perspectives.
Mrayyan, Majd T; Shishani, Kawkab; Al-Faouri, Ibrahim
2007-09-01
The aim of the study was to describe Jordanian nurses' perceptions about various issues related to medication errors. This is the first nursing study about medication errors in Jordan. This was a descriptive study. A convenient sample of 799 nurses from 24 hospitals was obtained. Descriptive and inferential statistics were used for data analysis. Over the course of their nursing career, the average number of recalled committed medication errors per nurse was 2.2. Using incident reports, the rate of medication errors reported to nurse managers was 42.1%. Medication errors occurred mainly when medication labels/packaging were of poor quality or damaged. Nurses failed to report medication errors because they were afraid that they might be subjected to disciplinary actions or even lose their jobs. In the stepwise regression model, gender was the only predictor of medication errors in Jordan. Strategies to reduce or eliminate medication errors are required.
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NASA Technical Reports Server (NTRS)
Bell, Thomas L.; Kundu, Prasun K.; Einaudi, Franco (Technical Monitor)
2000-01-01
Estimates from TRMM satellite data of monthly total rainfall over an area are subject to substantial sampling errors due to the limited number of visits to the area by the satellite during the month. Quantitative comparisons of TRMM averages with data collected by other satellites and by ground-based systems require some estimate of the size of this sampling error. A method of estimating this sampling error based on the actual statistics of the TRMM observations and on some modeling work has been developed. "Sampling error" in TRMM monthly averages is defined here relative to the monthly total a hypothetical satellite permanently stationed above the area would have reported. "Sampling error" therefore includes contributions from the random and systematic errors introduced by the satellite remote sensing system. As part of our long-term goal of providing error estimates for each grid point accessible to the TRMM instruments, sampling error estimates for TRMM based on rain retrievals from TRMM microwave (TMI) data are compared for different times of the year and different oceanic areas (to minimize changes in the statistics due to algorithmic differences over land and ocean). Changes in sampling error estimates due to changes in rain statistics due 1) to evolution of the official algorithms used to process the data, and 2) differences from other remote sensing systems such as the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I), are analyzed.
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NASA Astrophysics Data System (ADS)
Zhang, Min; Wang, Wen; Xiang, Kui; Lu, Keqing; Fan, Zongwei
2015-02-01
This paper describes a novel cylindrical capacitive sensor (CCS) to measure the spindle five degree-of-freedom (DOF) motion errors. The operating principle and mathematical models of the CCS are presented. Using Ansoft Maxwell software to calculate the different capacitances in different configurations, structural parameters of end face electrode are then investigated. Radial, axial and tilt motions are also simulated by making comparisons with the given displacements and the simulation values respectively. It could be found that the proposed CCS has a high accuracy for measuring radial motion error when the average eccentricity is about 15 μm. Besides, the maximum relative error of axial displacement is 1.3% when the axial motion is within [0.7, 1.3] mm, and the maximum relative error of the tilt displacement is 1.6% as rotor tilts around a single axis within [-0.6, 0.6]°. Finally, the feasibility of the CCS for measuring five DOF motion errors is verified through simulation and analysis.
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NASA Astrophysics Data System (ADS)
Siirila, E. R.; Fernandez-Garcia, D.; Sanchez-Vila, X.
2014-12-01
Particle tracking (PT) techniques, often considered favorable over Eulerian techniques due to artificial smoothening in breakthrough curves (BTCs), are evaluated in a risk-driven framework. Recent work has shown that given a relatively few number of particles (np), PT methods can yield well-constructed BTCs with kernel density estimators (KDEs). This work compares KDE and non-KDE BTCs simulated as a function of np (102-108) and averaged as a function of the exposure duration, ED. Results show that regardless of BTC shape complexity, un-averaged PT BTCs show a large bias over several orders of magnitude in concentration (C) when compared to the KDE results, remarkably even when np is as low as 102. With the KDE, several orders of magnitude less np are required to obtain the same global error in BTC shape as the PT technique. PT and KDE BTCs are averaged as a function of the ED with standard and new methods incorporating the optimal h (ANA). The lowest error curve is obtained through the ANA method, especially for smaller EDs. Percent error of peak of averaged-BTCs, important in a risk framework, is approximately zero for all scenarios and all methods for np ≥105, but vary between the ANA and PT methods, when np is lower. For fewer np, the ANA solution provides a lower error fit except when C oscillations are present during a short time frame. We show that obtaining a representative average exposure concentration is reliant on an accurate representation of the BTC, especially when data is scarce.
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NASA Astrophysics Data System (ADS)
Rahmat, R. F.; Nasution, F. R.; Seniman; Syahputra, M. F.; Sitompul, O. S.
2018-02-01
Weather is condition of air in a certain region at a relatively short period of time, measured with various parameters such as; temperature, air preasure, wind velocity, humidity and another phenomenons in the atmosphere. In fact, extreme weather due to global warming would lead to drought, flood, hurricane and other forms of weather occasion, which directly affects social andeconomic activities. Hence, a forecasting technique is to predict weather with distinctive output, particullary mapping process based on GIS with information about current weather status in certain cordinates of each region with capability to forecast for seven days afterward. Data used in this research are retrieved in real time from the server openweathermap and BMKG. In order to obtain a low error rate and high accuracy of forecasting, the authors use Bayesian Model Averaging (BMA) method. The result shows that the BMA method has good accuracy. Forecasting error value is calculated by mean square error shows (MSE). The error value emerges at minumum temperature rated at 0.28 and maximum temperature rated at 0.15. Meanwhile, the error value of minimum humidity rates at 0.38 and the error value of maximum humidity rates at 0.04. Afterall, the forecasting error rate of wind speed is at 0.076. The lower the forecasting error rate, the more optimized the accuracy is.
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Peak-flow characteristics of Wyoming streams
Miller, Kirk A.
2003-01-01
Peak-flow characteristics for unregulated streams in Wyoming are described in this report. Frequency relations for annual peak flows through water year 2000 at 364 streamflow-gaging stations in and near Wyoming were evaluated and revised or updated as needed. Analyses of historical floods, temporal trends, and generalized skew were included in the evaluation. Physical and climatic basin characteristics were determined for each gaging station using a geographic information system. Gaging stations with similar peak-flow and basin characteristics were grouped into six hydrologic regions. Regional statistical relations between peak-flow and basin characteristics were explored using multiple-regression techniques. Generalized least squares regression equations for estimating magnitudes of annual peak flows with selected recurrence intervals from 1.5 to 500 years were developed for each region. Average standard errors of estimate range from 34 to 131 percent. Average standard errors of prediction range from 35 to 135 percent. Several statistics for evaluating and comparing the errors in these estimates are described. Limitations of the equations are described. Methods for applying the regional equations for various circumstances are listed and examples are given.
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Center-to-Limb Variation of Deprojection Errors in SDO/HMI Vector Magnetograms
NASA Astrophysics Data System (ADS)
Falconer, David; Moore, Ronald; Barghouty, Nasser; Tiwari, Sanjiv K.; Khazanov, Igor
2015-04-01
For use in investigating the magnetic causes of coronal heating in active regions and for use in forecasting an active region’s productivity of major CME/flare eruptions, we have evaluated various sunspot-active-region magnetic measures (e.g., total magnetic flux, free-magnetic-energy proxies, magnetic twist measures) from HMI Active Region Patches (HARPs) after the HARP has been deprojected to disk center. From a few tens of thousand HARP vector magnetograms (of a few hundred sunspot active regions) that have been deprojected to disk center, we have determined that the errors in the whole-HARP magnetic measures from deprojection are negligibly small for HARPS deprojected from distances out to 45 heliocentric degrees. For some purposes the errors from deprojection are tolerable out to 60 degrees. We obtained this result by the following process. For each whole-HARP magnetic measure: 1) for each HARP disk passage, normalize the measured values by the measured value for that HARP at central meridian; 2) then for each 0.05 Rs annulus, average the values from all the HARPs in the annulus. This results in an average normalized value as a function of radius for each measure. Assuming no deprojection errors and that, among a large set of HARPs, the measure is as likely to decrease as to increase with HARP distance from disk center, the average of each annulus is expected to be unity, and, for a statistically large sample, the amount of deviation of the average from unity estimates the error from deprojection effects. The deprojection errors arise from 1) errors in the transverse field being deprojected into the vertical field for HARPs observed at large distances from disk center, 2) increasingly larger foreshortening at larger distances from disk center, and 3) possible errors in transverse-field-direction ambiguity resolution.From the compiled set of measured vales of whole-HARP magnetic nonpotentiality parameters measured from deprojected HARPs, we have examined the relation between each nonpotentiality parameter and the speed of CMEs from the measured active regions. For several different nonpotentiality parameters we find there is an upper limit to the CME speed, the limit increasing as the value of the parameter increases.
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Hess, Glen W.
2002-01-01
Techniques for estimating monthly streamflow-duration characteristics at ungaged and partial-record sites in central Nevada have been updated. These techniques were developed using streamflow records at six continuous-record sites, basin physical and climatic characteristics, and concurrent streamflow measurements at four partial-record sites. Two methods, the basin-characteristic method and the concurrent-measurement method, were developed to provide estimating techniques for selected streamflow characteristics at ungaged and partial-record sites in central Nevada. In the first method, logarithmic-regression analyses were used to relate monthly mean streamflows (from all months and by month) from continuous-record gaging sites of various percent exceedence levels or monthly mean streamflows (by month) to selected basin physical and climatic variables at ungaged sites. Analyses indicate that the total drainage area and percent of drainage area at altitudes greater than 10,000 feet are the most significant variables. For the equations developed from all months of monthly mean streamflow, the coefficient of determination averaged 0.84 and the standard error of estimate of the relations for the ungaged sites averaged 72 percent. For the equations derived from monthly means by month, the coefficient of determination averaged 0.72 and the standard error of estimate of the relations averaged 78 percent. If standard errors are compared, the relations developed in this study appear generally to be less accurate than those developed in a previous study. However, the new relations are based on additional data and the slight increase in error may be due to the wider range of streamflow for a longer period of record, 1995-2000. In the second method, streamflow measurements at partial-record sites were correlated with concurrent streamflows at nearby gaged sites by the use of linear-regression techniques. Statistical measures of results using the second method typically indicated greater accuracy than for the first method. However, to make estimates for individual months, the concurrent-measurement method requires several years additional streamflow data at more partial-record sites. Thus, exceedence values for individual months are not yet available due to the low number of concurrent-streamflow-measurement data available. Reliability, limitations, and applications of both estimating methods are described herein.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Hsin-Chen; Tan, Jun; Dolly, Steven
2015-02-15
Purpose: One of the most critical steps in radiation therapy treatment is accurate tumor and critical organ-at-risk (OAR) contouring. Both manual and automated contouring processes are prone to errors and to a large degree of inter- and intraobserver variability. These are often due to the limitations of imaging techniques in visualizing human anatomy as well as to inherent anatomical variability among individuals. Physicians/physicists have to reverify all the radiation therapy contours of every patient before using them for treatment planning, which is tedious, laborious, and still not an error-free process. In this study, the authors developed a general strategy basedmore » on novel geometric attribute distribution (GAD) models to automatically detect radiation therapy OAR contouring errors and facilitate the current clinical workflow. Methods: Considering the radiation therapy structures’ geometric attributes (centroid, volume, and shape), the spatial relationship of neighboring structures, as well as anatomical similarity of individual contours among patients, the authors established GAD models to characterize the interstructural centroid and volume variations, and the intrastructural shape variations of each individual structure. The GAD models are scalable and deformable, and constrained by their respective principal attribute variations calculated from training sets with verified OAR contours. A new iterative weighted GAD model-fitting algorithm was developed for contouring error detection. Receiver operating characteristic (ROC) analysis was employed in a unique way to optimize the model parameters to satisfy clinical requirements. A total of forty-four head-and-neck patient cases, each of which includes nine critical OAR contours, were utilized to demonstrate the proposed strategy. Twenty-nine out of these forty-four patient cases were utilized to train the inter- and intrastructural GAD models. These training data and the remaining fifteen testing data sets were separately employed to test the effectiveness of the proposed contouring error detection strategy. Results: An evaluation tool was implemented to illustrate how the proposed strategy automatically detects the radiation therapy contouring errors for a given patient and provides 3D graphical visualization of error detection results as well. The contouring error detection results were achieved with an average sensitivity of 0.954/0.906 and an average specificity of 0.901/0.909 on the centroid/volume related contouring errors of all the tested samples. As for the detection results on structural shape related contouring errors, an average sensitivity of 0.816 and an average specificity of 0.94 on all the tested samples were obtained. The promising results indicated the feasibility of the proposed strategy for the detection of contouring errors with low false detection rate. Conclusions: The proposed strategy can reliably identify contouring errors based upon inter- and intrastructural constraints derived from clinically approved contours. It holds great potential for improving the radiation therapy workflow. ROC and box plot analyses allow for analytically tuning of the system parameters to satisfy clinical requirements. Future work will focus on the improvement of strategy reliability by utilizing more training sets and additional geometric attribute constraints.« less
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Wu, S.-S.; Wang, L.; Qiu, X.
2008-01-01
This article presents a deterministic model for sub-block-level population estimation based on the total building volumes derived from geographic information system (GIS) building data and three census block-level housing statistics. To assess the model, we generated artificial blocks by aggregating census block areas and calculating the respective housing statistics. We then applied the model to estimate populations for sub-artificial-block areas and assessed the estimates with census populations of the areas. Our analyses indicate that the average percent error of population estimation for sub-artificial-block areas is comparable to those for sub-census-block areas of the same size relative to associated blocks. The smaller the sub-block-level areas, the higher the population estimation errors. For example, the average percent error for residential areas is approximately 0.11 percent for 100 percent block areas and 35 percent for 5 percent block areas.
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Real-time tumor motion estimation using respiratory surrogate via memory-based learning
NASA Astrophysics Data System (ADS)
Li, Ruijiang; Lewis, John H.; Berbeco, Ross I.; Xing, Lei
2012-08-01
Respiratory tumor motion is a major challenge in radiation therapy for thoracic and abdominal cancers. Effective motion management requires an accurate knowledge of the real-time tumor motion. External respiration monitoring devices (optical, etc) provide a noninvasive, non-ionizing, low-cost and practical approach to obtain the respiratory signal. Due to the highly complex and nonlinear relations between tumor and surrogate motion, its ultimate success hinges on the ability to accurately infer the tumor motion from respiratory surrogates. Given their widespread use in the clinic, such a method is critically needed. We propose to use a powerful memory-based learning method to find the complex relations between tumor motion and respiratory surrogates. The method first stores the training data in memory and then finds relevant data to answer a particular query. Nearby data points are assigned high relevance (or weights) and conversely distant data are assigned low relevance. By fitting relatively simple models to local patches instead of fitting one single global model, it is able to capture highly nonlinear and complex relations between the internal tumor motion and external surrogates accurately. Due to the local nature of weighting functions, the method is inherently robust to outliers in the training data. Moreover, both training and adapting to new data are performed almost instantaneously with memory-based learning, making it suitable for dynamically following variable internal/external relations. We evaluated the method using respiratory motion data from 11 patients. The data set consists of simultaneous measurement of 3D tumor motion and 1D abdominal surface (used as the surrogate signal in this study). There are a total of 171 respiratory traces, with an average peak-to-peak amplitude of ∼15 mm and average duration of ∼115 s per trace. Given only 5 s (roughly one breath) pretreatment training data, the method achieved an average 3D error of 1.5 mm and 95th percentile error of 3.4 mm on unseen test data. The average 3D error was further reduced to 1.4 mm when the model was tuned to its optimal setting for each respiratory trace. In one trace where a few outliers are present in the training data, the proposed method achieved an error reduction of as much as ∼50% compared with the best linear model (1.0 mm versus 2.1 mm). The memory-based learning technique is able to accurately capture the highly complex and nonlinear relations between tumor and surrogate motion in an efficient manner (a few milliseconds per estimate). Furthermore, the algorithm is particularly suitable to handle situations where the training data are contaminated by large errors or outliers. These desirable properties make it an ideal candidate for accurate and robust tumor gating/tracking using respiratory surrogates.
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[A study of refractive errors in a primary school in Cotonou, Benin].
Sounouvou, I; Tchabi, S; Doutetien, C; Sonon, F; Yehouessi, L; Bassabi, S K
2008-10-01
Determine the epidemiologic aspects and the degree of severity of different refractive errors in primary schoolchildren. A prospective and descriptive study was conducted from 1 December 2005 to 31 March 2006 on schoolchildren ranging from 4 to 16 years of age in a public primary school in Cotonou, Benin. The refraction was evaluated for any visual acuity lower than or equal to 0.7. The study included 1057 schoolchildren. The average age of the study population was 8.5+/-2.6 years with a slight predominance of females (51.8%). The prevalence of refractive error was 10.6% and astigmatism accounted for the most frequent refractive anomaly (91.9%). Myopia and the hyperopia were associated with astigmatism in 29.4% and 16.1% of the cases, respectively. The age bracket from 6 to 11 years accounted for the majority of refractive errors (75.9%), without age and sex being risk factors (p=0.811 and p=0.321, respectively). The average vision of the ametropic eye was 0.61, with a clear predominance of slight refractive errors (89.3%) and particularly of low-level simple astigmatism (45.5%). The relatively low prevalence of refractive error observed does not obviate the need for implementing actions to improve the ocular health of schoolchildren.
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Causal inference with measurement error in outcomes: Bias analysis and estimation methods.
Shu, Di; Yi, Grace Y
2017-01-01
Inverse probability weighting estimation has been popularly used to consistently estimate the average treatment effect. Its validity, however, is challenged by the presence of error-prone variables. In this paper, we explore the inverse probability weighting estimation with mismeasured outcome variables. We study the impact of measurement error for both continuous and discrete outcome variables and reveal interesting consequences of the naive analysis which ignores measurement error. When a continuous outcome variable is mismeasured under an additive measurement error model, the naive analysis may still yield a consistent estimator; when the outcome is binary, we derive the asymptotic bias in a closed-form. Furthermore, we develop consistent estimation procedures for practical scenarios where either validation data or replicates are available. With validation data, we propose an efficient method for estimation of average treatment effect; the efficiency gain is substantial relative to usual methods of using validation data. To provide protection against model misspecification, we further propose a doubly robust estimator which is consistent even when either the treatment model or the outcome model is misspecified. Simulation studies are reported to assess the performance of the proposed methods. An application to a smoking cessation dataset is presented.
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SU-F-J-206: Systematic Evaluation of the Minimum Detectable Shift Using a Range- Finding Camera
DOE Office of Scientific and Technical Information (OSTI.GOV)
Platt, M; Platt, M; Lamba, M
2016-06-15
Purpose: The robotic table used for patient alignment in proton therapy is calibrated only at commissioning under well-defined conditions and table shifts may vary over time and with differing conditions. The purpose of this study is to systematically investigate minimum detectable shifts using a time-of-flight (TOF) range-finding camera for table position feedback. Methods: A TOF camera was used to acquire one hundred 424 × 512 range images from a flat surface before and after known shifts. Range was assigned by averaging central regions of the image across multiple images. Depth resolution was determined by evaluating the difference between the actualmore » shift of the surface and the measured shift. Depth resolution was evaluated for number of images averaged, area of sensor over which depth was averaged, distance from camera to surface, central versus peripheral image regions, and angle of surface relative to camera. Results: For one to one thousand images with a shift of one millimeter the range in error was 0.852 ± 0.27 mm to 0.004 ± 0.01 mm (95% C.I.). For varying regions of the camera sensor the range in error was 0.02 ± 0.05 mm to 0.47 ± 0.04 mm. The following results are for 10 image averages. For areas ranging from one pixel to 9 × 9 pixels the range in error was 0.15 ± 0.09 to 0.29 ± 0.15 mm (1σ). For distances ranging from two to four meters the range in error was 0.15 ± 0.09 to 0.28 ± 0.15 mm. For an angle of incidence between thirty degrees and ninety degrees the average range in error was 0.11 ± 0.08 to 0.17 ± 0.09 mm. Conclusion: It is feasible to use a TOF camera for measuring shifts in flat surfaces under clinically relevant conditions with submillimeter precision.« less
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Relative Peripheral Refractive Error and the Risk of Onset and Progression of Myopia in Children
Sinnott, Loraine T.; Mitchell, G. Lynn; Jones-Jordan, Lisa A.; Moeschberger, Melvin L.; Cotter, Susan A.; Kleinstein, Robert N.; Manny, Ruth E.; Twelker, J. Daniel; Zadnik, Karla
2011-01-01
Purpose. To investigate whether relative peripheral hyperopia is a risk factor for either the onset of myopia in children or the rate of myopic progression. Methods. The risk of myopia onset was assessed in 2043 nonmyopic third-grade children (mean age ± SD = 8.8 ± 0.52 years) participating in the Collaborative Longitudinal Evaluation of Ethnicity and Refractive Error (CLEERE) Study between 1995 and 2007, 324 of whom became myopic by the eighth grade. Progression analyses used data from 774 myopic children in grades 1 to 8. Foveal and relative peripheral refractive error 30° in the nasal visual field was measured annually by using cycloplegic autorefraction. Axial length was measured by A-scan ultrasonography. Results. The association between more hyperopic relative peripheral refractive error in the third grade and the risk of the onset of myopia by the eighth grade varied by ethnic group (Asian children odds ratio [OR] = 1.56, 95% confidence interval [CI] = 1.06–2.30; African-American children OR = 0.75, 95% CI = 0.58–0.96; Hispanics, Native Americans, and whites showed no significant association). Myopia progression was greater per diopter of more hyperopic relative peripheral refractive error, but only by a small amount (−0.024 D per year; P = 0.02). Axial elongation was unrelated to the average relative peripheral refractive error (P = 0.77), regardless of ethnicity. Conclusions. Relative peripheral hyperopia appears to exert little consistent influence on the risk of the onset of myopic refractive error, on the rate of myopia progression, or on axial elongation. PMID:20739476
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Intuitive theories of information: beliefs about the value of redundancy.
Soll, J B
1999-03-01
In many situations, quantity estimates from multiple experts or diagnostic instruments must be collected and combined. Normatively, and all else equal, one should value information sources that are nonredundant, in the sense that correlation in forecast errors should be minimized. Past research on the preference for redundancy has been inconclusive. While some studies have suggested that people correctly place higher value on uncorrelated inputs when collecting estimates, others have shown that people either ignore correlation or, in some cases, even prefer it. The present experiments show that the preference for redundancy depends on one's intuitive theory of information. The most common intuitive theory identified is the Error Tradeoff Model (ETM), which explicitly distinguishes between measurement error and bias. According to ETM, measurement error can only be averaged out by consulting the same source multiple times (normatively false), and bias can only be averaged out by consulting different sources (normatively true). As a result, ETM leads people to prefer redundant estimates when the ratio of measurement error to bias is relatively high. Other participants favored different theories. Some adopted the normative model, while others were reluctant to mathematically average estimates from different sources in any circumstance. In a post hoc analysis, science majors were more likely than others to subscribe to the normative model. While tentative, this result lends insight into how intuitive theories might develop and also has potential ramifications for how statistical concepts such as correlation might best be learned and internalized. Copyright 1999 Academic Press.
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Zhang, Zhenwei; VanSwearingen, Jessie; Brach, Jennifer S.; Perera, Subashan
2016-01-01
Human gait is a complex interaction of many nonlinear systems and stride intervals exhibit self-similarity over long time scales that can be modeled as a fractal process. The scaling exponent represents the fractal degree and can be interpreted as a biomarker of relative diseases. The previous study showed that the average wavelet method provides the most accurate results to estimate this scaling exponent when applied to stride interval time series. The purpose of this paper is to determine the most suitable mother wavelet for the average wavelet method. This paper presents a comparative numerical analysis of sixteen mother wavelets using simulated and real fractal signals. Simulated fractal signals were generated under varying signal lengths and scaling exponents that indicate a range of physiologically conceivable fractal signals. The five candidates were chosen due to their good performance on the mean square error test for both short and long signals. Next, we comparatively analyzed these five mother wavelets for physiologically relevant stride time series lengths. Our analysis showed that the symlet 2 mother wavelet provides a low mean square error and low variance for long time intervals and relatively low errors for short signal lengths. It can be considered as the most suitable mother function without the burden of considering the signal length. PMID:27960102
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Acute acquired comitant esotropia related to excessive Smartphone use.
Lee, Hyo Seok; Park, Sang Woo; Heo, Hwan
2016-04-09
To describe the clinical characteristics and outcomes of acute acquired comitant esotropia (AACE) related to excessive smartphone use in adolescents. The medical records of 12 patients with AACE and a history of excessive smartphone use were retrospectively reviewed, and the duration of smartphone use, angle of deviation, refractive error, stereopsis, and treatment options were analyzed. All patients showed convergent and comitant esotropia ranging from 15 to 45 prism diopters (PD; average: 27.75 ± 11.47 PD) at far fixation. The angle of deviation was nearly equivalent for far and near fixation. Every patient used a smartphone for more than 4 h a day over a period of several months (minimum 4 months). Myopic refractive errors were detected in eight patients (average:-3.84 ± 1.68 diopters (D]), and the remaining four patients showed mild hyperopic refractive error (average: +0.84 ± 0.53 D). Reductions in esodeviation were noted in all patients after refraining from smartphone use, and bilateral medial rectus recession was performed in three patients with considerable remnant esodeviation. Postoperative exams showed orthophoria with good stereoacuity in these patients. Excessive smartphone use might influence AACE development in adolescents. Refraining from smartphone use can decrease the degree of esodeviation in these patients, and remnant deviation can be successfully managed with surgical correction.
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Single-ping ADCP measurements in the Strait of Gibraltar
NASA Astrophysics Data System (ADS)
Sammartino, Simone; García Lafuente, Jesús; Naranjo, Cristina; Sánchez Garrido, José Carlos; Sánchez Leal, Ricardo
2016-04-01
In most Acoustic Doppler Current Profiler (ADCP) user manuals, it is widely recommended to apply ensemble averaging of the single-pings measurements, in order to obtain reliable observations of the current speed. The random error related to the single-ping measurement is typically too high to be used directly, while the averaging operation reduces the ensemble error of a factor of approximately √N, with N the number of averaged pings. A 75 kHz ADCP moored in the western exit of the Strait of Gibraltar, included in the long-term monitoring of the Mediterranean outflow, has recently served as test setup for a different approach to current measurements. The ensemble averaging has been disabled, while maintaining the internal coordinate conversion made by the instrument, and a series of single-ping measurements has been collected every 36 seconds during a period of approximately 5 months. The huge amount of data has been fluently handled by the instrument, and no abnormal battery consumption has been recorded. On the other hand a long and unique series of very high frequency current measurements has been collected. Results of this novel approach have been exploited in a dual way: from a statistical point of view, the availability of single-ping measurements allows a real estimate of the (a posteriori) ensemble average error of both current and ancillary variables. While the theoretical random error for horizontal velocity is estimated a priori as ˜2 cm s-1 for a 50 pings ensemble, the value obtained by the a posteriori averaging is ˜15 cm s-1, with an asymptotical behavior starting from an averaging size of 10 pings per ensemble. This result suggests the presence of external sources of random error (e.g.: turbulence), of higher magnitude than the internal sources (ADCP intrinsic precision), which cannot be reduced by the ensemble averaging. On the other hand, although the instrumental configuration is clearly not suitable for a precise estimation of turbulent parameters, some hints of the turbulent structure of the flow can be obtained by the empirical computation of zonal Reynolds stress (along the predominant direction of the current) and rate of production and dissipation of turbulent kinetic energy. All the parameters show a clear correlation with tidal fluctuations of the current, with maximum values coinciding with flood tides, during the maxima of the outflow Mediterranean current.
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Accuracy of measurement in electrically evoked compound action potentials.
Hey, Matthias; Müller-Deile, Joachim
2015-01-15
Electrically evoked compound action potentials (ECAP) in cochlear implant (CI) patients are characterized by the amplitude of the N1P1 complex. The measurement of evoked potentials yields a combination of the measured signal with various noise components but for ECAP procedures performed in the clinical routine, only the averaged curve is accessible. To date no detailed analysis of error dimension has been published. The aim of this study was to determine the error of the N1P1 amplitude and to determine the factors that impact the outcome. Measurements were performed on 32 CI patients with either CI24RE (CA) or CI512 implants using the Software Custom Sound EP (Cochlear). N1P1 error approximation of non-averaged raw data consisting of recorded single-sweeps was compared to methods of error approximation based on mean curves. The error approximation of the N1P1 amplitude using averaged data showed comparable results to single-point error estimation. The error of the N1P1 amplitude depends on the number of averaging steps and amplification; in contrast, the error of the N1P1 amplitude is not dependent on the stimulus intensity. Single-point error showed smaller N1P1 error and better coincidence with 1/√(N) function (N is the number of measured sweeps) compared to the known maximum-minimum criterion. Evaluation of N1P1 amplitude should be accompanied by indication of its error. The retrospective approximation of this measurement error from the averaged data available in clinically used software is possible and best done utilizing the D-trace in forward masking artefact reduction mode (no stimulation applied and recording contains only the switch-on-artefact). Copyright © 2014 Elsevier B.V. All rights reserved.
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Improving the S-Shape Solar Radiation Estimation Method for Supporting Crop Models
Fodor, Nándor
2012-01-01
In line with the critical comments formulated in relation to the S-shape global solar radiation estimation method, the original formula was improved via a 5-step procedure. The improved method was compared to four-reference methods on a large North-American database. According to the investigated error indicators, the final 7-parameter S-shape method has the same or even better estimation efficiency than the original formula. The improved formula is able to provide radiation estimates with a particularly low error pattern index (PIdoy) which is especially important concerning the usability of the estimated radiation values in crop models. Using site-specific calibration, the radiation estimates of the improved S-shape method caused an average of 2.72 ± 1.02 (α = 0.05) relative error in the calculated biomass. Using only readily available site specific metadata the radiation estimates caused less than 5% relative error in the crop model calculations when they were used for locations in the middle, plain territories of the USA. PMID:22645451
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Schumacher, Robin F; Malone, Amelia S
2017-09-01
The goal of the present study was to describe fraction-calculation errors among 4 th -grade students and determine whether error patterns differed as a function of problem type (addition vs. subtraction; like vs. unlike denominators), orientation (horizontal vs. vertical), or mathematics-achievement status (low- vs. average- vs. high-achieving). We specifically addressed whether mathematics-achievement status was related to students' tendency to operate with whole number bias. We extended this focus by comparing low-performing students' errors in two instructional settings that focused on two different types of fraction understandings: core instruction that focused on part-whole understanding vs. small-group tutoring that focused on magnitude understanding. Results showed students across the sample were more likely to operate with whole number bias on problems with unlike denominators. Students with low or average achievement (who only participated in core instruction) were more likely to operate with whole number bias than students with low achievement who participated in small-group tutoring. We suggest instruction should emphasize magnitude understanding to sufficiently increase fraction understanding for all students in the upper elementary grades.
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NASA Technical Reports Server (NTRS)
Sylvester, W. B.
1984-01-01
A series of SEASAT repeat orbits over a sequence of best Low center positions is simulated by using the Seatrak satellite calculator. These Low centers are, upon appropriate interpolation to hourly positions, Located at various times during the + or - 3 hour assimilation cycle. Error analysis for a sample of best cyclone center positions taken from the Atlantic and Pacific oceans reveals a minimum average error of 1.1 deg of Longitude and a standard deviation of 0.9 deg of Longitude. The magnitude of the average error seems to suggest that by utilizing the + or - 3 hour window in the assimilation cycle, the quality of the SASS data is degraded to the Level of the background. A further consequence of this assimilation scheme is the effect which is manifested as a result of the blending of two or more more juxtaposed vector winds, generally possessing different properties (vector quantity and time). The outcome of this is to reduce gradients in the wind field and to deform isobaric and frontal patterns of the intial field.
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NASA Astrophysics Data System (ADS)
Sharma, Prabhat Kumar
2016-11-01
A framework is presented for the analysis of average symbol error rate (SER) for M-ary quadrature amplitude modulation in a free-space optical communication system. The standard probability density function (PDF)-based approach is extended to evaluate the average SER by representing the Q-function through its Meijer's G-function equivalent. Specifically, a converging power series expression for the average SER is derived considering the zero-boresight misalignment errors in the receiver side. The analysis presented here assumes a unified expression for the PDF of channel coefficient which incorporates the M-distributed atmospheric turbulence and Rayleigh-distributed radial displacement for the misalignment errors. The analytical results are compared with the results obtained using Q-function approximation. Further, the presented results are supported by the Monte Carlo simulations.
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Benchmarking homogenization algorithms for monthly data
NASA Astrophysics Data System (ADS)
Venema, V. K. C.; Mestre, O.; Aguilar, E.; Auer, I.; Guijarro, J. A.; Domonkos, P.; Vertacnik, G.; Szentimrey, T.; Stepanek, P.; Zahradnicek, P.; Viarre, J.; Müller-Westermeier, G.; Lakatos, M.; Williams, C. N.; Menne, M. J.; Lindau, R.; Rasol, D.; Rustemeier, E.; Kolokythas, K.; Marinova, T.; Andresen, L.; Acquaotta, F.; Fratiannil, S.; Cheval, S.; Klancar, M.; Brunetti, M.; Gruber, C.; Prohom Duran, M.; Likso, T.; Esteban, P.; Brandsma, T.; Willett, K.
2013-09-01
The COST (European Cooperation in Science and Technology) Action ES0601: Advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies. The algorithms were validated against a realistic benchmark dataset. Participants provided 25 separate homogenized contributions as part of the blind study as well as 22 additional solutions submitted after the details of the imposed inhomogeneities were revealed. These homogenized datasets were assessed by a number of performance metrics including i) the centered root mean square error relative to the true homogeneous values at various averaging scales, ii) the error in linear trend estimates and iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data. Moreover, state-of-the-art relative homogenization algorithms developed to work with an inhomogeneous reference are shown to perform best. The study showed that currently automatic algorithms can perform as well as manual ones.
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Luu, Phan; Tucker, Don M; Makeig, Scott
2004-08-01
The error-related negativity (ERN) is an event-related potential (ERP) peak occurring between 50 and 100 ms after the commission of a speeded motor response that the subject immediately realizes to be in error. The ERN is believed to index brain processes that monitor action outcomes. Our previous analyses of ERP and EEG data suggested that the ERN is dominated by partial phase-locking of intermittent theta-band EEG activity. In this paper, this possibility is further evaluated. The possibility that the ERN is produced by phase-locking of theta-band EEG activity was examined by analyzing the single-trial EEG traces from a forced-choice speeded response paradigm before and after applying theta-band (4-7 Hz) filtering and by comparing the averaged and single-trial phase-locked (ERP) and non-phase-locked (other) EEG data. Electrical source analyses were used to estimate the brain sources involved in the generation of the ERN. Beginning just before incorrect button presses in a speeded choice response paradigm, midfrontal theta-band activity increased in amplitude and became partially and transiently phase-locked to the subject's motor response, accounting for 57% of ERN peak amplitude. The portion of the theta-EEG activity increase remaining after subtracting the response-locked ERP from each trial was larger and longer lasting after error responses than after correct responses, extending on average 400 ms beyond the ERN peak. Multiple equivalent-dipole source analysis suggested 3 possible equivalent dipole sources of the theta-bandpassed ERN, while the scalp distribution of non-phase-locked theta amplitude suggested the presence of additional frontal theta-EEG sources. These results appear consistent with a body of research that demonstrates a relationship between limbic theta activity and action regulation, including error monitoring and learning.
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Methods for estimating streamflow at mountain fronts in southern New Mexico
Waltemeyer, S.D.
1994-01-01
The infiltration of streamflow is potential recharge to alluvial-basin aquifers at or near mountain fronts in southern New Mexico. Data for 13 streamflow-gaging stations were used to determine a relation between mean annual stream- flow and basin and climatic conditions. Regression analysis was used to develop an equation that can be used to estimate mean annual streamflow on the basis of drainage areas and mean annual precipi- tation. The average standard error of estimate for this equation is 46 percent. Regression analysis also was used to develop an equation to estimate mean annual streamflow on the basis of active- channel width. Measurements of the width of active channels were determined for 6 of the 13 gaging stations. The average standard error of estimate for this relation is 29 percent. Stream- flow estimates made using a regression equation based on channel geometry are considered more reliable than estimates made from an equation based on regional relations of basin and climatic conditions. The sample size used to develop these relations was small, however, and the reported standard error of estimate may not represent that of the entire population. Active-channel-width measurements were made at 23 ungaged sites along the Rio Grande upstream from Elephant Butte Reservoir. Data for additional sites would be needed for a more comprehensive assessment of mean annual streamflow in southern New Mexico.
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Effects of learning climate and registered nurse staffing on medication errors.
Chang, Yunkyung; Mark, Barbara
2011-01-01
Despite increasing recognition of the significance of learning from errors, little is known about how learning climate contributes to error reduction. The purpose of this study was to investigate whether learning climate moderates the relationship between error-producing conditions and medication errors. A cross-sectional descriptive study was done using data from 279 nursing units in 146 randomly selected hospitals in the United States. Error-producing conditions included work environment factors (work dynamics and nurse mix), team factors (communication with physicians and nurses' expertise), personal factors (nurses' education and experience), patient factors (age, health status, and previous hospitalization), and medication-related support services. Poisson models with random effects were used with the nursing unit as the unit of analysis. A significant negative relationship was found between learning climate and medication errors. It also moderated the relationship between nurse mix and medication errors: When learning climate was negative, having more registered nurses was associated with fewer medication errors. However, no relationship was found between nurse mix and medication errors at either positive or average levels of learning climate. Learning climate did not moderate the relationship between work dynamics and medication errors. The way nurse mix affects medication errors depends on the level of learning climate. Nursing units with fewer registered nurses and frequent medication errors should examine their learning climate. Future research should be focused on the role of learning climate as related to the relationships between nurse mix and medication errors.
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Lu, Dan; Ye, Ming; Meyer, Philip D.; Curtis, Gary P.; Shi, Xiaoqing; Niu, Xu-Feng; Yabusaki, Steve B.
2013-01-01
When conducting model averaging for assessing groundwater conceptual model uncertainty, the averaging weights are often evaluated using model selection criteria such as AIC, AICc, BIC, and KIC (Akaike Information Criterion, Corrected Akaike Information Criterion, Bayesian Information Criterion, and Kashyap Information Criterion, respectively). However, this method often leads to an unrealistic situation in which the best model receives overwhelmingly large averaging weight (close to 100%), which cannot be justified by available data and knowledge. It was found in this study that this problem was caused by using the covariance matrix, CE, of measurement errors for estimating the negative log likelihood function common to all the model selection criteria. This problem can be resolved by using the covariance matrix, Cek, of total errors (including model errors and measurement errors) to account for the correlation between the total errors. An iterative two-stage method was developed in the context of maximum likelihood inverse modeling to iteratively infer the unknown Cek from the residuals during model calibration. The inferred Cek was then used in the evaluation of model selection criteria and model averaging weights. While this method was limited to serial data using time series techniques in this study, it can be extended to spatial data using geostatistical techniques. The method was first evaluated in a synthetic study and then applied to an experimental study, in which alternative surface complexation models were developed to simulate column experiments of uranium reactive transport. It was found that the total errors of the alternative models were temporally correlated due to the model errors. The iterative two-stage method using Cekresolved the problem that the best model receives 100% model averaging weight, and the resulting model averaging weights were supported by the calibration results and physical understanding of the alternative models. Using Cek obtained from the iterative two-stage method also improved predictive performance of the individual models and model averaging in both synthetic and experimental studies.
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Weeland, Martine M; Nijhof, Karin S; Otten, R; Vermaes, Ignace P R; Buitelaar, Jan K
2017-10-01
This study tests the validity of Beck's cognitive theory and Nolen-Hoeksema's response style theory of depression in adolescents with and without MBID. The relationship between negative cognitive errors (Beck), response styles (Nolen-Hoeksema) and depressive symptoms was examined in 135 adolescents using linear regression. The cognitive error 'underestimation of the ability to cope' was more prevalent among adolescents with MBID than among adolescents with average intelligence. This was the only negative cognitive error that predicted depressive symptoms. There were no differences between groups in the prevalence of the three response styles. In line with the theory, ruminating was positively and problem-solving was negatively related to depressive symptoms. Distractive response styles were not related to depressive symptoms. The relationship between response styles, cognitive errors and depressive symptoms were similar for both groups. The main premises of both theories of depression are equally applicable to adolescents with and without MBID. The cognitive error 'Underestimation of the ability to cope' poses a specific risk factor for developing a depression for adolescents with MBID and requires special attention in treatment and prevention of depression. WHAT THIS PAPER ADDS?: Despite the high prevalence of depression among adolescents with MBID, little is known about the etiology and cognitive processes that play a role in the development of depression in this group. The current paper fills this gap in research by examining the core tenets of two important theories on the etiology of depression (Beck's cognitive theory and Nolen-Hoeksema's response style theory) in a clinical sample of adolescents with and without MBID. This paper demonstrated that the theories are equally applicable to adolescents with MBID, as to adolescents with average intellectual ability. However, the cognitive bias 'underestimation of the ability to cope' was the only cognitive error related to depressive symptoms, and was much more prevalent among adolescents with MBID than among adolescents with average intellectual ability. This suggests that underestimating one's coping skills may be a unique risk factor for depression among adolescents with MBID. This knowledge is important in understanding the causes and perpetuating mechanisms of depression in adolescents with MBID, and for the development of prevention- and treatment programs for adolescents with MBID. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Cost-effectiveness of the Federal stream-gaging program in Virginia
Carpenter, D.H.
1985-01-01
Data uses and funding sources were identified for the 77 continuous stream gages currently being operated in Virginia by the U.S. Geological Survey with a budget of $446,000. Two stream gages were identified as not being used sufficiently to warrant continuing their operation. Operation of these stations should be considered for discontinuation. Data collected at two other stations were identified as having uses primarily related to short-term studies; these stations should also be considered for discontinuation at the end of the data collection phases of the studies. The remaining 73 stations should be kept in the program for the foreseeable future. The current policy for operation of the 77-station program requires a budget of $446,000/yr. The average standard error of estimation of streamflow records is 10.1%. It was shown that this overall level of accuracy at the 77 sites could be maintained with a budget of $430,500 if resources were redistributed among the gages. A minimum budget of $428,500 is required to operate the 77-gage program; a smaller budget would not permit proper service and maintenance of the gages and recorders. At the minimum budget, with optimized operation, the average standard error would be 10.4%. The maximum budget analyzed was $650,000, which resulted in an average standard error of 5.5%. The study indicates that a major component of error is caused by lost or missing data. If perfect equipment were available, the standard error for the current program and budget could be reduced to 7.6%. This also can be interpreted to mean that the streamflow data have a standard error of this magnitude during times when the equipment is operating properly. (Author 's abstract)
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Measurement of vertebral rotation: Perdriolle versus Raimondi.
Weiss, H R
1995-01-01
The measurement of vertebral rotation according to Perdriolle is widely used in the French-speaking and Anglo-American countries. Even in this measurement technique there may be a relatively high estimation error because of the not very accurate grading in steps of 5 degrees. The measurement according to Raimondi seems to be easier to use and is more accurate, with 2 degrees steps. The purpose of our study was to determine the technical error of both measuring methods. The apex vertebra of 40 curves on 20 anteroposterior (AP) radiographs were measured by using the Perdriolle torsion meter and the Regolo Raimondi. Interrater and intrarater reliability were computed. The thoracic Cobb angle was 43 degrees, the lumbar Cobb angle 36 degrees. The average rotation according to Perdriolle was 19.1 degrees thoracic (SD 11.14), 12.7 degrees lumbar (11.21). Measurement of vertebral rotation according to Raimondi showed an average rotation of 20.25 degrees in the thoracic region (11.40) and 13.4 degrees lumbar (10.92). The intrarater reliability was r = 0.991 (Perdriolle) and r = 0.997 (Raimondi). The average intrarater error was 1.025 degrees in the Perdriolle measurement and 0.4 degrees in the Raimondi measurement. Interrater error was on average 3.112 degrees for the Perdriolle measurement and 3.630 degrees for the Raimondi measurement. This shows that both methods are useful tools for the follow-up of vertebral rotation as projected on standard X-rays for the experienced clinical. The Raimondi ruler is easier to use and is slightly more reliable.
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Forces associated with pneumatic power screwdriver operation: statics and dynamics.
Lin, Jia-Hua; Radwin, Robert G; Fronczak, Frank J; Richard, Terry G
2003-10-10
The statics and dynamics of pneumatic power screwdriver operation were investigated in the context of predicting forces acting against the human operator. A static force model is described in the paper, based on tool geometry, mass, orientation in space, feed force, torque build up, and stall torque. Three common power hand tool shapes are considered, including pistol grip, right angle, and in-line. The static model estimates handle force needed to support a power nutrunner when it acts against the tightened fastener with a constant torque. A system of equations for static force and moment equilibrium conditions are established, and the resultant handle force (resolved in orthogonal directions) is calculated in matrix form. A dynamic model is formulated to describe pneumatic motor torque build-up characteristics dependent on threaded fastener joint hardness. Six pneumatic tools were tested to validate the deterministic model. The average torque prediction error was 6.6% (SD = 5.4%) and the average handle force prediction error was 6.7% (SD = 6.4%) for a medium-soft threaded fastener joint. The average torque prediction error was 5.2% (SD = 5.3%) and the average handle force prediction error was 3.6% (SD = 3.2%) for a hard threaded fastener joint. Use of these equations for estimating handle forces based on passive mechanical elements representing the human operator is also described. These models together should be useful for considering tool handle force in the selection and design of power screwdrivers, particularly for minimizing handle forces in the prevention of injuries and work related musculoskeletal disorders.
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NASA Astrophysics Data System (ADS)
Gao, Zhi-yu; Kang, Yu; Li, Yan-shuai; Meng, Chao; Pan, Tao
2018-04-01
Elevated-temperature flow behavior of a novel Ni-Cr-Mo-B ultra-heavy-plate steel was investigated by conducting hot compressive deformation tests on a Gleeble-3800 thermo-mechanical simulator at a temperature range of 1123 K–1423 K with a strain rate range from 0.01 s‑1 to10 s‑1 and a height reduction of 70%. Based on the experimental results, classic strain-compensated Arrhenius-type, a new revised strain-compensated Arrhenius-type and classic modified Johnson-Cook constitutive models were developed for predicting the high-temperature deformation behavior of the steel. The predictability of these models were comparatively evaluated in terms of statistical parameters including correlation coefficient (R), average absolute relative error (AARE), average root mean square error (RMSE), normalized mean bias error (NMBE) and relative error. The statistical results indicate that the new revised strain-compensated Arrhenius-type model could give prediction of elevated-temperature flow stress for the steel accurately under the entire process conditions. However, the predicted values by the classic modified Johnson-Cook model could not agree well with the experimental values, and the classic strain-compensated Arrhenius-type model could track the deformation behavior more accurately compared with the modified Johnson-Cook model, but less accurately with the new revised strain-compensated Arrhenius-type model. In addition, reasons of differences in predictability of these models were discussed in detail.
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WE-G-BRA-04: Common Errors and Deficiencies in Radiation Oncology Practice
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kry, S; Dromgoole, L; Alvarez, P
Purpose: Dosimetric errors in radiotherapy dose delivery lead to suboptimal treatments and outcomes. This work reviews the frequency and severity of dosimetric and programmatic errors identified by on-site audits performed by the IROC Houston QA center. Methods: IROC Houston on-site audits evaluate absolute beam calibration, relative dosimetry data compared to the treatment planning system data, and processes such as machine QA. Audits conducted from 2000-present were abstracted for recommendations, including type of recommendation and magnitude of error when applicable. Dosimetric recommendations corresponded to absolute dose errors >3% and relative dosimetry errors >2%. On-site audits of 1020 accelerators at 409 institutionsmore » were reviewed. Results: A total of 1280 recommendations were made (average 3.1/institution). The most common recommendation was for inadequate QA procedures per TG-40 and/or TG-142 (82% of institutions) with the most commonly noted deficiency being x-ray and electron off-axis constancy versus gantry angle. Dosimetrically, the most common errors in relative dosimetry were in small-field output factors (59% of institutions), wedge factors (33% of institutions), off-axis factors (21% of institutions), and photon PDD (18% of institutions). Errors in calibration were also problematic: 20% of institutions had an error in electron beam calibration, 8% had an error in photon beam calibration, and 7% had an error in brachytherapy source calibration. Almost all types of data reviewed included errors up to 7% although 20 institutions had errors in excess of 10%, and 5 had errors in excess of 20%. The frequency of electron calibration errors decreased significantly with time, but all other errors show non-significant changes. Conclusion: There are many common and often serious errors made during the establishment and maintenance of a radiotherapy program that can be identified through independent peer review. Physicists should be cautious, particularly in areas highlighted herein that show a tendency for errors.« less
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Peak-flow frequency relations and evaluation of the peak-flow gaging network in Nebraska
Soenksen, Philip J.; Miller, Lisa D.; Sharpe, Jennifer B.; Watton, Jason R.
1999-01-01
Estimates of peak-flow magnitude and frequency are required for the efficient design of structures that convey flood flows or occupy floodways, such as bridges, culverts, and roads. The U.S. Geological Survey, in cooperation with the Nebraska Department of Roads, conducted a study to update peak-flow frequency analyses for selected streamflow-gaging stations, develop a new set of peak-flow frequency relations for ungaged streams, and evaluate the peak-flow gaging-station network for Nebraska. Data from stations located in or within about 50 miles of Nebraska were analyzed using guidelines of the Interagency Advisory Committee on Water Data in Bulletin 17B. New generalized skew relations were developed for use in frequency analyses of unregulated streams. Thirty-three drainage-basin characteristics related to morphology, soils, and precipitation were quantified using a geographic information system, related computer programs, and digital spatial data.For unregulated streams, eight sets of regional regression equations relating drainage-basin to peak-flow characteristics were developed for seven regions of the state using a generalized least squares procedure. Two sets of regional peak-flow frequency equations were developed for basins with average soil permeability greater than 4 inches per hour, and six sets of equations were developed for specific geographic areas, usually based on drainage-basin boundaries. Standard errors of estimate for the 100-year frequency equations (1percent probability) ranged from 12.1 to 63.8 percent. For regulated reaches of nine streams, graphs of peak flow for standard frequencies and distance upstream of the mouth were estimated.The regional networks of streamflow-gaging stations on unregulated streams were analyzed to evaluate how additional data might affect the average sampling errors of the newly developed peak-flow equations for the 100-year frequency occurrence. Results indicated that data from new stations, rather than more data from existing stations, probably would produce the greatest reduction in average sampling errors of the equations.
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Sobel, Michael E; Lindquist, Martin A
2014-07-01
Functional magnetic resonance imaging (fMRI) has facilitated major advances in understanding human brain function. Neuroscientists are interested in using fMRI to study the effects of external stimuli on brain activity and causal relationships among brain regions, but have not stated what is meant by causation or defined the effects they purport to estimate. Building on Rubin's causal model, we construct a framework for causal inference using blood oxygenation level dependent (BOLD) fMRI time series data. In the usual statistical literature on causal inference, potential outcomes, assumed to be measured without systematic error, are used to define unit and average causal effects. However, in general the potential BOLD responses are measured with stimulus dependent systematic error. Thus we define unit and average causal effects that are free of systematic error. In contrast to the usual case of a randomized experiment where adjustment for intermediate outcomes leads to biased estimates of treatment effects (Rosenbaum, 1984), here the failure to adjust for task dependent systematic error leads to biased estimates. We therefore adjust for systematic error using measured "noise covariates" , using a linear mixed model to estimate the effects and the systematic error. Our results are important for neuroscientists, who typically do not adjust for systematic error. They should also prove useful to researchers in other areas where responses are measured with error and in fields where large amounts of data are collected on relatively few subjects. To illustrate our approach, we re-analyze data from a social evaluative threat task, comparing the findings with results that ignore systematic error.
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A retrospective review of medical errors adjudicated in court between 2002 and 2012 in Spain.
Giraldo, Priscila; Sato, Luke; Sala, María; Comas, Merce; Dywer, Kathy; Castells, Xavier
2016-02-01
This paper describes verdicts in court involving injury-producing medical errors in Spain. A descriptive analysis of 1041 closed court verdicts from Spain between January 2002 and December 2012. It was determined whether a medical error had occurred, and among those with medical error (n = 270), characteristics and results of litigation were analyzed. Data on litigation were obtained from the Thomson Reuters Aranzadi Westlaw databases. All verdicts involving health system were reviewed and classified according to the presence of medical error. Among those, contributory factors, medical specialty involved, health impact (death, disability and severity) and results of litigation (resolution, time to verdict and economic compensations) were described. Medical errors were involved in 25.9% of court verdicts. The cause of medical error was a diagnosis-related problem in 25.1% and surgical treatment in 22.2%, and Obstetrics-Gynecology was the most frequent involved specialty (21%). Most of them were of high severity (59.4%), one-third (32%) caused death. The average time interval between the occurrence of the error and the verdict was 7.8 years. The average indemnity payment was €239 505.24; the highest was psychiatry (€7 585 075.86) and the lowest was Emergency Medicine (€69 871.19). This study indicates that in Spain medical errors are common among verdicts involving the health system, most of them causing high-severity adverse outcomes. The interval between the medical error and the verdict is excessive, and there is a wide range of economic compensation. © The Author 2015. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved.
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The random coding bound is tight for the average code.
NASA Technical Reports Server (NTRS)
Gallager, R. G.
1973-01-01
The random coding bound of information theory provides a well-known upper bound to the probability of decoding error for the best code of a given rate and block length. The bound is constructed by upperbounding the average error probability over an ensemble of codes. The bound is known to give the correct exponential dependence of error probability on block length for transmission rates above the critical rate, but it gives an incorrect exponential dependence at rates below a second lower critical rate. Here we derive an asymptotic expression for the average error probability over the ensemble of codes used in the random coding bound. The result shows that the weakness of the random coding bound at rates below the second critical rate is due not to upperbounding the ensemble average, but rather to the fact that the best codes are much better than the average at low rates.
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Increased error-related thalamic activity during early compared to late cocaine abstinence.
Li, Chiang-Shan R; Luo, Xi; Sinha, Rajita; Rounsaville, Bruce J; Carroll, Kathleen M; Malison, Robert T; Ding, Yu-Shin; Zhang, Sheng; Ide, Jaime S
2010-06-01
Altered cognitive control is implicated in the shaping of cocaine dependence. One of the key component processes of cognitive control is error monitoring. Our previous imaging work highlighted greater activity in distinct cortical and subcortical regions including the dorsal anterior cingulate cortex (dACC), thalamus and insula when participants committed an error during the stop signal task (Li et al., 2008b). Importantly, dACC, thalamic and insular activity has been associated with drug craving. One hypothesis is that the intense interoceptive activity during craving prevents these cerebral structures from adequately registering error and/or monitoring performance. Alternatively, the dACC, thalamus and insula show abnormally heightened responses to performance errors, suggesting that excessive responses to salient stimuli such as drug cues could precipitate craving. The two hypotheses would each predict decreased and increased activity during stop error (SE) as compared to stop success (SS) trials in the SST. Here we showed that cocaine dependent patients (PCD) experienced greater subjective feeling of loss of control and cocaine craving during early (average of day 6) compared to late (average of day 18) abstinence. Furthermore, compared to PCD during late abstinence, PCD scanned during early abstinence showed increased thalamic as well as insular but not dACC responses to errors (SE>SS). These findings support the hypothesis that heightened thalamic reactivity to salient stimuli co-occur with cocaine craving and loss of self control. Copyright (c) 2010 Elsevier Ireland Ltd. All rights reserved.
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Chang, Wen-Pin; Davies, Patricia L; Gavin, William J
2010-10-01
Recent studies have investigated the relationship between psychological symptoms and personality traits and error monitoring measured by error-related negativity (ERN) and error positivity (Pe) event-related potential (ERP) components, yet there remains a paucity of studies examining the collective simultaneous effects of psychological symptoms and personality traits on error monitoring. This present study, therefore, examined whether measures of hyperactivity-impulsivity, depression, anxiety and antisocial personality characteristics could collectively account for significant interindividual variability of both ERN and Pe amplitudes, in 29 healthy adults with no known disorders, ages 18-30 years. The bivariate zero-order correlation analyses found that only the anxiety measure was significantly related to both ERN and Pe amplitudes. However, multiple regression analyses that included all four characteristic measures while controlling for number of segments in the ERP average revealed that both depression and antisocial personality characteristics were significant predictors for the ERN amplitudes whereas antisocial personality was the only significant predictor for the Pe amplitude. These findings suggest that psychological symptoms and personality traits are associated with individual variations in error monitoring in healthy adults, and future studies should consider these variables when comparing group difference in error monitoring between adults with and without disabilities. © 2010 The Authors. European Journal of Neuroscience © 2010 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.
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Schiffer, Anne-Marike; Ahlheim, Christiane; Wurm, Moritz F.; Schubotz, Ricarda I.
2012-01-01
Influential concepts in neuroscientific research cast the brain a predictive machine that revises its predictions when they are violated by sensory input. This relates to the predictive coding account of perception, but also to learning. Learning from prediction errors has been suggested for take place in the hippocampal memory system as well as in the basal ganglia. The present fMRI study used an action-observation paradigm to investigate the contributions of the hippocampus, caudate nucleus and midbrain dopaminergic system to different types of learning: learning in the absence of prediction errors, learning from prediction errors, and responding to the accumulation of prediction errors in unpredictable stimulus configurations. We conducted analyses of the regions of interests' BOLD response towards these different types of learning, implementing a bootstrapping procedure to correct for false positives. We found both, caudate nucleus and the hippocampus to be activated by perceptual prediction errors. The hippocampal responses seemed to relate to the associative mismatch between a stored representation and current sensory input. Moreover, its response was significantly influenced by the average information, or Shannon entropy of the stimulus material. In accordance with earlier results, the habenula was activated by perceptual prediction errors. Lastly, we found that the substantia nigra was activated by the novelty of sensory input. In sum, we established that the midbrain dopaminergic system, the hippocampus, and the caudate nucleus were to different degrees significantly involved in the three different types of learning: acquisition of new information, learning from prediction errors and responding to unpredictable stimulus developments. We relate learning from perceptual prediction errors to the concept of predictive coding and related information theoretic accounts. PMID:22570715
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NASA Astrophysics Data System (ADS)
Lobit, P.; López Pérez, L.; Lhomme, J. P.; Gómez Tagle, A.
2017-07-01
This study evaluates the dew point method (Allen et al. 1998) to estimate atmospheric vapor pressure from minimum temperature, and proposes an improved model to estimate it from maximum and minimum temperature. Both methods were evaluated on 786 weather stations in Mexico. The dew point method induced positive bias in dry areas but also negative bias in coastal areas, and its average root mean square error for all evaluated stations was 0.38 kPa. The improved model assumed a bi-linear relation between estimated vapor pressure deficit (difference between saturated vapor pressure at minimum and average temperature) and measured vapor pressure deficit. The parameters of these relations were estimated from historical annual median values of relative humidity. This model removed bias and allowed for a root mean square error of 0.31 kPa. When no historical measurements of relative humidity were available, empirical relations were proposed to estimate it from latitude and altitude, with only a slight degradation on the model accuracy (RMSE = 0.33 kPa, bias = -0.07 kPa). The applicability of the method to other environments is discussed.
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Thorup, Charlotte Brun; Grønkjær, Mette; Dinesen, Birthe Irene
2017-01-01
Background Step counters have been used to observe activity and support physical activity, but there is limited evidence on their accuracy. Objective The purpose was to investigate the step accuracy of the Fitbit Zip (Zip) in healthy adults during treadmill walking and in patients with cardiac disease while hospitalised at home. Methods Twenty healthy adults aged 39±13.79 (mean ±SD) wore four Zips while walking on a treadmill at different speeds (1.7–6.1 km/hour), and 24 patients with cardiac disease (age 67±10.03) wore a Zip for 24 hours during hospitalisation and for 4 weeks thereafter at home. A Shimmer3 device was used as a criterion standard. Results At a treadmill speed of 3.6 km/hour, the relative error (±SD) for the Zips on the upper body was −0.02±0.67 on the right side and −0.09 (0.67) on the left side. For the Zips on the waist, this was 0.08±0.71 for the right side and -0.08 (0.47) on the left side. At a treadmill speed of 3.6 km/hour and higher, the average per cent of relative error was <3%. The 24-hour test for the hospitalised patients showed a relative error of −47.15±24.11 (interclass correlation coefficient (ICC): 0.60), and for the 24-hour test at home, the relative error was −27.51±28.78 (ICC: 0.87). Thus, none of the 24-hour tests had less than the expected 20% error. In time periods of evident walking during the 24 h test, the Zip had an average per cent relative error of <3% at 3.6 km/hour and higher speeds. Conclusions A speed of 3.6 km/hour or higher is required to expect acceptable accuracy in step measurement using a Zip, on a treadmill and in real life. Inaccuracies are directly related to slow speeds, which might be a problem for patients with cardiac disease who walk at a slow pace. PMID:28363918
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Combining forecast weights: Why and how?
NASA Astrophysics Data System (ADS)
Yin, Yip Chee; Kok-Haur, Ng; Hock-Eam, Lim
2012-09-01
This paper proposes a procedure called forecast weight averaging which is a specific combination of forecast weights obtained from different methods of constructing forecast weights for the purpose of improving the accuracy of pseudo out of sample forecasting. It is found that under certain specified conditions, forecast weight averaging can lower the mean squared forecast error obtained from model averaging. In addition, we show that in a linear and homoskedastic environment, this superior predictive ability of forecast weight averaging holds true irrespective whether the coefficients are tested by t statistic or z statistic provided the significant level is within the 10% range. By theoretical proofs and simulation study, we have shown that model averaging like, variance model averaging, simple model averaging and standard error model averaging, each produces mean squared forecast error larger than that of forecast weight averaging. Finally, this result also holds true marginally when applied to business and economic empirical data sets, Gross Domestic Product (GDP growth rate), Consumer Price Index (CPI) and Average Lending Rate (ALR) of Malaysia.
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Effects of Acids, Bases, and Heteroatoms on Proximal Radial Distribution Functions for Proteins.
Nguyen, Bao Linh; Pettitt, B Montgomery
2015-04-14
The proximal distribution of water around proteins is a convenient method of quantifying solvation. We consider the effect of charged and sulfur-containing amino acid side-chain atoms on the proximal radial distribution function (pRDF) of water molecules around proteins using side-chain analogs. The pRDF represents the relative probability of finding any solvent molecule at a distance from the closest or surface perpendicular protein atom. We consider the near-neighbor distribution. Previously, pRDFs were shown to be universal descriptors of the water molecules around C, N, and O atom types across hundreds of globular proteins. Using averaged pRDFs, a solvent density around any globular protein can be reconstructed with controllable relative error. Solvent reconstruction using the additional information from charged amino acid side-chain atom types from both small models and protein averages reveals the effects of surface charge distribution on solvent density and improves the reconstruction errors relative to simulation. Solvent density reconstructions from the small-molecule models are as effective and less computationally demanding than reconstructions from full macromolecular models in reproducing preferred hydration sites and solvent density fluctuations.
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Nelson, Jonathan M.; Kinzel, Paul J.; Schmeeckle, Mark Walter; McDonald, Richard R.; Minear, Justin T.
2016-01-01
Noncontact methods for measuring water-surface elevation and velocity in laboratory flumes and rivers are presented with examples. Water-surface elevations are measured using an array of acoustic transducers in the laboratory and using laser scanning in field situations. Water-surface velocities are based on using particle image velocimetry or other machine vision techniques on infrared video of the water surface. Using spatial and temporal averaging, results from these methods provide information that can be used to develop estimates of discharge for flows over known bathymetry. Making such estimates requires relating water-surface velocities to vertically averaged velocities; the methods here use standard relations. To examine where these relations break down, laboratory data for flows over simple bumps of three amplitudes are evaluated. As anticipated, discharges determined from surface information can have large errors where nonhydrostatic effects are large. In addition to investigating and characterizing this potential error in estimating discharge, a simple method for correction of the issue is presented. With a simple correction based on bed gradient along the flow direction, remotely sensed estimates of discharge appear to be viable.
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Fu, Xi; Qiao, Jia; Girod, Sabine; Niu, Feng; Liu, Jian Feng; Lee, Gordon K; Gui, Lai
2017-09-01
Mandible contour surgery, including reduction gonioplasty and genioplasty, has become increasingly popular in East Asia. However, it is technically challenging and, hence, leads to a long learning curve and high complication rates and often needs secondary revisions. The increasing use of 3-dimensional (3D) technology makes accurate single-stage mandible contour surgery with minimum complication rates possible with a virtual surgical plan (VSP) and 3-D surgical templates. This study is to establish a standardized protocol for VSP and 3-D surgical templates-assisted mandible contour surgery and evaluate the accuracy of the protocol. In this study, we enrolled 20 patients for mandible contour surgery. Our protocol is to perform VSP based on 3-D computed tomography data. Then, design and 3-D print surgical templates based on preoperative VSP. The accuracy of the method was analyzed by 3-D comparison of VSP and postoperative results using detailed computer analysis. All patients had symmetric, natural osteotomy lines and satisfactory facial ratios in a single-stage operation. The average relative error of VSP and postoperative result on the entire skull was 0.41 ± 0.13 mm. The average new left gonial error was 0.43 ± 0.77 mm. The average new right gonial error was 0.45 ± 0.69 mm. The average pognion error was 0.79 ± 1.21 mm. Patients were very satisfied with the aesthetic results. Surgeons were very satisfied with the performance of surgical templates to facilitate the operation. Our standardized protocol of VSP and 3-D printed surgical templates-assisted single-stage mandible contour surgery results in accurate, safe, and predictable outcome in a single stage.
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Decoy-state quantum key distribution with more than three types of photon intensity pulses
NASA Astrophysics Data System (ADS)
Chau, H. F.
2018-04-01
The decoy-state method closes source security loopholes in quantum key distribution (QKD) using a laser source. In this method, accurate estimates of the detection rates of vacuum and single-photon events plus the error rate of single-photon events are needed to give a good enough lower bound of the secret key rate. Nonetheless, the current estimation method for these detection and error rates, which uses three types of photon intensities, is accurate up to about 1 % relative error. Here I report an experimentally feasible way that greatly improves these estimates and hence increases the one-way key rate of the BB84 QKD protocol with unbiased bases selection by at least 20% on average in realistic settings. The major tricks are the use of more than three types of photon intensities plus the fact that estimating bounds of the above detection and error rates is numerically stable, although these bounds are related to the inversion of a high condition number matrix.
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Topping, David J.; Rubin, David M.; Wright, Scott A.; Melis, Theodore S.
2011-01-01
Several common methods for measuring suspended-sediment concentration in rivers in the United States use depth-integrating samplers to collect a velocity-weighted suspended-sediment sample in a subsample of a river cross section. Because depth-integrating samplers are always moving through the water column as they collect a sample, and can collect only a limited volume of water and suspended sediment, they collect only minimally time-averaged data. Four sources of error exist in the field use of these samplers: (1) bed contamination, (2) pressure-driven inrush, (3) inadequate sampling of the cross-stream spatial structure in suspended-sediment concentration, and (4) inadequate time averaging. The first two of these errors arise from misuse of suspended-sediment samplers, and the third has been the subject of previous study using data collected in the sand-bedded Middle Loup River in Nebraska. Of these four sources of error, the least understood source of error arises from the fact that depth-integrating samplers collect only minimally time-averaged data. To evaluate this fourth source of error, we collected suspended-sediment data between 1995 and 2007 at four sites on the Colorado River in Utah and Arizona, using a P-61 suspended-sediment sampler deployed in both point- and one-way depth-integrating modes, and D-96-A1 and D-77 bag-type depth-integrating suspended-sediment samplers. These data indicate that the minimal duration of time averaging during standard field operation of depth-integrating samplers leads to an error that is comparable in magnitude to that arising from inadequate sampling of the cross-stream spatial structure in suspended-sediment concentration. This random error arising from inadequate time averaging is positively correlated with grain size and does not largely depend on flow conditions or, for a given size class of suspended sediment, on elevation above the bed. Averaging over time scales >1 minute is the likely minimum duration required to result in substantial decreases in this error. During standard two-way depth integration, a depth-integrating suspended-sediment sampler collects a sample of the water-sediment mixture during two transits at each vertical in a cross section: one transit while moving from the water surface to the bed, and another transit while moving from the bed to the water surface. As the number of transits is doubled at an individual vertical, this error is reduced by ~30 percent in each size class of suspended sediment. For a given size class of suspended sediment, the error arising from inadequate sampling of the cross-stream spatial structure in suspended-sediment concentration depends only on the number of verticals collected, whereas the error arising from inadequate time averaging depends on both the number of verticals collected and the number of transits collected at each vertical. Summing these two errors in quadrature yields a total uncertainty in an equal-discharge-increment (EDI) or equal-width-increment (EWI) measurement of the time-averaged velocity-weighted suspended-sediment concentration in a river cross section (exclusive of any laboratory-processing errors). By virtue of how the number of verticals and transits influences the two individual errors within this total uncertainty, the error arising from inadequate time averaging slightly dominates that arising from inadequate sampling of the cross-stream spatial structure in suspended-sediment concentration. Adding verticals to an EDI or EWI measurement is slightly more effective in reducing the total uncertainty than adding transits only at each vertical, because a new vertical contributes both temporal and spatial information. However, because collection of depth-integrated samples at more transits at each vertical is generally easier and faster than at more verticals, addition of a combination of verticals and transits is likely a more practical approach to reducing the total uncertainty in most field situatio
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Zhang, Yu-ge; Xiao, Min; Dong, Yi-hua; Jiang, Yong
2012-08-01
A method to determine soil exchangeable calcium (Ca), magnesium (Mg), potassium (K), and sodium (Na) by using atomic absorption spectrophotometer (AAS) and extraction with ammonium acetate was developed. Results showed that the accuracy of exchangeable base cation data with AAS method fits well with the national standard referential soil data. The relative errors for parallel samples of exchangeable Ca and Mg with 66 pair samples ranged from 0.02%-3.14% and 0.06%-4.06%, and averaged to be 1.22% and 1.25%, respectively. The relative errors for exchangeable K and Na with AAS and flame photometer (FP) ranged from 0.06%-8.39% and 0.06-1.54, and averaged to be 3.72% and 0.56%, respectively. A case study showed that the determination method for exchangeable base cations by using AAS was proven to be reliable and trustable, which could reflect the real situation of soil cation exchange properties in farmlands.
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Assumption-free estimation of the genetic contribution to refractive error across childhood.
Guggenheim, Jeremy A; St Pourcain, Beate; McMahon, George; Timpson, Nicholas J; Evans, David M; Williams, Cathy
2015-01-01
Studies in relatives have generally yielded high heritability estimates for refractive error: twins 75-90%, families 15-70%. However, because related individuals often share a common environment, these estimates are inflated (via misallocation of unique/common environment variance). We calculated a lower-bound heritability estimate for refractive error free from such bias. Between the ages 7 and 15 years, participants in the Avon Longitudinal Study of Parents and Children (ALSPAC) underwent non-cycloplegic autorefraction at regular research clinics. At each age, an estimate of the variance in refractive error explained by single nucleotide polymorphism (SNP) genetic variants was calculated using genome-wide complex trait analysis (GCTA) using high-density genome-wide SNP genotype information (minimum N at each age=3,404). The variance in refractive error explained by the SNPs ("SNP heritability") was stable over childhood: Across age 7-15 years, SNP heritability averaged 0.28 (SE=0.08, p<0.001). The genetic correlation for refractive error between visits varied from 0.77 to 1.00 (all p<0.001) demonstrating that a common set of SNPs was responsible for the genetic contribution to refractive error across this period of childhood. Simulations suggested lack of cycloplegia during autorefraction led to a small underestimation of SNP heritability (adjusted SNP heritability=0.35; SE=0.09). To put these results in context, the variance in refractive error explained (or predicted) by the time participants spent outdoors was <0.005 and by the time spent reading was <0.01, based on a parental questionnaire completed when the child was aged 8-9 years old. Genetic variation captured by common SNPs explained approximately 35% of the variation in refractive error between unrelated subjects. This value sets an upper limit for predicting refractive error using existing SNP genotyping arrays, although higher-density genotyping in larger samples and inclusion of interaction effects is expected to raise this figure toward twin- and family-based heritability estimates. The same SNPs influenced refractive error across much of childhood. Notwithstanding the strong evidence of association between time outdoors and myopia, and time reading and myopia, less than 1% of the variance in myopia at age 15 was explained by crude measures of these two risk factors, indicating that their effects may be limited, at least when averaged over the whole population.
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Social deviance activates the brain's error-monitoring system.
Kim, Bo-Rin; Liss, Alison; Rao, Monica; Singer, Zachary; Compton, Rebecca J
2012-03-01
Social psychologists have long noted the tendency for human behavior to conform to social group norms. This study examined whether feedback indicating that participants had deviated from group norms would elicit a neural signal previously shown to be elicited by errors and monetary losses. While electroencephalograms were recorded, participants (N = 30) rated the attractiveness of 120 faces and received feedback giving the purported average rating made by a group of peers. The feedback was manipulated so that group ratings either were the same as a participant's rating or deviated by 1, 2, or 3 points. Feedback indicating deviance from the group norm elicited a feedback-related negativity, a brainwave signal known to be elicited by objective performance errors and losses. The results imply that the brain treats deviance from social norms as an error.
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Tortuosity correction of Kozeny's hydraulic diameter of a porous medium
NASA Astrophysics Data System (ADS)
Shin, C.
2017-02-01
The hydraulic diameter of a porous medium is the most important characteristic parameter governing porous flow aspects. Kozeny's hydraulic diameter has been used as the representative definition ever since he proposed it in 1927. However, it seems likely that this definition does not perfectly reflect the porous flow features even if the geometric relations of porous media are reasonably considered. Here we reviewed its definition by introducing Darcy's friction flow relation, and discovered that the term "tortuosity" should be included in the definition to more accurately characterize porous flows. Thus, the definition of "Tortuous Hydraulic Diameter (THD)," which corrects Kozeny's hydraulic diameter using tortuosity, is newly presented. Moreover, computational fluid dynamics simulations were performed to check the validity and applicability of the THD approach. As a result, it is seen that the THD demonstrates very low errors, with an average of 1.67%, whereas Kozeny's definition has relatively large errors, with an average of 12.8%. Accordingly, it is confirmed that the THD relation is the more accurate hydraulic diameter definition for a porous medium. Ultimately, the corrected definition can contribute to more reliable determinations of the other characteristic parameters and more reasonable porous flow analyses.
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Improving the Glucose Meter Error Grid With the Taguchi Loss Function.
Krouwer, Jan S
2016-07-01
Glucose meters often have similar performance when compared by error grid analysis. This is one reason that other statistics such as mean absolute relative deviation (MARD) are used to further differentiate performance. The problem with MARD is that too much information is lost. But additional information is available within the A zone of an error grid by using the Taguchi loss function. Applying the Taguchi loss function gives each glucose meter difference from reference a value ranging from 0 (no error) to 1 (error reaches the A zone limit). Values are averaged over all data which provides an indication of risk of an incorrect medical decision. This allows one to differentiate glucose meter performance for the common case where meters have a high percentage of values in the A zone and no values beyond the B zone. Examples are provided using simulated data. © 2015 Diabetes Technology Society.
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Nibali, Maria L; Tombleson, Tom; Brady, Philip H; Wagner, Phillip
2015-10-01
Understanding typical variation of vertical jump (VJ) performance and confounding sources of its typical variability (i.e., familiarization and competitive level) is pertinent in the routine monitoring of athletes. We evaluated the presence of systematic error (learning effect) and nonuniformity of error (heteroscedasticity) across VJ performances of athletes that differ in competitive level and quantified the reliability of VJ kinetic and kinematic variables relative to the smallest worthwhile change (SWC). One hundred thirteen high school athletes, 30 college athletes, and 35 professional athletes completed repeat VJ trials. Average eccentric rate of force development (RFD), average concentric (CON) force, CON impulse, and jump height measurements were obtained from vertical ground reaction force (VGRF) data. Systematic error was assessed by evaluating changes in the mean of repeat trials. Heteroscedasticity was evaluated by plotting the difference score (trial 2 - trial 1) against the mean of the trials. Variability of jump variables was calculated as the typical error (TE) and coefficient of variation (%CV). No substantial systematic error (effect size range: -0.07 to 0.11) or heteroscedasticity was present for any of the VJ variables. Vertical jump can be performed without the need for familiarization trials, and the variability can be conveyed as either the raw TE or the %CV. Assessment of VGRF variables is an effective and reliable means of assessing VJ performance. Average CON force and CON impulse are highly reliable (%CV: 2.7% ×/÷ 1.10), although jump height was the only variable to display a %CV ≤SWC. Eccentric RFD is highly variable yet should not be discounted from VJ assessments on this factor alone because it may be sensitive to changes in response to training or fatigue that exceed the TE.
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NASA Technical Reports Server (NTRS)
Kimes, D. S.; Kerber, A. G.; Sellers, P. J.
1993-01-01
Spatial averaging errors which may occur when creating hemispherical reflectance maps for different cover types from direct nadir technique to estimate the hemispherical reflectance are assessed by comparing the results with those obtained with a knowledge-based system called VEG (Kimes et al., 1991, 1992). It was found that hemispherical reflectance errors provided by using VEG are much less than those using the direct nadir techniques, depending on conditions. Suggestions are made concerning sampling and averaging strategies for creating hemispherical reflectance maps for photosynthetic, carbon cycle, and climate change studies.
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Impact of TRMM and SSM/I-derived Precipitation and Moisture Data on the GEOS Global Analysis
NASA Technical Reports Server (NTRS)
Hou, Arthur Y.; Zhang, Sara Q.; daSilva, Arlindo M.; Olson, William S.
1999-01-01
Current global analyses contain significant errors in primary hydrological fields such as precipitation, evaporation, and related cloud and moisture in the tropics. The Data Assimilation Office at NASA's Goddard Space Flight Center has been exploring the use of space-based rainfall and total precipitable water (TPW) estimates to constrain these hydrological parameters in the Goddard Earth Observing System (GEOS) global data assimilation system. We present results showing that assimilating the 6-hour averaged rain rates and TPW estimates from the Tropical Rainfall Measuring Mission (TRMM) and Special Sensor Microwave/Imager (SSM/I) instruments improves not only the precipitation and moisture estimates but also reduce state-dependent systematic errors in key climate parameters directly linked to convection such as the outgoing longwave radiation, clouds, and the large-scale circulation. The improved analysis also improves short-range forecasts beyond 1 day, but the impact is relatively modest compared with improvements in the time-averaged analysis. The study shows that, in the presence of biases and other errors of the forecast model, improving the short-range forecast is not necessarily prerequisite for improving the assimilation as a climate data set. The full impact of a given type of observation on the assimilated data set should not be measured solely in terms of forecast skills.
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NASA Technical Reports Server (NTRS)
Chelton, Dudley B.; Schlax, Michael G.
1991-01-01
The sampling error of an arbitrary linear estimate of a time-averaged quantity constructed from a time series of irregularly spaced observations at a fixed located is quantified through a formalism. The method is applied to satellite observations of chlorophyll from the coastal zone color scanner. The two specific linear estimates under consideration are the composite average formed from the simple average of all observations within the averaging period and the optimal estimate formed by minimizing the mean squared error of the temporal average based on all the observations in the time series. The resulting suboptimal estimates are shown to be more accurate than composite averages. Suboptimal estimates are also found to be nearly as accurate as optimal estimates using the correct signal and measurement error variances and correlation functions for realistic ranges of these parameters, which makes it a viable practical alternative to the composite average method generally employed at present.
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Antidepressant and antipsychotic medication errors reported to United States poison control centers.
Kamboj, Alisha; Spiller, Henry A; Casavant, Marcel J; Chounthirath, Thitphalak; Hodges, Nichole L; Smith, Gary A
2018-05-08
To investigate unintentional therapeutic medication errors associated with antidepressant and antipsychotic medications in the United States and expand current knowledge on the types of errors commonly associated with these medications. A retrospective analysis of non-health care facility unintentional therapeutic errors associated with antidepressant and antipsychotic medications was conducted using data from the National Poison Data System. From 2000 to 2012, poison control centers received 207 670 calls reporting unintentional therapeutic errors associated with antidepressant or antipsychotic medications that occurred outside of a health care facility, averaging 15 975 errors annually. The rate of antidepressant-related errors increased by 50.6% from 2000 to 2004, decreased by 6.5% from 2004 to 2006, and then increased 13.0% from 2006 to 2012. The rate of errors related to antipsychotic medications increased by 99.7% from 2000 to 2004 and then increased by 8.8% from 2004 to 2012. Overall, 70.1% of reported errors occurred among adults, and 59.3% were among females. The medications most frequently associated with errors were selective serotonin reuptake inhibitors (30.3%), atypical antipsychotics (24.1%), and other types of antidepressants (21.5%). Most medication errors took place when an individual inadvertently took or was given a medication twice (41.0%), inadvertently took someone else's medication (15.6%), or took the wrong medication (15.6%). This study provides a comprehensive overview of non-health care facility unintentional therapeutic errors associated with antidepressant and antipsychotic medications. The frequency and rate of these errors increased significantly from 2000 to 2012. Given that use of these medications is increasing in the US, this study provides important information about the epidemiology of the associated medication errors. Copyright © 2018 John Wiley & Sons, Ltd.
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NASA Technical Reports Server (NTRS)
Jekeli, C.
1979-01-01
Through the method of truncation functions, the oceanic geoid undulation is divided into two constituents: an inner zone contribution expressed as an integral of surface gravity disturbances over a spherical cap; and an outer zone contribution derived from a finite set of potential harmonic coefficients. Global, average error estimates are formulated for undulation differences, thereby providing accuracies for a relative geoid. The error analysis focuses on the outer zone contribution for which the potential coefficient errors are modeled. The method of computing undulations based on gravity disturbance data for the inner zone is compared to the similar, conventional method which presupposes gravity anomaly data within this zone.
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How good are the Garvey-Kelson predictions of nuclear masses?
NASA Astrophysics Data System (ADS)
Morales, Irving O.; López Vieyra, J. C.; Hirsch, J. G.; Frank, A.
2009-09-01
The Garvey-Kelson relations are used in an iterative process to predict nuclear masses in the neighborhood of nuclei with measured masses. Average errors in the predicted masses for the first three iteration shells are smaller than those obtained with the best nuclear mass models. Their quality is comparable with the Audi-Wapstra extrapolations, offering a simple and reproducible procedure for short range mass predictions. A systematic study of the way the error grows as a function of the iteration and the distance to the known masses region, shows that a correlation exists between the error and the residual neutron-proton interaction, produced mainly by the implicit assumption that V varies smoothly along the nuclear landscape.
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Dai, Wujiao; Shi, Qiang; Cai, Changsheng
2017-01-01
The carrier phase multipath effect is one of the most significant error sources in the precise positioning of BeiDou Navigation Satellite System (BDS). We analyzed the characteristics of BDS multipath, and found the multipath errors of geostationary earth orbit (GEO) satellite signals are systematic, whereas those of inclined geosynchronous orbit (IGSO) or medium earth orbit (MEO) satellites are both systematic and random. The modified multipath mitigation methods, including sidereal filtering algorithm and multipath hemispherical map (MHM) model, were used to improve BDS dynamic deformation monitoring. The results indicate that the sidereal filtering methods can reduce the root mean square (RMS) of positioning errors in the east, north and vertical coordinate directions by 15%, 37%, 25% and 18%, 51%, 27% in the coordinate and observation domains, respectively. By contrast, the MHM method can reduce the RMS by 22%, 52% and 27% on average. In addition, the BDS multipath errors in static baseline solutions are a few centimeters in multipath-rich environments, which is different from that of Global Positioning System (GPS) multipath. Therefore, we add a parameter representing the GEO multipath error in observation equation to the adjustment model to improve the precision of BDS static baseline solutions. And the results show that the modified model can achieve an average precision improvement of 82%, 54% and 68% in the east, north and up coordinate directions, respectively. PMID:28387744
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Dai, Wujiao; Shi, Qiang; Cai, Changsheng
2017-04-07
The carrier phase multipath effect is one of the most significant error sources in the precise positioning of BeiDou Navigation Satellite System (BDS). We analyzed the characteristics of BDS multipath, and found the multipath errors of geostationary earth orbit (GEO) satellite signals are systematic, whereas those of inclined geosynchronous orbit (IGSO) or medium earth orbit (MEO) satellites are both systematic and random. The modified multipath mitigation methods, including sidereal filtering algorithm and multipath hemispherical map (MHM) model, were used to improve BDS dynamic deformation monitoring. The results indicate that the sidereal filtering methods can reduce the root mean square (RMS) of positioning errors in the east, north and vertical coordinate directions by 15%, 37%, 25% and 18%, 51%, 27% in the coordinate and observation domains, respectively. By contrast, the MHM method can reduce the RMS by 22%, 52% and 27% on average. In addition, the BDS multipath errors in static baseline solutions are a few centimeters in multipath-rich environments, which is different from that of Global Positioning System (GPS) multipath. Therefore, we add a parameter representing the GEO multipath error in observation equation to the adjustment model to improve the precision of BDS static baseline solutions. And the results show that the modified model can achieve an average precision improvement of 82%, 54% and 68% in the east, north and up coordinate directions, respectively.
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Björkstén, Karin Sparring; Bergqvist, Monica; Andersén-Karlsson, Eva; Benson, Lina; Ulfvarson, Johanna
2016-08-24
Many studies address the prevalence of medication errors but few address medication errors serious enough to be regarded as malpractice. Other studies have analyzed the individual and system contributory factor leading to a medication error. Nurses have a key role in medication administration, and there are contradictory reports on the nurses' work experience in relation to the risk and type for medication errors. All medication errors where a nurse was held responsible for malpractice (n = 585) during 11 years in Sweden were included. A qualitative content analysis and classification according to the type and the individual and system contributory factors was made. In order to test for possible differences between nurses' work experience and associations within and between the errors and contributory factors, Fisher's exact test was used, and Cohen's kappa (k) was performed to estimate the magnitude and direction of the associations. There were a total of 613 medication errors in the 585 cases, the most common being "Wrong dose" (41 %), "Wrong patient" (13 %) and "Omission of drug" (12 %). In 95 % of the cases, an average of 1.4 individual contributory factors was found; the most common being "Negligence, forgetfulness or lack of attentiveness" (68 %), "Proper protocol not followed" (25 %), "Lack of knowledge" (13 %) and "Practice beyond scope" (12 %). In 78 % of the cases, an average of 1.7 system contributory factors was found; the most common being "Role overload" (36 %), "Unclear communication or orders" (30 %) and "Lack of adequate access to guidelines or unclear organisational routines" (30 %). The errors "Wrong patient due to mix-up of patients" and "Wrong route" and the contributory factors "Lack of knowledge" and "Negligence, forgetfulness or lack of attentiveness" were more common in less experienced nurses. The experienced nurses were more prone to "Practice beyond scope of practice" and to make errors in spite of "Lack of adequate access to guidelines or unclear organisational routines". Medication errors regarded as malpractice in Sweden were of the same character as medication errors worldwide. A complex interplay between individual and system factors often contributed to the errors.
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VizieR Online Data Catalog: V and R CCD photometry of visual binaries (Abad+, 2004)
NASA Astrophysics Data System (ADS)
Abad, C.; Docobo, J. A.; Lanchares, V.; Lahulla, J. F.; Abelleira, P.; Blanco, J.; Alvarez, C.
2003-11-01
Table 1 gives relevant data for the visual binaries observed. Observations were carried out over a short period of time, therefore we assign the mean epoch (1998.58) for the totality of data. Data of individual stars are presented as average data with errors, by parameter, when various observations have been calculated, as well as the number of observations involved. Errors corresponding to astrometric relative positions between components are always present. For single observations, parameter fitting errors, specially for dx and dy parameters, have been calculated analysing the chi2 test around the minimum. Following the rules for error propagation, theta and rho errors can be estimated. Then, Table 1 shows single observation errors with an additional significant digit. When a star does not have known references, we include it in Table 2, where J2000 position and magnitudes are from the USNO-A2.0 catalogue (Monet et al., 1998, Cat. ). (2 data files).
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Wang, Chunhao; Yin, Fang-Fang; Kirkpatrick, John P; Chang, Zheng
2017-08-01
To investigate the feasibility of using undersampled k-space data and an iterative image reconstruction method with total generalized variation penalty in the quantitative pharmacokinetic analysis for clinical brain dynamic contrast-enhanced magnetic resonance imaging. Eight brain dynamic contrast-enhanced magnetic resonance imaging scans were retrospectively studied. Two k-space sparse sampling strategies were designed to achieve a simulated image acquisition acceleration factor of 4. They are (1) a golden ratio-optimized 32-ray radial sampling profile and (2) a Cartesian-based random sampling profile with spatiotemporal-regularized sampling density constraints. The undersampled data were reconstructed to yield images using the investigated reconstruction technique. In quantitative pharmacokinetic analysis on a voxel-by-voxel basis, the rate constant K trans in the extended Tofts model and blood flow F B and blood volume V B from the 2-compartment exchange model were analyzed. Finally, the quantitative pharmacokinetic parameters calculated from the undersampled data were compared with the corresponding calculated values from the fully sampled data. To quantify each parameter's accuracy calculated using the undersampled data, error in volume mean, total relative error, and cross-correlation were calculated. The pharmacokinetic parameter maps generated from the undersampled data appeared comparable to the ones generated from the original full sampling data. Within the region of interest, most derived error in volume mean values in the region of interest was about 5% or lower, and the average error in volume mean of all parameter maps generated through either sampling strategy was about 3.54%. The average total relative error value of all parameter maps in region of interest was about 0.115, and the average cross-correlation of all parameter maps in region of interest was about 0.962. All investigated pharmacokinetic parameters had no significant differences between the result from original data and the reduced sampling data. With sparsely sampled k-space data in simulation of accelerated acquisition by a factor of 4, the investigated dynamic contrast-enhanced magnetic resonance imaging pharmacokinetic parameters can accurately estimate the total generalized variation-based iterative image reconstruction method for reliable clinical application.
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Reconstruction of regional mean temperature for East Asia since 1900s and its uncertainties
NASA Astrophysics Data System (ADS)
Hua, W.
2017-12-01
Regional average surface air temperature (SAT) is one of the key variables often used to investigate climate change. Unfortunately, because of the limited observations over East Asia, there were also some gaps in the observation data sampling for regional mean SAT analysis, which was important to estimate past climate change. In this study, the regional average temperature of East Asia since 1900s is calculated by the Empirical Orthogonal Function (EOF)-based optimal interpolation (OA) method with considering the data errors. The results show that our estimate is more precise and robust than the results from simple average, which provides a better way for past climate reconstruction. In addition to the reconstructed regional average SAT anomaly time series, we also estimated uncertainties of reconstruction. The root mean square error (RMSE) results show that the the error decreases with respect to time, and are not sufficiently large to alter the conclusions on the persist warming in East Asia during twenty-first century. Moreover, the test of influence of data error on reconstruction clearly shows the sensitivity of reconstruction to the size of the data error.
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Ground state properties of 3d metals from self-consistent GW approach
Kutepov, Andrey L.
2017-10-06
The self consistent GW approach (scGW) has been applied to calculate the ground state properties (equilibrium Wigner–Seitz radius S WZ and bulk modulus B) of 3d transition metals Sc, Ti, V, Fe, Co, Ni, and Cu. The approach systematically underestimates S WZ with average relative deviation from the experimental data of about 1% and it overestimates the calculated bulk modulus with relative error of about 25%. We show that scGW is superior in accuracy as compared to the local density approximation but it is less accurate than the generalized gradient approach for the materials studied. If compared to the randommore » phase approximation, scGW is slightly less accurate, but its error for 3d metals looks more systematic. Lastly, the systematic nature of the deviation from the experimental data suggests that the next order of the perturbation theory should allow one to reduce the error.« less
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Ground state properties of 3d metals from self-consistent GW approach
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kutepov, Andrey L.
The self consistent GW approach (scGW) has been applied to calculate the ground state properties (equilibrium Wigner–Seitz radius S WZ and bulk modulus B) of 3d transition metals Sc, Ti, V, Fe, Co, Ni, and Cu. The approach systematically underestimates S WZ with average relative deviation from the experimental data of about 1% and it overestimates the calculated bulk modulus with relative error of about 25%. We show that scGW is superior in accuracy as compared to the local density approximation but it is less accurate than the generalized gradient approach for the materials studied. If compared to the randommore » phase approximation, scGW is slightly less accurate, but its error for 3d metals looks more systematic. Lastly, the systematic nature of the deviation from the experimental data suggests that the next order of the perturbation theory should allow one to reduce the error.« less
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Radial basis function network learns ceramic processing and predicts related strength and density
NASA Technical Reports Server (NTRS)
Cios, Krzysztof J.; Baaklini, George Y.; Vary, Alex; Tjia, Robert E.
1993-01-01
Radial basis function (RBF) neural networks were trained using the data from 273 Si3N4 modulus of rupture (MOR) bars which were tested at room temperature and 135 MOR bars which were tested at 1370 C. Milling time, sintering time, and sintering gas pressure were the processing parameters used as the input features. Flexural strength and density were the outputs by which the RBF networks were assessed. The 'nodes-at-data-points' method was used to set the hidden layer centers and output layer training used the gradient descent method. The RBF network predicted strength with an average error of less than 12 percent and density with an average error of less than 2 percent. Further, the RBF network demonstrated a potential for optimizing and accelerating the development and processing of ceramic materials.
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NASA Astrophysics Data System (ADS)
Hüsami Afşar, Mehdi; Unal Şorman, Ali; Tugrul Yilmaz, Mustafa
2016-04-01
Different drought characteristics (e.g. duration, average severity, and average areal extent) often have monotonic relation that increased magnitude of one often follows a similar increase in the magnitude of the other drought characteristic. Hence it is viable to establish a relationship between different drought characteristics with the goal of predicting one using other ones. Copula functions that relate different variables using their joint and conditional cumulative probability distributions are often used to statistically model the drought characteristics. In this study bivariate and trivariate joint probabilities of these characteristics are obtained over Ankara (Turkey) between 1960 and 2013. Copula-based return period estimation of drought characteristics of duration, average severity, and average areal extent show joint probabilities of these characteristics can be satisfactorily achieved. Among different copula families investigated in this study, elliptical family (i.e. including normal and t-student copula functions) resulted in the lowest root mean square error. "This study was supported by TUBITAK fund #114Y676)."
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NASA Technical Reports Server (NTRS)
Whitmore, Stephen A.; Moes, Timothy R.
1994-01-01
Presented is a feasibility and error analysis for a hypersonic flush airdata system on a hypersonic flight experiment (HYFLITE). HYFLITE heating loads make intrusive airdata measurement impractical. Although this analysis is specifically for the HYFLITE vehicle and trajectory, the problems analyzed are generally applicable to hypersonic vehicles. A layout of the flush-port matrix is shown. Surface pressures are related airdata parameters using a simple aerodynamic model. The model is linearized using small perturbations and inverted using nonlinear least-squares. Effects of various error sources on the overall uncertainty are evaluated using an error simulation. Error sources modeled include boundarylayer/viscous interactions, pneumatic lag, thermal transpiration in the sensor pressure tubing, misalignment in the matrix layout, thermal warping of the vehicle nose, sampling resolution, and transducer error. Using simulated pressure data for input to the estimation algorithm, effects caused by various error sources are analyzed by comparing estimator outputs with the original trajectory. To obtain ensemble averages the simulation is run repeatedly and output statistics are compiled. Output errors resulting from the various error sources are presented as a function of Mach number. Final uncertainties with all modeled error sources included are presented as a function of Mach number.
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Time series forecasting of future claims amount of SOCSO's employment injury scheme (EIS)
NASA Astrophysics Data System (ADS)
Zulkifli, Faiz; Ismail, Isma Liana; Chek, Mohd Zaki Awang; Jamal, Nur Faezah; Ridzwan, Ahmad Nur Azam Ahmad; Jelas, Imran Md; Noor, Syamsul Ikram Mohd; Ahmad, Abu Bakar
2012-09-01
The Employment Injury Scheme (EIS) provides protection to employees who are injured due to accidents whilst working, commuting from home to the work place or during employee takes a break during an authorized recess time or while travelling that is related with his work. The main purpose of this study is to forecast value on claims amount of EIS for the year 2011 until 2015 by using appropriate models. These models were tested on the actual EIS data from year 1972 until year 2010. Three different forecasting models are chosen for comparisons. These are the Naïve with Trend Model, Average Percent Change Model and Double Exponential Smoothing Model. The best model is selected based on the smallest value of error measures using the Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). From the result, the best model that best fit the forecast for the EIS is the Average Percent Change Model. Furthermore, the result also shows the claims amount of EIS for the year 2011 to year 2015 continue to trend upwards from year 2010.
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NASA Astrophysics Data System (ADS)
Wang, Limin; Shen, Yiteng; Yu, Jingxian; Li, Ping; Zhang, Ridong; Gao, Furong
2018-01-01
In order to cope with system disturbances in multi-phase batch processes with different dimensions, a hybrid robust control scheme of iterative learning control combined with feedback control is proposed in this paper. First, with a hybrid iterative learning control law designed by introducing the state error, the tracking error and the extended information, the multi-phase batch process is converted into a two-dimensional Fornasini-Marchesini (2D-FM) switched system with different dimensions. Second, a switching signal is designed using the average dwell-time method integrated with the related switching conditions to give sufficient conditions ensuring stable running for the system. Finally, the minimum running time of the subsystems and the control law gains are calculated by solving the linear matrix inequalities. Meanwhile, a compound 2D controller with robust performance is obtained, which includes a robust extended feedback control for ensuring the steady-state tracking error to converge rapidly. The application on an injection molding process displays the effectiveness and superiority of the proposed strategy.
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Partial compensation interferometry measurement system for parameter errors of conicoid surface
NASA Astrophysics Data System (ADS)
Hao, Qun; Li, Tengfei; Hu, Yao; Wang, Shaopu; Ning, Yan; Chen, Zhuo
2018-06-01
Surface parameters, such as vertex radius of curvature and conic constant, are used to describe the shape of an aspheric surface. Surface parameter errors (SPEs) are deviations affecting the optical characteristics of an aspheric surface. Precise measurement of SPEs is critical in the evaluation of optical surfaces. In this paper, a partial compensation interferometry measurement system for SPE of a conicoid surface is proposed based on the theory of slope asphericity and the best compensation distance. The system is developed to measure the SPE-caused best compensation distance change and SPE-caused surface shape change and then calculate the SPEs with the iteration algorithm for accuracy improvement. Experimental results indicate that the average relative measurement accuracy of the proposed system could be better than 0.02% for the vertex radius of curvature error and 2% for the conic constant error.
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NASA Technical Reports Server (NTRS)
Baurle, R. A.
2015-01-01
Steady-state and scale-resolving simulations have been performed for flow in and around a model scramjet combustor flameholder. The cases simulated corresponded to those used to examine this flowfield experimentally using particle image velocimetry. A variety of turbulence models were used for the steady-state Reynolds-averaged simulations which included both linear and non-linear eddy viscosity models. The scale-resolving simulations used a hybrid Reynolds-averaged / large eddy simulation strategy that is designed to be a large eddy simulation everywhere except in the inner portion (log layer and below) of the boundary layer. Hence, this formulation can be regarded as a wall-modeled large eddy simulation. This effort was undertaken to formally assess the performance of the hybrid Reynolds-averaged / large eddy simulation modeling approach in a flowfield of interest to the scramjet research community. The numerical errors were quantified for both the steady-state and scale-resolving simulations prior to making any claims of predictive accuracy relative to the measurements. The steady-state Reynolds-averaged results showed a high degree of variability when comparing the predictions obtained from each turbulence model, with the non-linear eddy viscosity model (an explicit algebraic stress model) providing the most accurate prediction of the measured values. The hybrid Reynolds-averaged/large eddy simulation results were carefully scrutinized to ensure that even the coarsest grid had an acceptable level of resolution for large eddy simulation, and that the time-averaged statistics were acceptably accurate. The autocorrelation and its Fourier transform were the primary tools used for this assessment. The statistics extracted from the hybrid simulation strategy proved to be more accurate than the Reynolds-averaged results obtained using the linear eddy viscosity models. However, there was no predictive improvement noted over the results obtained from the explicit Reynolds stress model. Fortunately, the numerical error assessment at most of the axial stations used to compare with measurements clearly indicated that the scale-resolving simulations were improving (i.e. approaching the measured values) as the grid was refined. Hence, unlike a Reynolds-averaged simulation, the hybrid approach provides a mechanism to the end-user for reducing model-form errors.
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Erda, F G; Bloemen, J; Steppe, K
2014-01-01
In studies on internal CO2 transport, average xylem sap pH (pH(x)) is one of the factors used for calculation of the concentration of dissolved inorganic carbon in the xylem sap ([CO2 *]). Lack of detailed pH(x) measurements at high temporal resolution could be a potential source of error when evaluating [CO2*] dynamics. In this experiment, we performed continuous measurements of CO2 concentration ([CO2]) and stem temperature (T(stem)), complemented with pH(x) measurements at 30-min intervals during the day at various stages of the growing season (Day of the Year (DOY): 86 (late winter), 128 (mid-spring) and 155 (early summer)) on a plum tree (Prunus domestica L. cv. Reine Claude d'Oullins). We used the recorded pH(x) to calculate [CO2*] based on T(stem) and the corresponding measured [CO2]. No statistically significant difference was found between mean [CO2*] calculated with instantaneous pH(x) and daily average pH(x). However, using an average pH(x) value from a different part of the growing season than the measurements of [CO2] and T(stem) to estimate [CO2*] led to a statistically significant error. The error varied between 3.25 ± 0.01% under-estimation and 3.97 ± 0.01% over-estimation, relative to the true [CO2*] data. Measured pH(x) did not show a significant daily variation, unlike [CO2], which increased during the day and declined at night. As the growing season progressed, daily average [CO2] (3.4%, 5.3%, 7.4%) increased and average pH(x) (5.43, 5.29, 5.20) decreased. Increase in [CO2] will increase its solubility in xylem sap according to Henry's law, and the dissociation of [CO2*] will negatively affect pH(x). Our results are the first quantifying the error in [CO2*] due to the interaction between [CO2] and pH(x) on a seasonal time scale. We found significant changes in pH(x) across the growing season, but overall the effect on the calculation of [CO2*] remained within an error range of 4%. However, it is possible that the error could be more substantial for other tree species, particularly if pH(x) is in the more sensitive range (pH(x) > 6.5). © 2013 German Botanical Society and The Royal Botanical Society of the Netherlands.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Damato, AL; Bhagwat, MS; Buzurovic, I
Purpose: To investigate the use of a system using EM tracking, postprocessing and error-detection algorithms for measuring brachytherapy catheter locations and for detecting errors and resolving uncertainties in treatment-planning catheter digitization. Methods: An EM tracker was used to localize 13 catheters in a clinical surface applicator (A) and 15 catheters inserted into a phantom (B). Two pairs of catheters in (B) crossed paths at a distance <2 mm, producing an undistinguishable catheter artifact in that location. EM data was post-processed for noise reduction and reformatted to provide the dwell location configuration. CT-based digitization was automatically extracted from the brachytherapy planmore » DICOM files (CT). EM dwell digitization error was characterized in terms of the average and maximum distance between corresponding EM and CT dwells per catheter. The error detection rate (detected errors / all errors) was calculated for 3 types of errors: swap of two catheter numbers; incorrect catheter number identification superior to the closest position between two catheters (mix); and catheter-tip shift. Results: The averages ± 1 standard deviation of the average and maximum registration error per catheter were 1.9±0.7 mm and 3.0±1.1 mm for (A) and 1.6±0.6 mm and 2.7±0.8 mm for (B). The error detection rate was 100% (A and B) for swap errors, mix errors, and shift >4.5 mm (A) and >5.5 mm (B); errors were detected for shifts on average >2.0 mm (A) and >2.4 mm (B). Both mix errors associated with undistinguishable catheter artifacts were detected and at least one of the involved catheters was identified. Conclusion: We demonstrated the use of an EM tracking system for localization of brachytherapy catheters, detection of digitization errors and resolution of undistinguishable catheter artifacts. Automatic digitization may be possible with a registration between the imaging and the EM frame of reference. Research funded by the Kaye Family Award 2012.« less
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Effects of Acids, Bases, and Heteroatoms on Proximal Radial Distribution Functions for Proteins
Nguyen, Bao Linh; Pettitt, B. Montgomery
2015-01-01
The proximal distribution of water around proteins is a convenient method of quantifying solvation. We consider the effect of charged and sulfur-containing amino acid side-chain atoms on the proximal radial distribution function (pRDF) of water molecules around proteins using side-chain analogs. The pRDF represents the relative probability of finding any solvent molecule at a distance from the closest or surface perpendicular protein atom. We consider the near-neighbor distribution. Previously, pRDFs were shown to be universal descriptors of the water molecules around C, N, and O atom types across hundreds of globular proteins. Using averaged pRDFs, a solvent density around any globular protein can be reconstructed with controllable relative error. Solvent reconstruction using the additional information from charged amino acid side-chain atom types from both small models and protein averages reveals the effects of surface charge distribution on solvent density and improves the reconstruction errors relative to simulation. Solvent density reconstructions from the small-molecule models are as effective and less computationally demanding than reconstructions from full macromolecular models in reproducing preferred hydration sites and solvent density fluctuations. PMID:26388706
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NASA Astrophysics Data System (ADS)
Nooruddin, Hasan A.; Anifowose, Fatai; Abdulraheem, Abdulazeez
2014-03-01
Soft computing techniques are recently becoming very popular in the oil industry. A number of computational intelligence-based predictive methods have been widely applied in the industry with high prediction capabilities. Some of the popular methods include feed-forward neural networks, radial basis function network, generalized regression neural network, functional networks, support vector regression and adaptive network fuzzy inference system. A comparative study among most popular soft computing techniques is presented using a large dataset published in literature describing multimodal pore systems in the Arab D formation. The inputs to the models are air porosity, grain density, and Thomeer parameters obtained using mercury injection capillary pressure profiles. Corrected air permeability is the target variable. Applying developed permeability models in recent reservoir characterization workflow ensures consistency between micro and macro scale information represented mainly by Thomeer parameters and absolute permeability. The dataset was divided into two parts with 80% of data used for training and 20% for testing. The target permeability variable was transformed to the logarithmic scale as a pre-processing step and to show better correlations with the input variables. Statistical and graphical analysis of the results including permeability cross-plots and detailed error measures were created. In general, the comparative study showed very close results among the developed models. The feed-forward neural network permeability model showed the lowest average relative error, average absolute relative error, standard deviations of error and root means squares making it the best model for such problems. Adaptive network fuzzy inference system also showed very good results.
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Modeling the Error of the Medtronic Paradigm Veo Enlite Glucose Sensor.
Biagi, Lyvia; Ramkissoon, Charrise M; Facchinetti, Andrea; Leal, Yenny; Vehi, Josep
2017-06-12
Continuous glucose monitors (CGMs) are prone to inaccuracy due to time lags, sensor drift, calibration errors, and measurement noise. The aim of this study is to derive the model of the error of the second generation Medtronic Paradigm Veo Enlite (ENL) sensor and compare it with the Dexcom SEVEN PLUS (7P), G4 PLATINUM (G4P), and advanced G4 for Artificial Pancreas studies (G4AP) systems. An enhanced methodology to a previously employed technique was utilized to dissect the sensor error into several components. The dataset used included 37 inpatient sessions in 10 subjects with type 1 diabetes (T1D), in which CGMs were worn in parallel and blood glucose (BG) samples were analyzed every 15 ± 5 min Calibration error and sensor drift of the ENL sensor was best described by a linear relationship related to the gain and offset. The mean time lag estimated by the model is 9.4 ± 6.5 min. The overall average mean absolute relative difference (MARD) of the ENL sensor was 11.68 ± 5.07% Calibration error had the highest contribution to total error in the ENL sensor. This was also reported in the 7P, G4P, and G4AP. The model of the ENL sensor error will be useful to test the in silico performance of CGM-based applications, i.e., the artificial pancreas, employing this kind of sensor.
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Accuracy Study of a Robotic System for MRI-guided Prostate Needle Placement
Seifabadi, Reza; Cho, Nathan BJ.; Song, Sang-Eun; Tokuda, Junichi; Hata, Nobuhiko; Tempany, Clare M.; Fichtinger, Gabor; Iordachita, Iulian
2013-01-01
Background Accurate needle placement is the first concern in percutaneous MRI-guided prostate interventions. In this phantom study, different sources contributing to the overall needle placement error of a MRI-guided robot for prostate biopsy have been identified, quantified, and minimized to the possible extent. Methods and Materials The overall needle placement error of the system was evaluated in a prostate phantom. This error was broken into two parts: the error associated with the robotic system (called before-insertion error) and the error associated with needle-tissue interaction (called due-to-insertion error). The before-insertion error was measured directly in a soft phantom and different sources contributing into this part were identified and quantified. A calibration methodology was developed to minimize the 4-DOF manipulator’s error. The due-to-insertion error was indirectly approximated by comparing the overall error and the before-insertion error. The effect of sterilization on the manipulator’s accuracy and repeatability was also studied. Results The average overall system error in phantom study was 2.5 mm (STD=1.1mm). The average robotic system error in super soft phantom was 1.3 mm (STD=0.7 mm). Assuming orthogonal error components, the needle-tissue interaction error was approximated to be 2.13 mm thus having larger contribution to the overall error. The average susceptibility artifact shift was 0.2 mm. The manipulator’s targeting accuracy was 0.71 mm (STD=0.21mm) after robot calibration. The robot’s repeatability was 0.13 mm. Sterilization had no noticeable influence on the robot’s accuracy and repeatability. Conclusions The experimental methodology presented in this paper may help researchers to identify, quantify, and minimize different sources contributing into the overall needle placement error of an MRI-guided robotic system for prostate needle placement. In the robotic system analyzed here, the overall error of the studied system remained within the acceptable range. PMID:22678990
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Accuracy study of a robotic system for MRI-guided prostate needle placement.
Seifabadi, Reza; Cho, Nathan B J; Song, Sang-Eun; Tokuda, Junichi; Hata, Nobuhiko; Tempany, Clare M; Fichtinger, Gabor; Iordachita, Iulian
2013-09-01
Accurate needle placement is the first concern in percutaneous MRI-guided prostate interventions. In this phantom study, different sources contributing to the overall needle placement error of a MRI-guided robot for prostate biopsy have been identified, quantified and minimized to the possible extent. The overall needle placement error of the system was evaluated in a prostate phantom. This error was broken into two parts: the error associated with the robotic system (called 'before-insertion error') and the error associated with needle-tissue interaction (called 'due-to-insertion error'). Before-insertion error was measured directly in a soft phantom and different sources contributing into this part were identified and quantified. A calibration methodology was developed to minimize the 4-DOF manipulator's error. The due-to-insertion error was indirectly approximated by comparing the overall error and the before-insertion error. The effect of sterilization on the manipulator's accuracy and repeatability was also studied. The average overall system error in the phantom study was 2.5 mm (STD = 1.1 mm). The average robotic system error in the Super Soft plastic phantom was 1.3 mm (STD = 0.7 mm). Assuming orthogonal error components, the needle-tissue interaction error was found to be approximately 2.13 mm, thus making a larger contribution to the overall error. The average susceptibility artifact shift was 0.2 mm. The manipulator's targeting accuracy was 0.71 mm (STD = 0.21 mm) after robot calibration. The robot's repeatability was 0.13 mm. Sterilization had no noticeable influence on the robot's accuracy and repeatability. The experimental methodology presented in this paper may help researchers to identify, quantify and minimize different sources contributing into the overall needle placement error of an MRI-guided robotic system for prostate needle placement. In the robotic system analysed here, the overall error of the studied system remained within the acceptable range. Copyright © 2012 John Wiley & Sons, Ltd.
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Aljasmi, Fatema; Almalood, Fatema
2018-01-01
Background One of the important activities that physicians – particularly general practitioners – perform is prescribing. It occurs in most health care facilities and especially in primary health care (PHC) settings. Objectives This study aims to determine what types of prescribing errors are made in PHC at Bahrain Defence Force (BDF) Hospital, and how common they are. Methods This was a retrospective study of data from PHC at BDF Hospital. The data consisted of 379 prescriptions randomly selected from the pharmacy between March and May 2013, and errors in the prescriptions were classified into five types: major omission, minor omission, commission, integration, and skill-related errors. Results Of the total prescriptions, 54.4% (N=206) were given to male patients and 45.6% (N=173) to female patients; 24.8% were given to patients under the age of 10 years. On average, there were 2.6 drugs per prescription. In the prescriptions, 8.7% of drugs were prescribed by their generic names, and 28% (N=106) of prescriptions included an antibiotic. Out of the 379 prescriptions, 228 had an error, and 44.3% (N=439) of the 992 prescribed drugs contained errors. The proportions of errors were as follows: 9.9% (N=38) were minor omission errors; 73.6% (N=323) were major omission errors; 9.3% (N=41) were commission errors; and 17.1% (N=75) were skill-related errors. Conclusion This study provides awareness of the presence of prescription errors and frequency of the different types of errors that exist in this hospital. Understanding the different types of errors could help future studies explore the causes of specific errors and develop interventions to reduce them. Further research should be conducted to understand the causes of these errors and demonstrate whether the introduction of electronic prescriptions has an effect on patient outcomes. PMID:29445304
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Moore, L.J.; Ruggiero, P.; List, J.H.
2006-01-01
More than one type of shoreline indicator can be used in shoreline change analyses, and quantifying the effects of this practice on the resulting shoreline change rates is important. Comparison of three high water line (proxy-based) shorelines and a mean high water intercept (datum-based) shoreline collected from simultaneous aerial photographic and lidar surveys of a relatively steep reflective beach (tan ?? = 0.07), which experiences a moderately energetic wave climate (annual average Hs = 1.2 m), reveals an average horizontal offset of 18.8 m between the two types of shoreline indicators. Vertical offsets are also substantial and are correlated with foreshore beach slope and corresponding variations in wave runup. Incorporating the average horizontal offset into both a short-term, endpoint shoreline change analysis and a long-term, linear regression analysis causes rates to be shifted an average of -0.5 m/y and -0.1 m/y, respectively. The rate shift increases with increasing horizontal offset and decreasing measurement intervals and, depending on the rapidity of shoreline change rates, is responsible for varying degrees of analysis error. Our results demonstrate that under many circumstances, the error attributable to proxy-datum offsets is small relative to shoreline change rates and thus not important. Furthermore, we find that when the error associated with proxy-datum offsets is large enough to be important, the shoreline change rates themselves are not likely to be significant. A total water level model reveals that the high water line digitized by three independent coastal labs for this study was generated by a combination of large waves and a high tide several days before the collection of aerial photography. This illustrates the complexity of the high water line as a shoreline indicator and calls into question traditional definitions, which consider the high water line a wetted bound or "marks left by the previous high tide.".
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NASA Technical Reports Server (NTRS)
Bell, Thomas L.; Kundu, Prasun K.; Kummerow, Christian D.; Einaudi, Franco (Technical Monitor)
2000-01-01
Quantitative use of satellite-derived maps of monthly rainfall requires some measure of the accuracy of the satellite estimates. The rainfall estimate for a given map grid box is subject to both remote-sensing error and, in the case of low-orbiting satellites, sampling error due to the limited number of observations of the grid box provided by the satellite. A simple model of rain behavior predicts that Root-mean-square (RMS) random error in grid-box averages should depend in a simple way on the local average rain rate, and the predicted behavior has been seen in simulations using surface rain-gauge and radar data. This relationship was examined using satellite SSM/I data obtained over the western equatorial Pacific during TOGA COARE. RMS error inferred directly from SSM/I rainfall estimates was found to be larger than predicted from surface data, and to depend less on local rain rate than was predicted. Preliminary examination of TRMM microwave estimates shows better agreement with surface data. A simple method of estimating rms error in satellite rainfall estimates is suggested, based on quantities that can be directly computed from the satellite data.
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A systematic comparison of error correction enzymes by next-generation sequencing
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lubock, Nathan B.; Zhang, Di; Sidore, Angus M.
Gene synthesis, the process of assembling genelength fragments from shorter groups of oligonucleotides (oligos), is becoming an increasingly important tool in molecular and synthetic biology. The length, quality and cost of gene synthesis are limited by errors produced during oligo synthesis and subsequent assembly. Enzymatic error correction methods are cost-effective means to ameliorate errors in gene synthesis. Previous analyses of these methods relied on cloning and Sanger sequencing to evaluate their efficiencies, limiting quantitative assessment. Here, we develop a method to quantify errors in synthetic DNA by next-generation sequencing. We analyzed errors in model gene assemblies and systematically compared sixmore » different error correction enzymes across 11 conditions. We find that ErrASE and T7 Endonuclease I are the most effective at decreasing average error rates (up to 5.8-fold relative to the input), whereas MutS is the best for increasing the number of perfect assemblies (up to 25.2-fold). We are able to quantify differential specificities such as ErrASE preferentially corrects C/G transversions whereas T7 Endonuclease I preferentially corrects A/T transversions. More generally, this experimental and computational pipeline is a fast, scalable and extensible way to analyze errors in gene assemblies, to profile error correction methods, and to benchmark DNA synthesis methods.« less
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A predictability study of Lorenz's 28-variable model as a dynamical system
NASA Technical Reports Server (NTRS)
Krishnamurthy, V.
1993-01-01
The dynamics of error growth in a two-layer nonlinear quasi-geostrophic model has been studied to gain an understanding of the mathematical theory of atmospheric predictability. The growth of random errors of varying initial magnitudes has been studied, and the relation between this classical approach and the concepts of the nonlinear dynamical systems theory has been explored. The local and global growths of random errors have been expressed partly in terms of the properties of an error ellipsoid and the Liapunov exponents determined by linear error dynamics. The local growth of small errors is initially governed by several modes of the evolving error ellipsoid but soon becomes dominated by the longest axis. The average global growth of small errors is exponential with a growth rate consistent with the largest Liapunov exponent. The duration of the exponential growth phase depends on the initial magnitude of the errors. The subsequent large errors undergo a nonlinear growth with a steadily decreasing growth rate and attain saturation that defines the limit of predictability. The degree of chaos and the largest Liapunov exponent show considerable variation with change in the forcing, which implies that the time variation in the external forcing can introduce variable character to the predictability.
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A systematic comparison of error correction enzymes by next-generation sequencing
Lubock, Nathan B.; Zhang, Di; Sidore, Angus M.; ...
2017-08-01
Gene synthesis, the process of assembling genelength fragments from shorter groups of oligonucleotides (oligos), is becoming an increasingly important tool in molecular and synthetic biology. The length, quality and cost of gene synthesis are limited by errors produced during oligo synthesis and subsequent assembly. Enzymatic error correction methods are cost-effective means to ameliorate errors in gene synthesis. Previous analyses of these methods relied on cloning and Sanger sequencing to evaluate their efficiencies, limiting quantitative assessment. Here, we develop a method to quantify errors in synthetic DNA by next-generation sequencing. We analyzed errors in model gene assemblies and systematically compared sixmore » different error correction enzymes across 11 conditions. We find that ErrASE and T7 Endonuclease I are the most effective at decreasing average error rates (up to 5.8-fold relative to the input), whereas MutS is the best for increasing the number of perfect assemblies (up to 25.2-fold). We are able to quantify differential specificities such as ErrASE preferentially corrects C/G transversions whereas T7 Endonuclease I preferentially corrects A/T transversions. More generally, this experimental and computational pipeline is a fast, scalable and extensible way to analyze errors in gene assemblies, to profile error correction methods, and to benchmark DNA synthesis methods.« less
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ERIC Educational Resources Information Center
Medrich, Elliott A.; Griffith, Jeanne E.
This report addresses two related issues. First, it summarizes the past international studies of mathematics and science, describing each study and its primary results. In place of country by country performance rankings, the report presents the average performance for each country accompanied by an estimate of the statistical error circumscribing…
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NASA Technical Reports Server (NTRS)
Bell, Thomas L.; Abdullah, A.; Martin, Russell L.; North, Gerald R.
1990-01-01
Estimates of monthly average rainfall based on satellite observations from a low earth orbit will differ from the true monthly average because the satellite observes a given area only intermittently. This sampling error inherent in satellite monitoring of rainfall would occur even if the satellite instruments could measure rainfall perfectly. The size of this error is estimated for a satellite system being studied at NASA, the Tropical Rainfall Measuring Mission (TRMM). First, the statistical description of rainfall on scales from 1 to 1000 km is examined in detail, based on rainfall data from the Global Atmospheric Research Project Atlantic Tropical Experiment (GATE). A TRMM-like satellite is flown over a two-dimensional time-evolving simulation of rainfall using a stochastic model with statistics tuned to agree with GATE statistics. The distribution of sampling errors found from many months of simulated observations is found to be nearly normal, even though the distribution of area-averaged rainfall is far from normal. For a range of orbits likely to be employed in TRMM, sampling error is found to be less than 10 percent of the mean for rainfall averaged over a 500 x 500 sq km area.
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Survival analysis with error-prone time-varying covariates: a risk set calibration approach
Liao, Xiaomei; Zucker, David M.; Li, Yi; Spiegelman, Donna
2010-01-01
Summary Occupational, environmental, and nutritional epidemiologists are often interested in estimating the prospective effect of time-varying exposure variables such as cumulative exposure or cumulative updated average exposure, in relation to chronic disease endpoints such as cancer incidence and mortality. From exposure validation studies, it is apparent that many of the variables of interest are measured with moderate to substantial error. Although the ordinary regression calibration approach is approximately valid and efficient for measurement error correction of relative risk estimates from the Cox model with time-independent point exposures when the disease is rare, it is not adaptable for use with time-varying exposures. By re-calibrating the measurement error model within each risk set, a risk set regression calibration method is proposed for this setting. An algorithm for a bias-corrected point estimate of the relative risk using an RRC approach is presented, followed by the derivation of an estimate of its variance, resulting in a sandwich estimator. Emphasis is on methods applicable to the main study/external validation study design, which arises in important applications. Simulation studies under several assumptions about the error model were carried out, which demonstrated the validity and efficiency of the method in finite samples. The method was applied to a study of diet and cancer from Harvard’s Health Professionals Follow-up Study (HPFS). PMID:20486928
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[Conversion methods of freshwater snail tissue dry mass and ash free dry mass].
Zhao, Wei-Hua; Wang, Hai-Jun; Wang, Hong-Zhu; Liu, Xue-Qin
2009-06-01
Mollusk biomass is usually expressed as wet mass with shell, but this expression fails to represent real biomass due to the high calcium carbonate content in shells. Tissue dry mass and ash free dry mass are relatively close to real biomass. However, the determination process of these two parameters is very complicated, and thus, it is necessary to establish simple and practical conversion methods for these two parameters. A total of six taxa of freshwater snails (Bellamya sp., Alocinma longicornis, Parafossarulus striatulus, Parafossarulus eximius, Semisulcospira cancellata, and Radix sp.) common in the Yangtze Basin were selected to explore the relations of their five shell dimension parameters, dry and wet mass with shells with their tissue dry mass and ash free dry mass. The regressions of the tissue dry mass and ash free dry mass with the five shell dimension parameters were all exponential (y = ax(b)). Among them, shell width and shell length were more precise (the average percentage error between observed and predicted value being 22.0% and 22.5%, respectively) than the other three parameters in the conversion of dry mass. Wet mass with shell could be directly converted to tissue dry mass and ash free dry mass, with an average percentage error of 21.7%. According to the essence of definition and the errors of conversion, ash free dry mass would be the optimum parameter to express snail biomass.
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Liability claims and costs before and after implementation of a medical error disclosure program.
Kachalia, Allen; Kaufman, Samuel R; Boothman, Richard; Anderson, Susan; Welch, Kathleen; Saint, Sanjay; Rogers, Mary A M
2010-08-17
Since 2001, the University of Michigan Health System (UMHS) has fully disclosed and offered compensation to patients for medical errors. To compare liability claims and costs before and after implementation of the UMHS disclosure-with-offer program. Retrospective before-after analysis from 1995 to 2007. Public academic medical center and health system. Inpatients and outpatients involved in claims made to UMHS. Number of new claims for compensation, number of claims compensated, time to claim resolution, and claims-related costs. After full implementation of a disclosure-with-offer program, the average monthly rate of new claims decreased from 7.03 to 4.52 per 100,000 patient encounters (rate ratio [RR], 0.64 [95% CI, 0.44 to 0.95]). The average monthly rate of lawsuits decreased from 2.13 to 0.75 per 100,000 patient encounters (RR, 0.35 [CI, 0.22 to 0.58]). Median time from claim reporting to resolution decreased from 1.36 to 0.95 years. Average monthly cost rates decreased for total liability (RR, 0.41 [CI, 0.26 to 0.66]), patient compensation (RR, 0.41 [CI, 0.26 to 0.67]), and non-compensation-related legal costs (RR, 0.39 [CI, 0.22 to 0.67]). The study design cannot establish causality. Malpractice claims generally declined in Michigan during the latter part of the study period. The findings might not apply to other health systems, given that UMHS has a closed staff model covered by a captive insurance company and often assumes legal responsibility. The UMHS implemented a program of full disclosure of medical errors with offers of compensation without increasing its total claims and liability costs. Blue Cross Blue Shield of Michigan Foundation.
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Cost effectiveness of the U.S. Geological Survey's stream-gaging program in Illinois
Mades, D.M.; Oberg, K.A.
1984-01-01
Data uses and funding sources were identified for 138 continuous-record discharge-gaging stations currently (1983) operated as part of the stream-gaging program in Illinois. Streamflow data from five of those stations are used only for regional hydrology studies. Most streamflow data are used for defining regional hydrology, defining rainfall-runoff relations, flood forecasting, regulating navigation systems, and water-quality sampling. Based on the evaluations of data use and of alternative methods for determining streamflow in place of stream gaging, no stations in the 1983 stream-gaging program should be deactivated. The current budget (in 1983 dollars) for operating the 138-station program is $768,000 per year. The average standard error of instantaneous discharge for the current practice for visiting the gaging stations is 36.5 percent. Missing stage record accounts for one-third of the 36.5 percent average standard error. (USGS)
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Drug Distribution. Part 1. Models to Predict Membrane Partitioning.
Nagar, Swati; Korzekwa, Ken
2017-03-01
Tissue partitioning is an important component of drug distribution and half-life. Protein binding and lipid partitioning together determine drug distribution. Two structure-based models to predict partitioning into microsomal membranes are presented. An orientation-based model was developed using a membrane template and atom-based relative free energy functions to select drug conformations and orientations for neutral and basic drugs. The resulting model predicts the correct membrane positions for nine compounds tested, and predicts the membrane partitioning for n = 67 drugs with an average fold-error of 2.4. Next, a more facile descriptor-based model was developed for acids, neutrals and bases. This model considers the partitioning of neutral and ionized species at equilibrium, and can predict membrane partitioning with an average fold-error of 2.0 (n = 92 drugs). Together these models suggest that drug orientation is important for membrane partitioning and that membrane partitioning can be well predicted from physicochemical properties.
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NASA Technical Reports Server (NTRS)
Hardy, E. E. (Principal Investigator); Skaley, J. E.; Dawson, C. P.; Weiner, G. D.; Phillips, E. S.; Fisher, R. A.
1975-01-01
The author has identified the following significant results. Three sites were evaluated for land use inventory: Finger Lakes - Tompkins County, Lower Hudson Valley - Newburgh, and Suffolk County - Long Island. Special photo enhancement processes were developed to standardize the density range and contrast among S190A negatives. Enhanced black and white enlargements were converted to color by contact printing onto diazo film. A color prediction model related the density values on each spectral band for each category of land use to the spectral properties of the various diazo dyes. The S190A multispectral system proved to be almost as effective as the S190B high resolution camera for inventorying land use. Aggregate error for Level 1 averaged about 12% while Level 2 aggregate error averaged about 25%. The S190A system proved to be much superior to LANDSAT in inventorying land use, primarily because of increased resolution.
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A Lagrangian stochastic model for aerial spray transport above an oak forest
Wang, Yansen; Miller, David R.; Anderson, Dean E.; McManus, Michael L.
1995-01-01
An aerial spray droplets' transport model has been developed by applying recent advances in Lagrangian stochastic simulation of heavy particles. A two-dimensional Lagrangian stochastic model was adopted to simulate the spray droplet dispersion in atmospheric turbulence by adjusting the Lagrangian integral time scale along the drop trajectory. The other major physical processes affecting the transport of spray droplets above a forest canopy, the aircraft wingtip vortices and the droplet evaporation, were also included in each time step of the droplets' transport.The model was evaluated using data from an aerial spray field experiment. In generally neutral stability conditions, the accuracy of the model predictions varied from run-to-run as expected. The average root-mean-square error was 24.61 IU cm−2, and the average relative error was 15%. The model prediction was adequate in two-dimensional steady wind conditions, but was less accurate in variable wind condition. The results indicated that the model can simulate successfully the ensemble; average transport of aerial spray droplets under neutral, steady atmospheric wind conditions.
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On the accuracy and precision of numerical waveforms: effect of waveform extraction methodology
NASA Astrophysics Data System (ADS)
Chu, Tony; Fong, Heather; Kumar, Prayush; Pfeiffer, Harald P.; Boyle, Michael; Hemberger, Daniel A.; Kidder, Lawrence E.; Scheel, Mark A.; Szilagyi, Bela
2016-08-01
We present a new set of 95 numerical relativity simulations of non-precessing binary black holes (BBHs). The simulations sample comprehensively both black-hole spins up to spin magnitude of 0.9, and cover mass ratios 1-3. The simulations cover on average 24 inspiral orbits, plus merger and ringdown, with low initial orbital eccentricities e\\lt {10}-4. A subset of the simulations extends the coverage of non-spinning BBHs up to mass ratio q = 10. Gravitational waveforms at asymptotic infinity are computed with two independent techniques: extrapolation and Cauchy characteristic extraction. An error analysis based on noise-weighted inner products is performed. We find that numerical truncation error, error due to gravitational wave extraction, and errors due to the Fourier transformation of signals with finite length of the numerical waveforms are of similar magnitude, with gravitational wave extraction errors dominating at noise-weighted mismatches of ˜ 3× {10}-4. This set of waveforms will serve to validate and improve aligned-spin waveform models for gravitational wave science.
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Kinetic modelling for zinc (II) ions biosorption onto Luffa cylindrica
DOE Office of Scientific and Technical Information (OSTI.GOV)
Oboh, I., E-mail: innocentoboh@uniuyo.edu.ng; Aluyor, E.; Audu, T.
The biosorption of Zinc (II) ions onto a biomaterial - Luffa cylindrica has been studied. This biomaterial was characterized by elemental analysis, surface area, pore size distribution, scanning electron microscopy, and the biomaterial before and after sorption, was characterized by Fourier Transform Infra Red (FTIR) spectrometer. The kinetic nonlinear models fitted were Pseudo-first order, Pseudo-second order and Intra-particle diffusion. A comparison of non-linear regression method in selecting the kinetic model was made. Four error functions, namely coefficient of determination (R{sup 2}), hybrid fractional error function (HYBRID), average relative error (ARE), and sum of the errors squared (ERRSQ), were used tomore » predict the parameters of the kinetic models. The strength of this study is that a biomaterial with wide distribution particularly in the tropical world and which occurs as waste material could be put into effective utilization as a biosorbent to address a crucial environmental problem.« less
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Kinetic modelling for zinc (II) ions biosorption onto Luffa cylindrica
NASA Astrophysics Data System (ADS)
Oboh, I.; Aluyor, E.; Audu, T.
2015-03-01
The biosorption of Zinc (II) ions onto a biomaterial - Luffa cylindrica has been studied. This biomaterial was characterized by elemental analysis, surface area, pore size distribution, scanning electron microscopy, and the biomaterial before and after sorption, was characterized by Fourier Transform Infra Red (FTIR) spectrometer. The kinetic nonlinear models fitted were Pseudo-first order, Pseudo-second order and Intra-particle diffusion. A comparison of non-linear regression method in selecting the kinetic model was made. Four error functions, namely coefficient of determination (R2), hybrid fractional error function (HYBRID), average relative error (ARE), and sum of the errors squared (ERRSQ), were used to predict the parameters of the kinetic models. The strength of this study is that a biomaterial with wide distribution particularly in the tropical world and which occurs as waste material could be put into effective utilization as a biosorbent to address a crucial environmental problem.
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On Time/Space Aggregation of Fine-Scale Error Estimates (Invited)
NASA Astrophysics Data System (ADS)
Huffman, G. J.
2013-12-01
Estimating errors inherent in fine time/space-scale satellite precipitation data sets is still an on-going problem and a key area of active research. Complicating features of these data sets include the intrinsic intermittency of the precipitation in space and time and the resulting highly skewed distribution of precipitation rates. Additional issues arise from the subsampling errors that satellites introduce, the errors due to retrieval algorithms, and the correlated error that retrieval and merger algorithms sometimes introduce. Several interesting approaches have been developed recently that appear to make progress on these long-standing issues. At the same time, the monthly averages over 2.5°x2.5° grid boxes in the Global Precipitation Climatology Project (GPCP) Satellite-Gauge (SG) precipitation data set follow a very simple sampling-based error model (Huffman 1997) with coefficients that are set using coincident surface and GPCP SG data. This presentation outlines the unsolved problem of how to aggregate the fine-scale errors (discussed above) to an arbitrary time/space averaging volume for practical use in applications, reducing in the limit to simple Gaussian expressions at the monthly 2.5°x2.5° scale. Scatter diagrams with different time/space averaging show that the relationship between the satellite and validation data improves due to the reduction in random error. One of the key, and highly non-linear, issues is that fine-scale estimates tend to have large numbers of cases with points near the axes on the scatter diagram (one of the values is exactly or nearly zero, while the other value is higher). Averaging 'pulls' the points away from the axes and towards the 1:1 line, which usually happens for higher precipitation rates before lower rates. Given this qualitative observation of how aggregation affects error, we observe that existing aggregation rules, such as the Steiner et al. (2003) power law, only depend on the aggregated precipitation rate. Is this sufficient, or is it necessary to aggregate the precipitation error estimates across the time/space data cube used for averaging? At least for small time/space data cubes it would seem that the detailed variables that affect each precipitation error estimate in the aggregation, such as sensor type, land/ocean surface type, convective/stratiform type, and so on, drive variations that must be accounted for explicitly.
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NASA Astrophysics Data System (ADS)
Wu, Kang-Hung; Su, Ching-Lun; Chu, Yen-Hsyang
2015-03-01
In this article, we use the International Reference Ionosphere (IRI) model to simulate temporal and spatial distributions of global E region electron densities retrieved by the FORMOSAT-3/COSMIC satellites by means of GPS radio occultation (RO) technique. Despite regional discrepancies in the magnitudes of the E region electron density, the IRI model simulations can, on the whole, describe the COSMIC measurements in quality and quantity. On the basis of global ionosonde network and the IRI model, the retrieval errors of the global COSMIC-measured E region peak electron density (NmE) from July 2006 to July 2011 are examined and simulated. The COSMIC measurement and the IRI model simulation both reveal that the magnitudes of the percentage error (PE) and root mean-square-error (RMSE) of the relative RO retrieval errors of the NmE values are dependent on local time (LT) and geomagnetic latitude, with minimum in the early morning and at high latitudes and maximum in the afternoon and at middle latitudes. In addition, the seasonal variation of PE and RMSE values seems to be latitude dependent. After removing the IRI model-simulated GPS RO retrieval errors from the original COSMIC measurements, the average values of the annual and monthly mean percentage errors of the RO retrieval errors of the COSMIC-measured E region electron density are, respectively, substantially reduced by a factor of about 2.95 and 3.35, and the corresponding root-mean-square errors show averaged decreases of 15.6% and 15.4%, respectively. It is found that, with this process, the largest reduction in the PE and RMSE of the COSMIC-measured NmE occurs at the equatorial anomaly latitudes 10°N-30°N in the afternoon from 14 to 18 LT, with a factor of 25 and 2, respectively. Statistics show that the residual errors that remained in the corrected COSMIC-measured NmE vary in a range of -20% to 38%, which are comparable to or larger than the percentage errors of the IRI-predicted NmE fluctuating in a range of -6.5% to 20%.
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Westbrook, Johanna I; Raban, Magdalena Z; Walter, Scott R; Douglas, Heather
2018-01-09
Interruptions and multitasking have been demonstrated in experimental studies to reduce individuals' task performance. These behaviours are frequently used by clinicians in high-workload, dynamic clinical environments, yet their effects have rarely been studied. To assess the relative contributions of interruptions and multitasking by emergency physicians to prescribing errors. 36 emergency physicians were shadowed over 120 hours. All tasks, interruptions and instances of multitasking were recorded. Physicians' working memory capacity (WMC) and preference for multitasking were assessed using the Operation Span Task (OSPAN) and Inventory of Polychronic Values. Following observation, physicians were asked about their sleep in the previous 24 hours. Prescribing errors were used as a measure of task performance. We performed multivariate analysis of prescribing error rates to determine associations with interruptions and multitasking, also considering physician seniority, age, psychometric measures, workload and sleep. Physicians experienced 7.9 interruptions/hour. 28 clinicians were observed prescribing 239 medication orders which contained 208 prescribing errors. While prescribing, clinicians were interrupted 9.4 times/hour. Error rates increased significantly if physicians were interrupted (rate ratio (RR) 2.82; 95% CI 1.23 to 6.49) or multitasked (RR 1.86; 95% CI 1.35 to 2.56) while prescribing. Having below-average sleep showed a >15-fold increase in clinical error rate (RR 16.44; 95% CI 4.84 to 55.81). WMC was protective against errors; for every 10-point increase on the 75-point OSPAN, a 19% decrease in prescribing errors was observed. There was no effect of polychronicity, workload, physician gender or above-average sleep on error rates. Interruptions, multitasking and poor sleep were associated with significantly increased rates of prescribing errors among emergency physicians. WMC mitigated the negative influence of these factors to an extent. These results confirm experimental findings in other fields and raise questions about the acceptability of the high rates of multitasking and interruption in clinical environments. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
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Jin, Mengtong; Sun, Wenshuo; Li, Qin; Sun, Xiaohong; Pan, Yingjie; Zhao, Yong
2014-04-04
We evaluated the difference of three standard curves in quantifying viable Vibrio parahaemolyticus in samples by real-time reverse-transcriptase PCR (Real-time RT-PCR). The standard curve A was established by 10-fold diluted cDNA. The cDNA was reverse transcripted after RNA synthesized in vitro. The standard curve B and C were established by 10-fold diluted cDNA. The cDNA was synthesized after RNA isolated from Vibrio parahaemolyticus in pure cultures (10(8) CFU/mL) and shrimp samples (10(6) CFU/g) (Standard curve A and C were proposed for the first time). Three standard curves were performed to quantitatively detect V. parahaemolyticus in six samples, respectively (Two pure cultured V. parahaemolyticus samples, two artificially contaminated cooked Litopenaeus vannamei samples and two artificially contaminated Litopenaeus vannamei samples). Then we evaluated the quantitative results of standard curve and the plate counting results and then analysed the differences. The three standard curves all show a strong linear relationship between the fractional cycle number and V. parahaemolyticus concentration (R2 > 0.99); The quantitative results of Real-time PCR were significantly (p < 0.05) lower than the results of plate counting. The relative errors compared with the results of plate counting ranked standard curve A (30.0%) > standard curve C (18.8%) > standard curve B (6.9%); The average differences between standard curve A and standard curve B and C were - 2.25 Lg CFU/mL and - 0.75 Lg CFU/mL, respectively, and the mean relative errors were 48.2% and 15.9%, respectively; The average difference between standard curve B and C was among (1.47 -1.53) Lg CFU/mL and the average relative errors were among 19.0% - 23.8%. Standard curve B could be applied to Real-time RT-PCR when quantify the number of viable microorganisms in samples.
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High Accuracy Acoustic Relative Humidity Measurement in Duct Flow with Air
van Schaik, Wilhelm; Grooten, Mart; Wernaart, Twan; van der Geld, Cees
2010-01-01
An acoustic relative humidity sensor for air-steam mixtures in duct flow is designed and tested. Theory, construction, calibration, considerations on dynamic response and results are presented. The measurement device is capable of measuring line averaged values of gas velocity, temperature and relative humidity (RH) instantaneously, by applying two ultrasonic transducers and an array of four temperature sensors. Measurement ranges are: gas velocity of 0–12 m/s with an error of ±0.13 m/s, temperature 0–100 °C with an error of ±0.07 °C and relative humidity 0–100% with accuracy better than 2 % RH above 50 °C. Main advantage over conventional humidity sensors is the high sensitivity at high RH at temperatures exceeding 50 °C, with accuracy increasing with increasing temperature. The sensors are non-intrusive and resist highly humid environments. PMID:22163610
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High accuracy acoustic relative humidity measurement in duct flow with air.
van Schaik, Wilhelm; Grooten, Mart; Wernaart, Twan; van der Geld, Cees
2010-01-01
An acoustic relative humidity sensor for air-steam mixtures in duct flow is designed and tested. Theory, construction, calibration, considerations on dynamic response and results are presented. The measurement device is capable of measuring line averaged values of gas velocity, temperature and relative humidity (RH) instantaneously, by applying two ultrasonic transducers and an array of four temperature sensors. Measurement ranges are: gas velocity of 0-12 m/s with an error of ± 0.13 m/s, temperature 0-100 °C with an error of ± 0.07 °C and relative humidity 0-100% with accuracy better than 2 % RH above 50 °C. Main advantage over conventional humidity sensors is the high sensitivity at high RH at temperatures exceeding 50 °C, with accuracy increasing with increasing temperature. The sensors are non-intrusive and resist highly humid environments.
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Estimating Climatological Bias Errors for the Global Precipitation Climatology Project (GPCP)
NASA Technical Reports Server (NTRS)
Adler, Robert; Gu, Guojun; Huffman, George
2012-01-01
A procedure is described to estimate bias errors for mean precipitation by using multiple estimates from different algorithms, satellite sources, and merged products. The Global Precipitation Climatology Project (GPCP) monthly product is used as a base precipitation estimate, with other input products included when they are within +/- 50% of the GPCP estimates on a zonal-mean basis (ocean and land separately). The standard deviation s of the included products is then taken to be the estimated systematic, or bias, error. The results allow one to examine monthly climatologies and the annual climatology, producing maps of estimated bias errors, zonal-mean errors, and estimated errors over large areas such as ocean and land for both the tropics and the globe. For ocean areas, where there is the largest question as to absolute magnitude of precipitation, the analysis shows spatial variations in the estimated bias errors, indicating areas where one should have more or less confidence in the mean precipitation estimates. In the tropics, relative bias error estimates (s/m, where m is the mean precipitation) over the eastern Pacific Ocean are as large as 20%, as compared with 10%-15% in the western Pacific part of the ITCZ. An examination of latitudinal differences over ocean clearly shows an increase in estimated bias error at higher latitudes, reaching up to 50%. Over land, the error estimates also locate regions of potential problems in the tropics and larger cold-season errors at high latitudes that are due to snow. An empirical technique to area average the gridded errors (s) is described that allows one to make error estimates for arbitrary areas and for the tropics and the globe (land and ocean separately, and combined). Over the tropics this calculation leads to a relative error estimate for tropical land and ocean combined of 7%, which is considered to be an upper bound because of the lack of sign-of-the-error canceling when integrating over different areas with a different number of input products. For the globe the calculated relative error estimate from this study is about 9%, which is also probably a slight overestimate. These tropical and global estimated bias errors provide one estimate of the current state of knowledge of the planet's mean precipitation.
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Gildersleeve-Neumann, Christina E; Kester, Ellen S; Davis, Barbara L; Peña, Elizabeth D
2008-07-01
English speech acquisition by typically developing 3- to 4-year-old children with monolingual English was compared to English speech acquisition by typically developing 3- to 4-year-old children with bilingual English-Spanish backgrounds. We predicted that exposure to Spanish would not affect the English phonetic inventory but would increase error frequency and type in bilingual children. Single-word speech samples were collected from 33 children. Phonetically transcribed samples for the 3 groups (monolingual English children, English-Spanish bilingual children who were predominantly exposed to English, and English-Spanish bilingual children with relatively equal exposure to English and Spanish) were compared at 2 time points and for change over time for phonetic inventory, phoneme accuracy, and error pattern frequencies. Children demonstrated similar phonetic inventories. Some bilingual children produced Spanish phonemes in their English and produced few consonant cluster sequences. Bilingual children with relatively equal exposure to English and Spanish averaged more errors than did bilingual children who were predominantly exposed to English. Both bilingual groups showed higher error rates than English-only children overall, particularly for syllable-level error patterns. All language groups decreased in some error patterns, although the ones that decreased were not always the same across language groups. Some group differences of error patterns and accuracy were significant. Vowel error rates did not differ by language group. Exposure to English and Spanish may result in a higher English error rate in typically developing bilinguals, including the application of Spanish phonological properties to English. Slightly higher error rates are likely typical for bilingual preschool-aged children. Change over time at these time points for all 3 groups was similar, suggesting that all will reach an adult-like system in English with exposure and practice.
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Misagh, Pegah; Vazin, Afsaneh; Namazi, Soha
2018-01-01
This study was aimed at finding the occurrence rate of prescription errors in the outpatients› prescriptions written by faculty and non-faculty physicians practicing in Shiraz, Iran. In this cross-sectional study 2000 outpatient prescriptions were randomly collected from pharmacies affiliated with Shiraz University of Medical Sciences (SUMS) and social security insurance in Shiraz, Iran. Patient information including age, weight, diagnosis and chief complain were recorded. Physicians ‘characteristics were extracted from prescriptions. Prescription errors including errors in spelling, instruction, strength, dosage form and quantity as well as drug-drug interactions and contraindications were identified. The mean ± SD age of patients was 37.91 ± 21.10 years. Most of the patients were male (77.15%) and 81.50% of patients were adults. The average total number of drugs per prescription was 3.19 ± 1.60. The mean ± SD of prescription errors was 7.38 ± 4.06. Spelling error (26.4%), instruction error (21.03%), and strength error (19.18%) were the most frequent prescription errors. The mean ± SD of prescription errors was 7.83 ± 4.2 and 6.93 ± 3.88 in non-faculty and faculty physicians, respectively (P < 0.05). Number of prescription errors increased significantly as the number of prescribed drugs increased. All prescriptions had at least one error. The rate of prescription errors was higher in non-faculty physicians. Number of prescription errors related with the prescribed drugs in the prescription.
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Multi-Site λ-dynamics for simulated Structure-Activity Relationship studies
Knight, Jennifer L.; Brooks, Charles L.
2011-01-01
Multi-Site λ-dynamics (MSλD) is a new free energy simulation method that is based on λ-dynamics. It has been developed to enable multiple substituents at multiple sites on a common ligand core to be modeled simultaneously and their free energies assessed. The efficacy of MSλD for estimating relative hydration free energies and relative binding affinties is demonstrated using three test systems. Model compounds representing multiple identical benzene, dihydroxybenzene and dimethoxybenzene molecules show total combined MSλD trajectory lengths of ~1.5 ns are sufficient to reliably achieve relative hydration free energy estimates within 0.2 kcal/mol and are less sensitive to the number of trajectories that are used to generate these estimates for hybrid ligands that contain up to ten substituents modeled at a single site or five substituents modeled at each of two sites. Relative hydration free energies among six benzene derivatives calculated from MSλD simulations are in very good agreement with those from alchemical free energy simulations (with average unsigned differences of 0.23 kcal/mol and R2=0.991) and experiment (with average unsigned errors of 1.8 kcal/mol and R2=0.959). Estimates of the relative binding affinities among 14 inhibitors of HIV-1 reverse transcriptase obtained from MSλD simulations are in reasonable agreement with those from traditional free energy simulations and experiment (average unsigned errors of 0.9 kcal/mol and R2=0.402). For the same level of accuracy and precision MSλD simulations are achieved ~20–50 times faster than traditional free energy simulations and thus with reliable force field parameters can be used effectively to screen tens to hundreds of compounds in structure-based drug design applications. PMID:22125476
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NASA Astrophysics Data System (ADS)
Yang, Yanqiu; Yu, Lin; Zhang, Yixin
2017-04-01
A model of the average capacity of optical wireless communication link with pointing errors for the ground-to-train of the curved track is established based on the non-Kolmogorov. By adopting the gamma-gamma distribution model, we derive the average capacity expression for this channel. The numerical analysis reveals that heavier fog reduces the average capacity of link. The strength of atmospheric turbulence, the variance of pointing errors, and the covered track length need to be reduced for the larger average capacity of link. The normalized beamwidth and the average signal-to-noise ratio (SNR) of the turbulence-free link need to be increased. We can increase the transmit aperture to expand the beamwidth and enhance the signal intensity, thereby decreasing the impact of the beam wander accordingly. As the system adopting the automatic tracking of beam at the receiver positioned on the roof of the train, for eliminating the pointing errors caused by beam wander and train vibration, the equivalent average capacity of the channel will achieve a maximum value. The impact of the non-Kolmogorov spectral index's variation on the average capacity of link can be ignored.
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Measurements of stem diameter: implications for individual- and stand-level errors.
Paul, Keryn I; Larmour, John S; Roxburgh, Stephen H; England, Jacqueline R; Davies, Micah J; Luck, Hamish D
2017-08-01
Stem diameter is one of the most common measurements made to assess the growth of woody vegetation, and the commercial and environmental benefits that it provides (e.g. wood or biomass products, carbon sequestration, landscape remediation). Yet inconsistency in its measurement is a continuing source of error in estimates of stand-scale measures such as basal area, biomass, and volume. Here we assessed errors in stem diameter measurement through repeated measurements of individual trees and shrubs of varying size and form (i.e. single- and multi-stemmed) across a range of contrasting stands, from complex mixed-species plantings to commercial single-species plantations. We compared a standard diameter tape with a Stepped Diameter Gauge (SDG) for time efficiency and measurement error. Measurement errors in diameter were slightly (but significantly) influenced by size and form of the tree or shrub, and stem height at which the measurement was made. Compared to standard tape measurement, the mean systematic error with SDG measurement was only -0.17 cm, but varied between -0.10 and -0.52 cm. Similarly, random error was relatively large, with standard deviations (and percentage coefficients of variation) averaging only 0.36 cm (and 3.8%), but varying between 0.14 and 0.61 cm (and 1.9 and 7.1%). However, at the stand scale, sampling errors (i.e. how well individual trees or shrubs selected for measurement of diameter represented the true stand population in terms of the average and distribution of diameter) generally had at least a tenfold greater influence on random errors in basal area estimates than errors in diameter measurements. This supports the use of diameter measurement tools that have high efficiency, such as the SDG. Use of the SDG almost halved the time required for measurements compared to the diameter tape. Based on these findings, recommendations include the following: (i) use of a tape to maximise accuracy when developing allometric models, or when monitoring relatively small changes in permanent sample plots (e.g. National Forest Inventories), noting that care is required in irregular-shaped, large-single-stemmed individuals, and (ii) use of a SDG to maximise efficiency when using inventory methods to assess basal area, and hence biomass or wood volume, at the stand scale (i.e. in studies of impacts of management or site quality) where there are budgetary constraints, noting the importance of sufficient sample sizes to ensure that the population sampled represents the true population.
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A novel method for 3D measurement of RFID multi-tag network based on matching vision and wavelet
NASA Astrophysics Data System (ADS)
Zhuang, Xiao; Yu, Xiaolei; Zhao, Zhimin; Wang, Donghua; Zhang, Wenjie; Liu, Zhenlu; Lu, Dongsheng; Dong, Dingbang
2018-07-01
In the field of radio frequency identification (RFID), the three-dimensional (3D) distribution of RFID multi-tag networks has a significant impact on their reading performance. At the same time, in order to realize the anti-collision of RFID multi-tag networks in practical engineering applications, the 3D distribution of RFID multi-tag networks must be measured. In this paper, a novel method for the 3D measurement of RFID multi-tag networks is proposed. A dual-CCD system (vertical and horizontal cameras) is used to obtain images of RFID multi-tag networks from different angles. Then, the wavelet threshold denoising method is used to remove noise in the obtained images. The template matching method is used to determine the two-dimensional coordinates and vertical coordinate of each tag. The 3D coordinates of each tag are obtained subsequently. Finally, a model of the nonlinear relation between the 3D coordinate distribution of the RFID multi-tag network and the corresponding reading distance is established using the wavelet neural network. The experiment results show that the average prediction relative error is 0.71% and the time cost is 2.17 s. The values of the average prediction relative error and time cost are smaller than those of the particle swarm optimization neural network and genetic algorithm–back propagation neural network. The time cost of the wavelet neural network is about 1% of that of the other two methods. The method proposed in this paper has a smaller relative error. The proposed method can improve the real-time performance of RFID multi-tag networks and the overall dynamic performance of multi-tag networks.
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Interobserver error involved in independent attempts to measure cusp base areas of Pan M1s
Bailey, Shara E; Pilbrow, Varsha C; Wood, Bernard A
2004-01-01
Cusp base areas measured from digitized images increase the amount of detailed quantitative information one can collect from post-canine crown morphology. Although this method is gaining wide usage for taxonomic analyses of extant and extinct hominoids, the techniques for digitizing images and taking measurements differ between researchers. The aim of this study was to investigate interobserver error in order to help assess the reliability of cusp base area measurement within extant and extinct hominoid taxa. Two of the authors measured individual cusp base areas and total cusp base area of 23 maxillary first molars (M1) of Pan. From these, relative cusp base areas were calculated. No statistically significant interobserver differences were found for either absolute or relative cusp base areas. On average the hypocone and paracone showed the least interobserver error (< 1%) whereas the protocone and metacone showed the most (2.6–4.5%). We suggest that the larger measurement error in the metacone/protocone is due primarily to either weakly defined fissure patterns and/or the presence of accessory occlusal features. Overall, levels of interobserver error are similar to those found for intraobserver error. The results of our study suggest that if certain prescribed standards are employed then cusp and crown base areas measured by different individuals can be pooled into a single database. PMID:15447691
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NASA Astrophysics Data System (ADS)
Baldwin, A. T.; Watkins, L. L.; van der Marel, R. P.; Bianchini, P.; Bellini, A.; Anderson, J.
2016-08-01
We make use of the Hubble Space Telescope proper-motion catalogs derived by Bellini et al. to produce the first radial velocity dispersion profiles σ (R) for blue straggler stars (BSSs) in Galactic globular clusters (GCs), as well as the first dynamical estimates for the average mass of the entire BSS population. We show that BSSs typically have lower velocity dispersions than stars with mass equal to the main-sequence turnoff mass, as one would expect for a more massive population of stars. Since GCs are expected to experience some degree of energy equipartition, we use the relation σ \\propto {M}-η , where η is related to the degree of energy equipartition, along with our velocity dispersion profiles to estimate BSS masses. We estimate η as a function of cluster relaxation from recent Monte Carlo cluster simulations by Bianchini et al. and then derive an average mass ratio {M}{BSS}/{M}{MSTO}=1.50+/- 0.14 and an average mass {M}{BSS}=1.22+/- 0.12 M ⊙ from 598 BSSs across 19 GCs. The final error bars include any systematic errors that are random between different clusters, but not any potential biases inherent to our methodology. Our results are in good agreement with the average mass of {M}{BSS}=1.22+/- 0.06 M ⊙ for the 35 BSSs in Galactic GCs in the literature with properties that have allowed individual mass determination. Based on proprietary and archival observations with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by AURA, Inc., under NASA contract NAS 5-26555.
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Total ozone trend significance from space time variability of daily Dobson data
NASA Technical Reports Server (NTRS)
Wilcox, R. W.
1981-01-01
Estimates of standard errors of total ozone time and area means, as derived from ozone's natural temporal and spatial variability and autocorrelation in middle latitudes determined from daily Dobson data are presented. Assessing the significance of apparent total ozone trends is equivalent to assessing the standard error of the means. Standard errors of time averages depend on the temporal variability and correlation of the averaged parameter. Trend detectability is discussed, both for the present network and for satellite measurements.
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The calculation of average error probability in a digital fibre optical communication system
NASA Astrophysics Data System (ADS)
Rugemalira, R. A. M.
1980-03-01
This paper deals with the problem of determining the average error probability in a digital fibre optical communication system, in the presence of message dependent inhomogeneous non-stationary shot noise, additive Gaussian noise and intersymbol interference. A zero-forcing equalization receiver filter is considered. Three techniques for error rate evaluation are compared. The Chernoff bound and the Gram-Charlier series expansion methods are compared to the characteristic function technique. The latter predicts a higher receiver sensitivity
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Evaluation of causes and frequency of medication errors during information technology downtime.
Hanuscak, Tara L; Szeinbach, Sheryl L; Seoane-Vazquez, Enrique; Reichert, Brendan J; McCluskey, Charles F
2009-06-15
The causes and frequency of medication errors occurring during information technology downtime were evaluated. Individuals from a convenience sample of 78 hospitals who were directly responsible for supporting and maintaining clinical information systems (CISs) and automated dispensing systems (ADSs) were surveyed using an online tool between February 2007 and May 2007 to determine if medication errors were reported during periods of system downtime. The errors were classified using the National Coordinating Council for Medication Error Reporting and Prevention severity scoring index. The percentage of respondents reporting downtime was estimated. Of the 78 eligible hospitals, 32 respondents with CIS and ADS responsibilities completed the online survey for a response rate of 41%. For computerized prescriber order entry, patch installations and system upgrades caused an average downtime of 57% over a 12-month period. Lost interface and interface malfunction were reported for centralized and decentralized ADSs, with an average downtime response of 34% and 29%, respectively. The average downtime response was 31% for software malfunctions linked to clinical decision-support systems. Although patient harm did not result from 30 (54%) medication errors, the potential for harm was present for 9 (16%) of these errors. Medication errors occurred during CIS and ADS downtime despite the availability of backup systems and standard protocols to handle periods of system downtime. Efforts should be directed to reduce the frequency and length of down-time in order to minimize medication errors during such downtime.
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“So Big”: The Development of Body Self-awareness in Toddlers
Brownell, Celia A.; Zerwas, Stephanie; Ramani, Geetha B.
2012-01-01
Early development of body self-awareness was examined in 57 children at 18, 22, or 26 months of age, using tasks designed to require objective representation of one’s own body. All children made at least one body representation error, with approximately 2.5 errors per task on average. Errors declined with age. Children’s performance on comparison tasks that required them to reason about the relative size of objects and about objects as obstacles, without considering their own bodies, was unrelated to performance on the body awareness tasks. Thus, the ability to represent and reflect on one’s own body explicitly and objectively may be a unique dimension of early development, a distinct component of objective self-awareness which emerges in this age period. PMID:17883440
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Method to manage integration error in the Green-Kubo method.
Oliveira, Laura de Sousa; Greaney, P Alex
2017-02-01
The Green-Kubo method is a commonly used approach for predicting transport properties in a system from equilibrium molecular dynamics simulations. The approach is founded on the fluctuation dissipation theorem and relates the property of interest to the lifetime of fluctuations in its thermodynamic driving potential. For heat transport, the lattice thermal conductivity is related to the integral of the autocorrelation of the instantaneous heat flux. A principal source of error in these calculations is that the autocorrelation function requires a long averaging time to reduce remnant noise. Integrating the noise in the tail of the autocorrelation function becomes conflated with physically important slow relaxation processes. In this paper we present a method to quantify the uncertainty on transport properties computed using the Green-Kubo formulation based on recognizing that the integrated noise is a random walk, with a growing envelope of uncertainty. By characterizing the noise we can choose integration conditions to best trade off systematic truncation error with unbiased integration noise, to minimize uncertainty for a given allocation of computational resources.
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Method to manage integration error in the Green-Kubo method
NASA Astrophysics Data System (ADS)
Oliveira, Laura de Sousa; Greaney, P. Alex
2017-02-01
The Green-Kubo method is a commonly used approach for predicting transport properties in a system from equilibrium molecular dynamics simulations. The approach is founded on the fluctuation dissipation theorem and relates the property of interest to the lifetime of fluctuations in its thermodynamic driving potential. For heat transport, the lattice thermal conductivity is related to the integral of the autocorrelation of the instantaneous heat flux. A principal source of error in these calculations is that the autocorrelation function requires a long averaging time to reduce remnant noise. Integrating the noise in the tail of the autocorrelation function becomes conflated with physically important slow relaxation processes. In this paper we present a method to quantify the uncertainty on transport properties computed using the Green-Kubo formulation based on recognizing that the integrated noise is a random walk, with a growing envelope of uncertainty. By characterizing the noise we can choose integration conditions to best trade off systematic truncation error with unbiased integration noise, to minimize uncertainty for a given allocation of computational resources.
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Analysis of a Shock-Associated Noise Prediction Model Using Measured Jet Far-Field Noise Data
NASA Technical Reports Server (NTRS)
Dahl, Milo D.; Sharpe, Jacob A.
2014-01-01
A code for predicting supersonic jet broadband shock-associated noise was assessed using a database containing noise measurements of a jet issuing from a convergent nozzle. The jet was operated at 24 conditions covering six fully expanded Mach numbers with four total temperature ratios. To enable comparisons of the predicted shock-associated noise component spectra with data, the measured total jet noise spectra were separated into mixing noise and shock-associated noise component spectra. Comparisons between predicted and measured shock-associated noise component spectra were used to identify deficiencies in the prediction model. Proposed revisions to the model, based on a study of the overall sound pressure levels for the shock-associated noise component of the measured data, a sensitivity analysis of the model parameters with emphasis on the definition of the convection velocity parameter, and a least-squares fit of the predicted to the measured shock-associated noise component spectra, resulted in a new definition for the source strength spectrum in the model. An error analysis showed that the average error in the predicted spectra was reduced by as much as 3.5 dB for the revised model relative to the average error for the original model.
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Cost-effectiveness of the stream-gaging program in New Jersey
Schopp, R.D.; Ulery, R.L.
1984-01-01
The results of a study of the cost-effectiveness of the stream-gaging program in New Jersey are documented. This study is part of a 5-year nationwide analysis undertaken by the U.S. Geological Survey to define and document the most cost-effective means of furnishing streamflow information. This report identifies the principal uses of the data and relates those uses to funding sources, applies, at selected stations, alternative less costly methods (that is flow routing, regression analysis) for furnishing the data, and defines a strategy for operating the program which minimizes uncertainty in the streamflow data for specific operating budgets. Uncertainty in streamflow data is primarily a function of the percentage of missing record and the frequency of discharge measurements. In this report, 101 continuous stream gages and 73 crest-stage or stage-only gages are analyzed. A minimum budget of $548,000 is required to operate the present stream-gaging program in New Jersey with an average standard error of 27.6 percent. The maximum budget analyzed was $650,000, which resulted in an average standard error of 17.8 percent. The 1983 budget of $569,000 resulted in a standard error of 24.9 percent under present operating policy. (USGS)
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An Improved Computational Method for the Calculation of Mixture Liquid-Vapor Critical Points
NASA Astrophysics Data System (ADS)
Dimitrakopoulos, Panagiotis; Jia, Wenlong; Li, Changjun
2014-05-01
Knowledge of critical points is important to determine the phase behavior of a mixture. This work proposes a reliable and accurate method in order to locate the liquid-vapor critical point of a given mixture. The theoretical model is developed from the rigorous definition of critical points, based on the SRK equation of state (SRK EoS) or alternatively, on the PR EoS. In order to solve the resulting system of nonlinear equations, an improved method is introduced into an existing Newton-Raphson algorithm, which can calculate all the variables simultaneously in each iteration step. The improvements mainly focus on the derivatives of the Jacobian matrix, on the convergence criteria, and on the damping coefficient. As a result, all equations and related conditions required for the computation of the scheme are illustrated in this paper. Finally, experimental data for the critical points of 44 mixtures are adopted in order to validate the method. For the SRK EoS, average absolute errors of the predicted critical-pressure and critical-temperature values are 123.82 kPa and 3.11 K, respectively, whereas the commercial software package Calsep PVTSIM's prediction errors are 131.02 kPa and 3.24 K. For the PR EoS, the two above mentioned average absolute errors are 129.32 kPa and 2.45 K, while the PVTSIM's errors are 137.24 kPa and 2.55 K, respectively.
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Comparison of Highly Resolved Model-Based Exposure ...
Human exposure to air pollution in many studies is represented by ambient concentrations from space-time kriging of observed values. Space-time kriging techniques based on a limited number of ambient monitors may fail to capture the concentration from local sources. Further, because people spend more time indoors, using ambient concentration to represent exposure may cause error. To quantify the associated exposure error, we computed a series of six different hourly-based exposure metrics at 16,095 Census blocks of three Counties in North Carolina for CO, NOx, PM2.5, and elemental carbon (EC) during 2012. These metrics include ambient background concentration from space-time ordinary kriging (STOK), ambient on-road concentration from the Research LINE source dispersion model (R-LINE), a hybrid concentration combining STOK and R-LINE, and their associated indoor concentrations from an indoor infiltration mass balance model. Using a hybrid-based indoor concentration as the standard, the comparison showed that outdoor STOK metrics yielded large error at both population (67% to 93%) and individual level (average bias between −10% to 95%). For pollutants with significant contribution from on-road emission (EC and NOx), the on-road based indoor metric performs the best at the population level (error less than 52%). At the individual level, however, the STOK-based indoor concentration performs the best (average bias below 30%). For PM2.5, due to the relatively low co
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Error Reduction Methods for Integrated-path Differential-absorption Lidar Measurements
NASA Technical Reports Server (NTRS)
Chen, Jeffrey R.; Numata, Kenji; Wu, Stewart T.
2012-01-01
We report new modeling and error reduction methods for differential-absorption optical-depth (DAOD) measurements of atmospheric constituents using direct-detection integrated-path differential-absorption lidars. Errors from laser frequency noise are quantified in terms of the line center fluctuation and spectral line shape of the laser pulses, revealing relationships verified experimentally. A significant DAOD bias is removed by introducing a correction factor. Errors from surface height and reflectance variations can be reduced to tolerable levels by incorporating altimetry knowledge and "log after averaging", or by pointing the laser and receiver to a fixed surface spot during each wavelength cycle to shorten the time of "averaging before log".
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NASA Astrophysics Data System (ADS)
Bacha, Tulu
The Goddard Lidar Observatory for Wind (GLOW), a mobile direct detection Doppler LIDAR based on molecular backscattering for measurement of wind in the troposphere and lower stratosphere region of atmosphere is operated and its errors characterized. It was operated at Howard University Beltsville Center for Climate Observation System (BCCOS) side by side with other operating instruments: the NASA/Langely Research Center Validation Lidar (VALIDAR), Leosphere WLS70, and other standard wind sensing instruments. The performance of Goddard Lidar Observatory for Wind (GLOW) is presented for various optical thicknesses of cloud conditions. It was also compared to VALIDAR under various conditions. These conditions include clear and cloudy sky regions. The performance degradation due to the presence of cirrus clouds is quantified by comparing the wind speed error to cloud thickness. The cloud thickness is quantified in terms of aerosol backscatter ratio (ASR) and cloud optical depth (COD). ASR and COD are determined from Howard University Raman Lidar (HURL) operating at the same station as GLOW. The wind speed error of GLOW was correlated with COD and aerosol backscatter ratio (ASR) which are determined from HURL data. The correlation related in a weak linear relationship. Finally, the wind speed measurements of GLOW were corrected using the quantitative relation from the correlation relations. Using ASR reduced the GLOW wind error from 19% to 8% in a thin cirrus cloud and from 58% to 28% in a relatively thick cloud. After correcting for cloud induced error, the remaining error is due to shot noise and atmospheric variability. Shot-noise error is the statistical random error of backscattered photons detected by photon multiplier tube (PMT) can only be minimized by averaging large number of data recorded. The atmospheric backscatter measured by GLOW along its line-of-sight direction is also used to analyze error due to atmospheric variability within the volume of measurement. GLOW scans in five different directions (vertical and at elevation angles of 45° in north, south, east, and west) to generate wind profiles. The non-uniformity of the atmosphere in all scanning directions is a factor contributing to the measurement error of GLOW. The atmospheric variability in the scanning region leads to difference in the intensity of backscattered signals for scanning directions. Taking the ratio of the north (east) to south (west) and comparing the statistical differences lead to a weak linear relation between atmospheric variability and line-of-sights wind speed differences. This relation was used to make correction which reduced by about 50%.
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Bankfull characteristics of Ohio streams and their relation to peak streamflows
Sherwood, James M.; Huitger, Carrie A.
2005-01-01
Regional curves, simple-regression equations, and multiple-regression equations were developed to estimate bankfull width, bankfull mean depth, bankfull cross-sectional area, and bankfull discharge of rural, unregulated streams in Ohio. The methods are based on geomorphic, basin, and flood-frequency data collected at 50 study sites on unregulated natural alluvial streams in Ohio, of which 40 sites are near streamflow-gaging stations. The regional curves and simple-regression equations relate the bankfull characteristics to drainage area. The multiple-regression equations relate the bankfull characteristics to drainage area, main-channel slope, main-channel elevation index, median bed-material particle size, bankfull cross-sectional area, and local-channel slope. Average standard errors of prediction for bankfull width equations range from 20.6 to 24.8 percent; for bankfull mean depth, 18.8 to 20.6 percent; for bankfull cross-sectional area, 25.4 to 30.6 percent; and for bankfull discharge, 27.0 to 78.7 percent. The simple-regression (drainage-area only) equations have the highest average standard errors of prediction. The multiple-regression equations in which the explanatory variables included drainage area, main-channel slope, main-channel elevation index, median bed-material particle size, bankfull cross-sectional area, and local-channel slope have the lowest average standard errors of prediction. Field surveys were done at each of the 50 study sites to collect the geomorphic data. Bankfull indicators were identified and evaluated, cross-section and longitudinal profiles were surveyed, and bed- and bank-material were sampled. Field data were analyzed to determine various geomorphic characteristics such as bankfull width, bankfull mean depth, bankfull cross-sectional area, bankfull discharge, streambed slope, and bed- and bank-material particle-size distribution. The various geomorphic characteristics were analyzed by means of a combination of graphical and statistical techniques. The logarithms of the annual peak discharges for the 40 gaged study sites were fit by a Pearson Type III frequency distribution to develop flood-peak discharges associated with recurrence intervals of 2, 5, 10, 25, 50, and 100 years. The peak-frequency data were related to geomorphic, basin, and climatic variables by multiple-regression analysis. Simple-regression equations were developed to estimate 2-, 5-, 10-, 25-, 50-, and 100-year flood-peak discharges of rural, unregulated streams in Ohio from bankfull channel cross-sectional area. The average standard errors of prediction are 31.6, 32.6, 35.9, 41.5, 46.2, and 51.2 percent, respectively. The study and methods developed are intended to improve understanding of the relations between geomorphic, basin, and flood characteristics of streams in Ohio and to aid in the design of hydraulic structures, such as culverts and bridges, where stability of the stream and structure is an important element of the design criteria. The study was done in cooperation with the Ohio Department of Transportation and the U.S. Department of Transportation, Federal Highway Administration.
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Do stochastic inhomogeneities affect dark-energy precision measurements?
Ben-Dayan, I; Gasperini, M; Marozzi, G; Nugier, F; Veneziano, G
2013-01-11
The effect of a stochastic background of cosmological perturbations on the luminosity-redshift relation is computed to second order through a recently proposed covariant and gauge-invariant light-cone averaging procedure. The resulting expressions are free from both ultraviolet and infrared divergences, implying that such perturbations cannot mimic a sizable fraction of dark energy. Different averages are estimated and depend on the particular function of the luminosity distance being averaged. The energy flux being minimally affected by perturbations at large z is proposed as the best choice for precision estimates of dark-energy parameters. Nonetheless, its irreducible (stochastic) variance induces statistical errors on Ω(Λ)(z) typically lying in the few-percent range.
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Atmospheric mold spore counts in relation to meteorological parameters
NASA Astrophysics Data System (ADS)
Katial, R. K.; Zhang, Yiming; Jones, Richard H.; Dyer, Philip D.
Fungal spore counts of Cladosporium, Alternaria, and Epicoccum were studied during 8 years in Denver, Colorado. Fungal spore counts were obtained daily during the pollinating season by a Rotorod sampler. Weather data were obtained from the National Climatic Data Center. Daily averages of temperature, relative humidity, daily precipitation, barometric pressure, and wind speed were studied. A time series analysis was performed on the data to mathematically model the spore counts in relation to weather parameters. Using SAS PROC ARIMA software, a regression analysis was performed, regressing the spore counts on the weather variables assuming an autoregressive moving average (ARMA) error structure. Cladosporium was found to be positively correlated (P<0.02) with average daily temperature, relative humidity, and negatively correlated with precipitation. Alternaria and Epicoccum did not show increased predictability with weather variables. A mathematical model was derived for Cladosporium spore counts using the annual seasonal cycle and significant weather variables. The model for Alternaria and Epicoccum incorporated the annual seasonal cycle. Fungal spore counts can be modeled by time series analysis and related to meteorological parameters controlling for seasonallity; this modeling can provide estimates of exposure to fungal aeroallergens.
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Cawyer, Chase R; Anderson, Sarah B; Szychowski, Jeff M; Neely, Cherry; Owen, John
2018-03-01
To compare the accuracy of a new regression-derived formula developed from the National Fetal Growth Studies data to the common alternative method that uses the average of the gestational ages (GAs) calculated for each fetal biometric measurement (biparietal diameter, head circumference, abdominal circumference, and femur length). This retrospective cross-sectional study identified nonanomalous singleton pregnancies that had a crown-rump length plus at least 1 additional sonographic examination with complete fetal biometric measurements. With the use of the crown-rump length to establish the referent estimated date of delivery, each method's (National Institute of Child Health and Human Development regression versus Hadlock average [Radiology 1984; 152:497-501]), error at every examination was computed. Error, defined as the difference between the crown-rump length-derived GA and each method's predicted GA (weeks), was compared in 3 GA intervals: 1 (14 weeks-20 weeks 6 days), 2 (21 weeks-28 weeks 6 days), and 3 (≥29 weeks). In addition, the proportion of each method's examinations that had errors outside prespecified (±) day ranges was computed by using odds ratios. A total of 16,904 sonograms were identified. The overall and prespecified GA range subset mean errors were significantly smaller for the regression compared to the average (P < .01), and the regression had significantly lower odds of observing examinations outside the specified range of error in GA intervals 2 (odds ratio, 1.15; 95% confidence interval, 1.01-1.31) and 3 (odds ratio, 1.24; 95% confidence interval, 1.17-1.32) than the average method. In a contemporary unselected population of women dated by a crown-rump length-derived GA, the National Institute of Child Health and Human Development regression formula produced fewer estimates outside a prespecified margin of error than the commonly used Hadlock average; the differences were most pronounced for GA estimates at 29 weeks and later. © 2017 by the American Institute of Ultrasound in Medicine.
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Evaluation of a new model of aeolian transport in the presence of vegetation
Li, Junran; Okin, Gregory S.; Herrick, Jeffrey E.; Belnap, Jayne; Miller, Mark E.; Vest, Kimberly; Draut, Amy E.
2013-01-01
Aeolian transport is an important characteristic of many arid and semiarid regions worldwide that affects dust emission and ecosystem processes. The purpose of this paper is to evaluate a recent model of aeolian transport in the presence of vegetation. This approach differs from previous models by accounting for how vegetation affects the distribution of shear velocity on the surface rather than merely calculating the average effect of vegetation on surface shear velocity or simply using empirical relationships. Vegetation, soil, and meteorological data at 65 field sites with measurements of horizontal aeolian flux were collected from the Western United States. Measured fluxes were tested against modeled values to evaluate model performance, to obtain a set of optimum model parameters, and to estimate the uncertainty in these parameters. The same field data were used to model horizontal aeolian flux using three other schemes. Our results show that the model can predict horizontal aeolian flux with an approximate relative error of 2.1 and that further empirical corrections can reduce the approximate relative error to 1.0. The level of error is within what would be expected given uncertainties in threshold shear velocity and wind speed at our sites. The model outperforms the alternative schemes both in terms of approximate relative error and the number of sites at which threshold shear velocity was exceeded. These results lend support to an understanding of the physics of aeolian transport in which (1) vegetation's impact on transport is dependent upon the distribution of vegetation rather than merely its average lateral cover and (2) vegetation impacts surface shear stress locally by depressing it in the immediate lee of plants rather than by changing the bulk surface's threshold shear velocity. Our results also suggest that threshold shear velocity is exceeded more than might be estimated by single measurements of threshold shear stress and roughness length commonly associated with vegetated surfaces, highlighting the variation of threshold shear velocity with space and time in real landscapes.
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Improving laboratory data entry quality using Six Sigma.
Elbireer, Ali; Le Chasseur, Julie; Jackson, Brooks
2013-01-01
The Uganda Makerere University provides clinical laboratory support to over 70 clients in Uganda. With increased volume, manual data entry errors have steadily increased, prompting laboratory managers to employ the Six Sigma method to evaluate and reduce their problems. The purpose of this paper is to describe how laboratory data entry quality was improved by using Six Sigma. The Six Sigma Quality Improvement (QI) project team followed a sequence of steps, starting with defining project goals, measuring data entry errors to assess current performance, analyzing data and determining data-entry error root causes. Finally the team implemented changes and control measures to address the root causes and to maintain improvements. Establishing the Six Sigma project required considerable resources and maintaining the gains requires additional personnel time and dedicated resources. After initiating the Six Sigma project, there was a 60.5 percent reduction in data entry errors from 423 errors a month (i.e. 4.34 Six Sigma) in the first month, down to an average 166 errors/month (i.e. 4.65 Six Sigma) over 12 months. The team estimated the average cost of identifying and fixing a data entry error to be $16.25 per error. Thus, reducing errors by an average of 257 errors per month over one year has saved the laboratory an estimated $50,115 a year. The Six Sigma QI project provides a replicable framework for Ugandan laboratory staff and other resource-limited organizations to promote quality environment. Laboratory staff can deliver excellent care at a lower cost, by applying QI principles. This innovative QI method of reducing data entry errors in medical laboratories may improve the clinical workflow processes and make cost savings across the health care continuum.
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Gonçalves, Fabio; Treuhaft, Robert; Law, Beverly; ...
2017-01-07
Mapping and monitoring of forest carbon stocks across large areas in the tropics will necessarily rely on remote sensing approaches, which in turn depend on field estimates of biomass for calibration and validation purposes. Here, we used field plot data collected in a tropical moist forest in the central Amazon to gain a better understanding of the uncertainty associated with plot-level biomass estimates obtained specifically for the calibration of remote sensing measurements. In addition to accounting for sources of error that would be normally expected in conventional biomass estimates (e.g., measurement and allometric errors), we examined two sources of uncertaintymore » that are specific to the calibration process and should be taken into account in most remote sensing studies: the error resulting from spatial disagreement between field and remote sensing measurements (i.e., co-location error), and the error introduced when accounting for temporal differences in data acquisition. We found that the overall uncertainty in the field biomass was typically 25% for both secondary and primary forests, but ranged from 16 to 53%. Co-location and temporal errors accounted for a large fraction of the total variance (>65%) and were identified as important targets for reducing uncertainty in studies relating tropical forest biomass to remotely sensed data. Although measurement and allometric errors were relatively unimportant when considered alone, combined they accounted for roughly 30% of the total variance on average and should not be ignored. Lastly, our results suggest that a thorough understanding of the sources of error associated with field-measured plot-level biomass estimates in tropical forests is critical to determine confidence in remote sensing estimates of carbon stocks and fluxes, and to develop strategies for reducing the overall uncertainty of remote sensing approaches.« less
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MO-FG-202-05: Identifying Treatment Planning System Errors in IROC-H Phantom Irradiations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kerns, J; Followill, D; Howell, R
Purpose: Treatment Planning System (TPS) errors can affect large numbers of cancer patients receiving radiation therapy. Using an independent recalculation system, the Imaging and Radiation Oncology Core-Houston (IROC-H) can identify institutions that have not sufficiently modelled their linear accelerators in their TPS model. Methods: Linear accelerator point measurement data from IROC-H’s site visits was aggregated and analyzed from over 30 linear accelerator models. Dosimetrically similar models were combined to create “classes”. The class data was used to construct customized beam models in an independent treatment dose verification system (TVS). Approximately 200 head and neck phantom plans from 2012 to 2015more » were recalculated using this TVS. Comparison of plan accuracy was evaluated by comparing the measured dose to the institution’s TPS dose as well as the TVS dose. In cases where the TVS was more accurate than the institution by an average of >2%, the institution was identified as having a non-negligible TPS error. Results: Of the ∼200 recalculated plans, the average improvement using the TVS was ∼0.1%; i.e. the recalculation, on average, slightly outperformed the institution’s TPS. Of all the recalculated phantoms, 20% were identified as having a non-negligible TPS error. Fourteen plans failed current IROC-H criteria; the average TVS improvement of the failing plans was ∼3% and 57% were found to have non-negligible TPS errors. Conclusion: IROC-H has developed an independent recalculation system to identify institutions that have considerable TPS errors. A large number of institutions were found to have non-negligible TPS errors. Even institutions that passed IROC-H criteria could be identified as having a TPS error. Resolution of such errors would improve dose delivery for a large number of IROC-H phantoms and ultimately, patients.« less
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Non-Contact Thrust Stand Calibration Method for Repetitively-Pulsed Electric Thrusters
NASA Technical Reports Server (NTRS)
Wong, Andrea R.; Toftul, Alexandra; Polzin, Kurt A.; Pearson, J. Boise
2011-01-01
A thrust stand calibration technique for use in testing repetitively-pulsed electric thrusters for in-space propulsion has been developed and tested using a modified hanging pendulum thrust stand. In the implementation of this technique, current pulses are applied to a solenoidal coil to produce a pulsed magnetic field that acts against the magnetic field produced by a permanent magnet mounted to the thrust stand pendulum arm. The force on the magnet is applied in this non-contact manner, with the entire pulsed force transferred to the pendulum arm through a piezoelectric force transducer to provide a time-accurate force measurement. Modeling of the pendulum arm dynamics reveals that after an initial transient in thrust stand motion the quasisteady average deflection of the thrust stand arm away from the unforced or zero position can be related to the average applied force through a simple linear Hooke s law relationship. Modeling demonstrates that this technique is universally applicable except when the pulsing period is increased to the point where it approaches the period of natural thrust stand motion. Calibration data were obtained using a modified hanging pendulum thrust stand previously used for steady-state thrust measurements. Data were obtained for varying impulse bit at constant pulse frequency and for varying pulse frequency. The two data sets exhibit excellent quantitative agreement with each other as the constant relating average deflection and average thrust match within the errors on the linear regression curve fit of the data. Quantitatively, the error on the calibration coefficient is roughly 1% of the coefficient value.
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Chen, Chieh-Fan; Ho, Wen-Hsien; Chou, Huei-Yin; Yang, Shu-Mei; Chen, I-Te; Shi, Hon-Yi
2011-01-01
This study analyzed meteorological, clinical and economic factors in terms of their effects on monthly ED revenue and visitor volume. Monthly data from January 1, 2005 to September 30, 2009 were analyzed. Spearman correlation and cross-correlation analyses were performed to identify the correlation between each independent variable, ED revenue, and visitor volume. Autoregressive integrated moving average (ARIMA) model was used to quantify the relationship between each independent variable, ED revenue, and visitor volume. The accuracies were evaluated by comparing model forecasts to actual values with mean absolute percentage of error. Sensitivity of prediction errors to model training time was also evaluated. The ARIMA models indicated that mean maximum temperature, relative humidity, rainfall, non-trauma, and trauma visits may correlate positively with ED revenue, but mean minimum temperature may correlate negatively with ED revenue. Moreover, mean minimum temperature and stock market index fluctuation may correlate positively with trauma visitor volume. Mean maximum temperature, relative humidity and stock market index fluctuation may correlate positively with non-trauma visitor volume. Mean maximum temperature and relative humidity may correlate positively with pediatric visitor volume, but mean minimum temperature may correlate negatively with pediatric visitor volume. The model also performed well in forecasting revenue and visitor volume. PMID:22203886
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Chen, Chieh-Fan; Ho, Wen-Hsien; Chou, Huei-Yin; Yang, Shu-Mei; Chen, I-Te; Shi, Hon-Yi
2011-01-01
This study analyzed meteorological, clinical and economic factors in terms of their effects on monthly ED revenue and visitor volume. Monthly data from January 1, 2005 to September 30, 2009 were analyzed. Spearman correlation and cross-correlation analyses were performed to identify the correlation between each independent variable, ED revenue, and visitor volume. Autoregressive integrated moving average (ARIMA) model was used to quantify the relationship between each independent variable, ED revenue, and visitor volume. The accuracies were evaluated by comparing model forecasts to actual values with mean absolute percentage of error. Sensitivity of prediction errors to model training time was also evaluated. The ARIMA models indicated that mean maximum temperature, relative humidity, rainfall, non-trauma, and trauma visits may correlate positively with ED revenue, but mean minimum temperature may correlate negatively with ED revenue. Moreover, mean minimum temperature and stock market index fluctuation may correlate positively with trauma visitor volume. Mean maximum temperature, relative humidity and stock market index fluctuation may correlate positively with non-trauma visitor volume. Mean maximum temperature and relative humidity may correlate positively with pediatric visitor volume, but mean minimum temperature may correlate negatively with pediatric visitor volume. The model also performed well in forecasting revenue and visitor volume.
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Kowalik, William S.; Marsh, Stuart E.; Lyon, Ronald J. P.
1982-01-01
A method for estimating the reflectance of ground sites from satellite radiance data is proposed and tested. The method uses the known ground reflectance from several sites and satellite data gathered over a wide range of solar zenith angles. The method was tested on each of 10 different Landsat images using 10 small sites in the Walker Lake, Nevada area. Plots of raw Landsat digital numbers (DNs) versus the cosine of the solar zenith angle (cos Z) for the the test areas are linear, and the average correlation coefficients of the data for Landsat bands 4, 5, 6, and 7 are 0.94, 0.93, 0.94, and 0.94, respectively. Ground reflectance values for the 10 sites are proportional to the slope of the DN versus cos Z relation at each site. The slope of the DN versus cos Z relation for seven additional sites in Nevada and California were used to estimate the ground reflectances of those sites. The estimates for nearby sites are in error by an average of 1.2% and more distant sites are in error by 5.1%. The method can successfully estimate the reflectance of sites outside the original scene, but extrapolation of the reflectance estimation equations to other areas may violate assumptions of atmospheric homogeneity.
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Ansari, Mozafar; Othman, Faridah; Abunama, Taher; El-Shafie, Ahmed
2018-04-01
The function of a sewage treatment plant is to treat the sewage to acceptable standards before being discharged into the receiving waters. To design and operate such plants, it is necessary to measure and predict the influent flow rate. In this research, the influent flow rate of a sewage treatment plant (STP) was modelled and predicted by autoregressive integrated moving average (ARIMA), nonlinear autoregressive network (NAR) and support vector machine (SVM) regression time series algorithms. To evaluate the models' accuracy, the root mean square error (RMSE) and coefficient of determination (R 2 ) were calculated as initial assessment measures, while relative error (RE), peak flow criterion (PFC) and low flow criterion (LFC) were calculated as final evaluation measures to demonstrate the detailed accuracy of the selected models. An integrated model was developed based on the individual models' prediction ability for low, average and peak flow. An initial assessment of the results showed that the ARIMA model was the least accurate and the NAR model was the most accurate. The RE results also prove that the SVM model's frequency of errors above 10% or below - 10% was greater than the NAR model's. The influent was also forecasted up to 44 weeks ahead by both models. The graphical results indicate that the NAR model made better predictions than the SVM model. The final evaluation of NAR and SVM demonstrated that SVM made better predictions at peak flow and NAR fit well for low and average inflow ranges. The integrated model developed includes the NAR model for low and average influent and the SVM model for peak inflow.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Voisin, Sophie; Pinto, Frank M; Morin-Ducote, Garnetta
2013-01-01
Purpose: The primary aim of the present study was to test the feasibility of predicting diagnostic errors in mammography by merging radiologists gaze behavior and image characteristics. A secondary aim was to investigate group-based and personalized predictive models for radiologists of variable experience levels. Methods: The study was performed for the clinical task of assessing the likelihood of malignancy of mammographic masses. Eye-tracking data and diagnostic decisions for 40 cases were acquired from 4 Radiology residents and 2 breast imaging experts as part of an IRB-approved pilot study. Gaze behavior features were extracted from the eye-tracking data. Computer-generated and BIRADsmore » images features were extracted from the images. Finally, machine learning algorithms were used to merge gaze and image features for predicting human error. Feature selection was thoroughly explored to determine the relative contribution of the various features. Group-based and personalized user modeling was also investigated. Results: Diagnostic error can be predicted reliably by merging gaze behavior characteristics from the radiologist and textural characteristics from the image under review. Leveraging data collected from multiple readers produced a reasonable group model (AUC=0.79). Personalized user modeling was far more accurate for the more experienced readers (average AUC of 0.837 0.029) than for the less experienced ones (average AUC of 0.667 0.099). The best performing group-based and personalized predictive models involved combinations of both gaze and image features. Conclusions: Diagnostic errors in mammography can be predicted reliably by leveraging the radiologists gaze behavior and image content.« less
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Cost-effectiveness of the stream-gaging program in Missouri
Waite, L.A.
1987-01-01
This report documents the results of an evaluation of the cost effectiveness of the 1986 stream-gaging program in Missouri. Alternative methods of developing streamflow information and cost-effective resource allocation were used to evaluate the Missouri program. Alternative methods were considered statewide, but the cost effective resource allocation study was restricted to the area covered by the Rolla field headquarters. The average standard error of estimate for records of instantaneous discharge was 17 percent; assuming the 1986 budget and operating schedule, it was shown that this overall degree of accuracy could be improved to 16 percent by altering the 1986 schedule of station visitations. A minimum budget of $203,870, with a corresponding average standard error of estimate 17 percent, is required to operate the 1986 program for the Rolla field headquarters; a budget of less than this would not permit proper service and maintenance of the stations or adequate definition of stage-discharge relations. The maximum budget analyzed was $418,870, which resulted in an average standard error of estimate of 14 percent. Improved instrumentation can have a positive effect on streamflow uncertainties by decreasing lost records. An earlier study of data uses found that data uses were sufficient to justify continued operation of all stations. One of the stations investigated, Current River at Doniphan (07068000) was suitable for the application of alternative methods for simulating discharge records. However, the station was continued because of data use requirements. (Author 's abstract)
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Wollschläger, Daniel; Hammer, Gaël Paul; Schafft, Thomas; Dreger, Steffen; Blettner, Maria; Zeeb, Hajo
2018-05-01
Exposure to ionizing radiation of cosmic origin is an occupational risk factor in commercial aircrew. In a historic cohort of 26,774 German aircrew, radiation exposure was previously estimated only for cockpit crew using a job-exposure matrix (JEM). Here, a new method for retrospectively estimating cabin crew dose is developed. The German Federal Radiation Registry (SSR) documents individual monthly effective doses for all aircrew. SSR-provided doses on 12,941 aircrew from 2004 to 2015 were used to model cabin crew dose as a function of age, sex, job category, solar activity, and male pilots' dose; the mean annual effective dose was 2.25 mSv (range 0.01-6.39 mSv). In addition to an inverse association with solar activity, exposure followed age- and sex-dependent patterns related to individual career development and life phases. JEM-derived annual cockpit crew doses agreed with SSR-provided doses for 2004 (correlation 0.90, 0.40 mSv root mean squared error), while the estimated average annual effective dose for cabin crew had a prediction error of 0.16 mSv, equaling 7.2% of average annual dose. Past average annual cabin crew dose can be modeled by exploiting systematic external influences as well as individual behavioral determinants of radiation exposure, thereby enabling future dose-response analyses of the full aircrew cohort including measurement error information.
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Uncertainty Analysis in Humidity Measurements by the Psychrometer Method
Chen, Jiunyuan; Chen, Chiachung
2017-01-01
The most common and cheap indirect technique to measure relative humidity is by using psychrometer based on a dry and a wet temperature sensor. In this study, the measurement uncertainty of relative humidity was evaluated by this indirect method with some empirical equations for calculating relative humidity. Among the six equations tested, the Penman equation had the best predictive ability for the dry bulb temperature range of 15–50 °C. At a fixed dry bulb temperature, an increase in the wet bulb depression increased the error. A new equation for the psychrometer constant was established by regression analysis. This equation can be computed by using a calculator. The average predictive error of relative humidity was <0.1% by this new equation. The measurement uncertainty of the relative humidity affected by the accuracy of dry and wet bulb temperature and the numeric values of measurement uncertainty were evaluated for various conditions. The uncertainty of wet bulb temperature was the main factor on the RH measurement uncertainty. PMID:28216599
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Uncertainty Analysis in Humidity Measurements by the Psychrometer Method.
Chen, Jiunyuan; Chen, Chiachung
2017-02-14
The most common and cheap indirect technique to measure relative humidity is by using psychrometer based on a dry and a wet temperature sensor. In this study, the measurement uncertainty of relative humidity was evaluated by this indirect method with some empirical equations for calculating relative humidity. Among the six equations tested, the Penman equation had the best predictive ability for the dry bulb temperature range of 15-50 °C. At a fixed dry bulb temperature, an increase in the wet bulb depression increased the error. A new equation for the psychrometer constant was established by regression analysis. This equation can be computed by using a calculator. The average predictive error of relative humidity was <0.1% by this new equation. The measurement uncertainty of the relative humidity affected by the accuracy of dry and wet bulb temperature and the numeric values of measurement uncertainty were evaluated for various conditions. The uncertainty of wet bulb temperature was the main factor on the RH measurement uncertainty.
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Liu, Chao; Yao, Yong; Sun, Yun Xu; Xiao, Jun Jun; Zhao, Xin Hui
2010-10-01
A model is proposed to study the average capacity optimization in free-space optical (FSO) channels, accounting for effects of atmospheric turbulence and pointing errors. For a given transmitter laser power, it is shown that both transmitter beam divergence angle and beam waist can be tuned to maximize the average capacity. Meanwhile, their optimum values strongly depend on the jitter and operation wavelength. These results can be helpful for designing FSO communication systems.
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NASA Technical Reports Server (NTRS)
Edwards, M. H.; Arvidson, R. E.; Guinness, E. A.
1984-01-01
The problem of displaying information on the seafloor morphology is attacked by utilizing digital image processing techniques to generate images for Seabeam data covering three young seamounts on the eastern flank of the East Pacific Rise. Errors in locations between crossing tracks are corrected by interactively identifying features and translating tracks relative to a control track. Spatial interpolation techniques using moving averages are used to interpolate between gridded depth values to produce images in shaded relief and color-coded forms. The digitally processed images clarify the structural control on seamount growth and clearly show the lateral extent of volcanic materials, including the distribution and fault control of subsidiary volcanic constructional features. The image presentations also clearly show artifacts related to both residual navigational errors and to depth or location differences that depend on ship heading relative to slope orientation in regions with steep slopes.
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Estimating Relative Positions of Outer-Space Structures
NASA Technical Reports Server (NTRS)
Balian, Harry; Breckenridge, William; Brugarolas, Paul
2009-01-01
A computer program estimates the relative position and orientation of two structures from measurements, made by use of electronic cameras and laser range finders on one structure, of distances and angular positions of fiducial objects on the other structure. The program was written specifically for use in determining errors in the alignment of large structures deployed in outer space from a space shuttle. The program is based partly on equations for transformations among the various coordinate systems involved in the measurements and on equations that account for errors in the transformation operators. It computes a least-squares estimate of the relative position and orientation. Sequential least-squares estimates, acquired at a measurement rate of 4 Hz, are averaged by passing them through a fourth-order Butterworth filter. The program is executed in a computer aboard the space shuttle, and its position and orientation estimates are displayed to astronauts on a graphical user interface.
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Analytical skin friction and heat transfer formula for compressible internal flows
NASA Technical Reports Server (NTRS)
Dechant, Lawrence J.; Tattar, Marc J.
1994-01-01
An analytic, closed-form friction formula for turbulent, internal, compressible, fully developed flow was derived by extending the incompressible law-of-the-wall relation to compressible cases. The model is capable of analyzing heat transfer as a function of constant surface temperatures and surface roughness as well as analyzing adiabatic conditions. The formula reduces to Prandtl's law of friction for adiabatic, smooth, axisymmetric flow. In addition, the formula reduces to the Colebrook equation for incompressible, adiabatic, axisymmetric flow with various roughnesses. Comparisons with available experiments show that the model averages roughly 12.5 percent error for adiabatic flow and 18.5 percent error for flow involving heat transfer.
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Guo, Xiang; Wang, Ming Tian; Zhang, Guo Zhi
2017-12-01
The winter reproductive areas of Puccinia striiformis var. striiformis in Sichuan Basin are often the places mostly affected by wheat stripe rust. With data on the meteorological condition and stripe rust situation at typical stations in the winter reproductive area in Sichuan Basin from 1999 to 2016, this paper classified the meteorological conditions inducing wheat stripe rust into 5 grades, based on the incidence area ratio of the disease. The meteorological factors which were biologically related to wheat stripe rust were determined through multiple analytical methods, and a meteorological grade model for forecasting wheat stripe rust was created. The result showed that wheat stripe rust in Sichuan Basin was significantly correlated with many meteorological factors, such as the ave-rage (maximum and minimum) temperature, precipitation and its anomaly percentage, relative humidity and its anomaly percentage, average wind speed and sunshine duration. Among these, the average temperature and the anomaly percentage of relative humidity were the determining factors. According to a historical retrospective test, the accuracy of the forecast based on the model was 64% for samples in the county-level test, and 89% for samples in the municipal-level test. In a meteorological grade forecast of wheat stripe rust in the winter reproductive areas in Sichuan Basin in 2017, the prediction was accurate for 62.8% of the samples, with 27.9% error by one grade and only 9.3% error by two or more grades. As a result, the model could deliver satisfactory forecast results, and predicate future wheat stripe rust from a meteorological point of view.
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NASA Astrophysics Data System (ADS)
Yu, Karen; Keller, Christoph A.; Jacob, Daniel J.; Molod, Andrea M.; Eastham, Sebastian D.; Long, Michael S.
2018-01-01
Global simulations of atmospheric chemistry are commonly conducted with off-line chemical transport models (CTMs) driven by archived meteorological data from general circulation models (GCMs). The off-line approach has the advantages of simplicity and expediency, but it incurs errors due to temporal averaging in the meteorological archive and the inability to reproduce the GCM transport algorithms exactly. The CTM simulation is also often conducted at coarser grid resolution than the parent GCM. Here we investigate this cascade of CTM errors by using 222Rn-210Pb-7Be chemical tracer simulations off-line in the GEOS-Chem CTM at rectilinear 0.25° × 0.3125° (≈ 25 km) and 2° × 2.5° (≈ 200 km) resolutions and online in the parent GEOS-5 GCM at cubed-sphere c360 (≈ 25 km) and c48 (≈ 200 km) horizontal resolutions. The c360 GEOS-5 GCM meteorological archive, updated every 3 h and remapped to 0.25° × 0.3125°, is the standard operational product generated by the NASA Global Modeling and Assimilation Office (GMAO) and used as input by GEOS-Chem. We find that the GEOS-Chem 222Rn simulation at native 0.25° × 0.3125° resolution is affected by vertical transport errors of up to 20 % relative to the GEOS-5 c360 online simulation, in part due to loss of transient organized vertical motions in the GCM (resolved convection) that are temporally averaged out in the 3 h meteorological archive. There is also significant error caused by operational remapping of the meteorological archive from a cubed-sphere to a rectilinear grid. Decreasing the GEOS-Chem resolution from 0.25° × 0.3125° to 2° × 2.5° induces further weakening of vertical transport as transient vertical motions are averaged out spatially and temporally. The resulting 222Rn concentrations simulated by the coarse-resolution GEOS-Chem are overestimated by up to 40 % in surface air relative to the online c360 simulations and underestimated by up to 40 % in the upper troposphere, while the tropospheric lifetimes of 210Pb and 7Be against aerosol deposition are affected by 5-10 %. The lost vertical transport in the coarse-resolution GEOS-Chem simulation can be partly restored by recomputing the convective mass fluxes at the appropriate resolution to replace the archived convective mass fluxes and by correcting for bias in the spatial averaging of boundary layer mixing depths.
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Simultaneous Control of Error Rates in fMRI Data Analysis
Kang, Hakmook; Blume, Jeffrey; Ombao, Hernando; Badre, David
2015-01-01
The key idea of statistical hypothesis testing is to fix, and thereby control, the Type I error (false positive) rate across samples of any size. Multiple comparisons inflate the global (family-wise) Type I error rate and the traditional solution to maintaining control of the error rate is to increase the local (comparison-wise) Type II error (false negative) rates. However, in the analysis of human brain imaging data, the number of comparisons is so large that this solution breaks down: the local Type II error rate ends up being so large that scientifically meaningful analysis is precluded. Here we propose a novel solution to this problem: allow the Type I error rate to converge to zero along with the Type II error rate. It works because when the Type I error rate per comparison is very small, the accumulation (or global) Type I error rate is also small. This solution is achieved by employing the Likelihood paradigm, which uses likelihood ratios to measure the strength of evidence on a voxel-by-voxel basis. In this paper, we provide theoretical and empirical justification for a likelihood approach to the analysis of human brain imaging data. In addition, we present extensive simulations that show the likelihood approach is viable, leading to ‘cleaner’ looking brain maps and operationally superiority (lower average error rate). Finally, we include a case study on cognitive control related activation in the prefrontal cortex of the human brain. PMID:26272730
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Estimation of Rainfall Sampling Uncertainty: A Comparison of Two Diverse Approaches
NASA Technical Reports Server (NTRS)
Steiner, Matthias; Zhang, Yu; Baeck, Mary Lynn; Wood, Eric F.; Smith, James A.; Bell, Thomas L.; Lau, William K. M. (Technical Monitor)
2002-01-01
The spatial and temporal intermittence of rainfall causes the averages of satellite observations of rain rate to differ from the "true" average rain rate over any given area and time period, even if the satellite observations are perfectly accurate. The difference of satellite averages based on occasional observation by satellite systems and the continuous-time average of rain rate is referred to as sampling error. In this study, rms sampling error estimates are obtained for average rain rates over boxes 100 km, 200 km, and 500 km on a side, for averaging periods of 1 day, 5 days, and 30 days. The study uses a multi-year, merged radar data product provided by Weather Services International Corp. at a resolution of 2 km in space and 15 min in time, over an area of the central U.S. extending from 35N to 45N in latitude and 100W to 80W in longitude. The intervals between satellite observations are assumed to be equal, and similar In size to what present and future satellite systems are able to provide (from 1 h to 12 h). The sampling error estimates are obtained using a resampling method called "resampling by shifts," and are compared to sampling error estimates proposed by Bell based on earlier work by Laughlin. The resampling estimates are found to scale with areal size and time period as the theory predicts. The dependence on average rain rate and time interval between observations is also similar to what the simple theory suggests.
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Joch, Michael; Hegele, Mathias; Maurer, Heiko; Müller, Hermann; Maurer, Lisa Katharina
2017-07-01
The error (related) negativity (Ne/ERN) is an event-related potential in the electroencephalogram (EEG) correlating with error processing. Its conditions of appearance before terminal external error information suggest that the Ne/ERN is indicative of predictive processes in the evaluation of errors. The aim of the present study was to specifically examine the Ne/ERN in a complex motor task and to particularly rule out other explaining sources of the Ne/ERN aside from error prediction processes. To this end, we focused on the dependency of the Ne/ERN on visual monitoring about the action outcome after movement termination but before result feedback (action effect monitoring). Participants performed a semi-virtual throwing task by using a manipulandum to throw a virtual ball displayed on a computer screen to hit a target object. Visual feedback about the ball flying to the target was masked to prevent action effect monitoring. Participants received a static feedback about the action outcome (850 ms) after each trial. We found a significant negative deflection in the average EEG curves of the error trials peaking at ~250 ms after ball release, i.e., before error feedback. Furthermore, this Ne/ERN signal did not depend on visual ball-flight monitoring after release. We conclude that the Ne/ERN has the potential to indicate error prediction in motor tasks and that it exists even in the absence of action effect monitoring. NEW & NOTEWORTHY In this study, we are separating different kinds of possible contributors to an electroencephalogram (EEG) error correlate (Ne/ERN) in a throwing task. We tested the influence of action effect monitoring on the Ne/ERN amplitude in the EEG. We used a task that allows us to restrict movement correction and action effect monitoring and to control the onset of result feedback. We ascribe the Ne/ERN to predictive error processing where a conscious feeling of failure is not a prerequisite. Copyright © 2017 the American Physiological Society.
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Jones, J.W.; Jarnagin, T.
2009-01-01
Given the relatively high cost of mapping impervious surfaces at regional scales, substantial effort is being expended in the development of moderate-resolution, satellite-based methods for estimating impervious surface area (ISA). To rigorously assess the accuracy of these data products high quality, independently derived validation data are needed. High-resolution data were collected across a gradient of development within the Mid-Atlantic region to assess the accuracy of National Land Cover Data (NLCD) Landsat-based ISA estimates. Absolute error (satellite predicted area - "reference area") and relative error [satellite (predicted area - "reference area")/ "reference area"] were calculated for each of 240 sample regions that are each more than 15 Landsat pixels on a side. The ability to compile and examine ancillary data in a geographic information system environment provided for evaluation of both validation and NLCD data and afforded efficient exploration of observed errors. In a minority of cases, errors could be explained by temporal discontinuities between the date of satellite image capture and validation source data in rapidly changing places. In others, errors were created by vegetation cover over impervious surfaces and by other factors that bias the satellite processing algorithms. On average in the Mid-Atlantic region, the NLCD product underestimates ISA by approximately 5%. While the error range varies between 2 and 8%, this underestimation occurs regardless of development intensity. Through such analyses the errors, strengths, and weaknesses of particular satellite products can be explored to suggest appropriate uses for regional, satellite-based data in rapidly developing areas of environmental significance. ?? 2009 ASCE.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Gonçalves, Fabio; Treuhaft, Robert; Law, Beverly
Mapping and monitoring of forest carbon stocks across large areas in the tropics will necessarily rely on remote sensing approaches, which in turn depend on field estimates of biomass for calibration and validation purposes. Here, we used field plot data collected in a tropical moist forest in the central Amazon to gain a better understanding of the uncertainty associated with plot-level biomass estimates obtained specifically for the calibration of remote sensing measurements. In addition to accounting for sources of error that would be normally expected in conventional biomass estimates (e.g., measurement and allometric errors), we examined two sources of uncertaintymore » that are specific to the calibration process and should be taken into account in most remote sensing studies: the error resulting from spatial disagreement between field and remote sensing measurements (i.e., co-location error), and the error introduced when accounting for temporal differences in data acquisition. We found that the overall uncertainty in the field biomass was typically 25% for both secondary and primary forests, but ranged from 16 to 53%. Co-location and temporal errors accounted for a large fraction of the total variance (>65%) and were identified as important targets for reducing uncertainty in studies relating tropical forest biomass to remotely sensed data. Although measurement and allometric errors were relatively unimportant when considered alone, combined they accounted for roughly 30% of the total variance on average and should not be ignored. Lastly, our results suggest that a thorough understanding of the sources of error associated with field-measured plot-level biomass estimates in tropical forests is critical to determine confidence in remote sensing estimates of carbon stocks and fluxes, and to develop strategies for reducing the overall uncertainty of remote sensing approaches.« less
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Covariance analysis for evaluating head trackers
NASA Astrophysics Data System (ADS)
Kang, Donghoon
2017-10-01
Existing methods for evaluating the performance of head trackers usually rely on publicly available face databases, which contain facial images and the ground truths of their corresponding head orientations. However, most of the existing publicly available face databases are constructed by assuming that a frontal head orientation can be determined by compelling the person under examination to look straight ahead at the camera on the first video frame. Since nobody can accurately direct one's head toward the camera, this assumption may be unrealistic. Rather than obtaining estimation errors, we present a method for computing the covariance of estimation error rotations to evaluate the reliability of head trackers. As an uncertainty measure of estimators, the Schatten 2-norm of a square root of error covariance (or the algebraic average of relative error angles) can be used. The merit of the proposed method is that it does not disturb the person under examination by asking him to direct his head toward certain directions. Experimental results using real data validate the usefulness of our method.
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Colour application on mammography image segmentation
NASA Astrophysics Data System (ADS)
Embong, R.; Aziz, N. M. Nik Ab.; Karim, A. H. Abd; Ibrahim, M. R.
2017-09-01
The segmentation process is one of the most important steps in image processing and computer vision since it is vital in the initial stage of image analysis. Segmentation of medical images involves complex structures and it requires precise segmentation result which is necessary for clinical diagnosis such as the detection of tumour, oedema, and necrotic tissues. Since mammography images are grayscale, researchers are looking at the effect of colour in the segmentation process of medical images. Colour is known to play a significant role in the perception of object boundaries in non-medical colour images. Processing colour images require handling more data, hence providing a richer description of objects in the scene. Colour images contain ten percent (10%) additional edge information as compared to their grayscale counterparts. Nevertheless, edge detection in colour image is more challenging than grayscale image as colour space is considered as a vector space. In this study, we implemented red, green, yellow, and blue colour maps to grayscale mammography images with the purpose of testing the effect of colours on the segmentation of abnormality regions in the mammography images. We applied the segmentation process using the Fuzzy C-means algorithm and evaluated the percentage of average relative error of area for each colour type. The results showed that all segmentation with the colour map can be done successfully even for blurred and noisy images. Also the size of the area of the abnormality region is reduced when compare to the segmentation area without the colour map. The green colour map segmentation produced the smallest percentage of average relative error (10.009%) while yellow colour map segmentation gave the largest percentage of relative error (11.367%).
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Badrick, Tony; Graham, Peter
2018-03-28
Internal Quality Control and External Quality Assurance are separate but related processes that have developed independently in laboratory medicine over many years. They have different sample frequencies, statistical interpretations and immediacy. Both processes have evolved absorbing new understandings of the concept of laboratory error, sample material matrix and assay capability. However, we do not believe at the coalface that either process has led to much improvement in patient outcomes recently. It is the increasing reliability and automation of analytical platforms along with improved stability of reagents that has reduced systematic and random error, which in turn has minimised the risk of running less frequent IQC. We suggest that it is time to rethink the role of both these processes and unite them into a single approach using an Average of Normals model supported by more frequent External Quality Assurance samples. This new paradigm may lead to less confusion for laboratory staff and quicker responses to and identification of out of control situations.
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Ecological footprint model using the support vector machine technique.
Ma, Haibo; Chang, Wenjuan; Cui, Guangbai
2012-01-01
The per capita ecological footprint (EF) is one of the most widely recognized measures of environmental sustainability. It aims to quantify the Earth's biological resources required to support human activity. In this paper, we summarize relevant previous literature, and present five factors that influence per capita EF. These factors are: National gross domestic product (GDP), urbanization (independent of economic development), distribution of income (measured by the Gini coefficient), export dependence (measured by the percentage of exports to total GDP), and service intensity (measured by the percentage of service to total GDP). A new ecological footprint model based on a support vector machine (SVM), which is a machine-learning method based on the structural risk minimization principle from statistical learning theory was conducted to calculate the per capita EF of 24 nations using data from 123 nations. The calculation accuracy was measured by average absolute error and average relative error. They were 0.004883 and 0.351078% respectively. Our results demonstrate that the EF model based on SVM has good calculation performance.
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Use of upscaled elevation and surface roughness data in two-dimensional surface water models
Hughes, J.D.; Decker, J.D.; Langevin, C.D.
2011-01-01
In this paper, we present an approach that uses a combination of cell-block- and cell-face-averaging of high-resolution cell elevation and roughness data to upscale hydraulic parameters and accurately simulate surface water flow in relatively low-resolution numerical models. The method developed allows channelized features that preferentially connect large-scale grid cells at cell interfaces to be represented in models where these features are significantly smaller than the selected grid size. The developed upscaling approach has been implemented in a two-dimensional finite difference model that solves a diffusive wave approximation of the depth-integrated shallow surface water equations using preconditioned Newton–Krylov methods. Computational results are presented to show the effectiveness of the mixed cell-block and cell-face averaging upscaling approach in maintaining model accuracy, reducing model run-times, and how decreased grid resolution affects errors. Application examples demonstrate that sub-grid roughness coefficient variations have a larger effect on simulated error than sub-grid elevation variations.
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McGinitie, Teague M; Ebrahimi-Najafabadi, Heshmatollah; Harynuk, James J
2014-01-17
A new method for estimating the thermodynamic parameters of ΔH(T0), ΔS(T0), and ΔCP for use in thermodynamic modeling of GC×GC separations has been developed. The method is an alternative to the traditional isothermal separations required to fit a three-parameter thermodynamic model to retention data. Herein, a non-linear optimization technique is used to estimate the parameters from a series of temperature-programmed separations using the Nelder-Mead simplex algorithm. With this method, the time required to obtain estimates of thermodynamic parameters a series of analytes is significantly reduced. This new method allows for precise predictions of retention time with the average error being only 0.2s for 1D separations. Predictions for GC×GC separations were also in agreement with experimental measurements; having an average relative error of 0.37% for (1)tr and 2.1% for (2)tr. Copyright © 2013 Elsevier B.V. All rights reserved.
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A review of setup error in supine breast radiotherapy using cone-beam computed tomography
DOE Office of Scientific and Technical Information (OSTI.GOV)
Batumalai, Vikneswary, E-mail: Vikneswary.batumalai@sswahs.nsw.gov.au; Liverpool and Macarthur Cancer Therapy Centres, New South Wales; Ingham Institute of Applied Medical Research, Sydney, New South Wales
2016-10-01
Setup error in breast radiotherapy (RT) measured with 3-dimensional cone-beam computed tomography (CBCT) is becoming more common. The purpose of this study is to review the literature relating to the magnitude of setup error in breast RT measured with CBCT. The different methods of image registration between CBCT and planning computed tomography (CT) scan were also explored. A literature search, not limited by date, was conducted using Medline and Google Scholar with the following key words: breast cancer, RT, setup error, and CBCT. This review includes studies that reported on systematic and random errors, and the methods used when registeringmore » CBCT scans with planning CT scan. A total of 11 relevant studies were identified for inclusion in this review. The average magnitude of error is generally less than 5 mm across a number of studies reviewed. The common registration methods used when registering CBCT scans with planning CT scan are based on bony anatomy, soft tissue, and surgical clips. No clear relationships between the setup errors detected and methods of registration were observed from this review. Further studies are needed to assess the benefit of CBCT over electronic portal image, as CBCT remains unproven to be of wide benefit in breast RT.« less
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Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations
Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T.; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P.; Rötter, Reimund P.; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank
2016-01-01
We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations. PMID:27055028
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Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.
Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P; Rötter, Reimund P; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank
2016-01-01
We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.
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Evaluation of TRMM Ground-Validation Radar-Rain Errors Using Rain Gauge Measurements
NASA Technical Reports Server (NTRS)
Wang, Jianxin; Wolff, David B.
2009-01-01
Ground-validation (GV) radar-rain products are often utilized for validation of the Tropical Rainfall Measuring Mission (TRMM) spaced-based rain estimates, and hence, quantitative evaluation of the GV radar-rain product error characteristics is vital. This study uses quality-controlled gauge data to compare with TRMM GV radar rain rates in an effort to provide such error characteristics. The results show that significant differences of concurrent radar-gauge rain rates exist at various time scales ranging from 5 min to 1 day, despite lower overall long-term bias. However, the differences between the radar area-averaged rain rates and gauge point rain rates cannot be explained as due to radar error only. The error variance separation method is adapted to partition the variance of radar-gauge differences into the gauge area-point error variance and radar rain estimation error variance. The results provide relatively reliable quantitative uncertainty evaluation of TRMM GV radar rain estimates at various times scales, and are helpful to better understand the differences between measured radar and gauge rain rates. It is envisaged that this study will contribute to better utilization of GV radar rain products to validate versatile spaced-based rain estimates from TRMM, as well as the proposed Global Precipitation Measurement, and other satellites.
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Double ErrP Detection for Automatic Error Correction in an ERP-Based BCI Speller.
Cruz, Aniana; Pires, Gabriel; Nunes, Urbano J
2018-01-01
Brain-computer interface (BCI) is a useful device for people with severe motor disabilities. However, due to its low speed and low reliability, BCI still has a very limited application in daily real-world tasks. This paper proposes a P300-based BCI speller combined with a double error-related potential (ErrP) detection to automatically correct erroneous decisions. This novel approach introduces a second error detection to infer whether wrong automatic correction also elicits a second ErrP. Thus, two single-trial responses, instead of one, contribute to the final selection, improving the reliability of error detection. Moreover, to increase error detection, the evoked potential detected as target by the P300 classifier is combined with the evoked error potential at a feature-level. Discriminable error and positive potentials (response to correct feedback) were clearly identified. The proposed approach was tested on nine healthy participants and one tetraplegic participant. The online average accuracy for the first and second ErrPs were 88.4% and 84.8%, respectively. With automatic correction, we achieved an improvement around 5% achieving 89.9% in spelling accuracy for an effective 2.92 symbols/min. The proposed approach revealed that double ErrP detection can improve the reliability and speed of BCI systems.
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Decision-aided ICI mitigation with time-domain average approximation in CO-OFDM
NASA Astrophysics Data System (ADS)
Ren, Hongliang; Cai, Jiaxing; Ye, Xin; Lu, Jin; Cao, Quanjun; Guo, Shuqin; Xue, Lin-lin; Qin, Yali; Hu, Weisheng
2015-07-01
We introduce and investigate the feasibility of a novel iterative blind phase noise inter-carrier interference (ICI) mitigation scheme for coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems. The ICI mitigation scheme is performed through the combination of frequency-domain symbol decision-aided estimation and the ICI phase noise time-average approximation. An additional initial decision process with suitable threshold is introduced in order to suppress the decision error symbols. Our proposed ICI mitigation scheme is proved to be effective in removing the ICI for a simulated CO-OFDM with 16-QAM modulation format. With the slightly high computational complexity, it outperforms the time-domain average blind ICI (Avg-BL-ICI) algorithm at a relatively wide laser line-width and high OSNR.
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Wiese, Steffen; Teutenberg, Thorsten; Schmidt, Torsten C
2011-09-28
In the present work it is shown that the linear elution strength (LES) model which was adapted from temperature-programming gas chromatography (GC) can also be employed to predict retention times for segmented-temperature gradients based on temperature-gradient input data in liquid chromatography (LC) with high accuracy. The LES model assumes that retention times for isothermal separations can be predicted based on two temperature gradients and is employed to calculate the retention factor of an analyte when changing the start temperature of the temperature gradient. In this study it was investigated whether this approach can also be employed in LC. It was shown that this approximation cannot be transferred to temperature-programmed LC where a temperature range from 60°C up to 180°C is investigated. Major relative errors up to 169.6% were observed for isothermal retention factor predictions. In order to predict retention times for temperature gradients with different start temperatures in LC, another relationship is required to describe the influence of temperature on retention. Therefore, retention times for isothermal separations based on isothermal input runs were predicted using a plot of the natural logarithm of the retention factor vs. the inverse temperature and a plot of the natural logarithm of the retention factor vs. temperature. It could be shown that a plot of lnk vs. T yields more reliable isothermal/isocratic retention time predictions than a plot of lnk vs. 1/T which is usually employed. Hence, in order to predict retention times for temperature-gradients with different start temperatures in LC, two temperature gradient and two isothermal measurements have been employed. In this case, retention times can be predicted with a maximal relative error of 5.5% (average relative error: 2.9%). In comparison, if the start temperature of the simulated temperature gradient is equal to the start temperature of the input data, only two temperature-gradient measurements are required. Under these conditions, retention times can be predicted with a maximal relative error of 4.3% (average relative error: 2.2%). As an example, the systematic method development for an isothermal as well as a temperature gradient separation of selected sulfonamides by means of the adapted LES model is demonstrated using a pure water mobile phase. Both methods are compared and it is shown that the temperature-gradient separation provides some advantages over the isothermal separation in terms of limits of detection and analysis time. Copyright © 2011 Elsevier B.V. All rights reserved.
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Malpractice suits in chest radiology: an evaluation of the histories of 8265 radiologists.
Baker, Stephen R; Patel, Ronak H; Yang, Lily; Lelkes, Valdis M; Castro, Alejandro
2013-11-01
The aim of this study was to present rates of claims, causes of error, percentage of cases resulting in a judgment, and average payments made by radiologists in chest-related malpractice cases in a survey of 8265 radiologists. The malpractice histories of 8265 radiologists were evaluated from the credentialing files of One-Call Medical Inc., a preferred provider organization for computed tomography/magnetic resonance imaging in workers' compensation cases. Of the 8265 radiologists, 2680 (32.4%) had at least 1 malpractice suit. Of those who were sued, the rate of claims was 55.1 per 1000 person years. The rate of thorax-related suits was 6.6 claims per 1000 radiology practice years (95% confidence interval, 6.0-7.2). There were 496 suits encompassing 48 different causes. Errors in diagnosis comprised 78.0% of the causes. Failure to diagnose lung cancer was by far the most frequent diagnostic error, representing 211 cases or 42.5%. Of the 496 cases, an outcome was known in 417. Sixty-one percent of these were settled in favor of the plaintiff, with a mean payment of $277,230 (95% confidence interval, 226,967-338,614). Errors in diagnosis, and among them failure to diagnose lung cancer, were by far the most common reasons for initiating a malpractice suit against radiologists related to the thorax and its contents.
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Prevalence and pattern of prescription errors in a Nigerian kidney hospital.
Babatunde, Kehinde M; Akinbodewa, Akinwumi A; Akinboye, Ayodele O; Adejumo, Ademola O
2016-12-01
To determine (i) the prevalence and pattern of prescription errors in our Centre and, (ii) appraise pharmacists' intervention and correction of identified prescription errors. A descriptive, single blinded cross-sectional study. Kidney Care Centre is a public Specialist hospital. The monthly patient load averages 60 General Out-patient cases and 17.4 in-patients. A total of 31 medical doctors (comprising of 2 Consultant Nephrologists, 15 Medical Officers, 14 House Officers), 40 nurses and 24 ward assistants participated in the study. One pharmacist runs the daily call schedule. Prescribers were blinded to the study. Prescriptions containing only galenicals were excluded. An error detection mechanism was set up to identify and correct prescription errors. Life-threatening prescriptions were discussed with the Quality Assurance Team of the Centre who conveyed such errors to the prescriber without revealing the on-going study. Prevalence of prescription errors, pattern of prescription errors, pharmacist's intervention. A total of 2,660 (75.0%) combined prescription errors were found to have one form of error or the other; illegitimacy 1,388 (52.18%), omission 1,221(45.90%), wrong dose 51(1.92%) and no error of style was detected. Life-threatening errors were low (1.1-2.2%). Errors were found more commonly among junior doctors and non-medical doctors. Only 56 (1.6%) of the errors were detected and corrected during the process of dispensing. Prescription errors related to illegitimacy and omissions were highly prevalent. There is a need to improve on patient-to-healthcare giver ratio. A medication quality assurance unit is needed in our hospitals. No financial support was received by any of the authors for this study.
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Retrieving Storm Electric Fields from Aircrfaft Field Mill Data: Part II: Applications
NASA Technical Reports Server (NTRS)
Koshak, William; Mach, D. M.; Christian H. J.; Stewart, M. F.; Bateman M. G.
2006-01-01
The Lagrange multiplier theory developed in Part I of this study is applied to complete a relative calibration of a Citation aircraft that is instrumented with six field mill sensors. When side constraints related to average fields are used, the Lagrange multiplier method performs well in computer simulations. For mill measurement errors of 1 V m(sup -1) and a 5 V m(sup -1) error in the mean fair-weather field function, the 3D storm electric field is retrieved to within an error of about 12%. A side constraint that involves estimating the detailed structure of the fair-weather field was also tested using computer simulations. For mill measurement errors of 1 V m(sup -l), the method retrieves the 3D storm field to within an error of about 8% if the fair-weather field estimate is typically within 1 V m(sup -1) of the true fair-weather field. Using this type of side constraint and data from fair-weather field maneuvers taken on 29 June 2001, the Citation aircraft was calibrated. Absolute calibration was completed using the pitch down method developed in Part I, and conventional analyses. The resulting calibration matrices were then used to retrieve storm electric fields during a Citation flight on 2 June 2001. The storm field results are encouraging and agree favorably in many respects with results derived from earlier (iterative) techniques of calibration.
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Global Surface Temperature Change and Uncertainties Since 1861
NASA Technical Reports Server (NTRS)
Shen, Samuel S. P.; Lau, William K. M. (Technical Monitor)
2002-01-01
The objective of this talk is to analyze the warming trend and its uncertainties of the global and hemi-spheric surface temperatures. By the method of statistical optimal averaging scheme, the land surface air temperature and sea surface temperature observational data are used to compute the spatial average annual mean surface air temperature. The optimal averaging method is derived from the minimization of the mean square error between the true and estimated averages and uses the empirical orthogonal functions. The method can accurately estimate the errors of the spatial average due to observational gaps and random measurement errors. In addition, quantified are three independent uncertainty factors: urbanization, change of the in situ observational practices and sea surface temperature data corrections. Based on these uncertainties, the best linear fit to annual global surface temperature gives an increase of 0.61 +/- 0.16 C between 1861 and 2000. This lecture will also touch the topics on the impact of global change on nature and environment. as well as the latest assessment methods for the attributions of global change.
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Cohen, Michael X
2015-09-01
The purpose of this paper is to compare the effects of different spatial transformations applied to the same scalp-recorded EEG data. The spatial transformations applied are two referencing schemes (average and linked earlobes), the surface Laplacian, and beamforming (a distributed source localization procedure). EEG data were collected during a speeded reaction time task that provided a comparison of activity between error vs. correct responses. Analyses focused on time-frequency power, frequency band-specific inter-electrode connectivity, and within-subject cross-trial correlations between EEG activity and reaction time. Time-frequency power analyses showed similar patterns of midfrontal delta-theta power for errors compared to correct responses across all spatial transformations. Beamforming additionally revealed error-related anterior and lateral prefrontal beta-band activity. Within-subject brain-behavior correlations showed similar patterns of results across the spatial transformations, with the correlations being the weakest after beamforming. The most striking difference among the spatial transformations was seen in connectivity analyses: linked earlobe reference produced weak inter-site connectivity that was attributable to volume conduction (zero phase lag), while the average reference and Laplacian produced more interpretable connectivity results. Beamforming did not reveal any significant condition modulations of connectivity. Overall, these analyses show that some findings are robust to spatial transformations, while other findings, particularly those involving cross-trial analyses or connectivity, are more sensitive and may depend on the use of appropriate spatial transformations. Copyright © 2014 Elsevier B.V. All rights reserved.
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Murray, Christopher J. L; Lopez, Alan D; Barofsky, Jeremy T; Bryson-Cahn, Chloe; Lozano, Rafael
2007-01-01
Background Cause-of-death data for many developing countries are not available. Information on deaths in hospital by cause is available in many low- and middle-income countries but is not a representative sample of deaths in the population. We propose a method to estimate population cause-specific mortality fractions (CSMFs) using data already collected in many middle-income and some low-income developing nations, yet rarely used: in-hospital death records. Methods and Findings For a given cause of death, a community's hospital deaths are equal to total community deaths multiplied by the proportion of deaths occurring in hospital. If we can estimate the proportion dying in hospital, we can estimate the proportion dying in the population using deaths in hospital. We propose to estimate the proportion of deaths for an age, sex, and cause group that die in hospital from the subset of the population where vital registration systems function or from another population. We evaluated our method using nearly complete vital registration (VR) data from Mexico 1998–2005, which records whether a death occurred in a hospital. In this validation test, we used 45 disease categories. We validated our method in two ways: nationally and between communities. First, we investigated how the method's accuracy changes as we decrease the amount of Mexican VR used to estimate the proportion of each age, sex, and cause group dying in hospital. Decreasing VR data used for this first step from 100% to 9% produces only a 12% maximum relative error between estimated and true CSMFs. Even if Mexico collected full VR information only in its capital city with 9% of its population, our estimation method would produce an average relative error in CSMFs across the 45 causes of just over 10%. Second, we used VR data for the capital zone (Distrito Federal and Estado de Mexico) and estimated CSMFs for the three lowest-development states. Our estimation method gave an average relative error of 20%, 23%, and 31% for Guerrero, Chiapas, and Oaxaca, respectively. Conclusions Where accurate International Classification of Diseases (ICD)-coded cause-of-death data are available for deaths in hospital and for VR covering a subset of the population, we demonstrated that population CSMFs can be estimated with low average error. In addition, we showed in the case of Mexico that this method can substantially reduce error from biased hospital data, even when applied to areas with widely different levels of development. For countries with ICD-coded deaths in hospital, this method potentially allows the use of existing data to inform health policy. PMID:18031195
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Radiation Dry Bias of the Vaisala RS92 Humidity Sensor
NASA Technical Reports Server (NTRS)
Vomel, H.; Selkirk, H.; Miloshevich, L.; Valverde-Canossa, J.; Valdes, J.; Kyro, E.; Kivi, R.; Stolz, W.; Peng, G.; Diaz, J. A.
2007-01-01
The comparison of simultaneous humidity measurements by the Vaisala RS92 radiosonde and by the Cryogenic Frostpoint Hygrometer (CFH) launched at Alajuela, Cosla Rica, during July 2005 reveals a large solar radiation dry bias of the Vaisala RS92 humidity sensor and a minor temperature-dependent calibration error. For soundings launched at solar zenith angles between 10" and 30 , the average dry bias is on the order of 9% at the surface and increases to 50% at 15 km. A simple pressure- and temperature-dependent correction based on the comparison with the CFH can reduce this error to less than 7% at all altitudes up to 15.2 km, which is 700 m below the tropical tropopause. The correction does not depend on relative humidity, but is able to reproduce the relative humidity distribution observed by the CFH.
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Work-related accidents among the Iranian population: a time series analysis, 2000–2011
Karimlou, Masoud; Imani, Mehdi; Hosseini, Agha-Fatemeh; Dehnad, Afsaneh; Vahabi, Nasim; Bakhtiyari, Mahmood
2015-01-01
Background Work-related accidents result in human suffering and economic losses and are considered as a major health problem worldwide, especially in the economically developing world. Objectives To introduce seasonal autoregressive moving average (ARIMA) models for time series analysis of work-related accident data for workers insured by the Iranian Social Security Organization (ISSO) between 2000 and 2011. Methods In this retrospective study, all insured people experiencing at least one work-related accident during a 10-year period were included in the analyses. We used Box–Jenkins modeling to develop a time series model of the total number of accidents. Results There was an average of 1476 accidents per month (1476·05±458·77, mean±SD). The final ARIMA (p,d,q) (P,D,Q)s model for fitting to data was: ARIMA(1,1,1)×(0,1,1)12 consisting of the first ordering of the autoregressive, moving average and seasonal moving average parameters with 20·942 mean absolute percentage error (MAPE). Conclusions The final model showed that time series analysis of ARIMA models was useful for forecasting the number of work-related accidents in Iran. In addition, the forecasted number of work-related accidents for 2011 explained the stability of occurrence of these accidents in recent years, indicating a need for preventive occupational health and safety policies such as safety inspection. PMID:26119774
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Work-related accidents among the Iranian population: a time series analysis, 2000-2011.
Karimlou, Masoud; Salehi, Masoud; Imani, Mehdi; Hosseini, Agha-Fatemeh; Dehnad, Afsaneh; Vahabi, Nasim; Bakhtiyari, Mahmood
2015-01-01
Work-related accidents result in human suffering and economic losses and are considered as a major health problem worldwide, especially in the economically developing world. To introduce seasonal autoregressive moving average (ARIMA) models for time series analysis of work-related accident data for workers insured by the Iranian Social Security Organization (ISSO) between 2000 and 2011. In this retrospective study, all insured people experiencing at least one work-related accident during a 10-year period were included in the analyses. We used Box-Jenkins modeling to develop a time series model of the total number of accidents. There was an average of 1476 accidents per month (1476·05±458·77, mean±SD). The final ARIMA (p,d,q) (P,D,Q)s model for fitting to data was: ARIMA(1,1,1)×(0,1,1)12 consisting of the first ordering of the autoregressive, moving average and seasonal moving average parameters with 20·942 mean absolute percentage error (MAPE). The final model showed that time series analysis of ARIMA models was useful for forecasting the number of work-related accidents in Iran. In addition, the forecasted number of work-related accidents for 2011 explained the stability of occurrence of these accidents in recent years, indicating a need for preventive occupational health and safety policies such as safety inspection.
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Trommer, J.T.; Loper, J.E.; Hammett, K.M.
1996-01-01
Several traditional techniques have been used for estimating stormwater runoff from ungaged watersheds. Applying these techniques to water- sheds in west-central Florida requires that some of the empirical relationships be extrapolated beyond tested ranges. As a result, there is uncertainty as to the accuracy of these estimates. Sixty-six storms occurring in 15 west-central Florida watersheds were initially modeled using the Rational Method, the U.S. Geological Survey Regional Regression Equations, the Natural Resources Conservation Service TR-20 model, the U.S. Army Corps of Engineers Hydrologic Engineering Center-1 model, and the Environmental Protection Agency Storm Water Management Model. The techniques were applied according to the guidelines specified in the user manuals or standard engineering textbooks as though no field data were available and the selection of input parameters was not influenced by observed data. Computed estimates were compared with observed runoff to evaluate the accuracy of the techniques. One watershed was eliminated from further evaluation when it was determined that the area contributing runoff to the stream varies with the amount and intensity of rainfall. Therefore, further evaluation and modification of the input parameters were made for only 62 storms in 14 watersheds. Runoff ranged from 1.4 to 99.3 percent percent of rainfall. The average runoff for all watersheds included in this study was about 36 percent of rainfall. The average runoff for the urban, natural, and mixed land-use watersheds was about 41, 27, and 29 percent, respectively. Initial estimates of peak discharge using the rational method produced average watershed errors that ranged from an underestimation of 50.4 percent to an overestimation of 767 percent. The coefficient of runoff ranged from 0.20 to 0.60. Calibration of the technique produced average errors that ranged from an underestimation of 3.3 percent to an overestimation of 1.5 percent. The average calibrated coefficient of runoff for each watershed ranged from 0.02 to 0.72. The average values of the coefficient of runoff necessary to calibrate the urban, natural, and mixed land-use watersheds were 0.39, 0.16, and 0.08, respectively. The U.S. Geological Survey regional regression equations for determining peak discharge produced errors that ranged from an underestimation of 87.3 percent to an over- estimation of 1,140 percent. The regression equations for determining runoff volume produced errors that ranged from an underestimation of 95.6 percent to an overestimation of 324 percent. Regression equations developed from data used for this study produced errors that ranged between an underestimation of 82.8 percent and an over- estimation of 328 percent for peak discharge, and from an underestimation of 71.2 percent to an overestimation of 241 percent for runoff volume. Use of the equations developed for west-central Florida streams produced average errors for each type of watershed that were lower than errors associated with use of the U.S. Geological Survey equations. Initial estimates of peak discharges and runoff volumes using the Natural Resources Conservation Service TR-20 model, produced average errors of 44.6 and 42.7 percent respectively, for all the watersheds. Curve numbers and times of concentration were adjusted to match estimated and observed peak discharges and runoff volumes. The average change in the curve number for all the watersheds was a decrease of 2.8 percent. The average change in the time of concentration was an increase of 59.2 percent. The shape of the input dimensionless unit hydrograph also had to be adjusted to match the shape and peak time of the estimated and observed flood hydrographs. Peak rate factors for the modified input dimensionless unit hydrographs ranged from 162 to 454. The mean errors for peak discharges and runoff volumes were reduced to 18.9 and 19.5 percent, respectively, using the average calibrated input parameters for ea
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Peppas, Kostas P; Lazarakis, Fotis; Alexandridis, Antonis; Dangakis, Kostas
2012-08-01
In this Letter we investigate the error performance of multiple-input multiple-output free-space optical communication systems employing intensity modulation/direct detection and operating over strong atmospheric turbulence channels. Atmospheric-induced strong turbulence fading is modeled using the negative exponential distribution. For the considered system, an approximate yet accurate analytical expression for the average bit error probability is derived and an efficient method for its numerical evaluation is proposed. Numerically evaluated and computer simulation results are further provided to demonstrate the validity of the proposed mathematical analysis.
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Honda, Michitaka
2014-04-01
Several improvements were implemented in the edge method of presampled modulation transfer function measurements (MTFs). The estimation technique for edge angle was newly developed by applying an algorithm for principal components analysis. The error in the estimation was statistically confirmed to be less than 0.01 even in the presence of quantum noise. Secondly, the geometrical edge slope was approximated using a rationalized number, making it possible to obtain an oversampled edge response function (ESF) with equal intervals. Thirdly, the final MTFs were estimated using the average of multiple MTFs calculated for local areas. This averaging operation eliminates the errors caused by the rationalized approximation. Computer-simulated images were used to evaluate the accuracy of our method. The relative error between the estimated MTF and the theoretical MTF at the Nyquist frequency was less than 0.5% when the MTF was expressed as a sinc function. For MTFs representing an indirect detector and phase-contrast detector, good agreement was also observed for the estimated MTFs for each. The high accuracy of the MTF estimation was also confirmed, even for edge angles of around 10 degrees, which suggests the potential for simplification of the measurement conditions. The proposed method could be incorporated into an automated measurement technique using a software application.
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Analysis of a Shock-Associated Noise Prediction Model Using Measured Jet Far-Field Noise Data
NASA Technical Reports Server (NTRS)
Dahl, Milo D.; Sharpe, Jacob A.
2014-01-01
A code for predicting supersonic jet broadband shock-associated noise was assessed us- ing a database containing noise measurements of a jet issuing from a convergent nozzle. The jet was operated at 24 conditions covering six fully expanded Mach numbers with four total temperature ratios. To enable comparisons of the predicted shock-associated noise component spectra with data, the measured total jet noise spectra were separated into mixing noise and shock-associated noise component spectra. Comparisons between predicted and measured shock-associated noise component spectra were used to identify de ciencies in the prediction model. Proposed revisions to the model, based on a study of the overall sound pressure levels for the shock-associated noise component of the mea- sured data, a sensitivity analysis of the model parameters with emphasis on the de nition of the convection velocity parameter, and a least-squares t of the predicted to the mea- sured shock-associated noise component spectra, resulted in a new de nition for the source strength spectrum in the model. An error analysis showed that the average error in the predicted spectra was reduced by as much as 3.5 dB for the revised model relative to the average error for the original model.
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SU-F-T-313: Clinical Results of a New Customer Acceptance Test for Elekta VMAT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rusk, B; Fontenot, J
Purpose: To report the results of a customer acceptance test (CAT) for VMAT treatments for two matched Elekta linear accelerators. Methods: The CAT tests were performed on two clinically matched Elekta linear accelerators equipped with a 160-leaf MLC. Functional tests included performance checks of the control system during dynamic movements of the diaphragms, MLC, and gantry. Dosimetric tests included MLC picket fence tests at static and variable dose rates and a diaphragm alignment test, all performed using the on-board EPID. Additionally, beam symmetry during arc delivery was measured at the four cardinal angles for high and low dose rate modesmore » using a 2D detector array. Results of the dosimetric tests were analyzed using the VMAT CAT analysis tool. Results: Linear accelerator 1 (LN1) met all stated CAT tolerances. Linear accelerator 2 (LN2) passed the geometric, beam symmetry, and MLC position error tests but failed the relative dose average test for the diaphragm abutment and all three picket fence fields. Though peak doses in the abutment regions were consistent, the average dose was below the stated tolerance corresponding to a leaf junction that was too narrow. Despite this, no significant differences in patient specific VMAT quality assurance measured were observed between the accelerators and both passed monthly MLC quality assurance performed with the Hancock test. Conclusion: Results from the CAT showed LN2 with relative dose averages in the abutment regions of the diaphragm and MLC tests outside the tolerances resulting from differences in leaf gap distances. Tolerances of the dose average tests from the CAT may be small enough to detect MLC errors which do not significantly affect patient QA or the routine MLC tests.« less
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SU-F-T-465: Two Years of Radiotherapy Treatments Analyzed Through MLC Log Files
DOE Office of Scientific and Technical Information (OSTI.GOV)
Defoor, D; Kabat, C; Papanikolaou, N
Purpose: To present treatment statistics of a Varian Novalis Tx using more than 90,000 Varian Dynalog files collected over the past 2 years. Methods: Varian Dynalog files are recorded for every patient treated on our Varian Novalis Tx. The files are collected and analyzed daily to check interfraction agreement of treatment deliveries. This is accomplished by creating fluence maps from the data contained in the Dynalog files. From the Dynalog files we have also compiled statistics for treatment delivery times, MLC errors, gantry errors and collimator errors. Results: The mean treatment time for VMAT patients was 153 ± 86 secondsmore » while the mean treatment time for step & shoot was 256 ± 149 seconds. Patient’s treatment times showed a variation of 0.4% over there treatment course for VMAT and 0.5% for step & shoot. The average field sizes were 40 cm2 and 26 cm2 for VMAT and step & shoot respectively. VMAT beams contained and average overall leaf travel of 34.17 meters and step & shoot beams averaged less than half of that at 15.93 meters. When comparing planned and delivered fluence maps generated using the Dynalog files VMAT plans showed an average gamma passing percentage of 99.85 ± 0.47. Step & shoot plans showed an average gamma passing percentage of 97.04 ± 0.04. 5.3% of beams contained an MLC error greater than 1 mm and 2.4% had an error greater than 2mm. The mean gantry speed for VMAT plans was 1.01 degrees/s with a maximum of 6.5 degrees/s. Conclusion: Varian Dynalog files are useful for monitoring machine performance treatment parameters. The Dynalog files have shown that the performance of the Novalis Tx is consistent over the course of a patients treatment with only slight variations in patient treatment times and a low rate of MLC errors.« less
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Maradzike, Elvis; Gidofalvi, Gergely; Turney, Justin M; Schaefer, Henry F; DePrince, A Eugene
2017-09-12
Analytic energy gradients are presented for a variational two-electron reduced-density-matrix (2-RDM)-driven complete active space self-consistent field (CASSCF) method. The active-space 2-RDM is determined using a semidefinite programing (SDP) algorithm built upon an augmented Lagrangian formalism. Expressions for analytic gradients are simplified by the fact that the Lagrangian is stationary with respect to variations in both the primal and the dual solutions to the SDP problem. Orbital response contributions to the gradient are identical to those that arise in conventional CASSCF methods in which the electronic structure of the active space is described by a full configuration interaction (CI) wave function. We explore the relative performance of variational 2-RDM (v2RDM)- and CI-driven CASSCF for the equilibrium geometries of 20 small molecules. When enforcing two-particle N-representability conditions, full-valence v2RDM-CASSCF-optimized bond lengths display a mean unsigned error of 0.0060 Å and a maximum unsigned error of 0.0265 Å, relative to those obtained from full-valence CI-CASSCF. When enforcing partial three-particle N-representability conditions, the mean and maximum unsigned errors are reduced to only 0.0006 and 0.0054 Å, respectively. For these same molecules, full-valence v2RDM-CASSCF bond lengths computed in the cc-pVQZ basis set deviate from experimentally determined ones on average by 0.017 and 0.011 Å when enforcing two- and three-particle conditions, respectively, whereas CI-CASSCF displays an average deviation of 0.010 Å. The v2RDM-CASSCF approach with two-particle conditions is also applied to the equilibrium geometry of pentacene; optimized bond lengths deviate from those derived from experiment, on average, by 0.015 Å when using a cc-pVDZ basis set and a (22e,22o) active space.
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NASA Technical Reports Server (NTRS)
Piersol, Allan G.
1991-01-01
Analytical expressions have been derived to describe the mean square error in the estimation of the maximum rms value computed from a step-wise (or running) time average of a nonstationary random signal. These analytical expressions have been applied to the problem of selecting the optimum averaging times that will minimize the total mean square errors in estimates of the maximum sound pressure levels measured inside the Titan IV payload fairing (PLF) and the Space Shuttle payload bay (PLB) during lift-off. Based on evaluations of typical Titan IV and Space Shuttle launch data, it has been determined that the optimum averaging times for computing the maximum levels are (1) T (sub o) = 1.14 sec for the maximum overall level, and T(sub oi) = 4.88 f (sub i) (exp -0.2) sec for the maximum 1/3 octave band levels inside the Titan IV PLF, and (2) T (sub o) = 1.65 sec for the maximum overall level, and T (sub oi) = 7.10 f (sub i) (exp -0.2) sec for the maximum 1/3 octave band levels inside the Space Shuttle PLB, where f (sub i) is the 1/3 octave band center frequency. However, the results for both vehicles indicate that the total rms error in the maximum level estimates will be within 25 percent the minimum error for all averaging times within plus or minus 50 percent of the optimum averaging time, so a precise selection of the exact optimum averaging time is not critical. Based on these results, linear averaging times (T) are recommended for computing the maximum sound pressure level during lift-off.
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The Performance of Noncoherent Orthogonal M-FSK in the Presence of Timing and Frequency Errors
NASA Technical Reports Server (NTRS)
Hinedi, Sami; Simon, Marvin K.; Raphaeli, Dan
1993-01-01
Practical M-FSK systems experience a combination of time and frequency offsets (errors). This paper assesses the deleterious effect of these offsets, first individually and then combined, on the average bit error probability performance of the system.
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The Whole Warps the Sum of Its Parts.
Corbett, Jennifer E
2017-01-01
The efficiency of averaging properties of sets without encoding redundant details is analogous to gestalt proposals that perception is parsimoniously organized as a function of recurrent order in the world. This similarity suggests that grouping and averaging are part of a broader set of strategies allowing the visual system to circumvent capacity limitations. To examine how gestalt grouping affects the manner in which information is averaged and remembered, I compared the error in observers' adjustments of remembered sizes of individual circles in two different mean-size sets defined by similarity, proximity, connectedness, or a common region. Overall, errors were more similar within the same gestalt-defined groups than between different gestalt-defined groups, such that the remembered sizes of individual circles were biased toward the mean size of their respective gestalt-defined groups. These results imply that gestalt grouping facilitates perceptual averaging to minimize the error with which individual items are encoded, thereby optimizing the efficiency of visual short-term memory.
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Computation of Standard Errors
Dowd, Bryan E; Greene, William H; Norton, Edward C
2014-01-01
Objectives We discuss the problem of computing the standard errors of functions involving estimated parameters and provide the relevant computer code for three different computational approaches using two popular computer packages. Study Design We show how to compute the standard errors of several functions of interest: the predicted value of the dependent variable for a particular subject, and the effect of a change in an explanatory variable on the predicted value of the dependent variable for an individual subject and average effect for a sample of subjects. Empirical Application Using a publicly available dataset, we explain three different methods of computing standard errors: the delta method, Krinsky–Robb, and bootstrapping. We provide computer code for Stata 12 and LIMDEP 10/NLOGIT 5. Conclusions In most applications, choice of the computational method for standard errors of functions of estimated parameters is a matter of convenience. However, when computing standard errors of the sample average of functions that involve both estimated parameters and nonstochastic explanatory variables, it is important to consider the sources of variation in the function's values. PMID:24800304
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NASA Astrophysics Data System (ADS)
Valle, G.; Dell'Omodarme, M.; Prada Moroni, P. G.; Degl'Innocenti, S.
2018-01-01
Aims: We aim to perform a theoretical evaluation of the impact of the mass loss indetermination on asteroseismic grid based estimates of masses, radii, and ages of stars in the red giant branch (RGB) phase. Methods: We adopted the SCEPtER pipeline on a grid spanning the mass range [0.8; 1.8] M⊙. As observational constraints, we adopted the star effective temperatures, the metallicity [Fe/H], the average large frequency spacing Δν, and the frequency of maximum oscillation power νmax. The mass loss was modelled following a Reimers parametrization with the two different efficiencies η = 0.4 and η = 0.8. Results: In the RGB phase, the average random relative error (owing only to observational uncertainty) on mass and age estimates is about 8% and 30% respectively. The bias in mass and age estimates caused by the adoption of a wrong mass loss parameter in the recovery is minor for the vast majority of the RGB evolution. The biases get larger only after the RGB bump. In the last 2.5% of the RGB lifetime the error on the mass determination reaches 6.5% becoming larger than the random error component in this evolutionary phase. The error on the age estimate amounts to 9%, that is, equal to the random error uncertainty. These results are independent of the stellar metallicity [Fe/H] in the explored range. Conclusions: Asteroseismic-based estimates of stellar mass, radius, and age in the RGB phase can be considered mass loss independent within the range (η ∈ [0.0,0.8]) as long as the target is in an evolutionary phase preceding the RGB bump.
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Land Surface Temperature Measurements form EOS MODIS Data
NASA Technical Reports Server (NTRS)
Wan, Zhengming
1996-01-01
We have developed a physics-based land-surface temperature (LST) algorithm for simultaneously retrieving surface band-averaged emissivities and temperatures from day/night pairs of MODIS (Moderate Resolution Imaging Spectroradiometer) data in seven thermal infrared bands. The set of 14 nonlinear equations in the algorithm is solved with the statistical regression method and the least-squares fit method. This new LST algorithm was tested with simulated MODIS data for 80 sets of band-averaged emissivities calculated from published spectral data of terrestrial materials in wide ranges of atmospheric and surface temperature conditions. Comprehensive sensitivity and error analysis has been made to evaluate the performance of the new LST algorithm and its dependence on variations in surface emissivity and temperature, upon atmospheric conditions, as well as the noise-equivalent temperature difference (NE(Delta)T) and calibration accuracy specifications of the MODIS instrument. In cases with a systematic calibration error of 0.5%, the standard deviations of errors in retrieved surface daytime and nighttime temperatures fall between 0.4-0.5 K over a wide range of surface temperatures for mid-latitude summer conditions. The standard deviations of errors in retrieved emissivities in bands 31 and 32 (in the 10-12.5 micrometer IR spectral window region) are 0.009, and the maximum error in retrieved LST values falls between 2-3 K. Several issues related to the day/night LST algorithm (uncertainties in the day/night registration and in surface emissivity changes caused by dew occurrence, and the cloud cover) have been investigated. The LST algorithms have been validated with MODIS Airborne Simulator (MAS) dada and ground-based measurement data in two field campaigns conducted in Railroad Valley playa, NV in 1995 and 1996. The MODIS LST version 1 software has been delivered.
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Neutron-Star Radius from a Population of Binary Neutron Star Mergers.
Bose, Sukanta; Chakravarti, Kabir; Rezzolla, Luciano; Sathyaprakash, B S; Takami, Kentaro
2018-01-19
We show how gravitational-wave observations with advanced detectors of tens to several tens of neutron-star binaries can measure the neutron-star radius with an accuracy of several to a few percent, for mass and spatial distributions that are realistic, and with none of the sources located within 100 Mpc. We achieve such an accuracy by combining measurements of the total mass from the inspiral phase with those of the compactness from the postmerger oscillation frequencies. For estimating the measurement errors of these frequencies, we utilize analytical fits to postmerger numerical relativity waveforms in the time domain, obtained here for the first time, for four nuclear-physics equations of state and a couple of values for the mass. We further exploit quasiuniversal relations to derive errors in compactness from those frequencies. Measuring the average radius to well within 10% is possible for a sample of 100 binaries distributed uniformly in volume between 100 and 300 Mpc, so long as the equation of state is not too soft or the binaries are not too heavy. We also give error estimates for the Einstein Telescope.
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Performance appraisal of VAS radiometry for GOES-4, -5 and -6
NASA Technical Reports Server (NTRS)
Chesters, D.; Robinson, W. D.
1983-01-01
The first three VISSR Atmospheric Sounders (VAS) were launched on GOES-4, -5, and -6 in 1980, 1981 and 1983. Postlaunch radiometric performance is assessed for noise, biases, registration and reliability, with special attention to calibration and problems in the data processing chain. The postlaunch performance of the VAS radiometer meets its prelaunch design specifications, particularly those related to image formation and noise reduction. The best instrument is carried on GOES-5, currently operational as GOES-EAST. Single sample noise is lower than expected, especially for the small longwave and large shortwave detectors. Detector to detector offsets are correctable to within the resolution limits of the instrument. Truncation, zero point and droop errors are insignificant. Absolute calibration errors, estimated from HIRS and from radiation transfer calculations, indicate moderate, but stable biases. Relative calibration errors from scanline to scanline are noticeable, but meet sounding requirements for temporarily and spatially averaged sounding fields of view. The VAS instrument is a potentially useful radiometer for mesoscale sounding operations. Image quality is very good. Soundings derived from quality controlled data meet prelaunch requirements when calculated with noise and bias resistant algorithms.
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Typing mineral deposits using their grades and tonnages in an artificial neural network
Singer, Donald A.; Kouda, Ryoichi
2003-01-01
A test of the ability of a probabilistic neural network to classify deposits into types on the basis of deposit tonnage and average Cu, Mo, Ag, Au, Zn, and Pb grades is conducted. The purpose is to examine whether this type of system might serve as a basis for integrating geoscience information available in large mineral databases to classify sites by deposit type. Benefits of proper classification of many sites in large regions are relatively rapid identification of terranes permissive for deposit types and recognition of specific sites perhaps worthy of exploring further.Total tonnages and average grades of 1,137 well-explored deposits identified in published grade and tonnage models representing 13 deposit types were used to train and test the network. Tonnages were transformed by logarithms and grades by square roots to reduce effects of skewness. All values were scaled by subtracting the variable's mean and dividing by its standard deviation. Half of the deposits were selected randomly to be used in training the probabilistic neural network and the other half were used for independent testing. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class (type) and each variable (grade or tonnage).Deposit types were selected to challenge the neural network. For many types, tonnages or average grades are significantly different from other types, but individual deposits may plot in the grade and tonnage space of more than one type. Porphyry Cu, porphyry Cu-Au, and porphyry Cu-Mo types have similar tonnages and relatively small differences in grades. Redbed Cu deposits typically have tonnages that could be confused with porphyry Cu deposits, also contain Cu and, in some situations, Ag. Cyprus and kuroko massive sulfide types have about the same tonnages. Cu, Zn, Ag, and Au grades. Polymetallic vein, sedimentary exhalative Zn-Pb, and Zn-Pb skarn types contain many of the same metals. Sediment-hosted Au, Comstock Au-Ag, and low-sulfide Au-quartz vein types are principally Au deposits with differing amounts of Ag.Given the intent to test the neural network under the most difficult conditions, an overall 75% agreement between the experts and the neural network is considered excellent. Among the largestclassification errors are skarn Zn-Pb and Cyprus massive sulfide deposits classed by the neuralnetwork as kuroko massive sulfides—24 and 63% error respectively. Other large errors are the classification of 92% of porphyry Cu-Mo as porphyry Cu deposits. Most of the larger classification errors involve 25 or fewer training deposits, suggesting that some errors might be the result of small sample size. About 91% of the gold deposit types were classed properly and 98% of porphyry Cu deposits were classes as some type of porphyry Cu deposit. An experienced economic geologist would not make many of the classification errors that were made by the neural network because the geologic settings of deposits would be used to reduce errors. In a separate test, the probabilistic neural network correctly classed 93% of 336 deposits in eight deposit types when trained with presence or absence of 58 minerals and six generalized rock types. The overall success rate of the probabilistic neural network when trained on tonnage and average grades would probably be more than 90% with additional information on the presence of a few rock types.
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Mori, Shinichiro; Shibayama, Kouichi; Tanimoto, Katsuyuki; Kumagai, Motoki; Matsuzaki, Yuka; Furukawa, Takuji; Inaniwa, Taku; Shirai, Toshiyuki; Noda, Koji; Tsuji, Hiroshi; Kamada, Tadashi
2012-09-01
Our institute has constructed a new treatment facility for carbon ion scanning beam therapy. The first clinical trials were successfully completed at the end of November 2011. To evaluate patient setup accuracy, positional errors between the reference Computed Tomography (CT) scan and final patient setup images were calculated using 2D-3D registration software. Eleven patients with tumors of the head and neck, prostate and pelvis receiving carbon ion scanning beam treatment participated. The patient setup process takes orthogonal X-ray flat panel detector (FPD) images and the therapists adjust the patient table position in six degrees of freedom to register the reference position by manual or auto- (or both) registration functions. We calculated residual positional errors with the 2D-3D auto-registration function using the final patient setup orthogonal FPD images and treatment planning CT data. Residual error averaged over all patients in each fraction decreased from the initial to the last treatment fraction [1.09 mm/0.76° (averaged in the 1st and 2nd fractions) to 0.77 mm/0.61° (averaged in the 15th and 16th fractions)]. 2D-3D registration calculation time was 8.0 s on average throughout the treatment course. Residual errors in translation and rotation averaged over all patients as a function of date decreased with the passage of time (1.6 mm/1.2° in May 2011 to 0.4 mm/0.2° in December 2011). This retrospective residual positional error analysis shows that the accuracy of patient setup during the first clinical trials of carbon ion beam scanning therapy was good and improved with increasing therapist experience.
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Modeling transit bus fuel consumption on the basis of cycle properties.
Delgado, Oscar F; Clark, Nigel N; Thompson, Gregory J
2011-04-01
A method exists to predict heavy-duty vehicle fuel economy and emissions over an "unseen" cycle or during unseen on-road activity on the basis of fuel consumption and emissions data from measured chassis dynamometer test cycles and properties (statistical parameters) of those cycles. No regression is required for the method, which relies solely on the linear association of vehicle performance with cycle properties. This method has been advanced and examined using previously published heavy-duty truck data gathered using the West Virginia University heavy-duty chassis dynamometer with the trucks exercised over limited test cycles. In this study, data were available from a Washington Metropolitan Area Transit Authority emission testing program conducted in 2006. Chassis dynamometer data from two conventional diesel buses, two compressed natural gas buses, and one hybrid diesel bus were evaluated using an expanded driving cycle set of 16 or 17 different driving cycles. Cycle properties and vehicle fuel consumption measurements from three baseline cycles were selected to generate a linear model and then to predict unseen fuel consumption over the remaining 13 or 14 cycles. Average velocity, average positive acceleration, and number of stops per distance were found to be the desired cycle properties for use in the model. The methodology allowed for the prediction of fuel consumption with an average error of 8.5% from vehicles operating on a diverse set of chassis dynamometer cycles on the basis of relatively few experimental measurements. It was found that the data used for prediction should be acquired from a set that must include an idle cycle along with a relatively slow transient cycle and a relatively high speed cycle. The method was also applied to oxides of nitrogen prediction and was found to have less predictive capability than for fuel consumption with an average error of 20.4%.
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Waltemeyer, Scott D.
2006-01-01
Estimates of the magnitude and frequency of peak discharges are necessary for the reliable flood-hazard mapping in the Navajo Nation in Arizona, Utah, Colorado, and New Mexico. The Bureau of Indian Affairs, U.S. Army Corps of Engineers, and Navajo Nation requested that the U.S. Geological Survey update estimates of peak discharge magnitude for gaging stations in the region and update regional equations for estimation of peak discharge and frequency at ungaged sites. Equations were developed for estimating the magnitude of peak discharges for recurrence intervals of 2, 5, 10, 25, 50, 100, and 500 years at ungaged sites using data collected through 1999 at 146 gaging stations, an additional 13 years of peak-discharge data since a 1997 investigation, which used gaging-station data through 1986. The equations for estimation of peak discharges at ungaged sites were developed for flood regions 8, 11, high elevation, and 6 and are delineated on the basis of the hydrologic codes from the 1997 investigation. Peak discharges for selected recurrence intervals were determined at gaging stations by fitting observed data to a log-Pearson Type III distribution with adjustments for a low-discharge threshold and a zero skew coefficient. A low-discharge threshold was applied to frequency analysis of 82 of the 146 gaging stations. This application provides an improved fit of the log-Pearson Type III frequency distribution. Use of the low-discharge threshold generally eliminated the peak discharge having a recurrence interval of less than 1.4 years in the probability-density function. Within each region, logarithms of the peak discharges for selected recurrence intervals were related to logarithms of basin and climatic characteristics using stepwise ordinary least-squares regression techniques for exploratory data analysis. Generalized least-squares regression techniques, an improved regression procedure that accounts for time and spatial sampling errors, then was applied to the same data used in the ordinary least-squares regression analyses. The average standard error of prediction for a peak discharge have a recurrence interval of 100-years for region 8 was 53 percent (average) for the 100-year flood. The average standard of prediction, which includes average sampling error and average standard error of regression, ranged from 45 to 83 percent for the 100-year flood. Estimated standard error of prediction for a hybrid method for region 11 was large in the 1997 investigation. No distinction of floods produced from a high-elevation region was presented in the 1997 investigation. Overall, the equations based on generalized least-squares regression techniques are considered to be more reliable than those in the 1997 report because of the increased length of record and improved GIS method. Techniques for transferring flood-frequency relations to ungaged sites on the same stream can be estimated at an ungaged site by a direct application of the regional regression equation or at an ungaged site on a stream that has a gaging station upstream or downstream by using the drainage-area ratio and the drainage-area exponent from the regional regression equation of the respective region.
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Pairwise comparisons and visual perceptions of equal area polygons.
Adamic, P; Babiy, V; Janicki, R; Kakiashvili, T; Koczkodaj, W W; Tadeusiewicz, R
2009-02-01
The number of studies related to visual perception has been plentiful in recent years. Participants rated the areas of five randomly generated shapes of equal area, using a reference unit area that was displayed together with the shapes. Respondents were 179 university students from Canada and Poland. The average error estimated by respondents using the unit square was 25.75%. The error was substantially decreased to 5.51% when the shapes were compared to one another in pairs. This gain of 20.24% for this two-dimensional experiment was substantially better than the 11.78% gain reported in the previous one-dimensional experiments. This is the first statistically sound two-dimensional experiment demonstrating that pairwise comparisons improve accuracy.
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Checking-up of optical graduated rules by laser interferometry
NASA Astrophysics Data System (ADS)
Miron, Nicolae P.; Sporea, Dan G.
1996-05-01
The main aspects related to the operating principle, design, and implementation of high-productivity equipment for checking-up the graduation accuracy of optical graduated rules used as a length reference in optical measuring instruments for precision machine tools are presented. The graduation error checking-up is done with a Michelson interferometer as a length transducer. The instrument operation is managed by a computer, which controls the equipment, data acquisition, and processing. The evaluation is performed for rule lengths from 100 to 3000 mm, with a checking-up error less than 2 micrometers/m. The checking-up time is about 15 min for a 1000-mm rule, with averaging over four measurements.
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Cost effectiveness of the stream-gaging program in South Carolina
Barker, A.C.; Wright, B.C.; Bennett, C.S.
1985-01-01
The cost effectiveness of the stream-gaging program in South Carolina was documented for the 1983 water yr. Data uses and funding sources were identified for the 76 continuous stream gages currently being operated in South Carolina. The budget of $422,200 for collecting and analyzing streamflow data also includes the cost of operating stage-only and crest-stage stations. The streamflow records for one stream gage can be determined by alternate, less costly methods, and should be discontinued. The remaining 75 stations should be maintained in the program for the foreseeable future. The current policy for the operation of the 75 stations including the crest-stage and stage-only stations would require a budget of $417,200/yr. The average standard error of estimation of streamflow records is 16.9% for the present budget with missing record included. However, the standard error of estimation would decrease to 8.5% if complete streamflow records could be obtained. It was shown that the average standard error of estimation of 16.9% could be obtained at the 75 sites with a budget of approximately $395,000 if the gaging resources were redistributed among the gages. A minimum budget of $383,500 is required to operate the program; a budget less than this does not permit proper service and maintenance of the gages and recorders. At the minimum budget, the average standard error is 18.6%. The maximum budget analyzed was $850,000, which resulted in an average standard error of 7.6 %. (Author 's abstract)
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Estimation After a Group Sequential Trial.
Milanzi, Elasma; Molenberghs, Geert; Alonso, Ariel; Kenward, Michael G; Tsiatis, Anastasios A; Davidian, Marie; Verbeke, Geert
2015-10-01
Group sequential trials are one important instance of studies for which the sample size is not fixed a priori but rather takes one of a finite set of pre-specified values, dependent on the observed data. Much work has been devoted to the inferential consequences of this design feature. Molenberghs et al (2012) and Milanzi et al (2012) reviewed and extended the existing literature, focusing on a collection of seemingly disparate, but related, settings, namely completely random sample sizes, group sequential studies with deterministic and random stopping rules, incomplete data, and random cluster sizes. They showed that the ordinary sample average is a viable option for estimation following a group sequential trial, for a wide class of stopping rules and for random outcomes with a distribution in the exponential family. Their results are somewhat surprising in the sense that the sample average is not optimal, and further, there does not exist an optimal, or even, unbiased linear estimator. However, the sample average is asymptotically unbiased, both conditionally upon the observed sample size as well as marginalized over it. By exploiting ignorability they showed that the sample average is the conventional maximum likelihood estimator. They also showed that a conditional maximum likelihood estimator is finite sample unbiased, but is less efficient than the sample average and has the larger mean squared error. Asymptotically, the sample average and the conditional maximum likelihood estimator are equivalent. This previous work is restricted, however, to the situation in which the the random sample size can take only two values, N = n or N = 2 n . In this paper, we consider the more practically useful setting of sample sizes in a the finite set { n 1 , n 2 , …, n L }. It is shown that the sample average is then a justifiable estimator , in the sense that it follows from joint likelihood estimation, and it is consistent and asymptotically unbiased. We also show why simulations can give the false impression of bias in the sample average when considered conditional upon the sample size. The consequence is that no corrections need to be made to estimators following sequential trials. When small-sample bias is of concern, the conditional likelihood estimator provides a relatively straightforward modification to the sample average. Finally, it is shown that classical likelihood-based standard errors and confidence intervals can be applied, obviating the need for technical corrections.
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Unforced errors and error reduction in tennis
Brody, H
2006-01-01
Only at the highest level of tennis is the number of winners comparable to the number of unforced errors. As the average player loses many more points due to unforced errors than due to winners by an opponent, if the rate of unforced errors can be reduced, it should lead to an increase in points won. This article shows how players can improve their game by understanding and applying the laws of physics to reduce the number of unforced errors. PMID:16632568
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Estimates of the Modeling Error of the α -Models of Turbulence in Two and Three Space Dimensions
NASA Astrophysics Data System (ADS)
Dunca, Argus A.
2017-12-01
This report investigates the convergence rate of the weak solutions w^{α } of the Leray-α , modified Leray-α , Navier-Stokes-α and the zeroth ADM turbulence models to a weak solution u of the Navier-Stokes equations. It is assumed that this weak solution u of the NSE belongs to the space L^4(0, T; H^1) . It is shown that under this regularity condition the error u-w^{α } is O(α ) in the norms L^2(0, T; H^1) and L^{∞}(0, T; L^2) , thus improving related known results. It is also shown that the averaged error \\overline{u}-\\overline{w^{α }} is higher order, O(α ^{1.5}) , in the same norms, therefore the α -regularizations considered herein approximate better filtered flow structures than the exact (unfiltered) flow velocities.
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Pole of rotating analysis of present-day Juan de Fuca plate motion
NASA Technical Reports Server (NTRS)
Nishimura, C.; Wilson, D. S.; Hey, R. N.
1984-01-01
Convergence rates between the Juan de Fuca and North American plates are calculated by means of their relative, present-day pole of rotation. A method of calculating the propagation of errors in addition to the instantaneous poles of rotation is also formulated and applied to determine the Euler pole for Pacific-Juan de Fuca. This pole is vectorially added to previously published poles for North America-Pacific and 'hot spot'-Pacific to obtain North America-Juan de Fuca and 'hot spot'-Juan de Fuca, respectively. The errors associated with these resultant poles are determined by propagating the errors of the two summed angular velocity vectors. Under the assumption that hot spots are fixed with respect to a mantle reference frame, the average absolute velocity of the Juan de Puca plate is computed at approximately 15 mm/yr, thereby making it the slowest-moving of the oceanic plates.
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Cost effectiveness of the US Geological Survey stream-gaging program in Alabama
Jeffcoat, H.H.
1987-01-01
A study of the cost effectiveness of the stream gaging program in Alabama identified data uses and funding sources for 72 surface water stations (including dam stations, slope stations, and continuous-velocity stations) operated by the U.S. Geological Survey in Alabama with a budget of $393,600. Of these , 58 gaging stations were used in all phases of the analysis at a funding level of $328,380. For the current policy of operation of the 58-station program, the average standard error of estimation of instantaneous discharge is 29.3%. This overall level of accuracy can be maintained with a budget of $319,800 by optimizing routes and implementing some policy changes. The maximum budget considered in the analysis was $361,200, which gave an average standard error of estimation of 20.6%. The minimum budget considered was $299,360, with an average standard error of estimation of 36.5%. The study indicates that a major source of error in the stream gaging records is lost or missing data that are the result of streamside equipment failure. If perfect equipment were available, the standard error in estimating instantaneous discharge under the current program and budget could be reduced to 18.6%. This can also be interpreted to mean that the streamflow data records have a standard error of this magnitude during times when the equipment is operating properly. (Author 's abstract)
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Kumar, K Vasanth; Porkodi, K; Rocha, F
2008-01-15
A comparison of linear and non-linear regression method in selecting the optimum isotherm was made to the experimental equilibrium data of basic red 9 sorption by activated carbon. The r(2) was used to select the best fit linear theoretical isotherm. In the case of non-linear regression method, six error functions namely coefficient of determination (r(2)), hybrid fractional error function (HYBRID), Marquardt's percent standard deviation (MPSD), the average relative error (ARE), sum of the errors squared (ERRSQ) and sum of the absolute errors (EABS) were used to predict the parameters involved in the two and three parameter isotherms and also to predict the optimum isotherm. Non-linear regression was found to be a better way to obtain the parameters involved in the isotherms and also the optimum isotherm. For two parameter isotherm, MPSD was found to be the best error function in minimizing the error distribution between the experimental equilibrium data and predicted isotherms. In the case of three parameter isotherm, r(2) was found to be the best error function to minimize the error distribution structure between experimental equilibrium data and theoretical isotherms. The present study showed that the size of the error function alone is not a deciding factor to choose the optimum isotherm. In addition to the size of error function, the theory behind the predicted isotherm should be verified with the help of experimental data while selecting the optimum isotherm. A coefficient of non-determination, K(2) was explained and was found to be very useful in identifying the best error function while selecting the optimum isotherm.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Falconer, David A.; Tiwari, Sanjiv K.; Moore, Ronald L.
Projection errors limit the use of vector magnetograms of active regions (ARs) far from the disk center. In this Letter, for ARs observed up to 60° from the disk center, we demonstrate a method for measuring and reducing the projection error in the magnitude of any whole-AR parameter that is derived from a vector magnetogram that has been deprojected to the disk center. The method assumes that the center-to-limb curve of the average of the parameter’s absolute values, measured from the disk passage of a large number of ARs and normalized to each AR’s absolute value of the parameter atmore » central meridian, gives the average fractional projection error at each radial distance from the disk center. To demonstrate the method, we use a large set of large-flux ARs and apply the method to a whole-AR parameter that is among the simplest to measure: whole-AR magnetic flux. We measure 30,845 SDO /Helioseismic and Magnetic Imager vector magnetograms covering the disk passage of 272 large-flux ARs, each having whole-AR flux >10{sup 22} Mx. We obtain the center-to-limb radial-distance run of the average projection error in measured whole-AR flux from a Chebyshev fit to the radial-distance plot of the 30,845 normalized measured values. The average projection error in the measured whole-AR flux of an AR at a given radial distance is removed by multiplying the measured flux by the correction factor given by the fit. The correction is important for both the study of the evolution of ARs and for improving the accuracy of forecasts of an AR’s major flare/coronal mass ejection productivity.« less
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Cost-effectiveness of the stream-gaging program in Kentucky
Ruhl, K.J.
1989-01-01
This report documents the results of a study of the cost-effectiveness of the stream-gaging program in Kentucky. The total surface-water program includes 97 daily-discharge stations , 12 stage-only stations, and 35 crest-stage stations and is operated on a budget of $950,700. One station used for research lacks adequate source of funding and should be discontinued when the research ends. Most stations in the network are multiple-use with 65 stations operated for the purpose of defining hydrologic systems, 48 for project operation, 47 for definition of regional hydrology, and 43 for hydrologic forecasting purposes. Eighteen stations support water quality monitoring activities, one station is used for planning and design, and one station is used for research. The average standard error of estimation of streamflow records was determined only for stations in the Louisville Subdistrict. Under current operating policy, with a budget of $223,500, the average standard error of estimation is 28.5%. Altering the travel routes and measurement frequency to reduce the amount of lost stage record would allow a slight decrease in standard error to 26.9%. The results indicate that the collection of streamflow records in the Louisville Subdistrict is cost effective in its present mode of operation. In the Louisville Subdistrict, a minimum budget of $214,200 is required to operate the current network at an average standard error of 32.7%. A budget less than this does not permit proper service and maintenance of the gages and recorders. The maximum budget analyzed was $268,200, which would result in an average standard error of 16.9% indicating that if the budget was increased by 20%, the percent standard error would be reduced 40 %. (USGS)
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Estimation of lipids and lean mass of migrating sandpipers
Skagen, Susan K.; Knopf, Fritz L.; Cade, Brian S.
1993-01-01
Estimation of lean mass and lipid levels in birds involves the derivation of predictive equations that relate morphological measurements and, more recently, total body electrical conductivity (TOBEC) indices to known lean and lipid masses. Using cross-validation techniques, we evaluated the ability of several published and new predictive equations to estimate lean and lipid mass of Semipalmated Sandpipers (Calidris pusilla) and White-rumped Sandpipers (C. fuscicollis). We also tested ideas of Morton et al. (1991), who stated that current statistical approaches to TOBEC methodology misrepresent precision in estimating body fat. Three published interspecific equations using TOBEC indices predicted lean and lipid masses of our sample of birds with average errors of 8-28% and 53-155%, respectively. A new two-species equation relating lean mass and TOBEC indices revealed average errors of 4.6% and 23.2% in predicting lean and lipid mass, respectively. New intraspecific equations that estimate lipid mass directly from body mass, morphological measurements, and TOBEC indices yielded about a 13% error in lipid estimates. Body mass and morphological measurements explained a substantial portion of the variance (about 90%) in fat mass of both species. Addition of TOBEC indices improved the predictive model more for the smaller than for the larger sandpiper. TOBEC indices explained an additional 7.8% and 2.6% of the variance in fat mass and reduced the minimum breadth of prediction intervals by 0.95 g (32%) and 0.39 g (13%) for Semipalmated and White-rumped Sandpipers, respectively. The breadth of prediction intervals for models used to predict fat levels of individual birds must be considered when interpreting the resultant lipid estimates.
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Investigating three types of continuous auditory feedback in visuo-manual tracking.
Boyer, Éric O; Bevilacqua, Frédéric; Susini, Patrick; Hanneton, Sylvain
2017-03-01
The use of continuous auditory feedback for motor control and learning is still understudied and deserves more attention regarding fundamental mechanisms and applications. This paper presents the results of three experiments studying the contribution of task-, error-, and user-related sonification to visuo-manual tracking and assessing its benefits on sensorimotor learning. First results show that sonification can help decreasing the tracking error, as well as increasing the energy in participant's movement. In the second experiment, when alternating feedback presence, the user-related sonification did not show feedback dependency effects, contrary to the error and task-related feedback. In the third experiment, a reduced exposure of 50% diminished the positive effect of sonification on performance, whereas the increase of the average energy with sound was still significant. In a retention test performed on the next day without auditory feedback, movement energy was still superior for the groups previously trained with the feedback. Although performance was not affected by sound, a learning effect was measurable in both sessions and the user-related group improved its performance also in the retention test. These results confirm that a continuous auditory feedback can be beneficial for movement training and also show an interesting effect of sonification on movement energy. User-related sonification can prevent feedback dependency and increase retention. Consequently, sonification of the user's own motion appears as a promising solution to support movement learning with interactive feedback.
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Comparing interval estimates for small sample ordinal CFA models
Natesan, Prathiba
2015-01-01
Robust maximum likelihood (RML) and asymptotically generalized least squares (AGLS) methods have been recommended for fitting ordinal structural equation models. Studies show that some of these methods underestimate standard errors. However, these studies have not investigated the coverage and bias of interval estimates. An estimate with a reasonable standard error could still be severely biased. This can only be known by systematically investigating the interval estimates. The present study compares Bayesian, RML, and AGLS interval estimates of factor correlations in ordinal confirmatory factor analysis models (CFA) for small sample data. Six sample sizes, 3 factor correlations, and 2 factor score distributions (multivariate normal and multivariate mildly skewed) were studied. Two Bayesian prior specifications, informative and relatively less informative were studied. Undercoverage of confidence intervals and underestimation of standard errors was common in non-Bayesian methods. Underestimated standard errors may lead to inflated Type-I error rates. Non-Bayesian intervals were more positive biased than negatively biased, that is, most intervals that did not contain the true value were greater than the true value. Some non-Bayesian methods had non-converging and inadmissible solutions for small samples and non-normal data. Bayesian empirical standard error estimates for informative and relatively less informative priors were closer to the average standard errors of the estimates. The coverage of Bayesian credibility intervals was closer to what was expected with overcoverage in a few cases. Although some Bayesian credibility intervals were wider, they reflected the nature of statistical uncertainty that comes with the data (e.g., small sample). Bayesian point estimates were also more accurate than non-Bayesian estimates. The results illustrate the importance of analyzing coverage and bias of interval estimates, and how ignoring interval estimates can be misleading. Therefore, editors and policymakers should continue to emphasize the inclusion of interval estimates in research. PMID:26579002
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Comparing interval estimates for small sample ordinal CFA models.
Natesan, Prathiba
2015-01-01
Robust maximum likelihood (RML) and asymptotically generalized least squares (AGLS) methods have been recommended for fitting ordinal structural equation models. Studies show that some of these methods underestimate standard errors. However, these studies have not investigated the coverage and bias of interval estimates. An estimate with a reasonable standard error could still be severely biased. This can only be known by systematically investigating the interval estimates. The present study compares Bayesian, RML, and AGLS interval estimates of factor correlations in ordinal confirmatory factor analysis models (CFA) for small sample data. Six sample sizes, 3 factor correlations, and 2 factor score distributions (multivariate normal and multivariate mildly skewed) were studied. Two Bayesian prior specifications, informative and relatively less informative were studied. Undercoverage of confidence intervals and underestimation of standard errors was common in non-Bayesian methods. Underestimated standard errors may lead to inflated Type-I error rates. Non-Bayesian intervals were more positive biased than negatively biased, that is, most intervals that did not contain the true value were greater than the true value. Some non-Bayesian methods had non-converging and inadmissible solutions for small samples and non-normal data. Bayesian empirical standard error estimates for informative and relatively less informative priors were closer to the average standard errors of the estimates. The coverage of Bayesian credibility intervals was closer to what was expected with overcoverage in a few cases. Although some Bayesian credibility intervals were wider, they reflected the nature of statistical uncertainty that comes with the data (e.g., small sample). Bayesian point estimates were also more accurate than non-Bayesian estimates. The results illustrate the importance of analyzing coverage and bias of interval estimates, and how ignoring interval estimates can be misleading. Therefore, editors and policymakers should continue to emphasize the inclusion of interval estimates in research.
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Cost effectiveness of the U.S. Geological Survey's stream-gaging program in Wisconsin
Walker, J.F.; Osen, L.L.; Hughes, P.E.
1987-01-01
A minimum budget of $510,000 is required to operate the program; a budget less than this does not permit proper service and maintenance of the gaging stations. At this minimum budget, the theoretical average standard error of instantaneous discharge is 14.4%. The maximum budget analyzed was $650,000 and resulted in an average standard of error of instantaneous discharge of 7.2%.
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[Study on the ARIMA model application to predict echinococcosis cases in China].
En-Li, Tan; Zheng-Feng, Wang; Wen-Ce, Zhou; Shi-Zhu, Li; Yan, Lu; Lin, Ai; Yu-Chun, Cai; Xue-Jiao, Teng; Shun-Xian, Zhang; Zhi-Sheng, Dang; Chun-Li, Yang; Jia-Xu, Chen; Wei, Hu; Xiao-Nong, Zhou; Li-Guang, Tian
2018-02-26
To predict the monthly reported echinococcosis cases in China with the autoregressive integrated moving average (ARIMA) model, so as to provide a reference for prevention and control of echinococcosis. SPSS 24.0 software was used to construct the ARIMA models based on the monthly reported echinococcosis cases of time series from 2007 to 2015 and 2007 to 2014, respectively, and the accuracies of the two ARIMA models were compared. The model based on the data of the monthly reported cases of echinococcosis in China from 2007 to 2015 was ARIMA (1, 0, 0) (1, 1, 0) 12 , the relative error among reported cases and predicted cases was -13.97%, AR (1) = 0.367 ( t = 3.816, P < 0.001), SAR (1) = -0.328 ( t = -3.361, P = 0.001), and Ljung-Box Q = 14.119 ( df = 16, P = 0.590) . The model based on the data of the monthly reported cases of echinococcosis in China from 2007 to 2014 was ARIMA (1, 0, 0) (1, 0, 1) 12 , the relative error among reported cases and predicted cases was 0.56%, AR (1) = 0.413 ( t = 4.244, P < 0.001), SAR (1) = 0.809 ( t = 9.584, P < 0.001), SMA (1) = 0.356 ( t = 2.278, P = 0.025), and Ljung-Box Q = 18.924 ( df = 15, P = 0.217). The different time series may have different ARIMA models as for the same infectious diseases. It is needed to be further verified that the more data are accumulated, the shorter time of predication is, and the smaller the average of the relative error is. The establishment and prediction of an ARIMA model is a dynamic process that needs to be adjusted and optimized continuously according to the accumulated data, meantime, we should give full consideration to the intensity of the work related to infectious diseases reported (such as disease census and special investigation).
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Performance evaluation of a 1.6-µm methane DIAL system from ground, aircraft and UAV platforms.
Refaat, Tamer F; Ismail, Syed; Nehrir, Amin R; Hair, John W; Crawford, James H; Leifer, Ira; Shuman, Timothy
2013-12-16
Methane is an efficient absorber of infrared radiation and a potent greenhouse gas with a warming potential 72 times greater than carbon dioxide on a per molecule basis. Development of methane active remote sensing capability using the differential absorption lidar (DIAL) technique enables scientific assessments of the gas emission and impacts on the climate. A performance evaluation of a pulsed DIAL system for monitoring atmospheric methane is presented. This system leverages a robust injection-seeded pulsed Nd:YAG pumped Optical Parametric Oscillator (OPO) laser technology operating in the 1.645 µm spectral band. The system also leverages an efficient low noise, commercially available, InGaAs avalanche photo-detector (APD). Lidar signals and error budget are analyzed for system operation on ground in the range-resolved DIAL mode and from airborne platforms in the integrated path DIAL (IPDA) mode. Results indicate system capability of measuring methane concentration profiles with <1.0% total error up to 4.5 km range with 5 minute averaging from ground. For airborne IPDA, the total error in the column dry mixing ratio is less than 0.3% with 0.1 sec average using ground returns. This system has a unique capability of combining signals from the atmospheric scattering from layers above the surface with ground return signals, which provides methane column measurement between the atmospheric scattering layer and the ground directly. In such case 0.5% and 1.2% total errors are achieved with 10 sec average from airborne platforms at 8 km and 15.24 km altitudes, respectively. Due to the pulsed nature of the transmitter, the system is relatively insensitive to aerosol and cloud interferences. Such DIAL system would be ideal for investigating high latitude methane releases over polar ice sheets, permafrost regions, wetlands, and over ocean during day and night. This system would have commercial potential for fossil fuel leaks detection and industrial monitoring applications.
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The Limits of Coding with Joint Constraints on Detected and Undetected Error Rates
NASA Technical Reports Server (NTRS)
Dolinar, Sam; Andrews, Kenneth; Pollara, Fabrizio; Divsalar, Dariush
2008-01-01
We develop a remarkably tight upper bound on the performance of a parameterized family of bounded angle maximum-likelihood (BA-ML) incomplete decoders. The new bound for this class of incomplete decoders is calculated from the code's weight enumerator, and is an extension of Poltyrev-type bounds developed for complete ML decoders. This bound can also be applied to bound the average performance of random code ensembles in terms of an ensemble average weight enumerator. We also formulate conditions defining a parameterized family of optimal incomplete decoders, defined to minimize both the total codeword error probability and the undetected error probability for any fixed capability of the decoder to detect errors. We illustrate the gap between optimal and BA-ML incomplete decoding via simulation of a small code.
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NASA Astrophysics Data System (ADS)
Xu, Yadong; Serre, Marc L.; Reyes, Jeanette M.; Vizuete, William
2017-10-01
We have developed a Bayesian Maximum Entropy (BME) framework that integrates observations from a surface monitoring network and predictions from a Chemical Transport Model (CTM) to create improved exposure estimates that can be resolved into any spatial and temporal resolution. The flexibility of the framework allows for input of data in any choice of time scales and CTM predictions of any spatial resolution with varying associated degrees of estimation error and cost in terms of implementation and computation. This study quantifies the impact on exposure estimation error due to these choices by first comparing estimations errors when BME relied on ozone concentration data either as an hourly average, the daily maximum 8-h average (DM8A), or the daily 24-h average (D24A). Our analysis found that the use of DM8A and D24A data, although less computationally intensive, reduced estimation error more when compared to the use of hourly data. This was primarily due to the poorer CTM model performance in the hourly average predicted ozone. Our second analysis compared spatial variability and estimation errors when BME relied on CTM predictions with a grid cell resolution of 12 × 12 km2 versus a coarser resolution of 36 × 36 km2. Our analysis found that integrating the finer grid resolution CTM predictions not only reduced estimation error, but also increased the spatial variability in daily ozone estimates by 5 times. This improvement was due to the improved spatial gradients and model performance found in the finer resolved CTM simulation. The integration of observational and model predictions that is permitted in a BME framework continues to be a powerful approach for improving exposure estimates of ambient air pollution. The results of this analysis demonstrate the importance of also understanding model performance variability and its implications on exposure error.
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Shekarchi, Sayedali; Hallam, John; Christensen-Dalsgaard, Jakob
2013-11-01
Head-related transfer functions (HRTFs) are generally large datasets, which can be an important constraint for embedded real-time applications. A method is proposed here to reduce redundancy and compress the datasets. In this method, HRTFs are first compressed by conversion into autoregressive-moving-average (ARMA) filters whose coefficients are calculated using Prony's method. Such filters are specified by a few coefficients which can generate the full head-related impulse responses (HRIRs). Next, Legendre polynomials (LPs) are used to compress the ARMA filter coefficients. LPs are derived on the sphere and form an orthonormal basis set for spherical functions. Higher-order LPs capture increasingly fine spatial details. The number of LPs needed to represent an HRTF, therefore, is indicative of its spatial complexity. The results indicate that compression ratios can exceed 98% while maintaining a spectral error of less than 4 dB in the recovered HRTFs.
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Multi-GNSS signal-in-space range error assessment - Methodology and results
NASA Astrophysics Data System (ADS)
Montenbruck, Oliver; Steigenberger, Peter; Hauschild, André
2018-06-01
The positioning accuracy of global and regional navigation satellite systems (GNSS/RNSS) depends on a variety of influence factors. For constellation-specific performance analyses it has become common practice to separate a geometry-related quality factor (the dilution of precision, DOP) from the measurement and modeling errors of the individual ranging measurements (known as user equivalent range error, UERE). The latter is further divided into user equipment errors and contributions related to the space and control segment. The present study reviews the fundamental concepts and underlying assumptions of signal-in-space range error (SISRE) analyses and presents a harmonized framework for multi-GNSS performance monitoring based on the comparison of broadcast and precise ephemerides. The implications of inconsistent geometric reference points, non-common time systems, and signal-specific range biases are analyzed, and strategies for coping with these issues in the definition and computation of SIS range errors are developed. The presented concepts are, furthermore, applied to current navigation satellite systems, and representative results are presented along with a discussion of constellation-specific problems in their determination. Based on data for the January to December 2017 time frame, representative global average root-mean-square (RMS) SISRE values of 0.2 m, 0.6 m, 1 m, and 2 m are obtained for Galileo, GPS, BeiDou-2, and GLONASS, respectively. Roughly two times larger values apply for the corresponding 95th-percentile values. Overall, the study contributes to a better understanding and harmonization of multi-GNSS SISRE analyses and their use as key performance indicators for the various constellations.
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Knols, Ruud H; Aufdemkampe, Geert; de Bruin, Eling D; Uebelhart, Daniel; Aaronson, Neil K
2009-01-01
Background Hand-held dynamometry is a portable and inexpensive method to quantify muscle strength. To determine if muscle strength has changed, an examiner must know what part of the difference between a patient's pre-treatment and post-treatment measurements is attributable to real change, and what part is due to measurement error. This study aimed to determine the relative and absolute reliability of intra and inter-observer strength measurements with a hand-held dynamometer (HHD). Methods Two observers performed maximum voluntary peak torque measurements (MVPT) for isometric knee extension in 24 patients with haematological malignancies. For each patient, the measurements were carried out on the same day. The main outcome measures were the intraclass correlation coefficient (ICC ± 95%CI), the standard error of measurement (SEM), the smallest detectable difference (SDD), the relative values as % of the grand mean of the SEM and SDD, and the limits of agreement for the intra- and inter-observer '3 repetition average' and the 'highest value of 3 MVPT' knee extension strength measures. Results The intra-observer ICCs were 0.94 for the average of 3 MVPT (95%CI: 0.86–0.97) and 0.86 for the highest value of 3 MVPT (95%CI: 0.71–0.94). The ICCs for the inter-observer measurements were 0.89 for the average of 3 MVPT (95%CI: 0.75–0.95) and 0.77 for the highest value of 3 MVPT (95%CI: 0.54–0.90). The SEMs for the intra-observer measurements were 6.22 Nm (3.98% of the grand mean (GM) and 9.83 Nm (5.88% of GM). For the inter-observer measurements, the SEMs were 9.65 Nm (6.65% of GM) and 11.41 Nm (6.73% of GM). The SDDs for the generated parameters varied from 17.23 Nm (11.04% of GM) to 27.26 Nm (17.09% of GM) for intra-observer measurements, and 26.76 Nm (16.77% of GM) to 31.62 Nm (18.66% of GM) for inter-observer measurements, with similar results for the limits of agreement. Conclusion The results indicate that there is acceptable relative reliability for evaluating knee strength with a HHD, while the measurement error observed was modest. The HHD may be useful in detecting changes in knee extension strength at the individual patient level. PMID:19272149
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Smooth empirical Bayes estimation of observation error variances in linear systems
NASA Technical Reports Server (NTRS)
Martz, H. F., Jr.; Lian, M. W.
1972-01-01
A smooth empirical Bayes estimator was developed for estimating the unknown random scale component of each of a set of observation error variances. It is shown that the estimator possesses a smaller average squared error loss than other estimators for a discrete time linear system.
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Speeding up Coarse Point Cloud Registration by Threshold-Independent Baysac Match Selection
NASA Astrophysics Data System (ADS)
Kang, Z.; Lindenbergh, R.; Pu, S.
2016-06-01
This paper presents an algorithm for the automatic registration of terrestrial point clouds by match selection using an efficiently conditional sampling method -- threshold-independent BaySAC (BAYes SAmpling Consensus) and employs the error metric of average point-to-surface residual to reduce the random measurement error and then approach the real registration error. BaySAC and other basic sampling algorithms usually need to artificially determine a threshold by which inlier points are identified, which leads to a threshold-dependent verification process. Therefore, we applied the LMedS method to construct the cost function that is used to determine the optimum model to reduce the influence of human factors and improve the robustness of the model estimate. Point-to-point and point-to-surface error metrics are most commonly used. However, point-to-point error in general consists of at least two components, random measurement error and systematic error as a result of a remaining error in the found rigid body transformation. Thus we employ the measure of the average point-to-surface residual to evaluate the registration accuracy. The proposed approaches, together with a traditional RANSAC approach, are tested on four data sets acquired by three different scanners in terms of their computational efficiency and quality of the final registration. The registration results show the st.dev of the average point-to-surface residuals is reduced from 1.4 cm (plain RANSAC) to 0.5 cm (threshold-independent BaySAC). The results also show that, compared to the performance of RANSAC, our BaySAC strategies lead to less iterations and cheaper computational cost when the hypothesis set is contaminated with more outliers.
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Error reduction in EMG signal decomposition
Kline, Joshua C.
2014-01-01
Decomposition of the electromyographic (EMG) signal into constituent action potentials and the identification of individual firing instances of each motor unit in the presence of ambient noise are inherently probabilistic processes, whether performed manually or with automated algorithms. Consequently, they are subject to errors. We set out to classify and reduce these errors by analyzing 1,061 motor-unit action-potential trains (MUAPTs), obtained by decomposing surface EMG (sEMG) signals recorded during human voluntary contractions. Decomposition errors were classified into two general categories: location errors representing variability in the temporal localization of each motor-unit firing instance and identification errors consisting of falsely detected or missed firing instances. To mitigate these errors, we developed an error-reduction algorithm that combines multiple decomposition estimates to determine a more probable estimate of motor-unit firing instances with fewer errors. The performance of the algorithm is governed by a trade-off between the yield of MUAPTs obtained above a given accuracy level and the time required to perform the decomposition. When applied to a set of sEMG signals synthesized from real MUAPTs, the identification error was reduced by an average of 1.78%, improving the accuracy to 97.0%, and the location error was reduced by an average of 1.66 ms. The error-reduction algorithm in this study is not limited to any specific decomposition strategy. Rather, we propose it be used for other decomposition methods, especially when analyzing precise motor-unit firing instances, as occurs when measuring synchronization. PMID:25210159
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NASA Technical Reports Server (NTRS)
Nutter, Paul; Manobianco, John
1998-01-01
This report describes the Applied Meteorology Unit's objective verification of the National Centers for Environmental Prediction 29-km eta model during separate warm and cool season periods from May 1996 through January 1998. The verification of surface and upper-air point forecasts was performed at three selected stations important for 45th Weather Squadron, Spaceflight Meteorology Group, and National Weather Service, Melbourne operational weather concerns. The statistical evaluation identified model biases that may result from inadequate parameterization of physical processes. Since model biases are relatively small compared to the random error component, most of the total model error results from day-to-day variability in the forecasts and/or observations. To some extent, these nonsystematic errors reflect the variability in point observations that sample spatial and temporal scales of atmospheric phenomena that cannot be resolved by the model. On average, Meso-Eta point forecasts provide useful guidance for predicting the evolution of the larger scale environment. A more substantial challenge facing model users in real time is the discrimination of nonsystematic errors that tend to inflate the total forecast error. It is important that model users maintain awareness of ongoing model changes. Such changes are likely to modify the basic error characteristics, particularly near the surface.
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NASA Technical Reports Server (NTRS)
Pavlis, Nikolaos K.
1991-01-01
An error analysis study was conducted in order to assess the current accuracies and the future anticipated improvements in the estimation of geopotential differences over intercontinental locations. An observation/estimation scheme was proposed and studied, whereby gravity disturbance measurements on the Earth's surface, in caps surrounding the estimation points, are combined with corresponding data in caps directly over these points at the altitude of a low orbiting satellite, for the estimation of the geopotential difference between the terrestrial stations. The mathematical modeling required to relate the primary observables to the parameters to be estimated, was studied for the terrestrial data and the data at altitude. Emphasis was placed on the examination of systematic effects and on the corresponding reductions that need to be applied to the measurements to avoid systematic errors. The error estimation for the geopotential differences was performed using both truncation theory and least squares collocation with ring averages, in case observations on the Earth's surface only are used. The error analysis indicated that with the currently available global geopotential model OSU89B and with gravity disturbance data in 2 deg caps surrounding the estimation points, the error of the geopotential difference arising from errors in the reference model and the cap data is about 23 kgal cm, for 30 deg station separation.
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Quantification and characterization of leakage errors
NASA Astrophysics Data System (ADS)
Wood, Christopher J.; Gambetta, Jay M.
2018-03-01
We present a general framework for the quantification and characterization of leakage errors that result when a quantum system is encoded in the subspace of a larger system. To do this we introduce metrics for quantifying the coherent and incoherent properties of the resulting errors and we illustrate this framework with several examples relevant to superconducting qubits. In particular, we propose two quantities, the leakage and seepage rates, which together with average gate fidelity allow for characterizing the average performance of quantum gates in the presence of leakage and show how the randomized benchmarking protocol can be modified to enable the robust estimation of all three quantities for a Clifford gate set.
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Sullivan, James S.; Ball, Don G.
1997-01-01
The instantaneous V.sub.co signal on a charging capacitor is sampled and the charge voltage on capacitor C.sub.o is captured just prior to its discharge into the first stage of magnetic modulator. The captured signal is applied to an averaging circuit with a long time constant and to the positive input terminal of a differential amplifier. The averaged V.sub. co signal is split between a gain stage (G=0.975) and a feedback stage that determines the slope of the voltage ramp applied to the high speed comparator. The 97.5% portion of the averaged V.sub.co signal is applied to the negative input of a differential amplifier gain stage (G=10). The differential amplifier produces an error signal by subtracting 97.5% of the averaged V.sub.co signal from the instantaneous value of sampled V.sub.co signal and multiplying the difference by ten. The resulting error signal is applied to the positive input of a high speed comparator. The error signal is then compared to a voltage ramp that is proportional to the averaged V.sub.co values squared divided by the total volt-second product of the magnetic compression circuit.
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Sullivan, J.S.; Ball, D.G.
1997-09-09
The instantaneous V{sub co} signal on a charging capacitor is sampled and the charge voltage on capacitor C{sub o} is captured just prior to its discharge into the first stage of magnetic modulator. The captured signal is applied to an averaging circuit with a long time constant and to the positive input terminal of a differential amplifier. The averaged V{sub co} signal is split between a gain stage (G = 0.975) and a feedback stage that determines the slope of the voltage ramp applied to the high speed comparator. The 97.5% portion of the averaged V{sub co} signal is applied to the negative input of a differential amplifier gain stage (G = 10). The differential amplifier produces an error signal by subtracting 97.5% of the averaged V{sub co} signal from the instantaneous value of sampled V{sub co} signal and multiplying the difference by ten. The resulting error signal is applied to the positive input of a high speed comparator. The error signal is then compared to a voltage ramp that is proportional to the averaged V{sub co} values squared divided by the total volt-second product of the magnetic compression circuit. 11 figs.
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Improved estimation of anomalous diffusion exponents in single-particle tracking experiments
NASA Astrophysics Data System (ADS)
Kepten, Eldad; Bronshtein, Irena; Garini, Yuval
2013-05-01
The mean square displacement is a central tool in the analysis of single-particle tracking experiments, shedding light on various biophysical phenomena. Frequently, parameters are extracted by performing time averages on single-particle trajectories followed by ensemble averaging. This procedure, however, suffers from two systematic errors when applied to particles that perform anomalous diffusion. The first is significant at short-time lags and is induced by measurement errors. The second arises from the natural heterogeneity in biophysical systems. We show how to estimate and correct these two errors and improve the estimation of the anomalous parameters for the whole particle distribution. As a consequence, we manage to characterize ensembles of heterogeneous particles even for rather short and noisy measurements where regular time-averaged mean square displacement analysis fails. We apply this method to both simulations and in vivo measurements of telomere diffusion in 3T3 mouse embryonic fibroblast cells. The motion of telomeres is found to be subdiffusive with an average exponent constant in time. Individual telomere exponents are normally distributed around the average exponent. The proposed methodology has the potential to improve experimental accuracy while maintaining lower experimental costs and complexity.
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DNA assembly with error correction on a droplet digital microfluidics platform.
Khilko, Yuliya; Weyman, Philip D; Glass, John I; Adams, Mark D; McNeil, Melanie A; Griffin, Peter B
2018-06-01
Custom synthesized DNA is in high demand for synthetic biology applications. However, current technologies to produce these sequences using assembly from DNA oligonucleotides are costly and labor-intensive. The automation and reduced sample volumes afforded by microfluidic technologies could significantly decrease materials and labor costs associated with DNA synthesis. The purpose of this study was to develop a gene assembly protocol utilizing a digital microfluidic device. Toward this goal, we adapted bench-scale oligonucleotide assembly methods followed by enzymatic error correction to the Mondrian™ digital microfluidic platform. We optimized Gibson assembly, polymerase chain reaction (PCR), and enzymatic error correction reactions in a single protocol to assemble 12 oligonucleotides into a 339-bp double- stranded DNA sequence encoding part of the human influenza virus hemagglutinin (HA) gene. The reactions were scaled down to 0.6-1.2 μL. Initial microfluidic assembly methods were successful and had an error frequency of approximately 4 errors/kb with errors originating from the original oligonucleotide synthesis. Relative to conventional benchtop procedures, PCR optimization required additional amounts of MgCl 2 , Phusion polymerase, and PEG 8000 to achieve amplification of the assembly and error correction products. After one round of error correction, error frequency was reduced to an average of 1.8 errors kb - 1 . We demonstrated that DNA assembly from oligonucleotides and error correction could be completely automated on a digital microfluidic (DMF) platform. The results demonstrate that enzymatic reactions in droplets show a strong dependence on surface interactions, and successful on-chip implementation required supplementation with surfactants, molecular crowding agents, and an excess of enzyme. Enzymatic error correction of assembled fragments improved sequence fidelity by 2-fold, which was a significant improvement but somewhat lower than expected compared to bench-top assays, suggesting an additional capacity for optimization.
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NASA Technical Reports Server (NTRS)
Fisher, Brad; Wolff, David B.
2010-01-01
Passive and active microwave rain sensors onboard earth-orbiting satellites estimate monthly rainfall from the instantaneous rain statistics collected during satellite overpasses. It is well known that climate-scale rain estimates from meteorological satellites incur sampling errors resulting from the process of discrete temporal sampling and statistical averaging. Sampling and retrieval errors ultimately become entangled in the estimation of the mean monthly rain rate. The sampling component of the error budget effectively introduces statistical noise into climate-scale rain estimates that obscure the error component associated with the instantaneous rain retrieval. Estimating the accuracy of the retrievals on monthly scales therefore necessitates a decomposition of the total error budget into sampling and retrieval error quantities. This paper presents results from a statistical evaluation of the sampling and retrieval errors for five different space-borne rain sensors on board nine orbiting satellites. Using an error decomposition methodology developed by one of the authors, sampling and retrieval errors were estimated at 0.25 resolution within 150 km of ground-based weather radars located at Kwajalein, Marshall Islands and Melbourne, Florida. Error and bias statistics were calculated according to the land, ocean and coast classifications of the surface terrain mask developed for the Goddard Profiling (GPROF) rain algorithm. Variations in the comparative error statistics are attributed to various factors related to differences in the swath geometry of each rain sensor, the orbital and instrument characteristics of the satellite and the regional climatology. The most significant result from this study found that each of the satellites incurred negative longterm oceanic retrieval biases of 10 to 30%.
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Demand Forecasting: An Evaluation of DODs Accuracy Metric and Navys Procedures
2016-06-01
inventory management improvement plan, mean of absolute scaled error, lead time adjusted squared error, forecast accuracy, benchmarking, naïve method...Manager JASA Journal of the American Statistical Association LASE Lead-time Adjusted Squared Error LCI Life Cycle Indicator MA Moving Average MAE...Mean Squared Error xvi NAVSUP Naval Supply Systems Command NDAA National Defense Authorization Act NIIN National Individual Identification Number
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An electrophysiological signal that precisely tracks the emergence of error awareness
Murphy, Peter R.; Robertson, Ian H.; Allen, Darren; Hester, Robert; O'Connell, Redmond G.
2012-01-01
Recent electrophysiological research has sought to elucidate the neural mechanisms necessary for the conscious awareness of action errors. Much of this work has focused on the error positivity (Pe), a neural signal that is specifically elicited by errors that have been consciously perceived. While awareness appears to be an essential prerequisite for eliciting the Pe, the precise functional role of this component has not been identified. Twenty-nine participants performed a novel variant of the Go/No-go Error Awareness Task (EAT) in which awareness of commission errors was indicated via a separate speeded manual response. Independent component analysis (ICA) was used to isolate the Pe from other stimulus- and response-evoked signals. Single-trial analysis revealed that Pe peak latency was highly correlated with the latency at which awareness was indicated. Furthermore, the Pe was more closely related to the timing of awareness than it was to the initial erroneous response. This finding was confirmed in a separate study which derived IC weights from a control condition in which no indication of awareness was required, thus ruling out motor confounds. A receiver-operating-characteristic (ROC) curve analysis showed that the Pe could reliably predict whether an error would be consciously perceived up to 400 ms before the average awareness response. Finally, Pe latency and amplitude were found to be significantly correlated with overall error awareness levels between subjects. Our data show for the first time that the temporal dynamics of the Pe trace the emergence of error awareness. These findings have important implications for interpreting the results of clinical EEG studies of error processing. PMID:22470332
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Validating CFD Predictions of Pharmaceutical Aerosol Deposition with In Vivo Data.
Tian, Geng; Hindle, Michael; Lee, Sau; Longest, P Worth
2015-10-01
CFD provides a powerful approach to evaluate the deposition of pharmaceutical aerosols; however, previous studies have not compared CFD results of deposition throughout the lungs with in vivo data. The in vivo datasets selected for comparison with CFD predictions included fast and slow clearance of monodisperse aerosols as well as 2D gamma scintigraphy measurements for a dry powder inhaler (DPI) and softmist inhaler (SMI). The CFD model included the inhaler, a characteristic model of the mouth-throat (MT) and upper tracheobronchial (TB) airways, stochastic individual pathways (SIPs) representing the remaining TB region, and recent CFD-based correlations to predict pharmaceutical aerosol deposition in the alveolar airways. For the monodisperse aerosol, CFD predictions of total lung deposition agreed with in vivo data providing a percent relative error of 6% averaged across aerosol sizes of 1-7 μm. With the DPI and SMI, deposition was evaluated in the MT, central airways (bifurcations B1-B7), and intermediate plus peripheral airways (B8 through alveoli). Across these regions, CFD predictions produced an average relative error <10% for each inhaler. CFD simulations with the SIP modeling approach were shown to accurately predict regional deposition throughout the lungs for multiple aerosol types and different in vivo assessment methods.
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Validating CFD Predictions of Pharmaceutical Aerosol Deposition with In Vivo Data
Tian, Geng; Hindle, Michael; Lee, Sau; Longest, P. Worth
2015-01-01
Purpose CFD provides a powerful approach to evaluate the deposition of pharmaceutical aerosols; however, previous studies have not compared CFD results of deposition throughout the lungs with in vivo data. Methods The in vivo datasets selected for comparison with CFD predictions included fast and slow clearance of monodisperse aerosols as well as 2D gamma scintigraphy measurements for a dry powder inhaler (DPI) and softmist inhaler (SMI). The CFD model included the inhaler, a characteristic model of the mouth-throat (MT) and upper tracheobronchial (TB) airways, stochastic individual pathways (SIPs) representing the remaining TB region, and recent CFD-based correlations to predict pharmaceutical aerosol deposition in the alveolar airways. Results For the monodisperse aerosol, CFD predictions of total lung deposition agreed with in vivo data providing a percent relative error of 6% averaged across aerosol sizes of 1-7μm. With the DPI and SMI, deposition was evaluated in the MT, central airways (bifurcations B1-B7), and intermediate plus peripheral airways (B8 through alveoli). Across these regions, CFD predictions produced an average relative error <10% for each inhaler. Conclusions CFD simulations with the SIP modeling approach were shown to accurately predict regional deposition throughout the lungs for multiple aerosol types and different in vivo assessment methods. PMID:25944585
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Al-lela, Omer Qutaiba B; Bahari, Mohd Baidi; Al-abbassi, Mustafa G; Salih, Muhannad R M; Basher, Amena Y
2012-06-06
The immunization status of children is improved by interventions that increase community demand for compulsory and non-compulsory vaccines, one of the most important interventions related to immunization providers. The aim of this study is to evaluate the activities of immunization providers in terms of activities time and cost, to calculate the immunization doses cost, and to determine the immunization dose errors cost. Time-motion and cost analysis study design was used. Five public health clinics in Mosul-Iraq participated in the study. Fifty (50) vaccine doses were required to estimate activities time and cost. Micro-costing method was used; time and cost data were collected for each immunization-related activity performed by the clinic staff. A stopwatch was used to measure the duration of activity interactions between the parents and clinic staff. The immunization service cost was calculated by multiplying the average salary/min by activity time per minute. 528 immunization cards of Iraqi children were scanned to determine the number and the cost of immunization doses errors (extraimmunization doses and invalid doses). The average time for child registration was 6.7 min per each immunization dose, and the physician spent more than 10 min per dose. Nurses needed more than 5 min to complete child vaccination. The total cost of immunization activities was 1.67 US$ per each immunization dose. Measles vaccine (fifth dose) has a lower price (0.42 US$) than all other immunization doses. The cost of a total of 288 invalid doses was 744.55 US$ and the cost of a total of 195 extra immunization doses was 503.85 US$. The time spent on physicians' activities was longer than that spent on registrars' and nurses' activities. Physician total cost was higher than registrar cost and nurse cost. The total immunization cost will increase by about 13.3% owing to dose errors. Copyright © 2012 Elsevier Ltd. All rights reserved.
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An Improved Method of Heterogeneity Compensation for the Convolution / Superposition Algorithm
NASA Astrophysics Data System (ADS)
Jacques, Robert; McNutt, Todd
2014-03-01
Purpose: To improve the accuracy of convolution/superposition (C/S) in heterogeneous material by developing a new algorithm: heterogeneity compensated superposition (HCS). Methods: C/S has proven to be a good estimator of the dose deposited in a homogeneous volume. However, near heterogeneities electron disequilibrium occurs, leading to the faster fall-off and re-buildup of dose. We propose to filter the actual patient density in a position and direction sensitive manner, allowing the dose deposited near interfaces to be increased or decreased relative to C/S. We implemented the effective density function as a multivariate first-order recursive filter and incorporated it into GPU-accelerated, multi-energetic C/S implementation. We compared HCS against C/S using the ICCR 2000 Monte-Carlo accuracy benchmark, 23 similar accuracy benchmarks and 5 patient cases. Results: Multi-energetic HCS increased the dosimetric accuracy for the vast majority of voxels; in many cases near Monte-Carlo results were achieved. We defined the per-voxel error, %|mm, as the minimum of the distance to agreement in mm and the dosimetric percentage error relative to the maximum MC dose. HCS improved the average mean error by 0.79 %|mm for the patient volumes; reducing the average mean error from 1.93 %|mm to 1.14 %|mm. Very low densities (i.e. < 0.1 g / cm3) remained problematic, but may be solvable with a better filter function. Conclusions: HCS improved upon C/S's density scaled heterogeneity correction with a position and direction sensitive density filter. This method significantly improved the accuracy of the GPU based algorithm reaching the accuracy levels of Monte Carlo based methods with performance in a few tenths of seconds per beam. Acknowledgement: Funding for this research was provided by the NSF Cooperative Agreement EEC9731748, Elekta / IMPAC Medical Systems, Inc. and the Johns Hopkins University. James Satterthwaite provided the Monte Carlo benchmark simulations.
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On the challenges of drawing conclusions from p-values just below 0.05
2015-01-01
In recent years, researchers have attempted to provide an indication of the prevalence of inflated Type 1 error rates by analyzing the distribution of p-values in the published literature. De Winter & Dodou (2015) analyzed the distribution (and its change over time) of a large number of p-values automatically extracted from abstracts in the scientific literature. They concluded there is a ‘surge of p-values between 0.041–0.049 in recent decades’ which ‘suggests (but does not prove) questionable research practices have increased over the past 25 years.’ I show the changes in the ratio of fractions of p-values between 0.041–0.049 over the years are better explained by assuming the average power has decreased over time. Furthermore, I propose that their observation that p-values just below 0.05 increase more strongly than p-values above 0.05 can be explained by an increase in publication bias (or the file drawer effect) over the years (cf. Fanelli, 2012; Pautasso, 2010, which has led to a relative decrease of ‘marginally significant’ p-values in abstracts in the literature (instead of an increase in p-values just below 0.05). I explain why researchers analyzing large numbers of p-values need to relate their assumptions to a model of p-value distributions that takes into account the average power of the performed studies, the ratio of true positives to false positives in the literature, the effects of publication bias, and the Type 1 error rate (and possible mechanisms through which it has inflated). Finally, I discuss why publication bias and underpowered studies might be a bigger problem for science than inflated Type 1 error rates, and explain the challenges when attempting to draw conclusions about inflated Type 1 error rates from a large heterogeneous set of p-values. PMID:26246976
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Estimating Engine Airflow in Gas-Turbine Powered Aircraft with Clean and Distorted Inlet Flows
NASA Technical Reports Server (NTRS)
Williams, J. G.; Steenken, W. G.; Yuhas, A. J.
1996-01-01
The P404-GF-400 Powered F/A-18A High Alpha Research Vehicle (HARV) was used to examine the impact of inlet-generated total-pressure distortion on estimating levels of engine airflow. Five airflow estimation methods were studied. The Reference Method was a fan corrected airflow to fan corrected speed calibration from an uninstalled engine test. In-flight airflow estimation methods utilized the average, or individual, inlet duct static- to total-pressure ratios, and the average fan-discharge static-pressure to average inlet total-pressure ratio. Correlations were established at low distortion conditions for each method relative to the Reference Method. A range of distorted inlet flow conditions were obtained from -10 deg. to +60 deg. angle of attack and -7 deg. to +11 deg. angle of sideslip. The individual inlet duct pressure ratio correlation resulted in a 2.3 percent airflow spread for all distorted flow levels with a bias error of -0.7 percent. The fan discharge pressure ratio correlation gave results with a 0.6 percent airflow spread with essentially no systematic error. Inlet-generated total-pressure distortion and turbulence had no significant impact on the P404-GE400 engine airflow pumping. Therefore, a speed-flow relationship may provide the best airflow estimate for a specific engine under all flight conditions.
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Is there any electrophysiological evidence for subliminal error processing?
Shalgi, Shani; Deouell, Leon Y
2013-08-29
The role of error awareness in executive control and modification of behavior is not fully understood. In line with many recent studies showing that conscious awareness is unnecessary for numerous high-level processes such as strategic adjustments and decision making, it was suggested that error detection can also take place unconsciously. The Error Negativity (Ne) component, long established as a robust error-related component that differentiates between correct responses and errors, was a fine candidate to test this notion: if an Ne is elicited also by errors which are not consciously detected, it would imply a subliminal process involved in error monitoring that does not necessarily lead to conscious awareness of the error. Indeed, for the past decade, the repeated finding of a similar Ne for errors which became aware and errors that did not achieve awareness, compared to the smaller negativity elicited by correct responses (Correct Response Negativity; CRN), has lent the Ne the prestigious status of an index of subliminal error processing. However, there were several notable exceptions to these findings. The study in the focus of this review (Shalgi and Deouell, 2012) sheds new light on both types of previous results. We found that error detection as reflected by the Ne is correlated with subjective awareness: when awareness (or more importantly lack thereof) is more strictly determined using the wagering paradigm, no Ne is elicited without awareness. This result effectively resolves the issue of why there are many conflicting findings regarding the Ne and error awareness. The average Ne amplitude appears to be influenced by individual criteria for error reporting and therefore, studies containing different mixtures of participants who are more confident of their own performance or less confident, or paradigms that either encourage or don't encourage reporting low confidence errors will show different results. Based on this evidence, it is no longer possible to unquestioningly uphold the notion that the amplitude of the Ne is unrelated to subjective awareness, and therefore, that errors are detected without conscious awareness.
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Liu, Min Hsien; Chen, Cheng; Hong, Yaw Shun
2005-02-08
A three-parametric modification equation and the least-squares approach are adopted to calibrating hybrid density-functional theory energies of C(1)-C(10) straight-chain aldehydes, alcohols, and alkoxides to accurate enthalpies of formation DeltaH(f) and Gibbs free energies of formation DeltaG(f), respectively. All calculated energies of the C-H-O composite compounds were obtained based on B3LYP6-311++G(3df,2pd) single-point energies and the related thermal corrections of B3LYP6-31G(d,p) optimized geometries. This investigation revealed that all compounds had 0.05% average absolute relative error (ARE) for the atomization energies, with mean value of absolute error (MAE) of just 2.1 kJ/mol (0.5 kcal/mol) for the DeltaH(f) and 2.4 kJ/mol (0.6 kcal/mol) for the DeltaG(f) of formation.
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Double dissociation of value computations in orbitofrontal and anterior cingulate neurons
Kennerley, Steven W.; Behrens, Timothy E. J.; Wallis, Jonathan D.
2011-01-01
Damage to prefrontal cortex (PFC) impairs decision-making, but the underlying value computations that might cause such impairments remain unclear. Here we report that value computations are doubly dissociable within PFC neurons. While many PFC neurons encoded chosen value, they used opponent encoding schemes such that averaging the neuronal population eliminated value coding. However, a special population of neurons in anterior cingulate cortex (ACC) - but not orbitofrontal cortex (OFC) - multiplex chosen value across decision parameters using a unified encoding scheme, and encoded reward prediction errors. In contrast, neurons in OFC - but not ACC - encoded chosen value relative to the recent history of choice values. Together, these results suggest complementary valuation processes across PFC areas: OFC neurons dynamically evaluate current choices relative to recent choice values, while ACC neurons encode choice predictions and prediction errors using a common valuation currency reflecting the integration of multiple decision parameters. PMID:22037498
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Zhang, Tangtang; Wen, Jun; van der Velde, Rogier; Meng, Xianhong; Li, Zhenchao; Liu, Yuanyong; Liu, Rong
2008-01-01
The total atmospheric water vapor content (TAWV) and land surface temperature (LST) play important roles in meteorology, hydrology, ecology and some other disciplines. In this paper, the ENVISAT/AATSR (The Advanced Along-Track Scanning Radiometer) thermal data are used to estimate the TAWV and LST over the Loess Plateau in China by using a practical split window algorithm. The distribution of the TAWV is accord with that of the MODIS TAWV products, which indicates that the estimation of the total atmospheric water vapor content is reliable. Validations of the LST by comparing with the ground measurements indicate that the maximum absolute derivation, the maximum relative error and the average relative error is 4.0K, 11.8% and 5.0% respectively, which shows that the retrievals are believable; this algorithm can provide a new way to estimate the LST from AATSR data. PMID:27879795
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NASA Technical Reports Server (NTRS)
Oreopoulos, Lazaros
2004-01-01
The MODIS Level-3 optical thickness and effective radius cloud product is a gridded l deg. x 1 deg. dataset that is derived from aggregation and subsampling at 5 km of 1 km, resolution Level-2 orbital swath data (Level-2 granules). This study examines the impact of the 5 km subsampling on the mean, standard deviation and inhomogeneity parameter statistics of optical thickness and effective radius. The methodology is simple and consists of estimating mean errors for a large collection of Terra and Aqua Level-2 granules by taking the difference of the statistics at the original and subsampled resolutions. It is shown that the Level-3 sampling does not affect the various quantities investigated to the same degree, with second order moments suffering greater subsampling errors, as expected. Mean errors drop dramatically when averages over a sufficient number of regions (e.g., monthly and/or latitudinal averages) are taken, pointing to a dominance of errors that are of random nature. When histograms built from subsampled data with the same binning rules as in the Level-3 dataset are used to reconstruct the quantities of interest, the mean errors do not deteriorate significantly. The results in this paper provide guidance to users of MODIS Level-3 optical thickness and effective radius cloud products on the range of errors due to subsampling they should expect and perhaps account for, in scientific work with this dataset. In general, subsampling errors should not be a serious concern when moderate temporal and/or spatial averaging is performed.
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NASA Astrophysics Data System (ADS)
Santer, B. D.; Mears, C. A.; Gleckler, P. J.; Solomon, S.; Wigley, T.; Arblaster, J.; Cai, W.; Gillett, N. P.; Ivanova, D. P.; Karl, T. R.; Lanzante, J.; Meehl, G. A.; Stott, P.; Taylor, K. E.; Thorne, P.; Wehner, M. F.; Zou, C.
2010-12-01
We perform the most comprehensive comparison to date of simulated and observed temperature trends. Comparisons are made for different latitude bands, timescales, and temperature variables, using information from a multi-model archive and a variety of observational datasets. Our focus is on temperature changes in the lower troposphere (TLT), the mid- to upper troposphere (TMT), and at the sea surface (SST). For SST, TLT, and TMT, trend comparisons over the satellite era (1979 to 2009) always yield closest agreement in mid-latitudes of the Northern Hemisphere. There are pronounced discrepancies in the tropics and in the Southern Hemisphere: in both regions, the multi-model average warming is consistently larger than observed. At high latitudes in the Northern Hemisphere, the observed tropospheric warming exceeds multi-model average trends. The similarity in the latitudinal structure of this discrepancy pattern across different temperature variables and observational data sets suggests that these trend differences are real, and are not due to residual inhomogeneities in the observations. The interpretation of these results is hampered by the fact that the CMIP-3 multi-model archive analyzed here convolves errors in key external forcings with errors in the model response to forcing. Under a "forcing error" interpretation, model-average temperature trends in the Southern Hemisphere extratropics are biased warm because many models neglect (and/or inaccurately specify) changes in stratospheric ozone and the indirect effects of aerosols. An alternative "response error" explanation for the model trend errors is that there are fundamental problems with model clouds and ocean heat uptake over the Southern Ocean. When SST changes are compared over the longer period 1950 to 2009, there is close agreement between simulated and observed trends poleward of 50°S. This result is difficult to reconcile with the hypothesis that the trend discrepancies over 1979 to 2009 are primarily attributable to response errors. Our results suggest that biases in multi-model average temperature trends over the satellite era can be plausibly linked to forcing errors. Better partitioning of the forcing and response components of model errors will require a systematic program of numerical experimentation, with a focus on exploring the climate response to uncertainties in key historical forcings.
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[Spectrum simulation based on data derived from red tide].
Liu, Zhen-Yu; Cui, Ting-Wei; Yue, Jie; Jiang, Tao; Cao, Wen-Xi; Ma, Yi
2011-11-01
The present paper utilizes the absorption data of red tide water measured during the growing and dying course to retrieve imaginary part of the index of refraction based on Mie theory, carries out the simulation and analysis of average absorption efficiency factors, average backscattering efficiency factors and scattering phase function. The analysis of the simulation shows that Mie theory can be used to reproduce the absorption property of Chaetoceros socialis with an average error of 11%; the average backscattering efficiency factors depend on the value of absorption whose maximum value corresponds to the wavelength range from 400 to 700 nanometer; the average backscattering efficiency factors showed a maximum value on 17th with a low value during the outbreak of red tide and the minimum on 21th; the total scattering, weakly depending on the absorption, is proportional to the size parameters which represent the relative size of cell diameter with respect to the wavelength, while the angle scattering intensity is inversely proportional to wavelength.
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Errors in accident data, its types, causes and methods of rectification-analysis of the literature.
Ahmed, Ashar; Sadullah, Ahmad Farhan Mohd; Yahya, Ahmad Shukri
2017-07-29
Most of the decisions taken to improve road safety are based on accident data, which makes it the back bone of any country's road safety system. Errors in this data will lead to misidentification of black spots and hazardous road segments, projection of false estimates pertinent to accidents and fatality rates, and detection of wrong parameters responsible for accident occurrence, thereby making the entire road safety exercise ineffective. Its extent varies from country to country depending upon various factors. Knowing the type of error in the accident data and the factors causing it enables the application of the correct method for its rectification. Therefore there is a need for a systematic literature review that addresses the topic at a global level. This paper fulfils the above research gap by providing a synthesis of literature for the different types of errors found in the accident data of 46 countries across the six regions of the world. The errors are classified and discussed with respect to each type and analysed with respect to income level; assessment with regard to the magnitude for each type is provided; followed by the different causes that result in their occurrence, and the various methods used to address each type of error. Among high-income countries the extent of error in reporting slight, severe, non-fatal and fatal injury accidents varied between 39-82%, 16-52%, 12-84%, and 0-31% respectively. For middle-income countries the error for the same categories varied between 93-98%, 32.5-96%, 34-99% and 0.5-89.5% respectively. The only four studies available for low-income countries showed that the error in reporting non-fatal and fatal accidents varied between 69-80% and 0-61% respectively. The logistic relation of error in accident data reporting, dichotomised at 50%, indicated that as the income level of a country increases the probability of having less error in accident data also increases. Average error in recording information related to the variables in the categories of location, victim's information, vehicle's information, and environment was 27%, 37%, 16% and 19% respectively. Among the causes identified for errors in accident data reporting, Policing System was found to be the most important. Overall 26 causes of errors in accident data were discussed out of which 12 were related to reporting and 14 were related to recording. "Capture-Recapture" was the most widely used method among the 11 different methods: that can be used for the rectification of under-reporting. There were 12 studies pertinent to the rectification of accident location and almost all of them utilised a Geographical Information System (GIS) platform coupled with a matching algorithm to estimate the correct location. It is recommended that the policing system should be reformed and public awareness should be created to help reduce errors in accident data. Copyright © 2017 Elsevier Ltd. All rights reserved.
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NASA Astrophysics Data System (ADS)
Wang, Ting; Xiang, Jie; Fei, Jianfang; Wang, Yi; Liu, Chunxia; Li, Yuanxiang
2017-12-01
This paper presents an evaluation of the observational impacts on blended sea surface winds from a two-dimensional variational data assimilation (2D-Var) scheme. We begin by briefly introducing the analysis sensitivity with respect to observations in variational data assimilation systems and its relationship with the degrees of freedom for signal (DFS), and then the DFS concept is applied to the 2D-Var sea surface wind blending scheme. Two methods, a priori and a posteriori, are used to estimate the DFS of the zonal ( u) and meridional ( v) components of winds in the 2D-Var blending scheme. The a posteriori method can obtain almost the same results as the a priori method. Because only by-products of the blending scheme are used for the a posteriori method, the computation time is reduced significantly. The magnitude of the DFS is critically related to the observational and background error statistics. Changing the observational and background error variances can affect the DFS value. Because the observation error variances are assumed to be uniform, the observational influence at each observational location is related to the background error variance, and the observations located at the place where there are larger background error variances have larger influences. The average observational influence of u and v with respect to the analysis is about 40%, implying that the background influence with respect to the analysis is about 60%.
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NASA Astrophysics Data System (ADS)
Lisson, Jerold B.; Mounts, Darryl I.; Fehniger, Michael J.
1992-08-01
Localized wavefront performance analysis (LWPA) is a system that allows the full utilization of the system optical transfer function (OTF) for the specification and acceptance of hybrid imaging systems. We show that LWPA dictates the correction of wavefront errors with the greatest impact on critical imaging spatial frequencies. This is accomplished by the generation of an imaging performance map-analogous to a map of the optic pupil error-using a local OTF. The resulting performance map a function of transfer function spatial frequency is directly relatable to the primary viewing condition of the end-user. In addition to optimizing quality for the viewer it will be seen that the system has the potential for an improved matching of the optical and electronic bandpass of the imager and for the development of more realistic acceptance specifications. 1. LOCAL WAVEFRONT PERFORMANCE ANALYSIS The LWPA system generates a local optical quality factor (LOQF) in the form of a map analogous to that used for the presentation and evaluation of wavefront errors. In conjunction with the local phase transfer function (LPTF) it can be used for maximally efficient specification and correction of imaging system pupil errors. The LOQF and LPTF are respectively equivalent to the global modulation transfer function (MTF) and phase transfer function (PTF) parts of the OTF. The LPTF is related to difference of the average of the errors in separated regions of the pupil. Figure
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Flannery, Frank T; Parikh, Parul Divya; Oetgen, William J
2010-01-01
This study describes a large database of closed medical professional liability (MPL) claims involving family physicians in the United States. The purpose of this report is to provide information for practicing family physicians that will be useful in improving the quality of care, thereby reducing the incidence of patient injury and the consequent frequency of MPL claims. The Physician Insurers Association of America (PIAA) established a registry of closed MPL claims in 1985. This registry contains data describing 239,756 closed claims in the United States through 2008. The registry is maintained for educational programs that are designed to improve quality of care and reduce patient injury MPL claims. We summarized this closed claims database. Of 239,756 closed claims, 27,556 (11.5%) involved family physicians. Of these 27,556 closed claims, 8797 (31.9%) resulted in a payment, and the average payment was $164,107. In the entire registry, 29.5% of closed claims were paid, and the average payment was $209,156. The most common allegation among family medicine closed claims was diagnostic error, and the most prevalent diagnosis was acute myocardial infarction, which represented 24.1% of closed claims with diagnostic errors. Diagnostic errors related to patients with breast cancer represented the next most common condition, accounting for 21.3% of closed claims with diagnostic errors. MPL issues are common and are important to all practicing family physicians. Knowledge of the details of liability claims should assist practicing family physicians in improving quality of care, reducing patient injury, and reducing the incidence of MPL claims.
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Using video recording to identify management errors in pediatric trauma resuscitation.
Oakley, Ed; Stocker, Sergio; Staubli, Georg; Young, Simon
2006-03-01
To determine the ability of video recording to identify management errors in trauma resuscitation and to compare this method with medical record review. The resuscitation of children who presented to the emergency department of the Royal Children's Hospital between February 19, 2001, and August 18, 2002, for whom the trauma team was activated was video recorded. The tapes were analyzed, and management was compared with Advanced Trauma Life Support guidelines. Deviations from these guidelines were recorded as errors. Fifty video recordings were analyzed independently by 2 reviewers. Medical record review was undertaken for a cohort of the most seriously injured patients, and errors were identified. The errors detected with the 2 methods were compared. Ninety resuscitations were video recorded and analyzed. An average of 5.9 errors per resuscitation was identified with this method (range: 1-12 errors). Twenty-five children (28%) had an injury severity score of >11; there was an average of 2.16 errors per patient in this group. Only 10 (20%) of these errors were detected in the medical record review. Medical record review detected an additional 8 errors that were not evident on the video recordings. Concordance between independent reviewers was high, with 93% agreement. Video recording is more effective than medical record review in detecting management errors in pediatric trauma resuscitation. Management errors in pediatric trauma resuscitation are common and often involve basic resuscitation principles. Resuscitation of the most seriously injured children was associated with fewer errors. Video recording is a useful adjunct to trauma resuscitation auditing.
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Spatial interpolation of solar global radiation
NASA Astrophysics Data System (ADS)
Lussana, C.; Uboldi, F.; Antoniazzi, C.
2010-09-01
Solar global radiation is defined as the radiant flux incident onto an area element of the terrestrial surface. Its direct knowledge plays a crucial role in many applications, from agrometeorology to environmental meteorology. The ARPA Lombardia's meteorological network includes about one hundred of pyranometers, mostly distributed in the southern part of the Alps and in the centre of the Po Plain. A statistical interpolation method based on an implementation of the Optimal Interpolation is applied to the hourly average of the solar global radiation observations measured by the ARPA Lombardia's network. The background field is obtained using SMARTS (The Simple Model of the Atmospheric Radiative Transfer of Sunshine, Gueymard, 2001). The model is initialised by assuming clear sky conditions and it takes into account the solar position and orography related effects (shade and reflection). The interpolation of pyranometric observations introduces in the analysis fields information about cloud presence and influence. A particular effort is devoted to prevent observations affected by large errors of different kinds (representativity errors, systematic errors, gross errors) from entering the analysis procedure. The inclusion of direct cloud information from satellite observations is also planned.
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Andreasen Struijk, Lotte N S; Bentsen, Bo; Gaihede, Michael; Lontis, Eugen R
2017-11-01
For severely paralyzed individuals, alternative computer interfaces are becoming increasingly essential for everyday life as social and vocational activities are facilitated by information technology and as the environment becomes more automatic and remotely controllable. Tongue computer interfaces have proven to be desirable by the users partly due to their high degree of aesthetic acceptability, but so far the mature systems have shown a relatively low error-free text typing efficiency. This paper evaluated the intra-oral inductive tongue computer interface (ITCI) in its intended use: Error-free text typing in a generally available text editing system, Word. Individuals with tetraplegia and able bodied individuals used the ITCI for typing using a MATLAB interface and for Word typing for 4 to 5 experimental days, and the results showed an average error-free text typing rate in Word of 11.6 correct characters/min across all participants and of 15.5 correct characters/min for participants familiar with tongue piercings. Improvements in typing rates between the sessions suggest that typing ratescan be improved further through long-term use of the ITCI.
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Dauwalter, D.C.; Fisher, W.L.; Belt, K.C.
2006-01-01
We tested the precision and accuracy of the Trimble GeoXT??? global positioning system (GPS) handheld receiver on point and area features and compared estimates of stream habitat dimensions (e.g., lengths and areas of riffles and pools) that were made in three different Oklahoma streams using the GPS receiver and a tape measure. The precision of differentially corrected GPS (DGPS) points was not affected by the number of GPS position fixes (i.e., geographic location estimates) averaged per DGPS point. Horizontal error of points ranged from 0.03 to 2.77 m and did not differ with the number of position fixes per point. The error of area measurements ranged from 0.1% to 110.1% but decreased as the area increased. Again, error was independent of the number of position fixes averaged per polygon corner. The estimates of habitat lengths, widths, and areas did not differ when measured using two methods of data collection (GPS and a tape measure), nor did the differences among methods change at three stream sites with contrasting morphologies. Measuring features with a GPS receiver was up to 3.3 times faster on average than using a tape measure, although signal interference from high streambanks or overhanging vegetation occasionally limited satellite signal availability and prolonged measurements with a GPS receiver. There were also no differences in precision of habitat dimensions when mapped using a continuous versus a position fix average GPS data collection method. Despite there being some disadvantages to using the GPS in stream habitat studies, measuring stream habitats with a GPS resulted in spatially referenced data that allowed the assessment of relative habitat position and changes in habitats over time, and was often faster than using a tape measure. For most spatial scales of interest, the precision and accuracy of DGPS data are adequate and have logistical advantages when compared to traditional methods of measurement. ?? 2006 Springer Science+Business Media, Inc.
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Comparison of algorithms for automatic border detection of melanoma in dermoscopy images
NASA Astrophysics Data System (ADS)
Srinivasa Raghavan, Sowmya; Kaur, Ravneet; LeAnder, Robert
2016-09-01
Melanoma is one of the most rapidly accelerating cancers in the world [1]. Early diagnosis is critical to an effective cure. We propose a new algorithm for more accurately detecting melanoma borders in dermoscopy images. Proper border detection requires eliminating occlusions like hair and bubbles by processing the original image. The preprocessing step involves transforming the RGB image to the CIE L*u*v* color space, in order to decouple brightness from color information, then increasing contrast, using contrast-limited adaptive histogram equalization (CLAHE), followed by artifacts removal using a Gaussian filter. After preprocessing, the Chen-Vese technique segments the preprocessed images to create a lesion mask which undergoes a morphological closing operation. Next, the largest central blob in the lesion is detected, after which, the blob is dilated to generate an image output mask. Finally, the automatically-generated mask is compared to the manual mask by calculating the XOR error [3]. Our border detection algorithm was developed using training and test sets of 30 and 20 images, respectively. This detection method was compared to the SRM method [4] by calculating the average XOR error for each of the two algorithms. Average error for test images was 0.10, using the new algorithm, and 0.99, using SRM method. In comparing the average error values produced by the two algorithms, it is evident that the average XOR error for our technique is lower than the SRM method, thereby implying that the new algorithm detects borders of melanomas more accurately than the SRM algorithm.
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NASA Astrophysics Data System (ADS)
Fujiwara, Takahiro; Uchiito, Haruki; Tokairin, Tomoya; Kawai, Hiroyuki
2017-04-01
Regarding Structural Health Monitoring (SHM) for seismic acceleration, Wireless Sensor Networks (WSN) is a promising tool for low-cost monitoring. Compressed sensing and transmission schemes have been drawing attention to achieve effective data collection in WSN. Especially, SHM systems installing massive nodes of WSN require efficient data transmission due to restricted communications capability. The dominant frequency band of seismic acceleration is occupied within 100 Hz or less. In addition, the response motions on upper floors of a structure are activated at a natural frequency, resulting in induced shaking at the specified narrow band. Focusing on the vibration characteristics of structures, we introduce data compression techniques for seismic acceleration monitoring in order to reduce the amount of transmission data. We carry out a compressed sensing and transmission scheme by band pass filtering for seismic acceleration data. The algorithm executes the discrete Fourier transform for the frequency domain and band path filtering for the compressed transmission. Assuming that the compressed data is transmitted through computer networks, restoration of the data is performed by the inverse Fourier transform in the receiving node. This paper discusses the evaluation of the compressed sensing for seismic acceleration by way of an average error. The results present the average error was 0.06 or less for the horizontal acceleration, in conditions where the acceleration was compressed into 1/32. Especially, the average error on the 4th floor achieved a small error of 0.02. Those results indicate that compressed sensing and transmission technique is effective to reduce the amount of data with maintaining the small average error.
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Spatial Assessment of Model Errors from Four Regression Techniques
Lianjun Zhang; Jeffrey H. Gove; Jeffrey H. Gove
2005-01-01
Fomst modelers have attempted to account for the spatial autocorrelations among trees in growth and yield models by applying alternative regression techniques such as linear mixed models (LMM), generalized additive models (GAM), and geographicalIy weighted regression (GWR). However, the model errors are commonly assessed using average errors across the entire study...
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Flavour and identification threshold detection overview of Slovak adepts for certified testing.
Vietoris, VladimIr; Barborova, Petra; Jancovicova, Jana; Eliasova, Lucia; Karvaj, Marian
2016-07-01
During certification process of sensory assessors of Slovak certification body we obtained results for basic taste thresholds and lifestyle habits. 500 adult people were screened during experiment with food industry background. For analysis of basic and non basic tastes, we used standardized procedure of ISO 8586-1:1993. In flavour test experiment, group of (26-35 y.o) produced the lowest error ratio (1.438), highest is (56+ y.o.) group with result (2.0). Average error value based on gender for women was (1.510) in comparison to men (1.477). People with allergies have the average error ratio (1.437) in comparison to people without allergies (1.511). Non-smokers produced less errors (1.484) against the smokers (1.576). Another flavour threshold identification test detected differences among age groups (by age are values increased). The highest number of errors made by men in metallic taste was (24%) the same as made by women (22%). Higher error ratio made by men occurred in salty taste (19%) against women (10%). Analysis detected some differences between allergic/non-allergic, smokers/non-smokers groups.
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Analytical Evaluation of a Method of Midcourse Guidance for Rendezvous with Earth Satellites
NASA Technical Reports Server (NTRS)
Eggleston, John M.; Dunning, Robert S.
1961-01-01
A digital-computer simulation was made of the midcourse or ascent phase of a rendezvous between a ferry vehicle and a space station. The simulation involved a closed-loop guidance system in which both the relative position and relative velocity between ferry and station are measured (by simulated radar) and the relative-velocity corrections required to null the miss distance are computed and applied. The results are used to study the effectiveness of a particular set of guidance equations and to study the effects of errors in the launch conditions and errors in the navigation data. A number of trajectories were investigated over a variety of initial conditions for cases in which the space station was in a circular orbit and also in an elliptic orbit. Trajectories are described in terms of a rotating coordinate system fixed in the station. As a result of this study the following conclusions are drawn. Successful rendezvous can be achieved even with launch conditions which are substantially less accurate than those obtained with present-day techniques. The average total-velocity correction required during the midcourse phase is directly proportional to the radar accuracy but the miss distance is not. Errors in the time of booster burnout or in the position of the ferry at booster burnout are less important than errors in the ferry velocity at booster burnout. The use of dead bands to account for errors in the navigational (radar) equipment appears to depend upon a compromise between the magnitude of the velocity corrections to be made and the allowable miss distance at the termination of the midcourse phase of the rendezvous. When approximate guidance equations are used, there are limits on their accuracy which are dependent on the angular distance about the earth to the expected point of rendezvous.
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Leverentz, Hannah R; Truhlar, Donald G
2009-06-09
This work tests the capability of the electrostatically embedded many-body (EE-MB) method to calculate accurate (relative to conventional calculations carried out at the same level of electronic structure theory and with the same basis set) binding energies of mixed clusters (as large as 9-mers) consisting of water, ammonia, sulfuric acid, and ammonium and bisulfate ions. This work also investigates the dependence of the accuracy of the EE-MB approximation on the type and origin of the charges used for electrostatically embedding these clusters. The conclusions reached are that for all of the clusters and sets of embedding charges studied in this work, the electrostatically embedded three-body (EE-3B) approximation is capable of consistently yielding relative errors of less than 1% and an average relative absolute error of only 0.3%, and that the performance of the EE-MB approximation does not depend strongly on the specific set of embedding charges used. The electrostatically embedded pairwise approximation has errors about an order of magnitude larger than EE-3B. This study also explores the question of why the accuracy of the EE-MB approximation shows such little dependence on the types of embedding charges employed.
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On the error probability of general tree and trellis codes with applications to sequential decoding
NASA Technical Reports Server (NTRS)
Johannesson, R.
1973-01-01
An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random binary tree codes is derived and shown to be independent of the length of the tree. An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random L-branch binary trellis codes of rate R = 1/n is derived which separates the effects of the tail length T and the memory length M of the code. It is shown that the bound is independent of the length L of the information sequence. This implication is investigated by computer simulations of sequential decoding utilizing the stack algorithm. These simulations confirm the implication and further suggest an empirical formula for the true undetected decoding error probability with sequential decoding.
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Schoenberg, Mike R; Rum, Ruba S
2017-11-01
Rapid, clear and efficient communication of neuropsychological results is essential to benefit patient care. Errors in communication are a lead cause of medical errors; nevertheless, there remains a lack of consistency in how neuropsychological scores are communicated. A major limitation in the communication of neuropsychological results is the inconsistent use of qualitative descriptors for standardized test scores and the use of vague terminology. PubMed search from 1 Jan 2007 to 1 Aug 2016 to identify guidelines or consensus statements for the description and reporting of qualitative terms to communicate neuropsychological test scores was conducted. The review found the use of confusing and overlapping terms to describe various ranges of percentile standardized test scores. In response, we propose a simplified set of qualitative descriptors for normalized test scores (Q-Simple) as a means to reduce errors in communicating test results. The Q-Simple qualitative terms are: 'very superior', 'superior', 'high average', 'average', 'low average', 'borderline' and 'abnormal/impaired'. A case example illustrates the proposed Q-Simple qualitative classification system to communicate neuropsychological results for neurosurgical planning. The Q-Simple qualitative descriptor system is aimed as a means to improve and standardize communication of standardized neuropsychological test scores. Research are needed to further evaluate neuropsychological communication errors. Conveying the clinical implications of neuropsychological results in a manner that minimizes risk for communication errors is a quintessential component of evidence-based practice. Copyright © 2017 Elsevier B.V. All rights reserved.
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Empirical parameterization of setup, swash, and runup
Stockdon, H.F.; Holman, R.A.; Howd, P.A.; Sallenger, A.H.
2006-01-01
Using shoreline water-level time series collected during 10 dynamically diverse field experiments, an empirical parameterization for extreme runup, defined by the 2% exceedence value, has been developed for use on natural beaches over a wide range of conditions. Runup, the height of discrete water-level maxima, depends on two dynamically different processes; time-averaged wave setup and total swash excursion, each of which is parameterized separately. Setup at the shoreline was best parameterized using a dimensional form of the more common Iribarren-based setup expression that includes foreshore beach slope, offshore wave height, and deep-water wavelength. Significant swash can be decomposed into the incident and infragravity frequency bands. Incident swash is also best parameterized using a dimensional form of the Iribarren-based expression. Infragravity swash is best modeled dimensionally using offshore wave height and wavelength and shows no statistically significant linear dependence on either foreshore or surf-zone slope. On infragravity-dominated dissipative beaches, the magnitudes of both setup and swash, modeling both incident and infragravity frequency components together, are dependent only on offshore wave height and wavelength. Statistics of predicted runup averaged over all sites indicate a - 17 cm bias and an rms error of 38 cm: the mean observed runup elevation for all experiments was 144 cm. On intermediate and reflective beaches with complex foreshore topography, the use of an alongshore-averaged beach slope in practical applications of the runup parameterization may result in a relative runup error equal to 51% of the fractional variability between the measured and the averaged slope.
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Reducing patient identification errors related to glucose point-of-care testing.
Alreja, Gaurav; Setia, Namrata; Nichols, James; Pantanowitz, Liron
2011-01-01
Patient identification (ID) errors in point-of-care testing (POCT) can cause test results to be transferred to the wrong patient's chart or prevent results from being transmitted and reported. Despite the implementation of patient barcoding and ongoing operator training at our institution, patient ID errors still occur with glucose POCT. The aim of this study was to develop a solution to reduce identification errors with POCT. Glucose POCT was performed by approximately 2,400 clinical operators throughout our health system. Patients are identified by scanning in wristband barcodes or by manual data entry using portable glucose meters. Meters are docked to upload data to a database server which then transmits data to any medical record matching the financial number of the test result. With a new model, meters connect to an interface manager where the patient ID (a nine-digit account number) is checked against patient registration data from admission, discharge, and transfer (ADT) feeds and only matched results are transferred to the patient's electronic medical record. With the new process, the patient ID is checked prior to testing, and testing is prevented until ID errors are resolved. When averaged over a period of a month, ID errors were reduced to 3 errors/month (0.015%) in comparison with 61.5 errors/month (0.319%) before implementing the new meters. Patient ID errors may occur with glucose POCT despite patient barcoding. The verification of patient identification should ideally take place at the bedside before testing occurs so that the errors can be addressed in real time. The introduction of an ADT feed directly to glucose meters reduced patient ID errors in POCT.
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Reducing patient identification errors related to glucose point-of-care testing
Alreja, Gaurav; Setia, Namrata; Nichols, James; Pantanowitz, Liron
2011-01-01
Background: Patient identification (ID) errors in point-of-care testing (POCT) can cause test results to be transferred to the wrong patient's chart or prevent results from being transmitted and reported. Despite the implementation of patient barcoding and ongoing operator training at our institution, patient ID errors still occur with glucose POCT. The aim of this study was to develop a solution to reduce identification errors with POCT. Materials and Methods: Glucose POCT was performed by approximately 2,400 clinical operators throughout our health system. Patients are identified by scanning in wristband barcodes or by manual data entry using portable glucose meters. Meters are docked to upload data to a database server which then transmits data to any medical record matching the financial number of the test result. With a new model, meters connect to an interface manager where the patient ID (a nine-digit account number) is checked against patient registration data from admission, discharge, and transfer (ADT) feeds and only matched results are transferred to the patient's electronic medical record. With the new process, the patient ID is checked prior to testing, and testing is prevented until ID errors are resolved. Results: When averaged over a period of a month, ID errors were reduced to 3 errors/month (0.015%) in comparison with 61.5 errors/month (0.319%) before implementing the new meters. Conclusion: Patient ID errors may occur with glucose POCT despite patient barcoding. The verification of patient identification should ideally take place at the bedside before testing occurs so that the errors can be addressed in real time. The introduction of an ADT feed directly to glucose meters reduced patient ID errors in POCT. PMID:21633490
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Assessing the accuracy of ANFIS, EEMD-GRNN, PCR, and MLR models in predicting PM2.5
NASA Astrophysics Data System (ADS)
Ausati, Shadi; Amanollahi, Jamil
2016-10-01
Since Sanandaj is considered one of polluted cities of Iran, prediction of any type of pollution especially prediction of suspended particles of PM2.5, which are the cause of many diseases, could contribute to health of society by timely announcements and prior to increase of PM2.5. In order to predict PM2.5 concentration in the Sanandaj air the hybrid models consisting of an ensemble empirical mode decomposition and general regression neural network (EEMD-GRNN), Adaptive Neuro-Fuzzy Inference System (ANFIS), principal component regression (PCR), and linear model such as multiple liner regression (MLR) model were used. In these models the data of suspended particles of PM2.5 were the dependent variable and the data related to air quality including PM2.5, PM10, SO2, NO2, CO, O3 and meteorological data including average minimum temperature (Min T), average maximum temperature (Max T), average atmospheric pressure (AP), daily total precipitation (TP), daily relative humidity level of the air (RH) and daily wind speed (WS) for the year 2014 in Sanandaj were the independent variables. Among the used models, EEMD-GRNN model with values of R2 = 0.90, root mean square error (RMSE) = 4.9218 and mean absolute error (MAE) = 3.4644 in the training phase and with values of R2 = 0.79, RMSE = 5.0324 and MAE = 3.2565 in the testing phase, exhibited the best function in predicting this phenomenon. It can be concluded that hybrid models have accurate results to predict PM2.5 concentration compared with linear model.
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Dielectrophoresis enhances the whitening effect of carbamide peroxide on enamel.
Ivanoff, Chris S; Hottel, Timothy L; Garcia-Godoy, Franklin; Riga, Alan T
2011-10-01
To compare the enamel whitening effect of a 20-minute dielectrophoresis enhanced electrochemical delivery to a 20-minute diffusion treatment. Forty freshly extracted human teeth without detectable caries or restoration were stored in distilled water at 4 degrees C and used within 1 month of extraction. Two different bleaching gels (Plus White 5 Minute Speed Whitening Gel and 35% Opalescence PF gel) were tested. The study had two parts: Part 1--Quantitative comparison of hydrogen peroxide (H2O2, HP) absorption--following application of an over-the-counter 35% HP whitening gel (Plus White 5 Minute Speed Whitening Gel) to 30 (n = 30) extracted human teeth by conventional diffusion or dielectrophoresis. The amount of H2O2 that diffused from the dentin was measured by a colorimetric oxidation-reduction reaction kit. HP concentration was measured by UV-Vis spectroscopy at 550 nm. Part 2--HP diffusion in stained teeth--35% carbamide peroxide whitening gel (35% Opalescence PF gel) was applied to 10 extracted human teeth (n = 10) stained by immersion in a black tea solution for 48 hours. The teeth were randomly assigned to the 20-minute dielectrophoresis or diffusion treatment group; whitening was evaluated by a dental spectrophotometer and macro-photography. Part 1: The analysis found significant differences between both groups with relative percent errors of 3% or less (a single outlier had an RPE of 12%). The average absorbance for the dielectrophoresis group in round 1 was 79% greater than the diffusion group. The average absorbance for the dielectrophoresis group in round 2 was 130% greater than the diffusion group. A single-factor ANOVA found a statistically significant difference between the diffusion and dielectrophoresis groups (P = 0.01). Part 2--The average change in Shade Guide Units (SGU) was 0.6 for the diffusion group, well under the error of measurement of 0.82 SGU. The average change in SGU for the dielectrophoresis group was 9, significantly above the error of measurement and 14 times or 1,400% greater than the diffusion group average. A single-factor ANOVA found a statistically significant difference between the diffusion and dielectrophoresis treatment groups (P < 0.001).
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Lin, E-mail: godyalin@163.com; Singh, Uttam, E-mail: uttamsingh@hri.res.in; Pati, Arun K., E-mail: akpati@hri.res.in
Compact expressions for the average subentropy and coherence are obtained for random mixed states that are generated via various probability measures. Surprisingly, our results show that the average subentropy of random mixed states approaches the maximum value of the subentropy which is attained for the maximally mixed state as we increase the dimension. In the special case of the random mixed states sampled from the induced measure via partial tracing of random bipartite pure states, we establish the typicality of the relative entropy of coherence for random mixed states invoking the concentration of measure phenomenon. Our results also indicate thatmore » mixed quantum states are less useful compared to pure quantum states in higher dimension when we extract quantum coherence as a resource. This is because of the fact that average coherence of random mixed states is bounded uniformly, however, the average coherence of random pure states increases with the increasing dimension. As an important application, we establish the typicality of relative entropy of entanglement and distillable entanglement for a specific class of random bipartite mixed states. In particular, most of the random states in this specific class have relative entropy of entanglement and distillable entanglement equal to some fixed number (to within an arbitrary small error), thereby hugely reducing the complexity of computation of these entanglement measures for this specific class of mixed states.« less
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Data challenges in estimating the capacity value of solar photovoltaics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gami, Dhruv; Sioshansi, Ramteen; Denholm, Paul
We examine the robustness of solar capacity-value estimates to three important data issues. The first is the sensitivity to using hourly averaged as opposed to subhourly solar-insolation data. The second is the sensitivity to errors in recording and interpreting load data. The third is the sensitivity to using modeled as opposed to measured solar-insolation data. We demonstrate that capacity-value estimates of solar are sensitive to all three of these factors, with potentially large errors in the capacity-value estimate in a particular year. If multiple years of data are available, the biases introduced by using hourly averaged solar-insolation can be smoothedmore » out. Multiple years of data will not necessarily address the other data-related issues that we examine. Our analysis calls into question the accuracy of a number of solar capacity-value estimates relying exclusively on modeled solar-insolation data that are reported in the literature (including our own previous works). Lastly, our analysis also suggests that multiple years’ historical data should be used for remunerating solar generators for their capacity value in organized wholesale electricity markets.« less
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Data Challenges in Estimating the Capacity Value of Solar Photovoltaics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gami, Dhruv; Sioshansi, Ramteen; Denholm, Paul
We examine the robustness of solar capacity-value estimates to three important data issues. The first is the sensitivity to using hourly averaged as opposed to subhourly solar-insolation data. The second is the sensitivity to errors in recording and interpreting load data. The third is the sensitivity to using modeled as opposed to measured solar-insolation data. We demonstrate that capacity-value estimates of solar are sensitive to all three of these factors, with potentially large errors in the capacity-value estimate in a particular year. If multiple years of data are available, the biases introduced by using hourly averaged solar-insolation can be smoothedmore » out. Multiple years of data will not necessarily address the other data-related issues that we examine. Our analysis calls into question the accuracy of a number of solar capacity-value estimates relying exclusively on modeled solar-insolation data that are reported in the literature (including our own previous works). Our analysis also suggests that multiple years' historical data should be used for remunerating solar generators for their capacity value in organized wholesale electricity markets.« less
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Data challenges in estimating the capacity value of solar photovoltaics
Gami, Dhruv; Sioshansi, Ramteen; Denholm, Paul
2017-04-30
We examine the robustness of solar capacity-value estimates to three important data issues. The first is the sensitivity to using hourly averaged as opposed to subhourly solar-insolation data. The second is the sensitivity to errors in recording and interpreting load data. The third is the sensitivity to using modeled as opposed to measured solar-insolation data. We demonstrate that capacity-value estimates of solar are sensitive to all three of these factors, with potentially large errors in the capacity-value estimate in a particular year. If multiple years of data are available, the biases introduced by using hourly averaged solar-insolation can be smoothedmore » out. Multiple years of data will not necessarily address the other data-related issues that we examine. Our analysis calls into question the accuracy of a number of solar capacity-value estimates relying exclusively on modeled solar-insolation data that are reported in the literature (including our own previous works). Lastly, our analysis also suggests that multiple years’ historical data should be used for remunerating solar generators for their capacity value in organized wholesale electricity markets.« less
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On the determinants of the conjunction fallacy: probability versus inductive confirmation.
Tentori, Katya; Crupi, Vincenzo; Russo, Selena
2013-02-01
Major recent interpretations of the conjunction fallacy postulate that people assess the probability of a conjunction according to (non-normative) averaging rules as applied to the constituents' probabilities or represent the conjunction fallacy as an effect of random error in the judgment process. In the present contribution, we contrast such accounts with a different reading of the phenomenon based on the notion of inductive confirmation as defined by contemporary Bayesian theorists. Averaging rule hypotheses along with the random error model and many other existing proposals are shown to all imply that conjunction fallacy rates would rise as the perceived probability of the added conjunct does. By contrast, our account predicts that the conjunction fallacy depends on the added conjunct being perceived as inductively confirmed. Four studies are reported in which the judged probability versus confirmation of the added conjunct have been systematically manipulated and dissociated. The results consistently favor a confirmation-theoretic account of the conjunction fallacy against competing views. Our proposal is also discussed in connection with related issues in the study of human inductive reasoning. 2013 APA, all rights reserved
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Intervention program efficacy for spelling difficulties.
Sampaio, Maria Nobre; Capellini, Simone Aparecida
2014-01-01
To develop an intervention procedure for spelling difficulties and to verify the effectiveness of the intervention program in students with lower spelling performance. We developed an intervention program for spelling difficulties, according to the semiology of the errors. The program consisted of three modules totaling 16 sessions. The study included 40 students of the third to fifth grade of public elementary education of the city of Marilia (SP), of both genders, in aged of eight to 12 years old, being distributed in the following groups: GI (20 students with lower spelling performance) and GII (20 students with higher spelling performance). In situation of pre and post-testing, all groups were submitted to the Pro-Orthography. The results statistically analyzed showed that, in general, all groups had average of right that has higher in post-testing, reducing the types of errors second semiologycal classification, mainly related to natural spelling errors. However, the results also showed that the groups submitted to the intervention program showed better performance on spelling tests in relation to not submitted. The intervention program developed was effective once the groups submitted showed better performance on spelling tests in relation to not submitted. Therefore, the intervention program can help professionals in the Health and Education to minimize the problems related to spelling, giving students an intervention that is effective for the development of the spelling knowledge.
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Eigenvector method for umbrella sampling enables error analysis
Thiede, Erik H.; Van Koten, Brian; Weare, Jonathan; Dinner, Aaron R.
2016-01-01
Umbrella sampling efficiently yields equilibrium averages that depend on exploring rare states of a model by biasing simulations to windows of coordinate values and then combining the resulting data with physical weighting. Here, we introduce a mathematical framework that casts the step of combining the data as an eigenproblem. The advantage to this approach is that it facilitates error analysis. We discuss how the error scales with the number of windows. Then, we derive a central limit theorem for averages that are obtained from umbrella sampling. The central limit theorem suggests an estimator of the error contributions from individual windows, and we develop a simple and computationally inexpensive procedure for implementing it. We demonstrate this estimator for simulations of the alanine dipeptide and show that it emphasizes low free energy pathways between stable states in comparison to existing approaches for assessing error contributions. Our work suggests the possibility of using the estimator and, more generally, the eigenvector method for umbrella sampling to guide adaptation of the simulation parameters to accelerate convergence. PMID:27586912
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Michael, Claire W; Naik, Kalyani; McVicker, Michael
2013-05-01
We developed a value stream map (VSM) of the Papanicolaou test procedure to identify opportunities to reduce waste and errors, created a new VSM, and implemented a new process emphasizing Lean tools. Preimplementation data revealed the following: (1) processing time (PT) for 1,140 samples averaged 54 hours; (2) 27 accessioning errors were detected on review of 357 random requisitions (7.6%); (3) 5 of the 20,060 tests had labeling errors that had gone undetected in the processing stage. Four were detected later during specimen processing but 1 reached the reporting stage. Postimplementation data were as follows: (1) PT for 1,355 samples averaged 31 hours; (2) 17 accessioning errors were detected on review of 385 random requisitions (4.4%); and (3) no labeling errors were undetected. Our results demonstrate that implementation of Lean methods, such as first-in first-out processes and minimizing batch size by staff actively participating in the improvement process, allows for higher quality, greater patient safety, and improved efficiency.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, J; Shi, W; Andrews, D
2016-06-15
Purpose: To compare online image registrations of TrueBeam cone-beam CT (CBCT) and BrainLab ExacTrac x-ray imaging systems for cranial radiotherapy. Method: Phantom and patient studies were performed on a Varian TrueBeam STx linear accelerator (Version 2.5), which is integrated with a BrainLab ExacTrac imaging system (Version 6.1.1). The phantom study was based on a Rando head phantom, which was designed to evaluate isocenter-location dependence of the image registrations. Ten isocenters were selected at various locations in the phantom, which represented clinical treatment sites. CBCT and ExacTrac x-ray images were taken when the phantom was located at each isocenter. The patientmore » study included thirteen patients. CBCT and ExacTrac x-ray images were taken at each patient’s treatment position. Six-dimensional image registrations were performed on CBCT and ExacTrac, and residual errors calculated from CBCT and ExacTrac were compared. Results: In the phantom study, the average residual-error differences between CBCT and ExacTrac image registrations were: 0.16±0.10 mm, 0.35±0.20 mm, and 0.21±0.15 mm, in the vertical, longitudinal, and lateral directions, respectively. The average residual-error differences in the rotation, roll, and pitch were: 0.36±0.11 degree, 0.14±0.10 degree, and 0.12±0.10 degree, respectively. In the patient study, the average residual-error differences in the vertical, longitudinal, and lateral directions were: 0.13±0.13 mm, 0.37±0.21 mm, 0.22±0.17 mm, respectively. The average residual-error differences in the rotation, roll, and pitch were: 0.30±0.10 degree, 0.18±0.11 degree, and 0.22±0.13 degree, respectively. Larger residual-error differences (up to 0.79 mm) were observed in the longitudinal direction in the phantom and patient studies where isocenters were located in or close to frontal lobes, i.e., located superficially. Conclusion: Overall, the average residual-error differences were within 0.4 mm in the translational directions and were within 0.4 degree in the rotational directions.« less
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Performance of univariate forecasting on seasonal diseases: the case of tuberculosis.
Permanasari, Adhistya Erna; Rambli, Dayang Rohaya Awang; Dominic, P Dhanapal Durai
2011-01-01
The annual disease incident worldwide is desirable to be predicted for taking appropriate policy to prevent disease outbreak. This chapter considers the performance of different forecasting method to predict the future number of disease incidence, especially for seasonal disease. Six forecasting methods, namely linear regression, moving average, decomposition, Holt-Winter's, ARIMA, and artificial neural network (ANN), were used for disease forecasting on tuberculosis monthly data. The model derived met the requirement of time series with seasonality pattern and downward trend. The forecasting performance was compared using similar error measure in the base of the last 5 years forecast result. The findings indicate that ARIMA model was the most appropriate model since it obtained the less relatively error than the other model.
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Barriers to medication error reporting among hospital nurses.
Rutledge, Dana N; Retrosi, Tina; Ostrowski, Gary
2018-03-01
The study purpose was to report medication error reporting barriers among hospital nurses, and to determine validity and reliability of an existing medication error reporting barriers questionnaire. Hospital medication errors typically occur between ordering of a medication to its receipt by the patient with subsequent staff monitoring. To decrease medication errors, factors surrounding medication errors must be understood; this requires reporting by employees. Under-reporting can compromise patient safety by disabling improvement efforts. This 2017 descriptive study was part of a larger workforce engagement study at a faith-based Magnet ® -accredited community hospital in California (United States). Registered nurses (~1,000) were invited to participate in the online survey via email. Reported here are sample demographics (n = 357) and responses to the 20-item medication error reporting barriers questionnaire. Using factor analysis, four factors that accounted for 67.5% of the variance were extracted. These factors (subscales) were labelled Fear, Cultural Barriers, Lack of Knowledge/Feedback and Practical/Utility Barriers; each demonstrated excellent internal consistency. The medication error reporting barriers questionnaire, originally developed in long-term care, demonstrated good validity and excellent reliability among hospital nurses. Substantial proportions of American hospital nurses (11%-48%) considered specific factors as likely reporting barriers. Average scores on most barrier items were categorised "somewhat unlikely." The highest six included two barriers concerning the time-consuming nature of medication error reporting and four related to nurses' fear of repercussions. Hospitals need to determine the presence of perceived barriers among nurses using questionnaires such as the medication error reporting barriers and work to encourage better reporting. Barriers to medication error reporting make it less likely that nurses will report medication errors, especially errors where patient harm is not apparent or where an error might be hidden. Such under-reporting impedes collection of accurate medication error data and prevents hospitals from changing harmful practices. © 2018 John Wiley & Sons Ltd.
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A Foot-Mounted Inertial Measurement Unit (IMU) Positioning Algorithm Based on Magnetic Constraint
Zou, Jiaheng
2018-01-01
With the development of related applications, indoor positioning techniques have been more and more widely developed. Based on Wi-Fi, Bluetooth low energy (BLE) and geomagnetism, indoor positioning techniques often rely on the physical location of fingerprint information. The focus and difficulty of establishing the fingerprint database are in obtaining a relatively accurate physical location with as little given information as possible. This paper presents a foot-mounted inertial measurement unit (IMU) positioning algorithm under the loop closure constraint based on magnetic information. It can provide relatively reliable position information without maps and geomagnetic information and provides a relatively accurate coordinate for the collection of a fingerprint database. In the experiment, the features extracted by the multi-level Fourier transform method proposed in this paper are validated and the validity of loop closure matching is tested with a RANSAC-based method. Moreover, the loop closure detection results show that the cumulative error of the trajectory processed by the graph optimization algorithm is significantly suppressed, presenting a good accuracy. The average error of the trajectory under loop closure constraint is controlled below 2.15 m. PMID:29494542
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A Foot-Mounted Inertial Measurement Unit (IMU) Positioning Algorithm Based on Magnetic Constraint.
Wang, Yan; Li, Xin; Zou, Jiaheng
2018-03-01
With the development of related applications, indoor positioning techniques have been more and more widely developed. Based on Wi-Fi, Bluetooth low energy (BLE) and geomagnetism, indoor positioning techniques often rely on the physical location of fingerprint information. The focus and difficulty of establishing the fingerprint database are in obtaining a relatively accurate physical location with as little given information as possible. This paper presents a foot-mounted inertial measurement unit (IMU) positioning algorithm under the loop closure constraint based on magnetic information. It can provide relatively reliable position information without maps and geomagnetic information and provides a relatively accurate coordinate for the collection of a fingerprint database. In the experiment, the features extracted by the multi-level Fourier transform method proposed in this paper are validated and the validity of loop closure matching is tested with a RANSAC-based method. Moreover, the loop closure detection results show that the cumulative error of the trajectory processed by the graph optimization algorithm is significantly suppressed, presenting a good accuracy. The average error of the trajectory under loop closure constraint is controlled below 2.15 m.
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Virtual sensors for on-line wheel wear and part roughness measurement in the grinding process.
Arriandiaga, Ander; Portillo, Eva; Sánchez, Jose A; Cabanes, Itziar; Pombo, Iñigo
2014-05-19
Grinding is an advanced machining process for the manufacturing of valuable complex and accurate parts for high added value sectors such as aerospace, wind generation, etc. Due to the extremely severe conditions inside grinding machines, critical process variables such as part surface finish or grinding wheel wear cannot be easily and cheaply measured on-line. In this paper a virtual sensor for on-line monitoring of those variables is presented. The sensor is based on the modelling ability of Artificial Neural Networks (ANNs) for stochastic and non-linear processes such as grinding; the selected architecture is the Layer-Recurrent neural network. The sensor makes use of the relation between the variables to be measured and power consumption in the wheel spindle, which can be easily measured. A sensor calibration methodology is presented, and the levels of error that can be expected are discussed. Validation of the new sensor is carried out by comparing the sensor's results with actual measurements carried out in an industrial grinding machine. Results show excellent estimation performance for both wheel wear and surface roughness. In the case of wheel wear, the absolute error is within the range of microns (average value 32 μm). In the case of surface finish, the absolute error is well below Ra 1 μm (average value 0.32 μm). The present approach can be easily generalized to other grinding operations.
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Zumsteg, Zachary; DeMarco, John; Lee, Steve P; Steinberg, Michael L; Lin, Chun Shu; McBride, William; Lin, Kevin; Wang, Pin-Chieh; Kupelian, Patrick; Lee, Percy
2012-06-01
On-board cone-beam computed tomography (CBCT) is currently available for alignment of patients with head-and-neck cancer before radiotherapy. However, daily CBCT is time intensive and increases the overall radiation dose. We assessed the feasibility of using the average couch shifts from the first several CBCTs to estimate and correct for the presumed systematic setup error. 56 patients with head-and-neck cancer who received daily CBCT before intensity-modulated radiation therapy had recorded shift values in the medial-lateral, superior-inferior, and anterior-posterior dimensions. The average displacements in each direction were calculated for each patient based on the first five or 10 CBCT shifts and were presumed to represent the systematic setup error. The residual error after this correction was determined by subtracting the calculated shifts from the shifts obtained using daily CBCT. The magnitude of the average daily residual three-dimensional (3D) error was 4.8 ± 1.4 mm, 3.9 ± 1.3 mm, and 3.7 ± 1.1 mm for uncorrected, five CBCT corrected, and 10 CBCT corrected protocols, respectively. With no image guidance, 40.8% of fractions would have been >5 mm off target. Using the first five CBCT shifts to correct subsequent fractions, this percentage decreased to 19.0% of all fractions delivered and decreased the percentage of patients with average daily 3D errors >5 mm from 35.7% to 14.3% vs. no image guidance. Using an average of the first 10 CBCT shifts did not significantly improve this outcome. Using the first five CBCT shift measurements as an estimation of the systematic setup error improves daily setup accuracy for a subset of patients with head-and-neck cancer receiving intensity-modulated radiation therapy and primarily benefited those with large 3D correction vectors (>5 mm). Daily CBCT is still necessary until methods are developed that more accurately determine which patients may benefit from alternative imaging strategies. Copyright © 2012 Elsevier Inc. All rights reserved.
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Stable estimate of primary OC/EC ratios in the EC tracer method
NASA Astrophysics Data System (ADS)
Chu, Shao-Hang
In fine particulate matter studies, the primary OC/EC ratio plays an important role in estimating the secondary organic aerosol contribution to PM2.5 concentrations using the EC tracer method. In this study, numerical experiments are carried out to test and compare various statistical techniques in the estimation of primary OC/EC ratios. The influence of random measurement errors in both primary OC and EC measurements on the estimation of the expected primary OC/EC ratios is examined. It is found that random measurement errors in EC generally create an underestimation of the slope and an overestimation of the intercept of the ordinary least-squares regression line. The Deming regression analysis performs much better than the ordinary regression, but it tends to overcorrect the problem by slightly overestimating the slope and underestimating the intercept. Averaging the ratios directly is usually undesirable because the average is strongly influenced by unrealistically high values of OC/EC ratios resulting from random measurement errors at low EC concentrations. The errors generally result in a skewed distribution of the OC/EC ratios even if the parent distributions of OC and EC are close to normal. When measured OC contains a significant amount of non-combustion OC Deming regression is a much better tool and should be used to estimate both the primary OC/EC ratio and the non-combustion OC. However, if the non-combustion OC is negligibly small the best and most robust estimator of the OC/EC ratio turns out to be the simple ratio of the OC and EC averages. It not only reduces random errors by averaging individual variables separately but also acts as a weighted average of ratios to minimize the influence of unrealistically high OC/EC ratios created by measurement errors at low EC concentrations. The median of OC/EC ratios ranks a close second, and the geometric mean of ratios ranks third. This is because their estimations are insensitive to questionable extreme values. A real world example is given using the ambient data collected from an Atlanta STN site during the winter of 2001-2002.
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Propagation of Radiosonde Pressure Sensor Errors to Ozonesonde Measurements
NASA Technical Reports Server (NTRS)
Stauffer, R. M.; Morris, G.A.; Thompson, A. M.; Joseph, E.; Coetzee, G. J. R.; Nalli, N. R.
2014-01-01
Several previous studies highlight pressure (or equivalently, pressure altitude) discrepancies between the radiosonde pressure sensor and that derived from a GPS flown with the radiosonde. The offsets vary during the ascent both in absolute and percent pressure differences. To investigate this problem further, a total of 731 radiosonde-ozonesonde launches from the Southern Hemisphere subtropics to Northern mid-latitudes are considered, with launches between 2005 - 2013 from both longer-term and campaign-based intensive stations. Five series of radiosondes from two manufacturers (International Met Systems: iMet, iMet-P, iMet-S, and Vaisala: RS80-15N and RS92-SGP) are analyzed to determine the magnitude of the pressure offset. Additionally, electrochemical concentration cell (ECC) ozonesondes from three manufacturers (Science Pump Corporation; SPC and ENSCI-Droplet Measurement Technologies; DMT) are analyzed to quantify the effects these offsets have on the calculation of ECC ozone (O3) mixing ratio profiles (O3MR) from the ozonesonde-measured partial pressure. Approximately half of all offsets are 0.6 hPa in the free troposphere, with nearly a third 1.0 hPa at 26 km, where the 1.0 hPa error represents 5 persent of the total atmospheric pressure. Pressure offsets have negligible effects on O3MR below 20 km (96 percent of launches lie within 5 percent O3MR error at 20 km). Ozone mixing ratio errors above 10 hPa (30 km), can approach greater than 10 percent ( 25 percent of launches that reach 30 km exceed this threshold). These errors cause disagreement between the integrated ozonesonde-only column O3 from the GPS and radiosonde pressure profile by an average of +6.5 DU. Comparisons of total column O3 between the GPS and radiosonde pressure profiles yield average differences of +1.1 DU when the O3 is integrated to burst with addition of the McPeters and Labow (2012) above-burst O3 column climatology. Total column differences are reduced to an average of -0.5 DU when the O3 profile is integrated to 10 hPa with subsequent addition of the O3 climatology above 10 hPa. The RS92 radiosondes are superior in performance compared to other radiosondes, with average 26 km errors of -0.12 hPa or +0.61 percent O3MR error. iMet-P radiosondes had average 26 km errors of -1.95 hPa or +8.75 percent O3MR error. Based on our analysis, we suggest that ozonesondes always be coupled with a GPS-enabled radiosonde and that pressure-dependent variables, such as O3MR, be recalculated-reprocessed using the GPS-measured altitude, especially when 26 km pressure offsets exceed 1.0 hPa 5 percent.
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NASA Technical Reports Server (NTRS)
Hou, Arthur Y.; Zhang, Sara Q.; deSilva, Arlindo M.
2000-01-01
Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of tropical rainfall and total precipitable water (TPW) observations from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve short-range forecast and reanalyses. We describe a "1+1"D procedure for assimilating 6-hr averaged rainfall and TPW in the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS, hence the "1+1"D designation. The scheme minimizes the least-square differences between the observed TPW and rain rates and those produced by the column model over the 6-hr analysis window. This 1+lD scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but uses analysis increments instead of the initial condition as the control variable. Results show that assimilating the TMI and SSM/I rainfall and TPW observations improves not only the precipitation and moisture fields but also key climate parameters such as clouds, the radiation, the upper-tropospheric moisture, and the large-scale circulation in the tropics. In particular, assimilating these data reduce the state-dependent systematic errors in the assimilated products. The improved analysis also provides better initial conditions for short-range forecasts, but the improvements in forecast are less than improvements in the time-averaged assimilation fields, indicating that using these data types is effective in correcting biases and other errors of the forecast model in data assimilation.
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NASA Technical Reports Server (NTRS)
Hou, Arthur Y.; Zhang, Sara Q.; daSilva, Arlindo M.
1999-01-01
Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of tropical rainfall and total precipitable water (TPW) observations from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve short-range forecast and reanalyses. We describe a 1+1D procedure for assimilating 6-hr averaged rainfall and TPW in the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS, hence the 1+1D designation. The scheme minimizes the least-square differences between the observed TPW and rain rates and those produced by the column model over the 6-hr analysis window. This 1+1D scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but uses analysis increments instead of the initial condition as the control variable. Results show that assimilating the TMI and SSW rainfall and TPW observations improves not only the precipitation and moisture fields but also key climate parameters such as clouds, the radiation, the upper-tropospheric moisture, and the large-scale circulation in the tropics. In particular, assimilating these data reduce the state-dependent systematic errors in the assimilated products. The improved analysis also provides better initial conditions for short-range forecasts, but the improvements in forecast are less than improvements in the time-averaged assimilation fields, indicating that using these data types is effective in correcting biases and other errors of the forecast model in data assimilation.
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Moore, Laura J.; Griggs, Gary B.
2002-01-01
Quantification of cliff retreat rates for the southern half of Santa Cruz County, CA, USA, located within the Monterey Bay National Marine Sanctuary, using the softcopy/geographic information system (GIS) methodology results in average cliff retreat rates of 7–15 cm/yr between 1953 and 1994. The coastal dunes at the southern end of Santa Cruz County migrate seaward and landward through time and display net accretion between 1953 and 1994, which is partially due to development. In addition, three critically eroding segments of coastline with high average erosion rates ranging from 20 to 63 cm/yr are identified as erosion ‘hotspots’. These locations include: Opal Cliffs, Depot Hill and Manresa. Although cliff retreat is episodic, spatially variable at the scale of meters, and the factors affecting cliff retreat vary along the Santa Cruz County coastline, there is a compensation between factors affecting retreat such that over the long-term the coastline maintains a relatively smooth configuration. The softcopy/GIS methodology significantly reduces errors inherent in the calculation of retreat rates in high-relief areas (e.g. erosion rates generated in this study are generally correct to within 10 cm) by removing errors due to relief displacement. Although the resulting root mean squared error for erosion rates is relatively small, simple projections of past erosion rates are inadequate to provide predictions of future cliff position. Improved predictions can be made for individual coastal segments by using a mean erosion rate and the standard deviation as guides to future cliff behavior in combination with an understanding of processes acting along the coastal segments in question. This methodology can be applied on any high-relief coast where retreat rates can be measured.
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Parton Dynamics Inferred from High-Mass Drell-Yan Dimuons Induced by 120 GeV p+D Interactions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ramson, Bryan J.
2018-01-01
Fermilab Experiment 906/SeaQuest (E906/SeaQuest) is the latest in a well established tradition of studying leptoproduction from the annihilation of a quark and anti-quark, known as the Drell-Yan process. The broad goal of E906/SeaQuest is measuring various properties of nucleon structure in order to learn more about quarks and Quantum Chromodynamics (QCD), the mathematical description of the strong force. The present work investigated violations of the Lam-Tung relation between virtual photon polarization and quark and lepton angular momentum. The violation of Lam-Tung can be explained as the signature of quark-nucleon spin-orbit coupling through the use of the Transverse-Momentum-Dependent (TMD) framework, whichmore » assumes that the initial transverse momentum of quarks is smaller than the hard scattering scale, but also non-negligible. An analysis of the angular moments in Drell-Yan collected by E906/SeaQuest was performed with four different configurations in order to estimate the systematic errors attributed to each correction. After correction for background and error propagation, the final extraction of the azimuthal moment excluding contributions from the trigger was ν = 0.151 ± 0.88(stat.) ± 0.346(syst.) at an average transverse momentum of 0.87 ± 0.50 GeV/c and an average dimuon mass of 5.48 ± 0.70 GeV. In the future, the magnitude of the systematic errors on the extraction could potentially be reduced by improving the quality of the trigger efficiency calculation, improving the intensity dependent event reconstruction efficiency, considering the changes in acceptance due to a beam shift relative to the E906/SeaQuest spectrometer, and improving the modeling of background.« less
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The accuracy of eyelid movement parameters for drowsiness detection.
Wilkinson, Vanessa E; Jackson, Melinda L; Westlake, Justine; Stevens, Bronwyn; Barnes, Maree; Swann, Philip; Rajaratnam, Shantha M W; Howard, Mark E
2013-12-15
Drowsiness is a major risk factor for motor vehicle and occupational accidents. Real-time objective indicators of drowsiness could potentially identify drowsy individuals with the goal of intervening before an accident occurs. Several ocular measures are promising objective indicators of drowsiness; however, there is a lack of studies evaluating their accuracy for detecting behavioral impairment due to drowsiness in real time. In this study, eye movement parameters were measured during vigilance tasks following restricted sleep and in a rested state (n = 33 participants) at three testing points (n = 71 data points) to compare ocular measures to a gold standard measure of drowsiness (OSLER). The utility of these parameters for detecting drowsiness-related errors was evaluated using receiver operating characteristic curves (ROC) (adjusted by clustering for participant) and identification of optimal cutoff levels for identifying frequent drowsiness-related errors (4 missed signals in a minute using OSLER). Their accuracy was tested for detecting increasing frequencies of behavioral lapses on a different task (psychomotor vigilance task [PVT]). Ocular variables which measured the average duration of eyelid closure (inter-event duration [IED]) and the ratio of the amplitude to velocity of eyelid closure were reliable indicators of frequent errors (area under the curve for ROC of 0.73 to 0.83, p < 0.05). IED produced a sensitivity and specificity of 71% and 88% for detecting ≥ 3 lapses (PVT) in a minute and 100% and 86% for ≥ 5 lapses. A composite measure of several eye movement characteristics (Johns Drowsiness Scale) provided sensitivities of 77% and 100% for detecting 3 and ≥ 5 lapses in a minute, with specificities of 85% and 83%, respectively. Ocular measures, particularly those measuring the average duration of episodes of eye closure are promising real-time indicators of drowsiness.
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Longato, Enrico; Garrido, Maria; Saccardo, Desy; Montesinos Guevara, Camila; Mani, Ali R; Bolognesi, Massimo; Amodio, Piero; Facchinetti, Andrea; Sparacino, Giovanni; Montagnese, Sara
2017-01-01
A popular method to estimate proximal/distal temperature (TPROX and TDIST) consists in calculating a weighted average of nine wireless sensors placed on pre-defined skin locations. Specifically, TPROX is derived from five sensors placed on the infra-clavicular and mid-thigh area (left and right) and abdomen, and TDIST from four sensors located on the hands and feet. In clinical practice, the loss/removal of one or more sensors is a common occurrence, but limited information is available on how this affects the accuracy of temperature estimates. The aim of this study was to determine the accuracy of temperature estimates in relation to number/position of sensors removed. Thirteen healthy subjects wore all nine sensors for 24 hours and reference TPROX and TDIST time-courses were calculated using all sensors. Then, all possible combinations of reduced subsets of sensors were simulated and suitable weights for each sensor calculated. The accuracy of TPROX and TDIST estimates resulting from the reduced subsets of sensors, compared to reference values, was assessed by the mean squared error, the mean absolute error (MAE), the cross-validation error and the 25th and 75th percentiles of the reconstruction error. Tables of the accuracy and sensor weights for all possible combinations of sensors are provided. For instance, in relation to TPROX, a subset of three sensors placed in any combination of three non-homologous areas (abdominal, right or left infra-clavicular, right or left mid-thigh) produced an error of 0.13°C MAE, while the loss/removal of the abdominal sensor resulted in an error of 0.25°C MAE, with the greater impact on the quality of the reconstruction. This information may help researchers/clinicians: i) evaluate the expected goodness of their TPROX and TDIST estimates based on the number of available sensors; ii) select the most appropriate subset of sensors, depending on goals and operational constraints.
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Methods for accurate estimation of net discharge in a tidal channel
Simpson, M.R.; Bland, R.
2000-01-01
Accurate estimates of net residual discharge in tidally affected rivers and estuaries are possible because of recently developed ultrasonic discharge measurement techniques. Previous discharge estimates using conventional mechanical current meters and methods based on stage/discharge relations or water slope measurements often yielded errors that were as great as or greater than the computed residual discharge. Ultrasonic measurement methods consist of: 1) the use of ultrasonic instruments for the measurement of a representative 'index' velocity used for in situ estimation of mean water velocity and 2) the use of the acoustic Doppler current discharge measurement system to calibrate the index velocity measurement data. Methods used to calibrate (rate) the index velocity to the channel velocity measured using the Acoustic Doppler Current Profiler are the most critical factors affecting the accuracy of net discharge estimation. The index velocity first must be related to mean channel velocity and then used to calculate instantaneous channel discharge. Finally, discharge is low-pass filtered to remove the effects of the tides. An ultrasonic velocity meter discharge-measurement site in a tidally affected region of the Sacramento-San Joaquin Rivers was used to study the accuracy of the index velocity calibration procedure. Calibration data consisting of ultrasonic velocity meter index velocity and concurrent acoustic Doppler discharge measurement data were collected during three time periods. Two sets of data were collected during a spring tide (monthly maximum tidal current) and one of data collected during a neap tide (monthly minimum tidal current). The relative magnitude of instrumental errors, acoustic Doppler discharge measurement errors, and calibration errors were evaluated. Calibration error was found to be the most significant source of error in estimating net discharge. Using a comprehensive calibration method, net discharge estimates developed from the three sets of calibration data differed by less than an average of 4 cubic meters per second, or less than 0.5% of a typical peak tidal discharge rate of 750 cubic meters per second.
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Hydrograph simulation models of the Hillsborough and Alafia Rivers, Florida: a preliminary report
Turner, James F.
1972-01-01
Mathematical (digital) models that simulate flood hydrographs from rainfall records have been developed for the following gaging stations in the Hillsborough and Alafia River basins of west-central Florida: Hillsborough River near Tampa, Alafia River at Lithia, and north Prong Alafia River near Keysville. These models, which were developed from historical streamflow and and rainfall records, are based on rainfall-runoff and unit-hydrograph procedures involving an arbitrary separation of the flood hydrograph. These models assume the flood hydrograph to be composed of only two flow components, direct (storm) runoff, and base flow. Expressions describing these two flow components are derived from streamflow and rainfall records and are combined analytically to form algorithms (models), which are programmed for processing on a digital computing system. Most Hillsborough and Alafia River flood discharges can be simulated with expected relative errors less than or equal to 30 percent and flood peaks can be simulated with average relative errors less than 15 percent. Because of the inadequate rainfall network that is used in obtaining input data for the North Prong Alafia River model, simulated peaks are frequently in error by more than 40 percent, particularly for storms having highly variable areal rainfall distribution. Simulation errors are the result of rainfall sample errors and, to a lesser extent, model inadequacy. Data errors associated with the determination of mean basin precipitation are the result of the small number and poor areal distribution of rainfall stations available for use in the study. Model inadequacy, however, is attributed to the basic underlying theory, particularly the rainfall-runoff relation. These models broaden and enhance existing water-management capabilities within these basins by allowing the establishment and implementation of programs providing for continued development in these areas. Specifically, the models serve not only as a basis for forecasting floods, but also for simulating hydrologic information needed in flood-plain mapping and delineating and evaluating alternative flood control and abatement plans.
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Longato, Enrico; Garrido, Maria; Saccardo, Desy; Montesinos Guevara, Camila; Mani, Ali R.; Bolognesi, Massimo; Amodio, Piero; Facchinetti, Andrea; Sparacino, Giovanni
2017-01-01
A popular method to estimate proximal/distal temperature (TPROX and TDIST) consists in calculating a weighted average of nine wireless sensors placed on pre-defined skin locations. Specifically, TPROX is derived from five sensors placed on the infra-clavicular and mid-thigh area (left and right) and abdomen, and TDIST from four sensors located on the hands and feet. In clinical practice, the loss/removal of one or more sensors is a common occurrence, but limited information is available on how this affects the accuracy of temperature estimates. The aim of this study was to determine the accuracy of temperature estimates in relation to number/position of sensors removed. Thirteen healthy subjects wore all nine sensors for 24 hours and reference TPROX and TDIST time-courses were calculated using all sensors. Then, all possible combinations of reduced subsets of sensors were simulated and suitable weights for each sensor calculated. The accuracy of TPROX and TDIST estimates resulting from the reduced subsets of sensors, compared to reference values, was assessed by the mean squared error, the mean absolute error (MAE), the cross-validation error and the 25th and 75th percentiles of the reconstruction error. Tables of the accuracy and sensor weights for all possible combinations of sensors are provided. For instance, in relation to TPROX, a subset of three sensors placed in any combination of three non-homologous areas (abdominal, right or left infra-clavicular, right or left mid-thigh) produced an error of 0.13°C MAE, while the loss/removal of the abdominal sensor resulted in an error of 0.25°C MAE, with the greater impact on the quality of the reconstruction. This information may help researchers/clinicians: i) evaluate the expected goodness of their TPROX and TDIST estimates based on the number of available sensors; ii) select the most appropriate subset of sensors, depending on goals and operational constraints. PMID:28666029
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ERIC Educational Resources Information Center
Birjandi, Parviz; Siyyari, Masood
2016-01-01
This paper presents the results of an investigation into the role of two personality traits (i.e. Agreeableness and Conscientiousness from the Big Five personality traits) in predicting rating error in the self-assessment and peer-assessment of composition writing. The average self/peer-rating errors of 136 Iranian English major undergraduates…
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The Accuracy of Aggregate Student Growth Percentiles as Indicators of Educator Performance
ERIC Educational Resources Information Center
Castellano, Katherine E.; McCaffrey, Daniel F.
2017-01-01
Mean or median student growth percentiles (MGPs) are a popular measure of educator performance, but they lack rigorous evaluation. This study investigates the error in MGP due to test score measurement error (ME). Using analytic derivations, we find that errors in the commonly used MGP are correlated with average prior latent achievement: Teachers…
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ERIC Educational Resources Information Center
Schumacher, Robin F.; Malone, Amelia S.
2017-01-01
The goal of this study was to describe fraction-calculation errors among fourth-grade students and to determine whether error patterns differed as a function of problem type (addition vs. subtraction; like vs. unlike denominators), orientation (horizontal vs. vertical), or mathematics-achievement status (low-, average-, or high-achieving). We…
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Li, Yan; Li, Na; Han, Qunying; He, Shuixiang; Bae, Ricard S.; Liu, Zhengwen; Lv, Yi; Shi, Bingyin
2014-01-01
This study was conducted to evaluate the performance of physical examination (PE) skills during our diagnostic medicine course and analyze the characteristics of the data collected to provide information for practical guidance to improve the quality of teaching. Seventy-two fourth-year medical students were enrolled in the study. All received an assessment of PE skills after receiving a 17-week formal training course and systematic teaching. Their performance was evaluated and recorded in detail using a checklist, which included 5 aspects of PE skills: examination techniques, communication and care skills, content items, appropriateness of examination sequence, and time taken. Error frequency and type were designated as the assessment parameters in the survey. The results showed that the distribution and the percentage in examination errors between male and female students and among the different body parts examined were significantly different (p<0.001). The average error frequency per student in females (0.875) was lower than in males (1.375) although the difference was not statistically significant (p = 0.167). The average error frequency per student in cardiac (1.267) and pulmonary (1.389) examinations was higher than in abdominal (0.867) and head, neck and nervous system examinations (0.917). Female students had a lower average error frequency than males in cardiac examinations (p = 0.041). Additionally, error in examination techniques was the highest type of error among the 5 aspects of PE skills irrespective of participant gender and assessment content (p<0.001). These data suggest that PE skills in cardiac and pulmonary examinations and examination techniques may be included in the main focus of improving the teaching of diagnostics in these medical students. PMID:25329685
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Li, Yan; Li, Na; Han, Qunying; He, Shuixiang; Bae, Ricard S; Liu, Zhengwen; Lv, Yi; Shi, Bingyin
2014-01-01
This study was conducted to evaluate the performance of physical examination (PE) skills during our diagnostic medicine course and analyze the characteristics of the data collected to provide information for practical guidance to improve the quality of teaching. Seventy-two fourth-year medical students were enrolled in the study. All received an assessment of PE skills after receiving a 17-week formal training course and systematic teaching. Their performance was evaluated and recorded in detail using a checklist, which included 5 aspects of PE skills: examination techniques, communication and care skills, content items, appropriateness of examination sequence, and time taken. Error frequency and type were designated as the assessment parameters in the survey. The results showed that the distribution and the percentage in examination errors between male and female students and among the different body parts examined were significantly different (p<0.001). The average error frequency per student in females (0.875) was lower than in males (1.375) although the difference was not statistically significant (p = 0.167). The average error frequency per student in cardiac (1.267) and pulmonary (1.389) examinations was higher than in abdominal (0.867) and head, neck and nervous system examinations (0.917). Female students had a lower average error frequency than males in cardiac examinations (p = 0.041). Additionally, error in examination techniques was the highest type of error among the 5 aspects of PE skills irrespective of participant gender and assessment content (p<0.001). These data suggest that PE skills in cardiac and pulmonary examinations and examination techniques may be included in the main focus of improving the teaching of diagnostics in these medical students.
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ERIC Educational Resources Information Center
Huprich, Julia; Green, Ravonne
2007-01-01
The Council on Public Liberal Arts Colleges (COPLAC) libraries websites were assessed for Section 508 errors using the online WebXACT tool. Only three of the twenty-one institutions (14%) had zero accessibility errors. Eighty-six percent of the COPLAC institutions had an average of 1.24 errors. Section 508 compliance is required for institutions…
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A large-scale test of free-energy simulation estimates of protein-ligand binding affinities.
Mikulskis, Paulius; Genheden, Samuel; Ryde, Ulf
2014-10-27
We have performed a large-scale test of alchemical perturbation calculations with the Bennett acceptance-ratio (BAR) approach to estimate relative affinities for the binding of 107 ligands to 10 different proteins. Employing 20-Å truncated spherical systems and only one intermediate state in the perturbations, we obtain an error of less than 4 kJ/mol for 54% of the studied relative affinities and a precision of 0.5 kJ/mol on average. However, only four of the proteins gave acceptable errors, correlations, and rankings. The results could be improved by using nine intermediate states in the simulations or including the entire protein in the simulations using periodic boundary conditions. However, 27 of the calculated affinities still gave errors of more than 4 kJ/mol, and for three of the proteins the results were not satisfactory. This shows that the performance of BAR calculations depends on the target protein and that several transformations gave poor results owing to limitations in the molecular-mechanics force field or the restricted sampling possible within a reasonable simulation time. Still, the BAR results are better than docking calculations for most of the proteins.
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Gadoury, R.A.; Smath, J.A.; Fontaine, R.A.
1985-01-01
The report documents the results of a study of the cost-effectiveness of the U.S. Geological Survey 's continuous-record stream-gaging programs in Massachusetts and Rhode Island. Data uses and funding sources were identified for 91 gaging stations being operated in Massachusetts are being operated to provide data for two special purpose hydrologic studies, and they are planned to be discontinued at the conclusion of the studies. Cost-effectiveness analyses were performed on 63 continuous-record gaging stations in Massachusetts and 15 stations in Rhode Island, at budgets of $353,000 and $60,500, respectively. Current operations policies result in average standard errors per station of 12.3% in Massachusetts and 9.7% in Rhode Island. Minimum possible budgets to maintain the present numbers of gaging stations in the two States are estimated to be $340,000 and $59,000, with average errors per station of 12.8% and 10.0%, respectively. If the present budget levels were doubled, average standards errors per station would decrease to 8.1% and 4.2%, respectively. Further budget increases would not improve the standard errors significantly. (USGS)
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Evaluation and optimization of sampling errors for the Monte Carlo Independent Column Approximation
NASA Astrophysics Data System (ADS)
Räisänen, Petri; Barker, W. Howard
2004-07-01
The Monte Carlo Independent Column Approximation (McICA) method for computing domain-average broadband radiative fluxes is unbiased with respect to the full ICA, but its flux estimates contain conditional random noise. McICA's sampling errors are evaluated here using a global climate model (GCM) dataset and a correlated-k distribution (CKD) radiation scheme. Two approaches to reduce McICA's sampling variance are discussed. The first is to simply restrict all of McICA's samples to cloudy regions. This avoids wasting precious few samples on essentially homogeneous clear skies. Clear-sky fluxes need to be computed separately for this approach, but this is usually done in GCMs for diagnostic purposes anyway. Second, accuracy can be improved by repeated sampling, and averaging those CKD terms with large cloud radiative effects. Although this naturally increases computational costs over the standard CKD model, random errors for fluxes and heating rates are reduced by typically 50% to 60%, for the present radiation code, when the total number of samples is increased by 50%. When both variance reduction techniques are applied simultaneously, globally averaged flux and heating rate random errors are reduced by a factor of #3.
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NASA Technical Reports Server (NTRS)
Rahmat-Samii, Y.
1983-01-01
Based on the works of Ruze (1966) and Vu (1969), a novel mathematical model has been developed to determine efficiently the average power pattern degradations caused by random surface errors. In this model, both nonuniform root mean square (rms) surface errors and nonuniform illumination functions are employed. In addition, the model incorporates the dependence on F/D in the construction of the solution. The mathematical foundation of the model rests on the assumption that in each prescribed annular region of the antenna, the geometrical rms surface value is known. It is shown that closed-form expressions can then be derived, which result in a very efficient computational method for the average power pattern. Detailed parametric studies are performed with these expressions to determine the effects of different random errors and illumination tapers on parameters such as gain loss and sidelobe levels. The results clearly demonstrate that as sidelobe levels decrease, their dependence on the surface rms/wavelength becomes much stronger and, for a specified tolerance level, a considerably smaller rms/wavelength is required to maintain the low sidelobes within the required bounds.
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Cost-effectiveness of the streamflow-gaging program in Wyoming
Druse, S.A.; Wahl, K.L.
1988-01-01
This report documents the results of a cost-effectiveness study of the streamflow-gaging program in Wyoming. Regression analysis or hydrologic flow-routing techniques were considered for 24 combinations of stations from a 139-station network operated in 1984 to investigate suitability of techniques for simulating streamflow records. Only one station was determined to have sufficient accuracy in the regression analysis to consider discontinuance of the gage. The evaluation of the gaging-station network, which included the use of associated uncertainty in streamflow records, is limited to the nonwinter operation of the 47 stations operated by the Riverton Field Office of the U.S. Geological Survey. The current (1987) travel routes and measurement frequencies require a budget of $264,000 and result in an average standard error in streamflow records of 13.2%. Changes in routes and station visits using the same budget, could optimally reduce the standard error by 1.6%. Budgets evaluated ranged from $235,000 to $400,000. A $235,000 budget increased the optimal average standard error/station from 11.6 to 15.5%, and a $400,000 budget could reduce it to 6.6%. For all budgets considered, lost record accounts for about 40% of the average standard error. (USGS)
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Validation of the Kp Geomagnetic Index Forecast at CCMC
NASA Astrophysics Data System (ADS)
Frechette, B. P.; Mays, M. L.
2017-12-01
The Community Coordinated Modeling Center (CCMC) Space Weather Research Center (SWRC) sub-team provides space weather services to NASA robotic mission operators and science campaigns and prototypes new models, forecasting techniques, and procedures. The Kp index is a measure of geomagnetic disturbances for space weather in the magnetosphere such as geomagnetic storms and substorms. In this study, we performed validation on the Newell et al. (2007) Kp prediction equation from December 2010 to July 2017. The purpose of this research is to understand the Kp forecast performance because it's critical for NASA missions to have confidence in the space weather forecast. This research was done by computing the Kp error for each forecast (average, minimum, maximum) and each synoptic period. Then to quantify forecast performance we computed the mean error, mean absolute error, root mean square error, multiplicative bias and correlation coefficient. A contingency table was made for each forecast and skill scores were computed. The results are compared to the perfect score and reference forecast skill score. In conclusion, the skill score and error results show that the minimum of the predicted Kp over each synoptic period from the Newell et al. (2007) Kp prediction equation performed better than the maximum or average of the prediction. However, persistence (reference forecast) outperformed all of the Kp forecasts (minimum, maximum, and average). Overall, the Newell Kp prediction still predicts within a range of 1, even though persistence beats it.
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NASA Technical Reports Server (NTRS)
Chang, Alfred T. C.; Chiu, Long S.; Wilheit, Thomas T.
1993-01-01
Global averages and random errors associated with the monthly oceanic rain rates derived from the Special Sensor Microwave/Imager (SSM/I) data using the technique developed by Wilheit et al. (1991) are computed. Accounting for the beam-filling bias, a global annual average rain rate of 1.26 m is computed. The error estimation scheme is based on the existence of independent (morning and afternoon) estimates of the monthly mean. Calculations show overall random errors of about 50-60 percent for each 5 deg x 5 deg box. The results are insensitive to different sampling strategy (odd and even days of the month). Comparison of the SSM/I estimates with raingage data collected at the Pacific atoll stations showed a low bias of about 8 percent, a correlation of 0.7, and an rms difference of 55 percent.
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Observations of cloud liquid water path over oceans: Optical and microwave remote sensing methods
NASA Technical Reports Server (NTRS)
Lin, Bing; Rossow, William B.
1994-01-01
Published estimates of cloud liquid water path (LWP) from satellite-measured microwave radiation show little agreement, even about the relative magnitudes of LWP in the tropics and midlatitudes. To understand these differences and to obtain more reliable estimate, optical and microwave LWP retrieval methods are compared using the International Satellite Cloud Climatology Project (ISCCP) and special sensor microwave/imager (SSM/I) data. Errors in microwave LWP retrieval associated with uncertainties in surface, atmosphere, and cloud properties are assessed. Sea surface temperature may not produce great LWP errors, if accurate contemporaneous measurements are used in the retrieval. An uncertainty of estimated near-surface wind speed as high as 2 m/s produces uncertainty in LWP of about 5 mg/sq cm. Cloud liquid water temperature has only a small effect on LWP retrievals (rms errors less than 2 mg/sq cm), if errors in the temperature are less than 5 C; however, such errors can produce spurious variations of LWP with latitude and season. Errors in atmospheric column water vapor (CWV) are strongly coupled with errors in LWP (for some retrieval methods) causing errors as large as 30 mg/sq cm. Because microwave radiation is much less sensitive to clouds with small LWP (less than 7 mg/sq cm) than visible wavelength radiation, the microwave results are very sensitive to the process used to separate clear and cloudy conditions. Different cloud detection sensitivities in different microwave retrieval methods bias estimated LWP values. Comparing ISCCP and SSM/I LWPs, we find that the two estimated values are consistent in global, zonal, and regional means for warm, nonprecipitating clouds, which have average LWP values of about 5 mg/sq cm and occur much more frequently than precipitating clouds. Ice water path (IWP) can be roughly estimated from the differences between ISCCP total water path and SSM/I LWP for cold, nonprecipitating clouds. IWP in the winter hemisphere is about 3 times the LWP but only half the LWP in the summer hemisphere. Precipitating clouds contribute significantly to monthly, zonal mean LWP values determined from microwave, especially in the intertropical convergence zone (ITCZ), because they have almost 10 times the liquid water (cloud plus precipitation) of nonprecipitating clouds on average. There are significant differences among microwave LWP estimates associated with the treatment of precipitating clouds.
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NASA Astrophysics Data System (ADS)
Woodford, Curtis; Yartsev, Slav; Van Dyk, Jake
2007-08-01
This study aims to investigate the settings that provide optimum registration accuracy when registering megavoltage CT (MVCT) studies acquired on tomotherapy with planning kilovoltage CT (kVCT) studies of patients with lung cancer. For each experiment, the systematic difference between the actual and planned positions of the thorax phantom was determined by setting the phantom up at the planning isocenter, generating and registering an MVCT study. The phantom was translated by 5 or 10 mm, MVCT scanned, and registration was performed again. A root-mean-square equation that calculated the residual error of the registration based on the known shift and systematic difference was used to assess the accuracy of the registration process. The phantom study results for 18 combinations of different MVCT/kVCT registration options are presented and compared to clinical registration data from 17 lung cancer patients. MVCT studies acquired with coarse (6 mm), normal (4 mm) and fine (2 mm) slice spacings could all be registered with similar residual errors. No specific combination of resolution and fusion selection technique resulted in a lower residual error. A scan length of 6 cm with any slice spacing registered with the full image fusion selection technique and fine resolution will result in a low residual error most of the time. On average, large corrections made manually by clinicians to the automatic registration values are infrequent. Small manual corrections within the residual error averages of the registration process occur, but their impact on the average patient position is small. Registrations using the full image fusion selection technique and fine resolution of 6 cm MVCT scans with coarse slices have a low residual error, and this strategy can be clinically used for lung cancer patients treated on tomotherapy. Automatic registration values are accurate on average, and a quick verification on a sagittal MVCT slice should be enough to detect registration outliers.
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Zonal average earth radiation budget measurements from satellites for climate studies
NASA Technical Reports Server (NTRS)
Ellis, J. S.; Haar, T. H. V.
1976-01-01
Data from 29 months of satellite radiation budget measurements, taken intermittently over the period 1964 through 1971, are composited into mean month, season and annual zonally averaged meridional profiles. Individual months, which comprise the 29 month set, were selected as representing the best available total flux data for compositing into large scale statistics for climate studies. A discussion of spatial resolution of the measurements along with an error analysis, including both the uncertainty and standard error of the mean, are presented.
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Benchmarking homogenization algorithms for monthly data
NASA Astrophysics Data System (ADS)
Venema, V. K. C.; Mestre, O.; Aguilar, E.; Auer, I.; Guijarro, J. A.; Domonkos, P.; Vertacnik, G.; Szentimrey, T.; Stepanek, P.; Zahradnicek, P.; Viarre, J.; Müller-Westermeier, G.; Lakatos, M.; Williams, C. N.; Menne, M. J.; Lindau, R.; Rasol, D.; Rustemeier, E.; Kolokythas, K.; Marinova, T.; Andresen, L.; Acquaotta, F.; Fratianni, S.; Cheval, S.; Klancar, M.; Brunetti, M.; Gruber, C.; Prohom Duran, M.; Likso, T.; Esteban, P.; Brandsma, T.
2012-01-01
The COST (European Cooperation in Science and Technology) Action ES0601: advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies and because they represent two important types of statistics (additive and multiplicative). The algorithms were validated against a realistic benchmark dataset. The benchmark contains real inhomogeneous data as well as simulated data with inserted inhomogeneities. Random independent break-type inhomogeneities with normally distributed breakpoint sizes were added to the simulated datasets. To approximate real world conditions, breaks were introduced that occur simultaneously in multiple station series within a simulated network of station data. The simulated time series also contained outliers, missing data periods and local station trends. Further, a stochastic nonlinear global (network-wide) trend was added. Participants provided 25 separate homogenized contributions as part of the blind study. After the deadline at which details of the imposed inhomogeneities were revealed, 22 additional solutions were submitted. These homogenized datasets were assessed by a number of performance metrics including (i) the centered root mean square error relative to the true homogeneous value at various averaging scales, (ii) the error in linear trend estimates and (iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Contingency scores by themselves are not very informative. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data. Training the users on homogenization software was found to be very important. Moreover, state-of-the-art relative homogenization algorithms developed to work with an inhomogeneous reference are shown to perform best. The study showed that automatic algorithms can perform as well as manual ones.
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Benchmarking monthly homogenization algorithms
NASA Astrophysics Data System (ADS)
Venema, V. K. C.; Mestre, O.; Aguilar, E.; Auer, I.; Guijarro, J. A.; Domonkos, P.; Vertacnik, G.; Szentimrey, T.; Stepanek, P.; Zahradnicek, P.; Viarre, J.; Müller-Westermeier, G.; Lakatos, M.; Williams, C. N.; Menne, M.; Lindau, R.; Rasol, D.; Rustemeier, E.; Kolokythas, K.; Marinova, T.; Andresen, L.; Acquaotta, F.; Fratianni, S.; Cheval, S.; Klancar, M.; Brunetti, M.; Gruber, C.; Prohom Duran, M.; Likso, T.; Esteban, P.; Brandsma, T.
2011-08-01
The COST (European Cooperation in Science and Technology) Action ES0601: Advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies and because they represent two important types of statistics (additive and multiplicative). The algorithms were validated against a realistic benchmark dataset. The benchmark contains real inhomogeneous data as well as simulated data with inserted inhomogeneities. Random break-type inhomogeneities were added to the simulated datasets modeled as a Poisson process with normally distributed breakpoint sizes. To approximate real world conditions, breaks were introduced that occur simultaneously in multiple station series within a simulated network of station data. The simulated time series also contained outliers, missing data periods and local station trends. Further, a stochastic nonlinear global (network-wide) trend was added. Participants provided 25 separate homogenized contributions as part of the blind study as well as 22 additional solutions submitted after the details of the imposed inhomogeneities were revealed. These homogenized datasets were assessed by a number of performance metrics including (i) the centered root mean square error relative to the true homogeneous value at various averaging scales, (ii) the error in linear trend estimates and (iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Contingency scores by themselves are not very informative. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data. Training was found to be very important. Moreover, state-of-the-art relative homogenization algorithms developed to work with an inhomogeneous reference are shown to perform best. The study showed that currently automatic algorithms can perform as well as manual ones.
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Understanding fatal older road user crash circumstances and risk factors.
Koppel, Sjaan; Bugeja, Lyndal; Smith, Daisy; Lamb, Ashne; Dwyer, Jeremy; Fitzharris, Michael; Newstead, Stuart; D'Elia, Angelo; Charlton, Judith
2018-02-28
This study used medicolegal data to investigate fatal older road user (ORU) crash circumstances and risk factors relating to four key components of the Safe System approach (e.g., roads and roadsides, vehicles, road users, and speeds) to identify areas of priority for targeted prevention activity. The Coroners Court of Victoria's Surveillance Database was searched to identify coronial records with at least one deceased ORU in the state of Victoria, Australia, for 2013-2014. Information relating to the ORU, crash characteristics and circumstances, and risk factors was extracted and analyzed. The average rate of fatal ORU crashes per 100,000 population was 8.1 (95% confidence interval [CI] 6.0-10.2), which was more than double the average rate of fatal middle-aged road user crashes (3.6, 95% CI 2.5-4.6). There was a significant relationship between age group and deceased road user type (χ 2 (15, N = 226) = 3.56, p < 0.001). The proportion of deceased drivers decreased with age, whereas the proportion of deceased pedestrians increased with age. The majority of fatal ORU crashes involved a counterpart (another vehicle: 59.4%; fixed/stationary object: 25.4%), and occurred "on road" (87.0%), on roads that were paved (94.2%), dry (74.2%), and had light traffic volume (38.3%). Road user error was identified by the police and/or coroner for the majority of fatal ORU crashes (57.9%), with a significant proportion of deceased ORU deemed to have "misjudged" (40.9%) or "failed to yield" (37.9%). Road user error was the most significant risk factor identified in fatal ORU crashes, which suggests that there is a limited capacity of the Victorian road system to fully accommodate road user errors. Initiatives related to safer roads and roadsides, vehicles, and speed zones, as well as behavioral approaches, are key areas of priority for targeted activity to prevent fatal older road user crashes in the future.
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Effect of satellite formations and imaging modes on global albedo estimation
NASA Astrophysics Data System (ADS)
Nag, Sreeja; Gatebe, Charles K.; Miller, David W.; de Weck, Olivier L.
2016-05-01
We confirm the applicability of using small satellite formation flight for multi-angular earth observation to retrieve global, narrow band, narrow field-of-view albedo. The value of formation flight is assessed using a coupled systems engineering and science evaluation model, driven by Model Based Systems Engineering and Observing System Simulation Experiments. Albedo errors are calculated against bi-directional reflectance data obtained from NASA airborne campaigns made by the Cloud Absorption Radiometer for the seven major surface types, binned using MODIS' land cover map - water, forest, cropland, grassland, snow, desert and cities. A full tradespace of architectures with three to eight satellites, maintainable orbits and imaging modes (collective payload pointing strategies) are assessed. For an arbitrary 4-sat formation, changing the reference, nadir-pointing satellite dynamically reduces the average albedo error to 0.003, from 0.006 found in the static referencecase. Tracking pre-selected waypoints with all the satellites reduces the average error further to 0.001, allows better polar imaging and continued operations even with a broken formation. An albedo error of 0.001 translates to 1.36 W/m2 or 0.4% in Earth's outgoing radiation error. Estimation errors are found to be independent of the satellites' altitude and inclination, if the nadir-looking is changed dynamically. The formation satellites are restricted to differ in only right ascension of planes and mean anomalies within slotted bounds. Three satellites in some specific formations show average albedo errors of less than 2% with respect to airborne, ground data and seven satellites in any slotted formation outperform the monolithic error of 3.6%. In fact, the maximum possible albedo error, purely based on angular sampling, of 12% for monoliths is outperformed by a five-satellite formation in any slotted arrangement and an eight satellite formation can bring that error down four fold to 3%. More than 70% ground spot overlap between the satellites is possible with 0.5° of pointing accuracy, 2 Km of GPS accuracy and commands uplinked once a day. The formations can be maintained at less than 1 m/s of monthly ΔV per satellite.
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Bounding Averages Rigorously Using Semidefinite Programming: Mean Moments of the Lorenz System
NASA Astrophysics Data System (ADS)
Goluskin, David
2018-04-01
We describe methods for proving bounds on infinite-time averages in differential dynamical systems. The methods rely on the construction of nonnegative polynomials with certain properties, similarly to the way nonlinear stability can be proved using Lyapunov functions. Nonnegativity is enforced by requiring the polynomials to be sums of squares, a condition which is then formulated as a semidefinite program (SDP) that can be solved computationally. Although such computations are subject to numerical error, we demonstrate two ways to obtain rigorous results: using interval arithmetic to control the error of an approximate SDP solution, and finding exact analytical solutions to relatively small SDPs. Previous formulations are extended to allow for bounds depending analytically on parametric variables. These methods are illustrated using the Lorenz equations, a system with three state variables ( x, y, z) and three parameters (β ,σ ,r). Bounds are reported for infinite-time averages of all eighteen moments x^ly^mz^n up to quartic degree that are symmetric under (x,y)\\mapsto (-x,-y). These bounds apply to all solutions regardless of stability, including chaotic trajectories, periodic orbits, and equilibrium points. The analytical approach yields two novel bounds that are sharp: the mean of z^3 can be no larger than its value of (r-1)^3 at the nonzero equilibria, and the mean of xy^3 must be nonnegative. The interval arithmetic approach is applied at the standard chaotic parameters to bound eleven average moments that all appear to be maximized on the shortest periodic orbit. Our best upper bound on each such average exceeds its value on the maximizing orbit by less than 1%. Many bounds reported here are much tighter than would be possible without computer assistance.
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NASA Astrophysics Data System (ADS)
Wilson, M. D.; Durand, M.; Jung, H. C.; Alsdorf, D.
2015-04-01
The Surface Water and Ocean Topography (SWOT) mission, scheduled for launch in 2020, will provide a step-change improvement in the measurement of terrestrial surface-water storage and dynamics. In particular, it will provide the first, routine two-dimensional measurements of water-surface elevations. In this paper, we aimed to (i) characterise and illustrate in two dimensions the errors which may be found in SWOT swath measurements of terrestrial surface water, (ii) simulate the spatio-temporal sampling scheme of SWOT for the Amazon, and (iii) assess the impact of each of these on estimates of water-surface slope and river discharge which may be obtained from SWOT imagery. We based our analysis on a virtual mission for a ~260 km reach of the central Amazon (Solimões) River, using a hydraulic model to provide water-surface elevations according to SWOT spatio-temporal sampling to which errors were added based on a two-dimensional height error spectrum derived from the SWOT design requirements. We thereby obtained water-surface elevation measurements for the Amazon main stem as may be observed by SWOT. Using these measurements, we derived estimates of river slope and discharge and compared them to those obtained directly from the hydraulic model. We found that cross-channel and along-reach averaging of SWOT measurements using reach lengths greater than 4 km for the Solimões and 7.5 km for Purus reduced the effect of systematic height errors, enabling discharge to be reproduced accurately from the water height, assuming known bathymetry and friction. Using cross-sectional averaging and 20 km reach lengths, results show Nash-Sutcliffe model efficiency values of 0.99 for the Solimões and 0.88 for the Purus, with 2.6 and 19.1 % average overall error in discharge, respectively. We extend the results to other rivers worldwide and infer that SWOT-derived discharge estimates may be more accurate for rivers with larger channel widths (permitting a greater level of cross-sectional averaging and the use of shorter reach lengths) and higher water-surface slopes (reducing the proportional impact of slope errors on discharge calculation).
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Design of a Pneumatic Tool for Manual Drilling Operations in Confined Spaces
NASA Astrophysics Data System (ADS)
Janicki, Benjamin
This master's thesis describes the design process and testing results for a pneumatically actuated, manually-operated tool for confined space drilling operations. The purpose of this device is to back-drill pilot holes inside a commercial airplane wing. It is lightweight, and a "locator pin" enables the operator to align the drill over a pilot hole. A suction pad stabilizes the system, and an air motor and flexible drive shaft power the drill. Two testing procedures were performed to determine the practicality of this prototype. The first was the "offset drill test", which qualified the exit hole position error due to an initial position error relative to the original pilot hole. The results displayed a linear relationship, and it was determined that position errors of less than .060" would prevent the need for rework, with errors of up to .030" considered acceptable. For the second test, a series of holes were drilled with the pneumatic tool and analyzed for position error, diameter range, and cycle time. The position errors and hole diameter range were within the allowed tolerances. The average cycle time was 45 seconds, 73 percent of which was for drilling the hole, and 27 percent of which was for positioning the device. Recommended improvements are discussed in the conclusion, and include a more durable flexible drive shaft, a damper for drill feed control, and a more stable locator pin.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Marshall, S; Currier, B; Hodgdon, A
Purpose: The design of a new Portable Faraday Cup (PFC) used to calibrate proton accelerators was evaluated for energies between 50 and 220 MeV. Monte Carlo simulations performed in Geant4–10.0 were used to evaluate experimental results and reduce the relative detector error for this vacuum-less and low mass system, and invalidate current MCNP releases. Methods: The detector construction consisted of a copper conductor coated with an insulator and grounded with silver. Monte Carlo calculations in Geant4 were used to determine the net charge per proton input (gain) as a function of insulator thickness and beam energy. Kapton was chosen asmore » the insulating material and was designed to capture backscattered electrons. Charge displacement from/into Kapton was assumed to follow a linear proportionality to the origin/terminus depth toward the outer ground layer. Kapton thicknesses ranged from 0 to 200 microns, proton energies were set to match empirical studies ranging from 70 to 250 MeV. Each setup was averaged over 1 million events using the FTFP-BERT 2.0 physics list. Results: With increasing proton energy, the gain of Cu+KA gradually converges to the limit of pure copper, with relative error between 1.52% and 0.72%. The Ag layer created a more diverging behavior, accelerating the flux of negative charge into the device and increasing relative error when compared to pure copper from 1.21% to 1.63%. Conclusion: Gain vs. beam energy signatures were acquired for each device. Further analysis reveals proportionality between insulator thickness and measured gain, albeit an inverse proportionality between beam energy and in-flux of electrons. Increased silver grounding layer thickness also decreases gain, though the relative error expands with beam energy, contrary to the Kapton layer.« less
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Error in telemetry studies: Effects of animal movement on triangulation
Schmutz, Joel A.; White, Gary C.
1990-01-01
We used Monte Carlo simulations to investigate the effects of animal movement on error of estimated animal locations derived from radio-telemetry triangulation of sequentially obtained bearings. Simulated movements of 0-534 m resulted in up to 10-fold increases in average location error but <10% decreases in location precision when observer-to-animal distances were <1,000 m. Location error and precision were minimally affected by censorship of poor locations with Chi-square goodness-of-fit tests. Location error caused by animal movement can only be eliminated by taking simultaneous bearings.
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Lahue, Betsy J; Pyenson, Bruce; Iwasaki, Kosuke; Blumen, Helen E; Forray, Susan; Rothschild, Jeffrey M
2012-11-01
Harmful medication errors, or preventable adverse drug events (ADEs), are a prominent quality and cost issue in healthcare. Injectable medications are important therapeutic agents, but they are associated with a greater potential for serious harm than oral medications. The national burden of preventable ADEs associated with inpatient injectable medications and the associated medical professional liability (MPL) costs have not been previously described in the literature. To quantify the economic burden of preventable ADEs related to inpatient injectable medications in the United States. Medical error data (MedMarx 2009-2011) were utilized to derive the distribution of errors by injectable medication types. Hospital data (Premier 2010-2011) identified the numbers and the types of injections per hospitalization. US payer claims (2009-2010 MarketScan Commercial and Medicare 5% Sample) were used to calculate the incremental cost of ADEs by payer and by diagnosis-related group (DRG). The incremental cost of ADEs was defined as inclusive of the time of inpatient admission and the following 4 months. Actuarial calculations, assumptions based on published literature, and DRG proportions from 17 state discharge databases were used to derive the probability of preventable ADEs per hospitalization and their annual costs. MPL costs were assessed from state- and national-level industry reports, premium rates, and from closed claims databases between 1990 and 2011. The 2010 American Hospital Association database was used for hospital-level statistics. All costs were adjusted to 2013 dollars. Based on this medication-level analysis of reported harmful errors and the frequency of inpatient administrations with actuarial projections, we estimate that preventable ADEs associated with injectable medications impact 1.2 million hospitalizations annually. Using a matched cohort analysis of healthcare claims as a basis for evaluating incremental costs, we estimate that inpatient preventable ADEs associated with injectable medications increase the annual US payer costs by $2.7 billion to $5.1 billion, averaging $600,000 in extra costs per hospital. Across categories of injectable drugs, insulin had the highest risk per administration for a preventable ADE, although errors in the higher-volume categories of anti-infective, narcotic/analgesic, anticoagulant/thrombolytic and anxiolytic/sedative injectable medications harmed more patients. Our analysis of liability claims estimates that MPL associated with injectable medications totals $300 million to $610 million annually, with an average cost of $72,000 per US hospital. The incremental healthcare and MPL costs of preventable ADEs resulting from inpatient injectable medications are substantial. The data in this study strongly support the clinical and business cases of investing in efforts to prevent errors related to injectable medications.
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Lahue, Betsy J.; Pyenson, Bruce; Iwasaki, Kosuke; Blumen, Helen E.; Forray, Susan; Rothschild, Jeffrey M.
2012-01-01
Background Harmful medication errors, or preventable adverse drug events (ADEs), are a prominent quality and cost issue in healthcare. Injectable medications are important therapeutic agents, but they are associated with a greater potential for serious harm than oral medications. The national burden of preventable ADEs associated with inpatient injectable medications and the associated medical professional liability (MPL) costs have not been previously described in the literature. Objective To quantify the economic burden of preventable ADEs related to inpatient injectable medications in the United States. Methods Medical error data (MedMarx 2009–2011) were utilized to derive the distribution of errors by injectable medication types. Hospital data (Premier 2010–2011) identified the numbers and the types of injections per hospitalization. US payer claims (2009–2010 MarketScan Commercial and Medicare 5% Sample) were used to calculate the incremental cost of ADEs by payer and by diagnosis-related group (DRG). The incremental cost of ADEs was defined as inclusive of the time of inpatient admission and the following 4 months. Actuarial calculations, assumptions based on published literature, and DRG proportions from 17 state discharge databases were used to derive the probability of preventable ADEs per hospitalization and their annual costs. MPL costs were assessed from state- and national-level industry reports, premium rates, and from closed claims databases between 1990 and 2011. The 2010 American Hospital Association database was used for hospital-level statistics. All costs were adjusted to 2013 dollars. Results Based on this medication-level analysis of reported harmful errors and the frequency of inpatient administrations with actuarial projections, we estimate that preventable ADEs associated with injectable medications impact 1.2 million hospitalizations annually. Using a matched cohort analysis of healthcare claims as a basis for evaluating incremental costs, we estimate that inpatient preventable ADEs associated with injectable medications increase the annual US payer costs by $2.7 billion to $5.1 billion, averaging $600,000 in extra costs per hospital. Across categories of injectable drugs, insulin had the highest risk per administration for a preventable ADE, although errors in the higher-volume categories of anti-infective, narcotic/analgesic, anticoagulant/thrombolytic and anxiolytic/sedative injectable medications harmed more patients. Our analysis of liability claims estimates that MPL associated with injectable medications totals $300 million to $610 million annually, with an average cost of $72,000 per US hospital. Conclusion The incremental healthcare and MPL costs of preventable ADEs resulting from inpatient injectable medications are substantial. The data in this study strongly support the clinical and business cases of investing in efforts to prevent errors related to injectable medications. PMID:24991335
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Pennation angle dependency in skeletal muscle tissue doppler strain in dynamic contractions.
Lindberg, Frida; Öhberg, Fredrik; Granåsen, Gabriel; Brodin, Lars-Åke; Grönlund, Christer
2011-07-01
Tissue velocity imaging (TVI) is a Doppler based ultrasound technique that can be used to study regional deformation in skeletal muscle tissue. The aim of this study was to develop a biomechanical model to describe the TVI strain's dependency on the pennation angle. We demonstrate its impact as the subsequent strain measurement error using dynamic elbow contractions from the medial and the lateral part of biceps brachii at two different loadings; 5% and 25% of maximum voluntary contraction (MVC). The estimated pennation angles were on average about 4° in extended position and increased to a maximal of 13° in flexed elbow position. The corresponding relative angular error spread from around 7% up to around 40%. To accurately apply TVI on skeletal muscles, the error due to angle changes should be compensated for. As a suggestion, this could be done according to the presented model. Copyright © 2011 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.
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NASA Astrophysics Data System (ADS)
Joetzjer, E.; Pillet, M.; Ciais, P.; Barbier, N.; Chave, J.; Schlund, M.; Maignan, F.; Barichivich, J.; Luyssaert, S.; Hérault, B.; von Poncet, F.; Poulter, B.
2017-07-01
Despite advances in Earth observation and modeling, estimating tropical biomass remains a challenge. Recent work suggests that integrating satellite measurements of canopy height within ecosystem models is a promising approach to infer biomass. We tested the feasibility of this approach to retrieve aboveground biomass (AGB) at three tropical forest sites by assimilating remotely sensed canopy height derived from a texture analysis algorithm applied to the high-resolution Pleiades imager in the Organizing Carbon and Hydrology in Dynamic Ecosystems Canopy (ORCHIDEE-CAN) ecosystem model. While mean AGB could be estimated within 10% of AGB derived from census data in average across sites, canopy height derived from Pleiades product was spatially too smooth, thus unable to accurately resolve large height (and biomass) variations within the site considered. The error budget was evaluated in details, and systematic errors related to the ORCHIDEE-CAN structure contribute as a secondary source of error and could be overcome by using improved allometric equations.
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NASA Technical Reports Server (NTRS)
Otterson, D. A.; Seng, G. T.
1985-01-01
An high performance liquid chromatography (HPLC) method to estimate four aromatic classes in middistillate fuels is presented. Average refractive indices are used in a correlation to obtain the concentrations of each of the aromatic classes from HPLC data. The aromatic class concentrations can be obtained in about 15 min when the concentration of the aromatic group is known. Seven fuels with a wide range of compositions were used to test the method. Relative errors in the concentration of the two major aromatic classes were not over 10 percent. Absolute errors of the minor classes were all less than 0.3 percent. The data show that errors in group-type analyses using sulfuric acid derived standards are greater for fuels containing high concentrations of polycyclic aromatics. Corrections are based on the change in refractive index of the aromatic fraction which can occur when sulfuric acid and the fuel react. These corrections improved both the precision and the accuracy of the group-type results.
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NASA Astrophysics Data System (ADS)
Sun, Li-wei; Ye, Xin; Fang, Wei; He, Zhen-lei; Yi, Xiao-long; Wang, Yu-peng
2017-11-01
Hyper-spectral imaging spectrometer has high spatial and spectral resolution. Its radiometric calibration needs the knowledge of the sources used with high spectral resolution. In order to satisfy the requirement of source, an on-orbit radiometric calibration method is designed in this paper. This chain is based on the spectral inversion accuracy of the calibration light source. We compile the genetic algorithm progress which is used to optimize the channel design of the transfer radiometer and consider the degradation of the halogen lamp, thus realizing the high accuracy inversion of spectral curve in the whole working time. The experimental results show the average root mean squared error is 0.396%, the maximum root mean squared error is 0.448%, and the relative errors at all wavelengths are within 1% in the spectral range from 500 nm to 900 nm during 100 h operating time. The design lays a foundation for the high accuracy calibration of imaging spectrometer.
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Retrieving Storm Electric Fields From Aircraft Field Mill Data. Part 2; Applications
NASA Technical Reports Server (NTRS)
Koshak, W. J.; Mach, D. M.; Christian, H. J.; Stewart, M. F.; Bateman, M. G.
2005-01-01
The Lagrange multiplier theory and "pitch down method" developed in Part I of this study are applied to complete the calibration of a Citation aircraft that is instrumented with six field mill sensors. When side constraints related to average fields are used, the method performs well in computer simulations. For mill measurement errors of 1 V/m and a 5 V/m error in the mean fair weather field function, the 3-D storm electric field is retrieved to within an error of about 12%. A side constraint that involves estimating the detailed structure of the fair weather field was also tested using computer simulations. For mill measurement errors of 1 V/m, the method retrieves the 3-D storm field to within an error of about 8% if the fair weather field estimate is typically within 1 V/m of the true fair weather field. Using this side constraint and data from fair weather field maneuvers taken on 29 June 2001, the Citation aircraft was calibrated. The resulting calibration matrix was then used to retrieve storm electric fields during a Citation flight on 2 June 2001. The storm field results are encouraging and agree favorably with the results obtained from earlier calibration analyses that were based on iterative techniques.
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Class-specific Error Bounds for Ensemble Classifiers
DOE Office of Scientific and Technical Information (OSTI.GOV)
Prenger, R; Lemmond, T; Varshney, K
2009-10-06
The generalization error, or probability of misclassification, of ensemble classifiers has been shown to be bounded above by a function of the mean correlation between the constituent (i.e., base) classifiers and their average strength. This bound suggests that increasing the strength and/or decreasing the correlation of an ensemble's base classifiers may yield improved performance under the assumption of equal error costs. However, this and other existing bounds do not directly address application spaces in which error costs are inherently unequal. For applications involving binary classification, Receiver Operating Characteristic (ROC) curves, performance curves that explicitly trade off false alarms and missedmore » detections, are often utilized to support decision making. To address performance optimization in this context, we have developed a lower bound for the entire ROC curve that can be expressed in terms of the class-specific strength and correlation of the base classifiers. We present empirical analyses demonstrating the efficacy of these bounds in predicting relative classifier performance. In addition, we specify performance regions of the ROC curve that are naturally delineated by the class-specific strengths of the base classifiers and show that each of these regions can be associated with a unique set of guidelines for performance optimization of binary classifiers within unequal error cost regimes.« less
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Selecting a restoration technique to minimize OCR error.
Cannon, M; Fugate, M; Hush, D R; Scovel, C
2003-01-01
This paper introduces a learning problem related to the task of converting printed documents to ASCII text files. The goal of the learning procedure is to produce a function that maps documents to restoration techniques in such a way that on average the restored documents have minimum optical character recognition error. We derive a general form for the optimal function and use it to motivate the development of a nonparametric method based on nearest neighbors. We also develop a direct method of solution based on empirical error minimization for which we prove a finite sample bound on estimation error that is independent of distribution. We show that this empirical error minimization problem is an extension of the empirical optimization problem for traditional M-class classification with general loss function and prove computational hardness for this problem. We then derive a simple iterative algorithm called generalized multiclass ratchet (GMR) and prove that it produces an optimal function asymptotically (with probability 1). To obtain the GMR algorithm we introduce a new data map that extends Kesler's construction for the multiclass problem and then apply an algorithm called Ratchet to this mapped data, where Ratchet is a modification of the Pocket algorithm . Finally, we apply these methods to a collection of documents and report on the experimental results.
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Assessment of Satellite Surface Radiation Products in Highland Regions with Tibet Instrumental Data
NASA Technical Reports Server (NTRS)
Yang, Kun; Koike, Toshio; Stackhouse, Paul; Mikovitz, Colleen
2006-01-01
This study presents results of comparisons between instrumental radiation data in the elevated Tibetan Plateau and two global satellite products: the Global Energy and Water Cycle Experiment - Surface Radiation Budget (GEWEX-SRB) and International Satellite Cloud Climatology Project - Flux Data (ISCCP-FD). In general, shortwave radiation (SW) is estimated better by ISCCP-FD while longwave radiation (LW) is estimated better by GEWEX-SRB, but all the radiation components in both products are under-estimated. Severe and systematic errors were found in monthly-mean SRB SW (on plateau-average, -48 W/sq m for downward SW and -18 W/sq m for upward SW) and FD LW (on plateau-average, -37 W/sq m for downward LW and -62 W/sq m for upward LW) for radiation. Errors in monthly-mean diurnal variations are even larger than the monthly mean errors. Though the LW errors can be reduced about 10 W/sq m after a correction for altitude difference between the site and SRB and FD grids, these errors are still higher than that for other regions. The large errors in SRB SW was mainly due to a processing mistake for elevation effect, but the errors in SRB LW was mainly due to significant errors in input data. We suggest reprocessing satellite surface radiation budget data, at least for highland areas like Tibet.
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Schwantes-An, Tae-Hwi; Sung, Heejong; Sabourin, Jeremy A; Justice, Cristina M; Sorant, Alexa J M; Wilson, Alexander F
2016-01-01
In this study, the effects of (a) the minor allele frequency of the single nucleotide variant (SNV), (b) the degree of departure from normality of the trait, and (c) the position of the SNVs on type I error rates were investigated in the Genetic Analysis Workshop (GAW) 19 whole exome sequence data. To test the distribution of the type I error rate, 5 simulated traits were considered: standard normal and gamma distributed traits; 2 transformed versions of the gamma trait (log 10 and rank-based inverse normal transformations); and trait Q1 provided by GAW 19. Each trait was tested with 313,340 SNVs. Tests of association were performed with simple linear regression and average type I error rates were determined for minor allele frequency classes. Rare SNVs (minor allele frequency < 0.05) showed inflated type I error rates for non-normally distributed traits that increased as the minor allele frequency decreased. The inflation of average type I error rates increased as the significance threshold decreased. Normally distributed traits did not show inflated type I error rates with respect to the minor allele frequency for rare SNVs. There was no consistent effect of transformation on the uniformity of the distribution of the location of SNVs with a type I error.
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Quantitative evaluation of patient-specific quality assurance using online dosimetry system
NASA Astrophysics Data System (ADS)
Jung, Jae-Yong; Shin, Young-Ju; Sohn, Seung-Chang; Min, Jung-Whan; Kim, Yon-Lae; Kim, Dong-Su; Choe, Bo-Young; Suh, Tae-Suk
2018-01-01
In this study, we investigated the clinical performance of an online dosimetry system (Mobius FX system, MFX) by 1) dosimetric plan verification using gamma passing rates and dose volume metrics and 2) error-detection capability evaluation by deliberately introduced machine error. Eighteen volumetric modulated arc therapy (VMAT) plans were studied. To evaluate the clinical performance of the MFX, we used gamma analysis and dose volume histogram (DVH) analysis. In addition, to evaluate the error-detection capability, we used gamma analysis and DVH analysis utilizing three types of deliberately introduced errors (Type 1: gantry angle-independent multi-leaf collimator (MLC) error, Type 2: gantry angle-dependent MLC error, and Type 3: gantry angle error). A dosimetric verification comparison of physical dosimetry system (Delt4PT) and online dosimetry system (MFX), gamma passing rates of the two dosimetry systems showed very good agreement with treatment planning system (TPS) calculation. For the average dose difference between the TPS calculation and the MFX measurement, most of the dose metrics showed good agreement within a tolerance of 3%. For the error-detection comparison of Delta4PT and MFX, the gamma passing rates of the two dosimetry systems did not meet the 90% acceptance criterion with the magnitude of error exceeding 2 mm and 1.5 ◦, respectively, for error plans of Types 1, 2, and 3. For delivery with all error types, the average dose difference of PTV due to error magnitude showed good agreement between calculated TPS and measured MFX within 1%. Overall, the results of the online dosimetry system showed very good agreement with those of the physical dosimetry system. Our results suggest that a log file-based online dosimetry system is a very suitable verification tool for accurate and efficient clinical routines for patient-specific quality assurance (QA).
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Evaluation of statistical models for forecast errors from the HBV model
NASA Astrophysics Data System (ADS)
Engeland, Kolbjørn; Renard, Benjamin; Steinsland, Ingelin; Kolberg, Sjur
2010-04-01
SummaryThree statistical models for the forecast errors for inflow into the Langvatn reservoir in Northern Norway have been constructed and tested according to the agreement between (i) the forecast distribution and the observations and (ii) median values of the forecast distribution and the observations. For the first model observed and forecasted inflows were transformed by the Box-Cox transformation before a first order auto-regressive model was constructed for the forecast errors. The parameters were conditioned on weather classes. In the second model the Normal Quantile Transformation (NQT) was applied on observed and forecasted inflows before a similar first order auto-regressive model was constructed for the forecast errors. For the third model positive and negative errors were modeled separately. The errors were first NQT-transformed before conditioning the mean error values on climate, forecasted inflow and yesterday's error. To test the three models we applied three criterions: we wanted (a) the forecast distribution to be reliable; (b) the forecast intervals to be narrow; (c) the median values of the forecast distribution to be close to the observed values. Models 1 and 2 gave almost identical results. The median values improved the forecast with Nash-Sutcliffe R eff increasing from 0.77 for the original forecast to 0.87 for the corrected forecasts. Models 1 and 2 over-estimated the forecast intervals but gave the narrowest intervals. Their main drawback was that the distributions are less reliable than Model 3. For Model 3 the median values did not fit well since the auto-correlation was not accounted for. Since Model 3 did not benefit from the potential variance reduction that lies in bias estimation and removal it gave on average wider forecasts intervals than the two other models. At the same time Model 3 on average slightly under-estimated the forecast intervals, probably explained by the use of average measures to evaluate the fit.
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ERIC Educational Resources Information Center
Schumacher, Robin F.; Malone, Amelia S.
2017-01-01
The goal of the present study was to describe fraction-calculation errors among 4th-grade students and determine whether error patterns differed as a function of problem type (addition vs. subtraction; like vs. unlike denominators), orientation (horizontal vs. vertical), or mathematics-achievement status (low- vs. average- vs. high-achieving). We…
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Precoded spatial multiplexing MIMO system with spatial component interleaver.
Gao, Xiang; Wu, Zhanji
In this paper, the performance of precoded bit-interleaved coded modulation (BICM) spatial multiplexing multiple-input multiple-output (MIMO) system with spatial component interleaver is investigated. For the ideal precoded spatial multiplexing MIMO system with spatial component interleaver based on singular value decomposition (SVD) of the MIMO channel, the average pairwise error probability (PEP) of coded bits is derived. Based on the PEP analysis, the optimum spatial Q-component interleaver design criterion is provided to achieve the minimum error probability. For the limited feedback precoded proposed scheme with linear zero forcing (ZF) receiver, in order to minimize a bound on the average probability of a symbol vector error, a novel effective signal-to-noise ratio (SNR)-based precoding matrix selection criterion and a simplified criterion are proposed. Based on the average mutual information (AMI)-maximization criterion, the optimal constellation rotation angles are investigated. Simulation results indicate that the optimized spatial multiplexing MIMO system with spatial component interleaver can achieve significant performance advantages compared to the conventional spatial multiplexing MIMO system.
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Streamflow simulation studies of the Hillsborough, Alafia, and Anclote Rivers, west-central Florida
Turner, J.F.
1979-01-01
A modified version of the Georgia Tech Watershed Model was applied for the purpose of flow simulation in three large river basins of west-central Florida. Calibrations were evaluated by comparing the following synthesized and observed data: annual hydrographs for the 1959, 1960, 1973 and 1974 water years, flood hydrographs (maximum daily discharge and flood volume), and long-term annual flood-peak discharges (1950-72). Annual hydrographs, excluding the 1973 water year, were compared using average absolute error in annual runoff and daily flows and correlation coefficients of monthly and daily flows. Correlations coefficients for simulated and observed maximum daily discharges and flood volumes used for calibrating range from 0.91 to 0.98 and average standard errors of estimate range from 18 to 45 percent. Correlation coefficients for simulated and observed annual flood-peak discharges range from 0.60 to 0.74 and average standard errors of estimate range from 33 to 44 percent. (Woodard-USGS)
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ERROR IN ANNUAL AVERAGE DUE TO USE OF LESS THAN EVERYDAY MEASUREMENTS
Long term averages of the concentration of PM mass and components are of interest for determining compliance with annual averages, for developing exposure surrogated for cross-sectional epidemiologic studies of the long-term of PM, and for determination of aerosol sources by chem...
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June and August median streamflows estimated for ungaged streams in southern Maine
Lombard, Pamela J.
2010-01-01
Methods for estimating June and August median streamflows were developed for ungaged, unregulated streams in southern Maine. The methods apply to streams with drainage areas ranging in size from 0.4 to 74 square miles, with percentage of basin underlain by a sand and gravel aquifer ranging from 0 to 84 percent, and with distance from the centroid of the basin to a Gulf of Maine line paralleling the coast ranging from 14 to 94 miles. Equations were developed with data from 4 long-term continuous-record streamgage stations and 27 partial-record streamgage stations. Estimates of median streamflows at the continuous-record and partial-record stations are presented. A mathematical technique for estimating standard low-flow statistics, such as June and August median streamflows, at partial-record streamgage stations was applied by relating base-flow measurements at these stations to concurrent daily streamflows at nearby long-term (at least 10 years of record) continuous-record streamgage stations (index stations). Weighted least-squares regression analysis (WLS) was used to relate estimates of June and August median streamflows at streamgage stations to basin characteristics at these same stations to develop equations that can be used to estimate June and August median streamflows on ungaged streams. WLS accounts for different periods of record at the gaging stations. Three basin characteristics-drainage area, percentage of basin underlain by a sand and gravel aquifer, and distance from the centroid of the basin to a Gulf of Maine line paralleling the coast-are used in the final regression equation to estimate June and August median streamflows for ungaged streams. The three-variable equation to estimate June median streamflow has an average standard error of prediction from -35 to 54 percent. The three-variable equation to estimate August median streamflow has an average standard error of prediction from -45 to 83 percent. Simpler one-variable equations that use only drainage area to estimate June and August median streamflows were developed for use when less accuracy is acceptable. These equations have average standard errors of prediction from -46 to 87 percent and from -57 to 133 percent, respectively.
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Aerosol Climate Effects: Local Radiative Forcing and Column Closure Experiments
NASA Technical Reports Server (NTRS)
Russell, P. B.; Bergstrom, Robert W.; Kinne, S. A.
2000-01-01
In an effort to reduce uncertainties in climate change predictions, experiments are being planned and conducted to measure anthropogenic aerosol properties and effects, including effects on radiative fields. The global average, direct anthropogenic aerosol effect on upwelling shortwave fluxes is estimated to be about +1/2 W/sq m, whereas errors in flux changes measured with airborne and spaceborne radiometers are 2 to 8 W/sq m or larger. This poses the question of whether flux changes expected in field experiments will be large enough to measure accurately. This paper obtains a new expression for the aerosol-induced change in upwelling flux, compares it to two-stream and adding-doubling (AD) results, and uses all three methods to estimate expected flux changes. The new expression accounts for the solar zenith angle dependences of aerosol transmission and reflection, as well as of surface albedo, all of which can have a strong effect in determining flux changes measured in field experiments. Despite its relative simplicity, the new expression gives results similar to previous two-stream results. Relative to AD results, it agrees within a few watts per square meter for the intermediate solar elevation angles where the flux changes peak (roughly 10 to 30 degrees), but it has negative errors for higher Sun and positive errors for lower Sun. All three techniques yield aerosol-induced changes in upwelling flux of +8 to +50 W/sq m for aerosol midvisible optical depths of 0.1 to 0.5. Because such aerosol optical depths occur frequently off the U.S. and European Atlantic coasts in summer, the flux changes they induce should be measurable by airborne, and possibly by spaceborne, radiometers, provided sufficient care is taken in experiment design (including measurements to separate aerosol radiative effects from those of absorbing gases). The expected flux changes are about 15 to 100 times larger than the global average flux change expected for the global average anthropogenic sulfate optical depth of 0.04. Reasons for the larger flux changes include the larger optical depths considered here (factor 2.5 to 12), plus restricting the measurements to cloud-free, daytime conditions over the ocean (factor 5 to 9).
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Herscovitch, P.; Raichle, M.E.; Kilbourn, M.R.
1985-05-01
Tracers used to measure CBF with PET and the Kety autoradiographic approach should freely cross the blood-brain barrier. 0-15 water, which is not freely permeable, may underestimate CBF, especially at higher flows. The authors determined this under-estimation relative to flow measured with a freely diffusible tracer, C-11 butanol and used these data to calculate the extraction (E) and permeability surface area product (PS) for 0-15 water. Paired flow measurements were made with 0-15 water (CBF-wat) and C-11 butanol (CBF-but) in eight normal human subjects. Average CBF-but, 55.6 ml/(min . 100g) was significantly greater than CBF-water, 47.6 ml/(min . 100g). Themore » ratio of regional gray matter (GM) flow to white matter (WM) flow was significantly greater with C-11 butanol, indicating a greater underestimation of CBF with 0-15 water in the higher flow GM. Average E for water was 0.92 in WM and 0.82 in GM. The mean PS in GM, 148 ml/(min . 100g), was significantly greater than in WM, 94 ml/(min . 100g). Simulation studies demonstrated that a measurement error in CBF-wat or CBF-but causes an approximately equivalent error in E but a considerably larger error in PS due to the sensitivity of the equation, PS=-CBF . ln(1-E), to variations in E. Modest errors in E and PS result from tissue heterogeneity that occurs due to the limited spatial resolution of PET. The authors' measurements of E and PS for water are similar to data obtained by more invasive methods and demonstrate the ability of PET to measure brain water permeability.« less
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Effect of defuzzification method of fuzzy modeling
NASA Astrophysics Data System (ADS)
Lapohos, Tibor; Buchal, Ralph O.
1994-10-01
Imprecision can arise in fuzzy relational modeling as a result of fuzzification, inference and defuzzification. These three sources of imprecision are difficult to separate. We have determined through numerical studies that an important source of imprecision is the defuzzification stage. This imprecision adversely affects the quality of the model output. The most widely used defuzzification algorithm is known by the name of `center of area' (COA) or `center of gravity' (COG). In this paper, we show that this algorithm not only maps the near limit values of the variables improperly but also introduces errors for middle domain values of the same variables. Furthermore, the behavior of this algorithm is a function of the shape of the reference sets. We compare the COA method to the weighted average of cluster centers (WACC) procedure in which the transformation is carried out based on the values of the cluster centers belonging to each of the reference membership functions instead of using the functions themselves. We show that this procedure is more effective and computationally much faster than the COA. The method is tested for a family of reference sets satisfying certain constraints, that is, for any support value the sum of reference membership function values equals one and the peak values of the two marginal membership functions project to the boundaries of the universe of discourse. For all the member sets of this family of reference sets the defuzzification errors do not get bigger as the linguistic variables tend to their extreme values. In addition, the more reference sets that are defined for a certain linguistic variable, the less the average defuzzification error becomes. In case of triangle shaped reference sets there is no defuzzification error at all. Finally, an alternative solution is provided that improves the performance of the COA method.
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Point Charges Optimally Placed to Represent the Multipole Expansion of Charge Distributions
Onufriev, Alexey V.
2013-01-01
We propose an approach for approximating electrostatic charge distributions with a small number of point charges to optimally represent the original charge distribution. By construction, the proposed optimal point charge approximation (OPCA) retains many of the useful properties of point multipole expansion, including the same far-field asymptotic behavior of the approximate potential. A general framework for numerically computing OPCA, for any given number of approximating charges, is described. We then derive a 2-charge practical point charge approximation, PPCA, which approximates the 2-charge OPCA via closed form analytical expressions, and test the PPCA on a set of charge distributions relevant to biomolecular modeling. We measure the accuracy of the new approximations as the RMS error in the electrostatic potential relative to that produced by the original charge distribution, at a distance the extent of the charge distribution–the mid-field. The error for the 2-charge PPCA is found to be on average 23% smaller than that of optimally placed point dipole approximation, and comparable to that of the point quadrupole approximation. The standard deviation in RMS error for the 2-charge PPCA is 53% lower than that of the optimal point dipole approximation, and comparable to that of the point quadrupole approximation. We also calculate the 3-charge OPCA for representing the gas phase quantum mechanical charge distribution of a water molecule. The electrostatic potential calculated by the 3-charge OPCA for water, in the mid-field (2.8 Å from the oxygen atom), is on average 33.3% more accurate than the potential due to the point multipole expansion up to the octupole order. Compared to a 3 point charge approximation in which the charges are placed on the atom centers, the 3-charge OPCA is seven times more accurate, by RMS error. The maximum error at the oxygen-Na distance (2.23 Å ) is half that of the point multipole expansion up to the octupole order. PMID:23861790
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Smith, Brian J; Zhang, Lixun; Field, R William
2007-11-10
This paper presents a Bayesian model that allows for the joint prediction of county-average radon levels and estimation of the associated leukaemia risk. The methods are motivated by radon data from an epidemiologic study of residential radon in Iowa that include 2726 outdoor and indoor measurements. Prediction of county-average radon is based on a geostatistical model for the radon data which assumes an underlying continuous spatial process. In the radon model, we account for uncertainties due to incomplete spatial coverage, spatial variability, characteristic differences between homes, and detector measurement error. The predicted radon averages are, in turn, included as a covariate in Poisson models for incident cases of acute lymphocytic (ALL), acute myelogenous (AML), chronic lymphocytic (CLL), and chronic myelogenous (CML) leukaemias reported to the Iowa cancer registry from 1973 to 2002. Since radon and leukaemia risk are modelled simultaneously in our approach, the resulting risk estimates accurately reflect uncertainties in the predicted radon exposure covariate. Posterior mean (95 per cent Bayesian credible interval) estimates of the relative risk associated with a 1 pCi/L increase in radon for ALL, AML, CLL, and CML are 0.91 (0.78-1.03), 1.01 (0.92-1.12), 1.06 (0.96-1.16), and 1.12 (0.98-1.27), respectively. Copyright 2007 John Wiley & Sons, Ltd.
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Cost effectiveness of the US Geological Survey's stream-gaging program in New York
Wolcott, S.W.; Gannon, W.B.; Johnston, W.H.
1986-01-01
The U.S. Geological Survey conducted a 5-year nationwide analysis to define and document the most cost effective means of obtaining streamflow data. This report describes the stream gaging network in New York and documents the cost effectiveness of its operation; it also identifies data uses and funding sources for the 174 continuous-record stream gages currently operated (1983). Those gages as well as 189 crest-stage, stage-only, and groundwater gages are operated with a budget of $1.068 million. One gaging station was identified as having insufficient reason for continuous operation and was converted to a crest-stage gage. Current operation of the 363-station program requires a budget of $1.068 million/yr. The average standard error of estimation of continuous streamflow data is 13.4%. Results indicate that this degree of accuracy could be maintained with a budget of approximately $1.006 million if the gaging resources were redistributed among the gages. The average standard error for 174 stations was calculated for five hypothetical budgets. A minimum budget of $970,000 would be needed to operated the 363-gage program; a budget less than this does not permit proper servicing and maintenance of the gages and recorders. Under the restrictions of a minimum budget, the average standard error would be 16.0%. The maximum budget analyzed was $1.2 million, which would decrease the average standard error to 9.4%. (Author 's abstract)
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Experimental investigation of false positive errors in auditory species occurrence surveys
Miller, David A.W.; Weir, Linda A.; McClintock, Brett T.; Grant, Evan H. Campbell; Bailey, Larissa L.; Simons, Theodore R.
2012-01-01
False positive errors are a significant component of many ecological data sets, which in combination with false negative errors, can lead to severe biases in conclusions about ecological systems. We present results of a field experiment where observers recorded observations for known combinations of electronically broadcast calling anurans under conditions mimicking field surveys to determine species occurrence. Our objectives were to characterize false positive error probabilities for auditory methods based on a large number of observers, to determine if targeted instruction could be used to reduce false positive error rates, and to establish useful predictors of among-observer and among-species differences in error rates. We recruited 31 observers, ranging in abilities from novice to expert, that recorded detections for 12 species during 180 calling trials (66,960 total observations). All observers made multiple false positive errors and on average 8.1% of recorded detections in the experiment were false positive errors. Additional instruction had only minor effects on error rates. After instruction, false positive error probabilities decreased by 16% for treatment individuals compared to controls with broad confidence interval overlap of 0 (95% CI: -46 to 30%). This coincided with an increase in false negative errors due to the treatment (26%; -3 to 61%). Differences among observers in false positive and in false negative error rates were best predicted by scores from an online test and a self-assessment of observer ability completed prior to the field experiment. In contrast, years of experience conducting call surveys was a weak predictor of error rates. False positive errors were also more common for species that were played more frequently, but were not related to the dominant spectral frequency of the call. Our results corroborate other work that demonstrates false positives are a significant component of species occurrence data collected by auditory methods. Instructing observers to only report detections they are completely certain are correct is not sufficient to eliminate errors. As a result, analytical methods that account for false positive errors will be needed, and independent testing of observer ability is a useful predictor for among-observer variation in observation error rates.
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Is there any electrophysiological evidence for subliminal error processing?
Shalgi, Shani; Deouell, Leon Y.
2013-01-01
The role of error awareness in executive control and modification of behavior is not fully understood. In line with many recent studies showing that conscious awareness is unnecessary for numerous high-level processes such as strategic adjustments and decision making, it was suggested that error detection can also take place unconsciously. The Error Negativity (Ne) component, long established as a robust error-related component that differentiates between correct responses and errors, was a fine candidate to test this notion: if an Ne is elicited also by errors which are not consciously detected, it would imply a subliminal process involved in error monitoring that does not necessarily lead to conscious awareness of the error. Indeed, for the past decade, the repeated finding of a similar Ne for errors which became aware and errors that did not achieve awareness, compared to the smaller negativity elicited by correct responses (Correct Response Negativity; CRN), has lent the Ne the prestigious status of an index of subliminal error processing. However, there were several notable exceptions to these findings. The study in the focus of this review (Shalgi and Deouell, 2012) sheds new light on both types of previous results. We found that error detection as reflected by the Ne is correlated with subjective awareness: when awareness (or more importantly lack thereof) is more strictly determined using the wagering paradigm, no Ne is elicited without awareness. This result effectively resolves the issue of why there are many conflicting findings regarding the Ne and error awareness. The average Ne amplitude appears to be influenced by individual criteria for error reporting and therefore, studies containing different mixtures of participants who are more confident of their own performance or less confident, or paradigms that either encourage or don't encourage reporting low confidence errors will show different results. Based on this evidence, it is no longer possible to unquestioningly uphold the notion that the amplitude of the Ne is unrelated to subjective awareness, and therefore, that errors are detected without conscious awareness. PMID:24009548
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Insight solutions are correct more often than analytic solutions
Salvi, Carola; Bricolo, Emanuela; Kounios, John; Bowden, Edward; Beeman, Mark
2016-01-01
How accurate are insights compared to analytical solutions? In four experiments, we investigated how participants’ solving strategies influenced their solution accuracies across different types of problems, including one that was linguistic, one that was visual and two that were mixed visual-linguistic. In each experiment, participants’ self-judged insight solutions were, on average, more accurate than their analytic ones. We hypothesised that insight solutions have superior accuracy because they emerge into consciousness in an all-or-nothing fashion when the unconscious solving process is complete, whereas analytic solutions can be guesses based on conscious, prematurely terminated, processing. This hypothesis is supported by the finding that participants’ analytic solutions included relatively more incorrect responses (i.e., errors of commission) than timeouts (i.e., errors of omission) compared to their insight responses. PMID:27667960
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Space-borne remote sensing of CO2 by IPDA lidar with heterodyne detection: random error estimation
NASA Astrophysics Data System (ADS)
Matvienko, G. G.; Sukhanov, A. Y.
2015-11-01
Possibilities of measuring the CO2 column concentration by spaceborne integrated path differential lidar (IPDA) signals in the near IR absorption bands are investigated. It is shown that coherent detection principles applied in the nearinfrared spectral region promise a high sensitivity for the measurement of the integrated dry air column mixing ratio of the CO2. The simulations indicate that for CO2 the target observational requirements (0.2%) for the relative random error can be met with telescope aperture 0.5 m, detector bandwidth 10 MHz, laser energy per impulse 0.3 mJ and averaging 7500 impulses. It should also be noted that heterodyne technique allows to significantly reduce laser power and receiver overall dimensions compared to direct detection.
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Sources of error in estimating truck traffic from automatic vehicle classification data
DOT National Transportation Integrated Search
1998-10-01
Truck annual average daily traffic estimation errors resulting from sample classification counts are computed in this paper under two scenarios. One scenario investigates an improper factoring procedure that may be used by highway agencies. The study...
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Retrospective analysis of refractive errors in children with vision impairment.
Du, Jojo W; Schmid, Katrina L; Bevan, Jennifer D; Frater, Karen M; Ollett, Rhondelle; Hein, Bronwyn
2005-09-01
Emmetropization is the reduction in neonatal refractive errors that occurs after birth. Ocular disease may affect this process. We aimed to determine the relative frequency of ocular conditions causing vision impairment in the pediatric population and characterize the refractive anomalies present. We also compared the causes of vision impairment in children today to those between 1974 and 1981. Causes of vision impairment and refractive data of 872 children attending a pediatric low-vision clinic from 1985 to 2002 were retrospectively collated. As a result of associated impairments, refractive data were not available for 59 children. An analysis was made of the causes of vision impairment, the distribution of refractive errors in children with vision impairment, and the average type of refractive error for the most commonly seen conditions. We found that cortical or cerebral vision impairment (CVI) was the most common condition causing vision impairment, accounting for 27.6% of cases. This was followed by albinism (10.6%), retinopathy of prematurity (ROP; 7.0%), optic atrophy (6.2%), and optic nerve hypoplasia (5.3%). Vision impairment was associated with ametropia; fewer than 25% of the children had refractive errors < or = +/-1 D. The refractive error frequency plots (for 0 to 2-, 6 to 8-, and 12 to 14-year age bands) had a Gaussian distribution indicating that the emmetropization process was abnormal. The mean spherical equivalent refractive error of the children (n = 813) was +0.78 +/- 6.00 D with 0.94 +/- 1.24 D of astigmatism and 0.92 +/- 2.15 D of anisometropia. Most conditions causing vision impairment such as albinism were associated with low amounts of hyperopia. Moderate myopia was observed in children with ROP. The relative frequency of ocular conditions causing vision impairment in children has changed since the 1970s. Children with vision impairment often have an associated ametropia suggesting that the emmetropization system is also impaired.
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Using the Coronal Evolution to Successfully Forward Model CMEs' In Situ Magnetic Profiles
NASA Astrophysics Data System (ADS)
Kay, C.; Gopalswamy, N.
2017-12-01
Predicting the effects of a coronal mass ejection (CME) impact requires knowing if impact will occur, which part of the CME impacts, and its magnetic properties. We explore the relation between CME deflections and rotations, which change the position and orientation of a CME, and the resulting magnetic profiles at 1 AU. For 45 STEREO-era, Earth-impacting CMEs, we determine the solar source of each CME, reconstruct its coronal position and orientation, and perform a ForeCAT (Forecasting a CME's Altered Trajectory) simulation of the coronal deflection and rotation. From the reconstructed and modeled CME deflections and rotations, we determine the solar cycle variation and correlations with CME properties. We assume no evolution between the outer corona and 1 AU and use the ForeCAT results to drive the ForeCAT In situ Data Observer (FIDO) in situ magnetic field model, allowing for comparisons with ACE and Wind observations. We do not attempt to reproduce the arrival time. On average FIDO reproduces the in situ magnetic field for each vector component with an error equivalent to 35% of the average total magnetic field strength when the total modeled magnetic field is scaled to match the average observed value. Random walk best fits distinguish between ForeCAT's ability to determine FIDO's input parameters and the limitations of the simple flux rope model. These best fits reduce the average error to 30%. The FIDO results are sensitive to changes of order a degree in the CME latitude, longitude, and tilt, suggesting that accurate space weather predictions require accurate measurements of a CME's position and orientation.
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A Stochastic Kinematic Model of Class Averaging in Single-Particle Electron Microscopy
Park, Wooram; Midgett, Charles R.; Madden, Dean R.; Chirikjian, Gregory S.
2011-01-01
Single-particle electron microscopy is an experimental technique that is used to determine the 3D structure of biological macromolecules and the complexes that they form. In general, image processing techniques and reconstruction algorithms are applied to micrographs, which are two-dimensional (2D) images taken by electron microscopes. Each of these planar images can be thought of as a projection of the macromolecular structure of interest from an a priori unknown direction. A class is defined as a collection of projection images with a high degree of similarity, presumably resulting from taking projections along similar directions. In practice, micrographs are very noisy and those in each class are aligned and averaged in order to reduce the background noise. Errors in the alignment process are inevitable due to noise in the electron micrographs. This error results in blurry averaged images. In this paper, we investigate how blurring parameters are related to the properties of the background noise in the case when the alignment is achieved by matching the mass centers and the principal axes of the experimental images. We observe that the background noise in micrographs can be treated as Gaussian. Using the mean and variance of the background Gaussian noise, we derive equations for the mean and variance of translational and rotational misalignments in the class averaging process. This defines a Gaussian probability density on the Euclidean motion group of the plane. Our formulation is validated by convolving the derived blurring function representing the stochasticity of the image alignments with the underlying noiseless projection and comparing with the original blurry image. PMID:21660125
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Toward Joint Hypothesis-Tests Seismic Event Screening Analysis: Ms|mb and Event Depth
DOE Office of Scientific and Technical Information (OSTI.GOV)
Anderson, Dale; Selby, Neil
2012-08-14
Well established theory can be used to combine single-phenomenology hypothesis tests into a multi-phenomenology event screening hypothesis test (Fisher's and Tippett's tests). Commonly used standard error in Ms:mb event screening hypothesis test is not fully consistent with physical basis. Improved standard error - Better agreement with physical basis, and correctly partitions error to include Model Error as a component of variance, correctly reduces station noise variance through network averaging. For 2009 DPRK test - Commonly used standard error 'rejects' H0 even with better scaling slope ({beta} = 1, Selby et al.), improved standard error 'fails to rejects' H0.
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Trehan, Sumeet; Carlberg, Kevin T.; Durlofsky, Louis J.
2017-07-14
A machine learning–based framework for modeling the error introduced by surrogate models of parameterized dynamical systems is proposed. The framework entails the use of high-dimensional regression techniques (eg, random forests, and LASSO) to map a large set of inexpensively computed “error indicators” (ie, features) produced by the surrogate model at a given time instance to a prediction of the surrogate-model error in a quantity of interest (QoI). This eliminates the need for the user to hand-select a small number of informative features. The methodology requires a training set of parameter instances at which the time-dependent surrogate-model error is computed bymore » simulating both the high-fidelity and surrogate models. Using these training data, the method first determines regression-model locality (via classification or clustering) and subsequently constructs a “local” regression model to predict the time-instantaneous error within each identified region of feature space. We consider 2 uses for the resulting error model: (1) as a correction to the surrogate-model QoI prediction at each time instance and (2) as a way to statistically model arbitrary functions of the time-dependent surrogate-model error (eg, time-integrated errors). We then apply the proposed framework to model errors in reduced-order models of nonlinear oil-water subsurface flow simulations, with time-varying well-control (bottom-hole pressure) parameters. The reduced-order models used in this work entail application of trajectory piecewise linearization in conjunction with proper orthogonal decomposition. Moreover, when the first use of the method is considered, numerical experiments demonstrate consistent improvement in accuracy in the time-instantaneous QoI prediction relative to the original surrogate model, across a large number of test cases. When the second use is considered, results show that the proposed method provides accurate statistical predictions of the time- and well-averaged errors.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Trehan, Sumeet; Carlberg, Kevin T.; Durlofsky, Louis J.
A machine learning–based framework for modeling the error introduced by surrogate models of parameterized dynamical systems is proposed. The framework entails the use of high-dimensional regression techniques (eg, random forests, and LASSO) to map a large set of inexpensively computed “error indicators” (ie, features) produced by the surrogate model at a given time instance to a prediction of the surrogate-model error in a quantity of interest (QoI). This eliminates the need for the user to hand-select a small number of informative features. The methodology requires a training set of parameter instances at which the time-dependent surrogate-model error is computed bymore » simulating both the high-fidelity and surrogate models. Using these training data, the method first determines regression-model locality (via classification or clustering) and subsequently constructs a “local” regression model to predict the time-instantaneous error within each identified region of feature space. We consider 2 uses for the resulting error model: (1) as a correction to the surrogate-model QoI prediction at each time instance and (2) as a way to statistically model arbitrary functions of the time-dependent surrogate-model error (eg, time-integrated errors). We then apply the proposed framework to model errors in reduced-order models of nonlinear oil-water subsurface flow simulations, with time-varying well-control (bottom-hole pressure) parameters. The reduced-order models used in this work entail application of trajectory piecewise linearization in conjunction with proper orthogonal decomposition. Moreover, when the first use of the method is considered, numerical experiments demonstrate consistent improvement in accuracy in the time-instantaneous QoI prediction relative to the original surrogate model, across a large number of test cases. When the second use is considered, results show that the proposed method provides accurate statistical predictions of the time- and well-averaged errors.« less
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High order cell-centered scheme totally based on cell average
NASA Astrophysics Data System (ADS)
Liu, Ze-Yu; Cai, Qing-Dong
2018-05-01
This work clarifies the concept of cell average by pointing out the differences between cell average and cell centroid value, which are averaged cell-centered value and pointwise cell-centered value, respectively. Interpolation based on cell averages is constructed and high order QUICK-like numerical scheme is designed for such interpolation. A new approach of error analysis is introduced in this work, which is similar to Taylor’s expansion.
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Quan, Guo-zheng; Yu, Chun-tang; Liu, Ying-ying; Xia, Yu-feng
2014-01-01
The stress-strain data of 20MnNiMo alloy were collected from a series of hot compressions on Gleeble-1500 thermal-mechanical simulator in the temperature range of 1173 ∼ 1473 K and strain rate range of 0.01 ∼ 10 s(-1). Based on the experimental data, the improved Arrhenius-type constitutive model and the artificial neural network (ANN) model were established to predict the high temperature flow stress of as-cast 20MnNiMo alloy. The accuracy and reliability of the improved Arrhenius-type model and the trained ANN model were further evaluated in terms of the correlation coefficient (R), the average absolute relative error (AARE), and the relative error (η). For the former, R and AARE were found to be 0.9954 and 5.26%, respectively, while, for the latter, 0.9997 and 1.02%, respectively. The relative errors (η) of the improved Arrhenius-type model and the ANN model were, respectively, in the range of -39.99% ∼ 35.05% and -3.77% ∼ 16.74%. As for the former, only 16.3% of the test data set possesses η-values within ± 1%, while, as for the latter, more than 79% possesses. The results indicate that the ANN model presents a higher predictable ability than the improved Arrhenius-type constitutive model.
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Atwood, E.L.
1958-01-01
Response bias errors are studied by comparing questionnaire responses from waterfowl hunters using four large public hunting areas with actual hunting data from these areas during two hunting seasons. To the extent that the data permit, the sources of the error in the responses were studied and the contribution of each type to the total error was measured. Response bias errors, including both prestige and memory bias, were found to be very large as compared to non-response and sampling errors. Good fits were obtained with the seasonal kill distribution of the actual hunting data and the negative binomial distribution and a good fit was obtained with the distribution of total season hunting activity and the semi-logarithmic curve. A comparison of the actual seasonal distributions with the questionnaire response distributions revealed that the prestige and memory bias errors are both positive. The comparisons also revealed the tendency for memory bias errors to occur at digit frequencies divisible by five and for prestige bias errors to occur at frequencies which are multiples of the legal daily bag limit. A graphical adjustment of the response distributions was carried out by developing a smooth curve from those frequency classes not included in the predictable biased frequency classes referred to above. Group averages were used in constructing the curve, as suggested by Ezekiel [1950]. The efficiency of the technique described for reducing response bias errors in hunter questionnaire responses on seasonal waterfowl kill is high in large samples. The graphical method is not as efficient in removing response bias errors in hunter questionnaire responses on seasonal hunting activity where an average of 60 percent was removed.
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Green-Ampt approximations: A comprehensive analysis
NASA Astrophysics Data System (ADS)
Ali, Shakir; Islam, Adlul; Mishra, P. K.; Sikka, Alok K.
2016-04-01
Green-Ampt (GA) model and its modifications are widely used for simulating infiltration process. Several explicit approximate solutions to the implicit GA model have been developed with varying degree of accuracy. In this study, performance of nine explicit approximations to the GA model is compared with the implicit GA model using the published data for broad range of soil classes and infiltration time. The explicit GA models considered are Li et al. (1976) (LI), Stone et al. (1994) (ST), Salvucci and Entekhabi (1994) (SE), Parlange et al. (2002) (PA), Barry et al. (2005) (BA), Swamee et al. (2012) (SW), Ali et al. (2013) (AL), Almedeij and Esen (2014) (AE), and Vatankhah (2015) (VA). Six statistical indicators (e.g., percent relative error, maximum absolute percent relative error, average absolute percent relative errors, percent bias, index of agreement, and Nash-Sutcliffe efficiency) and relative computer computation time are used for assessing the model performance. Models are ranked based on the overall performance index (OPI). The BA model is found to be the most accurate followed by the PA and VA models for variety of soil classes and infiltration periods. The AE, SW, SE, and LI model also performed comparatively better. Based on the overall performance index, the explicit models are ranked as BA > PA > VA > LI > AE > SE > SW > ST > AL. Results of this study will be helpful in selection of accurate and simple explicit approximate GA models for solving variety of hydrological problems.
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Electron Gun and Collector Design for 94 GHz Gyro-amplifiers.
NASA Astrophysics Data System (ADS)
Nguyen, K.; Danly, B.; Levush, B.; Blank, M.; True, D.; Felch, K.; Borchard, P.
1997-05-01
The electrical design of the magnetron injection gun and collector for high average power TE_01 gyro-amplifiers has recently been completed using the EGUN(W.B. Herrmannsfeldt, AIP Conf. Proc. 177, pp. 45-58, 1988.) and DEMEOS(R. True, AIP Conf. Proc. 297, pp. 493-499, 1993.) codes. The gun employs an optimized double-anode geometry and a radical cathode cone angle of 500 to achieve superior beam optics that are relatively insensitive to electrode misalignments and field errors. Perpendicular velocity spread of 1.6% at an perpendicular to axial velocity ratio of 1.52 is obtained for a 6 A, 65 kV beam. The 1.28" diameter collector, which also serves as the output waveguide, has an average power density of < 350 W/cm^2 for a 59 kW average power beam. Details will be presented at the conference.
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NASA Astrophysics Data System (ADS)
Chen, Jing-Bo
2014-06-01
By using low-frequency components of the damped wavefield, Laplace-Fourier-domain full waveform inversion (FWI) can recover a long-wavelength velocity model from the original undamped seismic data lacking low-frequency information. Laplace-Fourier-domain modelling is an important foundation of Laplace-Fourier-domain FWI. Based on the numerical phase velocity and the numerical attenuation propagation velocity, a method for performing Laplace-Fourier-domain numerical dispersion analysis is developed in this paper. This method is applied to an average-derivative optimal scheme. The results show that within the relative error of 1 per cent, the Laplace-Fourier-domain average-derivative optimal scheme requires seven gridpoints per smallest wavelength and smallest pseudo-wavelength for both equal and unequal directional sampling intervals. In contrast, the classical five-point scheme requires 23 gridpoints per smallest wavelength and smallest pseudo-wavelength to achieve the same accuracy. Numerical experiments demonstrate the theoretical analysis.
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NASA Astrophysics Data System (ADS)
Ryu, Y. H.; Hodzic, A.; Barré, J.; Descombes, G.; Minnis, P.
2017-12-01
Clouds play a key role in radiation and hence O3 photochemistry by modulating photolysis rates and light-dependent emissions of biogenic volatile organic compounds (BVOCs). It is not well known, however, how much of the bias in O3 predictions is caused by inaccurate cloud predictions. This study quantifies the errors in surface O3 predictions associated with clouds in summertime over CONUS using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. Cloud fields used for photochemistry are corrected based on satellite cloud retrievals in sensitivity simulations. It is found that the WRF-Chem model is able to detect about 60% of clouds in the right locations and generally underpredicts cloud optical depths. The errors in hourly O3 due to the errors in cloud predictions can be up to 60 ppb. On average in summertime over CONUS, the errors in 8-h average O3 of 1-6 ppb are found to be attributable to those in cloud predictions under cloudy sky conditions. The contribution of changes in photolysis rates due to clouds is found to be larger ( 80 % on average) than that of light-dependent BVOC emissions. The effects of cloud corrections on O3 are about 2 times larger in VOC-limited than NOx-limited regimes, suggesting that the benefits of accurate cloud predictions would be greater in VOC-limited than NOx-limited regimes.
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SU-E-T-195: Gantry Angle Dependency of MLC Leaf Position Error
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ju, S; Hong, C; Kim, M
Purpose: The aim of this study was to investigate the gantry angle dependency of the multileaf collimator (MLC) leaf position error. Methods: An automatic MLC quality assurance system (AutoMLCQA) was developed to evaluate the gantry angle dependency of the MLC leaf position error using an electronic portal imaging device (EPID). To eliminate the EPID position error due to gantry rotation, we designed a reference maker (RM) that could be inserted into the wedge mount. After setting up the EPID, a reference image was taken of the RM using an open field. Next, an EPID-based picket-fence test (PFT) was performed withoutmore » the RM. These procedures were repeated at every 45° intervals of the gantry angle. A total of eight reference images and PFT image sets were analyzed using in-house software. The average MLC leaf position error was calculated at five pickets (-10, -5, 0, 5, and 10 cm) in accordance with general PFT guidelines using in-house software. This test was carried out for four linear accelerators. Results: The average MLC leaf position errors were within the set criterion of <1 mm (actual errors ranged from -0.7 to 0.8 mm) for all gantry angles, but significant gantry angle dependency was observed in all machines. The error was smaller at a gantry angle of 0° but increased toward the positive direction with gantry angle increments in the clockwise direction. The error reached a maximum value at a gantry angle of 90° and then gradually decreased until 180°. In the counter-clockwise rotation of the gantry, the same pattern of error was observed but the error increased in the negative direction. Conclusion: The AutoMLCQA system was useful to evaluate the MLC leaf position error for various gantry angles without the EPID position error. The Gantry angle dependency should be considered during MLC leaf position error analysis.« less
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Prediction of boiling points of organic compounds by QSPR tools.
Dai, Yi-min; Zhu, Zhi-ping; Cao, Zhong; Zhang, Yue-fei; Zeng, Ju-lan; Li, Xun
2013-07-01
The novel electro-negativity topological descriptors of YC, WC were derived from molecular structure by equilibrium electro-negativity of atom and relative bond length of molecule. The quantitative structure-property relationships (QSPR) between descriptors of YC, WC as well as path number parameter P3 and the normal boiling points of 80 alkanes, 65 unsaturated hydrocarbons and 70 alcohols were obtained separately. The high-quality prediction models were evidenced by coefficient of determination (R(2)), the standard error (S), average absolute errors (AAE) and predictive parameters (Qext(2),RCV(2),Rm(2)). According to the regression equations, the influences of the length of carbon backbone, the size, the degree of branching of a molecule and the role of functional groups on the normal boiling point were analyzed. Comparison results with reference models demonstrated that novel topological descriptors based on the equilibrium electro-negativity of atom and the relative bond length were useful molecular descriptors for predicting the normal boiling points of organic compounds. Copyright © 2013 Elsevier Inc. All rights reserved.
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NASA Astrophysics Data System (ADS)
Cai, Jun; Wang, Kuaishe; Shi, Jiamin; Wang, Wen; Liu, Yingying
2018-01-01
Constitutive analysis for hot working of BFe10-1-2 alloy was carried out by using experimental stress-strain data from isothermal hot compression tests, in a wide range of temperature of 1,023 1,273 K, and strain rate range of 0.001 10 s-1. A constitutive equation based on modified double multiple nonlinear regression was proposed considering the independent effects of strain, strain rate, temperature and their interrelation. The predicted flow stress data calculated from the developed equation was compared with the experimental data. Correlation coefficient (R), average absolute relative error (AARE) and relative errors were introduced to verify the validity of the developed constitutive equation. Subsequently, a comparative study was made on the capability of strain-compensated Arrhenius-type constitutive model. The results showed that the developed constitutive equation based on modified double multiple nonlinear regression could predict flow stress of BFe10-1-2 alloy with good correlation and generalization.
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Li, Jun; Shi, Wenyin; Andrews, David; Werner-Wasik, Maria; Lu, Bo; Yu, Yan; Dicker, Adam; Liu, Haisong
2017-06-01
The study was aimed to compare online 6 degree-of-freedom image registrations of TrueBeam cone-beam computed tomography and BrainLab ExacTrac X-ray imaging systems for intracranial radiosurgery. Phantom and patient studies were performed on a Varian TrueBeam STx linear accelerator (version 2.5), which is integrated with a BrainLab ExacTrac imaging system (version 6.1.1). The phantom study was based on a Rando head phantom and was designed to evaluate isocenter location dependence of the image registrations. Ten isocenters at various locations representing clinical treatment sites were selected in the phantom. Cone-beam computed tomography and ExacTrac X-ray images were taken when the phantom was located at each isocenter. The patient study included 34 patients. Cone-beam computed tomography and ExacTrac X-ray images were taken at each patient's treatment position. The 6 degree-of-freedom image registrations were performed on cone-beam computed tomography and ExacTrac, and residual errors calculated from cone-beam computed tomography and ExacTrac were compared. In the phantom study, the average residual error differences (absolute values) between cone-beam computed tomography and ExacTrac image registrations were 0.17 ± 0.11 mm, 0.36 ± 0.20 mm, and 0.25 ± 0.11 mm in the vertical, longitudinal, and lateral directions, respectively. The average residual error differences in the rotation, roll, and pitch were 0.34° ± 0.08°, 0.13° ± 0.09°, and 0.12° ± 0.10°, respectively. In the patient study, the average residual error differences in the vertical, longitudinal, and lateral directions were 0.20 ± 0.16 mm, 0.30 ± 0.18 mm, 0.21 ± 0.18 mm, respectively. The average residual error differences in the rotation, roll, and pitch were 0.40°± 0.16°, 0.17° ± 0.13°, and 0.20° ± 0.14°, respectively. Overall, the average residual error differences were <0.4 mm in the translational directions and <0.5° in the rotational directions. ExacTrac X-ray image registration is comparable to TrueBeam cone-beam computed tomography image registration in intracranial treatments.
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NASA Technical Reports Server (NTRS)
Oreopoulos, L.; Chou, M.-D.; Khairoutdinov, M.; Barker, H. W.; Cahalan, R. F.
2003-01-01
We test the performance of the shortwave (SW) and longwave (LW) Column Radiation Models (CORAMs) of Chou and collaborators with heterogeneous cloud fields from a global single-day dataset produced by NCAR's Community Atmospheric Model with a 2-D CRM installed in each gridbox. The original SW version of the CORAM performs quite well compared to reference Independent Column Approximation (ICA) calculations for boundary fluxes, largely due to the success of a combined overlap and cloud scaling parameterization scheme. The absolute magnitude of errors relative to ICA are even smaller for the LW CORAM which applies similar overlap. The vertical distribution of heating and cooling within the atmosphere is also simulated quite well with daily-averaged zonal errors always below 0.3 K/d for SW heating rates and 0.6 K/d for LW cooling rates. The SW CORAM's performance improves by introducing a scheme that accounts for cloud inhomogeneity. These results suggest that previous studies demonstrating the inaccuracy of plane-parallel models may have unfairly focused on worst scenario cases, and that current radiative transfer algorithms of General Circulation Models (GCMs) may be more capable than previously thought in estimating realistic spatial and temporal averages of radiative fluxes, as long as they are provided with correct mean cloud profiles. However, even if the errors of the particular CORAMs are small, they seem to be systematic, and the impact of the biases can be fully assessed only with GCM climate simulations.
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NASA Astrophysics Data System (ADS)
Guan, Weipeng; Wu, Yuxiang; Xie, Canyu; Chen, Hao; Cai, Ye; Chen, Yingcong
2017-10-01
An indoor positioning algorithm based on visible light communication (VLC) is presented. This algorithm is used to calculate a three-dimensional (3-D) coordinate of an indoor optical wireless environment, which includes sufficient orders of multipath reflections from reflecting surfaces of the room. Leveraging the global optimization ability of the genetic algorithm (GA), an innovative framework for 3-D position estimation based on a modified genetic algorithm is proposed. Unlike other techniques using VLC for positioning, the proposed system can achieve indoor 3-D localization without making assumptions about the height or acquiring the orientation angle of the mobile terminal. Simulation results show that an average localization error of less than 1.02 cm can be achieved. In addition, in most VLC-positioning systems, the effect of reflection is always neglected and its performance is limited by reflection, which makes the results not so accurate for a real scenario and the positioning errors at the corners are relatively larger than other places. So, we take the first-order reflection into consideration and use artificial neural network to match the model of a nonlinear channel. The studies show that under the nonlinear matching of direct and reflected channels the average positioning errors of four corners decrease from 11.94 to 0.95 cm. The employed algorithm is emerged as an effective and practical method for indoor localization and outperform other existing indoor wireless localization approaches.
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Virtual Sensors for On-line Wheel Wear and Part Roughness Measurement in the Grinding Process
Arriandiaga, Ander; Portillo, Eva; Sánchez, Jose A.; Cabanes, Itziar; Pombo, Iñigo
2014-01-01
Grinding is an advanced machining process for the manufacturing of valuable complex and accurate parts for high added value sectors such as aerospace, wind generation, etc. Due to the extremely severe conditions inside grinding machines, critical process variables such as part surface finish or grinding wheel wear cannot be easily and cheaply measured on-line. In this paper a virtual sensor for on-line monitoring of those variables is presented. The sensor is based on the modelling ability of Artificial Neural Networks (ANNs) for stochastic and non-linear processes such as grinding; the selected architecture is the Layer-Recurrent neural network. The sensor makes use of the relation between the variables to be measured and power consumption in the wheel spindle, which can be easily measured. A sensor calibration methodology is presented, and the levels of error that can be expected are discussed. Validation of the new sensor is carried out by comparing the sensor's results with actual measurements carried out in an industrial grinding machine. Results show excellent estimation performance for both wheel wear and surface roughness. In the case of wheel wear, the absolute error is within the range of microns (average value 32 μm). In the case of surface finish, the absolute error is well below Ra 1 μm (average value 0.32 μm). The present approach can be easily generalized to other grinding operations. PMID:24854055
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Bukaveckas, P.A.; Likens, G.E.; Winter, T.C.; Buso, D.C.
1998-01-01
Calculation of chemical flux rates for streams requires integration of continuous measurements of discharge with discrete measurements of solute concentrations. We compared two commonly used methods for interpolating chemistry data (time-averaging and flow-weighting) to determine whether discrepancies between the two methods were large relative to other sources of error in estimating flux rates. Flux rates of dissolved Si and SO42- were calculated from 10 years of data (1981-1990) for the NW inlet and Outlet of Mirror Lake and for a 40-day period (March 22 to April 30, 1993) during which we augmented our routine (weekly) chemical monitoring with collection of daily samples. The time-averaging method yielded higher estimates of solute flux during high-flow periods if no chemistry samples were collected corresponding to peak discharge. Concentration-discharge relationships should be used to interpolate stream chemistry during changing flow conditions if chemical changes are large. Caution should be used in choosing the appropriate time-scale over which data are pooled to derive the concentration-discharge regressions because the model parameters (slope and intercept) were found to be sensitive to seasonal and inter-annual variation. Both methods approximated solute flux to within 2-10% for a range of solutes that were monitored during the intensive sampling period. Our results suggest that errors arising from interpolation of stream chemistry data are small compared with other sources of error in developing watershed mass balances.
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NASA Astrophysics Data System (ADS)
McAfee, S. A.; DeLaFrance, A.
2017-12-01
Investigating the impacts of climate change often entails using projections from inherently imperfect general circulation models (GCMs) to drive models that simulate biophysical or societal systems in great detail. Error or bias in the GCM output is often assessed in relation to observations, and the projections are adjusted so that the output from impacts models can be compared to historical or observed conditions. Uncertainty in the projections is typically accommodated by running more than one future climate trajectory to account for differing emissions scenarios, model simulations, and natural variability. The current methods for dealing with error and uncertainty treat them as separate problems. In places where observed and/or simulated natural variability is large, however, it may not be possible to identify a consistent degree of bias in mean climate, blurring the lines between model error and projection uncertainty. Here we demonstrate substantial instability in mean monthly temperature bias across a suite of GCMs used in CMIP5. This instability is greatest in the highest latitudes during the cool season, where shifts from average temperatures below to above freezing could have profound impacts. In models with the greatest degree of bias instability, the timing of regional shifts from below to above average normal temperatures in a single climate projection can vary by about three decades, depending solely on the degree of bias assessed. This suggests that current bias correction methods based on comparison to 20- or 30-year normals may be inappropriate, particularly in the polar regions.
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NASA Technical Reports Server (NTRS)
Hou, Arthur Y.; Zhang, Sara Q.; daSilva, Arlindo M.
1999-01-01
Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of rainfall and total precipitable water (TPW) observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve these fields in reanalyses. The DAO has developed a "1+1"D procedure to assimilate 6-hr averaged rainfall and TPW into the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS. The "1+1" designation refers to one spatial dimension plus one temporal dimension. The scheme minimizes the least-square differences between the satellite-retrieved rain rates and those produced by the column model over the 6-hr analysis window. The control variables are analysis increments of moisture within the Incremental Analysis Update (IAU) framework of the GEOS DAS. This 1+1D scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but differs in its choice of the control variable. Instead of estimating the initial condition at the beginning of the assimilation cycle, it estimates the constant IAU forcing applied over a 6-hr assimilation cycle. In doing so, it imposes the forecast model as a weak constraint in a manner similar to the variational continuous assimilation techniques. We present results from an experiment in which the observed rain rate and TPW are assumed to be "perfect". They show that assimilating the TMI and SSM/I-derived surface precipitation and TPW observations improves not only the precipitation and moisture fields but also key climate parameters directly linked to convective activities such as clouds, the outgoing longwave radiation, and the large-scale circulation in the tropics. In particular, assimilating these data types reduce the state-dependent systematic errors in the assimilated products. The improved analysis also leads to a better short-range forecast, but the impact is modest compared with improvements in the time-averaged fields. These results suggest that, in the presence of biases and other errors of the forecast model, it is possible to improve the time-averaged "climate content" in the assimilated data without comparable improvements in the short-range forecast skill. Results of this experiment provide a useful benchmark for evaluating error covariance models for optimal use of these data types.
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On the use of unshielded cables in ionization chamber dosimetry for total-skin electron therapy.
Chen, Z; Agostinelli, A; Nath, R
1998-03-01
The dosimetry of total-skin electron therapy (TSET) usually requires ionization chamber measurements in a large electron beam (up to 120 cm x 200 cm). Exposing the chamber's electric cable, its connector and part of the extension cable to the large electron beam will introduce unwanted electronic signals that may lead to inaccurate dosimetry results. While the best strategy to minimize the cable-induced electronic signal is to shield the cables and its connector from the primary electrons, as has been recommended by the AAPM Task Group Report 23 on TSET, cables without additional shielding are often used in TSET dosimetry measurements for logistic reasons, for example when an automatic scanning dosimetry is used. This paper systematically investigates the consequences and the acceptability of using an unshielded cable in ionization chamber dosimetry in a large TSET electron beam. In this paper, we separate cable-induced signals into two types. The type-I signal includes all charges induced which do not change sign upon switching the chamber polarity, and type II includes all those that do. The type-I signal is easily cancelled by the polarity averaging method. The type-II cable-induced signal is independent of the depth of the chamber in a phantom and its magnitude relative to the true signal determines the acceptability of a cable for use under unshielded conditions. Three different cables were evaluated in two different TSET beams in this investigation. For dosimetry near the depth of maximum buildup, the cable-induced dosimetry error was found to be less than 0.2% when the two-polarity averaging technique was applied. At greater depths, the relative dosimetry error was found to increase at a rate approximately equal to the inverse of the electron depth dose. Since the application of the two-polarity averaging technique requires a constant-irradiation condition, it was demonstrated than an additional error of up to 4% could be introduced if the unshielded cable's spatial configuration were altered during the two-polarity measurements. This suggests that automatic scanning systems with unshielded cables should not be used in TSET ionization chamber dosimetry. However, the data did show that an unshielded cable may be used in TSET ionization chamber dosimetry if the size of cable-induced error in a given TSET beam is pre-evaluated and the measurement is carefully conducted. When such an evaluation has not been performed, additional shielding should be applied to the cable being used, making measurements at multiple points difficult.
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Lee, It Ee; Ghassemlooy, Zabih; Ng, Wai Pang; Khalighi, Mohammad-Ali
2013-02-01
Joint beam width and spatial coherence length optimization is proposed to maximize the average capacity in partially coherent free-space optical links, under the combined effects of atmospheric turbulence and pointing errors. An optimization metric is introduced to enable feasible translation of the joint optimal transmitter beam parameters into an analogous level of divergence of the received optical beam. Results show that near-ideal average capacity is best achieved through the introduction of a larger receiver aperture and the joint optimization technique.
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Cost effectiveness of the US Geological Survey's stream-gaging programs in New Hampshire and Vermont
Smath, J.A.; Blackey, F.E.
1986-01-01
Data uses and funding sources were identified for the 73 continuous stream gages currently (1984) being operated. Eight stream gages were identified as having insufficient reason to continue their operation. Parts of New Hampshire and Vermont were identified as needing additional hydrologic data. New gages should be established in these regions as funds become available. Alternative methods for providing hydrologic data at the stream gaging stations currently being operated were found to lack the accuracy that is required for their intended use. The current policy for operation of the stream gages requires a net budget of $297,000/yr. The average standard error of estimation of the streamflow records is 17.9%. This overall level of accuracy could be maintained with a budget of $285,000 if resources were redistributed among gages. Cost-effective analysis indicates that with the present budget, the average standard error could be reduced to 16.6%. A minimum budget of $278,000 is required to operate the present stream gaging program. Below this level, the gages and recorders would not receive the proper service and maintenance. At the minimum budget, the average standard error would be 20.4%. The loss of correlative data is a significant component of the error in streamflow records, especially at lower budgetary levels. (Author 's abstract)
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Time-resolved dosimetry using a pinpoint ionization chamber as quality assurance for IMRT and VMAT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Louwe, Robert J. W., E-mail: rob.louwe@ccdbh.org.nz; Satherley, Thomas; Day, Rebecca A.
Purpose: To develop a method to verify the dose delivery in relation to the individual control points of intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) using an ionization chamber. In addition to more effective problem solving during patient-specific quality assurance (QA), the aim is to eventually map out the limitations in the treatment chain and enable a targeted improvement of the treatment technique in an efficient way. Methods: Pretreatment verification was carried out for 255 treatment plans that included a broad range of treatment indications in two departments using the equipment of different vendors. In-house developed softwaremore » was used to enable calculation of the dose delivery for the individual beamlets in the treatment planning system (TPS), for data acquisition, and for analysis of the data. The observed deviations were related to various delivery and measurement parameters such as gantry angle, field size, and the position of the detector with respect to the field edge to distinguish between error sources. Results: The average deviation of the integral fraction dose during pretreatment verification of the planning target volume dose was −2.1% ± 2.2% (1 SD), −1.7% ± 1.7% (1 SD), and 0.0% ± 1.3% (1 SD) for IMRT at the Radboud University Medical Center (RUMC), VMAT (RUMC), and VMAT at the Wellington Blood and Cancer Centre, respectively. Verification of the dose to organs at risk gave very similar results but was generally subject to a larger measurement uncertainty due to the position of the detector at a high dose gradient. The observed deviations could be related to limitations of the TPS beam models, attenuation of the treatment couch, as well as measurement errors. The apparent systematic error of about −2% in the average deviation of the integral fraction dose in the RUMC results could be explained by the limitations of the TPS beam model in the calculation of the beam penumbra. Conclusions: This study showed that time-resolved dosimetry using an ionization chamber is feasible and can be largely automated which limits the required additional time compared to integrated dose measurements. It provides a unique QA method which enables identification and quantification of the contribution of various error sources during IMRT and VMAT delivery.« less
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Syamlal, Madhava; Celik, Ismail B.; Benyahia, Sofiane
2017-07-12
The two-fluid model (TFM) has become a tool for the design and troubleshooting of industrial fluidized bed reactors. To use TFM for scale up with confidence, the uncertainty in its predictions must be quantified. Here, we study two sources of uncertainty: discretization and time-averaging. First, we show that successive grid refinement may not yield grid-independent transient quantities, including cross-section–averaged quantities. Successive grid refinement would yield grid-independent time-averaged quantities on sufficiently fine grids. A Richardson extrapolation can then be used to estimate the discretization error, and the grid convergence index gives an estimate of the uncertainty. Richardson extrapolation may not workmore » for industrial-scale simulations that use coarse grids. We present an alternative method for coarse grids and assess its ability to estimate the discretization error. Second, we assess two methods (autocorrelation and binning) and find that the autocorrelation method is more reliable for estimating the uncertainty introduced by time-averaging TFM data.« less
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Robust Tomography using Randomized Benchmarking
NASA Astrophysics Data System (ADS)
Silva, Marcus; Kimmel, Shelby; Johnson, Blake; Ryan, Colm; Ohki, Thomas
2013-03-01
Conventional randomized benchmarking (RB) can be used to estimate the fidelity of Clifford operations in a manner that is robust against preparation and measurement errors -- thus allowing for a more accurate and relevant characterization of the average error in Clifford gates compared to standard tomography protocols. Interleaved RB (IRB) extends this result to the extraction of error rates for individual Clifford gates. In this talk we will show how to combine multiple IRB experiments to extract all information about the unital part of any trace preserving quantum process. Consequently, one can compute the average fidelity to any unitary, not just the Clifford group, with tighter bounds than IRB. Moreover, the additional information can be used to design improvements in control. MS, BJ, CR and TO acknowledge support from IARPA under contract W911NF-10-1-0324.
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Photos provide information on age, but not kinship, of Andean bear
Zug, Becky; Appleton, Robyn D.; Velez-Liendo, Ximena; Paisley, Susanna; LaCombe, Corrin
2015-01-01
Using photos of captive Andean bears of known age and pedigree, and photos of wild Andean bear cubs <6 months old, we evaluated the degree to which visual information may be used to estimate bears’ ages and assess their kinship. We demonstrate that the ages of Andean bear cubs ≤6 months old may be estimated from their size relative to their mothers with an average error of <0.01 ± 13.2 days (SD; n = 14), and that ages of adults ≥10 years old may be estimated from the proportion of their nose that is pink with an average error of <0.01 ± 3.5 years (n = 41). We also show that similarity among the bears’ natural markings, as perceived by humans, is not associated with pedigree kinship among the bears (R2 < 0.001, N = 1,043, p = 0.499). Thus, researchers may use photos of wild Andean bears to estimate the ages of young cubs and older adults, but not to infer their kinship. Given that camera trap photos are one of the most readily available sources of information on large cryptic mammals, we suggest that similar methods be tested for use in other poorly understood species. PMID:26213647
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NASA Astrophysics Data System (ADS)
De Felice, Matteo; Petitta, Marcello; Ruti, Paolo
2014-05-01
Photovoltaic diffusion is steadily growing on Europe, passing from a capacity of almost 14 GWp in 2011 to 21.5 GWp in 2012 [1]. Having accurate forecast is needed for planning and operational purposes, with the possibility to model and predict solar variability at different time-scales. This study examines the predictability of daily surface solar radiation comparing ECMWF operational forecasts with CM-SAF satellite measurements on the Meteosat (MSG) full disk domain. Operational forecasts used are the IFS system up to 10 days and the System4 seasonal forecast up to three months. Forecast are analysed considering average and variance of errors, showing error maps and average on specific domains with respect to prediction lead times. In all the cases, forecasts are compared with predictions obtained using persistence and state-of-art time-series models. We can observe a wide range of errors, with the performance of forecasts dramatically affected by orography and season. Lower errors are on southern Italy and Spain, with errors on some areas consistently under 10% up to ten days during summer (JJA). Finally, we conclude the study with some insight on how to "translate" the error on solar radiation to error on solar power production using available production data from solar power plants. [1] EurObserver, "Baromètre Photovoltaïque, Le journal des énergies renouvables, April 2012."
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Optimal interpolation schemes to constrain pmPM2.5 in regional modeling over the United States
NASA Astrophysics Data System (ADS)
Sousan, Sinan Dhia Jameel
This thesis presents the use of data assimilation with optimal interpolation (OI) to develop atmospheric aerosol concentration estimates for the United States at high spatial and temporal resolutions. Concentration estimates are highly desirable for a wide range of applications, including visibility, climate, and human health. OI is a viable data assimilation method that can be used to improve Community Multiscale Air Quality (CMAQ) model fine particulate matter (PM2.5) estimates. PM2.5 is the mass of solid and liquid particles with diameters less than or equal to 2.5 µm suspended in the gas phase. OI was employed by combining model estimates with satellite and surface measurements. The satellite data assimilation combined 36 x 36 km aerosol concentrations from CMAQ with aerosol optical depth (AOD) measured by MODIS and AERONET over the continental United States for 2002. Posterior model concentrations generated by the OI algorithm were compared with surface PM2.5 measurements to evaluate a number of possible data assimilation parameters, including model error, observation error, and temporal averaging assumptions. Evaluation was conducted separately for six geographic U.S. regions in 2002. Variability in model error and MODIS biases limited the effectiveness of a single data assimilation system for the entire continental domain. The best combinations of four settings and three averaging schemes led to a domain-averaged improvement in fractional error from 1.2 to 0.97 and from 0.99 to 0.89 at respective IMPROVE and STN monitoring sites. For 38% of OI results, MODIS OI degraded the forward model skill due to biases and outliers in MODIS AOD. Surface data assimilation combined 36 × 36 km aerosol concentrations from the CMAQ model with surface PM2.5 measurements over the continental United States for 2002. The model error covariance matrix was constructed by using the observational method. The observation error covariance matrix included site representation that scaled the observation error by land use (i.e. urban or rural locations). In theory, urban locations should have less effect on surrounding areas than rural sites, which can be controlled using site representation error. The annual evaluations showed substantial improvements in model performance with increases in the correlation coefficient from 0.36 (prior) to 0.76 (posterior), and decreases in the fractional error from 0.43 (prior) to 0.15 (posterior). In addition, the normalized mean error decreased from 0.36 (prior) to 0.13 (posterior), and the RMSE decreased from 5.39 µg m-3 (prior) to 2.32 µg m-3 (posterior). OI decreased model bias for both large spatial areas and point locations, and could be extended to more advanced data assimilation methods. The current work will be applied to a five year (2000-2004) CMAQ simulation aimed at improving aerosol model estimates. The posterior model concentrations will be used to inform exposure studies over the U.S. that relate aerosol exposure to mortality and morbidity rates. Future improvements for the OI techniques used in the current study will include combining both surface and satellite data to improve posterior model estimates. Satellite data have high spatial and temporal resolutions in comparison to surface measurements, which are scarce but more accurate than model estimates. The satellite data are subject to noise affected by location and season of retrieval. The implementation of OI to combine satellite and surface data sets has the potential to improve posterior model estimates for locations that have no direct measurements.
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Kaye, Stephen B
2009-04-01
To provide a scalar measure of refractive error, based on geometric lens power through principal, orthogonal and oblique meridians, that is not limited to the paraxial and sag height approximations. A function is derived to model sections through the principal meridian of a lens, followed by rotation of the section through orthogonal and oblique meridians. Average focal length is determined using the definition for the average of a function. Average univariate power in the principal meridian (including spherical aberration), can be computed from the average of a function over the angle of incidence as determined by the parameters of the given lens, or adequately computed from an integrated series function. Average power through orthogonal and oblique meridians, can be similarly determined using the derived formulae. The widely used computation for measuring refractive error, the spherical equivalent, introduces non-constant approximations, leading to a systematic bias. The equations proposed provide a good univariate representation of average lens power and are not subject to a systematic bias. They are particularly useful for the analysis of aggregate data, correlating with biological treatment variables and for developing analyses, which require a scalar equivalent representation of refractive power.
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Estimating 1970-99 average annual groundwater recharge in Wisconsin using streamflow data
Gebert, Warren A.; Walker, John F.; Kennedy, James L.
2011-01-01
Average annual recharge in Wisconsin for the period 1970-99 was estimated using streamflow data from U.S. Geological Survey continuous-record streamflow-gaging stations and partial-record sites. Partial-record sites have discharge measurements collected during low-flow conditions. The average annual base flow of a stream divided by the drainage area is a good approximation of the recharge rate; therefore, once average annual base flow is determined recharge can be calculated. Estimates of recharge for nearly 72 percent of the surface area of the State are provided. The results illustrate substantial spatial variability of recharge across the State, ranging from less than 1 inch to more than 12 inches per year. The average basin size for partial-record sites (50 square miles) was less than the average basin size for the gaging stations (305 square miles). Including results for smaller basins reveals a spatial variability that otherwise would be smoothed out using only estimates for larger basins. An error analysis indicates that the techniques used provide base flow estimates with standard errors ranging from 5.4 to 14 percent.
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Automated Quantification of Pneumothorax in CT
Do, Synho; Salvaggio, Kristen; Gupta, Supriya; Kalra, Mannudeep; Ali, Nabeel U.; Pien, Homer
2012-01-01
An automated, computer-aided diagnosis (CAD) algorithm for the quantification of pneumothoraces from Multidetector Computed Tomography (MDCT) images has been developed. Algorithm performance was evaluated through comparison to manual segmentation by expert radiologists. A combination of two-dimensional and three-dimensional processing techniques was incorporated to reduce required processing time by two-thirds (as compared to similar techniques). Volumetric measurements on relative pneumothorax size were obtained and the overall performance of the automated method shows an average error of just below 1%. PMID:23082091
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Bond, J.W.
1988-01-01
Data-compression codes offer the possibility of improving the thruput of existing communication systems in the near term. This study was undertaken to determine if data-compression codes could be utilized to provide message compression in a channel with up to a 0.10-bit error rate. The data-compression capabilities of codes were investigated by estimating the average number of bits-per-character required to transmit narrative files. The performance of the codes in a channel with errors (a noisy channel) was investigated in terms of the average numbers of characters-decoded-in-error and of characters-printed-in-error-per-bit-error. Results were obtained by encoding four narrative files, which were resident onmore » an IBM-PC and use a 58-character set. The study focused on Huffman codes and suffix/prefix comma-free codes. Other data-compression codes, in particular, block codes and some simple variants of block codes, are briefly discussed to place the study results in context. Comma-free codes were found to have the most-promising data compression because error propagation due to bit errors are limited to a few characters for these codes. A technique was found to identify a suffix/prefix comma-free code giving nearly the same data compressions as a Huffman code with much less error propagation than the Huffman codes. Greater data compression can be achieved through the use of this comma-free code word assignments based on conditioned probabilities of character occurrence.« less
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Quantifying Data Quality for Clinical Trials Using Electronic Data Capture
Nahm, Meredith L.; Pieper, Carl F.; Cunningham, Maureen M.
2008-01-01
Background Historically, only partial assessments of data quality have been performed in clinical trials, for which the most common method of measuring database error rates has been to compare the case report form (CRF) to database entries and count discrepancies. Importantly, errors arising from medical record abstraction and transcription are rarely evaluated as part of such quality assessments. Electronic Data Capture (EDC) technology has had a further impact, as paper CRFs typically leveraged for quality measurement are not used in EDC processes. Methods and Principal Findings The National Institute on Drug Abuse Treatment Clinical Trials Network has developed, implemented, and evaluated methodology for holistically assessing data quality on EDC trials. We characterize the average source-to-database error rate (14.3 errors per 10,000 fields) for the first year of use of the new evaluation method. This error rate was significantly lower than the average of published error rates for source-to-database audits, and was similar to CRF-to-database error rates reported in the published literature. We attribute this largely to an absence of medical record abstraction on the trials we examined, and to an outpatient setting characterized by less acute patient conditions. Conclusions Historically, medical record abstraction is the most significant source of error by an order of magnitude, and should be measured and managed during the course of clinical trials. Source-to-database error rates are highly dependent on the amount of structured data collection in the clinical setting and on the complexity of the medical record, dependencies that should be considered when developing data quality benchmarks. PMID:18725958
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Changes in the relation between snow station observations and basin scale snow water resources
NASA Astrophysics Data System (ADS)
Sexstone, G. A.; Penn, C. A.; Clow, D. W.; Moeser, D.; Liston, G. E.
2017-12-01
Snow monitoring stations that measure snow water equivalent or snow depth provide fundamental observations used for predicting water availability and flood risk in mountainous regions. In the western United States, snow station observations provided by the Natural Resources Conservation Service Snow Telemetry (SNOTEL) network are relied upon for forecasting spring and summer streamflow volume. Streamflow forecast accuracy has declined for many regions over the last several decades. Changes in snow accumulation and melt related to climate, land use, and forest cover are not accounted for in current forecasts, and are likely sources of error. Therefore, understanding and updating relations between snow station observations and basin scale snow water resources is crucial to improve accuracy of streamflow prediction. In this study, we investigated the representativeness of snow station observations when compared to simulated basin-wide snow water resources within the Rio Grande headwaters of Colorado. We used the combination of a process-based snow model (SnowModel), field-based measurements, and remote sensing observations to compare the spatiotemporal variability of simulated basin-wide snow accumulation and melt with that of SNOTEL station observations. Results indicated that observations are comparable to simulated basin-average winter precipitation but overestimate both the simulated basin-average snow water equivalent and snowmelt rate. Changes in the representation of snow station observations over time in the Rio Grande headwaters were also investigated and compared to observed streamflow and streamflow forecasting errors. Results from this study provide important insight in the context of non-stationarity for future water availability assessments and streamflow predictions.
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Triple collocation based merging of satellite soil moisture retrievals
USDA-ARS?s Scientific Manuscript database
We propose a method for merging soil moisture retrievals from space borne active and passive microwave instruments based on weighted averaging taking into account the error characteristics of the individual data sets. The merging scheme is parameterized using error variance estimates obtained from u...
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NASA Technical Reports Server (NTRS)
Mozer, F. S.
1976-01-01
A computer program simulated the spectrum which resulted when a radar signal was transmitted into the ionosphere for a finite time and received for an equal finite interval. The spectrum derived from this signal is statistical in nature because the signal is scattered from the ionosphere, which is statistical in nature. Many estimates of any property of the ionosphere can be made. Their average value will approach the average property of the ionosphere which is being measured. Due to the statistical nature of the spectrum itself, the estimators will vary about this average. The square root of the variance about this average is called the standard deviation, an estimate of the error which exists in any particular radar measurement. In order to determine the feasibility of the space shuttle radar, the magnitude of these errors for measurements of physical interest must be understood.
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Discrete distributed strain sensing of intelligent structures
NASA Technical Reports Server (NTRS)
Anderson, Mark S.; Crawley, Edward F.
1992-01-01
Techniques are developed for the design of discrete highly distributed sensor systems for use in intelligent structures. First the functional requirements for such a system are presented. Discrete spatially averaging strain sensors are then identified as satisfying the functional requirements. A variety of spatial weightings for spatially averaging sensors are examined, and their wave number characteristics are determined. Preferable spatial weightings are identified. Several numerical integration rules used to integrate such sensors in order to determine the global deflection of the structure are discussed. A numerical simulation is conducted using point and rectangular sensors mounted on a cantilevered beam under static loading. Gage factor and sensor position uncertainties are incorporated to assess the absolute error and standard deviation of the error in the estimated tip displacement found by numerically integrating the sensor outputs. An experiment is carried out using a statically loaded cantilevered beam with five point sensors. It is found that in most cases the actual experimental error is within one standard deviation of the absolute error as found in the numerical simulation.
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Ridge Polynomial Neural Network with Error Feedback for Time Series Forecasting
Ghazali, Rozaida; Herawan, Tutut
2016-01-01
Time series forecasting has gained much attention due to its many practical applications. Higher-order neural network with recurrent feedback is a powerful technique that has been used successfully for time series forecasting. It maintains fast learning and the ability to learn the dynamics of the time series over time. Network output feedback is the most common recurrent feedback for many recurrent neural network models. However, not much attention has been paid to the use of network error feedback instead of network output feedback. In this study, we propose a novel model, called Ridge Polynomial Neural Network with Error Feedback (RPNN-EF) that incorporates higher order terms, recurrence and error feedback. To evaluate the performance of RPNN-EF, we used four univariate time series with different forecasting horizons, namely star brightness, monthly smoothed sunspot numbers, daily Euro/Dollar exchange rate, and Mackey-Glass time-delay differential equation. We compared the forecasting performance of RPNN-EF with the ordinary Ridge Polynomial Neural Network (RPNN) and the Dynamic Ridge Polynomial Neural Network (DRPNN). Simulation results showed an average 23.34% improvement in Root Mean Square Error (RMSE) with respect to RPNN and an average 10.74% improvement with respect to DRPNN. That means that using network errors during training helps enhance the overall forecasting performance for the network. PMID:27959927
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Ridge Polynomial Neural Network with Error Feedback for Time Series Forecasting.
Waheeb, Waddah; Ghazali, Rozaida; Herawan, Tutut
2016-01-01
Time series forecasting has gained much attention due to its many practical applications. Higher-order neural network with recurrent feedback is a powerful technique that has been used successfully for time series forecasting. It maintains fast learning and the ability to learn the dynamics of the time series over time. Network output feedback is the most common recurrent feedback for many recurrent neural network models. However, not much attention has been paid to the use of network error feedback instead of network output feedback. In this study, we propose a novel model, called Ridge Polynomial Neural Network with Error Feedback (RPNN-EF) that incorporates higher order terms, recurrence and error feedback. To evaluate the performance of RPNN-EF, we used four univariate time series with different forecasting horizons, namely star brightness, monthly smoothed sunspot numbers, daily Euro/Dollar exchange rate, and Mackey-Glass time-delay differential equation. We compared the forecasting performance of RPNN-EF with the ordinary Ridge Polynomial Neural Network (RPNN) and the Dynamic Ridge Polynomial Neural Network (DRPNN). Simulation results showed an average 23.34% improvement in Root Mean Square Error (RMSE) with respect to RPNN and an average 10.74% improvement with respect to DRPNN. That means that using network errors during training helps enhance the overall forecasting performance for the network.
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Scientific Impacts of Wind Direction Errors
NASA Technical Reports Server (NTRS)
Liu, W. Timothy; Kim, Seung-Bum; Lee, Tong; Song, Y. Tony; Tang, Wen-Qing; Atlas, Robert
2004-01-01
An assessment on the scientific impact of random errors in wind direction (less than 45 deg) retrieved from space-based observations under weak wind (less than 7 m/s ) conditions was made. averages, and these weak winds cover most of the tropical, sub-tropical, and coastal oceans. Introduction of these errors in the semi-daily winds causes, on average, 5% changes of the yearly mean Ekman and Sverdrup volume transports computed directly from the winds, respectively. These poleward movements of water are the main mechanisms to redistribute heat from the warmer tropical region to the colder high- latitude regions, and they are the major manifestations of the ocean's function in modifying Earth's climate. Simulation by an ocean general circulation model shows that the wind errors introduce a 5% error in the meridional heat transport at tropical latitudes. The simulation also shows that the erroneous winds cause a pile-up of warm surface water in the eastern tropical Pacific, similar to the conditions during El Nino episode. Similar wind directional errors cause significant change in sea-surface temperature and sea-level patterns in coastal oceans in a coastal model simulation. Previous studies have shown that assimilation of scatterometer winds improves 3-5 day weather forecasts in the Southern Hemisphere. When directional information below 7 m/s was withheld, approximately 40% of the improvement was lost
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NASA Astrophysics Data System (ADS)
Ewan, B. C. R.; Ireland, S. N.
2000-12-01
Acoustic pyrometry uses the temperature dependence of sound speed in materials to measure temperature. This is normally achieved by measuring the transit time for a sound signal over a known path length and applying the material relation between temperature and velocity to extract an "average" temperature. Sources of error associated with the measurement of mean transit time are discussed in implementing the technique in gases, one of the principal causes being background noise in typical industrial environments. A number of transmitted signal and processing strategies which can be used in the area are examined and the expected error in mean transit time associated with each technique is quantified. Transmitted signals included pulses, pure frequencies, chirps, and pseudorandom binary sequences (prbs), while processing involves edge detection and correlation. Errors arise through the misinterpretation of the positions of edge arrival or correlation peaks due to instantaneous deviations associated with background noise and these become more severe as signal to noise amplitude ratios decrease. Population errors in the mean transit time are estimated for the different measurement strategies and it is concluded that PRBS combined with correlation can provide the lowest errors when operating in high noise environments. The operation of an instrument based on PRBS transmitted signals is described and test results under controlled noise conditions are presented. These confirm the value of the strategy and demonstrate that measurements can be made with signal to noise amplitude ratios down to 0.5.
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Multiple symbol partially coherent detection of MPSK
NASA Technical Reports Server (NTRS)
Simon, M. K.; Divsalar, D.
1992-01-01
It is shown that by using the known (or estimated) value of carrier tracking loop signal to noise ratio (SNR) in the decision metric, it is possible to improve the error probability performance of a partially coherent multiple phase-shift-keying (MPSK) system relative to that corresponding to the commonly used ideal coherent decision rule. Using a maximum-likeihood approach, an optimum decision metric is derived and shown to take the form of a weighted sum of the ideal coherent decision metric (i.e., correlation) and the noncoherent decision metric which is optimum for differential detection of MPSK. The performance of a receiver based on this optimum decision rule is derived and shown to provide continued improvement with increasing length of observation interval (data symbol sequence length). Unfortunately, increasing the observation length does not eliminate the error floor associated with the finite loop SNR. Nevertheless, in the limit of infinite observation length, the average error probability performance approaches the algebraic sum of the error floor and the performance of ideal coherent detection, i.e., at any error probability above the error floor, there is no degradation due to the partial coherence. It is shown that this limiting behavior is virtually achievable with practical size observation lengths. Furthermore, the performance is quite insensitive to mismatch between the estimate of loop SNR (e.g., obtained from measurement) fed to the decision metric and its true value. These results may be of use in low-cost Earth-orbiting or deep-space missions employing coded modulations.
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Muralikrishnan, B.; Blackburn, C.; Sawyer, D.; Phillips, S.; Bridges, R.
2010-01-01
We describe a method to estimate the scale errors in the horizontal angle encoder of a laser tracker in this paper. The method does not require expensive instrumentation such as a rotary stage or even a calibrated artifact. An uncalibrated but stable length is realized between two targets mounted on stands that are at tracker height. The tracker measures the distance between these two targets from different azimuthal positions (say, in intervals of 20° over 360°). Each target is measured in both front face and back face. Low order harmonic scale errors can be estimated from this data and may then be used to correct the encoder’s error map to improve the tracker’s angle measurement accuracy. We have demonstrated this for the second order harmonic in this paper. It is important to compensate for even order harmonics as their influence cannot be removed by averaging front face and back face measurements whereas odd orders can be removed by averaging. We tested six trackers from three different manufacturers. Two of those trackers are newer models introduced at the time of writing of this paper. For older trackers from two manufacturers, the length errors in a 7.75 m horizontal length placed 7 m away from a tracker were of the order of ± 65 μm before correcting the error map. They reduced to less than ± 25 μm after correcting the error map for second order scale errors. Newer trackers from the same manufacturers did not show this error. An older tracker from a third manufacturer also did not show this error. PMID:27134789
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SU-E-T-192: FMEA Severity Scores - Do We Really Know?
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tonigan, J; Johnson, J; Kry, S
2014-06-01
Purpose: Failure modes and effects analysis (FMEA) is a subjective risk mitigation technique that has not been applied to physics-specific quality management practices. There is a need for quantitative FMEA data as called for in the literature. This work focuses specifically on quantifying FMEA severity scores for physics components of IMRT delivery and comparing to subjective scores. Methods: Eleven physical failure modes (FMs) for head and neck IMRT dose calculation and delivery are examined near commonly accepted tolerance criteria levels. Phantom treatment planning studies and dosimetry measurements (requiring decommissioning in several cases) are performed to determine the magnitude of dosemore » delivery errors for the FMs (i.e., severity of the FM). Resultant quantitative severity scores are compared to FMEA scores obtained through an international survey and focus group studies. Results: Physical measurements for six FMs have resulted in significant PTV dose errors up to 4.3% as well as close to 1 mm significant distance-to-agreement error between PTV and OAR. Of the 129 survey responses, the vast majority of the responders used Varian machines with Pinnacle and Eclipse planning systems. The average years of experience was 17, yet familiarity with FMEA less than expected. Survey reports perception of dose delivery error magnitude varies widely, in some cases 50% difference in dose delivery error expected amongst respondents. Substantial variance is also seen for all FMs in occurrence, detectability, and severity scores assigned with average variance values of 5.5, 4.6, and 2.2, respectively. Survey shows for MLC positional FM(2mm) average of 7.6% dose error expected (range 0–50%) compared to 2% error seen in measurement. Analysis of ranking in survey, treatment planning studies, and quantitative value comparison will be presented. Conclusion: Resultant quantitative severity scores will expand the utility of FMEA for radiotherapy and verify accuracy of FMEA results compared to highly variable subjective scores.« less
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Ziegelwanger, Harald; Majdak, Piotr; Kreuzer, Wolfgang
2015-01-01
Head-related transfer functions (HRTFs) can be numerically calculated by applying the boundary element method on the geometry of a listener’s head and pinnae. The calculation results are defined by geometrical, numerical, and acoustical parameters like the microphone used in acoustic measurements. The scope of this study was to estimate requirements on the size and position of the microphone model and on the discretization of the boundary geometry as triangular polygon mesh for accurate sound localization. The evaluation involved the analysis of localization errors predicted by a sagittal-plane localization model, the comparison of equivalent head radii estimated by a time-of-arrival model, and the analysis of actual localization errors obtained in a sound-localization experiment. While the average edge length (AEL) of the mesh had a negligible effect on localization performance in the lateral dimension, the localization performance in sagittal planes, however, degraded for larger AELs with the geometrical error as dominant factor. A microphone position at an arbitrary position at the entrance of the ear canal, a microphone size of 1 mm radius, and a mesh with 1 mm AEL yielded a localization performance similar to or better than observed with acoustically measured HRTFs. PMID:26233020
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NASA Astrophysics Data System (ADS)
Maheshwera Reddy Paturi, Uma; Devarasetti, Harish; Abimbola Fadare, David; Reddy Narala, Suresh Kumar
2018-04-01
In the present paper, the artificial neural network (ANN) and response surface methodology (RSM) are used in modeling of surface roughness in WS2 (tungsten disulphide) solid lubricant assisted minimal quantity lubrication (MQL) machining. The real time MQL turning of Inconel 718 experimental data considered in this paper was available in the literature [1]. In ANN modeling, performance parameters such as mean square error (MSE), mean absolute percentage error (MAPE) and average error in prediction (AEP) for the experimental data were determined based on Levenberg–Marquardt (LM) feed forward back propagation training algorithm with tansig as transfer function. The MATLAB tool box has been utilized in training and testing of neural network model. Neural network model with three input neurons, one hidden layer with five neurons and one output neuron (3-5-1 architecture) is found to be most confidence and optimal. The coefficient of determination (R2) for both the ANN and RSM model were seen to be 0.998 and 0.982 respectively. The surface roughness predictions from ANN and RSM model were related with experimentally measured values and found to be in good agreement with each other. However, the prediction efficacy of ANN model is relatively high when compared with RSM model predictions.
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Application Bayesian Model Averaging method for ensemble system for Poland
NASA Astrophysics Data System (ADS)
Guzikowski, Jakub; Czerwinska, Agnieszka
2014-05-01
The aim of the project is to evaluate methods for generating numerical ensemble weather prediction using a meteorological data from The Weather Research & Forecasting Model and calibrating this data by means of Bayesian Model Averaging (WRF BMA) approach. We are constructing height resolution short range ensemble forecasts using meteorological data (temperature) generated by nine WRF's models. WRF models have 35 vertical levels and 2.5 km x 2.5 km horizontal resolution. The main emphasis is that the used ensemble members has a different parameterization of the physical phenomena occurring in the boundary layer. To calibrate an ensemble forecast we use Bayesian Model Averaging (BMA) approach. The BMA predictive Probability Density Function (PDF) is a weighted average of predictive PDFs associated with each individual ensemble member, with weights that reflect the member's relative skill. For test we chose a case with heat wave and convective weather conditions in Poland area from 23th July to 1st August 2013. From 23th July to 29th July 2013 temperature oscillated below or above 30 Celsius degree in many meteorology stations and new temperature records were added. During this time the growth of the hospitalized patients with cardiovascular system problems was registered. On 29th July 2013 an advection of moist tropical air masses was recorded in the area of Poland causes strong convection event with mesoscale convection system (MCS). MCS caused local flooding, damage to the transport infrastructure, destroyed buildings, trees and injuries and direct threat of life. Comparison of the meteorological data from ensemble system with the data recorded on 74 weather stations localized in Poland is made. We prepare a set of the model - observations pairs. Then, the obtained data from single ensemble members and median from WRF BMA system are evaluated on the basis of the deterministic statistical error Root Mean Square Error (RMSE), Mean Absolute Error (MAE). To evaluation probabilistic data The Brier Score (BS) and Continuous Ranked Probability Score (CRPS) were used. Finally comparison between BMA calibrated data and data from ensemble members will be displayed.
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NASA Astrophysics Data System (ADS)
Castiglioni, S.; Toth, E.
2009-04-01
In the calibration procedure of continuously-simulating models, the hydrologist has to choose which part of the observed hydrograph is most important to fit, either implicitly, through the visual agreement in manual calibration, or explicitly, through the choice of the objective function(s). Changing the objective functions it is in fact possible to emphasise different kind of errors, giving them more weight in the calibration phase. The objective functions used for calibrating hydrological models are generally of the quadratic type (mean squared error, correlation coefficient, coefficient of determination, etc) and are therefore oversensitive to high and extreme error values, that typically correspond to high and extreme streamflow values. This is appropriate when, like in the majority of streamflow forecasting applications, the focus is on the ability to reproduce potentially dangerous flood events; on the contrary, if the aim of the modelling is the reproduction of low and average flows, as it is the case in water resource management problems, this may result in a deterioration of the forecasting performance. This contribution presents the results of a series of automatic calibration experiments of a continuously-simulating rainfall-runoff model applied over several real-world case-studies, where the objective function is chosen so to highlight the fit of average and low flows. In this work a simple conceptual model will be used, of the lumped type, with a relatively low number of parameters to be calibrated. The experiments will be carried out for a set of case-study watersheds in Central Italy, covering an extremely wide range of geo-morphologic conditions and for whom at least five years of contemporary daily series of streamflow, precipitation and evapotranspiration estimates are available. Different objective functions will be tested in calibration and the results will be compared, over validation data, against those obtained with traditional squared functions. A companion work presents the results, over the same case-study watersheds and observation periods, of a system-theoretic model, again calibrated for reproducing average and low streamflows.
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Toward developing a standardized Arabic continuous text reading chart.
Alabdulkader, Balsam; Leat, Susan Jennifer
Near visual acuity is an essential measurement during an oculo-visual assessment. Short duration continuous text reading charts measure reading acuity and other aspects of reading performance. There is no standardized version of such chart in Arabic. The aim of this study is to create sentences of equal readability to use in the development of a standardized Arabic continuous text reading chart. Initially, 109 Arabic pairs of sentences were created for use in constructing a chart with similar layout to the Colenbrander chart. They were created to have the same grade level of difficulty and physical length. Fifty-three adults and sixteen children were recruited to validate the sentences. Reading speed in correct words per minute (CWPM) and standard length words per minute (SLWPM) was measured and errors were counted. Criteria based on reading speed and errors made in each sentence pair were used to exclude sentence pairs with more outlying characteristics, and to select the final group of sentence pairs. Forty-five sentence pairs were selected according to the elimination criteria. For adults, the average reading speed for the final sentences was 166 CWPM and 187 SLWPM and the average number of errors per sentence pair was 0.21. Childrens' average reading speed for the final group of sentences was 61 CWPM and 72 SLWPM. Their average error rate was 1.71. The reliability analysis showed that the final 45 sentence pairs are highly comparable. They will be used in constructing an Arabic short duration continuous text reading chart. Copyright © 2016 Spanish General Council of Optometry. Published by Elsevier España, S.L.U. All rights reserved.
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Astrometric observations of visual binaries using 26-inch refractor during 2007-2014 at Pulkovo
NASA Astrophysics Data System (ADS)
Izmailov, I. S.; Roshchina, E. A.
2016-04-01
We present the results of 15184 astrometric observations of 322 visual binaries carried out in 2007-2014 at Pulkovo observatory. In 2007, the 26-inch refractor ( F = 10413 mm, D = 65 cm) was equipped with the CCD camera FLI ProLine 09000 (FOV 12' × 12', 3056 × 3056 pixels, 0.238 arcsec pixel-1). Telescope automation and weather monitoring system installation allowed us to increase the number of observations significantly. Visual binary and multiple systems with an angular distance in the interval 1."1-78."6 with 7."3 on average were included in the observing program. The results were studied in detail for systematic errors using calibration star pairs. There was no detected dependence of errors on temperature, pressure, and hour angle. The dependence of the 26-inch refractor's scale on temperature was taken into account in calculations. The accuracy of measurement of a single CCD image is in the range of 0."0005 to 0."289, 0."021 on average along both coordinates. Mean errors in annual average values of angular distance and position angle are equal to 0."005 and 0.°04 respectively. The results are available here http://izmccd.puldb.ru/vds.htmand in the Strasbourg Astronomical Data Center (CDS). In the catalog, the separations and position angles per night of observation and annual average as well as errors for all the values and standard deviations of a single observation are presented. We present the results of comparison of 50 pairs of stars with known orbital solutions with ephemerides.
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Berndl, K; von Cranach, M; Grüsser, O J
1986-01-01
The perception and recognition of faces, mimic expression and gestures were investigated in normal subjects and schizophrenic patients by means of a movie test described in a previous report (Berndl et al. 1986). The error scores were compared with results from a semi-quantitative evaluation of psychopathological symptoms and with some data from the case histories. The overall error scores found in the three groups of schizophrenic patients (paranoic, hebephrenic, schizo-affective) were significantly increased (7-fold) over those of normals. No significant difference in the distribution of the error scores in the three different patient groups was found. In 10 different sub-tests following the movie the deficiencies found in the schizophrenic patients were analysed in detail. The error score for the averbal test was on average higher in paranoic patients than in the two other groups of patients, while the opposite was true for the error scores found in the verbal tests. Age and sex had some impact on the test results. In normals, female subjects were somewhat better than male. In schizophrenic patients the reverse was true. Thus female patients were more affected by the disease than male patients with respect to the task performance. The correlation between duration of the disease and error score was small; less than 10% of the error scores could be attributed to factors related to the duration of illness. Evaluation of psychopathological symptoms indicated that the stronger the schizophrenic defect, the higher the error score, but again this relationship was responsible for not more than 10% of the errors. The estimated degree of acute psychosis and overall sum of psychopathological abnormalities as scored in a semi-quantitative exploration did not correlate with the error score, but with each other. Similarly, treatment with psychopharmaceuticals, previous misuse of drugs or of alcohol had practically no effect on the outcome of the test data. The analysis of performance and test data of schizophrenic patients indicated that our findings are most likely not due to a "non-specific" impairment of cognitive function in schizophrenia, but point to a fairly selective defect in elementary cognitive visual functions necessary for averbal social communication. Some possible explanations of the data are discussed in relation to neuropsychological and neurophysiological findings on "face-specific" cortical areas located in the primate temporal lobe.
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Shahly, Victoria; Berglund, Patricia A; Coulouvrat, Catherine; Fitzgerald, Timothy; Hajak, Goeran; Roth, Thomas; Shillington, Alicia C; Stephenson, Judith J; Walsh, James K; Kessler, Ronald C
2012-10-01
Insomnia is a common and seriously impairing condition that often goes unrecognized. To examine associations of broadly defined insomnia (ie, meeting inclusion criteria for a diagnosis from International Statistical Classification of Diseases, 10th Revision, DSM-IV, or Research Diagnostic Criteria/International Classification of Sleep Disorders, Second Edition) with costly workplace accidents and errors after excluding other chronic conditions among workers in the America Insomnia Survey (AIS). A national cross-sectional telephone survey (65.0% cooperation rate) of commercially insured health plan members selected from the more than 34 million in the HealthCore Integrated Research Database. Four thousand nine hundred ninety-one employed AIS respondents. Costly workplace accidents or errors in the 12 months before the AIS interview were assessed with one question about workplace accidents "that either caused damage or work disruption with a value of $500 or more" and another about other mistakes "that cost your company $500 or more." Current insomnia with duration of at least 12 months was assessed with the Brief Insomnia Questionnaire, a validated (area under the receiver operating characteristic curve, 0.86 compared with diagnoses based on blinded clinical reappraisal interviews), fully structured diagnostic interview. Eighteen other chronic conditions were assessed with medical/pharmacy claims records and validated self-report scales. Insomnia had a significant odds ratio with workplace accidents and/or errors controlled for other chronic conditions (1.4). The odds ratio did not vary significantly with respondent age, sex, educational level, or comorbidity. The average costs of insomnia-related accidents and errors ($32 062) were significantly higher than those of other accidents and errors ($21 914). Simulations estimated that insomnia was associated with 7.2% of all costly workplace accidents and errors and 23.7% of all the costs of these incidents. These proportions are higher than for any other chronic condition, with annualized US population projections of 274 000 costly insomnia-related workplace accidents and errors having a combined value of US $31.1 billion. Effectiveness trials are needed to determine whether expanded screening, outreach, and treatment of workers with insomnia would yield a positive return on investment for employers.
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Kurrant, Douglas; Fear, Elise; Baran, Anastasia; LoVetri, Joe
2017-12-01
The authors have developed a method to combine a patient-specific map of tissue structure and average dielectric properties with microwave tomography. The patient-specific map is acquired with radar-based techniques and serves as prior information for microwave tomography. The impact that the degree of structural detail included in this prior information has on image quality was reported in a previous investigation. The aim of the present study is to extend this previous work by identifying and quantifying the impact that errors in the prior information have on image quality, including the reconstruction of internal structures and lesions embedded in fibroglandular tissue. This study also extends the work of others reported in literature by emulating a clinical setting with a set of experiments that incorporate heterogeneity into both the breast interior and glandular region, as well as prior information related to both fat and glandular structures. Patient-specific structural information is acquired using radar-based methods that form a regional map of the breast. Errors are introduced to create a discrepancy in the geometry and electrical properties between the regional map and the model used to generate the data. This permits the impact that errors in the prior information have on image quality to be evaluated. Image quality is quantitatively assessed by measuring the ability of the algorithm to reconstruct both internal structures and lesions embedded in fibroglandular tissue. The study is conducted using both 2D and 3D numerical breast models constructed from MRI scans. The reconstruction results demonstrate robustness of the method relative to errors in the dielectric properties of the background regional map, and to misalignment errors. These errors do not significantly influence the reconstruction accuracy of the underlying structures, or the ability of the algorithm to reconstruct malignant tissue. Although misalignment errors do not significantly impact the quality of the reconstructed fat and glandular structures for the 3D scenarios, the dielectric properties are reconstructed less accurately within the glandular structure for these cases relative to the 2D cases. However, general agreement between the 2D and 3D results was found. A key contribution of this paper is the detailed analysis of the impact of prior information errors on the reconstruction accuracy and ability to detect tumors. The results support the utility of acquiring patient-specific information with radar-based techniques and incorporating this information into MWT. The method is robust to errors in the dielectric properties of the background regional map, and to misalignment errors. Completion of this analysis is an important step toward developing the method into a practical diagnostic tool. © 2017 American Association of Physicists in Medicine.
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Derivation and precision of mean field electrodynamics with mesoscale fluctuations
NASA Astrophysics Data System (ADS)
Zhou, Hongzhe; Blackman, Eric G.
2018-06-01
Mean field electrodynamics (MFE) facilitates practical modelling of secular, large scale properties of astrophysical or laboratory systems with fluctuations. Practitioners commonly assume wide scale separation between mean and fluctuating quantities, to justify equality of ensemble and spatial or temporal averages. Often however, real systems do not exhibit such scale separation. This raises two questions: (I) What are the appropriate generalized equations of MFE in the presence of mesoscale fluctuations? (II) How precise are theoretical predictions from MFE? We address both by first deriving the equations of MFE for different types of averaging, along with mesoscale correction terms that depend on the ratio of averaging scale to variation scale of the mean. We then show that even if these terms are small, predictions of MFE can still have a significant precision error. This error has an intrinsic contribution from the dynamo input parameters and a filtering contribution from differences in the way observations and theory are projected through the measurement kernel. Minimizing the sum of these contributions can produce an optimal scale of averaging that makes the theory maximally precise. The precision error is important to quantify when comparing to observations because it quantifies the resolution of predictive power. We exemplify these principles for galactic dynamos, comment on broader implications, and identify possibilities for further work.
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Fitting a function to time-dependent ensemble averaged data.
Fogelmark, Karl; Lomholt, Michael A; Irbäck, Anders; Ambjörnsson, Tobias
2018-05-03
Time-dependent ensemble averages, i.e., trajectory-based averages of some observable, are of importance in many fields of science. A crucial objective when interpreting such data is to fit these averages (for instance, squared displacements) with a function and extract parameters (such as diffusion constants). A commonly overlooked challenge in such function fitting procedures is that fluctuations around mean values, by construction, exhibit temporal correlations. We show that the only available general purpose function fitting methods, correlated chi-square method and the weighted least squares method (which neglects correlation), fail at either robust parameter estimation or accurate error estimation. We remedy this by deriving a new closed-form error estimation formula for weighted least square fitting. The new formula uses the full covariance matrix, i.e., rigorously includes temporal correlations, but is free of the robustness issues, inherent to the correlated chi-square method. We demonstrate its accuracy in four examples of importance in many fields: Brownian motion, damped harmonic oscillation, fractional Brownian motion and continuous time random walks. We also successfully apply our method, weighted least squares including correlation in error estimation (WLS-ICE), to particle tracking data. The WLS-ICE method is applicable to arbitrary fit functions, and we provide a publically available WLS-ICE software.
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Metainference: A Bayesian inference method for heterogeneous systems.
Bonomi, Massimiliano; Camilloni, Carlo; Cavalli, Andrea; Vendruscolo, Michele
2016-01-01
Modeling a complex system is almost invariably a challenging task. The incorporation of experimental observations can be used to improve the quality of a model and thus to obtain better predictions about the behavior of the corresponding system. This approach, however, is affected by a variety of different errors, especially when a system simultaneously populates an ensemble of different states and experimental data are measured as averages over such states. To address this problem, we present a Bayesian inference method, called "metainference," that is able to deal with errors in experimental measurements and with experimental measurements averaged over multiple states. To achieve this goal, metainference models a finite sample of the distribution of models using a replica approach, in the spirit of the replica-averaging modeling based on the maximum entropy principle. To illustrate the method, we present its application to a heterogeneous model system and to the determination of an ensemble of structures corresponding to the thermal fluctuations of a protein molecule. Metainference thus provides an approach to modeling complex systems with heterogeneous components and interconverting between different states by taking into account all possible sources of errors.
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NASA Astrophysics Data System (ADS)
Braman, Kalen; Raman, Venkat
2011-11-01
A novel direct numerical simulation (DNS) based a posteriori technique has been developed to investigate scalar transport modeling error. The methodology is used to test Reynolds-averaged Navier-Stokes turbulent scalar flux models for compressible boundary layer flows. Time-averaged DNS velocity and turbulence fields provide the information necessary to evolve the time-averaged scalar transport equation without requiring the use of turbulence modeling. With this technique, passive dispersion of a scalar from a boundary layer surface in a supersonic flow is studied with scalar flux modeling error isolated from any flowfield modeling errors. Several different scalar flux models are used. It is seen that the simple gradient diffusion model overpredicts scalar dispersion, while anisotropic scalar flux models underpredict dispersion. Further, the use of more complex models does not necessarily guarantee an increase in predictive accuracy, indicating that key physics is missing from existing models. Using comparisons of both a priori and a posteriori scalar flux evaluations with DNS data, the main modeling shortcomings are identified. Results will be presented for different boundary layer conditions.
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An Adaptive 6-DOF Tracking Method by Hybrid Sensing for Ultrasonic Endoscopes
Du, Chengyang; Chen, Xiaodong; Wang, Yi; Li, Junwei; Yu, Daoyin
2014-01-01
In this paper, a novel hybrid sensing method for tracking an ultrasonic endoscope within the gastrointestinal (GI) track is presented, and the prototype of the tracking system is also developed. We implement 6-DOF localization by sensing integration and information fusion. On the hardware level, a tri-axis gyroscope and accelerometer, and a magnetic angular rate and gravity (MARG) sensor array are attached at the end of endoscopes, and three symmetric cylindrical coils are placed around patients' abdomens. On the algorithm level, an adaptive fast quaternion convergence (AFQC) algorithm is introduced to determine the orientation by fusing inertial/magnetic measurements, in which the effects of magnetic disturbance and acceleration are estimated to gain an adaptive convergence output. A simplified electro-magnetic tracking (SEMT) algorithm for dimensional position is also implemented, which can easily integrate the AFQC's results and magnetic measurements. Subsequently, the average position error is under 0.3 cm by reasonable setting, and the average orientation error is 1° without noise. If magnetic disturbance or acceleration exists, the average orientation error can be controlled to less than 3.5°. PMID:24915179
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On the timing problem in optical PPM communications.
NASA Technical Reports Server (NTRS)
Gagliardi, R. M.
1971-01-01
Investigation of the effects of imperfect timing in a direct-detection (noncoherent) optical system using pulse-position-modulation bits. Special emphasis is placed on specification of timing accuracy, and an examination of system degradation when this accuracy is not attained. Bit error probabilities are shown as a function of timing errors, from which average error probabilities can be computed for specific synchronization methods. Of significant importance is shown to be the presence of a residual, or irreducible error probability, due entirely to the timing system, that cannot be overcome by the data channel.
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Hui, Shisheng; Chen, Lizhang; Liu, Fuqiang; Ouyang, Yanhao
2015-12-01
To establish multiple seasonal autoregressive integrated moving average model(ARIMA) according to mumps disease incidence in Hunan province, and to predict the mumps incidence from May 2015 to April 2016 in Hunan province by the model. The data were downloaded from "Disease Surveillance Information Reporting Management System" in China Information System for Disease Control and Prevention. The monthly incidence of mumps in Hunan province was collected from January 2004 to April 2015 according to the onset date, including clinical diagnosis and laboratory confirmed cases. The predictive analysis method was the ARIMA model in SPSS 18.0 software, the ARIMA model was established on the monthly incidence of mumps from January 2004 to April 2014, and the date from May 2014 to April 2015 was used as the testing sample, Box-Ljung Q test was used to test the residual of the selected model. Finally, the monthly incidence of mumps from May 2015 to April 2016 was predicted by the model. The peak months of the mumps incidence were May to July every year, and the secondary peak months were November to January of the following year, during January 2004 to April 2014 in Hunan province. After the data sequence was handled by smooth sequence, model identification, establishment and diagnosis, the ARIMA(2,1,1) × (0,1,1)(12) was established, Box-Ljung Q test found, Q=8.40, P=0.868, the residual sequence was white noise, the established model to the data information extraction was complete, the model was reasonable. The R(2) value of the model fitting degree was 0.871, and the value of BIC was -1.646, while the average absolute error of the predicted value and the actual value was 0.025/100 000, the average relative error was 13.004%. The relative error of the model for the prediction of the mumps incidence in Hunan province was small, and the predicting results were reliable. Using the ARIMA(2,1,1) ×(0,1,1)(12) model to predict the mumps incidence from April 2016 to May 2015 in Hunan province, the peak months of the mumps incidence were May to July, and the secondary peak months were November to January of the following year, the incidence of the peak month was close to the same period. The ARIMA(2,1,1)×(0,1,1)(12) model is well fitted the trend of the mumps disease incidence in Hunan province, it has some practical value for the prevention and control of the disease.
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Polarization-basis tracking scheme for quantum key distribution using revealed sifted key bits.
Ding, Yu-Yang; Chen, Wei; Chen, Hua; Wang, Chao; Li, Ya-Ping; Wang, Shuang; Yin, Zhen-Qiang; Guo, Guang-Can; Han, Zheng-Fu
2017-03-15
The calibration of the polarization basis between the transmitter and receiver is an important task in quantum key distribution. A continuously working polarization-basis tracking scheme (PBTS) will effectively promote the efficiency of the system and reduce the potential security risk when switching between the transmission and calibration modes. Here, we proposed a single-photon level continuously working PBTS using only sifted key bits revealed during an error correction procedure, without introducing additional reference light or interrupting the transmission of quantum signals. We applied the scheme to a polarization-encoding BB84 QKD system in a 50 km fiber channel, and obtained an average quantum bit error rate (QBER) of 2.32% and a standard derivation of 0.87% during 24 h of continuous operation. The stable and relatively low QBER validates the effectiveness of the scheme.
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Cost-effectiveness of the stream-gaging program in Nebraska
Engel, G.B.; Wahl, K.L.; Boohar, J.A.
1984-01-01
This report documents the results of a study of the cost-effectiveness of the streamflow information program in Nebraska. Presently, 145 continuous surface-water stations are operated in Nebraska on a budget of $908,500. Data uses and funding sources are identified for each of the 145 stations. Data from most stations have multiple uses. All stations have sufficient justification for continuation, but two stations primarily are used in short-term research studies; their continued operation needs to be evaluated when the research studies end. The present measurement frequency produces an average standard error for instantaneous discharges of about 12 percent, including periods when stage data are missing. Altering the travel routes and the measurement frequency will allow a reduction in standard error of about 1 percent with the present budget. Standard error could be reduced to about 8 percent if lost record could be eliminated. A minimum budget of $822,000 is required to operate the present network, but operations at that funding level would result in an increase in standard error to about 16 percent. The maximum budget analyzed was $1,363,000, which would result in an average standard error of 6 percent. (USGS)
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Reliability and Validity Assessment of a Linear Position Transducer
Garnacho-Castaño, Manuel V.; López-Lastra, Silvia; Maté-Muñoz, José L.
2015-01-01
The objectives of the study were to determine the validity and reliability of peak velocity (PV), average velocity (AV), peak power (PP) and average power (AP) measurements were made using a linear position transducer. Validity was assessed by comparing measurements simultaneously obtained using the Tendo Weightlifting Analyzer Systemi and T-Force Dynamic Measurement Systemr (Ergotech, Murcia, Spain) during two resistance exercises, bench press (BP) and full back squat (BS), performed by 71 trained male subjects. For the reliability study, a further 32 men completed both lifts using the Tendo Weightlifting Analyzer Systemz in two identical testing sessions one week apart (session 1 vs. session 2). Intraclass correlation coefficients (ICCs) indicating the validity of the Tendo Weightlifting Analyzer Systemi were high, with values ranging from 0.853 to 0.989. Systematic biases and random errors were low to moderate for almost all variables, being higher in the case of PP (bias ±157.56 W; error ±131.84 W). Proportional biases were identified for almost all variables. Test-retest reliability was strong with ICCs ranging from 0.922 to 0.988. Reliability results also showed minimal systematic biases and random errors, which were only significant for PP (bias -19.19 W; error ±67.57 W). Only PV recorded in the BS showed no significant proportional bias. The Tendo Weightlifting Analyzer Systemi emerged as a reliable system for measuring movement velocity and estimating power in resistance exercises. The low biases and random errors observed here (mainly AV, AP) make this device a useful tool for monitoring resistance training. Key points This study determined the validity and reliability of peak velocity, average velocity, peak power and average power measurements made using a linear position transducer The Tendo Weight-lifting Analyzer Systemi emerged as a reliable system for measuring movement velocity and power. PMID:25729300
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Lee, It Ee; Ghassemlooy, Zabih; Ng, Wai Pang; Khalighi, Mohammad-Ali; Liaw, Shien-Kuei
2016-01-01
Joint effects of aperture averaging and beam width on the performance of free-space optical communication links, under the impairments of atmospheric loss, turbulence, and pointing errors (PEs), are investigated from an information theory perspective. The propagation of a spatially partially coherent Gaussian-beam wave through a random turbulent medium is characterized, taking into account the diverging and focusing properties of the optical beam as well as the scintillation and beam wander effects. Results show that a noticeable improvement in the average channel capacity can be achieved with an enlarged receiver aperture in the moderate-to-strong turbulence regime, even without knowledge of the channel state information. In particular, it is observed that the optimum beam width can be reduced to improve the channel capacity, albeit the presence of scintillation and PEs, given that either one or both of these adverse effects are least dominant. We show that, under strong turbulence conditions, the beam width increases linearly with the Rytov variance for a relatively smaller PE loss but changes exponentially with steeper increments for higher PE losses. Our findings conclude that the optimal beam width is dependent on the combined effects of turbulence and PEs, and this parameter should be adjusted according to the varying atmospheric channel conditions. Therefore, we demonstrate that the maximum channel capacity is best achieved through the introduction of a larger receiver aperture and a beam-width optimization technique.
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A real-time freehand ultrasound calibration system with automatic accuracy feedback and control.
Chen, Thomas Kuiran; Thurston, Adrian D; Ellis, Randy E; Abolmaesumi, Purang
2009-01-01
This article describes a fully automatic, real-time, freehand ultrasound calibration system. The system was designed to be simple and sterilizable, intended for operating-room usage. The calibration system employed an automatic-error-retrieval and accuracy-control mechanism based on a set of ground-truth data. Extensive validations were conducted on a data set of 10,000 images in 50 independent calibration trials to thoroughly investigate the accuracy, robustness, and performance of the calibration system. On average, the calibration accuracy (measured in three-dimensional reconstruction error against a known ground truth) of all 50 trials was 0.66 mm. In addition, the calibration errors converged to submillimeter in 98% of all trials within 12.5 s on average. Overall, the calibration system was able to consistently, efficiently and robustly achieve high calibration accuracy with real-time performance.
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Assessing the Online Social Environment for Surveillance of Obesity Prevalence
Chunara, Rumi; Bouton, Lindsay; Ayers, John W.; Brownstein, John S.
2013-01-01
Background Understanding the social environmental around obesity has been limited by available data. One promising approach used to bridge similar gaps elsewhere is to use passively generated digital data. Purpose This article explores the relationship between online social environment via web-based social networks and population obesity prevalence. Methods We performed a cross-sectional study using linear regression and cross validation to measure the relationship and predictive performance of user interests on the online social network Facebook to obesity prevalence in metros across the United States of America (USA) and neighborhoods within New York City (NYC). The outcomes, proportion of obese and/or overweight population in USA metros and NYC neighborhoods, were obtained via the Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance and NYC EpiQuery systems. Predictors were geographically specific proportion of users with activity-related and sedentary-related interests on Facebook. Results Higher proportion of the population with activity-related interests on Facebook was associated with a significant 12.0% (95% Confidence Interval (CI) 11.9 to 12.1) lower predicted prevalence of obese and/or overweight people across USA metros and 7.2% (95% CI: 6.8 to 7.7) across NYC neighborhoods. Conversely, greater proportion of the population with interest in television was associated with higher prevalence of obese and/or overweight people of 3.9% (95% CI: 3.7 to 4.0) (USA) and 27.5% (95% CI: 27.1 to 27.9, significant) (NYC). For activity-interests and national obesity outcomes, the average root mean square prediction error from 10-fold cross validation was comparable to the average root mean square error of a model developed using the entire data set. Conclusions Activity-related interests across the USA and sedentary-related interests across NYC were significantly associated with obesity prevalence. Further research is needed to understand how the online social environment relates to health outcomes and how it can be used to identify or target interventions. PMID:23637820
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A Quantum Theoretical Explanation for Probability Judgment Errors
ERIC Educational Resources Information Center
Busemeyer, Jerome R.; Pothos, Emmanuel M.; Franco, Riccardo; Trueblood, Jennifer S.
2011-01-01
A quantum probability model is introduced and used to explain human probability judgment errors including the conjunction and disjunction fallacies, averaging effects, unpacking effects, and order effects on inference. On the one hand, quantum theory is similar to other categorization and memory models of cognition in that it relies on vector…
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NASA Technical Reports Server (NTRS)
Baumeister, K. J.; Papell, S. S.
1973-01-01
General formulas are derived for determining gage averaging errors of strip-type heat flux meters used in the measurement of one-dimensional heat flux distributions. In addition, a correction procedure is presented which allows a better estimate for the true value of the local heat flux. As an example of the technique, the formulas are applied to the cases of heat transfer to air slot jets impinging on flat and concave surfaces. It is shown that for many practical problems, the use of very small heat flux gages is often unnecessary.
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Paixão, Fernanda; Silva, Wilkens Aurélio Buarque e; Silva, Frederico Andrade e; Ramos, Guilherme da Gama; Cruz, Mônica Vieira de Jesus
2007-01-01
The centric relation is a mandibular position that determines a balance relation among the temporomandibular joints, the chew muscles and the occlusion. This position makes possible to the dentist to plan and to execute oral rehabilitation respecting the physiological principles of the stomatognathic system. The aim of this study was to investigate the reproducibility of centric relation records obtained using two techniques: Dawson’s Bilateral Manipulation and Gysi’s Gothic Arch Tracing. Twenty volunteers (14 females and 6 males) with no dental loss, presenting occlusal contacts according to those described in Angle’s I classification and without signs and symptoms of temporomandibular disorders were selected. All volunteers were submitted five times with a 1-week interval, always in the same schedule, to the Dawson’s Bilateral Manipulation and to the Gysi’s Gothic Arch Tracing with aid of an intraoral apparatus. The average standard error of each technique was calculated (Bilateral Manipulation 0.94 and Gothic Arch Tracing 0.27). Shapiro-Wilk test was applied and the results allowed application of Student’s t-test (sampling error of 5%). The techniques showed different degrees of variability. The Gysi’s Gothic Arch Tracing was found to be more accurate than the Bilateral Manipulation in reproducing the centric relation records. PMID:19089144
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Paech, S.J.; Mecikalski, J.R.; Sumner, D.M.; Pathak, C.S.; Wu, Q.; Islam, S.; Sangoyomi, T.
2009-01-01
Estimates of incoming solar radiation (insolation) from Geostationary Operational Environmental Satellite observations have been produced for the state of Florida over a 10-year period (1995-2004). These insolation estimates were developed into well-calibrated half-hourly and daily integrated solar insolation fields over the state at 2 km resolution, in addition to a 2-week running minimum surface albedo product. Model results of the daily integrated insolation were compared with ground-based pyranometers, and as a result, the entire dataset was calibrated. This calibration was accomplished through a three-step process: (1) comparison with ground-based pyranometer measurements on clear (noncloudy) reference days, (2) correcting for a bias related to cloudiness, and (3) deriving a monthly bias correction factor. Precalibration results indicated good model performance, with a station-averaged model error of 2.2 MJ m-2/day (13%). Calibration reduced errors to 1.7 MJ m -2/day (10%), and also removed temporal-related, seasonal-related, and satellite sensor-related biases. The calibrated insolation dataset will subsequently be used by state of Florida Water Management Districts to produce statewide, 2-km resolution maps of estimated daily reference and potential evapotranspiration for water management-related activities. ?? 2009 American Water Resources Association.
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NASA Astrophysics Data System (ADS)
Tuozzolo, S.; Frasson, R. P. M.; Durand, M. T.
2017-12-01
We analyze a multi-temporal dataset of in-situ and airborne water surface measurements from the March 2015 AirSWOT field campaign on the Willamette River in Western Oregon, which included six days of AirSWOT flights over a 75km stretch of the river. We examine systematic errors associated with dark water and layover effects in the AirSWOT dataset, and test the efficacies of different filtering and spatial averaging techniques at reconstructing the water surface profile. Finally, we generate a spatially-averaged time-series of water surface elevation and water surface slope. These AirSWOT-derived reach-averaged values are ingested in a prospective SWOT discharge algorithm to assess its performance on SWOT-like data collected from a borderline SWOT-measurable river (mean width = 90m).
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Measurements of Aperture Averaging on Bit-Error-Rate
NASA Technical Reports Server (NTRS)
Bastin, Gary L.; Andrews, Larry C.; Phillips, Ronald L.; Nelson, Richard A.; Ferrell, Bobby A.; Borbath, Michael R.; Galus, Darren J.; Chin, Peter G.; Harris, William G.; Marin, Jose A.;
2005-01-01
We report on measurements made at the Shuttle Landing Facility (SLF) runway at Kennedy Space Center of receiver aperture averaging effects on a propagating optical Gaussian beam wave over a propagation path of 1,000 in. A commercially available instrument with both transmit and receive apertures was used to transmit a modulated laser beam operating at 1550 nm through a transmit aperture of 2.54 cm. An identical model of the same instrument was used as a receiver with a single aperture that was varied in size up to 20 cm to measure the effect of receiver aperture averaging on Bit Error Rate. Simultaneous measurements were also made with a scintillometer instrument and local weather station instruments to characterize atmospheric conditions along the propagation path during the experiments.
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Measurements of aperture averaging on bit-error-rate
NASA Astrophysics Data System (ADS)
Bastin, Gary L.; Andrews, Larry C.; Phillips, Ronald L.; Nelson, Richard A.; Ferrell, Bobby A.; Borbath, Michael R.; Galus, Darren J.; Chin, Peter G.; Harris, William G.; Marin, Jose A.; Burdge, Geoffrey L.; Wayne, David; Pescatore, Robert
2005-08-01
We report on measurements made at the Shuttle Landing Facility (SLF) runway at Kennedy Space Center of receiver aperture averaging effects on a propagating optical Gaussian beam wave over a propagation path of 1,000 m. A commercially available instrument with both transmit and receive apertures was used to transmit a modulated laser beam operating at 1550 nm through a transmit aperture of 2.54 cm. An identical model of the same instrument was used as a receiver with a single aperture that was varied in size up to 20 cm to measure the effect of receiver aperture averaging on Bit Error Rate. Simultaneous measurements were also made with a scintillometer instrument and local weather station instruments to characterize atmospheric conditions along the propagation path during the experiments.
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The Use of a “Hybrid” Trainer in an Established Laparoscopic Skills Program
Colsant, Brian J.; Lynch, Paul J.; Herman, Björn; Klonsky, Jonathan; Young, Steven M.
2006-01-01
Objectives: Tabletop inanimate trainers have proven to be a safe, inexpensive, and convenient platform for developing laparoscopic skills. Historically, programs that utilize these trainers rely on subjective evaluation of errors and time as the only measures of performance. Virtual reality simulators offer more extensive data collection capability, but they are expensive and lack realism. This study reviews a new electronic proctor (EP), and its performance within the Rosser Top Gun Laparoscopic Skills and Suturing Program. This “hybrid” training device seeks to capture the strengths of both platforms by providing an affordable, reliable, realistic training arena with metrics to objectively evaluate performance. Methods: An electronic proctor was designed for use in conjunction with drills from the Top Gun Program. The tabletop trainers used were outfitted with an automated electromechanically monitored task arena. Subjects performed 10 repetitions of each of 3 drills: “Cup Drop,” “Triangle Transfer,” and “Intracorporeal Suturing.” In real time, this device evaluates for instrument targeting accuracy, economy of motion, and adherence to the rules of the exercises. A buzzer and flashing light serve to alert the student to inaccuracies and breaches of the defined skill transference parameters. Results: Between July 2001 and June 2003, 117 subjects participated in courses. Seventy-three who met data evaluation criteria were assessed and compared with 744 surgeons who had previously taken the course. The total time to complete each task was significantly longer with the EP in place. The Cup Drop drill with the EP had a mean total time of 1661 seconds (average, 166.10) with 54.49 errors (average, 5.45) vs. 1252 seconds (average, 125.2) without the EP (P=0.000, t=6.735, df=814). The Triangle Transfer drill mean total time was 556 seconds (average, 55.63) and 167.57 errors (average. 16.75) (EP) vs. 454 seconds (non-EP) (average. 45.4) (P=0.000, t=4.447, df=814). The mean total times of the suturing task was 1777 seconds (average, 177.73) and 90.46 errors (average. 9.04) (EP) vs. 1682 seconds (non-EP) (average, 168.2) (P=0.040, t=1.150, df=814). When compared with surgeons who had participated in the Top Gun course prior to EP, the participants in the study collectively scored in the 18.3th percentile with the Cup Drop drill, 22.6th percentile with the Triangle Transfer drill, and 36.7th percentile with the Intracorporeal Suturing exercise. When penalizing for errors recorded by the EP, participants scored collectively in the 9.9th, 0.1th, and 17.7th percentile, respectively. No equipment failures occurred, and the agenda of the course did not have to be modified to accommodate the new platform. Conclusions: The EP utilized during the Top Gun Course was introduced without modification of the core curriculum and experienced no device failures. This hybrid trainer offers a cost-effective inanimate simulator that brings quality performance monitoring to traditional inanimate trainers. It appears that the EP influenced student performance by alerting them to errors made, thus causing an increased awareness of and focus on precision and accuracy. This suggests that the EP could have internal guidance capabilities. However, validation studies must be done in the future. PMID:16709348
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SU-F-P-42: “To Navigate, Or Not to Navigate: HDR BT in Recurrent Spine Lesions”
DOE Office of Scientific and Technical Information (OSTI.GOV)
Voros, L; Cohen, G; Zaider, M
Purpose: We compare the accuracy of HDR catheter placement for paraspinal lesions using O-arm CBCT imaging combined with StealthStation navigation and traditional fluoroscopically guided catheter placement. Methods: CT and MRI scans were acquired pre-treatment to outline the lesions and design treatment plans (pre-plans) to meet dosimetric constrains. The pre-planned catheter trajectories were transferred into the StealthStation Navigation system prior to the surgery. The StealthStation is an infra red (IR) optical navigation system used for guidance of surgical instruments. An intraoperative CBCT scan (O-arm) was acquired with reference IR optical fiducials anchored onto the patient and registered with the preplan imagemore » study to guide surgical instruments in relation to the patients’ anatomy and to place the brachytherapy catheters along the pre-planned trajectories. The final treatment plan was generated based on a 2nd intraoperative CBCT scan reflecting achieved implant geometry. The 2nd CBCT was later registered with the initial CT scan to compare the preplanned dwell positions with actual dwell positions (catheter placements). Similar workflow was used in placement of 8 catheters (1 patient) without navigation, but under fluoroscopy guidance in an interventional radiology suite. Results: A total of 18 catheters (3 patients) were placed using navigation assisted surgery. Average displacement of 0.66 cm (STD=0.37cm) was observed between the pre-plan source positions and actual source positions in the 3 dimensional space. This translates into an average 0.38 cm positioning error in one direction including registration errors, digitization errors, and the surgeons ability to follow the planned trajectory. In comparison, average displacement of non-navigated catheters was 0.50 cm (STD=0.22cm). Conclusion: Spinal lesion HDR brachytherapy planning is a difficult task. Catheter placement has a direct impact on target coverage and dose to critical structures. While limited to a handful of patients, our experience shows navigation and fluoroscopy guided placement yield similar results.« less
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2012-01-01
Background Electromyography (EMG) pattern-recognition based control strategies for multifunctional myoelectric prosthesis systems have been studied commonly in a controlled laboratory setting. Before these myoelectric prosthesis systems are clinically viable, it will be necessary to assess the effect of some disparities between the ideal laboratory setting and practical use on the control performance. One important obstacle is the impact of arm position variation that causes the changes of EMG pattern when performing identical motions in different arm positions. This study aimed to investigate the impacts of arm position variation on EMG pattern-recognition based motion classification in upper-limb amputees and the solutions for reducing these impacts. Methods With five unilateral transradial (TR) amputees, the EMG signals and tri-axial accelerometer mechanomyography (ACC-MMG) signals were simultaneously collected from both amputated and intact arms when performing six classes of arm and hand movements in each of five arm positions that were considered in the study. The effect of the arm position changes was estimated in terms of motion classification error and compared between amputated and intact arms. Then the performance of three proposed methods in attenuating the impact of arm positions was evaluated. Results With EMG signals, the average intra-position and inter-position classification errors across all five arm positions and five subjects were around 7.3% and 29.9% from amputated arms, respectively, about 1.0% and 10% low in comparison with those from intact arms. While ACC-MMG signals could yield a similar intra-position classification error (9.9%) as EMG, they had much higher inter-position classification error with an average value of 81.1% over the arm positions and the subjects. When the EMG data from all five arm positions were involved in the training set, the average classification error reached a value of around 10.8% for amputated arms. Using a two-stage cascade classifier, the average classification error was around 9.0% over all five arm positions. Reducing ACC-MMG channels from 8 to 2 only increased the average position classification error across all five arm positions from 0.7% to 1.0% in amputated arms. Conclusions The performance of EMG pattern-recognition based method in classifying movements strongly depends on arm positions. This dependency is a little stronger in intact arm than in amputated arm, which suggests that the investigations associated with practical use of a myoelectric prosthesis should use the limb amputees as subjects instead of using able-body subjects. The two-stage cascade classifier mode with ACC-MMG for limb position identification and EMG for limb motion classification may be a promising way to reduce the effect of limb position variation on classification performance. PMID:23036049
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Ries, Kernell G.; Eng, Ken
2010-01-01
The U.S. Geological Survey, in cooperation with the Maryland Department of the Environment, operated a network of 20 low-flow partial-record stations during 2008 in a region that extends from southwest of Baltimore to the northeastern corner of Maryland to obtain estimates of selected streamflow statistics at the station locations. The study area is expected to face a substantial influx of new residents and businesses as a result of military and civilian personnel transfers associated with the Federal Base Realignment and Closure Act of 2005. The estimated streamflow statistics, which include monthly 85-percent duration flows, the 10-year recurrence-interval minimum base flow, and the 7-day, 10-year low flow, are needed to provide a better understanding of the availability of water resources in the area to be affected by base-realignment activities. Streamflow measurements collected for this study at the low-flow partial-record stations and measurements collected previously for 8 of the 20 stations were related to concurrent daily flows at nearby index streamgages to estimate the streamflow statistics. Three methods were used to estimate the streamflow statistics and two methods were used to select the index streamgages. Of the three methods used to estimate the streamflow statistics, two of them--the Moments and MOVE1 methods--rely on correlating the streamflow measurements at the low-flow partial-record stations with concurrent streamflows at nearby, hydrologically similar index streamgages to determine the estimates. These methods, recommended for use by the U.S. Geological Survey, generally require about 10 streamflow measurements at the low-flow partial-record station. The third method transfers the streamflow statistics from the index streamgage to the partial-record station based on the average of the ratios of the measured streamflows at the partial-record station to the concurrent streamflows at the index streamgage. This method can be used with as few as one pair of streamflow measurements made on a single streamflow recession at the low-flow partial-record station, although additional pairs of measurements will increase the accuracy of the estimates. Errors associated with the two correlation methods generally were lower than the errors associated with the flow-ratio method, but the advantages of the flow-ratio method are that it can produce reasonably accurate estimates from streamflow measurements much faster and at lower cost than estimates obtained using the correlation methods. The two index-streamgage selection methods were (1) selection based on the highest correlation coefficient between the low-flow partial-record station and the index streamgages, and (2) selection based on Euclidean distance, where the Euclidean distance was computed as a function of geographic proximity and the basin characteristics: drainage area, percentage of forested area, percentage of impervious area, and the base-flow recession time constant, t. Method 1 generally selected index streamgages that were significantly closer to the low-flow partial-record stations than method 2. The errors associated with the estimated streamflow statistics generally were lower for method 1 than for method 2, but the differences were not statistically significant. The flow-ratio method for estimating streamflow statistics at low-flow partial-record stations was shown to be independent from the two correlation-based estimation methods. As a result, final estimates were determined for eight low-flow partial-record stations by weighting estimates from the flow-ratio method with estimates from one of the two correlation methods according to the respective variances of the estimates. Average standard errors of estimate for the final estimates ranged from 90.0 to 7.0 percent, with an average value of 26.5 percent. Average standard errors of estimate for the weighted estimates were, on average, 4.3 percent less than the best average standard errors of estima
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An urban runoff model designed to inform stormwater management decisions.
Beck, Nicole G; Conley, Gary; Kanner, Lisa; Mathias, Margaret
2017-05-15
We present an urban runoff model designed for stormwater managers to quantify runoff reduction benefits of mitigation actions that has lower input data and user expertise requirements than most commonly used models. The stormwater tool to estimate load reductions (TELR) employs a semi-distributed approach, where landscape characteristics and process representation are spatially-lumped within urban catchments on the order of 100 acres (40 ha). Hydrologic computations use a set of metrics that describe a 30-year rainfall distribution, combined with well-tested algorithms for rainfall-runoff transformation and routing to generate average annual runoff estimates for each catchment. User inputs include the locations and specifications for a range of structural best management practice (BMP) types. The model was tested in a set of urban catchments within the Lake Tahoe Basin of California, USA, where modeled annual flows matched that of the observed flows within 18% relative error for 5 of the 6 catchments and had good regional performance for a suite of performance metrics. Comparisons with continuous simulation models showed an average of 3% difference from TELR predicted runoff for a range of hypothetical urban catchments. The model usually identified the dominant BMP outflow components within 5% relative error of event-based measured flow data and simulated the correct proportionality between outflow components. TELR has been implemented as a web-based platform for use by municipal stormwater managers to inform prioritization, report program benefits and meet regulatory reporting requirements (www.swtelr.com). Copyright © 2017. Published by Elsevier Ltd.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Bauer, Anne H.; Seitz, Stella; Jerke, Jonathan
2011-05-10
We introduce a technique to measure gravitational lensing magnification using the variability of type I quasars. Quasars' variability amplitudes and luminosities are tightly correlated, on average. Magnification due to gravitational lensing increases the quasars' apparent luminosity, while leaving the variability amplitude unchanged. Therefore, the mean magnification of an ensemble of quasars can be measured through the mean shift in the variability-luminosity relation. As a proof of principle, we use this technique to measure the magnification of quasars spectroscopically identified in the Sloan Digital Sky Survey (SDSS), due to gravitational lensing by galaxy clusters in the SDSS MaxBCG catalog. The Palomar-QUESTmore » Variability Survey, reduced using the DeepSky pipeline, provides variability data for the sources. We measure the average quasar magnification as a function of scaled distance (r/R{sub 200}) from the nearest cluster; our measurements are consistent with expectations assuming Navarro-Frenk-White cluster profiles, particularly after accounting for the known uncertainty in the clusters' centers. Variability-based lensing measurements are a valuable complement to shape-based techniques because their systematic errors are very different, and also because the variability measurements are amenable to photometric errors of a few percent and to depths seen in current wide-field surveys. Given the volume data of the expected from current and upcoming surveys, this new technique has the potential to be competitive with weak lensing shear measurements of large-scale structure.« less
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Song, Mi; Chen, Zeng-Ping; Chen, Yao; Jin, Jing-Wen
2014-07-01
Liquid chromatography-mass spectrometry assays suffer from signal instability caused by the gradual fouling of the ion source, vacuum instability, aging of the ion multiplier, etc. To address this issue, in this contribution, an internal standard was added into the mobile phase. The internal standard was therefore ionized and detected together with the analytes of interest by the mass spectrometer to ensure that variations in measurement conditions and/or instrument have similar effects on the signal contributions of both the analytes of interest and the internal standard. Subsequently, based on the unique strategy of adding internal standard in mobile phase, a multiplicative effects model was developed for quantitative LC-MS assays and tested on a proof of concept model system: the determination of amino acids in water by LC-MS. The experimental results demonstrated that the proposed method could efficiently mitigate the detrimental effects of continuous signal variation, and achieved quantitative results with average relative predictive error values in the range of 8.0-15.0%, which were much more accurate than the corresponding results of conventional internal standard method based on the peak height ratio and partial least squares method (their average relative predictive error values were as high as 66.3% and 64.8%, respectively). Therefore, it is expected that the proposed method can be developed and extended in quantitative LC-MS analysis of more complex systems. Copyright © 2014 Elsevier B.V. All rights reserved.
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NASA Astrophysics Data System (ADS)
Salem, A. A.; Barsoum, B. N.; Izake, E. L.
2004-03-01
New spectrophotometric and fluorimetric methods have been developed to determine diazepam, bromazepam and clonazepam (1,4-benzodiazepines) in pure forms, pharmaceutical preparations and biological fluid. The new methods are based on measuring absorption or emission spectra in methanolic potassium hydroxide solution. Fluorimetric methods have proved selective with low detection limits, whereas photometric methods showed relatively high detection limits. Successive applications of developed methods for drugs determination in pharmaceutical preparations and urine samples were performed. Photometric methods gave linear calibration graphs in the ranges of 2.85-28.5, 0.316-3.16, and 0.316-3.16 μg ml -1 with detection limits of 1.27, 0.08 and 0.13 μg ml -1 for diazepam, bromazepam and clonazepam, respectively. Corresponding average errors of 2.60, 5.26 and 3.93 and relative standard deviations (R.S.D.s) of 2.79, 2.12 and 2.83, respectively, were obtained. Fluorimetric methods gave linear calibration graphs in the ranges of 0.03-0.34, 0.03-0.32 and 0.03-0.38 μg ml -1 with detection limits of 7.13, 5.67 and 16.47 ng ml -1 for diazepam, bromazepam and clonazepam, respectively. Corresponding average errors of 0.29, 4.33 and 5.42 and R.S.D.s of 1.27, 1.96 and 1.14 were obtained, respectively. Statistical Students t-test and F-test have been used and satisfactory results were obtained.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Johnson, P
Purpose: To determine causal factors related to high frame definition error when treating GK patients using a pre-planning workflow. Methods: 160 cases were retrospectively reviewed. All patients received treatment using a pre-planning workflow whereby stereotactic coordinates are determined from a CT scan acquired after framing using a fiducial box. The planning software automatically detects the fiducials and compares their location to expected values based on the rigid design of the fiducial system. Any difference is reported as mean and maximum frame definition error. The manufacturer recommends these values be less than 1.0 mm and 1.5 mm. In this study, framemore » definition error was analyzed in comparison with a variety of factors including which neurosurgeon/oncologist/physicist was involved with the procedure, number of post used during framing (3 or 4), type of lesion, and which CT scanner was utilized for acquisition. An analysis of variance (ANOVA) approach was used to statistically evaluate the data and determine causal factors related to instances of high frame definition error. Results: Two factors were identified as significant: number of post (p=0.0003) and CT scanner (p=0.0001). Further analysis showed that one of the four scanners was significantly different than the others. This diagnostic scanner was identified as an older model with localization lasers not tightly calibrated. The average value for maximum frame definition error using this scanner was 1.48 mm (4 posts) and 1.75 mm (3 posts). For the other scanners this value was 1.13 mm (4 posts) and 1.40 mm (3 posts). Conclusion: In utilizing a pre-planning workflow the choice of CT scanner matters. Any scanner utilized for GK should undergo routine QA at a level appropriate for radiation oncology. In terms of 3 vs 4 post, it is hypothesized that three posts provide less stability during CT acquisition. This will be tested in future work.« less
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Landsat-8 TIRS thermal radiometric calibration status
Barsi, Julia A.; Markham, Brian L.; Montanaro, Matthew; Gerace, Aaron; Hook, Simon; Schott, John R.; Raqueno, Nina G.; Morfitt, Ron
2017-01-01
The Thermal Infrared Sensor (TIRS) instrument is the thermal-band imager on the Landsat-8 platform. The initial onorbit calibration estimates of the two TIRS spectral bands indicated large average radiometric calibration errors, -0.29 and -0.51 W/m2 sr μm or -2.1K and -4.4K at 300K in Bands 10 and 11, respectively, as well as high variability in the errors, 0.87K and 1.67K (1-σ), respectively. The average error was corrected in operational processing in January 2014, though, this adjustment did not improve the variability. The source of the variability was determined to be stray light from far outside the field of view of the telescope. An algorithm for modeling the stray light effect was developed and implemented in the Landsat-8 processing system in February 2017. The new process has improved the overall calibration of the two TIRS bands, reducing the residual variability in the calibration from 0.87K to 0.51K at 300K for Band 10 and from 1.67K to 0.84K at 300K for Band 11. There are residual average lifetime bias errors in each band: 0.04 W/m2 sr μm (0.30K) and -0.04 W/m2 sr μm (-0.29K), for Bands 10 and 11, respectively.
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The efficacy of a novel mobile phone application for goldmann ptosis visual field interpretation.
Maamari, Robi N; D'Ambrosio, Michael V; Joseph, Jeffrey M; Tao, Jeremiah P
2014-01-01
To evaluate the efficacy of a novel mobile phone application that calculates superior visual field defects on Goldmann visual field charts. Experimental study in which the mobile phone application and 14 oculoplastic surgeons interpreted the superior visual field defect in 10 Goldmann charts. Percent error of the mobile phone application and the oculoplastic surgeons' estimates were calculated compared with computer software computation of the actual defects. Precision and time efficiency of the application were evaluated by processing the same Goldmann visual field chart 10 repeated times. The mobile phone application was associated with a mean percent error of 1.98% (95% confidence interval[CI], 0.87%-3.10%) in superior visual field defect calculation. The average mean percent error of the oculoplastic surgeons' visual estimates was 19.75% (95% CI, 14.39%-25.11%). Oculoplastic surgeons, on average, underestimated the defect in all 10 Goldmann charts. There was high interobserver variance among oculoplastic surgeons. The percent error of the 10 repeated measurements on a single chart was 0.93% (95% CI, 0.40%-1.46%). The average time to process 1 chart was 12.9 seconds (95% CI, 10.9-15.0 seconds). The mobile phone application was highly accurate, precise, and time-efficient in calculating the percent superior visual field defect using Goldmann charts. Oculoplastic surgeon visual interpretations were highly inaccurate, highly variable, and usually underestimated the field vision loss.
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Assessment of ecologic regression in the study of lung cancer and indoor radon.
Stidley, C A; Samet, J M
1994-02-01
Ecologic regression studies conducted to assess the cancer risk of indoor radon to the general population are subject to methodological limitations, and they have given seemingly contradictory results. The authors use simulations to examine the effects of two major methodological problems that affect these studies: measurement error and misspecification of the risk model. In a simulation study of the effect of measurement error caused by the sampling process used to estimate radon exposure for a geographic unit, both the effect of radon and the standard error of the effect estimate were underestimated, with greater bias for smaller sample sizes. In another simulation study, which addressed the consequences of uncontrolled confounding by cigarette smoking, even small negative correlations between county geometric mean annual radon exposure and the proportion of smokers resulted in negative average estimates of the radon effect. A third study considered consequences of using simple linear ecologic models when the true underlying model relation between lung cancer and radon exposure is nonlinear. These examples quantify potential biases and demonstrate the limitations of estimating risks from ecologic studies of lung cancer and indoor radon.
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NASA Technical Reports Server (NTRS)
Doggett, Leroy E.; Schaefer, Bradley E.
1994-01-01
We report the results of five Moonwatches, in which more than 2000 observers throughout North America attempted to sight the thin lunar crescent. For each Moonwatch we were able to determine the position of the Lunar Date Line (LDL), the line along which a normal observer has a 50% probability of spotting the Moon. The observational LDLs were then compared with predicted LDLs derived from crescent visibility prediction algorithms. We find that ancient and medieval rules are higly unreliable. More recent empirical criteria, based on the relative altitude and azimuth of the Moon at the time of sunset, have a reasonable accuracy, with the best specific formulation being due to Yallop. The modern theoretical model by Schaefer (based on the physiology of the human eye and the local observing conditions) is found to have the least systematic error, the least average error, and the least maximum error of all models tested. Analysis of the observations also provided information about atmospheric, optical and human factors that affect the observations. We show that observational lunar calendars have a natural bias to begin early.
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Accuracy assessment of high-rate GPS measurements for seismology
NASA Astrophysics Data System (ADS)
Elosegui, P.; Davis, J. L.; Ekström, G.
2007-12-01
Analysis of GPS measurements with a controlled laboratory system, built to simulate the ground motions caused by tectonic earthquakes and other transient geophysical signals such as glacial earthquakes, enables us to assess the technique of high-rate GPS. The root-mean-square (rms) position error of this system when undergoing realistic simulated seismic motions is 0.05~mm, with maximum position errors of 0.1~mm, thus providing "ground truth" GPS displacements. We have acquired an extensive set of high-rate GPS measurements while inducing seismic motions on a GPS antenna mounted on this system with a temporal spectrum similar to real seismic events. We found that, for a particular 15-min-long test event, the rms error of the 1-Hz GPS position estimates was 2.5~mm, with maximum position errors of 10~mm, and the error spectrum of the GPS estimates was approximately flicker noise. These results may however represent a best-case scenario since they were obtained over a short (~10~m) baseline, thereby greatly mitigating baseline-dependent errors, and when the number and distribution of satellites on the sky was good. For example, we have determined that the rms error can increase by a factor of 2--3 as the GPS constellation changes throughout the day, with an average value of 3.5~mm for eight identical, hourly-spaced, consecutive test events. The rms error also increases with increasing baseline, as one would expect, with an average rms error for a ~1400~km baseline of 9~mm. We will present an assessment of the accuracy of high-rate GPS based on these measurements, discuss the implications of this study for seismology, and describe new applications in glaciology.
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Alcohol impairs brain reactivity to explicit loss feedback.
Nelson, Lindsay D; Patrick, Christopher J; Collins, Paul; Lang, Alan R; Bernat, Edward M
2011-11-01
Alcohol impairs the brain's detection of performance errors as evidenced by attenuated error-related negativity (ERN), an event-related potential (ERP) thought to reflect a brain system that monitors one's behavior. However, it remains unclear whether alcohol impairs performance-monitoring capacity across a broader range of contexts, including those entailing external feedback. This study sought to determine whether alcohol-related monitoring deficits are specific to internal recognition of errors (reflected by the ERN) or occur also in external cuing contexts. We evaluated the impact of alcohol consumption on the feedback-related negativity (FRN), an ERP thought to engage a similar process as the ERN but elicited by negative performance feedback in the environment. In an undergraduate sample randomly assigned to drink alcohol (n = 37; average peak BAC = 0.087 g/100 ml, estimated from breath alcohol sampling) or placebo beverages (n = 42), ERP responses to gain and loss feedback were measured during a two-choice gambling task. Time-frequency analysis was used to parse the overlapping theta-FRN and delta-P3 and clarified the effects of alcohol on the measures. Alcohol intoxication attenuated both the theta-FRN and delta-P3 brain responses to feedback. The theta-FRN attenuation was stronger following loss than gain feedback. Attenuation of both theta-FRN and delta-P3 components indicates that alcohol pervasively attenuates the brain's response to feedback in this task. That theta-FRN attenuation was stronger following loss trials is consistent with prior ERN findings and suggests that alcohol broadly impairs the brain's recognition of negative performance outcomes across differing contexts.
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Intercomparison and validation of the mixed layer depth fields of global ocean syntheses
NASA Astrophysics Data System (ADS)
Toyoda, Takahiro; Fujii, Yosuke; Kuragano, Tsurane; Kamachi, Masafumi; Ishikawa, Yoichi; Masuda, Shuhei; Sato, Kanako; Awaji, Toshiyuki; Hernandez, Fabrice; Ferry, Nicolas; Guinehut, Stéphanie; Martin, Matthew J.; Peterson, K. Andrew; Good, Simon A.; Valdivieso, Maria; Haines, Keith; Storto, Andrea; Masina, Simona; Köhl, Armin; Zuo, Hao; Balmaseda, Magdalena; Yin, Yonghong; Shi, Li; Alves, Oscar; Smith, Gregory; Chang, You-Soon; Vernieres, Guillaume; Wang, Xiaochun; Forget, Gael; Heimbach, Patrick; Wang, Ou; Fukumori, Ichiro; Lee, Tong
2017-08-01
Intercomparison and evaluation of the global ocean surface mixed layer depth (MLD) fields estimated from a suite of major ocean syntheses are conducted. Compared with the reference MLDs calculated from individual profiles, MLDs calculated from monthly mean and gridded profiles show negative biases of 10-20 m in early spring related to the re-stratification process of relatively deep mixed layers. Vertical resolution of profiles also influences the MLD estimation. MLDs are underestimated by approximately 5-7 (14-16) m with the vertical resolution of 25 (50) m when the criterion of potential density exceeding the 10-m value by 0.03 kg m-3 is used for the MLD estimation. Using the larger criterion (0.125 kg m-3) generally reduces the underestimations. In addition, positive biases greater than 100 m are found in wintertime subpolar regions when MLD criteria based on temperature are used. Biases of the reanalyses are due to both model errors and errors related to differences between the assimilation methods. The result shows that these errors are partially cancelled out through the ensemble averaging. Moreover, the bias in the ensemble mean field of the reanalyses is smaller than in the observation-only analyses. This is largely attributed to comparably higher resolutions of the reanalyses. The robust reproduction of both the seasonal cycle and interannual variability by the ensemble mean of the reanalyses indicates a great potential of the ensemble mean MLD field for investigating and monitoring upper ocean processes.
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Yu, Chun-tang; Liu, Ying-ying; Xia, Yu-feng
2014-01-01
The stress-strain data of 20MnNiMo alloy were collected from a series of hot compressions on Gleeble-1500 thermal-mechanical simulator in the temperature range of 1173∼1473 K and strain rate range of 0.01∼10 s−1. Based on the experimental data, the improved Arrhenius-type constitutive model and the artificial neural network (ANN) model were established to predict the high temperature flow stress of as-cast 20MnNiMo alloy. The accuracy and reliability of the improved Arrhenius-type model and the trained ANN model were further evaluated in terms of the correlation coefficient (R), the average absolute relative error (AARE), and the relative error (η). For the former, R and AARE were found to be 0.9954 and 5.26%, respectively, while, for the latter, 0.9997 and 1.02%, respectively. The relative errors (η) of the improved Arrhenius-type model and the ANN model were, respectively, in the range of −39.99%∼35.05% and −3.77%∼16.74%. As for the former, only 16.3% of the test data set possesses η-values within ±1%, while, as for the latter, more than 79% possesses. The results indicate that the ANN model presents a higher predictable ability than the improved Arrhenius-type constitutive model. PMID:24688358
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SU-E-T-646: Quality Assurance of Truebeam Multi-Leaf Collimator Using a MLC QA Phantom
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, J; Lu, J; Hong, D
2015-06-15
Purpose: To perform a routine quality assurance procedure for Truebeam multi-leaf collimator (MLC) using MLC QA phantom, verify the stability and reliability of MLC during the treatment. Methods: MLC QA phantom is a specialized phantom for MLC quality assurance (QA), and contains five radio-opaque spheres that are embedded in an “L” shape. The phantom was placed isocentrically on the Truebeam treatment couch for the tests. A quality assurance plan was setted up in the Eclipse v10.0, the fields that need to be delivered in order to acquire the necessary images, the MLC shapes can then be obtained by the images.more » The images acquired by the electronic portal imaging device (EPID), and imported into the PIPSpro software for the analysis. The tests were delivered twelve weeks (once a week) to verify consistency of the delivery, and the images are acquired in the same manner each time. Results: For the Leaf position test, the average position error was 0.23mm±0.02mm (range: 0.18mm∼0.25mm). The Leaf width was measured at the isocenter, the average error was 0.06mm±0.02mm (range: 0.02mm∼0.08mm) for the Leaf width test. Multi-Port test showed the dynamic leaf shift error, the average error was 0.28mm±0.03mm (range: 0.2mm∼0.35mm). For the leaf transmission test, the average inter-leaf leakage value was 1.0%±0.17% (range: 0.8%∼1.3%) and the average inter-bank leakage value was 32.6%±2.1% (range: 30.2%∼36.1%). Conclusion: By the test of 12 weeks, the MLC system of the Truebeam is running in a good condition and the MLC system can be steadily and reliably carried out during the treatment. The MLC QA phantom is a useful test tool for the MLC QA.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Chengqiang, L; Yin, Y; Chen, L
Purpose: To investigate the impact of MLC position errors on simultaneous integrated boost intensity-modulated radiotherapy (SIB-IMRT) for patients with nasopharyngeal carcinoma. Methods: To compare the dosimetric differences between the simulated plans and the clinical plans, ten patients with locally advanced NPC treated with SIB-IMRT were enrolled in this study. All plans were calculated with an inverse planning system (Pinnacle3, Philips Medical System{sub )}. Random errors −2mm to 2mm{sub )},shift errors{sub (} 2mm,1mm and 0.5mm) and systematic extension/ contraction errors (±2mm, ±1mm and ±0.5mm) of the MLC leaf position were introduced respectively into the original plans to create the simulated plans.more » Dosimetry factors were compared between the original and the simulated plans. Results: The dosimetric impact of the random and system shift errors of MLC position was insignificant within 2mm, the maximum changes in D95% of PGTV,PTV1,PTV2 were-0.92±0.51%,1.00±0.24% and 0.62±0.17%, the maximum changes in the D0.1cc of spinal cord and brainstem were 1.90±2.80% and −1.78±1.42%, the maximum changes in the Dmean of parotids were1.36±1.23% and −2.25±2.04%.However,the impact of MLC extension or contraction errors was found significant. For 2mm leaf extension errors, the average changes in D95% of PGTV,PTV1,PTV2 were 4.31±0.67%,4.29±0.65% and 4.79±0.82%, the averaged value of the D0.1cc to spinal cord and brainstem were increased by 7.39±5.25% and 6.32±2.28%,the averaged value of the mean dose to left and right parotid were increased by 12.75±2.02%,13.39±2.17% respectively. Conclusion: The dosimetric effect was insignificant for random MLC leaf position errors up to 2mm. There was a high sensitivity to dose distribution for MLC extension or contraction errors.We should pay attention to the anatomic changes in target organs and anatomical structures during the course,individual radiotherapy was recommended to ensure adaptive doses.« less
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Stresses and elastic constants of crystalline sodium, from molecular dynamics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schiferl, S.K.
1985-02-01
The stresses and the elastic constants of bcc sodium are calculated by molecular dynamics (MD) for temperatures to T = 340K. The total adiabatic potential of a system of sodium atoms is represented by pseudopotential model. The resulting expression has two terms: a large, strictly volume-dependent potential, plus a sum over ion pairs of a small, volume-dependent two-body potential. The stresses and the elastic constants are given as strain derivatives of the Helmholtz free energy. The resulting expressions involve canonical ensemble averages (and fluctuation averages) of the position and volume derivatives of the potential. An ensemble correction relates the resultsmore » to MD equilibrium averages. Evaluation of the potential and its derivatives requires the calculation of integrals with infinite upper limits of integration, and integrand singularities. Methods for calculating these integrals and estimating the effects of integration errors are developed. A method is given for choosing initial conditions that relax quickly to a desired equilibrium state. Statistical methods developed earlier for MD data are extended to evaluate uncertainties in fluctuation averages, and to test for symmetry. 45 refs., 10 figs., 4 tabs.« less
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Trattner, Sigal; Prinsen, Peter; Wiegert, Jens; Gerland, Elazar-Lars; Shefer, Efrat; Morton, Tom; Thompson, Carla M; Yagil, Yoad; Cheng, Bin; Jambawalikar, Sachin; Al-Senan, Rani; Amurao, Maxwell; Halliburton, Sandra S; Einstein, Andrew J
2017-12-01
Metal-oxide-semiconductor field-effect transistors (MOSFETs) serve as a helpful tool for organ radiation dosimetry and their use has grown in computed tomography (CT). While different approaches have been used for MOSFET calibration, those using the commonly available 100 mm pencil ionization chamber have not incorporated measurements performed throughout its length, and moreover, no previous work has rigorously evaluated the multiple sources of error involved in MOSFET calibration. In this paper, we propose a new MOSFET calibration approach to translate MOSFET voltage measurements into absorbed dose from CT, based on serial measurements performed throughout the length of a 100-mm ionization chamber, and perform an analysis of the errors of MOSFET voltage measurements and four sources of error in calibration. MOSFET calibration was performed at two sites, to determine single calibration factors for tube potentials of 80, 100, and 120 kVp, using a 100-mm-long pencil ion chamber and a cylindrical computed tomography dose index (CTDI) phantom of 32 cm diameter. The dose profile along the 100-mm ion chamber axis was sampled in 5 mm intervals by nine MOSFETs in the nine holes of the CTDI phantom. Variance of the absorbed dose was modeled as a sum of the MOSFET voltage measurement variance and the calibration factor variance, the latter being comprised of three main subcomponents: ionization chamber reading variance, MOSFET-to-MOSFET variation and a contribution related to the fact that the average calibration factor of a few MOSFETs was used as an estimate for the average value of all MOSFETs. MOSFET voltage measurement error was estimated based on sets of repeated measurements. The calibration factor overall voltage measurement error was calculated from the above analysis. Calibration factors determined were close to those reported in the literature and by the manufacturer (~3 mV/mGy), ranging from 2.87 to 3.13 mV/mGy. The error σ V of a MOSFET voltage measurement was shown to be proportional to the square root of the voltage V: σV=cV where c = 0.11 mV. A main contributor to the error in the calibration factor was the ionization chamber reading error with 5% error. The usage of a single calibration factor for all MOSFETs introduced an additional error of about 5-7%, depending on the number of MOSFETs that were used to determine the single calibration factor. The expected overall error in a high-dose region (~30 mGy) was estimated to be about 8%, compared to 6% when an individual MOSFET calibration was performed. For a low-dose region (~3 mGy), these values were 13% and 12%. A MOSFET calibration method was developed using a 100-mm pencil ion chamber and a CTDI phantom, accompanied by an absorbed dose error analysis reflecting multiple sources of measurement error. When using a single calibration factor, per tube potential, for different MOSFETs, only a small error was introduced into absorbed dose determinations, thus supporting the use of a single calibration factor for experiments involving many MOSFETs, such as those required to accurately estimate radiation effective dose. © 2017 American Association of Physicists in Medicine.
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NASA Technical Reports Server (NTRS)
Del Genio, Anthony; Chen, Yonghua; Kim, Daehyun; Yao, Mao-Sung
2015-01-01
We have identified several errors in the calculations that were performed to create Fig. 3 of Del Genio et al. (2012). These errors affect the composite evolution of precipitation and column water vapor versus lag relative to the Madden-Julian oscillation (MJO) peak presented in that figure. The precipitation and column water vapor data for the April and November 2009 MJO events were composited incorrectly because the date of the MJO peak at a given longitude was assigned to the incorrect longitude band. In addition, the precipitation data for all MJO events were first accumulated daily and the daily accumulations averaged at each lag to create the composite, rather than the averaging of instantaneous values that was used for other composite figures in the paper. One poorly sampled day in the west Pacific therefore biases the composite precipitation in that region at several lags after the MJO peak. Finally, a 4-day running mean was mistakenly applied to the precipitation and column water vapor data rather than the intended 5-day running mean. The results of the corrections are that an anomalous west Pacific precipitation maximum510 days after the MJO peak is removed and the maximum in west Pacific precipitation one pentad before the MJO peak is now more evident; there is now a clear maximum in precipitation for the entire warm pool one pentad before the MJO peak; west Pacific column water vapor now varies more strongly as a function of lag relative to the peak; and precipitation, and to a lesser extent column water vapor, in general vary more smoothly with time. The corrections do not affect any other parts of the paper nor do they change the scientific conclusions we reached. The 4-day running mean error also affects Figs. 1 and 2 therein, with almost imperceptible impacts that do not affect any results or necessitate major changes to the text.
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The Accuracy of Eyelid Movement Parameters for Drowsiness Detection
Wilkinson, Vanessa E.; Jackson, Melinda L.; Westlake, Justine; Stevens, Bronwyn; Barnes, Maree; Swann, Philip; Rajaratnam, Shantha M. W.; Howard, Mark E.
2013-01-01
Study Objectives: Drowsiness is a major risk factor for motor vehicle and occupational accidents. Real-time objective indicators of drowsiness could potentially identify drowsy individuals with the goal of intervening before an accident occurs. Several ocular measures are promising objective indicators of drowsiness; however, there is a lack of studies evaluating their accuracy for detecting behavioral impairment due to drowsiness in real time. Methods: In this study, eye movement parameters were measured during vigilance tasks following restricted sleep and in a rested state (n = 33 participants) at three testing points (n = 71 data points) to compare ocular measures to a gold standard measure of drowsiness (OSLER). The utility of these parameters for detecting drowsiness-related errors was evaluated using receiver operating characteristic curves (ROC) (adjusted by clustering for participant) and identification of optimal cutoff levels for identifying frequent drowsiness-related errors (4 missed signals in a minute using OSLER). Their accuracy was tested for detecting increasing frequencies of behavioral lapses on a different task (psychomotor vigilance task [PVT]). Results: Ocular variables which measured the average duration of eyelid closure (inter-event duration [IED]) and the ratio of the amplitude to velocity of eyelid closure were reliable indicators of frequent errors (area under the curve for ROC of 0.73 to 0.83, p < 0.05). IED produced a sensitivity and specificity of 71% and 88% for detecting ≥ 3 lapses (PVT) in a minute and 100% and 86% for ≥ 5 lapses. A composite measure of several eye movement characteristics (Johns Drowsiness Scale) provided sensitivities of 77% and 100% for detecting 3 and ≥ 5 lapses in a minute, with specificities of 85% and 83%, respectively. Conclusions: Ocular measures, particularly those measuring the average duration of episodes of eye closure are promising real-time indicators of drowsiness. Citation: Wilkinson VE; Jackson ML; Westlake J; Stevens B; Barnes M; Swann P; Rajaratnam SMW; Howard ME. The accuracy of eyelid movement parameters for drowsiness detection. J Clin Sleep Med 2013;9(12):1315-1324. PMID:24340294
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, J; Peng, J; Xie, J
2015-06-15
Purpose: The purpose of this study is to investigate the sensitivity of the planar quality assurance to MLC errors with different beam complexities in intensity-modulate radiation therapy. Methods: sixteen patients’ planar quality assurance (QA) plans in our institution were enrolled in this study, including 10 dynamic MLC (DMLC) IMRT plans measured by Portal Dosimetry and 6 static MLC (SMLC) IMRT plans measured by Mapcheck. The gamma pass rate was calculated using vender’s software. The field numbers were 74 and 40 for DMLC and SMLC, respectively. A random error was generated and introduced to these fields. The modified gamma pass ratemore » was calculated by comparing the original measured fluence and modified fields’ fluence. A decreasing gamma pass rate was acquired using the original gamma pass rate minus the modified gamma pass rate. Eight complexity scores were calculated in MATLAB based on the fluence and MLC sequence of these fields. The complexity scores include fractal dimension, monitor unit of field, modulation index, fluence map complexity, weighted average of field area, weighted average of field perimeter, and small aperture ratio ( <5cm{sup 2} and <50cm{sup 2}). The Spearman’s rank correlation coefficient was implemented to analyze the correlation between these scores and decreasing gamma rate. Results: The relation between the decreasing gamma pass rate and field complexity was insignificant for most complexity scores. The most significant complexity score was fluence map complexity for SMLC, which have ρ =0.4274 (p-value=0.0063). For DMLC, the most significant complex score was fractal dimension, which have ρ=−0.3068 (p-value=0.0081). Conclusions: According to the primarily Result of this study, the sensitivity gamma pass rate was not strongly relate to the field complexity.« less
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TRMM On-Orbit Performance Re-Accessed After Control Change
NASA Technical Reports Server (NTRS)
Bilanow, Steve
2006-01-01
The Tropical Rainfall Measuring Mission (TRMM) spacecraft, a joint mission between the U.S. and Japan, launched onboard an HI1 rocket on November 27,1997 and transitioned in August, 2001 from an average operating altitude of 350 kilometers to 402.5 kilometers. Due to problems using the Earth Sensor Assembly (ESA) at the higher altitude, TRMM switched to a backup attitude control mode. Prior to the orbit boost TRMM controlled pitch and roll to the local vertical using ESA measurements while using gyro data to propagate yaw attitude between yaw updates from the Sun sensors. After the orbit boost, a Kalman filter used 3-axis gyro data with Sun sensor and magnetometers to estimate onboard attitude. While originally intended to meet a degraded attitude accuracy of 0.7 degrees, the new control mode met the original 0.2 degree attitude accuracy requirement after improving onboard ephemeris prediction and adjusting the magnetometer calibration onboard. Independent roll attitude checks using a science instrument, the Precipitation Radar (PR) which was built in Japan, provided a novel insight into the pointing performance. The PR data helped identify the pointing errors after the orbit boost, track the performance improvements, and show subtle effects from ephemeris errors and gyro bias errors. It also helped identify average bias trends throughout the mission. Roll errors tracked by the PR from sample orbits pre-boost and post-boost are shown in Figure 1. Prior to the orbit boost the largest attitude errors were due to occasional interference in the ESA. These errors were sometime larger than 0.2 degrees in pitch and roll, but usually less, as estimated from a comprehensive review of the attitude excursions using gyro data. Sudden jumps in the onboard roll show up as spikes in the reported attitude since the control responds within tens of seconds to null the pointing error. The PR estimated roll tracks well with an estimate of the roll history propagated using gyro data. After the orbit boost, the attitude errors shown by the PR roll have a smooth sine-wave type signal because of the way that attitude errors propagate with the use of gyro data. Yaw errors couple at orbit period to roll with '/4 orbit lag. By tracking the amplitude, phase, and bias of the sinusoidal PR roll error signal, it was shown that the average pitch rotation axis tends to be offset from orbit normal in a direction perpendicular to the Sun direction, as shown in Figure 2 for a 200 day period following the orbit boost. This is a result of the higher accuracy and stability of the Sun sensor measurements relative to the magnetometer measurements used in the Kalman filter. In November, 2001 a magnetometer calibration adjustment was uploaded which improved the pointing performance, keeping the roll and yaw amplitudes within about 0.1 degrees. After the boost, onboard ephemeris errors had a direct effect on the pitch pointing, being used to compute the Earth pointing reference frame. Improvements after the orbit boost have kept the the onboard ephemeris errors generally below 20 kilometers. Ephemeris errors have secondary effects on roll and yaw, especially during high beta angle when pitch effects can couple into roll and yaw. This is illustrated in figure 3. The onboard roll bias trends as measured by PR data show correlations with the Kalman filter's gyro bias error. This particularly shows up after yaw turns (every 2 to 4 weeks) as shown in Figure 3, when a slight roll bias is observed while the onboard computed gyro biases settle to new values. As for longer term trends, the PR data shows that the roll bias was influenced by Earth horizon radiance effects prior to the boost, changing values at yaw turns, and indicated a long term drift as shown in Figure 4. After the boost, the bias variations were smaller and showed some possible correlation with solar beta angle, probably due to sun sensor misalignment effects.
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Teo, Troy P; Ahmed, Syed Bilal; Kawalec, Philip; Alayoubi, Nadia; Bruce, Neil; Lyn, Ethan; Pistorius, Stephen
2018-02-01
The accurate prediction of intrafraction lung tumor motion is required to compensate for system latency in image-guided adaptive radiotherapy systems. The goal of this study was to identify an optimal prediction model that has a short learning period so that prediction and adaptation can commence soon after treatment begins, and requires minimal reoptimization for individual patients. Specifically, the feasibility of predicting tumor position using a combination of a generalized (i.e., averaged) neural network, optimized using historical patient data (i.e., tumor trajectories) obtained offline, coupled with the use of real-time online tumor positions (obtained during treatment delivery) was examined. A 3-layer perceptron neural network was implemented to predict tumor motion for a prediction horizon of 650 ms. A backpropagation algorithm and batch gradient descent approach were used to train the model. Twenty-seven 1-min lung tumor motion samples (selected from a CyberKnife patient dataset) were sampled at a rate of 7.5 Hz (0.133 s) to emulate the frame rate of an electronic portal imaging device (EPID). A sliding temporal window was used to sample the data for learning. The sliding window length was set to be equivalent to the first breathing cycle detected from each trajectory. Performing a parametric sweep, an averaged error surface of mean square errors (MSE) was obtained from the prediction responses of seven trajectories used for the training of the model (Group 1). An optimal input data size and number of hidden neurons were selected to represent the generalized model. To evaluate the prediction performance of the generalized model on unseen data, twenty tumor traces (Group 2) that were not involved in the training of the model were used for the leave-one-out cross-validation purposes. An input data size of 35 samples (4.6 s) and 20 hidden neurons were selected for the generalized neural network. An average sliding window length of 28 data samples was used. The average initial learning period prior to the availability of the first predicted tumor position was 8.53 ± 1.03 s. Average mean absolute error (MAE) of 0.59 ± 0.13 mm and 0.56 ± 0.18 mm were obtained from Groups 1 and 2, respectively, giving an overall MAE of 0.57 ± 0.17 mm. Average root-mean-square-error (RMSE) of 0.67 ± 0.36 for all the traces (0.76 ± 0.34 mm, Group 1 and 0.63 ± 0.36 mm, Group 2), is comparable to previously published results. Prediction errors are mainly due to the irregular periodicities between cycles. Since the errors from Groups 1 and 2 are within the same range, it demonstrates that this model can generalize and predict on unseen data. This is a first attempt to use an averaged MSE error surface (obtained from the prediction of different patients' tumor trajectories) to determine the parameters of a generalized neural network. This network could be deployed as a plug-and-play predictor for tumor trajectory during treatment delivery, eliminating the need for optimizing individual networks with pretreatment patient data. © 2017 American Association of Physicists in Medicine.
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Predictive momentum management for a space station measurement and computation requirements
NASA Technical Reports Server (NTRS)
Adams, John Carl
1986-01-01
An analysis is made of the effects of errors and uncertainties in the predicting of disturbance torques on the peak momentum buildup on a space station. Models of the disturbance torques acting on a space station in low Earth orbit are presented, to estimate how accurately they can be predicted. An analysis of the torque and momentum buildup about the pitch axis of the Dual Keel space station configuration is formulated, and a derivation of the Average Torque Equilibrium Attitude (ATEA) is presented, for the case of no MRMS (Mobile Remote Manipulation System) motion, Y vehicle axis MRMS motion, and Z vehicle axis MRMS motion. Results showed the peak momentum buildup to be approximately 20000 N-m-s and to be relatively insensitive to errors in the predicting torque models, for Z axis motion of the MRMS was found to vary significantly with model errors, but not exceed a value of approximately 15000 N-m-s for the Y axis MRMS motion with 1 deg attitude hold error. Minimum peak disturbance momentum was found not to occur at the ATEA angle, but at a slightly smaller angle. However, this minimum peak momentum attitude was found to produce significant disturbance momentum at the end of the predicting time interval.
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Measurement of tokamak error fields using plasma response and its applicability to ITER
Strait, Edward J.; Buttery, Richard J.; Casper, T. A.; ...
2014-04-17
The nonlinear response of a low-beta tokamak plasma to non-axisymmetric fields offers an alternative to direct measurement of the non-axisymmetric part of the vacuum magnetic fields, often termed “error fields”. Possible approaches are discussed for determination of error fields and the required current in non-axisymmetric correction coils, with an emphasis on two relatively new methods: measurement of the torque balance on a saturated magnetic island, and measurement of the braking of plasma rotation in the absence of an island. The former is well suited to ohmically heated discharges, while the latter is more appropriate for discharges with a modest amountmore » of neutral beam heating to drive rotation. Both can potentially provide continuous measurements during a discharge, subject to the limitation of a minimum averaging time. The applicability of these methods to ITER is discussed, and an estimate is made of their uncertainties in light of the specifications of ITER’s diagnostic systems. Furthermore, the use of plasma response-based techniques in normal ITER operational scenarios may allow identification of the error field contributions by individual central solenoid coils, but identification of the individual contributions by the outer poloidal field coils or other sources is less likely to be feasible.« less
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Caca, Ihsan; Cingu, Abdullah Kursat; Sahin, Alparslan; Ari, Seyhmus; Dursun, Mehmet Emin; Dag, Umut; Balsak, Selahattin; Alakus, Fuat; Yavuz, Abdullah; Palanci, Yilmaz
2013-01-01
To investigate the prevalence of refractive errors and other eye diseases, incidence and types of amblyopia in school-aged children, and their relation to gender, age, parental education, and socioeconomic factors. A total of 21,062 children 6 to 14 years old were screened. The examination included visual acuity measurements and ocular motility evaluation. Autorefraction under cycloplegia and examination of the external eye, anterior segment, media, and fundus were performed. There were 11,118 females and 9,944 males. The average age was 10.56 ± 3.59 years. When all of the children were evaluated, 3.2% had myopia and 5.9% had hyperopia. Astigmatism 0.50 D or greater was present in 14.3% of children. Myopia was associated with older age, female gender, and higher parental education. Hyperopia was inversely proportional with older age. Spectacles were needed in 4,476 (22.7%) children with refractive errors, and 10.6% of children were unaware of their spectacle needs. Amblyopia was detected in 2.6% of all children. The most common causes of amblyopia were anisometropia (1.2%) and strabismus (0.9%). Visual impairment is a common disorder in school-aged children. Eye health screening programs are beneficial in early detection and proper treatment of refractive errors. Copyright 2013, SLACK Incorporated.
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NASA Astrophysics Data System (ADS)
Fitzpatrick, Richard
2018-04-01
A two-fluid, neoclassical theory of the interaction of a single magnetic island chain with a resonant error-field in a quasi-cylindrical, low-β, tokamak plasma is presented. The plasmas typically found in large hot tokamaks lie in the so-called weak neoclassical flow-damping regime in which the neoclassical ion stress tensor is not the dominant term in the ion parallel equation of motion. Nevertheless, flow-damping in such plasmas dominates ion perpendicular viscosity, and is largely responsible for determining the phase velocity of a freely rotating island chain (which is in the ion diamagnetic direction relative to the local E × B frame at the rational surface). The critical vacuum island width required to lock the island chain is mostly determined by the ion neoclassical poloidal flow damping rate at the rational surface. The stabilizing effect of the average field-line curvature, as well as the destabilizing effect of the perturbed bootstrap current, is the same for a freely rotating, a non-uniformly rotating, and a locked island chain. The destabilizing effect of the error-field averages to zero when the chain is rotating and only manifests itself when the chain locks. The perturbed ion polarization current has a small destabilizing effect on a freely rotating island chain, but a large destabilizing effect on both a non-uniformly rotating and a locked island chain. This behavior may account for the experimentally observed fact that locked island chains are much more unstable than corresponding freely rotating chains.
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The Swiss cheese model of safety incidents: are there holes in the metaphor?
Perneger, Thomas V
2005-01-01
Background Reason's Swiss cheese model has become the dominant paradigm for analysing medical errors and patient safety incidents. The aim of this study was to determine if the components of the model are understood in the same way by quality and safety professionals. Methods Survey of a volunteer sample of persons who claimed familiarity with the model, recruited at a conference on quality in health care, and on the internet through quality-related websites. The questionnaire proposed several interpretations of components of the Swiss cheese model: a) slice of cheese, b) hole, c) arrow, d) active error, e) how to make the system safer. Eleven interpretations were compatible with this author's interpretation of the model, 12 were not. Results Eighty five respondents stated that they were very or quite familiar with the model. They gave on average 15.3 (SD 2.3, range 10 to 21) "correct" answers out of 23 (66.5%) – significantly more than 11.5 "correct" answers that would expected by chance (p < 0.001). Respondents gave on average 2.4 "correct" answers regarding the slice of cheese (out of 4), 2.7 "correct" answers about holes (out of 5), 2.8 "correct" answers about the arrow (out of 4), 3.3 "correct" answers about the active error (out of 5), and 4.1 "correct" answers about improving safety (out of 5). Conclusion The interpretations of specific features of the Swiss cheese model varied considerably among quality and safety professionals. Reaching consensus about concepts of patient safety requires further work. PMID:16280077
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A Quantitative Evaluation of Medication Histories and Reconciliation by Discipline
Stewart, Michael R.; Fogg, Sarah M.; Schminke, Brandon C.; Zackula, Rosalee E.; Nester, Tina M.; Eidem, Leslie A.; Rosendale, James C.; Ragan, Robert H.; Bond, Jack A.; Goertzen, Kreg W.
2014-01-01
Abstract Background/Objective: Medication reconciliation at transitions of care decreases medication errors, hospitalizations, and adverse drug events. We compared inpatient medication histories and reconciliation across disciplines and evaluated the nature of discrepancies. Methods: We conducted a prospective cohort study of patients admitted from the emergency department at our 760-bed hospital. Eligible patients had their medication histories conducted and reconciled in order by the admitting nurse (RN), certified pharmacy technician (CPhT), and pharmacist (RPh). Discharge medication reconciliation was not altered. Admission and discharge discrepancies were categorized by discipline, error type, and drug class and were assigned a criticality index score. A discrepancy rating system systematically measured discrepancies. Results: Of 175 consented patients, 153 were evaluated. Total admission and discharge discrepancies were 1,461 and 369, respectively. The average number of medications per participant at admission was 8.59 (1,314) with 9.41 (1,374) at discharge. Most discrepancies were committed by RNs: 53.2% (777) at admission and 56.1% (207) at discharge. The majority were omitted or incorrect. RNs had significantly higher admission discrepancy rates per medication (0.59) compared with CPhTs (0.36) and RPhs (0.16) (P < .001). RPhs corrected significantly more discrepancies per participant than RNs (6.39 vs 0.48; P < .001); average criticality index reduction was 79.0%. Estimated prevented adverse drug events (pADEs) cost savings were $589,744. Conclusions: RPhs committed the fewest discrepancies compared with RNs and CPhTs, resulting in more accurate medication histories and reconciliation. RPh involvement also prevented the greatest number of medication errors, contributing to considerable pADE-related cost savings. PMID:25477614
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Effect of humic substance photodegradation on bacterial growth and respiration in lake water
Anesio, A.M.; Graneli, W.; Aiken, G.R.; Kieber, D.J.; Mopper, K.
2005-01-01
This study addresses how humic substance (HS) chemical composition and photoreactivity affect bacterial growth, respiration, and growth efficiency (BGE) in lake water. Aqueous solutions of HSs from diverse aquatic environments representing different dissolved organic matter sources (autochthonous and allochthonous) were exposed to artificial solar UV radiation. These solutions were added to lake water passed through a 0.7-??m-pore-size filter (containing grazer-free lake bacteria) followed by dark incubation for 5, 43, and 65 h. For the 5-h incubation, several irradiated HSs inhibited bacterial carbon production (BCP) and this inhibition was highly correlated with H 2O2 photoproduction. The H2O2 decayed in the dark, and after 43 h, nearly all irradiated HSs enhanced BCP (average 39% increase relative to nonirradiated controls, standard error = 7.5%, n = 16). UV exposure of HSs also increased bacterial respiration (by ???18%, standard error = 5%, n = 4), but less than BCP, resulting in an average increase in BGE of 32% (standard error = 10%, n = 4). Photoenhancement of BCP did not correlate to HS bulk properties (i.e., elemental and chemical composition). However, when the photoenhancement of BCP was normalized to absorbance, several trends with HS origin and extraction method emerged. Absorbance-normalized hydrophilic acid and humic acid samples showed greater enhancement of BCP than hydrophobic acid and fulvic acid samples. Furthermore, absorbance-normalized autochthonous samples showed ???10-fold greater enhancement of BCP than allochthonous-dominated samples, indicating that the former are more efficient photoproducers of biological substrates. Copyright ?? 2005, American Society for Microbiology. All Rights Reserved.
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NASA Technical Reports Server (NTRS)
Iguchi, Takamichi; Tao, Wei-Kuo; Wu, Di; Peters-Lidard, Christa; Santanello, Joseph A.; Kemp, Eric; Tian, Yudong; Case, Jonathan; Wang, Weile; Ferraro, Robert;
2017-01-01
This study investigates the sensitivity of daily rainfall rates in regional seasonal simulations over the contiguous United States (CONUS) to different cumulus parameterization schemes. Daily rainfall fields were simulated at 24-km resolution using the NASA-Unified Weather Research and Forecasting (NU-WRF) Model for June-August 2000. Four cumulus parameterization schemes and two options for shallow cumulus components in a specific scheme were tested. The spread in the domain-mean rainfall rates across the parameterization schemes was generally consistent between the entire CONUS and most subregions. The selection of the shallow cumulus component in a specific scheme had more impact than that of the four cumulus parameterization schemes. Regional variability in the performance of each scheme was assessed by calculating optimally weighted ensembles that minimize full root-mean-square errors against reference datasets. The spatial pattern of the seasonally averaged rainfall was insensitive to the selection of cumulus parameterization over mountainous regions because of the topographical pattern constraint, so that the simulation errors were mostly attributed to the overall bias there. In contrast, the spatial patterns over the Great Plains regions as well as the temporal variation over most parts of the CONUS were relatively sensitive to cumulus parameterization selection. Overall, adopting a single simulation result was preferable to generating a better ensemble for the seasonally averaged daily rainfall simulation, as long as their overall biases had the same positive or negative sign. However, an ensemble of multiple simulation results was more effective in reducing errors in the case of also considering temporal variation.
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Fellner, Johann; Cencic, Oliver; Zellinger, Günter; Rechberger, Helmut
2011-10-01
Thermal utilization of municipal solid waste and commercial wastes has become of increasing importance in European waste management. As waste materials are generally composed of fossil and biogenic materials, a part of the energy generated can be considered as renewable and is thus subsidized in some European countries. Analogously, CO(2) emissions of waste incinerators are only partly accounted for in greenhouse gas inventories. A novel approach for determining these fractions is the so-called balance method. In the present study, the implementation of the balance method on a waste-to-energy plant using oxygen-enriched combustion air was investigated. The findings of the 4-year application indicate on the one hand the general applicability and robustness of the method, and on the other hand the importance of reliable monitoring data. In particular, measured volume flows of the flue gas and the oxygen-enriched combustion air as well as corresponding O(2) and CO(2) contents should regularly be validated. The fraction of renewable (biogenic) energy generated throughout the investigated period amounted to between 27 and 66% for weekly averages, thereby denoting the variation in waste composition over time. The average emission factor of the plant was approximately 45 g CO(2) MJ(-1) energy input or 450 g CO(2) kg(-1) waste incinerated. The maximum error of the final result was about 16% (relative error), which was well above the error (<8%) of the balance method for plants with conventional oxygen supply.
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The Alignment of the Mean Wind and Stress Vectors in the Unstable Surface Layer
NASA Astrophysics Data System (ADS)
Bernardes, M.; Dias, N. L.
2010-01-01
A significant non-alignment between the mean horizontal wind vector and the stress vector was observed for turbulence measurements both above the water surface of a large lake, and over a land surface (soybean crop). Possible causes for this discrepancy such as flow distortion, averaging times and the procedure used for extracting the turbulent fluctuations (low-pass filtering and filter widths etc.), were dismissed after a detailed analysis. Minimum averaging times always less than 30 min were established by calculating ogives, and error bounds for the turbulent stresses were derived with three different approaches, based on integral time scales (first-crossing and lag-window estimates) and on a bootstrap technique. It was found that the mean absolute value of the angle between the mean wind and stress vectors is highly related to atmospheric stability, with the non-alignment increasing distinctively with increasing instability. Given a coordinate rotation that aligns the mean wind with the x direction, this behaviour can be explained by the growth of the relative error of the u- w component with instability. As a result, under more unstable conditions the u- w and the v- w components become of the same order of magnitude, and the local stress vector gives the impression of being non-aligned with the mean wind vector. The relative error of the v- w component is large enough to make it undistinguishable from zero throughout the range of stabilities. Therefore, the standard assumptions of Monin-Obukhov similarity theory hold: it is fair to assume that the v- w stress component is actually zero, and that the non-alignment is a purely statistical effect. An analysis of the dimensionless budgets of the u- w and the v- w components confirms this interpretation, with both shear and buoyant production of u- w decreasing with increasing instability. In the v- w budget, shear production is zero by definition, while buoyancy displays very low-intensity fluctuations around zero. As local free convection is approached, the turbulence becomes effectively axisymetrical, and a practical limit seems to exist beyond which it is not possible to measure the u- w component accurately.
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Kim, Kyungsoo; Lim, Sung-Ho; Lee, Jaeseok; Kang, Won-Seok; Moon, Cheil; Choi, Ji-Woong
2016-01-01
Electroencephalograms (EEGs) measure a brain signal that contains abundant information about the human brain function and health. For this reason, recent clinical brain research and brain computer interface (BCI) studies use EEG signals in many applications. Due to the significant noise in EEG traces, signal processing to enhance the signal to noise power ratio (SNR) is necessary for EEG analysis, especially for non-invasive EEG. A typical method to improve the SNR is averaging many trials of event related potential (ERP) signal that represents a brain’s response to a particular stimulus or a task. The averaging, however, is very sensitive to variable delays. In this study, we propose two time delay estimation (TDE) schemes based on a joint maximum likelihood (ML) criterion to compensate the uncertain delays which may be different in each trial. We evaluate the performance for different types of signals such as random, deterministic, and real EEG signals. The results show that the proposed schemes provide better performance than other conventional schemes employing averaged signal as a reference, e.g., up to 4 dB gain at the expected delay error of 10°. PMID:27322267
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Optimized satellite image compression and reconstruction via evolution strategies
NASA Astrophysics Data System (ADS)
Babb, Brendan; Moore, Frank; Peterson, Michael
2009-05-01
This paper describes the automatic discovery, via an Evolution Strategy with Covariance Matrix Adaptation (CMA-ES), of vectors of real-valued coefficients representing matched forward and inverse transforms that outperform the 9/7 Cohen-Daubechies-Feauveau (CDF) discrete wavelet transform (DWT) for satellite image compression and reconstruction under conditions subject to quantization error. The best transform evolved during this study reduces the mean squared error (MSE) present in reconstructed satellite images by an average of 33.78% (1.79 dB), while maintaining the average information entropy (IE) of compressed images at 99.57% in comparison to the wavelet. In addition, this evolved transform achieves 49.88% (3.00 dB) average MSE reduction when tested on 80 images from the FBI fingerprint test set, and 42.35% (2.39 dB) average MSE reduction when tested on a set of 18 digital photographs, while achieving average IE of 104.36% and 100.08%, respectively. These results indicate that our evolved transform greatly improves the quality of reconstructed images without substantial loss of compression capability over a broad range of image classes.
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2014-04-24
tim at io n Er ro r ( cm ) 0 2 4 6 8 10 Color Statistics Angelova...Color_Statistics_Error) / Average_Slip_Error Position Estimation Error: Global Pose Po si tio n Es tim at io n Er ro r ( cm ) 0 2 4 6 8 10 12 Color...get some kind of clearance for releasing pose and odometry data) collected at the following sites – Taylor, Gascola, Somerset, Fort Bliss and
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The early results of excimer laser photorefractive keratectomy for compound myopic astigmatism.
Horgan, S E; Pearson, R V
1996-01-01
An excimer laser (VISX Twenty/Twenty Excimer Refractive System) was used to treat 51 eyes for myopia and astigmatism. Uncorrected pretreatment visual acuity was between 6/18 and 6/60 (log unit +0.45 to +1.0) in 59% and worse than 6/60 in 29%. The mean pretreatment spherical refractive error was -4.05 dioptre (range 1.25 to 13.25), and the mean pretreatment cylindrical error was -0.97 dioptre (range 0.25 to 4.00). Uncorrected visual acuity measured 6/6 or better (log unit 0.0 or less) in 80% at three months, and averaged 6/6 for all eyes at six months post-treatment, with 75% eyes obtaining 6/6 or better. The mean post-treatment spherical error decayed according to pre-treatment values, with a mean sphere of -0.20 dioptre for eyes initially less than -2.00 dioptre, -0.40 dioptre (for those between -2.25 and -3.00), -0.71 dioptre (for those between -4.25 and -5.00), and -1.15 dioptre for eyes initially above -6.25 dioptre. Vectored cylindrical correction exhibited response proportional to initial refraction, with a mean post-treatment cylinder of -1.83 dioptre for eyes formerly averaging -3.08 dioptre, -0.55 dioptre (eyes initially averaging -1.63 dioptre), and -0.51 dioptre (eyes initially averaging -0.67 dioptre). Vector analysis of post-treatment astigmatism showed 58% eyes exhibiting 51 or more degrees of axis shift, although 34% eyes remained within 20 degrees of their pretreatment axis. An effective reduction in spherocylindrical error was achieved with all eyes, although axis misalignment was a common event.
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Refractive errors in patients with newly diagnosed diabetes mellitus.
Yarbağ, Abdülhekim; Yazar, Hayrullah; Akdoğan, Mehmet; Pekgör, Ahmet; Kaleli, Suleyman
2015-01-01
Diabetes mellitus is a complex metabolic disorder that involves the small blood vessels, often causing widespread damage to tissues, including the eyes' optic refractive error. In patients with newly diagnosed diabetes mellitus who have unstable blood glucose levels, refraction may be incorrect. We aimed to investigate refraction in patients who were recently diagnosed with diabetes and treated at our centre. This prospective study was performed from February 2013 to January 2014. Patients were diagnosed with diabetes mellitus using laboratory biochemical tests and clinical examination. Venous fasting plasma glucose (fpg) levels were measured along with refractive errors. Two measurements were taken: initially and after four weeks. The last difference between the initial and end refractive measurements were evaluated. Our patients were 100 males and 30 females who had been newly diagnosed with type II DM. The refractive and fpg levels were measured twice in all patients. The average values of the initial measurements were as follows: fpg level, 415 mg/dl; average refractive value, +2.5 D (Dioptres). The average end of period measurements were fpg, 203 mg/dl; average refractive value, +0.75 D. There is a statistically significant difference between after four weeks measurements with initially measurements of fasting plasma glucose (fpg) levels (p<0.05) and there is a statistically significant relationship between changes in fpg changes with glasses ID (p<0.05) and the disappearance of blurred vision (to be greater than 50% success rate) were statistically significant (p<0.05). Also, were detected upon all these results the absence of any age and sex effects (p>0.05). Refractive error is affected in patients with newly diagnosed diabetes mellitus; therefore, plasma glucose levels should be considered in the selection of glasses.
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Quality assurance of dynamic parameters in volumetric modulated arc therapy.
Manikandan, A; Sarkar, B; Holla, R; Vivek, T R; Sujatha, N
2012-07-01
The purpose of this study was to demonstrate quality assurance checks for accuracy of gantry speed and position, dose rate and multileaf collimator (MLC) speed and position for a volumetric modulated arc treatment (VMAT) modality (Synergy S; Elekta, Stockholm, Sweden), and to check that all the necessary variables and parameters were synchronous. Three tests (for gantry position-dose delivery synchronisation, gantry speed-dose delivery synchronisation and MLC leaf speed and positions) were performed. The average error in gantry position was 0.5° and the average difference was 3 MU for a linear and a parabolic relationship between gantry position and delivered dose. In the third part of this test (sawtooth variation), the maximum difference was 9.3 MU, with a gantry position difference of 1.2°. In the sweeping field method test, a linear relationship was observed between recorded doses and distance from the central axis, as expected. In the open field method, errors were encountered at the beginning and at the end of the delivery arc, termed the "beginning" and "end" errors. For MLC position verification, the maximum error was -2.46 mm and the mean error was 0.0153 ±0.4668 mm, and 3.4% of leaves analysed showed errors of >±1 mm. This experiment demonstrates that the variables and parameters of the Synergy S are synchronous and that the system is suitable for delivering VMAT using a dynamic MLC.
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Improving Arterial Spin Labeling by Using Deep Learning.
Kim, Ki Hwan; Choi, Seung Hong; Park, Sung-Hong
2018-05-01
Purpose To develop a deep learning algorithm that generates arterial spin labeling (ASL) perfusion images with higher accuracy and robustness by using a smaller number of subtraction images. Materials and Methods For ASL image generation from pair-wise subtraction, we used a convolutional neural network (CNN) as a deep learning algorithm. The ground truth perfusion images were generated by averaging six or seven pairwise subtraction images acquired with (a) conventional pseudocontinuous arterial spin labeling from seven healthy subjects or (b) Hadamard-encoded pseudocontinuous ASL from 114 patients with various diseases. CNNs were trained to generate perfusion images from a smaller number (two or three) of subtraction images and evaluated by means of cross-validation. CNNs from the patient data sets were also tested on 26 separate stroke data sets. CNNs were compared with the conventional averaging method in terms of mean square error and radiologic score by using a paired t test and/or Wilcoxon signed-rank test. Results Mean square errors were approximately 40% lower than those of the conventional averaging method for the cross-validation with the healthy subjects and patients and the separate test with the patients who had experienced a stroke (P < .001). Region-of-interest analysis in stroke regions showed that cerebral blood flow maps from CNN (mean ± standard deviation, 19.7 mL per 100 g/min ± 9.7) had smaller mean square errors than those determined with the conventional averaging method (43.2 ± 29.8) (P < .001). Radiologic scoring demonstrated that CNNs suppressed noise and motion and/or segmentation artifacts better than the conventional averaging method did (P < .001). Conclusion CNNs provided superior perfusion image quality and more accurate perfusion measurement compared with those of the conventional averaging method for generation of ASL images from pair-wise subtraction images. © RSNA, 2017.