Sample records for absolute errors mae

  1. Forecasting Error Calculation with Mean Absolute Deviation and Mean Absolute Percentage Error

    NASA Astrophysics Data System (ADS)

    Khair, Ummul; Fahmi, Hasanul; Hakim, Sarudin Al; Rahim, Robbi

    2017-12-01

    Prediction using a forecasting method is one of the most important things for an organization, the selection of appropriate forecasting methods is also important but the percentage error of a method is more important in order for decision makers to adopt the right culture, the use of the Mean Absolute Deviation and Mean Absolute Percentage Error to calculate the percentage of mistakes in the least square method resulted in a percentage of 9.77% and it was decided that the least square method be worked for time series and trend data.

  2. Astigmatism error modification for absolute shape reconstruction using Fourier transform method

    NASA Astrophysics Data System (ADS)

    He, Yuhang; Li, Qiang; Gao, Bo; Liu, Ang; Xu, Kaiyuan; Wei, Xiaohong; Chai, Liqun

    2014-12-01

    A method is proposed to modify astigmatism errors in absolute shape reconstruction of optical plane using Fourier transform method. If a transmission and reflection flat are used in an absolute test, two translation measurements lead to obtain the absolute shapes by making use of the characteristic relationship between the differential and original shapes in spatial frequency domain. However, because the translation device cannot guarantee the test and reference flats rigidly parallel to each other after the translations, a tilt error exists in the obtained differential data, which caused power and astigmatism errors in the reconstructed shapes. In order to modify the astigmatism errors, a rotation measurement is added. Based on the rotation invariability of the form of Zernike polynomial in circular domain, the astigmatism terms are calculated by solving polynomial coefficient equations related to the rotation differential data, and subsequently the astigmatism terms including error are modified. Computer simulation proves the validity of the proposed method.

  3. Absolute color scale for improved diagnostics with wavefront error mapping.

    PubMed

    Smolek, Michael K; Klyce, Stephen D

    2007-11-01

    Wavefront data are expressed in micrometers and referenced to the pupil plane, but current methods to map wavefront error lack standardization. Many use normalized or floating scales that may confuse the user by generating ambiguous, noisy, or varying information. An absolute scale that combines consistent clinical information with statistical relevance is needed for wavefront error mapping. The color contours should correspond better to current corneal topography standards to improve clinical interpretation. Retrospective analysis of wavefront error data. Historic ophthalmic medical records. Topographic modeling system topographical examinations of 120 corneas across 12 categories were used. Corneal wavefront error data in micrometers from each topography map were extracted at 8 Zernike polynomial orders and for 3 pupil diameters expressed in millimeters (3, 5, and 7 mm). Both total aberrations (orders 2 through 8) and higher-order aberrations (orders 3 through 8) were expressed in the form of frequency histograms to determine the working range of the scale across all categories. The standard deviation of the mean error of normal corneas determined the map contour resolution. Map colors were based on corneal topography color standards and on the ability to distinguish adjacent color contours through contrast. Higher-order and total wavefront error contour maps for different corneal conditions. An absolute color scale was produced that encompassed a range of +/-6.5 microm and a contour interval of 0.5 microm. All aberrations in the categorical database were plotted with no loss of clinical information necessary for classification. In the few instances where mapped information was beyond the range of the scale, the type and severity of aberration remained legible. When wavefront data are expressed in micrometers, this absolute scale facilitates the determination of the severity of aberrations present compared with a floating scale, particularly for distinguishing

  4. Sub-nanometer periodic nonlinearity error in absolute distance interferometers

    NASA Astrophysics Data System (ADS)

    Yang, Hongxing; Huang, Kaiqi; Hu, Pengcheng; Zhu, Pengfei; Tan, Jiubin; Fan, Zhigang

    2015-05-01

    Periodic nonlinearity which can result in error in nanometer scale has become a main problem limiting the absolute distance measurement accuracy. In order to eliminate this error, a new integrated interferometer with non-polarizing beam splitter is developed. This leads to disappearing of the frequency and/or polarization mixing. Furthermore, a strict requirement on the laser source polarization is highly reduced. By combining retro-reflector and angel prism, reference and measuring beams can be spatially separated, and therefore, their optical paths are not overlapped. So, the main cause of the periodic nonlinearity error, i.e., the frequency and/or polarization mixing and leakage of beam, is eliminated. Experimental results indicate that the periodic phase error is kept within 0.0018°.

  5. Correction of a Technical Error in the Golf Swing: Error Amplification Versus Direct Instruction.

    PubMed

    Milanese, Chiara; Corte, Stefano; Salvetti, Luca; Cavedon, Valentina; Agostini, Tiziano

    2016-01-01

    Performance errors drive motor learning for many tasks. The authors' aim was to determine which of two strategies, method of amplification of error (MAE) or direct instruction (DI), would be more beneficial for error correction during a full golfing swing with a driver. Thirty-four golfers were randomly assigned to one of three training conditions (MAE, DI, and control). Participants were tested in a practice session in which each golfer performed 7 pretraining trials, 6 training-intervention trials, and 7 posttraining trials; and a retention test after 1 week. An optoeletronic motion capture system was used to measure the kinematic parameters of each golfer's performance. Results showed that MAE is an effective strategy for correcting the technical errors leading to a rapid improvement in performance. These findings could have practical implications for sport psychology and physical education because, while practice is obviously necessary for improving learning, the efficacy of the learning process is essential in enhancing learners' motivation and sport enjoyment.

  6. Methodological variations and their effects on reported medication administration error rates.

    PubMed

    McLeod, Monsey Chan; Barber, Nick; Franklin, Bryony Dean

    2013-04-01

    Medication administration errors (MAEs) are a problem, yet methodological variation between studies presents a potential barrier to understanding how best to increase safety. Using the UK as a case-study, we systematically summarised methodological variations in MAE studies, and their effects on reported MAE rates. Nine healthcare databases were searched for quantitative observational MAE studies in UK hospitals. Methodological variations were analysed and meta-analysis of MAE rates performed using studies that used the same definitions. Odds ratios (OR) were calculated to compare MAE rates between intravenous (IV) and non-IV doses, and between paediatric and adult doses. We identified 16 unique studies reporting three MAE definitions, 44 MAE subcategories and four different denominators. Overall adult MAE rates were 5.6% of a total of 21 533 non-IV opportunities for error (OE) (95% CI 4.6% to 6.7%) and 35% of a total of 154 IV OEs (95% CI 2% to 68%). MAEs were five times more likely in IV than non-IV doses (pooled OR 5.1; 95% CI 3.5 to 7.5). Including timing errors of ±30 min increased the MAE rate from 27% to 69% of 320 IV doses in one study. Five studies were unclear as to whether the denominator included dose omissions; omissions accounted for 0%-13% of IV doses and 1.8%-5.1% of non-IV doses. Wide methodological variations exist even within one country, some with significant effects on reported MAE rates. We have made recommendations for future MAE studies; these may be applied both within and outside the UK.

  7. Students' Mathematical Work on Absolute Value: Focusing on Conceptions, Errors and Obstacles

    ERIC Educational Resources Information Center

    Elia, Iliada; Özel, Serkan; Gagatsis, Athanasios; Panaoura, Areti; Özel, Zeynep Ebrar Yetkiner

    2016-01-01

    This study investigates students' conceptions of absolute value (AV), their performance in various items on AV, their errors in these items and the relationships between students' conceptions and their performance and errors. The Mathematical Working Space (MWS) is used as a framework for studying students' mathematical work on AV and the…

  8. Systematic literature review of hospital medication administration errors in children

    PubMed Central

    Ameer, Ahmed; Dhillon, Soraya; Peters, Mark J; Ghaleb, Maisoon

    2015-01-01

    Objective Medication administration is the last step in the medication process. It can act as a safety net to prevent unintended harm to patients if detected. However, medication administration errors (MAEs) during this process have been documented and thought to be preventable. In pediatric medicine, doses are usually administered based on the child’s weight or body surface area. This in turn increases the risk of drug miscalculations and therefore MAEs. The aim of this review is to report MAEs occurring in pediatric inpatients. Methods Twelve bibliographic databases were searched for studies published between January 2000 and February 2015 using “medication administration errors”, “hospital”, and “children” related terminologies. Handsearching of relevant publications was also carried out. A second reviewer screened articles for eligibility and quality in accordance with the inclusion/exclusion criteria. Key findings A total of 44 studies were systematically reviewed. MAEs were generally defined as a deviation of dose given from that prescribed; this included omitted doses and administration at the wrong time. Hospital MAEs in children accounted for a mean of 50% of all reported medication error reports (n=12,588). It was also identified in a mean of 29% of doses observed (n=8,894). The most prevalent type of MAEs related to preparation, infusion rate, dose, and time. This review has identified five types of interventions to reduce hospital MAEs in children: barcode medicine administration, electronic prescribing, education, use of smart pumps, and standard concentration. Conclusion This review has identified a wide variation in the prevalence of hospital MAEs in children. This is attributed to the definition and method used to investigate MAEs. The review also illustrated the complexity and multifaceted nature of MAEs. Therefore, there is a need to develop a set of safety measures to tackle these errors in pediatric practice. PMID:29354530

  9. Willingness of nurses to report medication administration errors in southern Taiwan: a cross-sectional survey.

    PubMed

    Lin, Yu-Hua; Ma, Su-mei

    2009-01-01

    Underreporting of medication administering errors (MAEs) is a threat to the quality of nursing care. The reasons for MAEs are complex and vary by health professional and institution. The purpose of this study was to explore the prevalence of MAEs and the willingness of nurses to report them. A cross-sectional study was conducted involving a survey of 14 medical surgical hospitals in southern Taiwan. Nurses voluntarily participated in this study. A structured questionnaire was completed by 605 participants. Data were collected from February 1, 2005 to March 15, 2005 using the following instruments: MAEs Unwillingness to Report Scale, Medication Errors Etiology Questionnaire, and Personal Features Questionnaire. One additional question was used to identify the willingness of nurses to report medication errors: "When medication errors occur, should they be reported to the department?" This question helped to identify the willingness or lack thereof, to report incident errors. The results indicated that 66.9% of the nurses reported experiencing MAEs and 87.7% of the nurses had a willingness to report the MAEs if there were no consequences for reporting. The nurses' willingness to report MAEs differed by job position, nursing grade, type of hospital, and hospital funding. The final logistic regression model demonstrated hospital funding to be the only statistically significant factor. The odds of a willingness to report MAEs increased 2.66-fold in private hospitals (p = 0.032, CI = 1.09 to 6.49), and 3.28 in nonprofit hospitals (p = 0.00, CI = 1.73 to 6.21) when compared to public hospitals. This study demonstrates that reporting of MAEs should be anonymous and without negative consequences in order to monitor and guide improvements in hospital medication systems.

  10. Causes of medication administration errors in hospitals: a systematic review of quantitative and qualitative evidence.

    PubMed

    Keers, Richard N; Williams, Steven D; Cooke, Jonathan; Ashcroft, Darren M

    2013-11-01

    Underlying systems factors have been seen to be crucial contributors to the occurrence of medication errors. By understanding the causes of these errors, the most appropriate interventions can be designed and implemented to minimise their occurrence. This study aimed to systematically review and appraise empirical evidence relating to the causes of medication administration errors (MAEs) in hospital settings. Nine electronic databases (MEDLINE, EMBASE, International Pharmaceutical Abstracts, ASSIA, PsycINFO, British Nursing Index, CINAHL, Health Management Information Consortium and Social Science Citations Index) were searched between 1985 and May 2013. Inclusion and exclusion criteria were applied to identify eligible publications through title analysis followed by abstract and then full text examination. English language publications reporting empirical data on causes of MAEs were included. Reference lists of included articles and relevant review papers were hand searched for additional studies. Studies were excluded if they did not report data on specific MAEs, used accounts from individuals not directly involved in the MAE concerned or were presented as conference abstracts with insufficient detail. A total of 54 unique studies were included. Causes of MAEs were categorised according to Reason's model of accident causation. Studies were assessed to determine relevance to the research question and how likely the results were to reflect the potential underlying causes of MAEs based on the method(s) used. Slips and lapses were the most commonly reported unsafe acts, followed by knowledge-based mistakes and deliberate violations. Error-provoking conditions influencing administration errors included inadequate written communication (prescriptions, documentation, transcription), problems with medicines supply and storage (pharmacy dispensing errors and ward stock management), high perceived workload, problems with ward-based equipment (access, functionality

  11. Assessing Suturing Skills in a Self-Guided Learning Setting: Absolute Symmetry Error

    ERIC Educational Resources Information Center

    Brydges, Ryan; Carnahan, Heather; Dubrowski, Adam

    2009-01-01

    Directed self-guidance, whereby trainees independently practice a skill-set in a structured setting, may be an effective technique for novice training. Currently, however, most evaluation methods require an expert to be present during practice. The study aim was to determine if absolute symmetry error, a clinically important measure that can be…

  12. Designing and evaluating an automated system for real-time medication administration error detection in a neonatal intensive care unit.

    PubMed

    Ni, Yizhao; Lingren, Todd; Hall, Eric S; Leonard, Matthew; Melton, Kristin; Kirkendall, Eric S

    2018-05-01

    Timely identification of medication administration errors (MAEs) promises great benefits for mitigating medication errors and associated harm. Despite previous efforts utilizing computerized methods to monitor medication errors, sustaining effective and accurate detection of MAEs remains challenging. In this study, we developed a real-time MAE detection system and evaluated its performance prior to system integration into institutional workflows. Our prospective observational study included automated MAE detection of 10 high-risk medications and fluids for patients admitted to the neonatal intensive care unit at Cincinnati Children's Hospital Medical Center during a 4-month period. The automated system extracted real-time medication use information from the institutional electronic health records and identified MAEs using logic-based rules and natural language processing techniques. The MAE summary was delivered via a real-time messaging platform to promote reduction of patient exposure to potential harm. System performance was validated using a physician-generated gold standard of MAE events, and results were compared with those of current practice (incident reporting and trigger tools). Physicians identified 116 MAEs from 10 104 medication administrations during the study period. Compared to current practice, the sensitivity with automated MAE detection was improved significantly from 4.3% to 85.3% (P = .009), with a positive predictive value of 78.0%. Furthermore, the system showed potential to reduce patient exposure to harm, from 256 min to 35 min (P < .001). The automated system demonstrated improved capacity for identifying MAEs while guarding against alert fatigue. It also showed promise for reducing patient exposure to potential harm following MAE events.

  13. Temperature Variability Associated with the Middle Atmosphere Electrodynamics (MAE-1) Campaign

    NASA Technical Reports Server (NTRS)

    Schmidlin, F. J.

    1999-01-01

    Meteorological rockets launched during the Middle Atmosphere Electrodynamics (MAE-1) Campaign in October 1980 from Andoya Rocket Range (ARR), Norway, exhibited large and unexpected temperature variability. Temperatures were found to vary as much as 20 C within a few hours and demonstrated a similar type of variability from one day to the next. Following examination of the reduced rocketsonde profiles the question was raised whether the observed variability was due to natural atmospheric variability or instrument malfunction. Small-scale variability, as observed, may result from one or multiple sources, e.g., intense storms upstream from the observing site, orography such as mountain waves off of the Greenland Plateau, convective activity, gravity waves, etc. Arranging the observations spaced over time showed that the perturbations moved downward. Prior to MAE-1 very few small rocketsonde measurements had been launched from ARR, thus the quality of the initial measurements in early October caused concern when the large variability was noted. We discuss the errors of the rocketsonde measurements, graphically review the nature of the variability observed, compare the data with other measurements, and postulate a possible cause for the variability.

  14. 31 CFR 354.9 - Liability of Sallie Mae and Federal Reserve Banks.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... Reserve Banks. 354.9 Section 354.9 Money and Finance: Treasury Regulations Relating to Money and Finance...-ENTRY SECURITIES OF THE STUDENT LOAN MARKETING ASSOCIATION (SALLIE MAE) § 354.9 Liability of Sallie Mae and Federal Reserve Banks. Sallie Mae and the Federal Reserve Banks may rely on the information...

  15. Probabilistic performance estimators for computational chemistry methods: The empirical cumulative distribution function of absolute errors

    NASA Astrophysics Data System (ADS)

    Pernot, Pascal; Savin, Andreas

    2018-06-01

    Benchmarking studies in computational chemistry use reference datasets to assess the accuracy of a method through error statistics. The commonly used error statistics, such as the mean signed and mean unsigned errors, do not inform end-users on the expected amplitude of prediction errors attached to these methods. We show that, the distributions of model errors being neither normal nor zero-centered, these error statistics cannot be used to infer prediction error probabilities. To overcome this limitation, we advocate for the use of more informative statistics, based on the empirical cumulative distribution function of unsigned errors, namely, (1) the probability for a new calculation to have an absolute error below a chosen threshold and (2) the maximal amplitude of errors one can expect with a chosen high confidence level. Those statistics are also shown to be well suited for benchmarking and ranking studies. Moreover, the standard error on all benchmarking statistics depends on the size of the reference dataset. Systematic publication of these standard errors would be very helpful to assess the statistical reliability of benchmarking conclusions.

  16. Optimal quantum error correcting codes from absolutely maximally entangled states

    NASA Astrophysics Data System (ADS)

    Raissi, Zahra; Gogolin, Christian; Riera, Arnau; Acín, Antonio

    2018-02-01

    Absolutely maximally entangled (AME) states are pure multi-partite generalizations of the bipartite maximally entangled states with the property that all reduced states of at most half the system size are in the maximally mixed state. AME states are of interest for multipartite teleportation and quantum secret sharing and have recently found new applications in the context of high-energy physics in toy models realizing the AdS/CFT-correspondence. We work out in detail the connection between AME states of minimal support and classical maximum distance separable (MDS) error correcting codes and, in particular, provide explicit closed form expressions for AME states of n parties with local dimension \

  17. Relative and Absolute Error Control in a Finite-Difference Method Solution of Poisson's Equation

    ERIC Educational Resources Information Center

    Prentice, J. S. C.

    2012-01-01

    An algorithm for error control (absolute and relative) in the five-point finite-difference method applied to Poisson's equation is described. The algorithm is based on discretization of the domain of the problem by means of three rectilinear grids, each of different resolution. We discuss some hardware limitations associated with the algorithm,…

  18. Error Budget for a Calibration Demonstration System for the Reflected Solar Instrument for the Climate Absolute Radiance and Refractivity Observatory

    NASA Technical Reports Server (NTRS)

    Thome, Kurtis; McCorkel, Joel; McAndrew, Brendan

    2013-01-01

    A goal of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission is to observe highaccuracy, long-term climate change trends over decadal time scales. The key to such a goal is to improving the accuracy of SI traceable absolute calibration across infrared and reflected solar wavelengths allowing climate change to be separated from the limit of natural variability. The advances required to reach on-orbit absolute accuracy to allow climate change observations to survive data gaps exist at NIST in the laboratory, but still need demonstration that the advances can move successfully from to NASA and/or instrument vendor capabilities for spaceborne instruments. The current work describes the radiometric calibration error budget for the Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer (SOLARIS) which is the calibration demonstration system (CDS) for the reflected solar portion of CLARREO. The goal of the CDS is to allow the testing and evaluation of calibration approaches, alternate design and/or implementation approaches and components for the CLARREO mission. SOLARIS also provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. The resulting SI-traceable error budget for reflectance retrieval using solar irradiance as a reference and methods for laboratory-based, absolute calibration suitable for climatequality data collections is given. Key components in the error budget are geometry differences between the solar and earth views, knowledge of attenuator behavior when viewing the sun, and sensor behavior such as detector linearity and noise behavior. Methods for demonstrating this error budget are also presented.

  19. Motion mechanisms with different spatiotemporal characteristics identified by an MAE technique with superimposed gratings.

    PubMed

    Shioiri, Satoshi; Matsumiya, Kazumichi

    2009-05-29

    We investigated spatiotemporal characteristics of motion mechanisms using a new type of motion aftereffect (MAE) we found. Our stimulus comprised two superimposed sinusoidal gratings with different spatial frequencies. After exposure to the moving stimulus, observers perceived the MAE in the static test in the direction opposite to that of the high spatial frequency grating even when low spatial frequency motion was perceived during adaptation. In contrast, in the flicker test, the MAE was perceived in the direction opposite to that of the low spatial frequency grating. These MAEs indicate that two different motion systems contribute to motion perception and can be isolated by using different test stimuli. Using a psychophysical technique based on the MAE, we investigated the differences between the two motion mechanisms. The results showed that the static MAE is the aftereffect of the motion system with a high spatial and low temporal frequency tuning (slow motion detector) and the flicker MAE is the aftereffect of the motion system with a low spatial and high temporal frequency tuning (fast motion detector). We also revealed that the two motion detectors differ in orientation tuning, temporal frequency tuning, and sensitivity to relative motion.

  20. Prediction of Shock Arrival Times from CME and Flare Data

    NASA Technical Reports Server (NTRS)

    Nunez, Marlon; Nieves-Chinchilla, Teresa; Pulkkinen, Antti

    2016-01-01

    This paper presents the Shock ARrival Model (SARM) for predicting shock arrival times for distances from 0.72 AU to 8.7 AU by using coronal mass ejections (CME) and flare data. SARM is an aerodynamic drag model described by a differential equation that has been calibrated with a dataset of 120 shocks observed from 1997 to 2010 by minimizing the mean absolute error (MAE), normalized to 1 AU. SARM should be used with CME data (radial, earthward or plane-of-sky speeds), and flare data (peak flux, duration, and location). In the case of 1 AU, the MAE and the median of absolute errors were 7.0 h and 5.0 h respectively, using the available CMEflare data. The best results for 1 AU (an MAE of 5.8 h) were obtained using both CME data, either radial or cone-model-estimated speeds, and flare data. For the prediction of shock arrivals at distances from 0.72 AU to 8.7 AU, the normalized MAE and the median were 7.1 h and 5.1 h respectively, using the available CMEflare data. SARM was also calibrated to be used with CME data alone or flare data alone, obtaining normalized MAE errors of 8.9 h and 8.6 h respectively for all shock events. The model verification was carried out with an additional dataset of 20 shocks observed from 2010 to 2012 with radial CME speeds to compare SARM with the empirical ESA model [Gopalswamy et al., 2005a] and the numerical MHD-based ENLIL model [Odstrcil et al., 2004]. The results show that the ENLIL's MAE was lower than the SARM's MAE, which was lower than the ESA's MAE. The SARM's best results were obtained when both flare and true CME speeds were used.

  1. A review on Black-Scholes model in pricing warrants in Bursa Malaysia

    NASA Astrophysics Data System (ADS)

    Gunawan, Nur Izzaty Ilmiah Indra; Ibrahim, Siti Nur Iqmal; Rahim, Norhuda Abdul

    2017-01-01

    This paper studies the accuracy of the Black-Scholes (BS) model and the dilution-adjusted Black-Scholes (DABS) model to pricing some warrants traded in the Malaysian market. Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) are used to compare the two models. Results show that the DABS model is more accurate than the BS model for the selected data.

  2. A large-area, spatially continuous assessment of land cover map error and its impact on downstream analyses.

    PubMed

    Estes, Lyndon; Chen, Peng; Debats, Stephanie; Evans, Tom; Ferreira, Stefanus; Kuemmerle, Tobias; Ragazzo, Gabrielle; Sheffield, Justin; Wolf, Adam; Wood, Eric; Caylor, Kelly

    2018-01-01

    Land cover maps increasingly underlie research into socioeconomic and environmental patterns and processes, including global change. It is known that map errors impact our understanding of these phenomena, but quantifying these impacts is difficult because many areas lack adequate reference data. We used a highly accurate, high-resolution map of South African cropland to assess (1) the magnitude of error in several current generation land cover maps, and (2) how these errors propagate in downstream studies. We first quantified pixel-wise errors in the cropland classes of four widely used land cover maps at resolutions ranging from 1 to 100 km, and then calculated errors in several representative "downstream" (map-based) analyses, including assessments of vegetative carbon stocks, evapotranspiration, crop production, and household food security. We also evaluated maps' spatial accuracy based on how precisely they could be used to locate specific landscape features. We found that cropland maps can have substantial biases and poor accuracy at all resolutions (e.g., at 1 km resolution, up to ∼45% underestimates of cropland (bias) and nearly 50% mean absolute error (MAE, describing accuracy); at 100 km, up to 15% underestimates and nearly 20% MAE). National-scale maps derived from higher-resolution imagery were most accurate, followed by multi-map fusion products. Constraining mapped values to match survey statistics may be effective at minimizing bias (provided the statistics are accurate). Errors in downstream analyses could be substantially amplified or muted, depending on the values ascribed to cropland-adjacent covers (e.g., with forest as adjacent cover, carbon map error was 200%-500% greater than in input cropland maps, but ∼40% less for sparse cover types). The average locational error was 6 km (600%). These findings provide deeper insight into the causes and potential consequences of land cover map error, and suggest several recommendations for land

  3. 31 CFR 354.5 - Obligations of Sallie Mae; no adverse claims.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ...-ENTRY SECURITIES OF THE STUDENT LOAN MARKETING ASSOCIATION (SALLIE MAE) § 354.5 Obligations of Sallie... a Federal Reserve Bank or otherwise as provided in § 354.4(c)(1), for the purposes of this part 354, Sallie Mae and the Federal Reserve Banks shall treat the Participant to whose Securities Account an...

  4. IMPROVEMENT OF SMVGEAR II ON VECTOR AND SCALAR MACHINES THROUGH ABSOLUTE ERROR TOLERANCE CONTROL (R823186)

    EPA Science Inventory

    The computer speed of SMVGEAR II was improved markedly on scalar and vector machines with relatively little loss in accuracy. The improvement was due to a method of frequently recalculating the absolute error tolerance instead of keeping it constant for a given set of chemistry. ...

  5. Medication Administration Errors in an Adult Emergency Department of a Tertiary Health Care Facility in Ghana.

    PubMed

    Acheampong, Franklin; Tetteh, Ashalley Raymond; Anto, Berko Panyin

    2016-12-01

    This study determined the incidence, types, clinical significance, and potential causes of medication administration errors (MAEs) at the emergency department (ED) of a tertiary health care facility in Ghana. This study used a cross-sectional nonparticipant observational technique. Study participants (nurses) were observed preparing and administering medication at the ED of a 2000-bed tertiary care hospital in Accra, Ghana. The observations were then compared with patients' medication charts, and identified errors were clarified with staff for possible causes. Of the 1332 observations made, involving 338 patients and 49 nurses, 362 had errors, representing 27.2%. However, the error rate excluding "lack of drug availability" fell to 12.8%. Without wrong time error, the error rate was 22.8%. The 2 most frequent error types were omission (n = 281, 77.6%) and wrong time (n = 58, 16%) errors. Omission error was mainly due to unavailability of medicine, 48.9% (n = 177). Although only one of the errors was potentially fatal, 26.7% were definitely clinically severe. The common themes that dominated the probable causes of MAEs were unavailability, staff factors, patient factors, prescription, and communication problems. This study gives credence to similar studies in different settings that MAEs occur frequently in the ED of hospitals. Most of the errors identified were not potentially fatal; however, preventive strategies need to be used to make life-saving processes such as drug administration in such specialized units error-free.

  6. Mapping the absolute magnetic field and evaluating the quadratic Zeeman-effect-induced systematic error in an atom interferometer gravimeter

    NASA Astrophysics Data System (ADS)

    Hu, Qing-Qing; Freier, Christian; Leykauf, Bastian; Schkolnik, Vladimir; Yang, Jun; Krutzik, Markus; Peters, Achim

    2017-09-01

    Precisely evaluating the systematic error induced by the quadratic Zeeman effect is important for developing atom interferometer gravimeters aiming at an accuracy in the μ Gal regime (1 μ Gal =10-8m /s2 ≈10-9g ). This paper reports on the experimental investigation of Raman spectroscopy-based magnetic field measurements and the evaluation of the systematic error in the gravimetric atom interferometer (GAIN) due to quadratic Zeeman effect. We discuss Raman duration and frequency step-size-dependent magnetic field measurement uncertainty, present vector light shift and tensor light shift induced magnetic field measurement offset, and map the absolute magnetic field inside the interferometer chamber of GAIN with an uncertainty of 0.72 nT and a spatial resolution of 12.8 mm. We evaluate the quadratic Zeeman-effect-induced gravity measurement error in GAIN as 2.04 μ Gal . The methods shown in this paper are important for precisely mapping the absolute magnetic field in vacuum and reducing the quadratic Zeeman-effect-induced systematic error in Raman transition-based precision measurements, such as atomic interferometer gravimeters.

  7. Optimization of microwave-assisted extraction with saponification (MAES) for the determination of polybrominated flame retardants in aquaculture samples.

    PubMed

    Fajar, N M; Carro, A M; Lorenzo, R A; Fernandez, F; Cela, R

    2008-08-01

    The efficiency of microwave-assisted extraction with saponification (MAES) for the determination of seven polybrominated flame retardants (polybrominated biphenyls, PBBs; and polybrominated diphenyl ethers, PBDEs) in aquaculture samples is described and compared with microwave-assisted extraction (MAE). Chemometric techniques based on experimental designs and desirability functions were used for simultaneous optimization of the operational parameters used in both MAES and MAE processes. Application of MAES to this group of contaminants in aquaculture samples, which had not been previously applied to this type of analytes, was shown to be superior to MAE in terms of extraction efficiency, extraction time and lipid content extracted from complex matrices (0.7% as against 18.0% for MAE extracts). PBBs and PBDEs were determined by gas chromatography with micro-electron capture detection (GC-muECD). The quantification limits for the analytes were 40-750 pg g(-1) (except for BB-15, which was 1.43 ng g(-1)). Precision for MAES-GC-muECD (%RSD < 11%) was significantly better than for MAE-GC-muECD (%RSD < 20%). The accuracy of both optimized methods was satisfactorily demonstrated by analysis of appropriate certified reference material (CRM), WMF-01.

  8. Understanding the causes of intravenous medication administration errors in hospitals: a qualitative critical incident study

    PubMed Central

    Keers, Richard N; Williams, Steven D; Cooke, Jonathan; Ashcroft, Darren M

    2015-01-01

    Objectives To investigate the underlying causes of intravenous medication administration errors (MAEs) in National Health Service (NHS) hospitals. Setting Two NHS teaching hospitals in the North West of England. Participants Twenty nurses working in a range of inpatient clinical environments were identified and recruited using purposive sampling at each study site. Primary outcome measures Semistructured interviews were conducted with nurse participants using the critical incident technique, where they were asked to discuss perceived causes of intravenous MAEs that they had been directly involved with. Transcribed interviews were analysed using the Framework approach and emerging themes were categorised according to Reason's model of accident causation. Results In total, 21 intravenous MAEs were discussed containing 23 individual active failures which included slips and lapses (n=11), mistakes (n=8) and deliberate violations of policy (n=4). Each active failure was associated with a range of error and violation provoking conditions. The working environment was implicated when nurses lacked healthcare team support and/or were exposed to a perceived increased workload during ward rounds, shift changes or emergencies. Nurses frequently reported that the quality of intravenous dose-checking activities was compromised due to high perceived workload and working relationships. Nurses described using approaches such as subconscious functioning and prioritising to manage their duties, which at times contributed to errors. Conclusions Complex interactions between active and latent failures can lead to intravenous MAEs in hospitals. Future interventions may need to be multimodal in design in order to mitigate these risks and reduce the burden of intravenous MAEs. PMID:25770226

  9. Quality improvements in decreasing medication administration errors made by nursing staff in an academic medical center hospital: a trend analysis during the journey to Joint Commission International accreditation and in the post-accreditation era

    PubMed Central

    Wang, Hua-fen; Jin, Jing-fen; Feng, Xiu-qin; Huang, Xin; Zhu, Ling-ling; Zhao, Xiao-ying; Zhou, Quan

    2015-01-01

    Background Medication errors may occur during prescribing, transcribing, prescription auditing, preparing, dispensing, administration, and monitoring. Medication administration errors (MAEs) are those that actually reach patients and remain a threat to patient safety. The Joint Commission International (JCI) advocates medication error prevention, but experience in reducing MAEs during the period of before and after JCI accreditation has not been reported. Methods An intervention study, aimed at reducing MAEs in hospitalized patients, was performed in the Second Affiliated Hospital of Zhejiang University, Hangzhou, People’s Republic of China, during the journey to JCI accreditation and in the post-JCI accreditation era (first half-year of 2011 to first half-year of 2014). Comprehensive interventions included organizational, information technology, educational, and process optimization-based measures. Data mining was performed on MAEs derived from a compulsory electronic reporting system. Results The number of MAEs continuously decreased from 143 (first half-year of 2012) to 64 (first half-year of 2014), with a decrease in occurrence rate by 60.9% (0.338% versus 0.132%, P<0.05). The number of MAEs related to high-alert medications decreased from 32 (the second half-year of 2011) to 16 (the first half-year of 2014), with a decrease in occurrence rate by 57.9% (0.0787% versus 0.0331%, P<0.05). Omission was the top type of MAE during the first half-year of 2011 to the first half-year of 2014, with a decrease by 50% (40 cases versus 20 cases). Intravenous administration error was the top type of error regarding administration route, but it continuously decreased from 64 (first half-year of 2012) to 27 (first half-year of 2014). More experienced registered nurses made fewer medication errors. The number of MAEs in surgical wards was twice that in medicinal wards. Compared with non-intensive care units, the intensive care units exhibited higher occurrence rates of MAEs

  10. Quality improvements in decreasing medication administration errors made by nursing staff in an academic medical center hospital: a trend analysis during the journey to Joint Commission International accreditation and in the post-accreditation era.

    PubMed

    Wang, Hua-Fen; Jin, Jing-Fen; Feng, Xiu-Qin; Huang, Xin; Zhu, Ling-Ling; Zhao, Xiao-Ying; Zhou, Quan

    2015-01-01

    Medication errors may occur during prescribing, transcribing, prescription auditing, preparing, dispensing, administration, and monitoring. Medication administration errors (MAEs) are those that actually reach patients and remain a threat to patient safety. The Joint Commission International (JCI) advocates medication error prevention, but experience in reducing MAEs during the period of before and after JCI accreditation has not been reported. An intervention study, aimed at reducing MAEs in hospitalized patients, was performed in the Second Affiliated Hospital of Zhejiang University, Hangzhou, People's Republic of China, during the journey to JCI accreditation and in the post-JCI accreditation era (first half-year of 2011 to first half-year of 2014). Comprehensive interventions included organizational, information technology, educational, and process optimization-based measures. Data mining was performed on MAEs derived from a compulsory electronic reporting system. The number of MAEs continuously decreased from 143 (first half-year of 2012) to 64 (first half-year of 2014), with a decrease in occurrence rate by 60.9% (0.338% versus 0.132%, P<0.05). The number of MAEs related to high-alert medications decreased from 32 (the second half-year of 2011) to 16 (the first half-year of 2014), with a decrease in occurrence rate by 57.9% (0.0787% versus 0.0331%, P<0.05). Omission was the top type of MAE during the first half-year of 2011 to the first half-year of 2014, with a decrease by 50% (40 cases versus 20 cases). Intravenous administration error was the top type of error regarding administration route, but it continuously decreased from 64 (first half-year of 2012) to 27 (first half-year of 2014). More experienced registered nurses made fewer medication errors. The number of MAEs in surgical wards was twice that in medicinal wards. Compared with non-intensive care units, the intensive care units exhibited higher occurrence rates of MAEs (1.81% versus 0.24%, P<0

  11. 78 FR 21393 - Notice of Submission of Proposed Information Collection to OMB Ginnie Mae Multiclass Securities...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-04-10

    ..., allowing the private sector to combine and restructure cash flows from Ginnie Mae Single Class MBS into... program, Ginnie Mae guarantees, with the full faith and credit of the United States, the timely payment of... combine and restructure cash flows from Ginnie Mae Single Class MBS into securities that meet unique...

  12. Effects of landuse change on the hydrologic regime of the Mae Chaem river basin, NW Thailand

    NASA Astrophysics Data System (ADS)

    Thanapakpawin, P.; Richey, J.; Thomas, D.; Rodda, S.; Campbell, B.; Logsdon, M.

    2007-02-01

    SummaryConflicts between upland shifting cultivation, upland commercial crops, and lowland irrigated agriculture cause water resource tension in the Mae Chaem watershed in Chiang Mai, Thailand. In this paper, we assess hydrologic regimes of the Mae Chaem River with landuse change. Three plausible future forest-to-crop expansion scenarios and a scenario of crop-to-forest reversal were developed based on the landcover transition from 1989 to 2000, with emphasis on influences of elevation bands and irrigation diversion. Basin hydrologic responses were simulated using the Distributed Hydrology Soil Vegetation Model (DHSVM). Meteorological data from six weather stations inside and adjacent to the Mae Chaem watershed during the period 1993-2000 were the climate inputs. Computed stream flow was compared to observed discharge at Ban Mae Mu gauge on Mae Mu river, Ban Mae Suk gauge on Mae Suk river, and at Kaeng Ob Luang, located downstream from the district town in Mae Chaem. With current assumptions, expansion of highland crop fields led to slightly higher regulated annual and wet-season water yields compared to similar expansion in the lowland-midland zone. Actual downstream water availability was sensitive to irrigation diversion. This modeling approach can be a useful tool for water allocation for small watersheds undergoing rapid commercialization, because it alerts land managers to the potential range of water supply in wet and dry seasons, and provides information on spatial distribution of basin hydrologic components.

  13. Demand Forecasting: An Evaluation of DODs Accuracy Metric and Navys Procedures

    DTIC Science & Technology

    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

  14. Sallie Mae Eyes Expansion beyond Its Charter.

    ERIC Educational Resources Information Center

    Zook, Jim

    1995-01-01

    The Student Loan Marketing Association (Sallie Mae) and the Clinton Administration are preparing legislation to transform the federally sponsored corporation into a private business but must negotiate complex political and financial issues. Destabilization of the private student-loan industry and conflict over direct-lending policies are central…

  15. Effective connectivity associated with auditory error detection in musicians with absolute pitch

    PubMed Central

    Parkinson, Amy L.; Behroozmand, Roozbeh; Ibrahim, Nadine; Korzyukov, Oleg; Larson, Charles R.; Robin, Donald A.

    2014-01-01

    It is advantageous to study a wide range of vocal abilities in order to fully understand how vocal control measures vary across the full spectrum. Individuals with absolute pitch (AP) are able to assign a verbal label to musical notes and have enhanced abilities in pitch identification without reliance on an external referent. In this study we used dynamic causal modeling (DCM) to model effective connectivity of ERP responses to pitch perturbation in voice auditory feedback in musicians with relative pitch (RP), AP, and non-musician controls. We identified a network compromising left and right hemisphere superior temporal gyrus (STG), primary motor cortex (M1), and premotor cortex (PM). We specified nine models and compared two main factors examining various combinations of STG involvement in feedback pitch error detection/correction process. Our results suggest that modulation of left to right STG connections are important in the identification of self-voice error and sensory motor integration in AP musicians. We also identify reduced connectivity of left hemisphere PM to STG connections in AP and RP groups during the error detection and corrections process relative to non-musicians. We suggest that this suppression may allow for enhanced connectivity relating to pitch identification in the right hemisphere in those with more precise pitch matching abilities. Musicians with enhanced pitch identification abilities likely have an improved auditory error detection and correction system involving connectivity of STG regions. Our findings here also suggest that individuals with AP are more adept at using feedback related to pitch from the right hemisphere. PMID:24634644

  16. Despite a Settlement, Sallie Mae Still Plays Host to College Student-Aid Sites

    ERIC Educational Resources Information Center

    Hermes, J. J.

    2008-01-01

    Last April, as part of a $2-million settlement with New York's attorney general, the nation's largest student-loan company, Sallie Mae, agreed to stop providing staff members for colleges' financial-aid offices and call centers at no cost to the institutions. But one year later, Sallie Mae still plays host to the entire online presence for the…

  17. The impact of a closed-loop electronic prescribing and administration system on prescribing errors, administration errors and staff time: a before-and-after study.

    PubMed

    Franklin, Bryony Dean; O'Grady, Kara; Donyai, Parastou; Jacklin, Ann; Barber, Nick

    2007-08-01

    To assess the impact of a closed-loop electronic prescribing, automated dispensing, barcode patient identification and electronic medication administration record (EMAR) system on prescribing and administration errors, confirmation of patient identity before administration, and staff time. Before-and-after study in a surgical ward of a teaching hospital, involving patients and staff of that ward. Closed-loop electronic prescribing, automated dispensing, barcode patient identification and EMAR system. Percentage of new medication orders with a prescribing error, percentage of doses with medication administration errors (MAEs) and percentage given without checking patient identity. Time spent prescribing and providing a ward pharmacy service. Nursing time on medication tasks. Prescribing errors were identified in 3.8% of 2450 medication orders pre-intervention and 2.0% of 2353 orders afterwards (p<0.001; chi(2) test). MAEs occurred in 7.0% of 1473 non-intravenous doses pre-intervention and 4.3% of 1139 afterwards (p = 0.005; chi(2) test). Patient identity was not checked for 82.6% of 1344 doses pre-intervention and 18.9% of 1291 afterwards (p<0.001; chi(2) test). Medical staff required 15 s to prescribe a regular inpatient drug pre-intervention and 39 s afterwards (p = 0.03; t test). Time spent providing a ward pharmacy service increased from 68 min to 98 min each weekday (p = 0.001; t test); 22% of drug charts were unavailable pre-intervention. Time per drug administration round decreased from 50 min to 40 min (p = 0.006; t test); nursing time on medication tasks outside of drug rounds increased from 21.1% to 28.7% (p = 0.006; chi(2) test). A closed-loop electronic prescribing, dispensing and barcode patient identification system reduced prescribing errors and MAEs, and increased confirmation of patient identity before administration. Time spent on medication-related tasks increased.

  18. Demand forecasting of electricity in Indonesia with limited historical data

    NASA Astrophysics Data System (ADS)

    Dwi Kartikasari, Mujiati; Rohmad Prayogi, Arif

    2018-03-01

    Demand forecasting of electricity is an important activity for electrical agents to know the description of electricity demand in future. Prediction of demand electricity can be done using time series models. In this paper, double moving average model, Holt’s exponential smoothing model, and grey model GM(1,1) are used to predict electricity demand in Indonesia under the condition of limited historical data. The result shows that grey model GM(1,1) has the smallest value of MAE (mean absolute error), MSE (mean squared error), and MAPE (mean absolute percentage error).

  19. Generalized approach for using unbiased symmetric metrics with negative values: normalized mean bias factor and normalized mean absolute error factor

    EPA Science Inventory

    Unbiased symmetric metrics provide a useful measure to quickly compare two datasets, with similar interpretations for both under and overestimations. Two examples include the normalized mean bias factor and normalized mean absolute error factor. However, the original formulations...

  20. Provider risk factors for medication administration error alerts: analyses of a large-scale closed-loop medication administration system using RFID and barcode.

    PubMed

    Hwang, Yeonsoo; Yoon, Dukyong; Ahn, Eun Kyoung; Hwang, Hee; Park, Rae Woong

    2016-12-01

    To determine the risk factors and rate of medication administration error (MAE) alerts by analyzing large-scale medication administration data and related error logs automatically recorded in a closed-loop medication administration system using radio-frequency identification and barcodes. The subject hospital adopted a closed-loop medication administration system. All medication administrations in the general wards were automatically recorded in real-time using radio-frequency identification, barcodes, and hand-held point-of-care devices. MAE alert logs recorded during a full 1 year of 2012. We evaluated risk factors for MAE alerts including administration time, order type, medication route, the number of medication doses administered, and factors associated with nurse practices by logistic regression analysis. A total of 2 874 539 medication dose records from 30 232 patients (882.6 patient-years) were included in 2012. We identified 35 082 MAE alerts (1.22% of total medication doses). The MAE alerts were significantly related to administration at non-standard time [odds ratio (OR) 1.559, 95% confidence interval (CI) 1.515-1.604], emergency order (OR 1.527, 95%CI 1.464-1.594), and the number of medication doses administered (OR 0.993, 95%CI 0.992-0.993). Medication route, nurse's employment duration, and working schedule were also significantly related. The MAE alert rate was 1.22% over the 1-year observation period in the hospital examined in this study. The MAE alerts were significantly related to administration time, order type, medication route, the number of medication doses administered, nurse's employment duration, and working schedule. The real-time closed-loop medication administration system contributed to improving patient safety by preventing potential MAEs. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  1. Analysis of the Mean Absolute Error (MAE) and the Root Mean Square Error (RMSE) in Assessing Rounding Model

    NASA Astrophysics Data System (ADS)

    Wang, Weijie; Lu, Yanmin

    2018-03-01

    Most existing Collaborative Filtering (CF) algorithms predict a rating as the preference of an active user toward a given item, which is always a decimal fraction. Meanwhile, the actual ratings in most data sets are integers. In this paper, we discuss and demonstrate why rounding can bring different influences to these two metrics; prove that rounding is necessary in post-processing of the predicted ratings, eliminate of model prediction bias, improving the accuracy of the prediction. In addition, we also propose two new rounding approaches based on the predicted rating probability distribution, which can be used to round the predicted rating to an optimal integer rating, and get better prediction accuracy compared to the Basic Rounding approach. Extensive experiments on different data sets validate the correctness of our analysis and the effectiveness of our proposed rounding approaches.

  2. The impact of a closed‐loop electronic prescribing and administration system on prescribing errors, administration errors and staff time: a before‐and‐after study

    PubMed Central

    Franklin, Bryony Dean; O'Grady, Kara; Donyai, Parastou; Jacklin, Ann; Barber, Nick

    2007-01-01

    Objectives To assess the impact of a closed‐loop electronic prescribing, automated dispensing, barcode patient identification and electronic medication administration record (EMAR) system on prescribing and administration errors, confirmation of patient identity before administration, and staff time. Design, setting and participants Before‐and‐after study in a surgical ward of a teaching hospital, involving patients and staff of that ward. Intervention Closed‐loop electronic prescribing, automated dispensing, barcode patient identification and EMAR system. Main outcome measures Percentage of new medication orders with a prescribing error, percentage of doses with medication administration errors (MAEs) and percentage given without checking patient identity. Time spent prescribing and providing a ward pharmacy service. Nursing time on medication tasks. Results Prescribing errors were identified in 3.8% of 2450 medication orders pre‐intervention and 2.0% of 2353 orders afterwards (p<0.001; χ2 test). MAEs occurred in 7.0% of 1473 non‐intravenous doses pre‐intervention and 4.3% of 1139 afterwards (p = 0.005; χ2 test). Patient identity was not checked for 82.6% of 1344 doses pre‐intervention and 18.9% of 1291 afterwards (p<0.001; χ2 test). Medical staff required 15 s to prescribe a regular inpatient drug pre‐intervention and 39 s afterwards (p = 0.03; t test). Time spent providing a ward pharmacy service increased from 68 min to 98 min each weekday (p = 0.001; t test); 22% of drug charts were unavailable pre‐intervention. Time per drug administration round decreased from 50 min to 40 min (p = 0.006; t test); nursing time on medication tasks outside of drug rounds increased from 21.1% to 28.7% (p = 0.006; χ2 test). Conclusions A closed‐loop electronic prescribing, dispensing and barcode patient identification system reduced prescribing errors and MAEs, and increased confirmation of patient identity before

  3. Optimization of microwave-assisted extraction (MAE) of coriander phenolic antioxidants - response surface methodology approach.

    PubMed

    Zeković, Zoran; Vladić, Jelena; Vidović, Senka; Adamović, Dušan; Pavlić, Branimir

    2016-10-01

    Microwave-assisted extraction (MAE) of polyphenols from coriander seeds was optimized by simultaneous maximization of total phenolic (TP) and total flavonoid (TF) yields, as well as maximized antioxidant activity determined by 1,1-diphenyl-2-picrylhydrazyl and reducing power assays. Box-Behnken experimental design with response surface methodology (RSM) was used for optimization of MAE. Extraction time (X1 , 15-35 min), ethanol concentration (X2 , 50-90% w/w) and irradiation power (X3 , 400-800 W) were investigated as independent variables. Experimentally obtained values of investigated responses were fitted to a second-order polynomial model, and multiple regression analysis and analysis of variance were used to determine fitness of the model and optimal conditions. The optimal MAE conditions for simultaneous maximization of polyphenol yield and increased antioxidant activity were an extraction time of 19 min, an ethanol concentration of 63% and an irradiation power of 570 W, while predicted values of TP, TF, IC50 and EC50 at optimal MAE conditions were 311.23 mg gallic acid equivalent per 100 g dry weight (DW), 213.66 mg catechin equivalent per 100 g DW, 0.0315 mg mL(-1) and 0.1311 mg mL(-1) respectively. RSM was successfully used for multi-response optimization of coriander seed polyphenols. Comparison of optimized MAE with conventional extraction techniques confirmed that MAE provides significantly higher polyphenol yields and extracts with increased antioxidant activity. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  4. 77 FR 74022 - Notice of Proposed Information Collection: Comment Request; Ginnie Mae Mortgage-Backed Securities...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-12-12

    ... multiple Issuer MBS is structured so that small issuers, who do not meet the minimum number of loans and... program, securities are backed by single-family or multifamily loans. Under the Ginnie Mae II program, securities are only backed by single family loans. Both the Ginnie Mae I and II MBS are modified pass-through...

  5. Demonstrating the Error Budget for the Climate Absolute Radiance and Refractivity Observatory Through Solar Irradiance Measurements

    NASA Technical Reports Server (NTRS)

    Thome, Kurtis; McCorkel, Joel; McAndrew, Brendan

    2016-01-01

    The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe highaccuracy, long-term climate change trends and to use decadal change observations as a method to determine the accuracy of climate change. A CLARREO objective is to improve the accuracy of SI-traceable, absolute calibration at infrared and reflected solar wavelengths to reach on-orbit accuracies required to allow climate change observations to survive data gaps and observe climate change at the limit of natural variability. Such an effort will also demonstrate National Institute of Standards and Technology (NIST) approaches for use in future spaceborne instruments. The current work describes the results of laboratory and field measurements with the Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer (SOLARIS) which is the calibration demonstration system (CDS) for the reflected solar portion of CLARREO. SOLARIS allows testing and evaluation of calibration approaches, alternate design and/or implementation approaches and components for the CLARREO mission. SOLARIS also provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. Results of laboratory calibration measurements are provided to demonstrate key assumptions about instrument behavior that are needed to achieve CLARREO's climate measurement requirements. Absolute radiometric response is determined using laser-based calibration sources and applied to direct solar views for comparison with accepted solar irradiance models to demonstrate accuracy values giving confidence in the error budget for the CLARREO reflectance retrieval.

  6. 75 FR 44804 - Privacy Act of 1974; Notice of a New Privacy Act System of Records (SORN), Ginnie Mae Mortgage...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-29

    ...The Department proposes to establish a new Privacy Act SORN subject to the Privacy Act of 1974 (5 U.S.C. 552a), as amended, entitled Ginnie Mae Mortgage-Backed Security Unclaimed Funds System. The new record system will be used to track unclaimed security holder payments. Such unclaimed payments are owed to certificate holders of Ginnie Mae-guaranteed mortgage-backed securities who cannot be located by the Ginnie Mae servicer. Ginnie Mae tracks this information to ensure that security holders are paid properly.

  7. Comparison of Two Hybrid Models for Forecasting the Incidence of Hemorrhagic Fever with Renal Syndrome in Jiangsu Province, China

    PubMed Central

    Wu, Wei; Guo, Junqiao; An, Shuyi; Guan, Peng; Ren, Yangwu; Xia, Linzi; Zhou, Baosen

    2015-01-01

    Background Cases of hemorrhagic fever with renal syndrome (HFRS) are widely distributed in eastern Asia, especially in China, Russia, and Korea. It is proved to be a difficult task to eliminate HFRS completely because of the diverse animal reservoirs and effects of global warming. Reliable forecasting is useful for the prevention and control of HFRS. Methods Two hybrid models, one composed of nonlinear autoregressive neural network (NARNN) and autoregressive integrated moving average (ARIMA) the other composed of generalized regression neural network (GRNN) and ARIMA were constructed to predict the incidence of HFRS in the future one year. Performances of the two hybrid models were compared with ARIMA model. Results The ARIMA, ARIMA-NARNN ARIMA-GRNN model fitted and predicted the seasonal fluctuation well. Among the three models, the mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of ARIMA-NARNN hybrid model was the lowest both in modeling stage and forecasting stage. As for the ARIMA-GRNN hybrid model, the MSE, MAE and MAPE of modeling performance and the MSE and MAE of forecasting performance were less than the ARIMA model, but the MAPE of forecasting performance did not improve. Conclusion Developing and applying the ARIMA-NARNN hybrid model is an effective method to make us better understand the epidemic characteristics of HFRS and could be helpful to the prevention and control of HFRS. PMID:26270814

  8. Comparison of Two Hybrid Models for Forecasting the Incidence of Hemorrhagic Fever with Renal Syndrome in Jiangsu Province, China.

    PubMed

    Wu, Wei; Guo, Junqiao; An, Shuyi; Guan, Peng; Ren, Yangwu; Xia, Linzi; Zhou, Baosen

    2015-01-01

    Cases of hemorrhagic fever with renal syndrome (HFRS) are widely distributed in eastern Asia, especially in China, Russia, and Korea. It is proved to be a difficult task to eliminate HFRS completely because of the diverse animal reservoirs and effects of global warming. Reliable forecasting is useful for the prevention and control of HFRS. Two hybrid models, one composed of nonlinear autoregressive neural network (NARNN) and autoregressive integrated moving average (ARIMA) the other composed of generalized regression neural network (GRNN) and ARIMA were constructed to predict the incidence of HFRS in the future one year. Performances of the two hybrid models were compared with ARIMA model. The ARIMA, ARIMA-NARNN ARIMA-GRNN model fitted and predicted the seasonal fluctuation well. Among the three models, the mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of ARIMA-NARNN hybrid model was the lowest both in modeling stage and forecasting stage. As for the ARIMA-GRNN hybrid model, the MSE, MAE and MAPE of modeling performance and the MSE and MAE of forecasting performance were less than the ARIMA model, but the MAPE of forecasting performance did not improve. Developing and applying the ARIMA-NARNN hybrid model is an effective method to make us better understand the epidemic characteristics of HFRS and could be helpful to the prevention and control of HFRS.

  9. Comparative Study of Four Time Series Methods in Forecasting Typhoid Fever Incidence in China

    PubMed Central

    Zhang, Xingyu; Liu, Yuanyuan; Yang, Min; Zhang, Tao; Young, Alistair A.; Li, Xiaosong

    2013-01-01

    Accurate incidence forecasting of infectious disease is critical for early prevention and for better government strategic planning. In this paper, we present a comprehensive study of different forecasting methods based on the monthly incidence of typhoid fever. The seasonal autoregressive integrated moving average (SARIMA) model and three different models inspired by neural networks, namely, back propagation neural networks (BPNN), radial basis function neural networks (RBFNN), and Elman recurrent neural networks (ERNN) were compared. The differences as well as the advantages and disadvantages, among the SARIMA model and the neural networks were summarized and discussed. The data obtained for 2005 to 2009 and for 2010 from the Chinese Center for Disease Control and Prevention were used as modeling and forecasting samples, respectively. The performances were evaluated based on three metrics: mean absolute error (MAE), mean absolute percentage error (MAPE), and mean square error (MSE). The results showed that RBFNN obtained the smallest MAE, MAPE and MSE in both the modeling and forecasting processes. The performances of the four models ranked in descending order were: RBFNN, ERNN, BPNN and the SARIMA model. PMID:23650546

  10. Comparative study of four time series methods in forecasting typhoid fever incidence in China.

    PubMed

    Zhang, Xingyu; Liu, Yuanyuan; Yang, Min; Zhang, Tao; Young, Alistair A; Li, Xiaosong

    2013-01-01

    Accurate incidence forecasting of infectious disease is critical for early prevention and for better government strategic planning. In this paper, we present a comprehensive study of different forecasting methods based on the monthly incidence of typhoid fever. The seasonal autoregressive integrated moving average (SARIMA) model and three different models inspired by neural networks, namely, back propagation neural networks (BPNN), radial basis function neural networks (RBFNN), and Elman recurrent neural networks (ERNN) were compared. The differences as well as the advantages and disadvantages, among the SARIMA model and the neural networks were summarized and discussed. The data obtained for 2005 to 2009 and for 2010 from the Chinese Center for Disease Control and Prevention were used as modeling and forecasting samples, respectively. The performances were evaluated based on three metrics: mean absolute error (MAE), mean absolute percentage error (MAPE), and mean square error (MSE). The results showed that RBFNN obtained the smallest MAE, MAPE and MSE in both the modeling and forecasting processes. The performances of the four models ranked in descending order were: RBFNN, ERNN, BPNN and the SARIMA model.

  11. Reliable absolute analog code retrieval approach for 3D measurement

    NASA Astrophysics Data System (ADS)

    Yu, Shuang; Zhang, Jing; Yu, Xiaoyang; Sun, Xiaoming; Wu, Haibin; Chen, Deyun

    2017-11-01

    The wrapped phase of phase-shifting approach can be unwrapped by using Gray code, but both the wrapped phase error and Gray code decoding error can result in period jump error, which will lead to gross measurement error. Therefore, this paper presents a reliable absolute analog code retrieval approach. The combination of unequal-period Gray code and phase shifting patterns at high frequencies are used to obtain high-frequency absolute analog code, and at low frequencies, the same unequal-period combination patterns are used to obtain the low-frequency absolute analog code. Next, the difference between the two absolute analog codes was employed to eliminate period jump errors, and a reliable unwrapped result can be obtained. Error analysis was used to determine the applicable conditions, and this approach was verified through theoretical analysis. The proposed approach was further verified experimentally. Theoretical analysis and experimental results demonstrate that the proposed approach can perform reliable analog code unwrapping.

  12. Absolute calibration of optical flats

    DOEpatents

    Sommargren, Gary E.

    2005-04-05

    The invention uses the phase shifting diffraction interferometer (PSDI) to provide a true point-by-point measurement of absolute flatness over the surface of optical flats. Beams exiting the fiber optics in a PSDI have perfect spherical wavefronts. The measurement beam is reflected from the optical flat and passed through an auxiliary optic to then be combined with the reference beam on a CCD. The combined beams include phase errors due to both the optic under test and the auxiliary optic. Standard phase extraction algorithms are used to calculate this combined phase error. The optical flat is then removed from the system and the measurement fiber is moved to recombine the two beams. The newly combined beams include only the phase errors due to the auxiliary optic. When the second phase measurement is subtracted from the first phase measurement, the absolute phase error of the optical flat is obtained.

  13. Microwave-assisted extraction (MAE) of bioactive saponin from mahogany seed (Swietenia mahogany Jacq)

    NASA Astrophysics Data System (ADS)

    Waziiroh, E.; Harijono; Kamilia, K.

    2018-03-01

    Mahogany is frequently used for medicines for cancer, tumor, and diabetes, as it contains saponin and flavonoid. Saponin is a complex glycosydic compound consisted of triterpenoids or steroids. Saponin can be extracted from a plant by using a solvent extraction. Microwave Assisted Extraction (MAE) is a non-conventional extraction method that use micro waves in the process. This research was conducted by a Complete Random Design with two factors which were extraction time (120, 150, and 180 seconds) and solvent ratio (10:1, 15:1, and 20:1 v/w). The best treatment of MAE were the solvent ratio 15:1 (v/w) for 180 seconds. The best treatment resulting crude saponin extract yield of 41.46%, containing 11.53% total saponins, and 49.17% of antioxidant activity. Meanwhile, the treatment of maceration method were the solvent ratio 20:1 (v/w) for 48 hours resulting 39.86% yield of saponin crude extract, 9.26% total saponins and 56.23% of antioxidant activity. The results showed MAE was more efficient (less time of extraction and solvent amount) than maceration method.

  14. 31 CFR 354.7 - Withdrawal of eligible Book-entry Sallie Mae Securities for conversion to definitive form.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 31 Money and Finance:Treasury 2 2011-07-01 2011-07-01 false Withdrawal of eligible Book-entry... PUBLIC DEBT REGULATIONS GOVERNING BOOK-ENTRY SECURITIES OF THE STUDENT LOAN MARKETING ASSOCIATION (SALLIE MAE) § 354.7 Withdrawal of eligible Book-entry Sallie Mae Securities for conversion to definitive form...

  15. 24 CFR 350.8 - Withdrawal of Eligible Book-entry Ginnie Mae Securities for Conversion to Definitive Form.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 24 Housing and Urban Development 2 2012-04-01 2012-04-01 false Withdrawal of Eligible Book-entry... ASSOCIATION, DEPARTMENT OF HOUSING AND URBAN DEVELOPMENT BOOK-ENTRY PROCEDURES § 350.8 Withdrawal of Eligible Book-entry Ginnie Mae Securities for Conversion to Definitive Form. (a) Eligible book-entry Ginnie Mae...

  16. 24 CFR 350.8 - Withdrawal of Eligible Book-entry Ginnie Mae Securities for Conversion to Definitive Form.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 24 Housing and Urban Development 2 2013-04-01 2013-04-01 false Withdrawal of Eligible Book-entry... ASSOCIATION, DEPARTMENT OF HOUSING AND URBAN DEVELOPMENT BOOK-ENTRY PROCEDURES § 350.8 Withdrawal of Eligible Book-entry Ginnie Mae Securities for Conversion to Definitive Form. (a) Eligible book-entry Ginnie Mae...

  17. Accuracy evaluation of Fourier series analysis and singular spectrum analysis for predicting the volume of motorcycle sales in Indonesia

    NASA Astrophysics Data System (ADS)

    Sasmita, Yoga; Darmawan, Gumgum

    2017-08-01

    This research aims to evaluate the performance of forecasting by Fourier Series Analysis (FSA) and Singular Spectrum Analysis (SSA) which are more explorative and not requiring parametric assumption. Those methods are applied to predicting the volume of motorcycle sales in Indonesia from January 2005 to December 2016 (monthly). Both models are suitable for seasonal and trend component data. Technically, FSA defines time domain as the result of trend and seasonal component in different frequencies which is difficult to identify in the time domain analysis. With the hidden period is 2,918 ≈ 3 and significant model order is 3, FSA model is used to predict testing data. Meanwhile, SSA has two main processes, decomposition and reconstruction. SSA decomposes the time series data into different components. The reconstruction process starts with grouping the decomposition result based on similarity period of each component in trajectory matrix. With the optimum of window length (L = 53) and grouping effect (r = 4), SSA predicting testing data. Forecasting accuracy evaluation is done based on Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The result shows that in the next 12 month, SSA has MAPE = 13.54 percent, MAE = 61,168.43 and RMSE = 75,244.92 and FSA has MAPE = 28.19 percent, MAE = 119,718.43 and RMSE = 142,511.17. Therefore, to predict volume of motorcycle sales in the next period should use SSA method which has better performance based on its accuracy.

  18. Determination of Magneto-crystalline Anisotropy Energy (MAE) Of ordered L10 CoPt and FePt nanoparticles

    NASA Astrophysics Data System (ADS)

    Alsaad, A.; Ahmad, A. A.; Shukri, A. A.; Bani-Younes, O. A.

    2018-02-01

    The structural and magnetic properties of both L10 ordered FePt and CoPt nanoparticles make them potential candidates for optical-electronic and magneto-optical devices. First, we carried out an ab initio total energy minimization study to find the geometrical optimization of both L10 phases of FePt and CoPt nanoparticles. Then, we investigated the magnetocrystalline anisotropy energy (MAE) of both systems along special line joining the points of high symmetry (A,B and C points) using super-cell slap approach with alternating layers Fe/Co and Pt along the (001) direction. We found that the point (A) has the highest MAE value for both systems, where the value of MAE in FePt is 8.89 × 107 erg/cm3 and in CoPt is 6.40 × 107 erg/cm3. Our spin density based calculations indicate that large spin-orbit interaction and the hybridization between Pt 5d states and Fe/Co 3d states are the dominant factors in determining the MAE in both systems.

  19. Assignment of the relative and absolute stereochemistry of two novel epoxides using NMR and DFT-GIAO calculations

    NASA Astrophysics Data System (ADS)

    Moraes, F. C.; Alvarenga, E. S.; Demuner, A. J.; Viana, V. M.

    2018-07-01

    Considering the potential biological application of isobenzofuranones, especially as agrochemical defensives, two novel epoxides, (1aR,2R,2aR,5S,5aS,6S,6aS)-5-(hydroxymethyl)hexahydro-2,6-methanooxireno[2,3-f]isobenzofuran-3(1aH)-one (9), and (1aS,2S,2aR,5S,5aS,6R,6aR)-5-(hydroxymethyl)hexahydro-2,6-methanooxireno[2,3-f]isobenzofuran-3(1aH)-one (10), were synthesized from the readily available D-mannitol in six steps. The multiplicities of the hydrogens located at the bridge of the bicycle are distinct for epoxides 9 and 10 due to W coupling, and this feature was employed to confirm the assignment of these nuclei. Besides analyses of the 2D NMR spectra, the assignments of the nuclei at the epoxide ring were also inferred from information obtained by theoretical calculations. The calculated 1H and 13C NMR chemical shifts for eight candidate structures were compared with the experimental chemical shifts of 9 and 10 by measuring the mean absolute errors (MAE) and by the DP4 statistical analysis. The structures and relative configurations of 9, and 10 were determined via NMR spectroscopy assisted with theoretical calculations. As consequence of the enantioselective syntheses starting from a natural polyol, the absolute configurations of the epoxides 9 and 10 were also defined.

  20. Does exposure to simulated patient cases improve accuracy of clinicians' predictive value estimates of diagnostic test results? A within-subjects experiment at St Michael's Hospital, Toronto, Canada.

    PubMed

    Armstrong, Bonnie; Spaniol, Julia; Persaud, Nav

    2018-02-13

    Clinicians often overestimate the probability of a disease given a positive test result (positive predictive value; PPV) and the probability of no disease given a negative test result (negative predictive value; NPV). The purpose of this study was to investigate whether experiencing simulated patient cases (ie, an 'experience format') would promote more accurate PPV and NPV estimates compared with a numerical format. Participants were presented with information about three diagnostic tests for the same fictitious disease and were asked to estimate the PPV and NPV of each test. Tests varied with respect to sensitivity and specificity. Information about each test was presented once in the numerical format and once in the experience format. The study used a 2 (format: numerical vs experience) × 3 (diagnostic test: gold standard vs low sensitivity vs low specificity) within-subjects design. The study was completed online, via Qualtrics (Provo, Utah, USA). 50 physicians (12 clinicians and 38 residents) from the Department of Family and Community Medicine at St Michael's Hospital in Toronto, Canada, completed the study. All participants had completed at least 1 year of residency. Estimation accuracy was quantified by the mean absolute error (MAE; absolute difference between estimate and true predictive value). PPV estimation errors were larger in the numerical format (MAE=32.6%, 95% CI 26.8% to 38.4%) compared with the experience format (MAE=15.9%, 95% CI 11.8% to 20.0%, d =0.697, P<0.001). Likewise, NPV estimation errors were larger in the numerical format (MAE=24.4%, 95% CI 14.5% to 34.3%) than in the experience format (MAE=11.0%, 95% CI 6.5% to 15.5%, d =0.303, P=0.015). Exposure to simulated patient cases promotes accurate estimation of predictive values in clinicians. This finding carries implications for diagnostic training and practice. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights

  1. African-American Soul Force: Dance, Music and Vera Mae Green.

    ERIC Educational Resources Information Center

    Bolles, A. Lynn

    1986-01-01

    The Black anthropologist, Vera Mae Green, is featured in this analysis of the concept of soul as applied to African-Americans. Music and dance are used to express soul in cultural context. But soul is also a force, an energy which encompasses the Black experience and makes Black culture persevere. (VM)

  2. Time series model for forecasting the number of new admission inpatients.

    PubMed

    Zhou, Lingling; Zhao, Ping; Wu, Dongdong; Cheng, Cheng; Huang, Hao

    2018-06-15

    Hospital crowding is a rising problem, effective predicting and detecting managment can helpful to reduce crowding. Our team has successfully proposed a hybrid model combining both the autoregressive integrated moving average (ARIMA) and the nonlinear autoregressive neural network (NARNN) models in the schistosomiasis and hand, foot, and mouth disease forecasting study. In this paper, our aim is to explore the application of the hybrid ARIMA-NARNN model to track the trends of the new admission inpatients, which provides a methodological basis for reducing crowding. We used the single seasonal ARIMA (SARIMA), NARNN and the hybrid SARIMA-NARNN model to fit and forecast the monthly and daily number of new admission inpatients. The root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) were used to compare the forecasting performance among the three models. The modeling time range of monthly data included was from January 2010 to June 2016, July to October 2016 as the corresponding testing data set. The daily modeling data set was from January 4 to September 4, 2016, while the testing time range included was from September 5 to October 2, 2016. For the monthly data, the modeling RMSE and the testing RMSE, MAE and MAPE of SARIMA-NARNN model were less than those obtained from the single SARIMA or NARNN model, but the MAE and MAPE of modeling performance of SARIMA-NARNN model did not improve. For the daily data, all RMSE, MAE and MAPE of NARNN model were the lowest both in modeling stage and testing stage. Hybrid model does not necessarily outperform its constituents' performances. It is worth attempting to explore the reliable model to forecast the number of new admission inpatients from different data.

  3. 78 FR 77450 - Fannie Mae and Freddie Mac Loan Purchase Limits: Request for Public Input on Implementation Issues

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-12-23

    ... reductions in Freddie Mac's and Fannie Mae's loan purchase limits. In short, no final decision on loan... decision to direct the setting of new and lower loan purchase limits by the Enterprises. A Plan for Setting... FEDERAL HOUSING FINANCE AGENCY [No. 2013-N-18] Fannie Mae and Freddie Mac Loan Purchase Limits...

  4. Estimates of the absolute error and a scheme for an approximate solution to scheduling problems

    NASA Astrophysics Data System (ADS)

    Lazarev, A. A.

    2009-02-01

    An approach is proposed for estimating absolute errors and finding approximate solutions to classical NP-hard scheduling problems of minimizing the maximum lateness for one or many machines and makespan is minimized. The concept of a metric (distance) between instances of the problem is introduced. The idea behind the approach is, given the problem instance, to construct another instance for which an optimal or approximate solution can be found at the minimum distance from the initial instance in the metric introduced. Instead of solving the original problem (instance), a set of approximating polynomially/pseudopolynomially solvable problems (instances) are considered, an instance at the minimum distance from the given one is chosen, and the resulting schedule is then applied to the original instance.

  5. Comparison of Accuracy in Intraocular Lens Power Calculation by Measuring Axial Length with Immersion Ultrasound Biometry and Partial Coherence Interferometry.

    PubMed

    Ruangsetakit, Varee

    2015-11-01

    To re-examine relative accuracy of intraocular lens (IOL) power calculation of immersion ultrasound biometry (IUB) and partial coherence interferometry (PCI) based on a new approach that limits its interest on the cases in which the IUB's IOL and PCI's IOL assignments disagree. Prospective observational study of 108 eyes that underwent cataract surgeries at Taksin Hospital. Two halves ofthe randomly chosen sample eyes were implanted with the IUB- and PCI-assigned lens. Postoperative refractive errors were measured in the fifth week. More accurate calculation was based on significantly smaller mean absolute errors (MAEs) and root mean squared errors (RMSEs) away from emmetropia. The distributions of the errors were examined to ensure that the higher accuracy was significant clinically as well. The (MAEs, RMSEs) were smaller for PCI of (0.5106 diopter (D), 0.6037D) than for IUB of (0.7000D, 0.8062D). The higher accuracy was principally contributedfrom negative errors, i.e., myopia. The MAEs and RMSEs for (IUB, PCI)'s negative errors were (0.7955D, 0.5185D) and (0.8562D, 0.5853D). Their differences were significant. The 72.34% of PCI errors fell within a clinically accepted range of ± 0.50D, whereas 50% of IUB errors did. PCI's higher accuracy was significant statistically and clinically, meaning that lens implantation based on PCI's assignments could improve postoperative outcomes over those based on IUB's assignments.

  6. An affordable cuff-less blood pressure estimation solution.

    PubMed

    Jain, Monika; Kumar, Niranjan; Deb, Sujay

    2016-08-01

    This paper presents a cuff-less hypertension pre-screening device that non-invasively monitors the Blood Pressure (BP) and Heart Rate (HR) continuously. The proposed device simultaneously records two clinically significant and highly correlated biomedical signals, viz., Electrocardiogram (ECG) and Photoplethysmogram (PPG). The device provides a common data acquisition platform that can interface with PC/laptop, Smart phone/tablet and Raspberry-pi etc. The hardware stores and processes the recorded ECG and PPG in order to extract the real-time BP and HR using kernel regression approach. The BP and HR estimation error is measured in terms of normalized mean square error, Error Standard Deviation (ESD) and Mean Absolute Error (MAE), with respect to a clinically proven digital BP monitor (OMRON HBP1300). The computed error falls under the maximum standard allowable error mentioned by Association for the Advancement of Medical Instrumentation; MAE <; 5 mmHg and ESD <; 8mmHg. The results are validated using two-tailed dependent sample t-test also. The proposed device is a portable low-cost home and clinic bases solution for continuous health monitoring.

  7. Palynology and organic/isotope geochemistry of the Mae Moh Basin, Northern Thailand

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Minh, L.V.; Abrajano, T.; Burden, E.

    The Mae Moh basin is one of several Tertiary intermontane basins in northern Thailand, whose evolution has been linked to the collision of the Indian plate with the Eurasian plate since the early Eocene. As in most of these basins, lacustrine/swamp sedimentation in the Mae Moh basin can be broadly divided into an Oligocene to Miocene synrift sequence and a Miocene to Quarternary postrift sequence. The dominance of swamp flora recognized from spore and pollen assemblages (e.g., Polypodiidites usmensis, Verrucatosporites, Cyrtostachys), as well as the abundance of macrophytes and woody debris, indicate overwhelming hot and humid swamp conditions, with lakemore » development restricted to relatively small areas. The distribution of alkanes and their compound-specific carbon isotope compositions are used to further show climatic variations affecting the lake/swamp ecology during the deposition of the synrift sequence.« less

  8. Experiments on the applicability of MAE techniques for predicting sound diffraction by irregular terrains. [Matched Asymptotic Expansion

    NASA Technical Reports Server (NTRS)

    Berthelot, Yves H.; Pierce, Allan D.; Kearns, James A.

    1987-01-01

    The sound field diffracted by a single smooth hill of finite impedance is studied both analytically, within the context of the theory of Matched Asymptotic Expansions (MAE), and experimentally, under laboratory scale modeling conditions. Special attention is given to the sound field on the diffracting surface and throughout the transition region between the illuminated and the shadow zones. The MAE theory yields integral equations that are amenable to numerical computations. Experimental results are obtained with a spark source producing a pulse of 42 microsec duration and about 130 Pa at 1 m. The insertion loss of the hill is inferred from measurements of the acoustic signals at two locations in the field, with subsequent Fourier analysis on an IBM PC/AT. In general, experimental results support the predictions of the MAE theory, and provide a basis for the analysis of more complicated geometries.

  9. Modeling and forecasting of KLCI weekly return using WT-ANN integrated model

    NASA Astrophysics Data System (ADS)

    Liew, Wei-Thong; Liong, Choong-Yeun; Hussain, Saiful Izzuan; Isa, Zaidi

    2013-04-01

    The forecasting of weekly return is one of the most challenging tasks in investment since the time series are volatile and non-stationary. In this study, an integrated model of wavelet transform and artificial neural network, WT-ANN is studied for modeling and forecasting of KLCI weekly return. First, the WT is applied to decompose the weekly return time series in order to eliminate noise. Then, a mathematical model of the time series is constructed using the ANN. The performance of the suggested model will be evaluated by root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE). The result shows that the WT-ANN model can be considered as a feasible and powerful model for time series modeling and prediction.

  10. [Application of wavelet neural networks model to forecast incidence of syphilis].

    PubMed

    Zhou, Xian-Feng; Feng, Zi-Jian; Yang, Wei-Zhong; Li, Xiao-Song

    2011-07-01

    To apply Wavelet Neural Networks (WNN) model to forecast incidence of Syphilis. Back Propagation Neural Network (BPNN) and WNN were developed based on the monthly incidence of Syphilis in Sichuan province from 2004 to 2008. The accuracy of forecast was compared between the two models. In the training approximation, the mean absolute error (MAE), rooted mean square error (RMSE) and mean absolute percentage error (MAPE) were 0.0719, 0.0862 and 11.52% respectively for WNN, and 0.0892, 0.1183 and 14.87% respectively for BPNN. The three indexes for generalization of models were 0.0497, 0.0513 and 4.60% for WNN, and 0.0816, 0.1119 and 7.25% for BPNN. WNN is a better model for short-term forecasting of Syphilis.

  11. QSAR modeling of human serum protein binding with several modeling techniques utilizing structure-information representation.

    PubMed

    Votano, Joseph R; Parham, Marc; Hall, L Mark; Hall, Lowell H; Kier, Lemont B; Oloff, Scott; Tropsha, Alexander

    2006-11-30

    Four modeling techniques, using topological descriptors to represent molecular structure, were employed to produce models of human serum protein binding (% bound) on a data set of 1008 experimental values, carefully screened from publicly available sources. To our knowledge, this data is the largest set on human serum protein binding reported for QSAR modeling. The data was partitioned into a training set of 808 compounds and an external validation test set of 200 compounds. Partitioning was accomplished by clustering the compounds in a structure descriptor space so that random sampling of 20% of the whole data set produced an external test set that is a good representative of the training set with respect to both structure and protein binding values. The four modeling techniques include multiple linear regression (MLR), artificial neural networks (ANN), k-nearest neighbors (kNN), and support vector machines (SVM). With the exception of the MLR model, the ANN, kNN, and SVM QSARs were ensemble models. Training set correlation coefficients and mean absolute error ranged from r2=0.90 and MAE=7.6 for ANN to r2=0.61 and MAE=16.2 for MLR. Prediction results from the validation set yielded correlation coefficients and mean absolute errors which ranged from r2=0.70 and MAE=14.1 for ANN to a low of r2=0.59 and MAE=18.3 for the SVM model. Structure descriptors that contribute significantly to the models are discussed and compared with those found in other published models. For the ANN model, structure descriptor trends with respect to their affects on predicted protein binding can assist the chemist in structure modification during the drug design process.

  12. Hydraulic head estimation at unobserved locations: Approximating the distribution of the absolute error based on geologic interpretations

    NASA Astrophysics Data System (ADS)

    Langousis, Andreas; Kaleris, Vassilios; Xeygeni, Vagia; Magkou, Foteini

    2017-04-01

    Assessing the availability of groundwater reserves at a regional level, requires accurate and robust hydraulic head estimation at multiple locations of an aquifer. To that extent, one needs groundwater observation networks that can provide sufficient information to estimate the hydraulic head at unobserved locations. The density of such networks is largely influenced by the spatial distribution of the hydraulic conductivity in the aquifer, and it is usually determined through trial-and-error, by solving the groundwater flow based on a properly selected set of alternative but physically plausible geologic structures. In this work, we use: 1) dimensional analysis, and b) a pulse-based stochastic model for simulation of synthetic aquifer structures, to calculate the distribution of the absolute error in hydraulic head estimation as a function of the standardized distance from the nearest measuring locations. The resulting distributions are proved to encompass all possible small-scale structural dependencies, exhibiting characteristics (bounds, multi-modal features etc.) that can be explained using simple geometric arguments. The obtained results are promising, pointing towards the direction of establishing design criteria based on large-scale geologic maps.

  13. Role of dispersion corrected hybrid GGA class in accurately calculating the bond dissociation energy of carbon halogen bond: A benchmark study

    NASA Astrophysics Data System (ADS)

    Kosar, Naveen; Mahmood, Tariq; Ayub, Khurshid

    2017-12-01

    Benchmark study has been carried out to find a cost effective and accurate method for bond dissociation energy (BDE) of carbon halogen (Csbnd X) bond. BDE of C-X bond plays a vital role in chemical reactions, particularly for kinetic barrier and thermochemistry etc. The compounds (1-16, Fig. 1) with Csbnd X bond used for current benchmark study are important reactants in organic, inorganic and bioorganic chemistry. Experimental data of Csbnd X bond dissociation energy is compared with theoretical results. The statistical analysis tools such as root mean square deviation (RMSD), standard deviation (SD), Pearson's correlation (R) and mean absolute error (MAE) are used for comparison. Overall, thirty-one density functionals from eight different classes of density functional theory (DFT) along with Pople and Dunning basis sets are evaluated. Among different classes of DFT, the dispersion corrected range separated hybrid GGA class along with 6-31G(d), 6-311G(d), aug-cc-pVDZ and aug-cc-pVTZ basis sets performed best for bond dissociation energy calculation of C-X bond. ωB97XD show the best performance with less deviations (RMSD, SD), mean absolute error (MAE) and a significant Pearson's correlation (R) when compared to experimental data. ωB97XD along with Pople basis set 6-311g(d) has RMSD, SD, R and MAE of 3.14 kcal mol-1, 3.05 kcal mol-1, 0.97 and -1.07 kcal mol-1, respectively.

  14. Absolute vs. relative error characterization of electromagnetic tracking accuracy

    NASA Astrophysics Data System (ADS)

    Matinfar, Mohammad; Narayanasamy, Ganesh; Gutierrez, Luis; Chan, Raymond; Jain, Ameet

    2010-02-01

    Electromagnetic (EM) tracking systems are often used for real time navigation of medical tools in an Image Guided Therapy (IGT) system. They are specifically advantageous when the medical device requires tracking within the body of a patient where line of sight constraints prevent the use of conventional optical tracking. EM tracking systems are however very sensitive to electromagnetic field distortions. These distortions, arising from changes in the electromagnetic environment due to the presence of conductive ferromagnetic surgical tools or other medical equipment, limit the accuracy of EM tracking, in some cases potentially rendering tracking data unusable. We present a mapping method for the operating region over which EM tracking sensors are used, allowing for characterization of measurement errors, in turn providing physicians with visual feedback about measurement confidence or reliability of localization estimates. In this instance, we employ a calibration phantom to assess distortion within the operating field of the EM tracker and to display in real time the distribution of measurement errors, as well as the location and extent of the field associated with minimal spatial distortion. The accuracy is assessed relative to successive measurements. Error is computed for a reference point and consecutive measurement errors are displayed relative to the reference in order to characterize the accuracy in near-real-time. In an initial set-up phase, the phantom geometry is calibrated by registering the data from a multitude of EM sensors in a non-ferromagnetic ("clean") EM environment. The registration results in the locations of sensors with respect to each other and defines the geometry of the sensors in the phantom. In a measurement phase, the position and orientation data from all sensors are compared with the known geometry of the sensor spacing, and localization errors (displacement and orientation) are computed. Based on error thresholds provided by the

  15. Sorption characteristics of cadmium in a clay soil of Mae Ku creek, Tak Province, Thailand

    NASA Astrophysics Data System (ADS)

    Thunyawatcharakul, P.; Chotpantarat, S.

    2018-05-01

    Mae Sot is a district in Tak province, the northern part of Thailand where has encountered with cadmium (Cd) contaminated in soils. Exposure of Cd can lead to severe health effect, for examples, bone softening, osteoporosis, renal dysfunction, and Itai-Itai disease. This study aims at elucidating sorption behavior of Cd in the contaminated soil collected from Mae Ku creek, Mae Sot district, Thailand. Batch sorption experiment was conducted in order to investigate sorption characteristics of Cd onto the contaminated soil. The soil sample taken from the study area consists of 26% sand, 16% silt 58% clay, which categorized as a clay soil, based on USDA classification. Soil pH is slightly alkaline (pH∼7.7) and organic matter in the soil is 2.93%. The initial concentration in the batch sorption experiment was in the range from 0- 200 ppm. The result from the batch sorption experiment showed that soil sample can adsorb Cd up to 173.5 ppm and the sorption behavior of the soil sample can be well described by Freundlich isotherm, indicating the multilayer sorption (R2 = 0.9964), with Freundlich constants of 0.312 and 1.760 L g-1 for 1/n and Kf, respectively.

  16. [Aquatic Ecological Index based on freshwater (ICE(RN-MAE)) for the Rio Negro watershed, Colombia].

    PubMed

    Forero, Laura Cristina; Longo, Magnolia; John Jairo, Ramirez; Guillermo, Chalar

    2014-04-01

    Aquatic Ecological Index based on freshwater (ICE(RN-MAE)) for the Rio Negro watershed, Colombia. Available indices to assess the ecological status of rivers in Colombia are mostly based on subjective hypotheses about macroinvertebrate tolerance to pollution, which have important limitations. Here we present the application of a method to establish an index of ecological quality for lotic systems in Colombia. The index, based on macroinvertebrate abundance and physicochemical variables, was developed as an alternative to the BMWP-Col index. The method consists on determining an environmental gradient from correlations between physicochemical variables and abundance. The scores obtained in each sampling point are used in a standardized correlation for a model of weighted averages (WA). In the WA model abundances are also weighted to estimate the optimum and tolerance values of each taxon; using this information we estimated the index of ecological quality based also on macroinvertebrate (ICE(RN-MAE)) abundance in each sampling site. Subsequently, we classified all sites using the index and concentrations of total phosphorus (TP) in a cluster analysis. Using TP and ICE(RN-MAE), mean, maximum, minimum and standard deviation, we defined threshold values corresponding to three categories of ecological status: good, fair and critical.

  17. Neural network cloud top pressure and height for MODIS

    NASA Astrophysics Data System (ADS)

    Håkansson, Nina; Adok, Claudia; Thoss, Anke; Scheirer, Ronald; Hörnquist, Sara

    2018-06-01

    Cloud top height retrieval from imager instruments is important for nowcasting and for satellite climate data records. A neural network approach for cloud top height retrieval from the imager instrument MODIS (Moderate Resolution Imaging Spectroradiometer) is presented. The neural networks are trained using cloud top layer pressure data from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) dataset. Results are compared with two operational reference algorithms for cloud top height: the MODIS Collection 6 Level 2 height product and the cloud top temperature and height algorithm in the 2014 version of the NWC SAF (EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Satellite Application Facility on Support to Nowcasting and Very Short Range Forecasting) PPS (Polar Platform System). All three techniques are evaluated using both CALIOP and CPR (Cloud Profiling Radar for CloudSat (CLOUD SATellite)) height. Instruments like AVHRR (Advanced Very High Resolution Radiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) contain fewer channels useful for cloud top height retrievals than MODIS, therefore several different neural networks are investigated to test how infrared channel selection influences retrieval performance. Also a network with only channels available for the AVHRR1 instrument is trained and evaluated. To examine the contribution of different variables, networks with fewer variables are trained. It is shown that variables containing imager information for neighboring pixels are very important. The error distributions of the involved cloud top height algorithms are found to be non-Gaussian. Different descriptive statistic measures are presented and it is exemplified that bias and SD (standard deviation) can be misleading for non-Gaussian distributions. The median and mode are found to better describe the tendency of the error distributions and IQR (interquartile range) and MAE (mean absolute error) are found

  18. The PMA Catalogue: 420 million positions and absolute proper motions

    NASA Astrophysics Data System (ADS)

    Akhmetov, V. S.; Fedorov, P. N.; Velichko, A. B.; Shulga, V. M.

    2017-07-01

    We present a catalogue that contains about 420 million absolute proper motions of stars. It was derived from the combination of positions from Gaia DR1 and 2MASS, with a mean difference of epochs of about 15 yr. Most of the systematic zonal errors inherent in the 2MASS Catalogue were eliminated before deriving the absolute proper motions. The absolute calibration procedure (zero-pointing of the proper motions) was carried out using about 1.6 million positions of extragalactic sources. The mean formal error of the absolute calibration is less than 0.35 mas yr-1. The derived proper motions cover the whole celestial sphere without gaps for a range of stellar magnitudes from 8 to 21 mag. In the sky areas where the extragalactic sources are invisible (the avoidance zone), a dedicated procedure was used that transforms the relative proper motions into absolute ones. The rms error of proper motions depends on stellar magnitude and ranges from 2-5 mas yr-1 for stars with 10 mag < G < 17 mag to 5-10 mas yr-1 for faint ones. The present catalogue contains the Gaia DR1 positions of stars for the J2015 epoch. The system of the PMA proper motions does not depend on the systematic errors of the 2MASS positions, and in the range from 14 to 21 mag represents an independent realization of a quasi-inertial reference frame in the optical and near-infrared wavelength range. The Catalogue also contains stellar magnitudes taken from the Gaia DR1 and 2MASS catalogues. A comparison of the PMA proper motions of stars with similar data from certain recent catalogues has been undertaken.

  19. High-resolution spatial databases of monthly climate variables (1961-2010) over a complex terrain region in southwestern China

    NASA Astrophysics Data System (ADS)

    Wu, Wei; Xu, An-Ding; Liu, Hong-Bin

    2015-01-01

    Climate data in gridded format are critical for understanding climate change and its impact on eco-environment. The aim of the current study is to develop spatial databases for three climate variables (maximum, minimum temperatures, and relative humidity) over a large region with complex topography in southwestern China. Five widely used approaches including inverse distance weighting, ordinary kriging, universal kriging, co-kriging, and thin-plate smoothing spline were tested. Root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) showed that thin-plate smoothing spline with latitude, longitude, and elevation outperformed other models. Average RMSE, MAE, and MAPE of the best models were 1.16 °C, 0.74 °C, and 7.38 % for maximum temperature; 0.826 °C, 0.58 °C, and 6.41 % for minimum temperature; and 3.44, 2.28, and 3.21 % for relative humidity, respectively. Spatial datasets of annual and monthly climate variables with 1-km resolution covering the period 1961-2010 were then obtained using the best performance methods. Comparative study showed that the current outcomes were in well agreement with public datasets. Based on the gridded datasets, changes in temperature variables were investigated across the study area. Future study might be needed to capture the uncertainty induced by environmental conditions through remote sensing and knowledge-based methods.

  20. Comparison of artificial intelligence methods and empirical equations to estimate daily solar radiation

    NASA Astrophysics Data System (ADS)

    Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

    2016-08-01

    In the present research, three artificial intelligence methods including Gene Expression Programming (GEP), Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) as well as, 48 empirical equations (10, 12 and 26 equations were temperature-based, sunshine-based and meteorological parameters-based, respectively) were used to estimate daily solar radiation in Kerman, Iran in the period of 1992-2009. To develop the GEP, ANN and ANFIS models, depending on the used empirical equations, various combinations of minimum air temperature, maximum air temperature, mean air temperature, extraterrestrial radiation, actual sunshine duration, maximum possible sunshine duration, sunshine duration ratio, relative humidity and precipitation were considered as inputs in the mentioned intelligent methods. To compare the accuracy of empirical equations and intelligent models, root mean square error (RMSE), mean absolute error (MAE), mean absolute relative error (MARE) and determination coefficient (R2) indices were used. The results showed that in general, sunshine-based and meteorological parameters-based scenarios in ANN and ANFIS models presented high accuracy than mentioned empirical equations. Moreover, the most accurate method in the studied region was ANN11 scenario with five inputs. The values of RMSE, MAE, MARE and R2 indices for the mentioned model were 1.850 MJ m-2 day-1, 1.184 MJ m-2 day-1, 9.58% and 0.935, respectively.

  1. Comparison of INAR(1)-Poisson model and Markov prediction model in forecasting the number of DHF patients in west java Indonesia

    NASA Astrophysics Data System (ADS)

    Ahdika, Atina; Lusiyana, Novyan

    2017-02-01

    World Health Organization (WHO) noted Indonesia as the country with the highest dengue (DHF) cases in Southeast Asia. There are no vaccine and specific treatment for DHF. One of the efforts which can be done by both government and resident is doing a prevention action. In statistics, there are some methods to predict the number of DHF cases to be used as the reference to prevent the DHF cases. In this paper, a discrete time series model, INAR(1)-Poisson model in specific, and Markov prediction model are used to predict the number of DHF patients in West Java Indonesia. The result shows that MPM is the best model since it has the smallest value of MAE (mean absolute error) and MAPE (mean absolute percentage error).

  2. [Prediction of schistosomiasis infection rates of population based on ARIMA-NARNN model].

    PubMed

    Ke-Wei, Wang; Yu, Wu; Jin-Ping, Li; Yu-Yu, Jiang

    2016-07-12

    To explore the effect of the autoregressive integrated moving average model-nonlinear auto-regressive neural network (ARIMA-NARNN) model on predicting schistosomiasis infection rates of population. The ARIMA model, NARNN model and ARIMA-NARNN model were established based on monthly schistosomiasis infection rates from January 2005 to February 2015 in Jiangsu Province, China. The fitting and prediction performances of the three models were compared. Compared to the ARIMA model and NARNN model, the mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of the ARIMA-NARNN model were the least with the values of 0.011 1, 0.090 0 and 0.282 4, respectively. The ARIMA-NARNN model could effectively fit and predict schistosomiasis infection rates of population, which might have a great application value for the prevention and control of schistosomiasis.

  3. Measuring teachers' knowledge of attention deficit hyperactivity disorder: the MAE-TDAH Questionnaire.

    PubMed

    Soroa, Marian; Balluerka, Nekane; Gorostiaga, Arantxa

    2014-10-28

    The lack of methodological rigor is frequent in most of instruments developed to assess the knowledge of teachers regarding Attention Deficit Hyperactivity Disorder (ADHD). The aim of this study was to develop a questionnaire, namely Questionnaire for the evaluation of teachers' knowledge of ADHD (MAE-TDAH), for measuring the level of knowledge about ADHD of infant and primary school teachers. A random sample of 526 teachers from 57 schools in the Autonomous Community of the Basque Country and Navarre was used for the analysis of the psychometric properties of the instrument. The participant teachers age range was between 22 and 65 (M = 42.59; SD = 10.89), and there were both generalist and specialized teachers. The measure showed a 4 factor structure (Etiology of ADHD, Symptoms/Diagnosis of ADHD, General information about ADHD and Treatment of ADHD) with adequate internal consistency (Omega values ranged between .83 and .91) and temporal stability indices (Spearman's Rho correlation values ranged between .62 and .79). Furthermore, evidence of convergent and external validity was obtained. Results suggest that the MAE-TDAH is a valid and reliable measure when it comes to evaluating teachers' level of knowledge of ADHD.

  4. DOE Office of Scientific and Technical Information (OSTI.GOV)

    Verma, Prakash; Bartlett, Rodney J., E-mail: bartlett@qtp.ufl.edu

    Core excitation energies are computed with time-dependent density functional theory (TD-DFT) using the ionization energy corrected exchange and correlation potential QTP(0,0). QTP(0,0) provides C, N, and O K-edge spectra to about an electron volt. A mean absolute error (MAE) of 0.77 and a maximum error of 2.6 eV is observed for QTP(0,0) for many small molecules. TD-DFT based on QTP (0,0) is then used to describe the core-excitation spectra of the 22 amino acids. TD-DFT with conventional functionals greatly underestimates core excitation energies, largely due to the significant error in the Kohn-Sham occupied eigenvalues. To the contrary, the ionization energymore » corrected potential, QTP(0,0), provides excellent approximations (MAE of 0.53 eV) for core ionization energies as eigenvalues of the Kohn-Sham equations. As a consequence, core excitation energies are accurately described with QTP(0,0), as are the core ionization energies important in X-ray photoionization spectra or electron spectroscopy for chemical analysis.« less

  5. Increasing the applicability of density functional theory. V. X-ray absorption spectra with ionization potential corrected exchange and correlation potentials.

    PubMed

    Verma, Prakash; Bartlett, Rodney J

    2016-07-21

    Core excitation energies are computed with time-dependent density functional theory (TD-DFT) using the ionization energy corrected exchange and correlation potential QTP(0,0). QTP(0,0) provides C, N, and O K-edge spectra to about an electron volt. A mean absolute error (MAE) of 0.77 and a maximum error of 2.6 eV is observed for QTP(0,0) for many small molecules. TD-DFT based on QTP (0,0) is then used to describe the core-excitation spectra of the 22 amino acids. TD-DFT with conventional functionals greatly underestimates core excitation energies, largely due to the significant error in the Kohn-Sham occupied eigenvalues. To the contrary, the ionization energy corrected potential, QTP(0,0), provides excellent approximations (MAE of 0.53 eV) for core ionization energies as eigenvalues of the Kohn-Sham equations. As a consequence, core excitation energies are accurately described with QTP(0,0), as are the core ionization energies important in X-ray photoionization spectra or electron spectroscopy for chemical analysis.

  6. Modeling rainfall-runoff process using soft computing techniques

    NASA Astrophysics Data System (ADS)

    Kisi, Ozgur; Shiri, Jalal; Tombul, Mustafa

    2013-02-01

    Rainfall-runoff process was modeled for a small catchment in Turkey, using 4 years (1987-1991) of measurements of independent variables of rainfall and runoff values. The models used in the study were Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Gene Expression Programming (GEP) which are Artificial Intelligence (AI) approaches. The applied models were trained and tested using various combinations of the independent variables. The goodness of fit for the model was evaluated in terms of the coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), coefficient of efficiency (CE) and scatter index (SI). A comparison was also made between these models and traditional Multi Linear Regression (MLR) model. The study provides evidence that GEP (with RMSE=17.82 l/s, MAE=6.61 l/s, CE=0.72 and R2=0.978) is capable of modeling rainfall-runoff process and is a viable alternative to other applied artificial intelligence and MLR time-series methods.

  7. DNA methylation markers in combination with skeletal and dental ages to improve age estimation in children.

    PubMed

    Shi, Lei; Jiang, Fan; Ouyang, Fengxiu; Zhang, Jun; Wang, Zhimin; Shen, Xiaoming

    2018-03-01

    Age estimation is critical in forensic science, in competitive sports and games and in other age-related fields, but the current methods are suboptimal. The combination of age-associated DNA methylation markers with skeletal age (SA) and dental age (DA) may improve the accuracy and precision of age estimation, but no study has examined this topic. In the current study, we measured SA (GP, TW3-RUS, and TW3-Carpal methods) and DA (Demirjian and Willems methods) by X-ray examination in 124 Chinese children (78 boys and 46 girls) aged 6-15 years. To identify age-associated CpG sites, we analyzed methylome-wide DNA methylation profiling by using the Illumina HumanMethylation450 BeadChip system in 48 randomly selected children. Five CpG sites were identified as associated with chronologic age (CA), with an absolute value of Pearson's correlation coefficient (r)>0.5 (p<0.01) and a false discovery rate<0.01. The validation of age-associated CpG sites was performed using droplet digital PCR techniques in all 124 children. After validation, four CpG sites for boys and five CpG sites for girls were further adopted to build the age estimation model with SA and DA using multivariate linear stepwise regressions. These CpG sites were located at 4 known genes: DDO, PRPH2, DHX8, and ITGA2B and at one unknown gene with the Illumina ID number of 22398226. The accuracy of age estimation methods was compared according to the mean absolute error (MAE) and root mean square error (RMSE). The best single measure for SA was the TW3-RUS method (MAE=0.69years, RMSE=0.95years) in boys, and the GP method (MAE=0.74years, RMSE=0.94years) in girls. For DA, the Willems method was the best single measure for both boys (MAE=0.63years, RMSE=0.78years) and girls (MAE=0.54years, RMSE=0.68years). The models that incorporated SA and DA with the methylation levels of age-associated CpG sites provided the highest accuracy of age estimation in both boys (MAE=0.47years, R 2 =0.886) and girls (MAE=0.33years, R

  8. An exact algorithm for optimal MAE stack filter design.

    PubMed

    Dellamonica, Domingos; Silva, Paulo J S; Humes, Carlos; Hirata, Nina S T; Barrera, Junior

    2007-02-01

    We propose a new algorithm for optimal MAE stack filter design. It is based on three main ingredients. First, we show that the dual of the integer programming formulation of the filter design problem is a minimum cost network flow problem. Next, we present a decomposition principle that can be used to break this dual problem into smaller subproblems. Finally, we propose a specialization of the network Simplex algorithm based on column generation to solve these smaller subproblems. Using our method, we were able to efficiently solve instances of the filter problem with window size up to 25 pixels. To the best of our knowledge, this is the largest dimension for which this problem was ever solved exactly.

  9. Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

    PubMed Central

    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

  10. Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.

    PubMed

    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.

  11. Modeling number of claims and prediction of total claim amount

    NASA Astrophysics Data System (ADS)

    Acar, Aslıhan Şentürk; Karabey, Uǧur

    2017-07-01

    In this study we focus on annual number of claims of a private health insurance data set which belongs to a local insurance company in Turkey. In addition to Poisson model and negative binomial model, zero-inflated Poisson model and zero-inflated negative binomial model are used to model the number of claims in order to take into account excess zeros. To investigate the impact of different distributional assumptions for the number of claims on the prediction of total claim amount, predictive performances of candidate models are compared by using root mean square error (RMSE) and mean absolute error (MAE) criteria.

  12. Relationship between postoperative refractive outcomes and cataract density: multiple regression analysis.

    PubMed

    Ueda, Tetsuo; Ikeda, Hitoe; Ota, Takeo; Matsuura, Toyoaki; Hara, Yoshiaki

    2010-05-01

    To evaluate the relationship between cataract density and the deviation from the predicted refraction. Department of Ophthalmology, Nara Medical University, Kashihara, Japan. Axial length (AL) was measured in eyes with mainly nuclear cataract using partial coherence interferometry (IOLMaster). The postoperative AL was measured in pseudophakic mode. The AL difference was calculated by subtracting the postoperative AL from the preoperative AL. Cataract density was measured with the pupil dilated using anterior segment Scheimpflug imaging (EAS-1000). The predicted postoperative refraction was calculated using the SRK/T formula. The subjective refraction 3 months postoperatively was also measured. The mean absolute prediction error (MAE) (mean of absolute difference between predicted postoperative refraction and spherical equivalent of postoperative subjective refraction) was calculated. The relationship between the MAE and cataract density, age, preoperative visual acuity, anterior chamber depth, corneal radius of curvature, and AL difference was evaluated using multiple regression analysis. In the 96 eyes evaluated, the MAE was correlated with cataract density (r = 0.37, P = .001) and the AL difference (r = 0.34, P = .003) but not with the other parameters. The AL difference was correlated with cataract density (r = 0.53, P<.0001). The postoperative refractive outcome was affected by cataract density. This should be taken into consideration in eyes with a higher density cataract. (c) 2010 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

  13. Comparison of artificial intelligence techniques for prediction of soil temperatures in Turkey

    NASA Astrophysics Data System (ADS)

    Citakoglu, Hatice

    2017-10-01

    Soil temperature is a meteorological data directly affecting the formation and development of plants of all kinds. Soil temperatures are usually estimated with various models including the artificial neural networks (ANNs), adaptive neuro-fuzzy inference system (ANFIS), and multiple linear regression (MLR) models. Soil temperatures along with other climate data are recorded by the Turkish State Meteorological Service (MGM) at specific locations all over Turkey. Soil temperatures are commonly measured at 5-, 10-, 20-, 50-, and 100-cm depths below the soil surface. In this study, the soil temperature data in monthly units measured at 261 stations in Turkey having records of at least 20 years were used to develop relevant models. Different input combinations were tested in the ANN and ANFIS models to estimate soil temperatures, and the best combination of significant explanatory variables turns out to be monthly minimum and maximum air temperatures, calendar month number, depth of soil, and monthly precipitation. Next, three standard error terms (mean absolute error (MAE, °C), root mean squared error (RMSE, °C), and determination coefficient ( R 2 )) were employed to check the reliability of the test data results obtained through the ANN, ANFIS, and MLR models. ANFIS (RMSE 1.99; MAE 1.09; R 2 0.98) is found to outperform both ANN and MLR (RMSE 5.80, 8.89; MAE 1.89, 2.36; R 2 0.93, 0.91) in estimating soil temperature in Turkey.

  14. Assessment of Demirjian's 8-teeth technique of age estimation and Indian-specific formulas in an East Indian population: A cross-sectional study.

    PubMed

    Rath, Hemamalini; Rath, Rachna; Mahapatra, Sandeep; Debta, Tribikram

    2017-01-01

    The age of an individual can be assessed by a plethora of widely available tooth-based techniques, among which radiological methods prevail. The Demirjian's technique of age assessment based on tooth development stages has been extensively investigated in different populations of the world. The present study is to assess the applicability of Demirjian's modified 8-teeth technique in age estimation of population of East India (Odisha), utilizing Acharya's Indian-specific cubic functions. One hundred and six pretreatment orthodontic radiographs of patients in an age group of 7-23 years with representation from both genders were assessed for eight left mandibular teeth and scored as per the Demirjian's 9-stage criteria for teeth development stages. Age was calculated on the basis of Acharya's Indian formula. Statistical analysis was performed to compare the estimated and actual age. All data were analyzed using SPSS 20.0 (SPSS Inc., Chicago, Illinois, USA) and MS Excel Package. The results revealed that the mean absolute error (MAE) in age estimation of the entire sample was 1.3 years with 50% of the cases having an error rate within ± 1 year. The MAE in males and females (7-16 years) was 1.8 and 1.5, respectively. Likewise, the MAE in males and females (16.1-23 years) was 1.1 and 1.3, respectively. The low error rate in estimating age justifies the application of this modified technique and Acharya's Indian formulas in the present East Indian population.

  15. Quality Aware Compression of Electrocardiogram Using Principal Component Analysis.

    PubMed

    Gupta, Rajarshi

    2016-05-01

    Electrocardiogram (ECG) compression finds wide application in various patient monitoring purposes. Quality control in ECG compression ensures reconstruction quality and its clinical acceptance for diagnostic decision making. In this paper, a quality aware compression method of single lead ECG is described using principal component analysis (PCA). After pre-processing, beat extraction and PCA decomposition, two independent quality criteria, namely, bit rate control (BRC) or error control (EC) criteria were set to select optimal principal components, eigenvectors and their quantization level to achieve desired bit rate or error measure. The selected principal components and eigenvectors were finally compressed using a modified delta and Huffman encoder. The algorithms were validated with 32 sets of MIT Arrhythmia data and 60 normal and 30 sets of diagnostic ECG data from PTB Diagnostic ECG data ptbdb, all at 1 kHz sampling. For BRC with a CR threshold of 40, an average Compression Ratio (CR), percentage root mean squared difference normalized (PRDN) and maximum absolute error (MAE) of 50.74, 16.22 and 0.243 mV respectively were obtained. For EC with an upper limit of 5 % PRDN and 0.1 mV MAE, the average CR, PRDN and MAE of 9.48, 4.13 and 0.049 mV respectively were obtained. For mitdb data 117, the reconstruction quality could be preserved up to CR of 68.96 by extending the BRC threshold. The proposed method yields better results than recently published works on quality controlled ECG compression.

  16. How America Pays for College, 2014: Sallie Mae's National Study of College Students and Parents

    ERIC Educational Resources Information Center

    Sallie Mae, Inc., 2014

    2014-01-01

    Sallie Mae has conducted "How America Pays for College" annually since 2008, providing information about the resources American families invest in an undergraduate college education. This study focuses particularly on the planning and payment behaviors in a given academic year. Now in its seventh year, the study provides a compelling…

  17. 24 CFR 350.11 - Notice of Attachment for Ginnie Mae Securities in Book-entry System.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... Securities in Book-entry System. 350.11 Section 350.11 Housing and Urban Development Regulations Relating to... AND URBAN DEVELOPMENT BOOK-ENTRY PROCEDURES § 350.11 Notice of Attachment for Ginnie Mae Securities in Book-entry System. The interest of a debtor in a Security Entitlement may be reached by a creditor only...

  18. 24 CFR 350.11 - Notice of Attachment for Ginnie Mae Securities in Book-entry System.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... Securities in Book-entry System. 350.11 Section 350.11 Housing and Urban Development Regulations Relating to... AND URBAN DEVELOPMENT BOOK-ENTRY PROCEDURES § 350.11 Notice of Attachment for Ginnie Mae Securities in Book-entry System. The interest of a debtor in a Security Entitlement may be reached by a creditor only...

  19. 24 CFR 350.11 - Notice of Attachment for Ginnie Mae Securities in Book-entry System.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... Securities in Book-entry System. 350.11 Section 350.11 Housing and Urban Development Regulations Relating to... AND URBAN DEVELOPMENT BOOK-ENTRY PROCEDURES § 350.11 Notice of Attachment for Ginnie Mae Securities in Book-entry System. The interest of a debtor in a Security Entitlement may be reached by a creditor only...

  20. Applications and Comparisons of Four Time Series Models in Epidemiological Surveillance Data

    PubMed Central

    Young, Alistair A.; Li, Xiaosong

    2014-01-01

    Public health surveillance systems provide valuable data for reliable predication of future epidemic events. This paper describes a study that used nine types of infectious disease data collected through a national public health surveillance system in mainland China to evaluate and compare the performances of four time series methods, namely, two decomposition methods (regression and exponential smoothing), autoregressive integrated moving average (ARIMA) and support vector machine (SVM). The data obtained from 2005 to 2011 and in 2012 were used as modeling and forecasting samples, respectively. The performances were evaluated based on three metrics: mean absolute error (MAE), mean absolute percentage error (MAPE), and mean square error (MSE). The accuracy of the statistical models in forecasting future epidemic disease proved their effectiveness in epidemiological surveillance. Although the comparisons found that no single method is completely superior to the others, the present study indeed highlighted that the SVMs outperforms the ARIMA model and decomposition methods in most cases. PMID:24505382

  1. Absolute measurement of the extreme UV solar flux

    NASA Technical Reports Server (NTRS)

    Carlson, R. W.; Ogawa, H. S.; Judge, D. L.; Phillips, E.

    1984-01-01

    A windowless rare-gas ionization chamber has been developed to measure the absolute value of the solar extreme UV flux in the 50-575-A region. Successful results were obtained on a solar-pointing sounding rocket. The ionization chamber, operated in total absorption, is an inherently stable absolute detector of ionizing UV radiation and was designed to be independent of effects from secondary ionization and gas effusion. The net error of the measurement is + or - 7.3 percent, which is primarily due to residual outgassing in the instrument, other errors such as multiple ionization, photoelectron collection, and extrapolation to the zero atmospheric optical depth being small in comparison. For the day of the flight, Aug. 10, 1982, the solar irradiance (50-575 A), normalized to unit solar distance, was found to be 5.71 + or - 0.42 x 10 to the 10th photons per sq cm sec.

  2. How America Pays for College, 2009. Sallie Mae's National Study of College Students and Parents

    ERIC Educational Resources Information Center

    Sallie Mae, Inc., 2009

    2009-01-01

    Sallie Mae's study, "How America Pays for College 2009," conducted by Gallup, provides a picture of how families made the investment in higher education last academic year and how they are beginning to meet the challenges of the economic recession. Based on a nationally representative survey of college-going students and parents of undergraduates,…

  3. How America Pays for College, 2010. Sallie Mae's National Study of College Students and Parents

    ERIC Educational Resources Information Center

    Sallie Mae, Inc., 2010

    2010-01-01

    This report presents the findings of a quantitative survey research program that Gallup, Inc. conducted on behalf of Sallie Mae. The overall objective of the study was to determine how American families are paying for higher education. The study also measures public attitudes toward college and various topics related to funding college. To achieve…

  4. How America Saves for College, 2009. Sallie Mae's National Study of College Students and Parents

    ERIC Educational Resources Information Center

    Sallie Mae, Inc., 2009

    2009-01-01

    Sallie Mae's study, "How America Saves for College 2009," conducted by Gallup, provides a measure of the commitment parents have to helping their children reach higher education and whether and how they are saving for the investment. Based on a nationally representative survey of parents of children under age 18, the study found that without…

  5. Optimization of microwave assisted extraction (MAE) and soxhlet extraction of phenolic compound from licorice root.

    PubMed

    Karami, Zohreh; Emam-Djomeh, Zahra; Mirzaee, Habib Allah; Khomeiri, Morteza; Mahoonak, Alireza Sadeghi; Aydani, Emad

    2015-06-01

    In present study, response surface methodology was used to optimize extraction condition of phenolic compounds from licorice root by microwave application. Investigated factors were solvent (ethanol 80 %, methanol 80 % and water), liquid/solid ratio (10:1-25:1) and time (2-6 min). Experiments were designed according to the central composite rotatable design. The results showed that extraction conditions had significant effect on the extraction yield of phenolic compounds and antioxidant capacities. Optimal condition in microwave assisted method were ethanol 80 % as solvent, extraction time of 5-6 min and liquid/solid ratio of 12.7/1. Results were compared with those obtained by soxhlet extraction. In soxhlet extraction, Optimum conditions were extraction time of 6 h for ethanol 80 % as solvent. Value of phenolic compounds and extraction yield of licorice root in microwave assisted (MAE), and soxhlet were 47.47 mg/g and 16.38 %, 41.709 mg/g and 14.49 %, respectively. These results implied that MAE was more efficient extracting method than soxhlet.

  6. How America Pays for College, 2011. Sallie Mae's National Study of College Students and Parents

    ERIC Educational Resources Information Center

    Sallie Mae, Inc., 2011

    2011-01-01

    Sallie Mae's national study, "How America Pays for College," now in its fourth year, shows the resilience of American families' strongly held belief in the value of a college education. Even in the face of rising tuition costs and the worst economic decline in a generation, between academic years 2007-2008 and 2009-2010 Americans paid increasingly…

  7. In vitro antibacterial activity of a novel resin-based pulp capping material containing the quaternary ammonium salt MAE-DB and Portland cement.

    PubMed

    Yang, Yanwei; Huang, Li; Dong, Yan; Zhang, Hongchen; Zhou, Wei; Ban, Jinghao; Wei, Jingjing; Liu, Yan; Gao, Jing; Chen, Jihua

    2014-01-01

    Vital pulp preservation in the treatment of deep caries is challenging due to bacterial infection. The objectives of this study were to synthesize a novel, light-cured composite material containing bioactive calcium-silicate (Portland cement, PC) and the antimicrobial quaternary ammonium salt monomer 2-methacryloxylethyl dodecyl methyl ammonium bromide (MAE-DB) and to evaluate its effects on Streptococcus mutans growth in vitro. The experimental material was prepared from a 2 : 1 ratio of PC mixed with a resin of 2-hydroxyethylmethacrylate, bisphenol glycerolate dimethacrylate, and triethylene glycol dimethacrylate (4 : 3 : 1) containing 5 wt% MAE-DB. Cured resin containing 5% MAE-DB without PC served as the positive control material, and resin without MAE-DB or PC served as the negative control material. Mineral trioxide aggregate (MTA) and calcium hydroxide (Dycal) served as commercial controls. S. mutans biofilm formation on material surfaces and growth in the culture medium were tested according to colony-forming units (CFUs) and metabolic activity after 24 h incubation over freshly prepared samples or samples aged in water for 6 months. Biofilm formation was also assessed by Live/Dead staining and scanning electron microscopy. S. mutans biofilm formation on the experimental material was significantly inhibited, with CFU counts, metabolic activity, viability staining, and morphology similar to those of biofilms on the positive control material. None of the materials affected bacterial growth in solution. Contact-inhibition of biofilm formation was retained by the aged experimental material. Significant biofilm formation was observed on MTA and Dycal. The synthesized material containing HEMA-BisGMA-TEGDMA resin with MAE-DB as the antimicrobial agent and PC to support mineralized tissue formation inhibited S. mutans biofilm formation even after aging in water for 6 months, but had no inhibitory effect on bacteria in solution. Therefore, this material shows

  8. Generalized regression neural network (GRNN)-based approach for colored dissolved organic matter (CDOM) retrieval: case study of Connecticut River at Middle Haddam Station, USA.

    PubMed

    Heddam, Salim

    2014-11-01

    The prediction of colored dissolved organic matter (CDOM) using artificial neural network approaches has received little attention in the past few decades. In this study, colored dissolved organic matter (CDOM) was modeled using generalized regression neural network (GRNN) and multiple linear regression (MLR) models as a function of Water temperature (TE), pH, specific conductance (SC), and turbidity (TU). Evaluation of the prediction accuracy of the models is based on the root mean square error (RMSE), mean absolute error (MAE), coefficient of correlation (CC), and Willmott's index of agreement (d). The results indicated that GRNN can be applied successfully for prediction of colored dissolved organic matter (CDOM).

  9. Determination and error analysis of emittance and spectral emittance measurements by remote sensing

    NASA Technical Reports Server (NTRS)

    Dejesusparada, N. (Principal Investigator); Kumar, R.

    1977-01-01

    The author has identified the following significant results. From the theory of remote sensing of surface temperatures, an equation of the upper bound of absolute error of emittance was determined. It showed that the absolute error decreased with an increase in contact temperature, whereas, it increased with an increase in environmental integrated radiant flux density. Change in emittance had little effect on the absolute error. A plot of the difference between temperature and band radiance temperature vs. emittance was provided for the wavelength intervals: 4.5 to 5.5 microns, 8 to 13.5 microns, and 10.2 to 12.5 microns.

  10. The absolute radiometric calibration of the advanced very high resolution radiometer

    NASA Technical Reports Server (NTRS)

    Slater, P. N.; Teillet, P. M.; Ding, Y.

    1988-01-01

    The need for independent, redundant absolute radiometric calibration methods is discussed with reference to the Thematic Mapper. Uncertainty requirements for absolute calibration of between 0.5 and 4 percent are defined based on the accuracy of reflectance retrievals at an agricultural site. It is shown that even very approximate atmospheric corrections can reduce the error in reflectance retrieval to 0.02 over the reflectance range 0 to 0.4.

  11. Motion-induced error reduction by combining Fourier transform profilometry with phase-shifting profilometry.

    PubMed

    Li, Beiwen; Liu, Ziping; Zhang, Song

    2016-10-03

    We propose a hybrid computational framework to reduce motion-induced measurement error by combining the Fourier transform profilometry (FTP) and phase-shifting profilometry (PSP). The proposed method is composed of three major steps: Step 1 is to extract continuous relative phase maps for each isolated object with single-shot FTP method and spatial phase unwrapping; Step 2 is to obtain an absolute phase map of the entire scene using PSP method, albeit motion-induced errors exist on the extracted absolute phase map; and Step 3 is to shift the continuous relative phase maps from Step 1 to generate final absolute phase maps for each isolated object by referring to the absolute phase map with error from Step 2. Experiments demonstrate the success of the proposed computational framework for measuring multiple isolated rapidly moving objects.

  12. Improved modification for the density-functional theory calculation of thermodynamic properties for C-H-O composite compounds.

    PubMed

    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.

  13. Analysis of dextromethorphan and dextrorphan in decomposed skeletal tissues by microwave assisted extraction, microplate solid-phase extraction and gas chromatography- mass spectrometry (MAE-MPSPE-GCMS).

    PubMed

    Fraser, Candice D; Cornthwaite, Heather M; Watterson, James H

    2015-08-01

    Analysis of decomposed skeletal tissues for dextromethorphan (DXM) and dextrorphan (DXT) using microwave assisted extraction (MAE), microplate solid-phase extraction (MPSPE) and gas chromatography-mass spectrometry (GC-MS) is described. Rats (n = 3) received 100 mg/kg DXM (i.p.) and were euthanized by CO2 asphyxiation roughly 20 min post-dose. Remains decomposed to skeleton outdoors and vertebral bones were recovered, cleaned, and pulverized. Pulverized bone underwent MAE using methanol as an extraction solvent in a closed microwave system, followed by MPSPE and GC-MS. Analyte stability under MAE conditions was assessed and found to be stable for at least 60 min irradiation time. The majority (>90%) of each analyte was recovered after 15 min. The MPSPE-GCMS method was fit to a quadratic response (R(2)  > 0.99), over the concentration range 10-10 000 ng⋅mL(-1) , with coefficients of variation <20% in triplicate analysis. The MPSPE-GCMS method displayed a limit of detection of 10 ng⋅mL(-1) for both analytes. Following MAE for 60 min (80 °C, 1200 W), MPSPE-GCMS analysis of vertebral bone of DXM-exposed rats detected both analytes in all samples (DXM: 0.9-1.5 µg⋅g(-1) ; DXT: 0.5-1.8 µg⋅g(-1) ). Copyright © 2014 John Wiley & Sons, Ltd.

  14. The effect of modeled absolute timing variability and relative timing variability on observational learning.

    PubMed

    Grierson, Lawrence E M; Roberts, James W; Welsher, Arthur M

    2017-05-01

    There is much evidence to suggest that skill learning is enhanced by skill observation. Recent research on this phenomenon indicates a benefit of observing variable/erred demonstrations. In this study, we explore whether it is variability within the relative organization or absolute parameterization of a movement that facilitates skill learning through observation. To do so, participants were randomly allocated into groups that observed a model with no variability, absolute timing variability, relative timing variability, or variability in both absolute and relative timing. All participants performed a four-segment movement pattern with specific absolute and relative timing goals prior to and following the observational intervention, as well as in a 24h retention test and transfers tests that featured new relative and absolute timing goals. Absolute timing error indicated that all groups initially acquired the absolute timing, maintained their performance at 24h retention, and exhibited performance deterioration in both transfer tests. Relative timing error revealed that the observation of no variability and relative timing variability produced greater performance at the post-test, 24h retention and relative timing transfer tests, but for the no variability group, deteriorated at absolute timing transfer test. The results suggest that the learning of absolute timing following observation unfolds irrespective of model variability. However, the learning of relative timing benefits from holding the absolute features constant, while the observation of no variability partially fails in transfer. We suggest learning by observing no variability and variable/erred models unfolds via similar neural mechanisms, although the latter benefits from the additional coding of information pertaining to movements that require a correction. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. An Evaluation of Portable Wet Bulb Globe Temperature Monitor Accuracy.

    PubMed

    Cooper, Earl; Grundstein, Andrew; Rosen, Adam; Miles, Jessica; Ko, Jupil; Curry, Patrick

    2017-12-01

      Wet bulb globe temperature (WBGT) is the gold standard for assessing environmental heat stress during physical activity. Many manufacturers of commercially available instruments fail to report WBGT accuracy.   To determine the accuracy of several commercially available WBGT monitors compared with a standardized reference device.   Observational study.   Field test.   Six commercially available WBGT devices.   Data were recorded for 3 sessions (1 in the morning and 2 in the afternoon) at 2-minute intervals for at least 2 hours. Mean absolute error (MAE), root mean square error (RMSE), mean bias error (MBE), and the Pearson correlation coefficient ( r) were calculated to determine instrument performance compared with the reference unit.   The QUESTemp° 34 (MAE = 0.24°C, RMSE = 0.44°C, MBE = -0.64%) and Extech HT30 Heat Stress Wet Bulb Globe Temperature Meter (Extech; MAE = 0.61°C, RMSE = 0.79°C, MBE = 0.44%) demonstrated the least error in relation to the reference standard, whereas the General WBGT8778 Heat Index Checker (General; MAE = 1.18°C, RMSE = 1.34°C, MBE = 4.25%) performed the poorest. The QUESTemp° 34 and Kestrel 4400 Heat Stress Tracker units provided conservative measurements that slightly overestimated the WBGT provided by the reference unit. Finally, instruments using the psychrometric wet bulb temperature (General, REED Heat Index WBGT Meter, and WBGT-103 Heat Stroke Checker) tended to underestimate the WBGT, and the resulting values more frequently fell into WBGT-based activity categories with fewer restrictions as defined by the American College of Sports Medicine.   The QUESTemp° 34, followed by the Extech, had the smallest error compared with the reference unit. Moreover, the QUESTemp° 34, Extech, and Kestrel units appeared to offer conservative yet accurate assessments of the WBGT, potentially minimizing the risk of allowing physical activity to continue in stressful heat environments. Instruments using the

  16. Comparison of the WSA-ENLIL model with three CME cone types

    NASA Astrophysics Data System (ADS)

    Jang, Soojeong; Moon, Y.; Na, H.

    2013-07-01

    We have made a comparison of the CME-associated shock propagation based on the WSA-ENLIL model with three cone types using 29 halo CMEs from 2001 to 2002. These halo CMEs have cone model parameters as well as their associated interplanetary (IP) shocks. For this study we consider three different cone types (an asymmetric cone model, an ice-cream cone model and an elliptical cone model) to determine 3-D CME parameters (radial velocity, angular width and source location), which are the input values of the WSA-ENLIL model. The mean absolute error (MAE) of the arrival times for the asymmetric cone model is 10.6 hours, which is about 1 hour smaller than those of the other models. Their ensemble average of MAE is 9.5 hours. However, this value is still larger than that (8.7 hours) of the empirical model of Kim et al. (2007). We will compare their IP shock velocities and densities with those from ACE in-situ measurements and discuss them in terms of the prediction of geomagnetic storms.Abstract (2,250 Maximum Characters): We have made a comparison of the CME-associated shock propagation based on the WSA-ENLIL model with three cone types using 29 halo CMEs from 2001 to 2002. These halo CMEs have cone model parameters as well as their associated interplanetary (IP) shocks. For this study we consider three different cone types (an asymmetric cone model, an ice-cream cone model and an elliptical cone model) to determine 3-D CME parameters (radial velocity, angular width and source location), which are the input values of the WSA-ENLIL model. The mean absolute error (MAE) of the arrival times for the asymmetric cone model is 10.6 hours, which is about 1 hour smaller than those of the other models. Their ensemble average of MAE is 9.5 hours. However, this value is still larger than that (8.7 hours) of the empirical model of Kim et al. (2007). We will compare their IP shock velocities and densities with those from ACE in-situ measurements and discuss them in terms of the

  17. Comparative Efficacy of the New Optical Biometer on Intraocular Lens Power Calculation (AL-Scan versus IOLMaster).

    PubMed

    Ha, Ahnul; Wee, Won Ryang; Kim, Mee Kum

    2018-05-15

    To evaluate the agreement in axial length (AL), keratometry, and anterior chamber depth measurements between AL-Scan and IOLMaster biometers and to compare the efficacy of the AL-Scan on intraocular lens (IOL) power calculations and refractive outcomes with those obtained by the IOLMaster. Medical records of 48 eyes from 48 patients who underwent uneventful phacoemulsification and IOL insertion were retrospectively reviewed. One of the two types of monofocal aspheric IOLs were implanted (Tecnis ZCB00 [Tecnis, n = 34] or CT Asphina 509M [Asphina, n = 14]). Two different partial coherence interferometers measured and compared AL, keratometry (2.4 mm), anterior chamber depth, and IOL power calculations with SRK/T, Hoffer Q, Holladay2, and Haigis formulas. The difference between expected and actual final refractive error was compared as refractive mean error (ME), refractive mean absolute error (MAE), and median absolute error (MedAE). AL measured by the AL-Scan was shorter than that measured by the IOLMaster (p = 0.029). The IOL power of Tecnis did not differ between the four formulas; however, the Asphina measurement calculated using Hoffer Q for the AL-Scan was lower (0.28 diopters, p = 0.015) than that calculated by the IOLMaster. There were no statistically significant differences between the calculations by MAE and MedAE for the four formulas in either IOL. In SRK/T, ME in Tecnis-inserted eyes measured by AL-Scan showed a tendency toward myopia (p = 0.032). Measurement by AL-Scan provides reliable biometry data and power calculations compared to the IOLMaster; however, refractive outcomes of Tecnis-inserted eyes by AL-Scan calculated using SRK/T can show a slight myopic tendency. © 2018 The Korean Ophthalmological Society.

  18. How America Saves for College, 2014: Sallie Mae's National Study of Parents with Children under Age 18

    ERIC Educational Resources Information Center

    Sallie Mae, Inc., 2014

    2014-01-01

    This is the fourth report in the Sallie Mae series "How America Saves for College," which launched in 2009. To understand how American families are planning for their children's education, the study captures data on parents' decision-making about savings, the use of savings vehicles, and the amount they save, as well as attitudes toward…

  19. Stellar Atmospheric Parameterization Based on Deep Learning

    NASA Astrophysics Data System (ADS)

    Pan, R. Y.; Li, X. R.

    2016-07-01

    Deep learning is a typical learning method widely studied in machine learning, pattern recognition, and artificial intelligence. This work investigates the stellar atmospheric parameterization problem by constructing a deep neural network with five layers. The proposed scheme is evaluated on both real spectra from Sloan Digital Sky Survey (SDSS) and the theoretic spectra computed with Kurucz's New Opacity Distribution Function (NEWODF) model. On the SDSS spectra, the mean absolute errors (MAEs) are 79.95 for the effective temperature (T_{eff}/K), 0.0058 for lg (T_{eff}/K), 0.1706 for surface gravity (lg (g/(cm\\cdot s^{-2}))), and 0.1294 dex for metallicity ([Fe/H]), respectively; On the theoretic spectra, the MAEs are 15.34 for T_{eff}/K, 0.0011 for lg (T_{eff}/K), 0.0214 for lg (g/(cm\\cdot s^{-2})), and 0.0121 dex for [Fe/H], respectively.

  20. Evaluation and Applications of the Prediction of Intensity Model Error (PRIME) Model

    NASA Astrophysics Data System (ADS)

    Bhatia, K. T.; Nolan, D. S.; Demaria, M.; Schumacher, A.

    2015-12-01

    Forecasters and end users of tropical cyclone (TC) intensity forecasts would greatly benefit from a reliable expectation of model error to counteract the lack of consistency in TC intensity forecast performance. As a first step towards producing error predictions to accompany each TC intensity forecast, Bhatia and Nolan (2013) studied the relationship between synoptic parameters, TC attributes, and forecast errors. In this study, we build on previous results of Bhatia and Nolan (2013) by testing the ability of the Prediction of Intensity Model Error (PRIME) model to forecast the absolute error and bias of four leading intensity models available for guidance in the Atlantic basin. PRIME forecasts are independently evaluated at each 12-hour interval from 12 to 120 hours during the 2007-2014 Atlantic hurricane seasons. The absolute error and bias predictions of PRIME are compared to their respective climatologies to determine their skill. In addition to these results, we will present the performance of the operational version of PRIME run during the 2015 hurricane season. PRIME verification results show that it can reliably anticipate situations where particular models excel, and therefore could lead to a more informed protocol for hurricane evacuations and storm preparations. These positive conclusions suggest that PRIME forecasts also have the potential to lower the error in the original intensity forecasts of each model. As a result, two techniques are proposed to develop a post-processing procedure for a multimodel ensemble based on PRIME. The first approach is to inverse-weight models using PRIME absolute error predictions (higher predicted absolute error corresponds to lower weights). The second multimodel ensemble applies PRIME bias predictions to each model's intensity forecast and the mean of the corrected models is evaluated. The forecasts of both of these experimental ensembles are compared to those of the equal-weight ICON ensemble, which currently

  1. Multivariate Time Series Forecasting of Crude Palm Oil Price Using Machine Learning Techniques

    NASA Astrophysics Data System (ADS)

    Kanchymalay, Kasturi; Salim, N.; Sukprasert, Anupong; Krishnan, Ramesh; Raba'ah Hashim, Ummi

    2017-08-01

    The aim of this paper was to study the correlation between crude palm oil (CPO) price, selected vegetable oil prices (such as soybean oil, coconut oil, and olive oil, rapeseed oil and sunflower oil), crude oil and the monthly exchange rate. Comparative analysis was then performed on CPO price forecasting results using the machine learning techniques. Monthly CPO prices, selected vegetable oil prices, crude oil prices and monthly exchange rate data from January 1987 to February 2017 were utilized. Preliminary analysis showed a positive and high correlation between the CPO price and soy bean oil price and also between CPO price and crude oil price. Experiments were conducted using multi-layer perception, support vector regression and Holt Winter exponential smoothing techniques. The results were assessed by using criteria of root mean square error (RMSE), means absolute error (MAE), means absolute percentage error (MAPE) and Direction of accuracy (DA). Among these three techniques, support vector regression(SVR) with Sequential minimal optimization (SMO) algorithm showed relatively better results compared to multi-layer perceptron and Holt Winters exponential smoothing method.

  2. The Absolute Magnitude of the Sun in Several Filters

    NASA Astrophysics Data System (ADS)

    Willmer, Christopher N. A.

    2018-06-01

    This paper presents a table with estimates of the absolute magnitude of the Sun and the conversions from vegamag to the AB and ST systems for several wide-band filters used in ground-based and space-based observatories. These estimates use the dustless spectral energy distribution (SED) of Vega, calibrated absolutely using the SED of Sirius, to set the vegamag zero-points and a composite spectrum of the Sun that coadds space-based observations from the ultraviolet to the near-infrared with models of the Solar atmosphere. The uncertainty of the absolute magnitudes is estimated by comparing the synthetic colors with photometric measurements of solar analogs and is found to be ∼0.02 mag. Combined with the uncertainty of ∼2% in the calibration of the Vega SED, the errors of these absolute magnitudes are ∼3%–4%. Using these SEDs, for three of the most utilized filters in extragalactic work the estimated absolute magnitudes of the Sun are M B = 5.44, M V = 4.81, and M K = 3.27 mag in the vegamag system and M B = 5.31, M V = 4.80, and M K = 5.08 mag in AB.

  3. Hybrid empirical mode decomposition- ARIMA for forecasting exchange rates

    NASA Astrophysics Data System (ADS)

    Abadan, Siti Sarah; Shabri, Ani; Ismail, Shuhaida

    2015-02-01

    This paper studied the forecasting of monthly Malaysian Ringgit (MYR)/ United State Dollar (USD) exchange rates using the hybrid of two methods which are the empirical model decomposition (EMD) and the autoregressive integrated moving average (ARIMA). MYR is pegged to USD during the Asian financial crisis causing the exchange rates are fixed to 3.800 from 2nd of September 1998 until 21st of July 2005. Thus, the chosen data in this paper is the post-July 2005 data, starting from August 2005 to July 2010. The comparative study using root mean square error (RMSE) and mean absolute error (MAE) showed that the EMD-ARIMA outperformed the single-ARIMA and the random walk benchmark model.

  4. Expected accuracy of proximal and distal temperature estimated by wireless sensors, in relation to their number and position on the skin.

    PubMed

    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.

  5. Expected accuracy of proximal and distal temperature estimated by wireless sensors, in relation to their number and position on the skin

    PubMed Central

    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

  6. How America Saves for College, 2013. Sallie Mae's National Study of Parents with Children under Age 18

    ERIC Educational Resources Information Center

    Sallie Mae, Inc., 2013

    2013-01-01

    Sallie Mae has conducted an ongoing study, "How America Pays for College," annually since 2008. Through that study, the researchers are able to provide a clearer picture of how the typical American undergraduate is paying for college today. This report is the third in the "How America Saves for College" series conducted since 2009. Interviews took…

  7. 75 FR 58421 - Notice of Submission of Proposed Information Collection to OMB Ginnie Mae Mortgage-Backed...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-24

    ...The proposed information collection requirement described below has been submitted to the Office of Management and Budget (OMB) for review, as required by the Paperwork Reduction Act. The Department is soliciting public comments on the subject proposal. This information is collected by Ginnie Mae from issuers/customers that participate in its Mortgage-Backed Securities programs to monitor performance and compliance with established rules and regulations.

  8. Robust nonlinear canonical correlation analysis: application to seasonal climate forecasting

    NASA Astrophysics Data System (ADS)

    Cannon, A. J.; Hsieh, W. W.

    2008-02-01

    Robust variants of nonlinear canonical correlation analysis (NLCCA) are introduced to improve performance on datasets with low signal-to-noise ratios, for example those encountered when making seasonal climate forecasts. The neural network model architecture of standard NLCCA is kept intact, but the cost functions used to set the model parameters are replaced with more robust variants. The Pearson product-moment correlation in the double-barreled network is replaced by the biweight midcorrelation, and the mean squared error (mse) in the inverse mapping networks can be replaced by the mean absolute error (mae). Robust variants of NLCCA are demonstrated on a synthetic dataset and are used to forecast sea surface temperatures in the tropical Pacific Ocean based on the sea level pressure field. Results suggest that adoption of the biweight midcorrelation can lead to improved performance, especially when a strong, common event exists in both predictor/predictand datasets. Replacing the mse by the mae leads to improved performance on the synthetic dataset, but not on the climate dataset except at the longest lead time, which suggests that the appropriate cost function for the inverse mapping networks is more problem dependent.

  9. Spatially explicit estimation of aboveground boreal forest biomass in the Yukon River Basin, Alaska

    USGS Publications Warehouse

    Ji, Lei; Wylie, Bruce K.; Brown, Dana R. N.; Peterson, Birgit E.; Alexander, Heather D.; Mack, Michelle C.; Rover, Jennifer R.; Waldrop, Mark P.; McFarland, Jack W.; Chen, Xuexia; Pastick, Neal J.

    2015-01-01

    Quantification of aboveground biomass (AGB) in Alaska’s boreal forest is essential to the accurate evaluation of terrestrial carbon stocks and dynamics in northern high-latitude ecosystems. Our goal was to map AGB at 30 m resolution for the boreal forest in the Yukon River Basin of Alaska using Landsat data and ground measurements. We acquired Landsat images to generate a 3-year (2008–2010) composite of top-of-atmosphere reflectance for six bands as well as the brightness temperature (BT). We constructed a multiple regression model using field-observed AGB and Landsat-derived reflectance, BT, and vegetation indices. A basin-wide boreal forest AGB map at 30 m resolution was generated by applying the regression model to the Landsat composite. The fivefold cross-validation with field measurements had a mean absolute error (MAE) of 25.7 Mg ha−1 (relative MAE 47.5%) and a mean bias error (MBE) of 4.3 Mg ha−1(relative MBE 7.9%). The boreal forest AGB product was compared with lidar-based vegetation height data; the comparison indicated that there was a significant correlation between the two data sets.

  10. Predicting online ratings based on the opinion spreading process

    NASA Astrophysics Data System (ADS)

    He, Xing-Sheng; Zhou, Ming-Yang; Zhuo, Zhao; Fu, Zhong-Qian; Liu, Jian-Guo

    2015-10-01

    Predicting users' online ratings is always a challenge issue and has drawn lots of attention. In this paper, we present a rating prediction method by combining the user opinion spreading process with the collaborative filtering algorithm, where user similarity is defined by measuring the amount of opinion a user transfers to another based on the primitive user-item rating matrix. The proposed method could produce a more precise rating prediction for each unrated user-item pair. In addition, we introduce a tunable parameter λ to regulate the preferential diffusion relevant to the degree of both opinion sender and receiver. The numerical results for Movielens and Netflix data sets show that this algorithm has a better accuracy than the standard user-based collaborative filtering algorithm using Cosine and Pearson correlation without increasing computational complexity. By tuning λ, our method could further boost the prediction accuracy when using Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) as measurements. In the optimal cases, on Movielens and Netflix data sets, the corresponding algorithmic accuracy (MAE and RMSE) are improved 11.26% and 8.84%, 13.49% and 10.52% compared to the item average method, respectively.

  11. Using a Hybrid Model to Forecast the Prevalence of Schistosomiasis in Humans.

    PubMed

    Zhou, Lingling; Xia, Jing; Yu, Lijing; Wang, Ying; Shi, Yun; Cai, Shunxiang; Nie, Shaofa

    2016-03-23

    We previously proposed a hybrid model combining both the autoregressive integrated moving average (ARIMA) and the nonlinear autoregressive neural network (NARNN) models in forecasting schistosomiasis. Our purpose in the current study was to forecast the annual prevalence of human schistosomiasis in Yangxin County, using our ARIMA-NARNN model, thereby further certifying the reliability of our hybrid model. We used the ARIMA, NARNN and ARIMA-NARNN models to fit and forecast the annual prevalence of schistosomiasis. The modeling time range included was the annual prevalence from 1956 to 2008 while the testing time range included was from 2009 to 2012. The mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) were used to measure the model performance. We reconstructed the hybrid model to forecast the annual prevalence from 2013 to 2016. The modeling and testing errors generated by the ARIMA-NARNN model were lower than those obtained from either the single ARIMA or NARNN models. The predicted annual prevalence from 2013 to 2016 demonstrated an initial decreasing trend, followed by an increase. The ARIMA-NARNN model can be well applied to analyze surveillance data for early warning systems for the control and elimination of schistosomiasis.

  12. Fundamental principles of absolute radiometry and the philosophy of this NBS program (1968 to 1971)

    NASA Technical Reports Server (NTRS)

    Geist, J.

    1972-01-01

    A description is given work performed on a program to develop an electrically calibrated detector (also called absolute radiometer, absolute detector, and electrically calibrated radiometer) that could be used to realize, maintain, and transfer a scale of total irradiance. The program includes a comprehensive investigation of the theoretical basis of absolute detector radiometry, as well as the design and construction of a number of detectors. A theoretical analysis of the sources of error is also included.

  13. Absolute Parameters for the F-type Eclipsing Binary BW Aquarii

    NASA Astrophysics Data System (ADS)

    Maxted, P. F. L.

    2018-05-01

    BW Aqr is a bright eclipsing binary star containing a pair of F7V stars. The absolute parameters of this binary (masses, radii, etc.) are known to good precision so they are often used to test stellar models, particularly in studies of convective overshooting. ... Maxted & Hutcheon (2018) analysed the Kepler K2 data for BW Aqr and noted that it shows variability between the eclipses that may be caused by tidally induced pulsations. ... Table 1 shows the absolute parameters for BW Aqr derived from an improved analysis of the Kepler K2 light curve plus the RV measurements from both Imbert (1979) and Lester & Gies (2018). ... The values in Table 1 with their robust error estimates from the standard deviation of the mean are consistent with the values and errors from Maxted & Hutcheon (2018) based on the PPD calculated using emcee for a fit to the entire K2 light curve.

  14. Absolute GPS Positioning Using Genetic Algorithms

    NASA Astrophysics Data System (ADS)

    Ramillien, G.

    A new inverse approach for restoring the absolute coordinates of a ground -based station from three or four observed GPS pseudo-ranges is proposed. This stochastic method is based on simulations of natural evolution named genetic algorithms (GA). These iterative procedures provide fairly good and robust estimates of the absolute positions in the Earth's geocentric reference system. For comparison/validation, GA results are compared to the ones obtained using the classical linearized least-square scheme for the determination of the XYZ location proposed by Bancroft (1985) which is strongly limited by the number of available observations (i.e. here, the number of input pseudo-ranges must be four). The r.m.s. accuracy of the non -linear cost function reached by this latter method is typically ~10-4 m2 corresponding to ~300-500-m accuracies for each geocentric coordinate. However, GA can provide more acceptable solutions (r.m.s. errors < 10-5 m2), even when only three instantaneous pseudo-ranges are used, such as a lost of lock during a GPS survey. Tuned GA parameters used in different simulations are N=1000 starting individuals, as well as Pc=60-70% and Pm=30-40% for the crossover probability and mutation rate, respectively. Statistical tests on the ability of GA to recover acceptable coordinates in presence of important levels of noise are made simulating nearly 3000 random samples of erroneous pseudo-ranges. Here, two main sources of measurement errors are considered in the inversion: (1) typical satellite-clock errors and/or 300-metre variance atmospheric delays, and (2) Geometrical Dilution of Precision (GDOP) due to the particular GPS satellite configuration at the time of acquisition. Extracting valuable information and even from low-quality starting range observations, GA offer an interesting alternative for high -precision GPS positioning.

  15. Preliminary Error Budget for the Reflected Solar Instrument for the Climate Absolute Radiance and Refractivity Observatory

    NASA Technical Reports Server (NTRS)

    Thome, Kurtis; Gubbels, Timothy; Barnes, Robert

    2011-01-01

    The Climate Absolute Radiance and Refractivity Observatory (CLARREO) plans to observe climate change trends over decadal time scales to determine the accuracy of climate projections. The project relies on spaceborne earth observations of SI-traceable variables sensitive to key decadal change parameters. The mission includes a reflected solar instrument retrieving at-sensor reflectance over the 320 to 2300 nm spectral range with 500-m spatial resolution and 100-km swath. Reflectance is obtained from the ratio of measurements of the earth s surface to those while viewing the sun relying on a calibration approach that retrieves reflectance with uncertainties less than 0.3%. The calibration is predicated on heritage hardware, reduction of sensor complexity, adherence to detector-based calibration standards, and an ability to simulate in the laboratory on-orbit sources in both size and brightness to provide the basis of a transfer to orbit of the laboratory calibration including a link to absolute solar irradiance measurements. The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe high-accuracy, long-term climate change trends and to use decadal change observations as the most critical method to determine the accuracy of climate change projections such as those in the IPCC Report. A rigorously known accuracy of both decadal change observations as well as climate projections is critical in order to enable sound policy decisions. The CLARREO Project will implement a spaceborne earth observation mission designed to provide rigorous SI traceable observations (i.e., radiance, reflectance, and refractivity) that are sensitive to a wide range of key decadal change variables, including: 1) Surface temperature and atmospheric temperature profile 2) Atmospheric water vapor profile 3) Far infrared water vapor greenhouse 4) Aerosol properties and anthropogenic aerosol direct radiative forcing 5) Total and spectral solar

  16. Systematic errors of EIT systems determined by easily-scalable resistive phantoms.

    PubMed

    Hahn, G; Just, A; Dittmar, J; Hellige, G

    2008-06-01

    We present a simple method to determine systematic errors that will occur in the measurements by EIT systems. The approach is based on very simple scalable resistive phantoms for EIT systems using a 16 electrode adjacent drive pattern. The output voltage of the phantoms is constant for all combinations of current injection and voltage measurements and the trans-impedance of each phantom is determined by only one component. It can be chosen independently from the input and output impedance, which can be set in order to simulate measurements on the human thorax. Additional serial adapters allow investigation of the influence of the contact impedance at the electrodes on resulting errors. Since real errors depend on the dynamic properties of an EIT system, the following parameters are accessible: crosstalk, the absolute error of each driving/sensing channel and the signal to noise ratio in each channel. Measurements were performed on a Goe-MF II EIT system under four different simulated operational conditions. We found that systematic measurement errors always exceeded the error level of stochastic noise since the Goe-MF II system had been optimized for a sufficient signal to noise ratio but not for accuracy. In time difference imaging and functional EIT (f-EIT) systematic errors are reduced to a minimum by dividing the raw data by reference data. This is not the case in absolute EIT (a-EIT) where the resistivity of the examined object is determined on an absolute scale. We conclude that a reduction of systematic errors has to be one major goal in future system design.

  17. Landsat-7 ETM+ radiometric stability and absolute calibration

    USGS Publications Warehouse

    Markham, B.L.; Barker, J.L.; Barsi, J.A.; Kaita, E.; Thome, K.J.; Helder, D.L.; Palluconi, Frank Don; Schott, J.R.; Scaramuzza, Pat; ,

    2002-01-01

    Launched in April 1999, the Landsat-7 ETM+ instrument is in its fourth year of operation. The quality of the acquired calibrated imagery continues to be high, especially with respect to its three most important radiometric performance parameters: reflective band instrument stability to better than ??1%, reflective band absolute calibration to better than ??5%, and thermal band absolute calibration to better than ??0.6 K. The ETM+ instrument has been the most stable of any of the Landsat instruments, in both the reflective and thermal channels. To date, the best on-board calibration source for the reflective bands has been the Full Aperture Solar Calibrator, which has indicated changes of at most -1.8% to -2.0% (95% C.I.) change per year in the ETM+ gain (band 4). However, this change is believed to be caused by changes in the solar diffuser panel, as opposed to a change in the instrument's gain. This belief is based partially on ground observations, which bound the changes in gain in band 4 at -0.7% to +1.5%. Also, ETM+ stability is indicated by the monitoring of desert targets. These image-based results for four Saharan and Arabian sites, for a collection of 35 scenes over the three years since launch, bound the gain change at -0.7% to +0.5% in band 4. Thermal calibration from ground observations revealed an offset error of +0.31 W/m 2 sr um soon after launch. This offset was corrected within the U. S. ground processing system at EROS Data Center on 21-Dec-00, and since then, the band 6 on-board calibration has indicated changes of at most +0.02% to +0.04% (95% C.I.) per year. The latest ground observations have detected no remaining offset error with an RMS error of ??0.6 K. The stability and absolute calibration of the Landsat-7 ETM+ sensor make it an ideal candidate to be used as a reference source for radiometric cross-calibrating to other land remote sensing satellite systems.

  18. Informing the Human Plasma Protein Binding of Environmental Chemicals by Machine Learning in the Pharmaceutical Space: Applicability Domain and Limits of Predictability.

    PubMed

    Ingle, Brandall L; Veber, Brandon C; Nichols, John W; Tornero-Velez, Rogelio

    2016-11-28

    The free fraction of a xenobiotic in plasma (F ub ) is an important determinant of chemical adsorption, distribution, metabolism, elimination, and toxicity, yet experimental plasma protein binding data are scarce for environmentally relevant chemicals. The presented work explores the merit of utilizing available pharmaceutical data to predict F ub for environmentally relevant chemicals via machine learning techniques. Quantitative structure-activity relationship (QSAR) models were constructed with k nearest neighbors (kNN), support vector machines (SVM), and random forest (RF) machine learning algorithms from a training set of 1045 pharmaceuticals. The models were then evaluated with independent test sets of pharmaceuticals (200 compounds) and environmentally relevant ToxCast chemicals (406 total, in two groups of 238 and 168 compounds). The selection of a minimal feature set of 10-15 2D molecular descriptors allowed for both informative feature interpretation and practical applicability domain assessment via a bounded box of descriptor ranges and principal component analysis. The diverse pharmaceutical and environmental chemical sets exhibit similarities in terms of chemical space (99-82% overlap), as well as comparable bias and variance in constructed learning curves. All the models exhibit significant predictability with mean absolute errors (MAE) in the range of 0.10-0.18F ub . The models performed best for highly bound chemicals (MAE 0.07-0.12), neutrals (MAE 0.11-0.14), and acids (MAE 0.14-0.17). A consensus model had the highest accuracy across both pharmaceuticals (MAE 0.151-0.155) and environmentally relevant chemicals (MAE 0.110-0.131). The inclusion of the majority of the ToxCast test sets within the AD of the consensus model, coupled with high prediction accuracy for these chemicals, indicates the model provides a QSAR for F ub that is broadly applicable to both pharmaceuticals and environmentally relevant chemicals.

  19. Online absolute pose compensation and steering control of industrial robot based on six degrees of freedom laser measurement

    NASA Astrophysics Data System (ADS)

    Yang, Juqing; Wang, Dayong; Fan, Baixing; Dong, Dengfeng; Zhou, Weihu

    2017-03-01

    In-situ intelligent manufacturing for large-volume equipment requires industrial robots with absolute high-accuracy positioning and orientation steering control. Conventional robots mainly employ an offline calibration technology to identify and compensate key robotic parameters. However, the dynamic and static parameters of a robot change nonlinearly. It is not possible to acquire a robot's actual parameters and control the absolute pose of the robot with a high accuracy within a large workspace by offline calibration in real-time. This study proposes a real-time online absolute pose steering control method for an industrial robot based on six degrees of freedom laser tracking measurement, which adopts comprehensive compensation and correction of differential movement variables. First, the pose steering control system and robot kinematics error model are constructed, and then the pose error compensation mechanism and algorithm are introduced in detail. By accurately achieving the position and orientation of the robot end-tool, mapping the computed Jacobian matrix of the joint variable and correcting the joint variable, the real-time online absolute pose compensation for an industrial robot is accurately implemented in simulations and experimental tests. The average positioning error is 0.048 mm and orientation accuracy is better than 0.01 deg. The results demonstrate that the proposed method is feasible, and the online absolute accuracy of a robot is sufficiently enhanced.

  20. Spinal intra-operative three-dimensional navigation with infra-red tool tracking: correlation between clinical and absolute engineering accuracy

    NASA Astrophysics Data System (ADS)

    Guha, Daipayan; Jakubovic, Raphael; Gupta, Shaurya; Yang, Victor X. D.

    2017-02-01

    Computer-assisted navigation (CAN) may guide spinal surgeries, reliably reducing screw breach rates. Definitions of screw breach, if reported, vary widely across studies. Absolute quantitative error is theoretically a more precise and generalizable metric of navigation accuracy, but has been computed variably and reported in fewer than 25% of clinical studies of CAN-guided pedicle screw accuracy. We reviewed a prospectively-collected series of 209 pedicle screws placed with CAN guidance to characterize the correlation between clinical pedicle screw accuracy, based on postoperative imaging, and absolute quantitative navigation accuracy. We found that acceptable screw accuracy was achieved for significantly fewer screws based on 2mm grade vs. Heary grade, particularly in the lumbar spine. Inter-rater agreement was good for the Heary classification and moderate for the 2mm grade, significantly greater among radiologists than surgeon raters. Mean absolute translational/angular accuracies were 1.75mm/3.13° and 1.20mm/3.64° in the axial and sagittal planes, respectively. There was no correlation between clinical and absolute navigation accuracy, in part because surgeons appear to compensate for perceived translational navigation error by adjusting screw medialization angle. Future studies of navigation accuracy should therefore report absolute translational and angular errors. Clinical screw grades based on post-operative imaging, if reported, may be more reliable if performed in multiple by radiologist raters.

  1. Absolute Plate Velocities from Seismic Anisotropy: Importance of Correlated Errors

    NASA Astrophysics Data System (ADS)

    Gordon, R. G.; Zheng, L.; Kreemer, C.

    2014-12-01

    The orientation of seismic anisotropy inferred beneath the interiors of plates may provide a means to estimate the motions of the plate relative to the deeper mantle. Here we analyze a global set of shear-wave splitting data to estimate plate motions and to better understand the dispersion of the data, correlations in the errors, and their relation to plate speed. The errors in plate motion azimuths inferred from shear-wave splitting beneath any one tectonic plate are shown to be correlated with the errors of other azimuths from the same plate. To account for these correlations, we adopt a two-tier analysis: First, find the pole of rotation and confidence limits for each plate individually. Second, solve for the best fit to these poles while constraining relative plate angular velocities to consistency with the MORVEL relative plate angular velocities. Our preferred set of angular velocities, SKS-MORVEL, is determined from the poles from eight plates weighted proportionally to the root-mean-square velocity of each plate. SKS-MORVEL indicates that eight plates (Amur, Antarctica, Caribbean, Eurasia, Lwandle, Somalia, Sundaland, and Yangtze) have angular velocities that differ insignificantly from zero. The net rotation of the lithosphere is 0.25±0.11º Ma-1 (95% confidence limits) right-handed about 57.1ºS, 68.6ºE. The within-plate dispersion of seismic anisotropy for oceanic lithosphere (σ=19.2°) differs insignificantly from that for continental lithosphere (σ=21.6°). The between-plate dispersion, however, is significantly smaller for oceanic lithosphere (σ=7.4°) than for continental lithosphere (σ=14.7°). Two of the slowest-moving plates, Antarctica (vRMS=4 mm a-1, σ=29°) and Eurasia (vRMS=3 mm a-1, σ=33°), have two of the largest within-plate dispersions, which may indicate that a plate must move faster than ≈5 mm a-1 to result in seismic anisotropy useful for estimating plate motion.

  2. Prediction of Backbreak in Open-Pit Blasting Operations Using the Machine Learning Method

    NASA Astrophysics Data System (ADS)

    Khandelwal, Manoj; Monjezi, M.

    2013-03-01

    Backbreak is an undesirable phenomenon in blasting operations. It can cause instability of mine walls, falling down of machinery, improper fragmentation, reduced efficiency of drilling, etc. The existence of various effective parameters and their unknown relationships are the main reasons for inaccuracy of the empirical models. Presently, the application of new approaches such as artificial intelligence is highly recommended. In this paper, an attempt has been made to predict backbreak in blasting operations of Soungun iron mine, Iran, incorporating rock properties and blast design parameters using the support vector machine (SVM) method. To investigate the suitability of this approach, the predictions by SVM have been compared with multivariate regression analysis (MVRA). The coefficient of determination (CoD) and the mean absolute error (MAE) were taken as performance measures. It was found that the CoD between measured and predicted backbreak was 0.987 and 0.89 by SVM and MVRA, respectively, whereas the MAE was 0.29 and 1.07 by SVM and MVRA, respectively.

  3. Examination of Spectral Transformations on Spectral Mixture Analysis

    NASA Astrophysics Data System (ADS)

    Deng, Y.; Wu, C.

    2018-04-01

    While many spectral transformation techniques have been applied on spectral mixture analysis (SMA), few study examined their necessity and applicability. This paper focused on exploring the difference between spectrally transformed schemes and untransformed scheme to find out which transformed scheme performed better in SMA. In particular, nine spectrally transformed schemes as well as untransformed scheme were examined in two study areas. Each transformed scheme was tested 100 times using different endmember classes' spectra under the endmember model of vegetation- high albedo impervious surface area-low albedo impervious surface area-soil (V-ISAh-ISAl-S). Performance of each scheme was assessed based on mean absolute error (MAE). Statistical analysis technique, Paired-Samples T test, was applied to test the significance of mean MAEs' difference between transformed and untransformed schemes. Results demonstrated that only NSMA could exceed the untransformed scheme in all study areas. Some transformed schemes showed unstable performance since they outperformed the untransformed scheme in one area but weakened the SMA result in another region.

  4. Understanding the many-body expansion for large systems. II. Accuracy considerations

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lao, Ka Un; Liu, Kuan-Yu; Richard, Ryan M.

    2016-04-28

    To complement our study of the role of finite precision in electronic structure calculations based on a truncated many-body expansion (MBE, or “n-body expansion”), we examine the accuracy of such methods in the present work. Accuracy may be defined either with respect to a supersystem calculation computed at the same level of theory as the n-body calculations, or alternatively with respect to high-quality benchmarks. Both metrics are considered here. In applications to a sequence of water clusters, (H{sub 2}O){sub N=6−55} described at the B3LYP/cc-pVDZ level, we obtain mean absolute errors (MAEs) per H{sub 2}O monomer of ∼1.0 kcal/mol for two-bodymore » expansions, where the benchmark is a B3LYP/cc-pVDZ calculation on the entire cluster. Three- and four-body expansions exhibit MAEs of 0.5 and 0.1 kcal/mol/monomer, respectively, without resort to charge embedding. A generalized many-body expansion truncated at two-body terms [GMBE(2)], using 3–4 H{sub 2}O molecules per fragment, outperforms all of these methods and affords a MAE of ∼0.02 kcal/mol/monomer, also without charge embedding. GMBE(2) requires significantly fewer (although somewhat larger) subsystem calculations as compared to MBE(4), reducing problems associated with floating-point roundoff errors. When compared to high-quality benchmarks, we find that error cancellation often plays a critical role in the success of MBE(n) calculations, even at the four-body level, as basis-set superposition error can compensate for higher-order polarization interactions. A many-body counterpoise correction is introduced for the GMBE, and its two-body truncation [GMBCP(2)] is found to afford good results without error cancellation. Together with a method such as ωB97X-V/aug-cc-pVTZ that can describe both covalent and non-covalent interactions, the GMBE(2)+GMBCP(2) approach provides an accurate, stable, and tractable approach for large systems.« less

  5. Fringe order correction for the absolute phase recovered by two selected spatial frequency fringe projections in fringe projection profilometry.

    PubMed

    Ding, Yi; Peng, Kai; Yu, Miao; Lu, Lei; Zhao, Kun

    2017-08-01

    The performance of the two selected spatial frequency phase unwrapping methods is limited by a phase error bound beyond which errors will occur in the fringe order leading to a significant error in the recovered absolute phase map. In this paper, we propose a method to detect and correct the wrong fringe orders. Two constraints are introduced during the fringe order determination of two selected spatial frequency phase unwrapping methods. A strategy to detect and correct the wrong fringe orders is also described. Compared with the existing methods, we do not need to estimate the threshold associated with absolute phase values to determine the fringe order error, thus making it more reliable and avoiding the procedure of search in detecting and correcting successive fringe order errors. The effectiveness of the proposed method is validated by the experimental results.

  6. Absolute magnitude calibration using trigonometric parallax - Incomplete, spectroscopic samples

    NASA Technical Reports Server (NTRS)

    Ratnatunga, Kavan U.; Casertano, Stefano

    1991-01-01

    A new numerical algorithm is used to calibrate the absolute magnitude of spectroscopically selected stars from their observed trigonometric parallax. This procedure, based on maximum-likelihood estimation, can retrieve unbiased estimates of the intrinsic absolute magnitude and its dispersion even from incomplete samples suffering from selection biases in apparent magnitude and color. It can also make full use of low accuracy and negative parallaxes and incorporate censorship on reported parallax values. Accurate error estimates are derived for each of the fitted parameters. The algorithm allows an a posteriori check of whether the fitted model gives a good representation of the observations. The procedure is described in general and applied to both real and simulated data.

  7. Absolute method of measuring magnetic susceptibility

    USGS Publications Warehouse

    Thorpe, A.; Senftle, F.E.

    1959-01-01

    An absolute method of standardization and measurement of the magnetic susceptibility of small samples is presented which can be applied to most techniques based on the Faraday method. The fact that the susceptibility is a function of the area under the curve of sample displacement versus distance of the magnet from the sample, offers a simple method of measuring the susceptibility without recourse to a standard sample. Typical results on a few substances are compared with reported values, and an error of less than 2% can be achieved. ?? 1959 The American Institute of Physics.

  8. Bone mineral density at distal forearm in men over 40 years of age in Mae Chaem district, Chiang Mai Province, Thailand: a pilot study.

    PubMed

    Tungjai, Montree; Kaewjaeng, Siriprapa; Jumpee, Chayanit; Sriburee, Sompong; Hongsriti, Pongsiri; Tapanya, Monruedee; Maghanemi, Utumma; Ratanasthien, Kwanchai; Kothan, Suchart

    2017-09-01

    To study the prevalence of bone mineral density (BMD) and osteoporosis in the distal forearm among Thai men over 40 years of age in Mae Chaem District, Chiang Mai Province, Thailand. The subjects in this study were 194 Thai men, aged between 40 and 87 years who resided in Mae Chaem District, Chiang Mai Province, Thailand. Self-administered questionnaires were used for receiving the demographic characteristics information. BMD was measured by peripheral dual energy X-ray absorptiometry at the nondominant distal forearm in all men. The BMD was highest in the age-group 40-49 years and lowest in the age-group 70-87 years. The average T-score at the distal forearm was also highest in the age-group 40-49 years and lowest in the age-group 70-87 years. The BMD decreased as a function of age-group (p < .05). In contrast, the BMD increased as a function of weight (p < .05). Height had weak impact on the BMD in the distal forearm (p > .05). The percentage of osteopenia and osteoporosis are increased as a function of age-group in, while decreased in that of normal bone density. We found the prevalence of osteoporosis in men who resided in Mae Chaem District, Chiang Mai Province, Thailand.

  9. Measurement and modeling of particulate matter concentrations: Applying spatial analysis and regression techniques to assess air quality.

    PubMed

    Sajjadi, Seyed Ali; Zolfaghari, Ghasem; Adab, Hamed; Allahabadi, Ahmad; Delsouz, Mehri

    2017-01-01

    This paper presented the levels of PM 2.5 and PM 10 in different stations at the city of Sabzevar, Iran. Furthermore, this study was an attempt to evaluate spatial interpolation methods for determining the PM 2.5 and PM 10 concentrations in the city of Sabzevar. Particulate matters were measured by Haz-Dust EPAM at 48 stations. Then, four interpolating models, including Radial Basis Functions (RBF), Inverse Distance Weighting (IDW), Ordinary Kriging (OK), and Universal Kriging (UK) were used to investigate the status of air pollution in the city. Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) were employed to compare the four models. The results showed that the PM 2.5 concentrations in the stations were between 10 and 500 μg/m 3 . Furthermore, the PM 10 concentrations for all of 48 stations ranged from 20 to 1500 μg/m 3 . The concentrations obtained for the period of nine months were greater than the standard limits. There was difference in the values of MAPE, RMSE, MBE, and MAE. The results indicated that the MAPE in IDW method was lower than other methods: (41.05 for PM 2.5 and 25.89 for PM 10 ). The best interpolation method for the particulate matter (PM 2.5 and PM 10 ) seemed to be IDW method. •The PM 10 and PM 2.5 concentration measurements were performed in the period of warm and risky in terms of particulate matter at 2016.•Concentrations of PM 2.5 and PM 10 were measured by a monitoring device, environmental dust model Haz-Dust EPAM 5000.•Interpolation is used to convert data from observation points to continuous fields to compare spatial patterns sampled by these measurements with spatial patterns of other spatial entities.

  10. How America Pays for College, 2017. Sallie Mae's 10th National Study of College Students and Parents

    ERIC Educational Resources Information Center

    Sallie Mae Bank, 2017

    2017-01-01

    "How America Pays for College", introduced in 2008, is a Sallie Mae national study conducted by Ipsos that annually surveys undergraduate students and parents of undergraduates about how much they pay for college and the resources they use to fund the expense. Now in its tenth year, this study also asks families about their attitudes…

  11. A new accuracy measure based on bounded relative error for time series forecasting

    PubMed Central

    Twycross, Jamie; Garibaldi, Jonathan M.

    2017-01-01

    Many accuracy measures have been proposed in the past for time series forecasting comparisons. However, many of these measures suffer from one or more issues such as poor resistance to outliers and scale dependence. In this paper, while summarising commonly used accuracy measures, a special review is made on the symmetric mean absolute percentage error. Moreover, a new accuracy measure called the Unscaled Mean Bounded Relative Absolute Error (UMBRAE), which combines the best features of various alternative measures, is proposed to address the common issues of existing measures. A comparative evaluation on the proposed and related measures has been made with both synthetic and real-world data. The results indicate that the proposed measure, with user selectable benchmark, performs as well as or better than other measures on selected criteria. Though it has been commonly accepted that there is no single best accuracy measure, we suggest that UMBRAE could be a good choice to evaluate forecasting methods, especially for cases where measures based on geometric mean of relative errors, such as the geometric mean relative absolute error, are preferred. PMID:28339480

  12. A new accuracy measure based on bounded relative error for time series forecasting.

    PubMed

    Chen, Chao; Twycross, Jamie; Garibaldi, Jonathan M

    2017-01-01

    Many accuracy measures have been proposed in the past for time series forecasting comparisons. However, many of these measures suffer from one or more issues such as poor resistance to outliers and scale dependence. In this paper, while summarising commonly used accuracy measures, a special review is made on the symmetric mean absolute percentage error. Moreover, a new accuracy measure called the Unscaled Mean Bounded Relative Absolute Error (UMBRAE), which combines the best features of various alternative measures, is proposed to address the common issues of existing measures. A comparative evaluation on the proposed and related measures has been made with both synthetic and real-world data. The results indicate that the proposed measure, with user selectable benchmark, performs as well as or better than other measures on selected criteria. Though it has been commonly accepted that there is no single best accuracy measure, we suggest that UMBRAE could be a good choice to evaluate forecasting methods, especially for cases where measures based on geometric mean of relative errors, such as the geometric mean relative absolute error, are preferred.

  13. [Comparison of three daily global solar radiation models].

    PubMed

    Yang, Jin-Ming; Fan, Wen-Yi; Zhao, Ying-Hui

    2014-08-01

    Three daily global solar radiation estimation models ( Å-P model, Thornton-Running model and model provided by Liu Ke-qun et al.) were analyzed and compared using data of 13 weather stations from 1982 to 2012 from three northeastern provinces and eastern Inner Mongolia. After cross-validation analysis, the result showed that mean absolute error (MAE) for each model was 1.71, 2.83 and 1.68 MJ x m(-2) x d(-1) respectively, showing that Å-P model and model provided by Liu Ke-qun et al. which used percentage of sunshine had an advantage over Thornton-Running model which didn't use percentage of sunshine. Model provided by Liu Ke-qun et al. played a good effect on the situation of non-sunshine, and its MAE and bias percentage were 18.5% and 33.8% smaller than those of Å-P model, respectively. High precision results could be obtained by using the simple linear model of Å-P. Å-P model, Thornton-Running model and model provided by Liu Ke-qun et al. overvalued daily global solar radiation by 12.2%, 19.2% and 9.9% respectively. MAE for each station varied little with the spatial change of location, and annual MAE decreased with the advance of years. The reason for this might be that the change of observation accuracy caused by the replacement of radiation instrument in 1993. MAEs for rainy days, non-sunshine days and warm seasons of the three models were greater than those for days without rain, sunshine days and cold seasons respectively, showing that different methods should be used for different weather conditions on estimating solar radiation with meteorological elements.

  14. Deep learning methods for protein torsion angle prediction.

    PubMed

    Li, Haiou; Hou, Jie; Adhikari, Badri; Lyu, Qiang; Cheng, Jianlin

    2017-09-18

    Deep learning is one of the most powerful machine learning methods that has achieved the state-of-the-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a number of areas such as protein residue-residue contact prediction, secondary structure prediction, and fold recognition. In this work, we developed deep learning methods to improve the prediction of torsion (dihedral) angles of proteins. We design four different deep learning architectures to predict protein torsion angles. The architectures including deep neural network (DNN) and deep restricted Boltzmann machine (DRBN), deep recurrent neural network (DRNN) and deep recurrent restricted Boltzmann machine (DReRBM) since the protein torsion angle prediction is a sequence related problem. In addition to existing protein features, two new features (predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments) are used as input to each of the four deep learning architectures to predict phi and psi angles of protein backbone. The mean absolute error (MAE) of phi and psi angles predicted by DRNN, DReRBM, DRBM and DNN is about 20-21° and 29-30° on an independent dataset. The MAE of phi angle is comparable to the existing methods, but the MAE of psi angle is 29°, 2° lower than the existing methods. On the latest CASP12 targets, our methods also achieved the performance better than or comparable to a state-of-the art method. Our experiment demonstrates that deep learning is a valuable method for predicting protein torsion angles. The deep recurrent network architecture performs slightly better than deep feed-forward architecture, and the predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments are useful features for improving prediction accuracy.

  15. Smartphone application for mechanical quality assurance of medical linear accelerators

    NASA Astrophysics Data System (ADS)

    Kim, Hwiyoung; Lee, Hyunseok; In Park, Jong; Choi, Chang Heon; Park, So-Yeon; Kim, Hee Jung; Kim, Young Suk; Ye, Sung-Joon

    2017-06-01

    Mechanical quality assurance (QA) of medical linear accelerators consists of time-consuming and human-error-prone procedures. We developed a smartphone application system for mechanical QA. The system consists of two smartphones: one attached to a gantry for obtaining real-time information on the mechanical parameters of the medical linear accelerator, and another displaying real-time information via a Bluetooth connection with the former. Motion sensors embedded in the smartphone were used to measure gantry and collimator rotations. Images taken by the smartphone’s high-resolution camera were processed to evaluate accuracies of jaw-positioning, crosshair centering and source-to-surface distance (SSD). The application was developed using Android software development kit and OpenCV library. The accuracy and precision of the system was validated against an optical rotation stage and digital calipers, prior to routine QA measurements of five medical linear accelerators. The system accuracy and precision in measuring angles and lengths were determined to be 0.05  ±  0.05° and 0.25  ±  0.14 mm, respectively. The mean absolute errors (MAEs) in QA measurements of gantry and collimator rotation were 0.05  ±  0.04° and 0.05  ±  0.04°, respectively. The MAE in QA measurements of light field was 0.39  ±  0.36 mm. The MAEs in QA measurements of crosshair centering and SSD were 0.40  ±  0.35 mm and 0.41  ±  0.32 mm, respectively. In conclusion, most routine mechanical QA procedures could be performed using the smartphone application system with improved precision and within a shorter time-frame, while eliminating potential human errors.

  16. Smartphone application for mechanical quality assurance of medical linear accelerators.

    PubMed

    Kim, Hwiyoung; Lee, Hyunseok; Park, Jong In; Choi, Chang Heon; Park, So-Yeon; Kim, Hee Jung; Kim, Young Suk; Ye, Sung-Joon

    2017-06-07

    Mechanical quality assurance (QA) of medical linear accelerators consists of time-consuming and human-error-prone procedures. We developed a smartphone application system for mechanical QA. The system consists of two smartphones: one attached to a gantry for obtaining real-time information on the mechanical parameters of the medical linear accelerator, and another displaying real-time information via a Bluetooth connection with the former. Motion sensors embedded in the smartphone were used to measure gantry and collimator rotations. Images taken by the smartphone's high-resolution camera were processed to evaluate accuracies of jaw-positioning, crosshair centering and source-to-surface distance (SSD). The application was developed using Android software development kit and OpenCV library. The accuracy and precision of the system was validated against an optical rotation stage and digital calipers, prior to routine QA measurements of five medical linear accelerators. The system accuracy and precision in measuring angles and lengths were determined to be 0.05  ±  0.05° and 0.25  ±  0.14 mm, respectively. The mean absolute errors (MAEs) in QA measurements of gantry and collimator rotation were 0.05  ±  0.04° and 0.05  ±  0.04°, respectively. The MAE in QA measurements of light field was 0.39  ±  0.36 mm. The MAEs in QA measurements of crosshair centering and SSD were 0.40  ±  0.35 mm and 0.41  ±  0.32 mm, respectively. In conclusion, most routine mechanical QA procedures could be performed using the smartphone application system with improved precision and within a shorter time-frame, while eliminating potential human errors.

  17. Comprehensive modeling of monthly mean soil temperature using multivariate adaptive regression splines and support vector machine

    NASA Astrophysics Data System (ADS)

    Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

    2017-07-01

    Soil temperature (T s) and its thermal regime are the most important factors in plant growth, biological activities, and water movement in soil. Due to scarcity of the T s data, estimation of soil temperature is an important issue in different fields of sciences. The main objective of the present study is to investigate the accuracy of multivariate adaptive regression splines (MARS) and support vector machine (SVM) methods for estimating the T s. For this aim, the monthly mean data of the T s (at depths of 5, 10, 50, and 100 cm) and meteorological parameters of 30 synoptic stations in Iran were utilized. To develop the MARS and SVM models, various combinations of minimum, maximum, and mean air temperatures (T min, T max, T); actual and maximum possible sunshine duration; sunshine duration ratio (n, N, n/N); actual, net, and extraterrestrial solar radiation data (R s, R n, R a); precipitation (P); relative humidity (RH); wind speed at 2 m height (u 2); and water vapor pressure (Vp) were used as input variables. Three error statistics including root-mean-square-error (RMSE), mean absolute error (MAE), and determination coefficient (R 2) were used to check the performance of MARS and SVM models. The results indicated that the MARS was superior to the SVM at different depths. In the test and validation phases, the most accurate estimations for the MARS were obtained at the depth of 10 cm for T max, T min, T inputs (RMSE = 0.71 °C, MAE = 0.54 °C, and R 2 = 0.995) and for RH, V p, P, and u 2 inputs (RMSE = 0.80 °C, MAE = 0.61 °C, and R 2 = 0.996), respectively.

  18. Generation, Validation, and Application of Abundance Map Reference Data for Spectral Unmixing

    NASA Astrophysics Data System (ADS)

    Williams, McKay D.

    coarse scale imagery-specific AMRD, and 3) demonstration of comparisons between coarse scale unmixing abundances and AMRD. Spatial alignment was performed using our scene-wide spectral comparison (SWSC) algorithm, which aligned imagery with accuracy approaching the distance of a single fine scale pixel. We compared simple rectangular aggregation to coarse sensor point spread function (PSF) aggregation, and found that the PSF approach returned lower error, but that rectangular aggregation more accurately estimated true abundances at ground level. We demonstrated various metrics for comparing unmixing results to AMRD, including mean absolute error (MAE) and linear regression (LR). We additionally introduced reference data mean adjusted MAE (MA-MAE), and reference data confidence interval adjusted MAE (CIA-MAE), which account for known error in the reference data itself. MA-MAE analysis indicated that fully constrained linear unmixing of coarse scale imagery across all three scenes returned an error of 10.83% per class and pixel, with regression analysis yielding a slope = 0.85, intercept = 0.04, and R2 = 0.81. Our reference data research has demonstrated a viable methodology to efficiently generate, validate, and apply AMRD to specific examples of airborne remote sensing imagery, thereby enabling direct quantitative assessment of spectral unmixing performance.

  19. Assessment of errors in static electrical impedance tomography with adjacent and trigonometric current patterns.

    PubMed

    Kolehmainen, V; Vauhkonen, M; Karjalainen, P A; Kaipio, J P

    1997-11-01

    In electrical impedance tomography (EIT), difference imaging is often preferred over static imaging. This is because of the many unknowns in the forward modelling which make it difficult to obtain reliable absolute resistivity estimates. However, static imaging and absolute resistivity values are needed in some potential applications of EIT. In this paper we demonstrate by simulation the effects of different error components that are included in the reconstruction of static EIT images. All simulations are carried out in two dimensions with the so-called complete electrode model. Errors that are considered are the modelling error in the boundary shape of an object, errors in the electrode sizes and localizations and errors in the contact impedances under the electrodes. Results using both adjacent and trigonometric current patterns are given.

  20. Corsica: A Multi-Mission Absolute Calibration Site

    NASA Astrophysics Data System (ADS)

    Bonnefond, P.; Exertier, P.; Laurain, O.; Guinle, T.; Femenias, P.

    2013-09-01

    In collaboration with the CNES and NASA oceanographic projects (TOPEX/Poseidon and Jason), the OCA (Observatoire de la Côte d'Azur) developed a verification site in Corsica since 1996, operational since 1998. CALibration/VALidation embraces a wide variety of activities, ranging from the interpretation of information from internal-calibration modes of the sensors to validation of the fully corrected estimates of the reflector heights using in situ data. Now, Corsica is, like the Harvest platform (NASA side) [14], an operating calibration site able to support a continuous monitoring with a high level of accuracy: a 'point calibration' which yields instantaneous bias estimates with a 10-day repeatability of 30 mm (standard deviation) and mean errors of 4 mm (standard error). For a 35-day repeatability (ERS, Envisat), due to a smaller time series, the standard error is about the double ( 7 mm).In this paper, we will present updated results of the absolute Sea Surface Height (SSH) biases for TOPEX/Poseidon (T/P), Jason-1, Jason-2, ERS-2 and Envisat.

  1. Left-hemisphere activation is associated with enhanced vocal pitch error detection in musicians with absolute pitch

    PubMed Central

    Behroozmand, Roozbeh; Ibrahim, Nadine; Korzyukov, Oleg; Robin, Donald A.; Larson, Charles R.

    2014-01-01

    The ability to process auditory feedback for vocal pitch control is crucial during speaking and singing. Previous studies have suggested that musicians with absolute pitch (AP) develop specialized left-hemisphere mechanisms for pitch processing. The present study adopted an auditory feedback pitch perturbation paradigm combined with ERP recordings to test the hypothesis whether the neural mechanisms of the left-hemisphere enhance vocal pitch error detection and control in AP musicians compared with relative pitch (RP) musicians and non-musicians (NM). Results showed a stronger N1 response to pitch-shifted voice feedback in the right-hemisphere for both AP and RP musicians compared with the NM group. However, the left-hemisphere P2 component activation was greater in AP and RP musicians compared with NMs and also for the AP compared with RP musicians. The NM group was slower in generating compensatory vocal reactions to feedback pitch perturbation compared with musicians, and they failed to re-adjust their vocal pitch after the feedback perturbation was removed. These findings suggest that in the earlier stages of cortical neural processing, the right hemisphere is more active in musicians for detecting pitch changes in voice feedback. In the later stages, the left-hemisphere is more active during the processing of auditory feedback for vocal motor control and seems to involve specialized mechanisms that facilitate pitch processing in the AP compared with RP musicians. These findings indicate that the left hemisphere mechanisms of AP ability are associated with improved auditory feedback pitch processing during vocal pitch control in tasks such as speaking or singing. PMID:24355545

  2. Absolute angular encoder based on optical diffraction

    NASA Astrophysics Data System (ADS)

    Wu, Jian; Zhou, Tingting; Yuan, Bo; Wang, Liqiang

    2015-08-01

    A new encoding method for absolute angular encoder based on optical diffraction was proposed in the present study. In this method, an encoder disc is specially designed that a series of elements are uniformly spaced in one circle and each element is consisted of four diffraction gratings, which are tilted in the directions of 30°, 60°, -60° and -30°, respectively. The disc is illuminated by a coherent light and the diffractive signals are received. The positions of diffractive spots are used for absolute encoding and their intensities are for subdivision, which is different from the traditional optical encoder based on transparent/opaque binary principle. Since the track's width in the disc is not limited in the diffraction pattern, it provides a new way to solve the contradiction between the size and resolution, which is good for minimization of encoder. According to the proposed principle, the diffraction pattern disc with a diameter of 40 mm was made by lithography in the glass substrate. A prototype of absolute angular encoder with a resolution of 20" was built up. Its maximum error was tested as 78" by comparing with a small angle measuring system based on laser beam deflection.

  3. Using a Hybrid Model to Forecast the Prevalence of Schistosomiasis in Humans

    PubMed Central

    Zhou, Lingling; Xia, Jing; Yu, Lijing; Wang, Ying; Shi, Yun; Cai, Shunxiang; Nie, Shaofa

    2016-01-01

    Background: We previously proposed a hybrid model combining both the autoregressive integrated moving average (ARIMA) and the nonlinear autoregressive neural network (NARNN) models in forecasting schistosomiasis. Our purpose in the current study was to forecast the annual prevalence of human schistosomiasis in Yangxin County, using our ARIMA-NARNN model, thereby further certifying the reliability of our hybrid model. Methods: We used the ARIMA, NARNN and ARIMA-NARNN models to fit and forecast the annual prevalence of schistosomiasis. The modeling time range included was the annual prevalence from 1956 to 2008 while the testing time range included was from 2009 to 2012. The mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) were used to measure the model performance. We reconstructed the hybrid model to forecast the annual prevalence from 2013 to 2016. Results: The modeling and testing errors generated by the ARIMA-NARNN model were lower than those obtained from either the single ARIMA or NARNN models. The predicted annual prevalence from 2013 to 2016 demonstrated an initial decreasing trend, followed by an increase. Conclusions: The ARIMA-NARNN model can be well applied to analyze surveillance data for early warning systems for the control and elimination of schistosomiasis. PMID:27023573

  4. Globular Clusters: Absolute Proper Motions and Galactic Orbits

    NASA Astrophysics Data System (ADS)

    Chemel, A. A.; Glushkova, E. V.; Dambis, A. K.; Rastorguev, A. S.; Yalyalieva, L. N.; Klinichev, A. D.

    2018-04-01

    We cross-match objects from several different astronomical catalogs to determine the absolute proper motions of stars within the 30-arcmin radius fields of 115 Milky-Way globular clusters with the accuracy of 1-2 mas yr-1. The proper motions are based on positional data recovered from the USNO-B1, 2MASS, URAT1, ALLWISE, UCAC5, and Gaia DR1 surveys with up to ten positions spanning an epoch difference of up to about 65 years, and reduced to Gaia DR1 TGAS frame using UCAC5 as the reference catalog. Cluster members are photometrically identified by selecting horizontal- and red-giant branch stars on color-magnitude diagrams, and the mean absolute proper motions of the clusters with a typical formal error of about 0.4 mas yr-1 are computed by averaging the proper motions of selected members. The inferred absolute proper motions of clusters are combined with available radial-velocity data and heliocentric distance estimates to compute the cluster orbits in terms of the Galactic potential models based on Miyamoto and Nagai disk, Hernquist spheroid, and modified isothermal dark-matter halo (axisymmetric model without a bar) and the same model + rotating Ferre's bar (non-axisymmetric). Five distant clusters have higher-than-escape velocities, most likely due to large errors of computed transversal velocities, whereas the computed orbits of all other clusters remain bound to the Galaxy. Unlike previously published results, we find the bar to affect substantially the orbits of most of the clusters, even those at large Galactocentric distances, bringing appreciable chaotization, especially in the portions of the orbits close to the Galactic center, and stretching out the orbits of some of the thick-disk clusters.

  5. Error Analysis of Wind Measurements for the University of Illinois Sodium Doppler Temperature System

    NASA Technical Reports Server (NTRS)

    Pfenninger, W. Matthew; Papen, George C.

    1992-01-01

    Four-frequency lidar measurements of temperature and wind velocity require accurate frequency tuning to an absolute reference and long term frequency stability. We quantify frequency tuning errors for the Illinois sodium system, to measure absolute frequencies and a reference interferometer to measure relative frequencies. To determine laser tuning errors, we monitor the vapor cell and interferometer during lidar data acquisition and analyze the two signals for variations as functions of time. Both sodium cell and interferometer are the same as those used to frequency tune the laser. By quantifying the frequency variations of the laser during data acquisition, an error analysis of temperature and wind measurements can be calculated. These error bounds determine the confidence in the calculated temperatures and wind velocities.

  6. Intelligent Ensemble Forecasting System of Stock Market Fluctuations Based on Symetric and Asymetric Wavelet Functions

    NASA Astrophysics Data System (ADS)

    Lahmiri, Salim; Boukadoum, Mounir

    2015-08-01

    We present a new ensemble system for stock market returns prediction where continuous wavelet transform (CWT) is used to analyze return series and backpropagation neural networks (BPNNs) for processing CWT-based coefficients, determining the optimal ensemble weights, and providing final forecasts. Particle swarm optimization (PSO) is used for finding optimal weights and biases for each BPNN. To capture symmetry/asymmetry in the underlying data, three wavelet functions with different shapes are adopted. The proposed ensemble system was tested on three Asian stock markets: The Hang Seng, KOSPI, and Taiwan stock market data. Three statistical metrics were used to evaluate the forecasting accuracy; including, mean of absolute errors (MAE), root mean of squared errors (RMSE), and mean of absolute deviations (MADs). Experimental results showed that our proposed ensemble system outperformed the individual CWT-ANN models each with different wavelet function. In addition, the proposed ensemble system outperformed the conventional autoregressive moving average process. As a result, the proposed ensemble system is suitable to capture symmetry/asymmetry in financial data fluctuations for better prediction accuracy.

  7. Error Analysis of non-TLD HDR Brachytherapy Dosimetric Techniques

    NASA Astrophysics Data System (ADS)

    Amoush, Ahmad

    The American Association of Physicists in Medicine Task Group Report43 (AAPM-TG43) and its updated version TG-43U1 rely on the LiF TLD detector to determine the experimental absolute dose rate for brachytherapy. The recommended uncertainty estimates associated with TLD experimental dosimetry include 5% for statistical errors (Type A) and 7% for systematic errors (Type B). TG-43U1 protocol does not include recommendation for other experimental dosimetric techniques to calculate the absolute dose for brachytherapy. This research used two independent experimental methods and Monte Carlo simulations to investigate and analyze uncertainties and errors associated with absolute dosimetry of HDR brachytherapy for a Tandem applicator. An A16 MicroChamber* and one dose MOSFET detectors† were selected to meet the TG-43U1 recommendations for experimental dosimetry. Statistical and systematic uncertainty analyses associated with each experimental technique were analyzed quantitatively using MCNPX 2.6‡ to evaluate source positional error, Tandem positional error, the source spectrum, phantom size effect, reproducibility, temperature and pressure effects, volume averaging, stem and wall effects, and Tandem effect. Absolute dose calculations for clinical use are based on Treatment Planning System (TPS) with no corrections for the above uncertainties. Absolute dose and uncertainties along the transverse plane were predicted for the A16 microchamber. The generated overall uncertainties are 22%, 17%, 15%, 15%, 16%, 17%, and 19% at 1cm, 2cm, 3cm, 4cm, and 5cm, respectively. Predicting the dose beyond 5cm is complicated due to low signal-to-noise ratio, cable effect, and stem effect for the A16 microchamber. Since dose beyond 5cm adds no clinical information, it has been ignored in this study. The absolute dose was predicted for the MOSFET detector from 1cm to 7cm along the transverse plane. The generated overall uncertainties are 23%, 11%, 8%, 7%, 7%, 9%, and 8% at 1cm, 2cm, 3cm

  8. A Model of Self-Monitoring Blood Glucose Measurement Error.

    PubMed

    Vettoretti, Martina; Facchinetti, Andrea; Sparacino, Giovanni; Cobelli, Claudio

    2017-07-01

    A reliable model of the probability density function (PDF) of self-monitoring of blood glucose (SMBG) measurement error would be important for several applications in diabetes, like testing in silico insulin therapies. In the literature, the PDF of SMBG error is usually described by a Gaussian function, whose symmetry and simplicity are unable to properly describe the variability of experimental data. Here, we propose a new methodology to derive more realistic models of SMBG error PDF. The blood glucose range is divided into zones where error (absolute or relative) presents a constant standard deviation (SD). In each zone, a suitable PDF model is fitted by maximum-likelihood to experimental data. Model validation is performed by goodness-of-fit tests. The method is tested on two databases collected by the One Touch Ultra 2 (OTU2; Lifescan Inc, Milpitas, CA) and the Bayer Contour Next USB (BCN; Bayer HealthCare LLC, Diabetes Care, Whippany, NJ). In both cases, skew-normal and exponential models are used to describe the distribution of errors and outliers, respectively. Two zones were identified: zone 1 with constant SD absolute error; zone 2 with constant SD relative error. Goodness-of-fit tests confirmed that identified PDF models are valid and superior to Gaussian models used so far in the literature. The proposed methodology allows to derive realistic models of SMBG error PDF. These models can be used in several investigations of present interest in the scientific community, for example, to perform in silico clinical trials to compare SMBG-based with nonadjunctive CGM-based insulin treatments.

  9. TU-AB-BRA-03: Atlas-Based Algorithms with Local Registration-Goodness Weighting for MRI-Driven Electron Density Mapping

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Farjam, R; Tyagi, N; Veeraraghavan, H

    Purpose: To develop image-analysis algorithms to synthesize CT with accurate electron densities for MR-only radiotherapy of head & neck (H&N) and pelvis anatomies. Methods: CT and 3T-MRI (Philips, mDixon sequence) scans were randomly selected from a pool of H&N (n=11) and pelvis (n=12) anatomies to form an atlas. All MRIs were pre-processed to eliminate scanner and patient-induced intensity inhomogeneities and standardize their intensity histograms. CT and MRI for each patient were then co-registered to construct CT-MRI atlases. For more accurate CT-MR fusion, bone intensities in CT were suppressed to improve the similarity between CT and MRI. For a new patient,more » all CT-MRI atlases are deformed onto the new patients’ MRI initially. A newly-developed generalized registration error (GRE) metric was then calculated as a measure of local registration accuracy. The synthetic CT value at each point is a 1/GRE-weighted average of CTs from all CT-MR atlases. For evaluation, the mean absolute error (MAE) between the original and synthetic CT (generated in a leave-one-out scheme) was computed. The planning dose from the original and synthetic CT was also compared. Results: For H&N patients, MAE was 67±9, 114±22, and 116±9 HU over the entire-CT, air and bone regions, respectively. For pelvis anatomy, MAE was 47±5 and 146±14 for the entire and bone regions. In comparison with MIRADA medical, an FDA-approved registration tool, we found that our proposed registration strategy reduces MAE by ∼30% and ∼50% over the entire and bone regions, respectively. GRE-weighted strategy further lowers MAE by ∼15% to ∼40%. Our primary dose calculation also showed highly consistent results between the original and synthetic CT. Conclusion: We’ve developed a novel image-analysis technique to synthesize CT for H&N and pelvis anatomies. Our proposed image fusion strategy and GRE metric help generate more accurate synthetic CT using locally more similar atlases (Support

  10. Twice cutting method reduces tibial cutting error in unicompartmental knee arthroplasty.

    PubMed

    Inui, Hiroshi; Taketomi, Shuji; Yamagami, Ryota; Sanada, Takaki; Tanaka, Sakae

    2016-01-01

    Bone cutting error can be one of the causes of malalignment in unicompartmental knee arthroplasty (UKA). The amount of cutting error in total knee arthroplasty has been reported. However, none have investigated cutting error in UKA. The purpose of this study was to reveal the amount of cutting error in UKA when open cutting guide was used and clarify whether cutting the tibia horizontally twice using the same cutting guide reduced the cutting errors in UKA. We measured the alignment of the tibial cutting guides, the first-cut cutting surfaces and the second cut cutting surfaces using the navigation system in 50 UKAs. Cutting error was defined as the angular difference between the cutting guide and cutting surface. The mean absolute first-cut cutting error was 1.9° (1.1° varus) in the coronal plane and 1.1° (0.6° anterior slope) in the sagittal plane, whereas the mean absolute second-cut cutting error was 1.1° (0.6° varus) in the coronal plane and 1.1° (0.4° anterior slope) in the sagittal plane. Cutting the tibia horizontally twice reduced the cutting errors in the coronal plane significantly (P<0.05). Our study demonstrated that in UKA, cutting the tibia horizontally twice using the same cutting guide reduced cutting error in the coronal plane. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. Automated absolute phase retrieval in across-track interferometry

    NASA Technical Reports Server (NTRS)

    Madsen, Soren N.; Zebker, Howard A.

    1992-01-01

    Discussed is a key element in the processing of topographic radar maps acquired by the NASA/JPL airborne synthetic aperture radar configured as an across-track interferometer (TOPSAR). TOPSAR utilizes a single transmit and two receive antennas; the three-dimensional target location is determined by triangulation based on a known baseline and two measured slant ranges. The slant range difference is determined very accurately from the phase difference between the signals received by the two antennas. This phase is measured modulo 2pi, whereas it is the absolute phase which relates directly to the difference in slant range. It is shown that splitting the range bandwidth into two subbands in the processor and processing each individually allows for the absolute phase. The underlying principles and system errors which must be considered are discussed, together with the implementation and results from processing data acquired during the summer of 1991.

  12. An absolute cavity pyrgeometer to measure the absolute outdoor longwave irradiance with traceability to international system of units, SI

    NASA Astrophysics Data System (ADS)

    Reda, Ibrahim; Zeng, Jinan; Scheuch, Jonathan; Hanssen, Leonard; Wilthan, Boris; Myers, Daryl; Stoffel, Tom

    2012-03-01

    This article describes a method of measuring the absolute outdoor longwave irradiance using an absolute cavity pyrgeometer (ACP), U.S. Patent application no. 13/049, 275. The ACP consists of domeless thermopile pyrgeometer, gold-plated concentrator, temperature controller, and data acquisition. The dome was removed from the pyrgeometer to remove errors associated with dome transmittance and the dome correction factor. To avoid thermal convection and wind effect errors resulting from using a domeless thermopile, the gold-plated concentrator was placed above the thermopile. The concentrator is a dual compound parabolic concentrator (CPC) with 180° view angle to measure the outdoor incoming longwave irradiance from the atmosphere. The incoming irradiance is reflected from the specular gold surface of the CPC and concentrated on the 11 mm diameter of the pyrgeometer's blackened thermopile. The CPC's interior surface design and the resulting cavitation result in a throughput value that was characterized by the National Institute of Standards and Technology. The ACP was installed horizontally outdoor on an aluminum plate connected to the temperature controller to control the pyrgeometer's case temperature. The responsivity of the pyrgeometer's thermopile detector was determined by lowering the case temperature and calculating the rate of change of the thermopile output voltage versus the changing net irradiance. The responsivity is then used to calculate the absolute atmospheric longwave irradiance with an uncertainty estimate (U95) of ±3.96 W m-2 with traceability to the International System of Units, SI. The measured irradiance was compared with the irradiance measured by two pyrgeometers calibrated by the World Radiation Center with traceability to the Interim World Infrared Standard Group, WISG. A total of 408 readings were collected over three different nights. The calculated irradiance measured by the ACP was 1.5 W/m2 lower than that measured by the two

  13. Left-hemisphere activation is associated with enhanced vocal pitch error detection in musicians with absolute pitch.

    PubMed

    Behroozmand, Roozbeh; Ibrahim, Nadine; Korzyukov, Oleg; Robin, Donald A; Larson, Charles R

    2014-02-01

    The ability to process auditory feedback for vocal pitch control is crucial during speaking and singing. Previous studies have suggested that musicians with absolute pitch (AP) develop specialized left-hemisphere mechanisms for pitch processing. The present study adopted an auditory feedback pitch perturbation paradigm combined with ERP recordings to test the hypothesis whether the neural mechanisms of the left-hemisphere enhance vocal pitch error detection and control in AP musicians compared with relative pitch (RP) musicians and non-musicians (NM). Results showed a stronger N1 response to pitch-shifted voice feedback in the right-hemisphere for both AP and RP musicians compared with the NM group. However, the left-hemisphere P2 component activation was greater in AP and RP musicians compared with NMs and also for the AP compared with RP musicians. The NM group was slower in generating compensatory vocal reactions to feedback pitch perturbation compared with musicians, and they failed to re-adjust their vocal pitch after the feedback perturbation was removed. These findings suggest that in the earlier stages of cortical neural processing, the right hemisphere is more active in musicians for detecting pitch changes in voice feedback. In the later stages, the left-hemisphere is more active during the processing of auditory feedback for vocal motor control and seems to involve specialized mechanisms that facilitate pitch processing in the AP compared with RP musicians. These findings indicate that the left hemisphere mechanisms of AP ability are associated with improved auditory feedback pitch processing during vocal pitch control in tasks such as speaking or singing. Copyright © 2013 Elsevier Inc. All rights reserved.

  14. Spatial and temporal variability of the overall error of National Atmospheric Deposition Program measurements determined by the USGS collocated-sampler program, water years 1989-2001

    USGS Publications Warehouse

    Wetherbee, G.A.; Latysh, N.E.; Gordon, J.D.

    2005-01-01

    Data from the U.S. Geological Survey (USGS) collocated-sampler program for the National Atmospheric Deposition Program/National Trends Network (NADP/NTN) are used to estimate the overall error of NADP/NTN measurements. Absolute errors are estimated by comparison of paired measurements from collocated instruments. Spatial and temporal differences in absolute error were identified and are consistent with longitudinal distributions of NADP/NTN measurements and spatial differences in precipitation characteristics. The magnitude of error for calcium, magnesium, ammonium, nitrate, and sulfate concentrations, specific conductance, and sample volume is of minor environmental significance to data users. Data collected after a 1994 sample-handling protocol change are prone to less absolute error than data collected prior to 1994. Absolute errors are smaller during non-winter months than during winter months for selected constituents at sites where frozen precipitation is common. Minimum resolvable differences are estimated for different regions of the USA to aid spatial and temporal watershed analyses.

  15. Elevation correction factor for absolute pressure measurements

    NASA Technical Reports Server (NTRS)

    Panek, Joseph W.; Sorrells, Mark R.

    1996-01-01

    With the arrival of highly accurate multi-port pressure measurement systems, conditions that previously did not affect overall system accuracy must now be scrutinized closely. Errors caused by elevation differences between pressure sensing elements and model pressure taps can be quantified and corrected. With multi-port pressure measurement systems, the sensing elements are connected to pressure taps that may be many feet away. The measurement system may be at a different elevation than the pressure taps due to laboratory space or test article constraints. This difference produces a pressure gradient that is inversely proportional to height within the interface tube. The pressure at the bottom of the tube will be higher than the pressure at the top due to the weight of the tube's column of air. Tubes with higher pressures will exhibit larger absolute errors due to the higher air density. The above effect is well documented but has generally been taken into account with large elevations only. With error analysis techniques, the loss in accuracy from elevation can be easily quantified. Correction factors can be applied to maintain the high accuracies of new pressure measurement systems.

  16. [Spatial interpolation of soil organic matter using regression Kriging and geographically weighted regression Kriging].

    PubMed

    Yang, Shun-hua; Zhang, Hai-tao; Guo, Long; Ren, Yan

    2015-06-01

    Relative elevation and stream power index were selected as auxiliary variables based on correlation analysis for mapping soil organic matter. Geographically weighted regression Kriging (GWRK) and regression Kriging (RK) were used for spatial interpolation of soil organic matter and compared with ordinary Kriging (OK), which acts as a control. The results indicated that soil or- ganic matter was significantly positively correlated with relative elevation whilst it had a significantly negative correlation with stream power index. Semivariance analysis showed that both soil organic matter content and its residuals (including ordinary least square regression residual and GWR resi- dual) had strong spatial autocorrelation. Interpolation accuracies by different methods were esti- mated based on a data set of 98 validation samples. Results showed that the mean error (ME), mean absolute error (MAE) and root mean square error (RMSE) of RK were respectively 39.2%, 17.7% and 20.6% lower than the corresponding values of OK, with a relative-improvement (RI) of 20.63. GWRK showed a similar tendency, having its ME, MAE and RMSE to be respectively 60.6%, 23.7% and 27.6% lower than those of OK, with a RI of 59.79. Therefore, both RK and GWRK significantly improved the accuracy of OK interpolation of soil organic matter due to their in- corporation of auxiliary variables. In addition, GWRK performed obviously better than RK did in this study, and its improved performance should be attributed to the consideration of sample spatial locations.

  17. Artificial Neural Network to Predict Vine Water Status Spatial Variability Using Multispectral Information Obtained from an Unmanned Aerial Vehicle (UAV).

    PubMed

    Poblete, Tomas; Ortega-Farías, Samuel; Moreno, Miguel Angel; Bardeen, Matthew

    2017-10-30

    Water stress, which affects yield and wine quality, is often evaluated using the midday stem water potential (Ψ stem ). However, this measurement is acquired on a per plant basis and does not account for the assessment of vine water status spatial variability. The use of multispectral cameras mounted on unmanned aerial vehicle (UAV) is capable to capture the variability of vine water stress in a whole field scenario. It has been reported that conventional multispectral indices (CMI) that use information between 500-800 nm, do not accurately predict plant water status since they are not sensitive to water content. The objective of this study was to develop artificial neural network (ANN) models derived from multispectral images to predict the Ψ stem spatial variability of a drip-irrigated Carménère vineyard in Talca, Maule Region, Chile. The coefficient of determination (R²) obtained between ANN outputs and ground-truth measurements of Ψ stem were between 0.56-0.87, with the best performance observed for the model that included the bands 550, 570, 670, 700 and 800 nm. Validation analysis indicated that the ANN model could estimate Ψ stem with a mean absolute error (MAE) of 0.1 MPa, root mean square error (RMSE) of 0.12 MPa, and relative error (RE) of -9.1%. For the validation of the CMI, the MAE, RMSE and RE values were between 0.26-0.27 MPa, 0.32-0.34 MPa and -24.2-25.6%, respectively.

  18. Solid waste forecasting using modified ANFIS modeling.

    PubMed

    Younes, Mohammad K; Nopiah, Z M; Basri, N E Ahmad; Basri, H; Abushammala, Mohammed F M; K N A, Maulud

    2015-10-01

    Solid waste prediction is crucial for sustainable solid waste management. Usually, accurate waste generation record is challenge in developing countries which complicates the modelling process. Solid waste generation is related to demographic, economic, and social factors. However, these factors are highly varied due to population and economy growths. The objective of this research is to determine the most influencing demographic and economic factors that affect solid waste generation using systematic approach, and then develop a model to forecast solid waste generation using a modified Adaptive Neural Inference System (MANFIS). The model evaluation was performed using Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and the coefficient of determination (R²). The results show that the best input variables are people age groups 0-14, 15-64, and people above 65 years, and the best model structure is 3 triangular fuzzy membership functions and 27 fuzzy rules. The model has been validated using testing data and the resulted training RMSE, MAE and R² were 0.2678, 0.045 and 0.99, respectively, while for testing phase RMSE =3.986, MAE = 0.673 and R² = 0.98. To date, a few attempts have been made to predict the annual solid waste generation in developing countries. This paper presents modeling of annual solid waste generation using Modified ANFIS, it is a systematic approach to search for the most influencing factors and then modify the ANFIS structure to simplify the model. The proposed method can be used to forecast the waste generation in such developing countries where accurate reliable data is not always available. Moreover, annual solid waste prediction is essential for sustainable planning.

  19. Hybrid artificial intelligence approach based on neural fuzzy inference model and metaheuristic optimization for flood susceptibilitgy modeling in a high-frequency tropical cyclone area using GIS

    NASA Astrophysics Data System (ADS)

    Tien Bui, Dieu; Pradhan, Biswajeet; Nampak, Haleh; Bui, Quang-Thanh; Tran, Quynh-An; Nguyen, Quoc-Phi

    2016-09-01

    This paper proposes a new artificial intelligence approach based on neural fuzzy inference system and metaheuristic optimization for flood susceptibility modeling, namely MONF. In the new approach, the neural fuzzy inference system was used to create an initial flood susceptibility model and then the model was optimized using two metaheuristic algorithms, Evolutionary Genetic and Particle Swarm Optimization. A high-frequency tropical cyclone area of the Tuong Duong district in Central Vietnam was used as a case study. First, a GIS database for the study area was constructed. The database that includes 76 historical flood inundated areas and ten flood influencing factors was used to develop and validate the proposed model. Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Receiver Operating Characteristic (ROC) curve, and area under the ROC curve (AUC) were used to assess the model performance and its prediction capability. Experimental results showed that the proposed model has high performance on both the training (RMSE = 0.306, MAE = 0.094, AUC = 0.962) and validation dataset (RMSE = 0.362, MAE = 0.130, AUC = 0.911). The usability of the proposed model was evaluated by comparing with those obtained from state-of-the art benchmark soft computing techniques such as J48 Decision Tree, Random Forest, Multi-layer Perceptron Neural Network, Support Vector Machine, and Adaptive Neuro Fuzzy Inference System. The results show that the proposed MONF model outperforms the above benchmark models; we conclude that the MONF model is a new alternative tool that should be used in flood susceptibility mapping. The result in this study is useful for planners and decision makers for sustainable management of flood-prone areas.

  20. Absolute plate velocities from seismic anisotropy: Importance of correlated errors

    NASA Astrophysics Data System (ADS)

    Zheng, Lin; Gordon, Richard G.; Kreemer, Corné

    2014-09-01

    The errors in plate motion azimuths inferred from shear wave splitting beneath any one tectonic plate are shown to be correlated with the errors of other azimuths from the same plate. To account for these correlations, we adopt a two-tier analysis: First, find the pole of rotation and confidence limits for each plate individually. Second, solve for the best fit to these poles while constraining relative plate angular velocities to consistency with the MORVEL relative plate angular velocities. Our preferred set of angular velocities, SKS-MORVEL, is determined from the poles from eight plates weighted proportionally to the root-mean-square velocity of each plate. SKS-MORVEL indicates that eight plates (Amur, Antarctica, Caribbean, Eurasia, Lwandle, Somalia, Sundaland, and Yangtze) have angular velocities that differ insignificantly from zero. The net rotation of the lithosphere is 0.25 ± 0.11° Ma-1 (95% confidence limits) right handed about 57.1°S, 68.6°E. The within-plate dispersion of seismic anisotropy for oceanic lithosphere (σ = 19.2°) differs insignificantly from that for continental lithosphere (σ = 21.6°). The between-plate dispersion, however, is significantly smaller for oceanic lithosphere (σ = 7.4°) than for continental lithosphere (σ = 14.7°). Two of the slowest-moving plates, Antarctica (vRMS = 4 mm a-1, σ = 29°) and Eurasia (vRMS = 3 mm a-1, σ = 33°), have two of the largest within-plate dispersions, which may indicate that a plate must move faster than ≈ 5 mm a-1 to result in seismic anisotropy useful for estimating plate motion. The tendency of observed azimuths on the Arabia plate to be counterclockwise of plate motion may provide information about the direction and amplitude of superposed asthenospheric flow or about anisotropy in the lithospheric mantle.

  1. A Novel Displacement and Tilt Detection Method Using Passive UHF RFID Technology.

    PubMed

    Lai, Xiaozheng; Cai, Zhirong; Xie, Zeming; Zhu, Hailong

    2018-05-21

    The displacement and tilt angle of an object are useful information for wireless monitoring applications. In this paper, a low-cost detection method based on passive radio frequency identification (RFID) technology is proposed. This method uses a standard ultrahigh-frequency (UHF) RFID reader to measure the phase variation of the tag response and detect the displacement and tilt angle of RFID tags attached to the targeted object. An accurate displacement result can be detected by the RFID system with a linearly polarized (LP) reader antenna. Based on the displacement results, an accurate tilt angle can also be detected by the RFID system with a circularly polarized (CP) reader antenna, which has been proved to have a linear relationship with the phase parameter of the tag’s backscattered wave. As far as accuracy is concerned, the mean absolute error (MAE) of displacement is less than 2 mm and the MAE of the tilt angle is less than 2.5° for an RFID system with 500 mm working range.

  2. Sparse dictionary for synthetic transmit aperture medical ultrasound imaging.

    PubMed

    Wang, Ping; Jiang, Jin-Yang; Li, Na; Luo, Han-Wu; Li, Fang; Cui, Shi-Gang

    2017-07-01

    It is possible to recover a signal below the Nyquist sampling limit using a compressive sensing technique in ultrasound imaging. However, the reconstruction enabled by common sparse transform approaches does not achieve satisfactory results. Considering the ultrasound echo signal's features of attenuation, repetition, and superposition, a sparse dictionary with the emission pulse signal is proposed. Sparse coefficients in the proposed dictionary have high sparsity. Images reconstructed with this dictionary were compared with those obtained with the three other common transforms, namely, discrete Fourier transform, discrete cosine transform, and discrete wavelet transform. The performance of the proposed dictionary was analyzed via a simulation and experimental data. The mean absolute error (MAE) was used to quantify the quality of the reconstructions. Experimental results indicate that the MAE associated with the proposed dictionary was always the smallest, the reconstruction time required was the shortest, and the lateral resolution and contrast of the reconstructed images were also the closest to the original images. The proposed sparse dictionary performed better than the other three sparse transforms. With the same sampling rate, the proposed dictionary achieved excellent reconstruction quality.

  3. Predicting the reference evapotranspiration based on tensor decomposition

    NASA Astrophysics Data System (ADS)

    Misaghian, Negin; Shamshirband, Shahaboddin; Petković, Dalibor; Gocic, Milan; Mohammadi, Kasra

    2017-11-01

    Most of the available models for reference evapotranspiration (ET0) estimation are based upon only an empirical equation for ET0. Thus, one of the main issues in ET0 estimation is the appropriate integration of time information and different empirical ET0 equations to determine ET0 and boost the precision. The FAO-56 Penman-Monteith, adjusted Hargreaves, Blaney-Criddle, Priestley-Taylor, and Jensen-Haise equations were utilized in this study for estimating ET0 for two stations of Belgrade and Nis in Serbia using collected data for the period of 1980 to 2010. Three-order tensor is used to capture three-way correlations among months, years, and ET0 information. Afterward, the latent correlations among ET0 parameters were found by the multiway analysis to enhance the quality of the prediction. The suggested method is valuable as it takes into account simultaneous relations between elements, boosts the prediction precision, and determines latent associations. Models are compared with respect to coefficient of determination ( R 2), mean absolute error (MAE), and root-mean-square error (RMSE). The proposed tensor approach has a R 2 value of greater than 0.9 for all selected ET0 methods at both selected stations, which is acceptable for the ET0 prediction. RMSE is ranged between 0.247 and 0.485 mm day-1 at Nis station and between 0.277 and 0.451 mm day-1 at Belgrade station, while MAE is between 0.140 and 0.337 mm day-1 at Nis and between 0.208 and 0.360 mm day-1 at Belgrade station. The best performances are achieved by Priestley-Taylor model at Nis station ( R 2 = 0.985, MAE = 0.140 mm day-1, RMSE = 0.247 mm day-1) and FAO-56 Penman-Monteith model at Belgrade station (MAE = 0.208 mm day-1, RMSE = 0.277 mm day-1, R 2 = 0.975).

  4. Comparison of the biometric formulas used for applanation A-scan ultrasound biometry.

    PubMed

    Özcura, Fatih; Aktaş, Serdar; Sağdık, Hacı Murat; Tetikoğlu, Mehmet

    2016-10-01

    The purpose of the study was to compare the accuracy of various biometric formulas for predicting postoperative refraction determined using applanation A-scan ultrasound. This retrospective comparative study included 485 eyes that underwent uneventful phacoemulsification with intraocular lens (IOL) implantation. Applanation A-scan ultrasound biometry and postoperative manifest refraction were obtained in all eyes. Biometric data were entered into each of the five IOL power calculation formulas: SRK-II, SRK/T, Holladay I, Hoffer Q, and Binkhorst II. All eyes were divided into three groups according to axial length: short (≤22.0 mm), average (22.0-25.0 mm), and long (≥25.0 mm) eyes. The postoperative spherical equivalent was calculated and compared with the predicted refractive error using each biometric formula. The results showed that all formulas had significantly lower mean absolute error (MAE) in comparison with Binkhorst II formula (P < 0.01). The lowest MAE was obtained with the SRK-II for average (0.49 ± 0.40 D) and short (0.67 ± 0.54 D) eyes and the SRK/T for long (0.61 ± 0.50 D) eyes. The highest postoperative hyperopic shift was seen with the SRK-II for average (46.8 %), short (28.1 %), and long (48.4 %) eyes. The highest postoperative myopic shift was seen with the Holladay I for average (66.4 %) and long (71.0 %) eyes and the SRK/T for short eyes (80.6 %). In conclusion, the SRK-II formula produced the lowest MAE in average and short eyes and the SRK/T formula produced the lowest MAE in long eyes. The SRK-II has the highest postoperative hyperopic shift in all eyes. The highest postoperative myopic shift is with the Holladay I for average and long eyes and SRK/T for short eyes.

  5. Estimating error statistics for Chambon-la-Forêt observatory definitive data

    NASA Astrophysics Data System (ADS)

    Lesur, Vincent; Heumez, Benoît; Telali, Abdelkader; Lalanne, Xavier; Soloviev, Anatoly

    2017-08-01

    We propose a new algorithm for calibrating definitive observatory data with the goal of providing users with estimates of the data error standard deviations (SDs). The algorithm has been implemented and tested using Chambon-la-Forêt observatory (CLF) data. The calibration process uses all available data. It is set as a large, weakly non-linear, inverse problem that ultimately provides estimates of baseline values in three orthogonal directions, together with their expected standard deviations. For this inverse problem, absolute data error statistics are estimated from two series of absolute measurements made within a day. Similarly, variometer data error statistics are derived by comparing variometer data time series between different pairs of instruments over few years. The comparisons of these time series led us to use an autoregressive process of order 1 (AR1 process) as a prior for the baselines. Therefore the obtained baselines do not vary smoothly in time. They have relatively small SDs, well below 300 pT when absolute data are recorded twice a week - i.e. within the daily to weekly measures recommended by INTERMAGNET. The algorithm was tested against the process traditionally used to derive baselines at CLF observatory, suggesting that statistics are less favourable when this latter process is used. Finally, two sets of definitive data were calibrated using the new algorithm. Their comparison shows that the definitive data SDs are less than 400 pT and may be slightly overestimated by our process: an indication that more work is required to have proper estimates of absolute data error statistics. For magnetic field modelling, the results show that even on isolated sites like CLF observatory, there are very localised signals over a large span of temporal frequencies that can be as large as 1 nT. The SDs reported here encompass signals of a few hundred metres and less than a day wavelengths.

  6. The AFGL (Air Force Geophysics Laboratory) Absolute Gravity System’s Error Budget Revisted.

    DTIC Science & Technology

    1985-05-08

    also be induced by equipment not associated with the system. A systematic bias of 68 pgal was observed by the Istituto di Metrologia "G. Colonnetti...Laboratory Astrophysics, Univ. of Colo., Boulder, Colo. IMGC: Istituto di Metrologia "G. Colonnetti", Torino, Italy Table 1. Absolute Gravity Values...measurements were made with three Model D and three Model G La Coste-Romberg gravity meters. These instruments were operated by the following agencies

  7. Wind power application research on the fusion of the determination and ensemble prediction

    NASA Astrophysics Data System (ADS)

    Lan, Shi; Lina, Xu; Yuzhu, Hao

    2017-07-01

    The fused product of wind speed for the wind farm is designed through the use of wind speed products of ensemble prediction from the European Centre for Medium-Range Weather Forecasts (ECMWF) and professional numerical model products on wind power based on Mesoscale Model5 (MM5) and Beijing Rapid Update Cycle (BJ-RUC), which are suitable for short-term wind power forecasting and electric dispatch. The single-valued forecast is formed by calculating the different ensemble statistics of the Bayesian probabilistic forecasting representing the uncertainty of ECMWF ensemble prediction. Using autoregressive integrated moving average (ARIMA) model to improve the time resolution of the single-valued forecast, and based on the Bayesian model averaging (BMA) and the deterministic numerical model prediction, the optimal wind speed forecasting curve and the confidence interval are provided. The result shows that the fusion forecast has made obvious improvement to the accuracy relative to the existing numerical forecasting products. Compared with the 0-24 h existing deterministic forecast in the validation period, the mean absolute error (MAE) is decreased by 24.3 % and the correlation coefficient (R) is increased by 12.5 %. In comparison with the ECMWF ensemble forecast, the MAE is reduced by 11.7 %, and R is increased 14.5 %. Additionally, MAE did not increase with the prolongation of the forecast ahead.

  8. Evaluation of 16 genotype-guided Warfarin Dosing Algorithms in 310 Korean Patients Receiving Warfarin Treatment: Poor Prediction Performance in VKORC1 1173C Carriers.

    PubMed

    Yang, Mina; Choi, Rihwa; Kim, June Soo; On, Young Keun; Bang, Oh Young; Cho, Hyun-Jung; Lee, Soo-Youn

    2016-12-01

    The purpose of this study was to evaluate the performance of 16 previously published warfarin dosing algorithms in Korean patients. The 16 algorithms were selected through a literature search and evaluated using a cohort of 310 Korean patients with atrial fibrillation or cerebral infarction who were receiving warfarin therapy. A large interindividual variation (up to 11-fold) in warfarin dose was observed (median, 25 mg/wk; range, 7-77 mg/wk). Estimated dose and actual maintenance dose correlated well overall (r range, 0.52-0.73). Mean absolute error (MAE) of the 16 algorithms ranged from -1.2 to -20.1 mg/wk. The percentage of patients whose estimated dose fell within 20% of the actual dose ranged from 1.0% to 49%. All algorithms showed poor accuracy with increased MAE in a higher dose range. Performance of the dosing algorithms was worse in patients with VKORC1 1173TC or CC than in total (r range, 0.38-0.61 vs 0.52-0.73; MAE range, -2.6 to -28.0 mg/wk vs -1.2 to -20.1 mg/wk). The algorithms had comparable prediction abilities but showed limited accuracy depending on ethnicity, warfarin dose, and VKORC1 genotype. Further studies are needed to develop genotype-guided warfarin dosing algorithms with greater accuracy in the Korean population. Copyright © 2016 Elsevier HS Journals, Inc. All rights reserved.

  9. Informing the Human Plasma Protein Binding of ...

    EPA Pesticide Factsheets

    The free fraction of a xenobiotic in plasma (Fub) is an important determinant of chemical adsorption, distribution, metabolism, elimination, and toxicity, yet experimental plasma protein binding data is scarce for environmentally relevant chemicals. The presented work explores the merit of utilizing available pharmaceutical data to predict Fub for environmentally relevant chemicals via machine learning techniques. Quantitative structure-activity relationship (QSAR) models were constructed with k nearest neighbors (kNN), support vector machines (SVM), and random forest (RF) machine learning algorithms from a training set of 1045 pharmaceuticals. The models were then evaluated with independent test sets of pharmaceuticals (200 compounds) and environmentally relevant ToxCast chemicals (406 total, in two groups of 238 and 168 compounds). The selection of a minimal feature set of 10-15 2D molecular descriptors allowed for both informative feature interpretation and practical applicability domain assessment via a bounded box of descriptor ranges and principal component analysis. The diverse pharmaceutical and environmental chemical sets exhibit similarities in terms of chemical space (99-82% overlap), as well as comparable bias and variance in constructed learning curves. All the models exhibit significant predictability with mean absolute errors (MAE) in the range of 0.10-0.18 Fub. The models performed best for highly bound chemicals (MAE 0.07-0.12), neutrals (MAE 0

  10. Absolute Radiometric Calibration of EUNIS-06

    NASA Technical Reports Server (NTRS)

    Thomas, R. J.; Rabin, D. M.; Kent, B. J.; Paustian, W.

    2007-01-01

    The Extreme-Ultraviolet Normal-Incidence Spectrometer (EUNIS) is a soundingrocket payload that obtains imaged high-resolution spectra of individual solar features, providing information about the Sun's corona and upper transition region. Shortly after its successful initial flight last year, a complete end-to-end calibration was carried out to determine the instrument's absolute radiometric response over its Longwave bandpass of 300 - 370A. The measurements were done at the Rutherford-Appleton Laboratory (RAL) in England, using the same vacuum facility and EUV radiation source used in the pre-flight calibrations of both SOHO/CDS and Hinode/EIS, as well as in three post-flight calibrations of our SERTS sounding rocket payload, the precursor to EUNIS. The unique radiation source provided by the Physikalisch-Technische Bundesanstalt (PTB) had been calibrated to an absolute accuracy of 7% (l-sigma) at 12 wavelengths covering our bandpass directly against the Berlin electron storage ring BESSY, which is itself a primary radiometric source standard. Scans of the EUNIS aperture were made to determine the instrument's absolute spectral sensitivity to +- 25%, considering all sources of error, and demonstrate that EUNIS-06 was the most sensitive solar E W spectrometer yet flown. The results will be matched against prior calibrations which relied on combining measurements of individual optical components, and on comparisons with theoretically predicted 'insensitive' line ratios. Coordinated observations were made during the EUNIS-06 flight by SOHO/CDS and EIT that will allow re-calibrations of those instruments as well. In addition, future EUNIS flights will provide similar calibration updates for TRACE, Hinode/EIS, and STEREO/SECCHI/EUVI.

  11. Pharmacokinetics of low-dose nedaplatin and validation of AUC prediction in patients with non-small-cell lung carcinoma.

    PubMed

    Niioka, Takenori; Uno, Tsukasa; Yasui-Furukori, Norio; Takahata, Takenori; Shimizu, Mikiko; Sugawara, Kazunobu; Tateishi, Tomonori

    2007-04-01

    The aim of this study was to determine the pharmacokinetics of low-dose nedaplatin combined with paclitaxel and radiation therapy in patients having non-small-cell lung carcinoma and establish the optimal dosage regimen for low-dose nedaplatin. We also evaluated predictive accuracy of reported formulas to estimate the area under the plasma concentration-time curve (AUC) of low-dose nedaplatin. A total of 19 patients were administered a constant intravenous infusion of 20 mg/m(2) body surface area (BSA) nedaplatin for an hour, and blood samples were collected at 1, 2, 3, 4, 6, 8, and 19 h after the administration. Plasma concentrations of unbound platinum were measured, and the actual value of platinum AUC (actual AUC) was calculated based on these data. The predicted value of platinum AUC (predicted AUC) was determined by three predictive methods reported in previous studies, consisting of Bayesian method, limited sampling strategies with plasma concentration at a single time point, and simple formula method (SFM) without measured plasma concentration. Three error indices, mean prediction error (ME, measure of bias), mean absolute error (MAE, measure of accuracy), and root mean squared prediction error (RMSE, measure of precision), were obtained from the difference between the actual and the predicted AUC, to compare the accuracy between the three predictive methods. The AUC showed more than threefold inter-patient variation, and there was a favorable correlation between nedaplatin clearance and creatinine clearance (Ccr) (r = 0.832, P < 0.01). In three error indices, MAE and RMSE showed significant difference between the three AUC predictive methods, and the method of SFM had the most favorable results, in which %ME, %MAE, and %RMSE were 5.5, 10.7, and 15.4, respectively. The dosage regimen of low-dose nedaplatin should be established based on Ccr rather than on BSA. Since prediction accuracy of SFM, which did not require measured plasma concentration, was most

  12. Improvements in absolute seismometer sensitivity calibration using local earth gravity measurements

    USGS Publications Warehouse

    Anthony, Robert E.; Ringler, Adam; Wilson, David

    2018-01-01

    The ability to determine both absolute and relative seismic amplitudes is fundamentally limited by the accuracy and precision with which scientists are able to calibrate seismometer sensitivities and characterize their response. Currently, across the Global Seismic Network (GSN), errors in midband sensitivity exceed 3% at the 95% confidence interval and are the least‐constrained response parameter in seismic recording systems. We explore a new methodology utilizing precise absolute Earth gravity measurements to determine the midband sensitivity of seismic instruments. We first determine the absolute sensitivity of Kinemetrics EpiSensor accelerometers to 0.06% at the 99% confidence interval by inverting them in a known gravity field at the Albuquerque Seismological Laboratory (ASL). After the accelerometer is calibrated, we install it in its normal configuration next to broadband seismometers and subject the sensors to identical ground motions to perform relative calibrations of the broadband sensors. Using this technique, we are able to determine the absolute midband sensitivity of the vertical components of Nanometrics Trillium Compact seismometers to within 0.11% and Streckeisen STS‐2 seismometers to within 0.14% at the 99% confidence interval. The technique enables absolute calibrations from first principles that are traceable to National Institute of Standards and Technology (NIST) measurements while providing nearly an order of magnitude more precision than step‐table calibrations.

  13. Sea surface temperature predictions using a multi-ocean analysis ensemble scheme

    NASA Astrophysics Data System (ADS)

    Zhang, Ying; Zhu, Jieshun; Li, Zhongxian; Chen, Haishan; Zeng, Gang

    2017-08-01

    This study examined the global sea surface temperature (SST) predictions by a so-called multiple-ocean analysis ensemble (MAE) initialization method which was applied in the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2). Different from most operational climate prediction practices which are initialized by a specific ocean analysis system, the MAE method is based on multiple ocean analyses. In the paper, the MAE method was first justified by analyzing the ocean temperature variability in four ocean analyses which all are/were applied for operational climate predictions either at the European Centre for Medium-range Weather Forecasts or at NCEP. It was found that these systems exhibit substantial uncertainties in estimating the ocean states, especially at the deep layers. Further, a set of MAE hindcasts was conducted based on the four ocean analyses with CFSv2, starting from each April during 1982-2007. The MAE hindcasts were verified against a subset of hindcasts from the NCEP CFS Reanalysis and Reforecast (CFSRR) Project. Comparisons suggested that MAE shows better SST predictions than CFSRR over most regions where ocean dynamics plays a vital role in SST evolutions, such as the El Niño and Atlantic Niño regions. Furthermore, significant improvements were also found in summer precipitation predictions over the equatorial eastern Pacific and Atlantic oceans, for which the local SST prediction improvements should be responsible. The prediction improvements by MAE imply a problem for most current climate predictions which are based on a specific ocean analysis system. That is, their predictions would drift towards states biased by errors inherent in their ocean initialization system, and thus have large prediction errors. In contrast, MAE arguably has an advantage by sampling such structural uncertainties, and could efficiently cancel these errors out in their predictions.

  14. Utilization of a novel digital measurement tool for quantitative assessment of upper extremity motor dexterity: a controlled pilot study.

    PubMed

    Getachew, Ruth; Lee, Sunghoon I; Kimball, Jon A; Yew, Andrew Y; Lu, Derek S; Li, Charles H; Garst, Jordan H; Ghalehsari, Nima; Paak, Brian H; Razaghy, Mehrdad; Espinal, Marie; Ostowari, Arsha; Ghavamrezaii, Amir A; Pourtaheri, Sahar; Wu, Irene; Sarrafzadeh, Majid; Lu, Daniel C

    2014-08-13

    The current methods of assessing motor function rely primarily on the clinician's judgment of the patient's physical examination and the patient's self-administered surveys. Recently, computerized handgrip tools have been designed as an objective method to quantify upper-extremity motor function. This pilot study explores the use of the MediSens handgrip as a potential clinical tool for objectively assessing the motor function of the hand. Eleven patients with cervical spondylotic myelopathy (CSM) were followed for three months. Eighteen age-matched healthy participants were followed for two months. The neuromotor function and the patient-perceived motor function of these patients were assessed with the MediSens device and the Oswestry Disability Index respectively. The MediSens device utilized a target tracking test to investigate the neuromotor capacity of the participants. The mean absolute error (MAE) between the target curve and the curve tracing achieved by the participants was used as the assessment metric. The patients' adjusted MediSens MAE scores were then compared to the controls. The CSM patients were further classified as either "functional" or "nonfunctional" in order to validate the system's responsiveness. Finally, the correlation between the MediSens MAE score and the ODI score was investigated. The control participants had lower MediSens MAE scores of 8.09%±1.60%, while the cervical spinal disorder patients had greater MediSens MAE scores of 11.24%±6.29%. Following surgery, the functional CSM patients had an average MediSens MAE score of 7.13%±1.60%, while the nonfunctional CSM patients had an average score of 12.41%±6.32%. The MediSens MAE and the ODI scores showed a statistically significant correlation (r=-0.341, p<1.14×10⁻⁵). A Bland-Altman plot was then used to validate the agreement between the two scores. Furthermore, the percentage improvement of the the two scores after receiving the surgical intervention showed a significant

  15. Medication errors in chemotherapy preparation and administration: a survey conducted among oncology nurses in Turkey.

    PubMed

    Ulas, Arife; Silay, Kamile; Akinci, Sema; Dede, Didem Sener; Akinci, Muhammed Bulent; Sendur, Mehmet Ali Nahit; Cubukcu, Erdem; Coskun, Hasan Senol; Degirmenci, Mustafa; Utkan, Gungor; Ozdemir, Nuriye; Isikdogan, Abdurrahman; Buyukcelik, Abdullah; Inanc, Mevlude; Bilici, Ahmet; Odabasi, Hatice; Cihan, Sener; Avci, Nilufer; Yalcin, Bulent

    2015-01-01

    Medication errors in oncology may cause severe clinical problems due to low therapeutic indices and high toxicity of chemotherapeutic agents. We aimed to investigate unintentional medication errors and underlying factors during chemotherapy preparation and administration based on a systematic survey conducted to reflect oncology nurses experience. This study was conducted in 18 adult chemotherapy units with volunteer participation of 206 nurses. A survey developed by primary investigators and medication errors (MAEs) defined preventable errors during prescription of medication, ordering, preparation or administration. The survey consisted of 4 parts: demographic features of nurses; workload of chemotherapy units; errors and their estimated monthly number during chemotherapy preparation and administration; and evaluation of the possible factors responsible from ME. The survey was conducted by face to face interview and data analyses were performed with descriptive statistics. Chi-square or Fisher exact tests were used for a comparative analysis of categorical data. Some 83.4% of the 210 nurses reported one or more than one error during chemotherapy preparation and administration. Prescribing or ordering wrong doses by physicians (65.7%) and noncompliance with administration sequences during chemotherapy administration (50.5%) were the most common errors. The most common estimated average monthly error was not following the administration sequence of the chemotherapeutic agents (4.1 times/month, range 1-20). The most important underlying reasons for medication errors were heavy workload (49.7%) and insufficient number of staff (36.5%). Our findings suggest that the probability of medication error is very high during chemotherapy preparation and administration, the most common involving prescribing and ordering errors. Further studies must address the strategies to minimize medication error in chemotherapy receiving patients, determine sufficient protective measures

  16. Network Adjustment of Orbit Errors in SAR Interferometry

    NASA Astrophysics Data System (ADS)

    Bahr, Hermann; Hanssen, Ramon

    2010-03-01

    Orbit errors can induce significant long wavelength error signals in synthetic aperture radar (SAR) interferograms and thus bias estimates of wide-scale deformation phenomena. The presented approach aims for correcting orbit errors in a preprocessing step to deformation analysis by modifying state vectors. Whereas absolute errors in the orbital trajectory are negligible, the influence of relative errors (baseline errors) is parametrised by their parallel and perpendicular component as a linear function of time. As the sensitivity of the interferometric phase is only significant with respect to the perpendicular base-line and the rate of change of the parallel baseline, the algorithm focuses on estimating updates to these two parameters. This is achieved by a least squares approach, where the unwrapped residual interferometric phase is observed and atmospheric contributions are considered to be stochastic with constant mean. To enhance reliability, baseline errors are adjusted in an overdetermined network of interferograms, yielding individual orbit corrections per acquisition.

  17. Relevant reduction effect with a modified thermoplastic mask of rotational error for glottic cancer in IMRT

    NASA Astrophysics Data System (ADS)

    Jung, Jae Hong; Jung, Joo-Young; Cho, Kwang Hwan; Ryu, Mi Ryeong; Bae, Sun Hyun; Moon, Seong Kwon; Kim, Yong Ho; Choe, Bo-Young; Suh, Tae Suk

    2017-02-01

    The purpose of this study was to analyze the glottis rotational error (GRE) by using a thermoplastic mask for patients with the glottic cancer undergoing intensity-modulated radiation therapy (IMRT). We selected 20 patients with glottic cancer who had received IMRT by using the tomotherapy. The image modalities with both kilovoltage computed tomography (planning kVCT) and megavoltage CT (daily MVCT) images were used for evaluating the error. Six anatomical landmarks in the image were defined to evaluate a correlation between the absolute GRE (°) and the length of contact with the underlying skin of the patient by the mask (mask, mm). We also statistically analyzed the results by using the Pearson's correlation coefficient and a linear regression analysis ( P <0.05). The mask and the absolute GRE were verified to have a statistical correlation ( P < 0.01). We found a statistical significance for each parameter in the linear regression analysis (mask versus absolute roll: P = 0.004 [ P < 0.05]; mask versus 3D-error: P = 0.000 [ P < 0.05]). The range of the 3D-errors with contact by the mask was from 1.2% - 39.7% between the maximumand no-contact case in this study. A thermoplastic mask with a tight, increased contact area may possibly contribute to the uncertainty of the reproducibility as a variation of the absolute GRE. Thus, we suggest that a modified mask, such as one that covers only the glottis area, can significantly reduce the patients' setup errors during the treatment.

  18. RaptorX-Angle: real-value prediction of protein backbone dihedral angles through a hybrid method of clustering and deep learning.

    PubMed

    Gao, Yujuan; Wang, Sheng; Deng, Minghua; Xu, Jinbo

    2018-05-08

    Protein dihedral angles provide a detailed description of protein local conformation. Predicted dihedral angles can be used to narrow down the conformational space of the whole polypeptide chain significantly, thus aiding protein tertiary structure prediction. However, direct angle prediction from sequence alone is challenging. In this article, we present a novel method (named RaptorX-Angle) to predict real-valued angles by combining clustering and deep learning. Tested on a subset of PDB25 and the targets in the latest two Critical Assessment of protein Structure Prediction (CASP), our method outperforms the existing state-of-art method SPIDER2 in terms of Pearson Correlation Coefficient (PCC) and Mean Absolute Error (MAE). Our result also shows approximately linear relationship between the real prediction errors and our estimated bounds. That is, the real prediction error can be well approximated by our estimated bounds. Our study provides an alternative and more accurate prediction of dihedral angles, which may facilitate protein structure prediction and functional study.

  19. Modified Bat Algorithm for Feature Selection with the Wisconsin Diagnosis Breast Cancer (WDBC) Dataset

    PubMed

    Jeyasingh, Suganthi; Veluchamy, Malathi

    2017-05-01

    Early diagnosis of breast cancer is essential to save lives of patients. Usually, medical datasets include a large variety of data that can lead to confusion during diagnosis. The Knowledge Discovery on Database (KDD) process helps to improve efficiency. It requires elimination of inappropriate and repeated data from the dataset before final diagnosis. This can be done using any of the feature selection algorithms available in data mining. Feature selection is considered as a vital step to increase the classification accuracy. This paper proposes a Modified Bat Algorithm (MBA) for feature selection to eliminate irrelevant features from an original dataset. The Bat algorithm was modified using simple random sampling to select the random instances from the dataset. Ranking was with the global best features to recognize the predominant features available in the dataset. The selected features are used to train a Random Forest (RF) classification algorithm. The MBA feature selection algorithm enhanced the classification accuracy of RF in identifying the occurrence of breast cancer. The Wisconsin Diagnosis Breast Cancer Dataset (WDBC) was used for estimating the performance analysis of the proposed MBA feature selection algorithm. The proposed algorithm achieved better performance in terms of Kappa statistic, Mathew’s Correlation Coefficient, Precision, F-measure, Recall, Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Relative Absolute Error (RAE) and Root Relative Squared Error (RRSE). Creative Commons Attribution License

  20. Error analysis on spinal motion measurement using skin mounted sensors.

    PubMed

    Yang, Zhengyi; Ma, Heather Ting; Wang, Deming; Lee, Raymond

    2008-01-01

    Measurement errors of skin-mounted sensors in measuring forward bending movement of the lumbar spines are investigated. In this investigation, radiographic images capturing the entire lumbar spines' positions were acquired and used as a 'gold' standard. Seventeen young male volunteers (21 (SD 1) years old) agreed to participate in the study. Light-weight miniature sensors of the electromagnetic tracking systems-Fastrak were attached to the skin overlying the spinous processes of the lumbar spine. With the sensors attached, the subjects were requested to take lateral radiographs in two postures: neutral upright and full flexion. The ranges of motions of lumbar spine were calculated from two sets of digitized data: the bony markers of vertebral bodies and the sensors and compared. The differences between the two sets of results were then analyzed. The relative movement between sensor and vertebrae was decomposed into sensor sliding and titling, from which sliding error and titling error were introduced. Gross motion range of forward bending of lumbar spine measured from bony markers of vertebrae is 67.8 degrees (SD 10.6 degrees ) and that from sensors is 62.8 degrees (SD 12.8 degrees ). The error and absolute error for gross motion range were 5.0 degrees (SD 7.2 degrees ) and 7.7 degrees (SD 3.9 degrees ). The contributions of sensors placed on S1 and L1 to the absolute error were 3.9 degrees (SD 2.9 degrees ) and 4.4 degrees (SD 2.8 degrees ), respectively.

  1. Mapping site index and volume increment from forest inventory, Landsat, and ecological variables in Tahoe National Forest, California, USA

    USGS Publications Warehouse

    Huang, Shengli; Ramirez, Carlos; Conway, Scott; Kennedy, Kama; Kohler, Tanya; Liu, Jinxun

    2016-01-01

    High-resolution site index (SI) and mean annual increment (MAI) maps are desired for local forest management. We integrated field inventory, Landsat, and ecological variables to produce 30 m SI and MAI maps for the Tahoe National Forest (TNF) where different tree species coexist. We converted species-specific SI using adjustment factors. Then, the SI map was produced by (i) intensifying plots to expand the training sets to more climatic, topographic, soil, and forest reflective classes, (ii) using results from a stepwise regression to enable a weighted imputation that minimized the effects of outlier plots within classes, and (iii) local interpolation and strata median filling to assign values to pixels without direct imputations. The SI (reference age is 50 years) map had an R2 of 0.7637, a root-mean-square error (RMSE) of 3.60, and a mean absolute error (MAE) of 3.07 m. The MAI map was similarly produced with an R2 of 0.6882, an RMSE of 1.73, and a MAE of 1.20 m3·ha−1·year−1. Spatial patterns and trends of SI and MAI were analyzed to be related to elevation, aspect, slope, soil productivity, and forest type. The 30 m SI and MAI maps can be used to support decisions on fire, plantation, biodiversity, and carbon.

  2. A novel capacitive absolute positioning sensor based on time grating with nanometer resolution

    NASA Astrophysics Data System (ADS)

    Pu, Hongji; Liu, Hongzhong; Liu, Xiaokang; Peng, Kai; Yu, Zhicheng

    2018-05-01

    The present work proposes a novel capacitive absolute positioning sensor based on time grating. The sensor includes a fine incremental-displacement measurement component combined with a coarse absolute-position measurement component to obtain high-resolution absolute positioning measurements. A single row type sensor was proposed to achieve fine displacement measurement, which combines the two electrode rows of a previously proposed double-row type capacitive displacement sensor based on time grating into a single row. To achieve absolute positioning measurement, the coarse measurement component is designed as a single-row type displacement sensor employing a single spatial period over the entire measurement range. In addition, this component employs a rectangular induction electrode and four groups of orthogonal discrete excitation electrodes with half-sinusoidal envelope shapes, which were formed by alternately extending the rectangular electrodes of the fine measurement component. The fine and coarse measurement components are tightly integrated to form a compact absolute positioning sensor. A prototype sensor was manufactured using printed circuit board technology for testing and optimization of the design in conjunction with simulations. Experimental results show that the prototype sensor achieves a ±300 nm measurement accuracy with a 1 nm resolution over a displacement range of 200 mm when employing error compensation. The proposed sensor is an excellent alternative to presently available long-range absolute nanometrology sensors owing to its low cost, simple structure, and ease of manufacturing.

  3. Teaching Absolute Value Meaningfully

    ERIC Educational Resources Information Center

    Wade, Angela

    2012-01-01

    What is the meaning of absolute value? And why do teachers teach students how to solve absolute value equations? Absolute value is a concept introduced in first-year algebra and then reinforced in later courses. Various authors have suggested instructional methods for teaching absolute value to high school students (Wei 2005; Stallings-Roberts…

  4. The Drag-based Ensemble Model (DBEM) for Coronal Mass Ejection Propagation

    NASA Astrophysics Data System (ADS)

    Dumbović, Mateja; Čalogović, Jaša; Vršnak, Bojan; Temmer, Manuela; Mays, M. Leila; Veronig, Astrid; Piantschitsch, Isabell

    2018-02-01

    The drag-based model for heliospheric propagation of coronal mass ejections (CMEs) is a widely used analytical model that can predict CME arrival time and speed at a given heliospheric location. It is based on the assumption that the propagation of CMEs in interplanetary space is solely under the influence of magnetohydrodynamical drag, where CME propagation is determined based on CME initial properties as well as the properties of the ambient solar wind. We present an upgraded version, the drag-based ensemble model (DBEM), that covers ensemble modeling to produce a distribution of possible ICME arrival times and speeds. Multiple runs using uncertainty ranges for the input values can be performed in almost real-time, within a few minutes. This allows us to define the most likely ICME arrival times and speeds, quantify prediction uncertainties, and determine forecast confidence. The performance of the DBEM is evaluated and compared to that of ensemble WSA-ENLIL+Cone model (ENLIL) using the same sample of events. It is found that the mean error is ME = ‑9.7 hr, mean absolute error MAE = 14.3 hr, and root mean square error RMSE = 16.7 hr, which is somewhat higher than, but comparable to ENLIL errors (ME = ‑6.1 hr, MAE = 12.8 hr and RMSE = 14.4 hr). Overall, DBEM and ENLIL show a similar performance. Furthermore, we find that in both models fast CMEs are predicted to arrive earlier than observed, most likely owing to the physical limitations of models, but possibly also related to an overestimation of the CME initial speed for fast CMEs.

  5. Comparison of intraocular lens power prediction using immersion ultrasound and optical biometry with and without formula optimization.

    PubMed

    Nemeth, Gabor; Nagy, Attila; Berta, Andras; Modis, Laszlo

    2012-09-01

    Comparison of postoperative refraction results using ultrasound biometry with closed immersion shell and optical biometry. Three hundred and sixty-four eyes of 306 patients (age: 70.6 ± 12.8 years) underwent cataract surgery where intraocular lenses calculated by SRK/T formula were implanted. In 159 cases immersion ultrasonic biometry, in 205 eyes optical biometry was used. Differences between predicted and actual postoperative refractions were calculated both prior to and after optimization with the SRK/T formula, after which we analysed the similar data in the case of Holladay, Haigis, and Hoffer-Q formulas. Mean absolute error (MAE) and the percentage rate of patients within ±0.5 and ±1.0 D difference in the predicted error were calculated with these four formulas. MAE was 0.5-0.7 D in cases of both methods with SRK/T, Holladay, and Hoffer-Q formula, but higher with Haigis formula. With no optimization, 60-65 % of the patients were under 0.5 D error in the immersion group (except for Haigis formula). Using the optical method, this value was slightly higher (62-67 %), however, in this case, Haigis formula also did not perform so well (45 %). Refraction results significantly improved with Holladay, Hoffer-Q, and Haigis formulas in both groups. The rate of patients under 0.5 D error increased to 65 % by the immersion technique, and up to 80 % by the optical one. According to our results, optical biometry offers only slightly better outcomes compared to those of immersion shell with no optimized formulas. However, in case of new generation formulas with both methods, the optimization of IOL-constants give significantly better results.

  6. A digital, constant-frequency pulsed phase-locked-loop instrument for real-time, absolute ultrasonic phase measurements

    NASA Astrophysics Data System (ADS)

    Haldren, H. A.; Perey, D. F.; Yost, W. T.; Cramer, K. E.; Gupta, M. C.

    2018-05-01

    A digitally controlled instrument for conducting single-frequency and swept-frequency ultrasonic phase measurements has been developed based on a constant-frequency pulsed phase-locked-loop (CFPPLL) design. This instrument uses a pair of direct digital synthesizers to generate an ultrasonically transceived tone-burst and an internal reference wave for phase comparison. Real-time, constant-frequency phase tracking in an interrogated specimen is possible with a resolution of 0.000 38 rad (0.022°), and swept-frequency phase measurements can be obtained. Using phase measurements, an absolute thickness in borosilicate glass is presented to show the instrument's efficacy, and these results are compared to conventional ultrasonic pulse-echo time-of-flight (ToF) measurements. The newly developed instrument predicted the thickness with a mean error of -0.04 μm and a standard deviation of error of 1.35 μm. Additionally, the CFPPLL instrument shows a lower measured phase error in the absence of changing temperature and couplant thickness than high-resolution cross-correlation ToF measurements at a similar signal-to-noise ratio. By showing higher accuracy and precision than conventional pulse-echo ToF measurements and lower phase errors than cross-correlation ToF measurements, the new digitally controlled CFPPLL instrument provides high-resolution absolute ultrasonic velocity or path-length measurements in solids or liquids, as well as tracking of material property changes with high sensitivity. The ability to obtain absolute phase measurements allows for many new applications than possible with previous ultrasonic pulsed phase-locked loop instruments. In addition to improved resolution, swept-frequency phase measurements add useful capability in measuring properties of layered structures, such as bonded joints, or materials which exhibit non-linear frequency-dependent behavior, such as dispersive media.

  7. Intraocular lens power calculations for cataract surgery after phototherapeutic keratectomy in granular corneal dystrophy type 2.

    PubMed

    Jung, Se Hwan; Han, Kyung Eun; Sgrignoli, Bradford; Kim, Tae-Im; Lee, Hyung Keun; Kim, Eung Kweon

    2012-10-01

    To investigate the predictability of various intraocular lens (IOL) power calculation methods in granular corneal dystrophy type 2 (GCD2) with prior phototherapeutic keratectomy (PTK) and to suggest the more predictable IOL power calculation method. Medical records of 20 eyes from 16 patients with GCD2, all having undergone cataract surgery after PTK, were retrospectively evaluated. Postoperative cataract refractive errors were compared with target diopters (D) using IOL power calculation methods as follows: 1) myopic and 2) hyperopic Haigis-L formula in IOLMaster (Carl Zeiss Meditec); 3) SRK/T formula using 4.5-mm zone Holladay equivalent keratometry readings (EKRs) (single-K Holladay EKRs method); 4) central keratometry power of true net power map in the Pentacam system (Oculus Optikgeräte GmbH); and 5) clinical history, Aramberri double-K, and double-K Holladay EKRs methods. Topographic status of corneal curvature after PTK was evaluated. Fourteen (70%) of 20 eyes showed central island formation after PTK. When central island was present, the mean absolute error (MAE) using the hyperopic Haigis-L formula was 0.25±0.15 D. When central island was not present, the myopic Haigis-L formula showed MAE of 0.33±0.16 D. When central island formation and IOLMaster keratometry underestimation were present, the hyperopic Haigis-L formula showed the least MAE of 0.26±0.08 D when switching the IOL-Master keratometry values equal to 4.5-mm zone Holladay EKRs. In planning for cataract surgery after PTK in GCD2, topographic analysis for central island formation is necessary. With or without central island formation, the hyperopic or myopic Haigis-L formula can be applied. When IOLMaster keratometry shows underestimation, the Haigis-L formula using 4.5-mm zone Holladay EKRs can be considered. Copyright 2012, SLACK Incorporated.

  8. Mapping health assessment questionnaire disability index (HAQ-DI) score, pain visual analog scale (VAS), and disease activity score in 28 joints (DAS28) onto the EuroQol-5D (EQ-5D) utility score with the KORean Observational study Network for Arthritis (KORONA) registry data.

    PubMed

    Kim, Hye-Lin; Kim, Dam; Jang, Eun Jin; Lee, Min-Young; Song, Hyun Jin; Park, Sun-Young; Cho, Soo-Kyung; Sung, Yoon-Kyoung; Choi, Chan-Bum; Won, Soyoung; Bang, So-Young; Cha, Hoon-Suk; Choe, Jung-Yoon; Chung, Won Tae; Hong, Seung-Jae; Jun, Jae-Bum; Kim, Jinseok; Kim, Seong-Kyu; Kim, Tae-Hwan; Kim, Tae-Jong; Koh, Eunmi; Lee, Hwajeong; Lee, Hye-Soon; Lee, Jisoo; Lee, Shin-Seok; Lee, Sung Won; Park, Sung-Hoon; Shim, Seung-Cheol; Yoo, Dae-Hyun; Yoon, Bo Young; Bae, Sang-Cheol; Lee, Eui-Kyung

    2016-04-01

    The aim of this study was to estimate the mapping model for EuroQol-5D (EQ-5D) utility values using the health assessment questionnaire disability index (HAQ-DI), pain visual analog scale (VAS), and disease activity score in 28 joints (DAS28) in a large, nationwide cohort of rheumatoid arthritis (RA) patients in Korea. The KORean Observational study Network for Arthritis (KORONA) registry data on 3557 patients with RA were used. Data were randomly divided into a modeling set (80 % of the data) and a validation set (20 % of the data). The ordinary least squares (OLS), Tobit, and two-part model methods were employed to construct a model to map to the EQ-5D index. Using a combination of HAQ-DI, pain VAS, and DAS28, four model versions were examined. To evaluate the predictive accuracy of the models, the root-mean-square error (RMSE) and mean absolute error (MAE) were calculated using the validation dataset. A model that included HAQ-DI, pain VAS, and DAS28 produced the highest adjusted R (2) as well as the lowest Akaike information criterion, RMSE, and MAE, regardless of the statistical methods used in modeling set. The mapping equation of the OLS method is given as EQ-5D = 0.95-0.21 × HAQ-DI-0.24 × pain VAS/100-0.01 × DAS28 (adjusted R (2) = 57.6 %, RMSE = 0.1654 and MAE = 0.1222). Also in the validation set, the RMSE and MAE were shown to be the smallest. The model with HAQ-DI, pain VAS, and DAS28 showed the best performance, and this mapping model enabled the estimation of an EQ-5D value for RA patients in whom utility values have not been measured.

  9. The Absolute Stability Analysis in Fuzzy Control Systems with Parametric Uncertainties and Reference Inputs

    NASA Astrophysics Data System (ADS)

    Wu, Bing-Fei; Ma, Li-Shan; Perng, Jau-Woei

    This study analyzes the absolute stability in P and PD type fuzzy logic control systems with both certain and uncertain linear plants. Stability analysis includes the reference input, actuator gain and interval plant parameters. For certain linear plants, the stability (i.e. the stable equilibriums of error) in P and PD types is analyzed with the Popov or linearization methods under various reference inputs and actuator gains. The steady state errors of fuzzy control systems are also addressed in the parameter plane. The parametric robust Popov criterion for parametric absolute stability based on Lur'e systems is also applied to the stability analysis of P type fuzzy control systems with uncertain plants. The PD type fuzzy logic controller in our approach is a single-input fuzzy logic controller and is transformed into the P type for analysis. In our work, the absolute stability analysis of fuzzy control systems is given with respect to a non-zero reference input and an uncertain linear plant with the parametric robust Popov criterion unlike previous works. Moreover, a fuzzy current controlled RC circuit is designed with PSPICE models. Both numerical and PSPICE simulations are provided to verify the analytical results. Furthermore, the oscillation mechanism in fuzzy control systems is specified with various equilibrium points of view in the simulation example. Finally, the comparisons are also given to show the effectiveness of the analysis method.

  10. A novel alkaloid isolated from Crotalaria paulina and identified by NMR and DFT calculations

    NASA Astrophysics Data System (ADS)

    Oliveira, Ramon Prata; Demuner, Antonio Jacinto; Alvarenga, Elson Santiago; Barbosa, Luiz Claudio Almeida; de Melo Silva, Thiago

    2018-01-01

    Pyrrolizidine alkaloids (PAs) are secondary metabolites found in Crotalaria genus and are known to have several biological activities. A novel macrocycle bislactone alkaloid, coined ethylcrotaline, was isolated and purified from the aerial parts of Crotalaria paulina. The novel macrocycle was identified with the aid of high resolution mass spectrometry and advanced nuclear magnetic resonance techniques. The relative stereochemistry of the alkaloid was defined by comparing the calculated quantum mechanical hydrogen and carbon chemical shifts of eight candidate structures with the experimental NMR data. The best fit between the eight candidate structures and the experimental NMR chemical shifts was defined by the DP4 statistical analyses and the Mean Absolute Error (MAE) calculations.

  11. Google Earth elevation data extraction and accuracy assessment for transportation applications.

    PubMed

    Wang, Yinsong; Zou, Yajie; Henrickson, Kristian; Wang, Yinhai; Tang, Jinjun; Park, Byung-Jung

    2017-01-01

    Roadway elevation data is critical for a variety of transportation analyses. However, it has been challenging to obtain such data and most roadway GIS databases do not have them. This paper intends to address this need by proposing a method to extract roadway elevation data from Google Earth (GE) for transportation applications. A comprehensive accuracy assessment of the GE-extracted elevation data is conducted for the area of conterminous USA. The GE elevation data was compared with the ground truth data from nationwide GPS benchmarks and roadway monuments from six states in the conterminous USA. This study also compares the GE elevation data with the elevation raster data from the U.S. Geological Survey National Elevation Dataset (USGS NED), which is a widely used data source for extracting roadway elevation. Mean absolute error (MAE) and root mean squared error (RMSE) are used to assess the accuracy and the test results show MAE, RMSE and standard deviation of GE roadway elevation error are 1.32 meters, 2.27 meters and 2.27 meters, respectively. Finally, the proposed extraction method was implemented and validated for the following three scenarios: (1) extracting roadway elevation differentiating by directions, (2) multi-layered roadway recognition in freeway segment and (3) slope segmentation and grade calculation in freeway segment. The methodology validation results indicate that the proposed extraction method can locate the extracting route accurately, recognize multi-layered roadway section, and segment the extracted route by grade automatically. Overall, it is found that the high accuracy elevation data available from GE provide a reliable data source for various transportation applications.

  12. Artificial Neural Network to Predict Vine Water Status Spatial Variability Using Multispectral Information Obtained from an Unmanned Aerial Vehicle (UAV)

    PubMed Central

    Bardeen, Matthew

    2017-01-01

    Water stress, which affects yield and wine quality, is often evaluated using the midday stem water potential (Ψstem). However, this measurement is acquired on a per plant basis and does not account for the assessment of vine water status spatial variability. The use of multispectral cameras mounted on unmanned aerial vehicle (UAV) is capable to capture the variability of vine water stress in a whole field scenario. It has been reported that conventional multispectral indices (CMI) that use information between 500–800 nm, do not accurately predict plant water status since they are not sensitive to water content. The objective of this study was to develop artificial neural network (ANN) models derived from multispectral images to predict the Ψstem spatial variability of a drip-irrigated Carménère vineyard in Talca, Maule Region, Chile. The coefficient of determination (R2) obtained between ANN outputs and ground-truth measurements of Ψstem were between 0.56–0.87, with the best performance observed for the model that included the bands 550, 570, 670, 700 and 800 nm. Validation analysis indicated that the ANN model could estimate Ψstem with a mean absolute error (MAE) of 0.1 MPa, root mean square error (RMSE) of 0.12 MPa, and relative error (RE) of −9.1%. For the validation of the CMI, the MAE, RMSE and RE values were between 0.26–0.27 MPa, 0.32–0.34 MPa and −24.2–25.6%, respectively. PMID:29084169

  13. 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

  14. Absolute measurements of large mirrors

    NASA Astrophysics Data System (ADS)

    Su, Peng

    times the mirror under test in relation to the test system. The result was a separation of errors in the optical test system to those errors from the mirror under test. This method proved to be accurate to 12nm rms. Another absolute measurement technique discussed in this dissertation utilizes the property of a paraboloidal surface of reflecting rays parallel to its optical axis, to its focal point. We have developed a scanning pentaprism technique that exploits this geometry to measure off-axis paraboloidal mirrors such as the GMT segments. This technique was demonstrated on a 1.7 m diameter prototype and proved to have a precision of about 50 nm rms.

  15. Easy Absolute Values? Absolutely

    ERIC Educational Resources Information Center

    Taylor, Sharon E.; Mittag, Kathleen Cage

    2015-01-01

    The authors teach a problem-solving course for preservice middle-grades education majors that includes concepts dealing with absolute-value computations, equations, and inequalities. Many of these students like mathematics and plan to teach it, so they are adept at symbolic manipulations. Getting them to think differently about a concept that they…

  16. Absolutely relative or relatively absolute: violations of value invariance in human decision making.

    PubMed

    Teodorescu, Andrei R; Moran, Rani; Usher, Marius

    2016-02-01

    Making decisions based on relative rather than absolute information processing is tied to choice optimality via the accumulation of evidence differences and to canonical neural processing via accumulation of evidence ratios. These theoretical frameworks predict invariance of decision latencies to absolute intensities that maintain differences and ratios, respectively. While information about the absolute values of the choice alternatives is not necessary for choosing the best alternative, it may nevertheless hold valuable information about the context of the decision. To test the sensitivity of human decision making to absolute values, we manipulated the intensities of brightness stimuli pairs while preserving either their differences or their ratios. Although asked to choose the brighter alternative relative to the other, participants responded faster to higher absolute values. Thus, our results provide empirical evidence for human sensitivity to task irrelevant absolute values indicating a hard-wired mechanism that precedes executive control. Computational investigations of several modelling architectures reveal two alternative accounts for this phenomenon, which combine absolute and relative processing. One account involves accumulation of differences with activation dependent processing noise and the other emerges from accumulation of absolute values subject to the temporal dynamics of lateral inhibition. The potential adaptive role of such choice mechanisms is discussed.

  17. Wavelet regression model in forecasting crude oil price

    NASA Astrophysics Data System (ADS)

    Hamid, Mohd Helmie; Shabri, Ani

    2017-05-01

    This study presents the performance of wavelet multiple linear regression (WMLR) technique in daily crude oil forecasting. WMLR model was developed by integrating the discrete wavelet transform (DWT) and multiple linear regression (MLR) model. The original time series was decomposed to sub-time series with different scales by wavelet theory. Correlation analysis was conducted to assist in the selection of optimal decomposed components as inputs for the WMLR model. The daily WTI crude oil price series has been used in this study to test the prediction capability of the proposed model. The forecasting performance of WMLR model were also compared with regular multiple linear regression (MLR), Autoregressive Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) using root mean square errors (RMSE) and mean absolute errors (MAE). Based on the experimental results, it appears that the WMLR model performs better than the other forecasting technique tested in this study.

  18. Comparing alchemical and physical pathway methods for computing the absolute binding free energy of charged ligands.

    PubMed

    Deng, Nanjie; Cui, Di; Zhang, Bin W; Xia, Junchao; Cruz, Jeffrey; Levy, Ronald

    2018-06-13

    Accurately predicting absolute binding free energies of protein-ligand complexes is important as a fundamental problem in both computational biophysics and pharmaceutical discovery. Calculating binding free energies for charged ligands is generally considered to be challenging because of the strong electrostatic interactions between the ligand and its environment in aqueous solution. In this work, we compare the performance of the potential of mean force (PMF) method and the double decoupling method (DDM) for computing absolute binding free energies for charged ligands. We first clarify an unresolved issue concerning the explicit use of the binding site volume to define the complexed state in DDM together with the use of harmonic restraints. We also provide an alternative derivation for the formula for absolute binding free energy using the PMF approach. We use these formulas to compute the binding free energy of charged ligands at an allosteric site of HIV-1 integrase, which has emerged in recent years as a promising target for developing antiviral therapy. As compared with the experimental results, the absolute binding free energies obtained by using the PMF approach show unsigned errors of 1.5-3.4 kcal mol-1, which are somewhat better than the results from DDM (unsigned errors of 1.6-4.3 kcal mol-1) using the same amount of CPU time. According to the DDM decomposition of the binding free energy, the ligand binding appears to be dominated by nonpolar interactions despite the presence of very large and favorable intermolecular ligand-receptor electrostatic interactions, which are almost completely cancelled out by the equally large free energy cost of desolvation of the charged moiety of the ligands in solution. We discuss the relative strengths of computing absolute binding free energies using the alchemical and physical pathway methods.

  19. 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

  20. Improved Correction of Atmospheric Pressure Data Obtained by Smartphones through Machine Learning

    PubMed Central

    Kim, Yong-Hyuk; Ha, Ji-Hun; Kim, Na-Young; Im, Hyo-Hyuc; Sim, Sangjin; Choi, Reno K. Y.

    2016-01-01

    A correction method using machine learning aims to improve the conventional linear regression (LR) based method for correction of atmospheric pressure data obtained by smartphones. The method proposed in this study conducts clustering and regression analysis with time domain classification. Data obtained in Gyeonggi-do, one of the most populous provinces in South Korea surrounding Seoul with the size of 10,000 km2, from July 2014 through December 2014, using smartphones were classified with respect to time of day (daytime or nighttime) as well as day of the week (weekday or weekend) and the user's mobility, prior to the expectation-maximization (EM) clustering. Subsequently, the results were analyzed for comparison by applying machine learning methods such as multilayer perceptron (MLP) and support vector regression (SVR). The results showed a mean absolute error (MAE) 26% lower on average when regression analysis was performed through EM clustering compared to that obtained without EM clustering. For machine learning methods, the MAE for SVR was around 31% lower for LR and about 19% lower for MLP. It is concluded that pressure data from smartphones are as good as the ones from national automatic weather station (AWS) network. PMID:27524999

  1. Improving gridded snow water equivalent products in British Columbia, Canada: multi-source data fusion by neural network models

    NASA Astrophysics Data System (ADS)

    Snauffer, Andrew M.; Hsieh, William W.; Cannon, Alex J.; Schnorbus, Markus A.

    2018-03-01

    Estimates of surface snow water equivalent (SWE) in mixed alpine environments with seasonal melts are particularly difficult in areas of high vegetation density, topographic relief, and snow accumulations. These three confounding factors dominate much of the province of British Columbia (BC), Canada. An artificial neural network (ANN) was created using as predictors six gridded SWE products previously evaluated for BC. Relevant spatiotemporal covariates were also included as predictors, and observations from manual snow surveys at stations located throughout BC were used as target data. Mean absolute errors (MAEs) and interannual correlations for April surveys were found using cross-validation. The ANN using the three best-performing SWE products (ANN3) had the lowest mean station MAE across the province. ANN3 outperformed each product as well as product means and multiple linear regression (MLR) models in all of BC's five physiographic regions except for the BC Plains. Subsequent comparisons with predictions generated by the Variable Infiltration Capacity (VIC) hydrologic model found ANN3 to better estimate SWE over the VIC domain and within most regions. The superior performance of ANN3 over the individual products, product means, MLR, and VIC was found to be statistically significant across the province.

  2. Phosphorus allotropes: Stability of black versus red phosphorus re-examined by means of the van der Waals inclusive density functional method

    NASA Astrophysics Data System (ADS)

    Aykol, Muratahan; Doak, Jeff W.; Wolverton, C.

    2017-06-01

    We evaluate the energetic stabilities of white, red, and black allotropes of phosphorus using density functional theory (DFT) and hybrid functional methods, van der Waals (vdW) corrections (DFT+vdW and hybrid+vdW), vdW density functionals, and random phase approximation (RPA). We find that stability of black phosphorus over red-V (i.e., the violet form) is not ubiquitous among these methods, and the calculated enthalpies for the reaction phosphorus (red-V)→phosphorus (black) are scattered between -20 and 40 meV/atom. With local density and generalized gradient approximations, and hybrid functionals, mean absolute errors (MAEs) in densities of P allotropes relative to experiments are found to be around 10%-25%, whereas with vdW-inclusive methods, MAEs in densities drop below ˜5 %. While the inconsistency among the density functional methods could not shed light on the stability puzzle of black versus red phosphorus, comparison of their accuracy in predicting densities and the supplementary RPA results on relative stabilities indicate that opposite to the common belief, black and red phosphorus are almost degenerate, or the red-V (violet) form of phosphorus might even be the ground state.

  3. Numerical evaluation of magnetic absolute measurements with arbitrarily distributed DI-fluxgate theodolite orientations

    NASA Astrophysics Data System (ADS)

    Brunke, Heinz-Peter; Matzka, Jürgen

    2018-01-01

    At geomagnetic observatories the absolute measurements are needed to determine the calibration parameters of the continuously recording vector magnetometer (variometer). Absolute measurements are indispensable for determining the vector of the geomagnetic field over long periods of time. A standard DI (declination, inclination) measuring scheme for absolute measurements establishes routines in magnetic observatories. The traditional measuring schema uses a fixed number of eight orientations (Jankowski et al., 1996).

    We present a numerical method, allowing for the evaluation of an arbitrary number (minimum of five as there are five independent parameters) of telescope orientations. Our method provides D, I and Z base values and calculated error bars of them.

    A general approach has significant advantages. Additional measurements may be seamlessly incorporated for higher accuracy. Individual erroneous readings are identified and can be discarded without invalidating the entire data set. A priori information can be incorporated. We expect the general method to also ease requirements for automated DI-flux measurements. The method can reveal certain properties of the DI theodolite which are not captured by the conventional method.

    Based on the alternative evaluation method, a new faster and less error-prone measuring schema is presented. It avoids needing to calculate the magnetic meridian prior to the inclination measurements.

    Measurements in the vicinity of the magnetic equator are possible with theodolites and without a zenith ocular.

    The implementation of the method in MATLAB is available as source code at the GFZ Data Center Brunke (2017).

  4. Fluctuation theorems in feedback-controlled open quantum systems: Quantum coherence and absolute irreversibility

    NASA Astrophysics Data System (ADS)

    Murashita, Yûto; Gong, Zongping; Ashida, Yuto; Ueda, Masahito

    2017-10-01

    The thermodynamics of quantum coherence has attracted growing attention recently, where the thermodynamic advantage of quantum superposition is characterized in terms of quantum thermodynamics. We investigate the thermodynamic effects of quantum coherent driving in the context of the fluctuation theorem. We adopt a quantum-trajectory approach to investigate open quantum systems under feedback control. In these systems, the measurement backaction in the forward process plays a key role, and therefore the corresponding time-reversed quantum measurement and postselection must be considered in the backward process, in sharp contrast to the classical case. The state reduction associated with quantum measurement, in general, creates a zero-probability region in the space of quantum trajectories of the forward process, which causes singularly strong irreversibility with divergent entropy production (i.e., absolute irreversibility) and hence makes the ordinary fluctuation theorem break down. In the classical case, the error-free measurement ordinarily leads to absolute irreversibility, because the measurement restricts classical paths to the region compatible with the measurement outcome. In contrast, in open quantum systems, absolute irreversibility is suppressed even in the presence of the projective measurement due to those quantum rare events that go through the classically forbidden region with the aid of quantum coherent driving. This suppression of absolute irreversibility exemplifies the thermodynamic advantage of quantum coherent driving. Absolute irreversibility is shown to emerge in the absence of coherent driving after the measurement, especially in systems under time-delayed feedback control. We show that absolute irreversibility is mitigated by increasing the duration of quantum coherent driving or decreasing the delay time of feedback control.

  5. Absolute biological needs.

    PubMed

    McLeod, Stephen

    2014-07-01

    Absolute needs (as against instrumental needs) are independent of the ends, goals and purposes of personal agents. Against the view that the only needs are instrumental needs, David Wiggins and Garrett Thomson have defended absolute needs on the grounds that the verb 'need' has instrumental and absolute senses. While remaining neutral about it, this article does not adopt that approach. Instead, it suggests that there are absolute biological needs. The absolute nature of these needs is defended by appeal to: their objectivity (as against mind-dependence); the universality of the phenomenon of needing across the plant and animal kingdoms; the impossibility that biological needs depend wholly upon the exercise of the abilities characteristic of personal agency; the contention that the possession of biological needs is prior to the possession of the abilities characteristic of personal agency. Finally, three philosophical usages of 'normative' are distinguished. On two of these, to describe a phenomenon or claim as 'normative' is to describe it as value-dependent. A description of a phenomenon or claim as 'normative' in the third sense does not entail such value-dependency, though it leaves open the possibility that value depends upon the phenomenon or upon the truth of the claim. It is argued that while survival needs (or claims about them) may well be normative in this third sense, they are normative in neither of the first two. Thus, the idea of absolute need is not inherently normative in either of the first two senses. © 2013 John Wiley & Sons Ltd.

  6. Application of Holt exponential smoothing and ARIMA method for data population in West Java

    NASA Astrophysics Data System (ADS)

    Supriatna, A.; Susanti, D.; Hertini, E.

    2017-01-01

    One method of time series that is often used to predict data that contains trend is Holt. Holt method using different parameters used in the original data which aims to smooth the trend value. In addition to Holt, ARIMA method can be used on a wide variety of data including data pattern containing a pattern trend. Data actual of population from 1998-2015 contains the trends so can be solved by Holt and ARIMA method to obtain the prediction value of some periods. The best method is measured by looking at the smallest MAPE and MAE error. The result using Holt method is 47.205.749 populations in 2016, 47.535.324 populations in 2017, and 48.041.672 populations in 2018, with MAPE error is 0,469744 and MAE error is 189.731. While the result using ARIMA method is 46.964.682 populations in 2016, 47.342.189 in 2017, and 47.899.696 in 2018, with MAPE error is 0,4380 and MAE is 176.626.

  7. Taxi trips distribution modeling based on Entropy-Maximizing theory: A case study in Harbin city-China

    NASA Astrophysics Data System (ADS)

    Tang, Jinjun; Zhang, Shen; Chen, Xinqiang; Liu, Fang; Zou, Yajie

    2018-03-01

    Understanding Origin-Destination distribution of taxi trips is very important for improving effects of transportation planning and enhancing quality of taxi services. This study proposes a new method based on Entropy-Maximizing theory to model OD distribution in Harbin city using large-scale taxi GPS trajectories. Firstly, a K-means clustering method is utilized to partition raw pick-up and drop-off location into different zones, and trips are assumed to start from and end at zone centers. A generalized cost function is further defined by considering travel distance, time and fee between each OD pair. GPS data collected from more than 1000 taxis at an interval of 30 s during one month are divided into two parts: data from first twenty days is treated as training dataset and last ten days is taken as testing dataset. The training dataset is used to calibrate model while testing dataset is used to validate model. Furthermore, three indicators, mean absolute error (MAE), root mean square error (RMSE) and mean percentage absolute error (MPAE), are applied to evaluate training and testing performance of Entropy-Maximizing model versus Gravity model. The results demonstrate Entropy-Maximizing model is superior to Gravity model. Findings of the study are used to validate the feasibility of OD distribution from taxi GPS data in urban system.

  8. Mapping health outcome measures from a stroke registry to EQ-5D weights.

    PubMed

    Ghatnekar, Ola; Eriksson, Marie; Glader, Eva-Lotta

    2013-03-07

    To map health outcome related variables from a national register, not part of any validated instrument, with EQ-5D weights among stroke patients. We used two cross-sectional data sets including patient characteristics, outcome variables and EQ-5D weights from the national Swedish stroke register. Three regression techniques were used on the estimation set (n=272): ordinary least squares (OLS), Tobit, and censored least absolute deviation (CLAD). The regression coefficients for "dressing", "toileting", "mobility", "mood", "general health" and "proxy-responders" were applied to the validation set (n=272), and the performance was analysed with mean absolute error (MAE) and mean square error (MSE). The number of statistically significant coefficients varied by model, but all models generated consistent coefficients in terms of sign. Mean utility was underestimated in all models (least in OLS) and with lower variation (least in OLS) compared to the observed. The maximum attainable EQ-5D weight ranged from 0.90 (OLS) to 1.00 (Tobit and CLAD). Health states with utility weights <0.5 had greater errors than those with weights ≥ 0.5 (P<0.01). This study indicates that it is possible to map non-validated health outcome measures from a stroke register into preference-based utilities to study the development of stroke care over time, and to compare with other conditions in terms of utility.

  9. The Absolute Proper Motion of NGC 6397 Revisited

    NASA Astrophysics Data System (ADS)

    Rees, Richard; Cudworth, Kyle

    2018-01-01

    We compare several determinations of the absolute proper motion of the Galactic globular cluster NGC 6397: (1) our own determination relative to field stars derived from scans of 38 photographic plates spanning 97 years in epoch; (2) using our proper motion membership to identify cluster stars in various catalogs in the literature (UCAC4, UCAC5, PPMXL, HSOY, Tycho-2, Hipparcos, TGAS); (3) published results from the Yale SPM Program (both tied to Hipparcos and relative to galaxies) and two from HST observations relative to galaxies. The various determinations are not in good agreement. Curiously, the Yale SPM relative to galaxies does not agree with the HST determinations, and the individual HST error ellipses are close to each other but do not overlap. The Yale SPM relative to galaxies does agree with our determination, Tycho-2, and the Yale SPM tied to Hipparcos. It is not clear which of the current determinations is most reliable; we have found evidence of systematic errors in some of them (including one of the HST determinations). This research has been partially supported by the NSF.

  10. The JILA (Joint Institute for Laboratory Astrophysics) portable absolute gravity apparatus

    NASA Astrophysics Data System (ADS)

    Faller, J. E.; Guo, Y. G.; Gschwind, J.; Niebauer, T. M.; Rinker, R. L.; Xue, J.

    1983-08-01

    We have developed a new and highly portable absolute gravity apparatus based on the principles of free-fall laser interferometry. A primary concern over the past several years has been the detection, understanding, and elimination of systematic errors. In the Spring of 1982, we used this instrument to carry out a survey at twelve sites in the United States. Over a period of eight weeks, the instrument was driven a distance of nearly 20,000 km to sites in California, New Mexico, Colorado, Wyoming, Maryland, and Massachusetts. The time required to carry out a measurement at each location was typically one day. Over the next several years, our intention is to see absolute gravity measurements become both usable and used in the field. To this end, and in the context of cooperative research programs with a number of scientific institutes throughout the world, we are building additional instruments (incorporating further refinements) which are to be used for geodetic, geophysical, geological, and tectonic studies. With these new instruments we expect to improve (perhaps by a factor of two) on the 6-10 microgal accuracy of our present instrument. Today, one can make absolutely gravity measurements as accurately as - possibly even more accurately than - one can make relative measurements. Given reasonable success with the new instruments in the field, the last years of this century should see absolute gravity measurement mature both as a new geodetic data type and as a useful geophysical tool.

  11. Effective Acceleration Model for the Arrival Time of Interplanetary Shocks driven by Coronal Mass Ejections

    NASA Astrophysics Data System (ADS)

    Paouris, Evangelos; Mavromichalaki, Helen

    2017-12-01

    In a previous work (Paouris and Mavromichalaki in Solar Phys. 292, 30, 2017), we presented a total of 266 interplanetary coronal mass ejections (ICMEs) with as much information as possible. We developed a new empirical model for estimating the acceleration of these events in the interplanetary medium from this analysis. In this work, we present a new approach on the effective acceleration model (EAM) for predicting the arrival time of the shock that preceds a CME, using data of a total of 214 ICMEs. For the first time, the projection effects of the linear speed of CMEs are taken into account in this empirical model, which significantly improves the prediction of the arrival time of the shock. In particular, the mean value of the time difference between the observed time of the shock and the predicted time was equal to +3.03 hours with a mean absolute error (MAE) of 18.58 hours and a root mean squared error (RMSE) of 22.47 hours. After the improvement of this model, the mean value of the time difference is decreased to -0.28 hours with an MAE of 17.65 hours and an RMSE of 21.55 hours. This improved version was applied to a set of three recent Earth-directed CMEs reported in May, June, and July of 2017, and we compare our results with the values predicted by other related models.

  12. Area under the curve predictions of dalbavancin, a new lipoglycopeptide agent, using the end of intravenous infusion concentration data point by regression analyses such as linear, log-linear and power models.

    PubMed

    Bhamidipati, Ravi Kanth; Syed, Muzeeb; Mullangi, Ramesh; Srinivas, Nuggehally

    2018-02-01

    1. Dalbavancin, a lipoglycopeptide, is approved for treating gram-positive bacterial infections. Area under plasma concentration versus time curve (AUC inf ) of dalbavancin is a key parameter and AUC inf /MIC ratio is a critical pharmacodynamic marker. 2. Using end of intravenous infusion concentration (i.e. C max ) C max versus AUC inf relationship for dalbavancin was established by regression analyses (i.e. linear, log-log, log-linear and power models) using 21 pairs of subject data. 3. The predictions of the AUC inf were performed using published C max data by application of regression equations. The quotient of observed/predicted values rendered fold difference. The mean absolute error (MAE)/root mean square error (RMSE) and correlation coefficient (r) were used in the assessment. 4. MAE and RMSE values for the various models were comparable. The C max versus AUC inf exhibited excellent correlation (r > 0.9488). The internal data evaluation showed narrow confinement (0.84-1.14-fold difference) with a RMSE < 10.3%. The external data evaluation showed that the models predicted AUC inf with a RMSE of 3.02-27.46% with fold difference largely contained within 0.64-1.48. 5. Regardless of the regression models, a single time point strategy of using C max (i.e. end of 30-min infusion) is amenable as a prospective tool for predicting AUC inf of dalbavancin in patients.

  13. Real-Time and Meter-Scale Absolute Distance Measurement by Frequency-Comb-Referenced Multi-Wavelength Interferometry.

    PubMed

    Wang, Guochao; Tan, Lilong; Yan, Shuhua

    2018-02-07

    We report on a frequency-comb-referenced absolute interferometer which instantly measures long distance by integrating multi-wavelength interferometry with direct synthetic wavelength interferometry. The reported interferometer utilizes four different wavelengths, simultaneously calibrated to the frequency comb of a femtosecond laser, to implement subwavelength distance measurement, while direct synthetic wavelength interferometry is elaborately introduced by launching a fifth wavelength to extend a non-ambiguous range for meter-scale measurement. A linearity test performed comparatively with a He-Ne laser interferometer shows a residual error of less than 70.8 nm in peak-to-valley over a 3 m distance, and a 10 h distance comparison is demonstrated to gain fractional deviations of ~3 × 10 -8 versus 3 m distance. Test results reveal that the presented absolute interferometer enables precise, stable, and long-term distance measurements and facilitates absolute positioning applications such as large-scale manufacturing and space missions.

  14. Alcohol consumption, beverage prices and measurement error.

    PubMed

    Young, Douglas J; Bielinska-Kwapisz, Agnieszka

    2003-03-01

    Alcohol price data collected by the American Chamber of Commerce Researchers Association (ACCRA) have been widely used in studies of alcohol consumption and related behaviors. A number of problems with these data suggest that they contain substantial measurement error, which biases conventional statistical estimators toward a finding of little or no effect of prices on behavior. We test for measurement error, assess the magnitude of the bias and provide an alternative estimator that is likely to be superior. The study utilizes data on per capita alcohol consumption across U.S. states and the years 1982-1997. State and federal alcohol taxes are used as instrumental variables for prices. Formal tests strongly confim the hypothesis of measurement error. Instrumental variable estimates of the price elasticity of demand range from -0.53 to -1.24. These estimates are substantially larger in absolute value than ordinary least squares estimates, which sometimes are not significantly different from zero or even positive. The ACCRA price data are substantially contaminated with measurement error, but using state and federal taxes as instrumental variables mitigates the problem.

  15. A Comparison of the Forecast Skills among Three Numerical Models

    NASA Astrophysics Data System (ADS)

    Lu, D.; Reddy, S. R.; White, L. J.

    2003-12-01

    Three numerical weather forecast models, MM5, COAMPS and WRF, operating with a joint effort of NOAA HU-NCAS and Jackson State University (JSU) during summer 2003 have been chosen to study their forecast skills against observations. The models forecast over the same region with the same initialization, boundary condition, forecast length and spatial resolution. AVN global dataset have been ingested as initial conditions. Grib resolution of 27 km is chosen to represent the current mesoscale model. The forecasts with the length of 36h are performed to output the result with 12h interval. The key parameters used to evaluate the forecast skill include 12h accumulated precipitation, sea level pressure, wind, surface temperature and dew point. Precipitation is evaluated statistically using conventional skill scores, Threat Score (TS) and Bias Score (BS), for different threshold values based on 12h rainfall observations whereas other statistical methods such as Mean Error (ME), Mean Absolute Error(MAE) and Root Mean Square Error (RMSE) are applied to other forecast parameters.

  16. Application of RBFN network and GM (1, 1) for groundwater level simulation

    NASA Astrophysics Data System (ADS)

    Li, Zijun; Yang, Qingchun; Wang, Luchen; Martín, Jordi Delgado

    2017-10-01

    Groundwater is a prominent resource of drinking and domestic water in the world. In this context, a feasible water resources management plan necessitates acceptable predictions of groundwater table depth fluctuations, which can help ensure the sustainable use of a watershed's aquifers for urban and rural water supply. Due to the difficulties of identifying non-linear model structure and estimating the associated parameters, in this study radial basis function neural network (RBFNN) and GM (1, 1) models are used for the prediction of monthly groundwater level fluctuations in the city of Longyan, Fujian Province (South China). The monthly groundwater level data monitored from January 2003 to December 2011 are used in both models. The error criteria are estimated using the coefficient of determination ( R 2), mean absolute error (E) and root mean squared error (RMSE). The results show that both the models can forecast the groundwater level with fairly high accuracy, but the RBFN network model can be a promising tool to simulate and forecast groundwater level since it has a relatively smaller RMSE and MAE.

  17. Fast adaptive diamond search algorithm for block-matching motion estimation using spatial correlation

    NASA Astrophysics Data System (ADS)

    Park, Sang-Gon; Jeong, Dong-Seok

    2000-12-01

    In this paper, we propose a fast adaptive diamond search algorithm (FADS) for block matching motion estimation. Many fast motion estimation algorithms reduce the computational complexity by the UESA (Unimodal Error Surface Assumption) where the matching error monotonically increases as the search moves away from the global minimum point. Recently, many fast BMAs (Block Matching Algorithms) make use of the fact that global minimum points in real world video sequences are centered at the position of zero motion. But these BMAs, especially in large motion, are easily trapped into the local minima and result in poor matching accuracy. So, we propose a new motion estimation algorithm using the spatial correlation among the neighboring blocks. We move the search origin according to the motion vectors of the spatially neighboring blocks and their MAEs (Mean Absolute Errors). The computer simulation shows that the proposed algorithm has almost the same computational complexity with DS (Diamond Search), but enhances PSNR. Moreover, the proposed algorithm gives almost the same PSNR as that of FS (Full Search), even for the large motion with half the computational load.

  18. Modeling of surface dust concentrations using neural networks and kriging

    NASA Astrophysics Data System (ADS)

    Buevich, Alexander G.; Medvedev, Alexander N.; Sergeev, Alexander P.; Tarasov, Dmitry A.; Shichkin, Andrey V.; Sergeeva, Marina V.; Atanasova, T. B.

    2016-12-01

    Creating models which are able to accurately predict the distribution of pollutants based on a limited set of input data is an important task in environmental studies. In the paper two neural approaches: (multilayer perceptron (MLP)) and generalized regression neural network (GRNN)), and two geostatistical approaches: (kriging and cokriging), are using for modeling and forecasting of dust concentrations in snow cover. The area of study is under the influence of dust emissions from a copper quarry and a several industrial companies. The comparison of two mentioned approaches is conducted. Three indices are used as the indicators of the models accuracy: the mean absolute error (MAE), root mean square error (RMSE) and relative root mean square error (RRMSE). Models based on artificial neural networks (ANN) have shown better accuracy. When considering all indices, the most precision model was the GRNN, which uses as input parameters for modeling the coordinates of sampling points and the distance to the probable emissions source. The results of work confirm that trained ANN may be more suitable tool for modeling of dust concentrations in snow cover.

  19. Error analysis of multi-needle Langmuir probe measurement technique.

    PubMed

    Barjatya, Aroh; Merritt, William

    2018-04-01

    Multi-needle Langmuir probe is a fairly new instrument technique that has been flown on several recent sounding rockets and is slated to fly on a subset of QB50 CubeSat constellation. This paper takes a fundamental look into the data analysis procedures used for this instrument to derive absolute electron density. Our calculations suggest that while the technique remains promising, the current data analysis procedures could easily result in errors of 50% or more. We present a simple data analysis adjustment that can reduce errors by at least a factor of five in typical operation.

  20. Error analysis of multi-needle Langmuir probe measurement technique

    NASA Astrophysics Data System (ADS)

    Barjatya, Aroh; Merritt, William

    2018-04-01

    Multi-needle Langmuir probe is a fairly new instrument technique that has been flown on several recent sounding rockets and is slated to fly on a subset of QB50 CubeSat constellation. This paper takes a fundamental look into the data analysis procedures used for this instrument to derive absolute electron density. Our calculations suggest that while the technique remains promising, the current data analysis procedures could easily result in errors of 50% or more. We present a simple data analysis adjustment that can reduce errors by at least a factor of five in typical operation.

  1. 3D Tendon Strain Estimation Using High-frequency Volumetric Ultrasound Images: A Feasibility Study.

    PubMed

    Carvalho, Catarina; Slagmolen, Pieter; Bogaerts, Stijn; Scheys, Lennart; D'hooge, Jan; Peers, Koen; Maes, Frederik; Suetens, Paul

    2018-03-01

    Estimation of strain in tendons for tendinopathy assessment is a hot topic within the sports medicine community. It is believed that, if accurately estimated, existing treatment and rehabilitation protocols can be improved and presymptomatic abnormalities can be detected earlier. State-of-the-art studies present inaccurate and highly variable strain estimates, leaving this problem without solution. Out-of-plane motion, present when acquiring two-dimensional (2D) ultrasound (US) images, is a known problem and may be responsible for such errors. This work investigates the benefit of high-frequency, three-dimensional (3D) US imaging to reduce errors in tendon strain estimation. Volumetric US images were acquired in silico, in vitro, and ex vivo using an innovative acquisition approach that combines the acquisition of 2D high-frequency US images with a mechanical guided system. An affine image registration method was used to estimate global strain. 3D strain estimates were then compared with ground-truth values and with 2D strain estimates. The obtained results for in silico data showed a mean absolute error (MAE) of 0.07%, 0.05%, and 0.27% for 3D estimates along axial, lateral direction, and elevation direction and a respective MAE of 0.21% and 0.29% for 2D strain estimates. Although 3D could outperform 2D, this does not occur in in vitro and ex vivo settings, likely due to 3D acquisition artifacts. Comparison against the state-of-the-art methods showed competitive results. The proposed work shows that 3D strain estimates are more accurate than 2D estimates but acquisition of appropriate 3D US images remains a challenge.

  2. Google Earth elevation data extraction and accuracy assessment for transportation applications

    PubMed Central

    Wang, Yinsong; Zou, Yajie; Henrickson, Kristian; Wang, Yinhai; Tang, Jinjun; Park, Byung-Jung

    2017-01-01

    Roadway elevation data is critical for a variety of transportation analyses. However, it has been challenging to obtain such data and most roadway GIS databases do not have them. This paper intends to address this need by proposing a method to extract roadway elevation data from Google Earth (GE) for transportation applications. A comprehensive accuracy assessment of the GE-extracted elevation data is conducted for the area of conterminous USA. The GE elevation data was compared with the ground truth data from nationwide GPS benchmarks and roadway monuments from six states in the conterminous USA. This study also compares the GE elevation data with the elevation raster data from the U.S. Geological Survey National Elevation Dataset (USGS NED), which is a widely used data source for extracting roadway elevation. Mean absolute error (MAE) and root mean squared error (RMSE) are used to assess the accuracy and the test results show MAE, RMSE and standard deviation of GE roadway elevation error are 1.32 meters, 2.27 meters and 2.27 meters, respectively. Finally, the proposed extraction method was implemented and validated for the following three scenarios: (1) extracting roadway elevation differentiating by directions, (2) multi-layered roadway recognition in freeway segment and (3) slope segmentation and grade calculation in freeway segment. The methodology validation results indicate that the proposed extraction method can locate the extracting route accurately, recognize multi-layered roadway section, and segment the extracted route by grade automatically. Overall, it is found that the high accuracy elevation data available from GE provide a reliable data source for various transportation applications. PMID:28445480

  3. Mapping the EORTC QLQ-C30 onto the EQ-5D-3L: assessing the external validity of existing mapping algorithms.

    PubMed

    Doble, Brett; Lorgelly, Paula

    2016-04-01

    To determine the external validity of existing mapping algorithms for predicting EQ-5D-3L utility values from EORTC QLQ-C30 responses and to establish their generalizability in different types of cancer. A main analysis (pooled) sample of 3560 observations (1727 patients) and two disease severity patient samples (496 and 93 patients) with repeated observations over time from Cancer 2015 were used to validate the existing algorithms. Errors were calculated between observed and predicted EQ-5D-3L utility values using a single pooled sample and ten pooled tumour type-specific samples. Predictive accuracy was assessed using mean absolute error (MAE) and standardized root-mean-squared error (RMSE). The association between observed and predicted EQ-5D utility values and other covariates across the distribution was tested using quantile regression. Quality-adjusted life years (QALYs) were calculated using observed and predicted values to test responsiveness. Ten 'preferred' mapping algorithms were identified. Two algorithms estimated via response mapping and ordinary least-squares regression using dummy variables performed well on number of validation criteria, including accurate prediction of the best and worst QLQ-C30 health states, predicted values within the EQ-5D tariff range, relatively small MAEs and RMSEs, and minimal differences between estimated QALYs. Comparison of predictive accuracy across ten tumour type-specific samples highlighted that algorithms are relatively insensitive to grouping by tumour type and affected more by differences in disease severity. Two of the 'preferred' mapping algorithms suggest more accurate predictions, but limitations exist. We recommend extensive scenario analyses if mapped utilities are used in cost-utility analyses.

  4. Jasminum flexile flower absolute from India--a detailed comparison with three other jasmine absolutes.

    PubMed

    Braun, Norbert A; Kohlenberg, Birgit; Sim, Sherina; Meier, Manfred; Hammerschmidt, Franz-Josef

    2009-09-01

    Jasminum flexile flower absolute from the south of India and the corresponding vacuum headspace (VHS) sample of the absolute were analyzed using GC and GC-MS. Three other commercially available Indian jasmine absolutes from the species: J. sambac, J. officinale subsp. grandiflorum, and J. auriculatum and the respective VHS samples were used for comparison purposes. One hundred and twenty-one compounds were characterized in J. flexile flower absolute, with methyl linolate, benzyl salicylate, benzyl benzoate, (2E,6E)-farnesol, and benzyl acetate as the main constituents. A detailed olfactory evaluation was also performed.

  5. Pixel-based absolute surface metrology by three flat test with shifted and rotated maps

    NASA Astrophysics Data System (ADS)

    Zhai, Dede; Chen, Shanyong; Xue, Shuai; Yin, Ziqiang

    2018-03-01

    In traditional three flat test, it only provides the absolute profile along one surface diameter. In this paper, an absolute testing algorithm based on shift-rotation with three flat test has been proposed to reconstruct two-dimensional surface exactly. Pitch and yaw error during shift procedure is analyzed and compensated in our method. Compared with multi-rotation method proposed before, it only needs a 90° rotation and a shift, which is easy to carry out especially in condition of large size surface. It allows pixel level spatial resolution to be achieved without interpolation or assumption to the test surface. In addition, numerical simulations and optical tests are implemented and show the high accuracy recovery capability of the proposed method.

  6. Numerical model estimating the capabilities and limitations of the fast Fourier transform technique in absolute interferometry

    NASA Astrophysics Data System (ADS)

    Talamonti, James J.; Kay, Richard B.; Krebs, Danny J.

    1996-05-01

    A numerical model was developed to emulate the capabilities of systems performing noncontact absolute distance measurements. The model incorporates known methods to minimize signal processing and digital sampling errors and evaluates the accuracy limitations imposed by spectral peak isolation by using Hanning, Blackman, and Gaussian windows in the fast Fourier transform technique. We applied this model to the specific case of measuring the relative lengths of a compound Michelson interferometer. By processing computer-simulated data through our model, we project the ultimate precision for ideal data, and data containing AM-FM noise. The precision is shown to be limited by nonlinearities in the laser scan. absolute distance, interferometer.

  7. Error correcting coding-theory for structured light illumination systems

    NASA Astrophysics Data System (ADS)

    Porras-Aguilar, Rosario; Falaggis, Konstantinos; Ramos-Garcia, Ruben

    2017-06-01

    Intensity discrete structured light illumination systems project a series of projection patterns for the estimation of the absolute fringe order using only the temporal grey-level sequence at each pixel. This work proposes the use of error-correcting codes for pixel-wise correction of measurement errors. The use of an error correcting code is advantageous in many ways: it allows reducing the effect of random intensity noise, it corrects outliners near the border of the fringe commonly present when using intensity discrete patterns, and it provides a robustness in case of severe measurement errors (even for burst errors where whole frames are lost). The latter aspect is particular interesting in environments with varying ambient light as well as in critical safety applications as e.g. monitoring of deformations of components in nuclear power plants, where a high reliability is ensured even in case of short measurement disruptions. A special form of burst errors is the so-called salt and pepper noise, which can largely be removed with error correcting codes using only the information of a given pixel. The performance of this technique is evaluated using both simulations and experiments.

  8. Absolute nuclear material assay

    DOEpatents

    Prasad, Manoj K [Pleasanton, CA; Snyderman, Neal J [Berkeley, CA; Rowland, Mark S [Alamo, CA

    2012-05-15

    A method of absolute nuclear material assay of an unknown source comprising counting neutrons from the unknown source and providing an absolute nuclear material assay utilizing a model to optimally compare to the measured count distributions. In one embodiment, the step of providing an absolute nuclear material assay comprises utilizing a random sampling of analytically computed fission chain distributions to generate a continuous time-evolving sequence of event-counts by spreading the fission chain distribution in time.

  9. Absolute nuclear material assay

    DOEpatents

    Prasad, Manoj K [Pleasanton, CA; Snyderman, Neal J [Berkeley, CA; Rowland, Mark S [Alamo, CA

    2010-07-13

    A method of absolute nuclear material assay of an unknown source comprising counting neutrons from the unknown source and providing an absolute nuclear material assay utilizing a model to optimally compare to the measured count distributions. In one embodiment, the step of providing an absolute nuclear material assay comprises utilizing a random sampling of analytically computed fission chain distributions to generate a continuous time-evolving sequence of event-counts by spreading the fission chain distribution in time.

  10. Fuzzy Counter Propagation Neural Network Control for a Class of Nonlinear Dynamical Systems

    PubMed Central

    Sakhre, Vandana; Jain, Sanjeev; Sapkal, Vilas S.; Agarwal, Dev P.

    2015-01-01

    Fuzzy Counter Propagation Neural Network (FCPN) controller design is developed, for a class of nonlinear dynamical systems. In this process, the weight connecting between the instar and outstar, that is, input-hidden and hidden-output layer, respectively, is adjusted by using Fuzzy Competitive Learning (FCL). FCL paradigm adopts the principle of learning, which is used to calculate Best Matched Node (BMN) which is proposed. This strategy offers a robust control of nonlinear dynamical systems. FCPN is compared with the existing network like Dynamic Network (DN) and Back Propagation Network (BPN) on the basis of Mean Absolute Error (MAE), Mean Square Error (MSE), Best Fit Rate (BFR), and so forth. It envisages that the proposed FCPN gives better results than DN and BPN. The effectiveness of the proposed FCPN algorithms is demonstrated through simulations of four nonlinear dynamical systems and multiple input and single output (MISO) and a single input and single output (SISO) gas furnace Box-Jenkins time series data. PMID:26366169

  11. Fuzzy Counter Propagation Neural Network Control for a Class of Nonlinear Dynamical Systems.

    PubMed

    Sakhre, Vandana; Jain, Sanjeev; Sapkal, Vilas S; Agarwal, Dev P

    2015-01-01

    Fuzzy Counter Propagation Neural Network (FCPN) controller design is developed, for a class of nonlinear dynamical systems. In this process, the weight connecting between the instar and outstar, that is, input-hidden and hidden-output layer, respectively, is adjusted by using Fuzzy Competitive Learning (FCL). FCL paradigm adopts the principle of learning, which is used to calculate Best Matched Node (BMN) which is proposed. This strategy offers a robust control of nonlinear dynamical systems. FCPN is compared with the existing network like Dynamic Network (DN) and Back Propagation Network (BPN) on the basis of Mean Absolute Error (MAE), Mean Square Error (MSE), Best Fit Rate (BFR), and so forth. It envisages that the proposed FCPN gives better results than DN and BPN. The effectiveness of the proposed FCPN algorithms is demonstrated through simulations of four nonlinear dynamical systems and multiple input and single output (MISO) and a single input and single output (SISO) gas furnace Box-Jenkins time series data.

  12. Real-Time and Meter-Scale Absolute Distance Measurement by Frequency-Comb-Referenced Multi-Wavelength Interferometry

    PubMed Central

    Tan, Lilong; Yan, Shuhua

    2018-01-01

    We report on a frequency-comb-referenced absolute interferometer which instantly measures long distance by integrating multi-wavelength interferometry with direct synthetic wavelength interferometry. The reported interferometer utilizes four different wavelengths, simultaneously calibrated to the frequency comb of a femtosecond laser, to implement subwavelength distance measurement, while direct synthetic wavelength interferometry is elaborately introduced by launching a fifth wavelength to extend a non-ambiguous range for meter-scale measurement. A linearity test performed comparatively with a He–Ne laser interferometer shows a residual error of less than 70.8 nm in peak-to-valley over a 3 m distance, and a 10 h distance comparison is demonstrated to gain fractional deviations of ~3 × 10−8 versus 3 m distance. Test results reveal that the presented absolute interferometer enables precise, stable, and long-term distance measurements and facilitates absolute positioning applications such as large-scale manufacturing and space missions. PMID:29414897

  13. Effect of trabeculectomy on the accuracy of intraocular lens calculations in patients with open-angle glaucoma.

    PubMed

    Bae, Hyoung Won; Lee, Yun Ha; Kim, Do Wook; Lee, Taekjune; Hong, Samin; Seong, Gong Je; Kim, Chan Yun

    2016-08-01

    The objective of the study is to examine the effect of trabeculectomy on intraocular lens power calculations in patients with open-angle glaucoma (OAG) undergoing cataract surgery. The design is retrospective data analysis. There are a total of 55 eyes of 55 patients with OAG who had a cataract surgery alone or in combination with trabeculectomy. We classified OAG subjects into the following groups based on surgical history: only cataract surgery (OC group), cataract surgery after prior trabeculectomy (CAT group), and cataract surgery performed in combination with trabeculectomy (CCT group). Differences between actual and predicted postoperative refractive error. Mean error (ME, difference between postoperative and predicted SE) in the CCT group was significantly lower (towards myopia) than that of the OC group (P = 0.008). Additionally, mean absolute error (MAE, absolute value of ME) in the CAT group was significantly greater than in the OC group (P = 0.006). Using linear mixed models, the ME calculated with the SRK II formula was more accurate than the ME predicted by the SRK T formula in the CAT (P = 0.032) and CCT (P = 0.035) groups. The intraocular lens power prediction accuracy was lower in the CAT and CCT groups than in the OC group. The prediction error was greater in the CAT group than in the OC group, and the direction of the prediction error tended to be towards myopia in the CCT group. The SRK II formula may be more accurate in predicting residual refractive error in the CAT and CCT groups. © 2016 Royal Australian and New Zealand College of Ophthalmologists.

  14. Potential role of acetyl-CoA synthetase (acs) and malate dehydrogenase (mae) in the evolution of the acetate switch in Bacteria and Archaea

    USGS Publications Warehouse

    Barnhart, Elliott P.; McClure, Marcella A.; Johnson, Kiki; Cleveland, Sean; Hunt, Kristopher A.; Fields, Matthew W.

    2015-01-01

    Although many Archaea have AMP-Acs (acetyl-coenzyme A synthetase) and ADP-Acs, the extant methanogenic genus Methanosarcina is the only identified Archaeal genus that can utilize acetate via acetate kinase (Ack) and phosphotransacetylase (Pta). Despite the importance of ack as the potential urkinase in the ASKHA phosphotransferase superfamily, an origin hypothesis does not exist for the acetate kinase in Bacteria, Archaea, or Eukarya. Here we demonstrate that Archaeal AMP-Acs and ADP-Acs contain paralogous ATPase motifs previously identified in Ack, which demonstrate a novel relation between these proteins in Archaea. The identification of ATPase motif conservation and resulting structural features in AMP- and ADP-acetyl-CoA synthetase proteins in this study expand the ASKHA superfamily to include acetyl-CoA synthetase. Additional phylogenetic analysis showed that Pta and MaeB sequences had a common ancestor, and that the Pta lineage within the halophilc archaea was an ancestral lineage. These results suggested that divergence of a duplicated maeB within an ancient halophilic, archaeal lineage formed a putative pta ancestor. These results provide a potential scenario for the establishment of the Ack/Pta pathway and provide novel insight into the evolution of acetate metabolism for all three domains of life.

  15. Potential Role of Acetyl-CoA Synthetase (acs) and Malate Dehydrogenase (mae) in the Evolution of the Acetate Switch in Bacteria and Archaea

    DOE PAGES

    Barnhart, Elliott P.; McClure, Marcella A.; Johnson, Kiki; ...

    2015-08-03

    Although many Archaea have AMP-Acs (acetyl-coenzyme A synthetase) and ADP-Acs, the extant methanogenic genus Methanosarcina is the only identified Archaeal genus that can utilize acetate via acetate kinase (Ack) and phosphotransacetylase (Pta). Despite the importance of ack as the potential urkinase in the ASKHA phosphotransferase superfamily, an origin hypothesis does not exist for the acetate kinase in Bacteria, Archaea, or Eukarya. Here we demonstrate that Archaeal AMP-Acs and ADP-Acs contain paralogous ATPase motifs previously identified in Ack, which demonstrate a novel relation between these proteins in Archaea. The identification of ATPase motif conservation and resulting structural features in AMP- andmore » ADP-acetyl-CoA synthetase proteins in this study expand the ASKHA superfamily to include acetyl-CoA synthetase. Additional phylogenetic analysis showed that Pta and MaeB sequences had a common ancestor, and that the Pta lineage within the halophilc archaea was an ancestral lineage. Lastly, these results suggested that divergence of a duplicated maeB within an ancient halophilic, archaeal lineage formed a putative pta ancestor. These results provide a potential scenario for the establishment of the Ack/Pta pathway and provide novel insight into the evolution of acetate metabolism for all three domains of life.« less

  16. Prediction of matching condition for a microstrip subsystem using artificial neural network and adaptive neuro-fuzzy inference system

    NASA Astrophysics Data System (ADS)

    Salehi, Mohammad Reza; Noori, Leila; Abiri, Ebrahim

    2016-11-01

    In this paper, a subsystem consisting of a microstrip bandpass filter and a microstrip low noise amplifier (LNA) is designed for WLAN applications. The proposed filter has a small implementation area (49 mm2), small insertion loss (0.08 dB) and wide fractional bandwidth (FBW) (61%). To design the proposed LNA, the compact microstrip cells, an field effect transistor, and only a lumped capacitor are used. It has a low supply voltage and a low return loss (-40 dB) at the operation frequency. The matching condition of the proposed subsystem is predicted using subsystem analysis, artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). To design the proposed filter, the transmission matrix of the proposed resonator is obtained and analysed. The performance of the proposed ANN and ANFIS models is tested using the numerical data by four performance measures, namely the correlation coefficient (CC), the mean absolute error (MAE), the average percentage error (APE) and the root mean square error (RMSE). The obtained results show that these models are in good agreement with the numerical data, and a small error between the predicted values and numerical solution is obtained.

  17. Information systems and human error in the lab.

    PubMed

    Bissell, Michael G

    2004-01-01

    Health system costs in clinical laboratories are incurred daily due to human error. Indeed, a major impetus for automating clinical laboratories has always been the opportunity it presents to simultaneously reduce cost and improve quality of operations by decreasing human error. But merely automating these processes is not enough. To the extent that introduction of these systems results in operators having less practice in dealing with unexpected events or becoming deskilled in problemsolving, however new kinds of error will likely appear. Clinical laboratories could potentially benefit by integrating findings on human error from modern behavioral science into their operations. Fully understanding human error requires a deep understanding of human information processing and cognition. Predicting and preventing negative consequences requires application of this understanding to laboratory operations. Although the occurrence of a particular error at a particular instant cannot be absolutely prevented, human error rates can be reduced. The following principles are key: an understanding of the process of learning in relation to error; understanding the origin of errors since this knowledge can be used to reduce their occurrence; optimal systems should be forgiving to the operator by absorbing errors, at least for a time; although much is known by industrial psychologists about how to write operating procedures and instructions in ways that reduce the probability of error, this expertise is hardly ever put to use in the laboratory; and a feedback mechanism must be designed into the system that enables the operator to recognize in real time that an error has occurred.

  18. Ultraspectral sounding retrieval error budget and estimation

    NASA Astrophysics Data System (ADS)

    Zhou, Daniel K.; Larar, Allen M.; Liu, Xu; Smith, William L.; Strow, Larrabee L.; Yang, Ping

    2011-11-01

    The ultraspectral infrared radiances obtained from satellite observations provide atmospheric, surface, and/or cloud information. The intent of the measurement of the thermodynamic state is the initialization of weather and climate models. Great effort has been given to retrieving and validating these atmospheric, surface, and/or cloud properties. Error Consistency Analysis Scheme (ECAS), through fast radiative transfer model (RTM) forward and inverse calculations, has been developed to estimate the error budget in terms of absolute and standard deviation of differences in both spectral radiance and retrieved geophysical parameter domains. The retrieval error is assessed through ECAS without assistance of other independent measurements such as radiosonde data. ECAS re-evaluates instrument random noise, and establishes the link between radiometric accuracy and retrieved geophysical parameter accuracy. ECAS can be applied to measurements of any ultraspectral instrument and any retrieval scheme with associated RTM. In this paper, ECAS is described and demonstration is made with the measurements of the METOP-A satellite Infrared Atmospheric Sounding Interferometer (IASI).

  19. Ultraspectral Sounding Retrieval Error Budget and Estimation

    NASA Technical Reports Server (NTRS)

    Zhou, Daniel K.; Larar, Allen M.; Liu, Xu; Smith, William L.; Strow, L. Larrabee; Yang, Ping

    2011-01-01

    The ultraspectral infrared radiances obtained from satellite observations provide atmospheric, surface, and/or cloud information. The intent of the measurement of the thermodynamic state is the initialization of weather and climate models. Great effort has been given to retrieving and validating these atmospheric, surface, and/or cloud properties. Error Consistency Analysis Scheme (ECAS), through fast radiative transfer model (RTM) forward and inverse calculations, has been developed to estimate the error budget in terms of absolute and standard deviation of differences in both spectral radiance and retrieved geophysical parameter domains. The retrieval error is assessed through ECAS without assistance of other independent measurements such as radiosonde data. ECAS re-evaluates instrument random noise, and establishes the link between radiometric accuracy and retrieved geophysical parameter accuracy. ECAS can be applied to measurements of any ultraspectral instrument and any retrieval scheme with associated RTM. In this paper, ECAS is described and demonstration is made with the measurements of the METOP-A satellite Infrared Atmospheric Sounding Interferometer (IASI)..

  20. The juvenile face as a suitable age indicator in child pornography cases: a pilot study on the reliability of automated and visual estimation approaches.

    PubMed

    Ratnayake, M; Obertová, Z; Dose, M; Gabriel, P; Bröker, H M; Brauckmann, M; Barkus, A; Rizgeliene, R; Tutkuviene, J; Ritz-Timme, S; Marasciuolo, L; Gibelli, D; Cattaneo, C

    2014-09-01

    In cases of suspected child pornography, the age of the victim represents a crucial factor for legal prosecution. The conventional methods for age estimation provide unreliable age estimates, particularly if teenage victims are concerned. In this pilot study, the potential of age estimation for screening purposes is explored for juvenile faces. In addition to a visual approach, an automated procedure is introduced, which has the ability to rapidly scan through large numbers of suspicious image data in order to trace juvenile faces. Age estimations were performed by experts, non-experts and the Demonstrator of a developed software on frontal facial images of 50 females aged 10-19 years from Germany, Italy, and Lithuania. To test the accuracy, the mean absolute error (MAE) between the estimates and the real ages was calculated for each examiner and the Demonstrator. The Demonstrator achieved the lowest MAE (1.47 years) for the 50 test images. Decreased image quality had no significant impact on the performance and classification results. The experts delivered slightly less accurate MAE (1.63 years). Throughout the tested age range, both the manual and the automated approach led to reliable age estimates within the limits of natural biological variability. The visual analysis of the face produces reasonably accurate age estimates up to the age of 18 years, which is the legally relevant age threshold for victims in cases of pedo-pornography. This approach can be applied in conjunction with the conventional methods for a preliminary age estimation of juveniles depicted on images.

  1. A cross comparison of spatiotemporally enhanced springtime phenological measurements from satellites and ground in a northern U.S. mixed forest

    USGS Publications Warehouse

    Liang, Liang; Schwartz, Mark D.; Zhuosen Wang,; Gao, Feng; Schaaf, Crystal B.; Bin Tan,; Morisette, Jeffrey T.; Zhang, Xiaoyang

    2014-01-01

    Cross comparison of satellite-derived land surface phenology (LSP) and ground measurements is useful to ensure the relevance of detected seasonal vegetation change to the underlying biophysical processes. While standard 16-day and 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index (VI)-based springtime LSP has been evaluated in previous studies, it remains unclear whether LSP with enhanced temporal and spatial resolutions can capture additional details of ground phenology. In this paper, we compared LSP derived from 500-m daily MODIS and 30-m MODIS-Landsat fused VI data with landscape phenology (LP) in a northern U.S. mixed forest. LP was previously developed from intensively observed deciduous and coniferous tree phenology using an upscaling approach. Results showed that daily MODIS-based LSP consistently estimated greenup onset dates at the study area (625 m × 625 m) level with 4.48 days of mean absolute error (MAE), slightly better than that of using 16-day standard VI (4.63 days MAE). For the observed study areas, the time series with increased number of observations confirmed that post-bud burst deciduous tree phenology contributes the most to vegetation reflectance change. Moreover, fused VI time series demonstrated closer correspondences with LP at the community level (0.1-20 ha) than using MODIS alone at the study area level (390 ha). The fused LSP captured greenup onset dates for respective forest communities of varied sizes and compositions with four days of the overall MAE. This study supports further use of spatiotemporally enhanced LSP for more precise phenological monitoring.

  2. A comparison of multiple indicator kriging and area-to-point Poisson kriging for mapping patterns of herbivore species abundance in Kruger National Park, South Africa

    PubMed Central

    Kerry, Ruth; Goovaerts, Pierre; Smit, Izak P.J.; Ingram, Ben R.

    2015-01-01

    Kruger National Park (KNP), South Africa, provides protected habitats for the unique animals of the African savannah. For the past 40 years, annual aerial surveys of herbivores have been conducted to aid management decisions based on (1) the spatial distribution of species throughout the park and (2) total species populations in a year. The surveys are extremely time consuming and costly. For many years, the whole park was surveyed, but in 1998 a transect survey approach was adopted. This is cheaper and less time consuming but leaves gaps in the data spatially. Also the distance method currently employed by the park only gives estimates of total species populations but not their spatial distribution. We compare the ability of multiple indicator kriging and area-to-point Poisson kriging to accurately map species distribution in the park. A leave-one-out cross-validation approach indicates that multiple indicator kriging makes poor estimates of the number of animals, particularly the few large counts, as the indicator variograms for such high thresholds are pure nugget. Poisson kriging was applied to the prediction of two types of abundance data: spatial density and proportion of a given species. Both Poisson approaches had standardized mean absolute errors (St. MAEs) of animal counts at least an order of magnitude lower than multiple indicator kriging. The spatial density, Poisson approach (1), gave the lowest St. MAEs for the most abundant species and the proportion, Poisson approach (2), did for the least abundant species. Incorporating environmental data into Poisson approach (2) further reduced St. MAEs. PMID:25729318

  3. A comparison of multiple indicator kriging and area-to-point Poisson kriging for mapping patterns of herbivore species abundance in Kruger National Park, South Africa.

    PubMed

    Kerry, Ruth; Goovaerts, Pierre; Smit, Izak P J; Ingram, Ben R

    Kruger National Park (KNP), South Africa, provides protected habitats for the unique animals of the African savannah. For the past 40 years, annual aerial surveys of herbivores have been conducted to aid management decisions based on (1) the spatial distribution of species throughout the park and (2) total species populations in a year. The surveys are extremely time consuming and costly. For many years, the whole park was surveyed, but in 1998 a transect survey approach was adopted. This is cheaper and less time consuming but leaves gaps in the data spatially. Also the distance method currently employed by the park only gives estimates of total species populations but not their spatial distribution. We compare the ability of multiple indicator kriging and area-to-point Poisson kriging to accurately map species distribution in the park. A leave-one-out cross-validation approach indicates that multiple indicator kriging makes poor estimates of the number of animals, particularly the few large counts, as the indicator variograms for such high thresholds are pure nugget. Poisson kriging was applied to the prediction of two types of abundance data: spatial density and proportion of a given species. Both Poisson approaches had standardized mean absolute errors (St. MAEs) of animal counts at least an order of magnitude lower than multiple indicator kriging. The spatial density, Poisson approach (1), gave the lowest St. MAEs for the most abundant species and the proportion, Poisson approach (2), did for the least abundant species. Incorporating environmental data into Poisson approach (2) further reduced St. MAEs.

  4. Neuromuscular function of the quadriceps muscle during isometric maximal, submaximal and submaximal fatiguing voluntary contractions in knee osteoarthrosis patients

    PubMed Central

    Jacksteit, Robert; Jackszis, Mario; Feldhege, Frank; Weippert, Matthias; Mittelmeier, Wolfram; Bader, Rainer; Skripitz, Ralf; Behrens, Martin

    2017-01-01

    Introduction Knee osteoarthrosis (KOA) is commonly associated with a dysfunction of the quadriceps muscle which contributes to alterations in motor performance. The underlying neuromuscular mechanisms of muscle dysfunction are not fully understood. The main objective of this study was to analyze how KOA affects neuromuscular function of the quadriceps muscle during different contraction intensities. Materials and methods The following parameters were assessed in 20 patients and 20 healthy controls: (i) joint position sense, i.e. position control (mean absolute error, MAE) at 30° and 50° of knee flexion, (ii) simple reaction time task performance, (iii) isometric maximal voluntary torque (IMVT) and root mean square of the EMG signal (RMS-EMG), (iv) torque control, i.e. accuracy (MAE), absolute fluctuation (standard deviation, SD), relative fluctuation (coefficient of variation, CV) and periodicity (mean frequency, MNF) of the torque signal at 20%, 40% and 60% IMVT, (v) EMG-torque relationship at 20%, 40% and 60% IMVT and (vi) performance fatigability, i.e. time to task failure (TTF) at 40% IMVT. Results Compared to the control group, the KOA group displayed: (i) significantly higher MAE of the angle signal at 30° (99.3%; P = 0.027) and 50° (147.9%; P < 0.001), (ii) no significant differences in reaction time, (iii) significantly lower IMVT (-41.6%; P = 0.001) and tendentially lower RMS-EMG of the rectus femoris (-33.7%; P = 0.054), (iv) tendentially higher MAE of the torque signal at 20% IMVT (65.9%; P = 0.068), significantly lower SD of the torque signal at all three torque levels and greater MNF at 60% IMVT (44.8%; P = 0.018), (v) significantly increased RMS-EMG of the vastus lateralis at 20% (70.8%; P = 0.003) and 40% IMVT (33.3%; P = 0.034), significantly lower RMS-EMG of the biceps femoris at 20% (-63.6%; P = 0.044) and 40% IMVT (-41.3%; P = 0.028) and tendentially lower at 60% IMVT (-24.3%; P = 0.075) and (vi) significantly shorter TTF (-51.1%; P = 0

  5. Seasonality and Trend Forecasting of Tuberculosis Prevalence Data in Eastern Cape, South Africa, Using a Hybrid Model.

    PubMed

    Azeez, Adeboye; Obaromi, Davies; Odeyemi, Akinwumi; Ndege, James; Muntabayi, Ruffin

    2016-07-26

    Tuberculosis (TB) is a deadly infectious disease caused by Mycobacteria tuberculosis. Tuberculosis as a chronic and highly infectious disease is prevalent in almost every part of the globe. More than 95% of TB mortality occurs in low/middle income countries. In 2014, approximately 10 million people were diagnosed with active TB and two million died from the disease. In this study, our aim is to compare the predictive powers of the seasonal autoregressive integrated moving average (SARIMA) and neural network auto-regression (SARIMA-NNAR) models of TB incidence and analyse its seasonality in South Africa. TB incidence cases data from January 2010 to December 2015 were extracted from the Eastern Cape Health facility report of the electronic Tuberculosis Register (ERT.Net). A SARIMA model and a combined model of SARIMA model and a neural network auto-regression (SARIMA-NNAR) model were used in analysing and predicting the TB data from 2010 to 2015. Simulation performance parameters of mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), mean percent error (MPE), mean absolute scaled error (MASE) and mean absolute percentage error (MAPE) were applied to assess the better performance of prediction between the models. Though practically, both models could predict TB incidence, the combined model displayed better performance. For the combined model, the Akaike information criterion (AIC), second-order AIC (AICc) and Bayesian information criterion (BIC) are 288.56, 308.31 and 299.09 respectively, which were lower than the SARIMA model with corresponding values of 329.02, 327.20 and 341.99, respectively. The seasonality trend of TB incidence was forecast to have a slightly increased seasonal TB incidence trend from the SARIMA-NNAR model compared to the single model. The combined model indicated a better TB incidence forecasting with a lower AICc. The model also indicates the need for resolute intervention to reduce infectious disease

  6. Magnetic Resonance-Based Automatic Air Segmentation for Generation of Synthetic Computed Tomography Scans in the Head Region.

    PubMed

    Zheng, Weili; Kim, Joshua P; Kadbi, Mo; Movsas, Benjamin; Chetty, Indrin J; Glide-Hurst, Carri K

    2015-11-01

    To incorporate a novel imaging sequence for robust air and tissue segmentation using ultrashort echo time (UTE) phase images and to implement an innovative synthetic CT (synCT) solution as a first step toward MR-only radiation therapy treatment planning for brain cancer. Ten brain cancer patients were scanned with a UTE/Dixon sequence and other clinical sequences on a 1.0 T open magnet with simulation capabilities. Bone-enhanced images were generated from a weighted combination of water/fat maps derived from Dixon images and inverted UTE images. Automated air segmentation was performed using unwrapped UTE phase maps. Segmentation accuracy was assessed by calculating segmentation errors (true-positive rate, false-positive rate, and Dice similarity indices using CT simulation (CT-SIM) as ground truth. The synCTs were generated using a voxel-based, weighted summation method incorporating T2, fluid attenuated inversion recovery (FLAIR), UTE1, and bone-enhanced images. Mean absolute error (MAE) characterized Hounsfield unit (HU) differences between synCT and CT-SIM. A dosimetry study was conducted, and differences were quantified using γ-analysis and dose-volume histogram analysis. On average, true-positive rate and false-positive rate for the CT and MR-derived air masks were 80.8% ± 5.5% and 25.7% ± 6.9%, respectively. Dice similarity indices values were 0.78 ± 0.04 (range, 0.70-0.83). Full field of view MAE between synCT and CT-SIM was 147.5 ± 8.3 HU (range, 138.3-166.2 HU), with the largest errors occurring at bone-air interfaces (MAE 422.5 ± 33.4 HU for bone and 294.53 ± 90.56 HU for air). Gamma analysis revealed pass rates of 99.4% ± 0.04%, with acceptable treatment plan quality for the cohort. A hybrid MRI phase/magnitude UTE image processing technique was introduced that significantly improved bone and air contrast in MRI. Segmented air masks and bone-enhanced images were integrated into our synCT pipeline for brain, and results agreed well with clinical

  7. Absolute Plate Velocities from Seismic Anisotropy

    NASA Astrophysics Data System (ADS)

    Kreemer, Corné; Zheng, Lin; Gordon, Richard

    2015-04-01

    The orientation of seismic anisotropy inferred beneath plate interiors may provide a means to estimate the motions of the plate relative to the sub-asthenospheric mantle. Here we analyze two global sets of shear-wave splitting data, that of Kreemer [2009] and an updated and expanded data set, to estimate plate motions and to better understand the dispersion of the data, correlations in the errors, and their relation to plate speed. We also explore the effect of using geologically current plate velocities (i.e., the MORVEL set of angular velocities [DeMets et al. 2010]) compared with geodetically current plate velocities (i.e., the GSRM v1.2 angular velocities [Kreemer et al. 2014]). We demonstrate that the errors in plate motion azimuths inferred from shear-wave splitting beneath any one tectonic plate are correlated with the errors of other azimuths from the same plate. To account for these correlations, we adopt a two-tier analysis: First, find the pole of rotation and confidence limits for each plate individually. Second, solve for the best fit to these poles while constraining relative plate angular velocities to consistency with the MORVEL relative plate angular velocities. The SKS-MORVEL absolute plate angular velocities (based on the Kreemer [2009] data set) are determined from the poles from eight plates weighted proportionally to the root-mean-square velocity of each plate. SKS-MORVEL indicates that eight plates (Amur, Antarctica, Caribbean, Eurasia, Lwandle, Somalia, Sundaland, and Yangtze) have angular velocities that differ insignificantly from zero. The net rotation of the lithosphere is 0.25±0.11° Ma-1 (95% confidence limits) right-handed about 57.1°S, 68.6°E. The within-plate dispersion of seismic anisotropy for oceanic lithosphere (σ=19.2° ) differs insignificantly from that for continental lithosphere (σ=21.6° ). The between-plate dispersion, however, is significantly smaller for oceanic lithosphere (σ=7.4° ) than for continental

  8. An error criterion for determining sampling rates in closed-loop control systems

    NASA Technical Reports Server (NTRS)

    Brecher, S. M.

    1972-01-01

    The determination of an error criterion which will give a sampling rate for adequate performance of linear, time-invariant closed-loop, discrete-data control systems was studied. The proper modelling of the closed-loop control system for characterization of the error behavior, and the determination of an absolute error definition for performance of the two commonly used holding devices are discussed. The definition of an adequate relative error criterion as a function of the sampling rate and the parameters characterizing the system is established along with the determination of sampling rates. The validity of the expressions for the sampling interval was confirmed by computer simulations. Their application solves the problem of making a first choice in the selection of sampling rates.

  9. Unifying distance-based goodness-of-fit indicators for hydrologic model assessment

    NASA Astrophysics Data System (ADS)

    Cheng, Qinbo; Reinhardt-Imjela, Christian; Chen, Xi; Schulte, Achim

    2014-05-01

    The goodness-of-fit indicator, i.e. efficiency criterion, is very important for model calibration. However, recently the knowledge about the goodness-of-fit indicators is all empirical and lacks a theoretical support. Based on the likelihood theory, a unified distance-based goodness-of-fit indicator termed BC-GED model is proposed, which uses the Box-Cox (BC) transformation to remove the heteroscedasticity of model errors and the generalized error distribution (GED) with zero-mean to fit the distribution of model errors after BC. The BC-GED model can unify all recent distance-based goodness-of-fit indicators, and reveals the mean square error (MSE) and the mean absolute error (MAE) that are widely used goodness-of-fit indicators imply statistic assumptions that the model errors follow the Gaussian distribution and the Laplace distribution with zero-mean, respectively. The empirical knowledge about goodness-of-fit indicators can be also easily interpreted by BC-GED model, e.g. the sensitivity to high flow of the goodness-of-fit indicators with large power of model errors results from the low probability of large model error in the assumed distribution of these indicators. In order to assess the effect of the parameters (i.e. the BC transformation parameter λ and the GED kurtosis coefficient β also termed the power of model errors) of BC-GED model on hydrologic model calibration, six cases of BC-GED model were applied in Baocun watershed (East China) with SWAT-WB-VSA model. Comparison of the inferred model parameters and model simulation results among the six indicators demonstrates these indicators can be clearly separated two classes by the GED kurtosis β: β >1 and β ≤ 1. SWAT-WB-VSA calibrated by the class β >1 of distance-based goodness-of-fit indicators captures high flow very well and mimics the baseflow very badly, but it calibrated by the class β ≤ 1 mimics the baseflow very well, because first the larger value of β, the greater emphasis is put on

  10. Evaluation of centroiding algorithm error for Nano-JASMINE

    NASA Astrophysics Data System (ADS)

    Hara, Takuji; Gouda, Naoteru; Yano, Taihei; Yamada, Yoshiyuki

    2014-08-01

    The Nano-JASMINE mission has been designed to perform absolute astrometric measurements with unprecedented accuracy; the end-of-mission parallax standard error is required to be of the order of 3 milli arc seconds for stars brighter than 7.5 mag in the zw-band(0.6μm-1.0μm) .These requirements set a stringent constraint on the accuracy of the estimation of the location of the stellar image on the CCD for each observation. However each stellar images have individual shape depend on the spectral energy distribution of the star, the CCD properties, and the optics and its associated wave front errors. So it is necessity that the centroiding algorithm performs a high accuracy in any observables. Referring to the study of Gaia, we use LSF fitting method for centroiding algorithm, and investigate systematic error of the algorithm for Nano-JASMINE. Furthermore, we found to improve the algorithm by restricting sample LSF when we use a Principle Component Analysis. We show that centroiding algorithm error decrease after adapted the method.

  11. Use of Selected Goodness-of-Fit Statistics to Assess the Accuracy of a Model of Henry Hagg Lake, Oregon

    NASA Astrophysics Data System (ADS)

    Rounds, S. A.; Sullivan, A. B.

    2004-12-01

    Assessing a model's ability to reproduce field data is a critical step in the modeling process. For any model, some method of determining goodness-of-fit to measured data is needed to aid in calibration and to evaluate model performance. Visualizations and graphical comparisons of model output are an excellent way to begin that assessment. At some point, however, model performance must be quantified. Goodness-of-fit statistics, including the mean error (ME), mean absolute error (MAE), root mean square error, and coefficient of determination, typically are used to measure model accuracy. Statistical tools such as the sign test or Wilcoxon test can be used to test for model bias. The runs test can detect phase errors in simulated time series. Each statistic is useful, but each has its limitations. None provides a complete quantification of model accuracy. In this study, a suite of goodness-of-fit statistics was applied to a model of Henry Hagg Lake in northwest Oregon. Hagg Lake is a man-made reservoir on Scoggins Creek, a tributary to the Tualatin River. Located on the west side of the Portland metropolitan area, the Tualatin Basin is home to more than 450,000 people. Stored water in Hagg Lake helps to meet the agricultural and municipal water needs of that population. Future water demands have caused water managers to plan for a potential expansion of Hagg Lake, doubling its storage to roughly 115,000 acre-feet. A model of the lake was constructed to evaluate the lake's water quality and estimate how that quality might change after raising the dam. The laterally averaged, two-dimensional, U.S. Army Corps of Engineers model CE-QUAL-W2 was used to construct the Hagg Lake model. Calibrated for the years 2000 and 2001 and confirmed with data from 2002 and 2003, modeled parameters included water temperature, ammonia, nitrate, phosphorus, algae, zooplankton, and dissolved oxygen. Several goodness-of-fit statistics were used to quantify model accuracy and bias. Model

  12. The correction of vibration in frequency scanning interferometry based absolute distance measurement system for dynamic measurements

    NASA Astrophysics Data System (ADS)

    Lu, Cheng; Liu, Guodong; Liu, Bingguo; Chen, Fengdong; Zhuang, Zhitao; Xu, Xinke; Gan, Yu

    2015-10-01

    Absolute distance measurement systems are of significant interest in the field of metrology, which could improve the manufacturing efficiency and accuracy of large assemblies in fields such as aircraft construction, automotive engineering, and the production of modern windmill blades. Frequency scanning interferometry demonstrates noticeable advantages as an absolute distance measurement system which has a high precision and doesn't depend on a cooperative target. In this paper , the influence of inevitable vibration in the frequency scanning interferometry based absolute distance measurement system is analyzed. The distance spectrum is broadened as the existence of Doppler effect caused by vibration, which will bring in a measurement error more than 103 times bigger than the changes of optical path difference. In order to decrease the influence of vibration, the changes of the optical path difference are monitored by a frequency stabilized laser, which runs parallel to the frequency scanning interferometry. The experiment has verified the effectiveness of this method.

  13. Use of 3H/3He Ages to evaluate and improve groundwater flow models in a complex buried-valley aquifer

    USGS Publications Warehouse

    Sheets, Rodney A.; Bair, E. Scott; Rowe, Gary L.

    1998-01-01

    Combined use of the tritium/helium 3 (3H/3He) dating technique and particle-tracking analysis can improve flow-model calibration. As shown at two sites in the Great Miami buried-valley aquifer in southwestern Ohio, the combined use of 3H/3He age dating and particle tracking led to a lower mean absolute error between measured heads and simulated heads than in the original calibrated models and/or between simulated travel times and 3H/3He ages. Apparent groundwater ages were obtained for water samples collected from 44 wells at two locations where previously constructed finite difference models of groundwater flow were available (Mound Plant and Wright-Patterson Air Force Base (WPAFB)). The two-layer Mound Plant model covers 11 km2 within the buried-valley aquifer. The WPAFB model has three layers and covers 262 km2 within the buried-valley aquifer and adjacent bedrock uplands. Sampled wells were chosen along flow paths determined from potentiometric maps or particle-tracking analyses. Water samples were collected at various depths within the aquifer. In the Mound Plant area, samples used for comparison of 3H/3He ages with simulated travel times were from wells completed in the uppermost model layer. Simulated travel times agreed well with 3H/3He ages. The mean absolute error (MAE) was 3.5 years. Agreement in ages at WPAFB decreased with increasing depth in the system. The MAEs were 1.63, 17.2, and 255 years for model layers 1, 2, and 3, respectively. Discrepancies between the simulated travel times and 3H/3He ages were assumed to be due to improper conceptualization or incorrect parameterization of the flow models. Selected conceptual and parameter modifications to the models resulted in improved agreement between 3H/3He ages and simulated travel times and between measured and simulated heads and flows.

  14. Daily Suspended Sediment Discharge Prediction Using Multiple Linear Regression and Artificial Neural Network

    NASA Astrophysics Data System (ADS)

    Uca; Toriman, Ekhwan; Jaafar, Othman; Maru, Rosmini; Arfan, Amal; Saleh Ahmar, Ansari

    2018-01-01

    Prediction of suspended sediment discharge in a catchments area is very important because it can be used to evaluation the erosion hazard, management of its water resources, water quality, hydrology project management (dams, reservoirs, and irrigation) and to determine the extent of the damage that occurred in the catchments. Multiple Linear Regression analysis and artificial neural network can be used to predict the amount of daily suspended sediment discharge. Regression analysis using the least square method, whereas artificial neural networks using Radial Basis Function (RBF) and feedforward multilayer perceptron with three learning algorithms namely Levenberg-Marquardt (LM), Scaled Conjugate Descent (SCD) and Broyden-Fletcher-Goldfarb-Shanno Quasi-Newton (BFGS). The number neuron of hidden layer is three to sixteen, while in output layer only one neuron because only one output target. The mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R2 ) and coefficient of efficiency (CE) of the multiple linear regression (MLRg) value Model 2 (6 input variable independent) has the lowest the value of MAE and RMSE (0.0000002 and 13.6039) and highest R2 and CE (0.9971 and 0.9971). When compared between LM, SCG and RBF, the BFGS model structure 3-7-1 is the better and more accurate to prediction suspended sediment discharge in Jenderam catchment. The performance value in testing process, MAE and RMSE (13.5769 and 17.9011) is smallest, meanwhile R2 and CE (0.9999 and 0.9998) is the highest if it compared with the another BFGS Quasi-Newton model (6-3-1, 9-10-1 and 12-12-1). Based on the performance statistics value, MLRg, LM, SCG, BFGS and RBF suitable and accurately for prediction by modeling the non-linear complex behavior of suspended sediment responses to rainfall, water depth and discharge. The comparison between artificial neural network (ANN) and MLRg, the MLRg Model 2 accurately for to prediction suspended sediment discharge (kg

  15. WE-AB-207A-02: John’s Equation Based Consistency Condition and Incomplete Projection Restoration Upon Circular Orbit CBCT

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ma, J; Qi, H; Wu, S

    Purpose: In transmitted X-ray tomography imaging, projections are sometimes incomplete due to a variety of reasons, such as geometry inaccuracy, defective detector cells, etc. To address this issue, we have derived a direct consistency condition based on John’s Equation, and proposed a method to effectively restore incomplete projections based on this consistency condition. Methods: Through parameter substitutions, we have derived a direct consistency condition equation from John’s equation, in which the left side is only projection derivative of view and the right side is projection derivative of other geometrical parameters. Based on this consistency condition, a projection restoration method ismore » proposed, which includes five steps: 1) Forward projecting reconstructed image and using linear interpolation to estimate the incomplete projections as the initial result; 2) Performing Fourier transform on the projections; 3) Restoring the incomplete frequency data using the consistency condition equation; 4) Performing inverse Fourier transform; 5) Repeat step 2)∼4) until our criteria is met to terminate the iteration. Results: A beam-blocking-based scatter correction case and a bad-pixel correction case were used to demonstrate the efficacy and robustness of our restoration method. The mean absolute error (MAE), signal noise ratio (SNR) and mean square error (MSE) were employed as our evaluation metrics of the reconstructed images. For the scatter correction case, the MAE is reduced from 63.3% to 71.7% with 4 iterations. Compared with the existing Patch’s method, the MAE of our method is further reduced by 8.72%. For the bad-pixel case, the SNR of the reconstructed image by our method is increased from 13.49% to 21.48%, with the MSE being decreased by 45.95%, compared with linear interpolation method. Conclusion: Our studies have demonstrated that our restoration method based on the new consistency condition could effectively restore the incomplete

  16. Surface modeling of soil antibiotics.

    PubMed

    Shi, Wen-jiao; Yue, Tian-xiang; Du, Zheng-ping; Wang, Zong; Li, Xue-wen

    2016-02-01

    Large numbers of livestock and poultry feces are continuously applied into soils in intensive vegetable cultivation areas, and then some veterinary antibiotics are persistent existed in soils and cause health risk. For the spatial heterogeneity of antibiotic residues, developing a suitable technique to interpolate soil antibiotic residues is still a challenge. In this study, we developed an effective interpolator, high accuracy surface modeling (HASM) combined vegetable types, to predict the spatial patterns of soil antibiotics, using 100 surface soil samples collected from an intensive vegetable cultivation area located in east of China, and the fluoroquinolones (FQs), including ciprofloxacin (CFX), enrofloxacin (EFX) and norfloxacin (NFX), were analyzed as the target antibiotics. The results show that vegetable type is an effective factor to be combined to improve the interpolator performance. HASM achieves less mean absolute errors (MAEs) and root mean square errors (RMSEs) for total FQs (NFX+CFX+EFX), NFX, CFX and EFX than kriging with external drift (KED), stratified kriging (StK), ordinary kriging (OK) and inverse distance weighting (IDW). The MAE of HASM for FQs is 55.1 μg/kg, and the MAEs of KED, StK, OK and IDW are 99.0 μg/kg, 102.8 μg/kg, 106.3 μg/kg and 108.7 μg/kg, respectively. Further, RMSE simulated by HASM for FQs (CFX, EFX and NFX) are 106.2 μg/kg (88.6 μg/kg, 20.4 μg/kg and 39.2 μg/kg), and less 30% (27%, 22% and 36%), 33% (27%, 27% and 43%), 38% (34%, 23% and 41%) and 42% (32%, 35% and 51%) than the ones by KED, StK, OK and IDW, respectively. HASM also provides better maps with more details and more consistent maximum and minimum values of soil antibiotics compared with the measured data. The better performance can be concluded that HASM takes the vegetable type information as global approximate information, and takes local sampling data as its optimum control constraints. Copyright © 2015 Elsevier B.V. All rights reserved.

  17. Integrated Navigation System Design for Micro Planetary Rovers: Comparison of Absolute Heading Estimation Algorithms and Nonlinear Filtering

    PubMed Central

    Ilyas, Muhammad; Hong, Beomjin; Cho, Kuk; Baeg, Seung-Ho; Park, Sangdeok

    2016-01-01

    This paper provides algorithms to fuse relative and absolute microelectromechanical systems (MEMS) navigation sensors, suitable for micro planetary rovers, to provide a more accurate estimation of navigation information, specifically, attitude and position. Planetary rovers have extremely slow speed (~1 cm/s) and lack conventional navigation sensors/systems, hence the general methods of terrestrial navigation may not be applicable to these applications. While relative attitude and position can be tracked in a way similar to those for ground robots, absolute navigation information is hard to achieve on a remote celestial body, like Moon or Mars, in contrast to terrestrial applications. In this study, two absolute attitude estimation algorithms were developed and compared for accuracy and robustness. The estimated absolute attitude was fused with the relative attitude sensors in a framework of nonlinear filters. The nonlinear Extended Kalman filter (EKF) and Unscented Kalman filter (UKF) were compared in pursuit of better accuracy and reliability in this nonlinear estimation problem, using only on-board low cost MEMS sensors. Experimental results confirmed the viability of the proposed algorithms and the sensor suite, for low cost and low weight micro planetary rovers. It is demonstrated that integrating the relative and absolute navigation MEMS sensors reduces the navigation errors to the desired level. PMID:27223293

  18. Integrated Navigation System Design for Micro Planetary Rovers: Comparison of Absolute Heading Estimation Algorithms and Nonlinear Filtering.

    PubMed

    Ilyas, Muhammad; Hong, Beomjin; Cho, Kuk; Baeg, Seung-Ho; Park, Sangdeok

    2016-05-23

    This paper provides algorithms to fuse relative and absolute microelectromechanical systems (MEMS) navigation sensors, suitable for micro planetary rovers, to provide a more accurate estimation of navigation information, specifically, attitude and position. Planetary rovers have extremely slow speed (~1 cm/s) and lack conventional navigation sensors/systems, hence the general methods of terrestrial navigation may not be applicable to these applications. While relative attitude and position can be tracked in a way similar to those for ground robots, absolute navigation information is hard to achieve on a remote celestial body, like Moon or Mars, in contrast to terrestrial applications. In this study, two absolute attitude estimation algorithms were developed and compared for accuracy and robustness. The estimated absolute attitude was fused with the relative attitude sensors in a framework of nonlinear filters. The nonlinear Extended Kalman filter (EKF) and Unscented Kalman filter (UKF) were compared in pursuit of better accuracy and reliability in this nonlinear estimation problem, using only on-board low cost MEMS sensors. Experimental results confirmed the viability of the proposed algorithms and the sensor suite, for low cost and low weight micro planetary rovers. It is demonstrated that integrating the relative and absolute navigation MEMS sensors reduces the navigation errors to the desired level.

  19. A portable respiratory rate estimation system with a passive single-lead electrocardiogram acquisition module.

    PubMed

    Nayan, Nazrul Anuar; Risman, Nur Sabrina; Jaafar, Rosmina

    2016-07-27

    Among vital signs of acutely ill hospital patients, respiratory rate (RR) is a highly accurate predictor of health deterioration. This study proposes a system that consists of a passive and non-invasive single-lead electrocardiogram (ECG) acquisition module and an ECG-derived respiratory (EDR) algorithm in the working prototype of a mobile application. Before estimating RR that produces the EDR rate, ECG signals were evaluated based on the signal quality index (SQI). The SQI algorithm was validated quantitatively using the PhysioNet/Computing in Cardiology Challenge 2011 training data set. The RR extraction algorithm was validated by adopting 40 MIT PhysioNet Multiparameter Intelligent Monitoring in Intensive Care II data set. The estimated RR showed a mean absolute error (MAE) of 1.4 compared with the ``gold standard'' RR. The proposed system was used to record 20 ECGs of healthy subjects and obtained the estimated RR with MAE of 0.7 bpm. Results indicate that the proposed hardware and algorithm could replace the manual counting method, uncomfortable nasal airflow sensor, chest band, and impedance pneumotachography often used in hospitals. The system also takes advantage of the prevalence of smartphone usage and increase the monitoring frequency of the current ECG of patients with critical illnesses.

  20. Stellar Atmospheric Parameterization Based on Deep Learning

    NASA Astrophysics Data System (ADS)

    Pan, Ru-yang; Li, Xiang-ru

    2017-07-01

    Deep learning is a typical learning method widely studied in the fields of machine learning, pattern recognition, and artificial intelligence. This work investigates the problem of stellar atmospheric parameterization by constructing a deep neural network with five layers, and the node number in each layer of the network is respectively 3821-500-100-50-1. The proposed scheme is verified on both the real spectra measured by the Sloan Digital Sky Survey (SDSS) and the theoretic spectra computed with the Kurucz's New Opacity Distribution Function (NEWODF) model, to make an automatic estimation for three physical parameters: the effective temperature (Teff), surface gravitational acceleration (lg g), and metallic abundance (Fe/H). The results show that the stacked autoencoder deep neural network has a better accuracy for the estimation. On the SDSS spectra, the mean absolute errors (MAEs) are 79.95 for Teff/K, 0.0058 for (lg Teff/K), 0.1706 for lg (g/(cm·s-2)), and 0.1294 dex for the [Fe/H], respectively; On the theoretic spectra, the MAEs are 15.34 for Teff/K, 0.0011 for lg (Teff/K), 0.0214 for lg(g/(cm · s-2)), and 0.0121 dex for [Fe/H], respectively.

  1. Evaluation of genotype-guided acenocoumarol dosing algorithms in Russian patients.

    PubMed

    Sychev, Dmitriy Alexeyevich; Rozhkov, Aleksandr Vladimirovich; Ananichuk, Anna Viktorovna; Kazakov, Ruslan Evgenyevich

    2017-05-24

    Acenocoumarol dose is normally determined via step-by-step adjustment process based on International Normalized Ratio (INR) measurements. During this time, the risk of adverse reactions is especially high. Several genotype-based acenocoumarol dosing algorithms have been created to predict ideal doses at the start of anticoagulant therapy. Nine dosing algorithms were selected through a literature search. These were evaluated using a cohort of 63 patients with atrial fibrillation receiving acenocoumarol therapy. None of the existing algorithms could predict the ideal acenocoumarol dose in 50% of Russian patients. The Wolkanin-Bartnik algorithtm based on European population was the best-performing one with the highest correlation values (r=0.397), mean absolute error (MAE) 0.82 (±0.61). EU-PACT also managed to give an estimate within the ideal range in 43% of the cases. The two least accurate results were yielded by the Indian population-based algorithms. Among patients receiving amiodarone, algorithms by Schie and Tong proved to be the most effective with the MAE of 0.48±0.42 mg/day and 0.56±0.31 mg/day, respectively. Patient ethnicity and amiodarone intake are factors that must be considered when building future algorithms. Further research is required to find the perfect dosing formula of acenocoumarol maintenance doses in Russian patients.

  2. Computational Depth of Anesthesia via Multiple Vital Signs Based on Artificial Neural Networks.

    PubMed

    Sadrawi, Muammar; Fan, Shou-Zen; Abbod, Maysam F; Jen, Kuo-Kuang; Shieh, Jiann-Shing

    2015-01-01

    This study evaluated the depth of anesthesia (DoA) index using artificial neural networks (ANN) which is performed as the modeling technique. Totally 63-patient data is addressed, for both modeling and testing of 17 and 46 patients, respectively. The empirical mode decomposition (EMD) is utilized to purify between the electroencephalography (EEG) signal and the noise. The filtered EEG signal is subsequently extracted to achieve a sample entropy index by every 5-second signal. Then, it is combined with other mean values of vital signs, that is, electromyography (EMG), heart rate (HR), pulse, systolic blood pressure (SBP), diastolic blood pressure (DBP), and signal quality index (SQI) to evaluate the DoA index as the input. The 5 doctor scores are averaged to obtain an output index. The mean absolute error (MAE) is utilized as the performance evaluation. 10-fold cross-validation is performed in order to generalize the model. The ANN model is compared with the bispectral index (BIS). The results show that the ANN is able to produce lower MAE than BIS. For the correlation coefficient, ANN also has higher value than BIS tested on the 46-patient testing data. Sensitivity analysis and cross-validation method are applied in advance. The results state that EMG has the most effecting parameter, significantly.

  3. Computational Depth of Anesthesia via Multiple Vital Signs Based on Artificial Neural Networks

    PubMed Central

    Sadrawi, Muammar; Fan, Shou-Zen; Abbod, Maysam F.; Jen, Kuo-Kuang; Shieh, Jiann-Shing

    2015-01-01

    This study evaluated the depth of anesthesia (DoA) index using artificial neural networks (ANN) which is performed as the modeling technique. Totally 63-patient data is addressed, for both modeling and testing of 17 and 46 patients, respectively. The empirical mode decomposition (EMD) is utilized to purify between the electroencephalography (EEG) signal and the noise. The filtered EEG signal is subsequently extracted to achieve a sample entropy index by every 5-second signal. Then, it is combined with other mean values of vital signs, that is, electromyography (EMG), heart rate (HR), pulse, systolic blood pressure (SBP), diastolic blood pressure (DBP), and signal quality index (SQI) to evaluate the DoA index as the input. The 5 doctor scores are averaged to obtain an output index. The mean absolute error (MAE) is utilized as the performance evaluation. 10-fold cross-validation is performed in order to generalize the model. The ANN model is compared with the bispectral index (BIS). The results show that the ANN is able to produce lower MAE than BIS. For the correlation coefficient, ANN also has higher value than BIS tested on the 46-patient testing data. Sensitivity analysis and cross-validation method are applied in advance. The results state that EMG has the most effecting parameter, significantly. PMID:26568957

  4. Instrumentation and First Results of the Reflected Solar Demonstration System for the Climate Absolute Radiance and Refractivity Observatory

    NASA Technical Reports Server (NTRS)

    McCorkel, Joel; Thome, Kurtis; Hair, Jason; McAndrew, Brendan; Jennings, Don; Rabin, Douglas; Daw, Adrian; Lundsford, Allen

    2012-01-01

    The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission key goals include enabling observation of high accuracy long-term climate change trends, use of these observations to test and improve climate forecasts, and calibration of operational and research sensors. The spaceborne instrument suites include a reflected solar spectroradiometer, emitted infrared spectroradiometer, and radio occultation receivers. The requirement for the RS instrument is that derived reflectance must be traceable to Sl standards with an absolute uncertainty of <0.3% and the error budget that achieves this requirement is described in previo1L5 work. This work describes the Solar/Lunar Absolute Reflectance Imaging Spectroradiometer (SOLARIS), a calibration demonstration system for RS instrument, and presents initial calibration and characterization methods and results. SOLARIS is an Offner spectrometer with two separate focal planes each with its own entrance aperture and grating covering spectral ranges of 320-640, 600-2300 nm over a full field-of-view of 10 degrees with 0.27 milliradian sampling. Results from laboratory measurements including use of integrating spheres, transfer radiometers and spectral standards combined with field-based solar and lunar acquisitions are presented. These results will be used to assess the accuracy and repeatability of the radiometric and spectral characteristics of SOLARIS, which will be presented against the sensor-level requirements addressed in the CLARREO RS instrument error budget.

  5. Absolute Timing of the Crab Pulsar with RXTE

    NASA Technical Reports Server (NTRS)

    Rots, Arnold H.; Jahoda, Keith; Lyne, Andrew G.

    2004-01-01

    We have monitored the phase of the main X-ray pulse of the Crab pulsar with the Rossi X-ray Timing Explorer (RXTE) for almost eight years, since the start of the mission in January 1996. The absolute time of RXTE's clock is sufficiently accurate to allow this phase to be compared directly with the radio profile. Our monitoring observations of the pulsar took place bi-weekly (during the periods when it was at least 30 degrees from the Sun) and we correlated the data with radio timing ephemerides derived from observations made at Jodrell Bank. We have determined the phase of the X-ray main pulse for each observation with a typical error in the individual data points of 50 microseconds. The total ensemble is consistent with a phase that is constant over the monitoring period, with the X-ray pulse leading the radio pulse by 0.01025 plus or minus 0.00120 period in phase, or 344 plus or minus 40 microseconds in time. The error estimate is dominated by a systematic error of 40 microseconds, most likely constant, arising from uncertainties in the instrumental calibration of the radio data. The statistical error is 0.00015 period, or 5 microseconds. The separation of the main pulse and interpulse appears to be unchanging at time scales of a year or less, with an average value of 0.4001 plus or minus 0.0002 period. There is no apparent variation in these values with energy over the 2-30 keV range. The lag between the radio and X-ray pulses ma be constant in phase (i.e., rotational in nature) or constant in time (i.e., due to a pathlength difference). We are not (yet) able to distinguish between these two interpretations.

  6. Comparative Time Series Analysis of Aerosol Optical Depth over Sites in United States and China Using ARIMA Modeling

    NASA Astrophysics Data System (ADS)

    Li, X.; Zhang, C.; Li, W.

    2017-12-01

    Long-term spatiotemporal analysis and modeling of aerosol optical depth (AOD) distribution is of paramount importance to study radiative forcing, climate change, and human health. This study is focused on the trends and variations of AOD over six stations located in United States and China during 2003 to 2015, using satellite-retrieved Moderate Resolution Imaging Spectrometer (MODIS) Collection 6 retrievals and ground measurements derived from Aerosol Robotic NETwork (AERONET). An autoregressive integrated moving average (ARIMA) model is applied to simulate and predict AOD values. The R2, adjusted R2, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Bayesian Information Criterion (BIC) are used as indices to select the best fitted model. Results show that there is a persistent decreasing trend in AOD for both MODIS data and AERONET data over three stations. Monthly and seasonal AOD variations reveal consistent aerosol patterns over stations along mid-latitudes. Regional differences impacted by climatology and land cover types are observed for the selected stations. Statistical validation of time series models indicates that the non-seasonal ARIMA model performs better for AERONET AOD data than for MODIS AOD data over most stations, suggesting the method works better for data with higher quality. By contrast, the seasonal ARIMA model reproduces the seasonal variations of MODIS AOD data much more precisely. Overall, the reasonably predicted results indicate the applicability and feasibility of the stochastic ARIMA modeling technique to forecast future and missing AOD values.

  7. Mapping health outcome measures from a stroke registry to EQ-5D weights

    PubMed Central

    2013-01-01

    Purpose To map health outcome related variables from a national register, not part of any validated instrument, with EQ-5D weights among stroke patients. Methods We used two cross-sectional data sets including patient characteristics, outcome variables and EQ-5D weights from the national Swedish stroke register. Three regression techniques were used on the estimation set (n = 272): ordinary least squares (OLS), Tobit, and censored least absolute deviation (CLAD). The regression coefficients for “dressing“, “toileting“, “mobility”, “mood”, “general health” and “proxy-responders” were applied to the validation set (n = 272), and the performance was analysed with mean absolute error (MAE) and mean square error (MSE). Results The number of statistically significant coefficients varied by model, but all models generated consistent coefficients in terms of sign. Mean utility was underestimated in all models (least in OLS) and with lower variation (least in OLS) compared to the observed. The maximum attainable EQ-5D weight ranged from 0.90 (OLS) to 1.00 (Tobit and CLAD). Health states with utility weights <0.5 had greater errors than those with weights ≥0.5 (P < 0.01). Conclusion This study indicates that it is possible to map non-validated health outcome measures from a stroke register into preference-based utilities to study the development of stroke care over time, and to compare with other conditions in terms of utility. PMID:23496957

  8. 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.

  9. Parameter Optimisation and Uncertainty Analysis in Visual MODFLOW based Flow Model for predicting the groundwater head in an Eastern Indian Aquifer

    NASA Astrophysics Data System (ADS)

    Mohanty, B.; Jena, S.; Panda, R. K.

    2016-12-01

    The overexploitation of groundwater elicited in abandoning several shallow tube wells in the study Basin in Eastern India. For the sustainability of groundwater resources, basin-scale modelling of groundwater flow is indispensable for the effective planning and management of the water resources. The basic intent of this study is to develop a 3-D groundwater flow model of the study basin using the Visual MODFLOW Flex 2014.2 package and successfully calibrate and validate the model using 17 years of observed data. The sensitivity analysis was carried out to quantify the susceptibility of aquifer system to the river bank seepage, recharge from rainfall and agriculture practices, horizontal and vertical hydraulic conductivities, and specific yield. To quantify the impact of parameter uncertainties, Sequential Uncertainty Fitting Algorithm (SUFI-2) and Markov chain Monte Carlo (McMC) techniques were implemented. Results from the two techniques were compared and the advantages and disadvantages were analysed. Nash-Sutcliffe coefficient (NSE), Coefficient of Determination (R2), Mean Absolute Error (MAE), Mean Percent Deviation (Dv) and Root Mean Squared Error (RMSE) were adopted as criteria of model evaluation during calibration and validation of the developed model. NSE, R2, MAE, Dv and RMSE values for groundwater flow model during calibration and validation were in acceptable range. Also, the McMC technique was able to provide more reasonable results than SUFI-2. The calibrated and validated model will be useful to identify the aquifer properties, analyse the groundwater flow dynamics and the change in groundwater levels in future forecasts.

  10. Alternatives to accuracy and bias metrics based on percentage errors for radiation belt modeling applications

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Morley, Steven Karl

    This report reviews existing literature describing forecast accuracy metrics, concentrating on those based on relative errors and percentage errors. We then review how the most common of these metrics, the mean absolute percentage error (MAPE), has been applied in recent radiation belt modeling literature. Finally, we describe metrics based on the ratios of predicted to observed values (the accuracy ratio) that address the drawbacks inherent in using MAPE. Specifically, we define and recommend the median log accuracy ratio as a measure of bias and the median symmetric accuracy as a measure of accuracy.

  11. Estimating the absolute wealth of households.

    PubMed

    Hruschka, Daniel J; Gerkey, Drew; Hadley, Craig

    2015-07-01

    To estimate the absolute wealth of households using data from demographic and health surveys. We developed a new metric, the absolute wealth estimate, based on the rank of each surveyed household according to its material assets and the assumed shape of the distribution of wealth among surveyed households. Using data from 156 demographic and health surveys in 66 countries, we calculated absolute wealth estimates for households. We validated the method by comparing the proportion of households defined as poor using our estimates with published World Bank poverty headcounts. We also compared the accuracy of absolute versus relative wealth estimates for the prediction of anthropometric measures. The median absolute wealth estimates of 1,403,186 households were 2056 international dollars per capita (interquartile range: 723-6103). The proportion of poor households based on absolute wealth estimates were strongly correlated with World Bank estimates of populations living on less than 2.00 United States dollars per capita per day (R(2)  = 0.84). Absolute wealth estimates were better predictors of anthropometric measures than relative wealth indexes. Absolute wealth estimates provide new opportunities for comparative research to assess the effects of economic resources on health and human capital, as well as the long-term health consequences of economic change and inequality.

  12. A Sensor Dynamic Measurement Error Prediction Model Based on NAPSO-SVM.

    PubMed

    Jiang, Minlan; Jiang, Lan; Jiang, Dingde; Li, Fei; Song, Houbing

    2018-01-15

    Dynamic measurement error correction is an effective way to improve sensor precision. Dynamic measurement error prediction is an important part of error correction, and support vector machine (SVM) is often used for predicting the dynamic measurement errors of sensors. Traditionally, the SVM parameters were always set manually, which cannot ensure the model's performance. In this paper, a SVM method based on an improved particle swarm optimization (NAPSO) is proposed to predict the dynamic measurement errors of sensors. Natural selection and simulated annealing are added in the PSO to raise the ability to avoid local optima. To verify the performance of NAPSO-SVM, three types of algorithms are selected to optimize the SVM's parameters: the particle swarm optimization algorithm (PSO), the improved PSO optimization algorithm (NAPSO), and the glowworm swarm optimization (GSO). The dynamic measurement error data of two sensors are applied as the test data. The root mean squared error and mean absolute percentage error are employed to evaluate the prediction models' performances. The experimental results show that among the three tested algorithms the NAPSO-SVM method has a better prediction precision and a less prediction errors, and it is an effective method for predicting the dynamic measurement errors of sensors.

  13. A Sensor Dynamic Measurement Error Prediction Model Based on NAPSO-SVM

    PubMed Central

    Jiang, Minlan; Jiang, Lan; Jiang, Dingde; Li, Fei

    2018-01-01

    Dynamic measurement error correction is an effective way to improve sensor precision. Dynamic measurement error prediction is an important part of error correction, and support vector machine (SVM) is often used for predicting the dynamic measurement errors of sensors. Traditionally, the SVM parameters were always set manually, which cannot ensure the model’s performance. In this paper, a SVM method based on an improved particle swarm optimization (NAPSO) is proposed to predict the dynamic measurement errors of sensors. Natural selection and simulated annealing are added in the PSO to raise the ability to avoid local optima. To verify the performance of NAPSO-SVM, three types of algorithms are selected to optimize the SVM’s parameters: the particle swarm optimization algorithm (PSO), the improved PSO optimization algorithm (NAPSO), and the glowworm swarm optimization (GSO). The dynamic measurement error data of two sensors are applied as the test data. The root mean squared error and mean absolute percentage error are employed to evaluate the prediction models’ performances. The experimental results show that among the three tested algorithms the NAPSO-SVM method has a better prediction precision and a less prediction errors, and it is an effective method for predicting the dynamic measurement errors of sensors. PMID:29342942

  14. Predicting active-layer soil thickness using topographic variables at a small watershed scale

    PubMed Central

    Li, Aidi; Tan, Xing; Wu, Wei; Liu, Hongbin; Zhu, Jie

    2017-01-01

    Knowledge about the spatial distribution of active-layer (AL) soil thickness is indispensable for ecological modeling, precision agriculture, and land resource management. However, it is difficult to obtain the details on AL soil thickness by using conventional soil survey method. In this research, the objective is to investigate the possibility and accuracy of mapping the spatial distribution of AL soil thickness through random forest (RF) model by using terrain variables at a small watershed scale. A total of 1113 soil samples collected from the slope fields were randomly divided into calibration (770 soil samples) and validation (343 soil samples) sets. Seven terrain variables including elevation, aspect, relative slope position, valley depth, flow path length, slope height, and topographic wetness index were derived from a digital elevation map (30 m). The RF model was compared with multiple linear regression (MLR), geographically weighted regression (GWR) and support vector machines (SVM) approaches based on the validation set. Model performance was evaluated by precision criteria of mean error (ME), mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). Comparative results showed that RF outperformed MLR, GWR and SVM models. The RF gave better values of ME (0.39 cm), MAE (7.09 cm), and RMSE (10.85 cm) and higher R2 (62%). The sensitivity analysis demonstrated that the DEM had less uncertainty than the AL soil thickness. The outcome of the RF model indicated that elevation, flow path length and valley depth were the most important factors affecting the AL soil thickness variability across the watershed. These results demonstrated the RF model is a promising method for predicting spatial distribution of AL soil thickness using terrain parameters. PMID:28877196

  15. Population pharmacokinetics modeling of oxcarbazepine to characterize drug interactions in Chinese children with epilepsy

    PubMed Central

    Wang, Yang; Zhang, Hua-nian; Niu, Chang-he; Gao, Ping; Chen, Yu-jun; Peng, Jing; Liu, Mao-chang; Xu, Hua

    2014-01-01

    Aim: To develop a population pharmacokinetics model of oxcarbazepine in Chinese pediatric patients with epilepsy, and to study the interactions between oxcarbazepine and other antiepileptic drugs (AEDs). Methods: A total of 688 patients with epilepsy aged 2 months to 18 years were divided into model (n=573) and valid (n=115) groups. Serum concentrations of the main active metabolite of oxcarbazepine, 10-hydroxycarbazepine (MHD), were determined 0.5–48 h after the last dosage. A population pharmacokinetics (PPK) model was constructed using NLME software. This model was internally evaluated using Bootstrapping and goodness-of-fit plots inspection. The data of the valid group were used to calculate the mean prediction error (MPE), mean absolute prediction error (MAE), mean squared prediction error (MSE) and the 95% confidence intervals (95% CI) to externally evaluate the model. Results: The population values of pharmacokinetic parameters estimated in the final model were as follows: Ka=0.83 h-1, Vd=0.67 L/kg, and CL=0.035 L·kg−1·h−1. The enzyme-inducing AEDs (carbamazepine, phenytoin, phenobarbital) and newer generation AEDs (levetiracetam, lamotrigine, topiramate) increased the weight-normalized CL value of MHD by 17.4% and 10.5%, respectively, whereas the enzyme-inhibiting AED valproic acid decreased it by 3%. No significant association was found between the CL value of MHD and the other covariates. For the final model, the evaluation results (95% CI) were MPE=0.01 (−0.07–0.10) mg/L, MAE=0.46 (0.40–0.51) mg/L, MSE=0.39 (0.27–0.51) (mg/L)2. Conclusion: A PPK model of OXC in Chinese pediatric patients with epilepsy is established. The enzyme-inducing AEDs and some newer generation AEDs (lamotrigine, topiramate) could slightly increase the metabolism of MHD. PMID:25220641

  16. The statistical properties and possible causes of polar motion prediction errors

    NASA Astrophysics Data System (ADS)

    Kosek, Wieslaw; Kalarus, Maciej; Wnek, Agnieszka; Zbylut-Gorska, Maria

    2015-08-01

    The pole coordinate data predictions from different prediction contributors of the Earth Orientation Parameters Combination of Prediction Pilot Project (EOPCPPP) were studied to determine the statistical properties of polar motion forecasts by looking at the time series of differences between them and the future IERS pole coordinates data. The mean absolute errors, standard deviations as well as the skewness and kurtosis of these differences were computed together with their error bars as a function of prediction length. The ensemble predictions show a little smaller mean absolute errors or standard deviations however their skewness and kurtosis values are similar as the for predictions from different contributors. The skewness and kurtosis enable to check whether these prediction differences satisfy normal distribution. The kurtosis values diminish with the prediction length which means that the probability distribution of these prediction differences is becoming more platykurtic than letptokurtic. Non zero skewness values result from oscillating character of these differences for particular prediction lengths which can be due to the irregular change of the annual oscillation phase in the joint fluid (atmospheric + ocean + land hydrology) excitation functions. The variations of the annual oscillation phase computed by the combination of the Fourier transform band pass filter and the Hilbert transform from pole coordinates data as well as from pole coordinates model data obtained from fluid excitations are in a good agreement.

  17. Stepped-wedge cluster randomised controlled trial to assess the effectiveness of an electronic medication management system to reduce medication errors, adverse drug events and average length of stay at two paediatric hospitals: a study protocol

    PubMed Central

    Westbrook, J I; Li, L; Raban, M Z; Baysari, M T; Prgomet, M; Georgiou, A; Kim, T; Lake, R; McCullagh, C; Dalla-Pozza, L; Karnon, J; O'Brien, T A; Ambler, G; Day, R; Cowell, C T; Gazarian, M; Worthington, R; Lehmann, C U; White, L; Barbaric, D; Gardo, A; Kelly, M; Kennedy, P

    2016-01-01

    Introduction Medication errors are the most frequent cause of preventable harm in hospitals. Medication management in paediatric patients is particularly complex and consequently potential for harms are greater than in adults. Electronic medication management (eMM) systems are heralded as a highly effective intervention to reduce adverse drug events (ADEs), yet internationally evidence of their effectiveness in paediatric populations is limited. This study will assess the effectiveness of an eMM system to reduce medication errors, ADEs and length of stay (LOS). The study will also investigate system impact on clinical work processes. Methods and analysis A stepped-wedge cluster randomised controlled trial (SWCRCT) will measure changes pre-eMM and post-eMM system implementation in prescribing and medication administration error (MAE) rates, potential and actual ADEs, and average LOS. In stage 1, 8 wards within the first paediatric hospital will be randomised to receive the eMM system 1 week apart. In stage 2, the second paediatric hospital will randomise implementation of a modified eMM and outcomes will be assessed. Prescribing errors will be identified through record reviews, and MAEs through direct observation of nurses and record reviews. Actual and potential severity will be assigned. Outcomes will be assessed at the patient-level using mixed models, taking into account correlation of admissions within wards and multiple admissions for the same patient, with adjustment for potential confounders. Interviews and direct observation of clinicians will investigate the effects of the system on workflow. Data from site 1 will be used to develop improvements in the eMM and implemented at site 2, where the SWCRCT design will be repeated (stage 2). Ethics and dissemination The research has been approved by the Human Research Ethics Committee of the Sydney Children's Hospitals Network and Macquarie University. Results will be reported through academic journals and

  18. Stepped-wedge cluster randomised controlled trial to assess the effectiveness of an electronic medication management system to reduce medication errors, adverse drug events and average length of stay at two paediatric hospitals: a study protocol.

    PubMed

    Westbrook, J I; Li, L; Raban, M Z; Baysari, M T; Mumford, V; Prgomet, M; Georgiou, A; Kim, T; Lake, R; McCullagh, C; Dalla-Pozza, L; Karnon, J; O'Brien, T A; Ambler, G; Day, R; Cowell, C T; Gazarian, M; Worthington, R; Lehmann, C U; White, L; Barbaric, D; Gardo, A; Kelly, M; Kennedy, P

    2016-10-21

    Medication errors are the most frequent cause of preventable harm in hospitals. Medication management in paediatric patients is particularly complex and consequently potential for harms are greater than in adults. Electronic medication management (eMM) systems are heralded as a highly effective intervention to reduce adverse drug events (ADEs), yet internationally evidence of their effectiveness in paediatric populations is limited. This study will assess the effectiveness of an eMM system to reduce medication errors, ADEs and length of stay (LOS). The study will also investigate system impact on clinical work processes. A stepped-wedge cluster randomised controlled trial (SWCRCT) will measure changes pre-eMM and post-eMM system implementation in prescribing and medication administration error (MAE) rates, potential and actual ADEs, and average LOS. In stage 1, 8 wards within the first paediatric hospital will be randomised to receive the eMM system 1 week apart. In stage 2, the second paediatric hospital will randomise implementation of a modified eMM and outcomes will be assessed. Prescribing errors will be identified through record reviews, and MAEs through direct observation of nurses and record reviews. Actual and potential severity will be assigned. Outcomes will be assessed at the patient-level using mixed models, taking into account correlation of admissions within wards and multiple admissions for the same patient, with adjustment for potential confounders. Interviews and direct observation of clinicians will investigate the effects of the system on workflow. Data from site 1 will be used to develop improvements in the eMM and implemented at site 2, where the SWCRCT design will be repeated (stage 2). The research has been approved by the Human Research Ethics Committee of the Sydney Children's Hospitals Network and Macquarie University. Results will be reported through academic journals and seminar and conference presentations. Australian New Zealand

  19. Estimating the absolute wealth of households

    PubMed Central

    Gerkey, Drew; Hadley, Craig

    2015-01-01

    Abstract Objective To estimate the absolute wealth of households using data from demographic and health surveys. Methods We developed a new metric, the absolute wealth estimate, based on the rank of each surveyed household according to its material assets and the assumed shape of the distribution of wealth among surveyed households. Using data from 156 demographic and health surveys in 66 countries, we calculated absolute wealth estimates for households. We validated the method by comparing the proportion of households defined as poor using our estimates with published World Bank poverty headcounts. We also compared the accuracy of absolute versus relative wealth estimates for the prediction of anthropometric measures. Findings The median absolute wealth estimates of 1 403 186 households were 2056 international dollars per capita (interquartile range: 723–6103). The proportion of poor households based on absolute wealth estimates were strongly correlated with World Bank estimates of populations living on less than 2.00 United States dollars per capita per day (R2 = 0.84). Absolute wealth estimates were better predictors of anthropometric measures than relative wealth indexes. Conclusion Absolute wealth estimates provide new opportunities for comparative research to assess the effects of economic resources on health and human capital, as well as the long-term health consequences of economic change and inequality. PMID:26170506

  20. Test Plan for a Calibration Demonstration System for the Reflected Solar Instrument for the Climate Absolute Radiance and Refractivity Observatory

    NASA Technical Reports Server (NTRS)

    Thome, Kurtis; McCorkel, Joel; Hair, Jason; McAndrew, Brendan; Daw, Adrian; Jennings, Donald; Rabin, Douglas

    2012-01-01

    The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe high-accuracy, long-term climate change trends and to use decadal change observations as the most critical method to determine the accuracy of climate change. One of the major objectives of CLARREO is to advance the accuracy of SI traceable absolute calibration at infrared and reflected solar wavelengths. This advance is required to reach the on-orbit absolute accuracy required to allow climate change observations to survive data gaps while remaining sufficiently accurate to observe climate change to within the uncertainty of the limit of natural variability. While these capabilities exist at NIST in the laboratory, there is a need to demonstrate that it can move successfully from NIST to NASA and/or instrument vendor capabilities for future spaceborne instruments. The current work describes the test plan for the Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer (SOLARIS) which is the calibration demonstration system (CDS) for the reflected solar portion of CLARREO. The goal of the CDS is to allow the testing and evaluation of calibration approaches , alternate design and/or implementation approaches and components for the CLARREO mission. SOLARIS also provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. The end result of efforts with the SOLARIS CDS will be an SI-traceable error budget for reflectance retrieval using solar irradiance as a reference and methods for laboratory-based, absolute calibration suitable for climate-quality data collections. The CLARREO mission addresses the need to observe high-accuracy, long-term climate change trends and advance the accuracy of SI traceable absolute calibration. The current work describes the test plan for the SOLARIS which is the calibration demonstration

  1. Applying airline safety practices to medication administration.

    PubMed

    Pape, Theresa M

    2003-04-01

    Medication administration errors (MAE) continue as major problems for health care institutions, nurses, and patients. However, MAEs are often the result of system failures leading to patient injury, increased hospital costs, and blaming. Costs include those related to increased hospital length of stay and legal expenses. Contributing factors include distractions, lack of focus, poor communication, and failure to follow standard protocols during medication administration.

  2. Tinker-OpenMM: Absolute and relative alchemical free energies using AMOEBA on GPUs.

    PubMed

    Harger, Matthew; Li, Daniel; Wang, Zhi; Dalby, Kevin; Lagardère, Louis; Piquemal, Jean-Philip; Ponder, Jay; Ren, Pengyu

    2017-09-05

    The capabilities of the polarizable force fields for alchemical free energy calculations have been limited by the high computational cost and complexity of the underlying potential energy functions. In this work, we present a GPU-based general alchemical free energy simulation platform for polarizable potential AMOEBA. Tinker-OpenMM, the OpenMM implementation of the AMOEBA simulation engine has been modified to enable both absolute and relative alchemical simulations on GPUs, which leads to a ∼200-fold improvement in simulation speed over a single CPU core. We show that free energy values calculated using this platform agree with the results of Tinker simulations for the hydration of organic compounds and binding of host-guest systems within the statistical errors. In addition to absolute binding, we designed a relative alchemical approach for computing relative binding affinities of ligands to the same host, where a special path was applied to avoid numerical instability due to polarization between the different ligands that bind to the same site. This scheme is general and does not require ligands to have similar scaffolds. We show that relative hydration and binding free energy calculated using this approach match those computed from the absolute free energy approach. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  3. Improving the Glucose Meter Error Grid With the Taguchi Loss Function.

    PubMed

    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.

  4. Incorporating Measurement Error from Modeled Air Pollution Exposures into Epidemiological Analyses.

    PubMed

    Samoli, Evangelia; Butland, Barbara K

    2017-12-01

    Outdoor air pollution exposures used in epidemiological studies are commonly predicted from spatiotemporal models incorporating limited measurements, temporal factors, geographic information system variables, and/or satellite data. Measurement error in these exposure estimates leads to imprecise estimation of health effects and their standard errors. We reviewed methods for measurement error correction that have been applied in epidemiological studies that use model-derived air pollution data. We identified seven cohort studies and one panel study that have employed measurement error correction methods. These methods included regression calibration, risk set regression calibration, regression calibration with instrumental variables, the simulation extrapolation approach (SIMEX), and methods under the non-parametric or parameter bootstrap. Corrections resulted in small increases in the absolute magnitude of the health effect estimate and its standard error under most scenarios. Limited application of measurement error correction methods in air pollution studies may be attributed to the absence of exposure validation data and the methodological complexity of the proposed methods. Future epidemiological studies should consider in their design phase the requirements for the measurement error correction method to be later applied, while methodological advances are needed under the multi-pollutants setting.

  5. 20 CFR 404.1205 - Absolute coverage groups.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 20 Employees' Benefits 2 2011-04-01 2011-04-01 false Absolute coverage groups. 404.1205 Section... Covered § 404.1205 Absolute coverage groups. (a) General. An absolute coverage group is a permanent... are not under a retirement system. An absolute coverage group may include positions which were...

  6. Optimal Design of the Absolute Positioning Sensor for a High-Speed Maglev Train and Research on Its Fault Diagnosis

    PubMed Central

    Zhang, Dapeng; Long, Zhiqiang; Xue, Song; Zhang, Junge

    2012-01-01

    This paper studies an absolute positioning sensor for a high-speed maglev train and its fault diagnosis method. The absolute positioning sensor is an important sensor for the high-speed maglev train to accomplish its synchronous traction. It is used to calibrate the error of the relative positioning sensor which is used to provide the magnetic phase signal. On the basis of the analysis for the principle of the absolute positioning sensor, the paper describes the design of the sending and receiving coils and realizes the hardware and the software for the sensor. In order to enhance the reliability of the sensor, a support vector machine is used to recognize the fault characters, and the signal flow method is used to locate the faulty parts. The diagnosis information not only can be sent to an upper center control computer to evaluate the reliability of the sensors, but also can realize on-line diagnosis for debugging and the quick detection when the maglev train is off-line. The absolute positioning sensor we study has been used in the actual project. PMID:23112619

  7. Optimal design of the absolute positioning sensor for a high-speed maglev train and research on its fault diagnosis.

    PubMed

    Zhang, Dapeng; Long, Zhiqiang; Xue, Song; Zhang, Junge

    2012-01-01

    This paper studies an absolute positioning sensor for a high-speed maglev train and its fault diagnosis method. The absolute positioning sensor is an important sensor for the high-speed maglev train to accomplish its synchronous traction. It is used to calibrate the error of the relative positioning sensor which is used to provide the magnetic phase signal. On the basis of the analysis for the principle of the absolute positioning sensor, the paper describes the design of the sending and receiving coils and realizes the hardware and the software for the sensor. In order to enhance the reliability of the sensor, a support vector machine is used to recognize the fault characters, and the signal flow method is used to locate the faulty parts. The diagnosis information not only can be sent to an upper center control computer to evaluate the reliability of the sensors, but also can realize on-line diagnosis for debugging and the quick detection when the maglev train is off-line. The absolute positioning sensor we study has been used in the actual project.

  8. Is adult gait less susceptible than paediatric gait to hip joint centre regression equation error?

    PubMed

    Kiernan, D; Hosking, J; O'Brien, T

    2016-03-01

    Hip joint centre (HJC) regression equation error during paediatric gait has recently been shown to have clinical significance. In relation to adult gait, it has been inferred that comparable errors with children in absolute HJC position may in fact result in less significant kinematic and kinetic error. This study investigated the clinical agreement of three commonly used regression equation sets (Bell et al., Davis et al. and Orthotrak) for adult subjects against the equations of Harrington et al. The relationship between HJC position error and subject size was also investigated for the Davis et al. set. Full 3-dimensional gait analysis was performed on 12 healthy adult subjects with data for each set compared to Harrington et al. The Gait Profile Score, Gait Variable Score and GDI-kinetic were used to assess clinical significance while differences in HJC position between the Davis and Harrington sets were compared to leg length and subject height using regression analysis. A number of statistically significant differences were present in absolute HJC position. However, all sets fell below the clinically significant thresholds (GPS <1.6°, GDI-Kinetic <3.6 points). Linear regression revealed a statistically significant relationship for both increasing leg length and increasing subject height with decreasing error in anterior/posterior and superior/inferior directions. Results confirm a negligible clinical error for adult subjects suggesting that any of the examined sets could be used interchangeably. Decreasing error with both increasing leg length and increasing subject height suggests that the Davis set should be used cautiously on smaller subjects. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Evaluation of Voice Acoustics as Predictors of Clinical Depression Scores.

    PubMed

    Hashim, Nik Wahidah; Wilkes, Mitch; Salomon, Ronald; Meggs, Jared; France, Daniel J

    2017-03-01

    The aim of the present study was to determine if acoustic measures of voice, characterizing specific spectral and timing properties, predict clinical ratings of depression severity measured in a sample of patients using the Hamilton Depression Rating Scale (HAMD) and Beck Depression Inventory (BDI-II). This is a prospective study. Voice samples and clinical depression scores were collected prospectively from consenting adult patients who were referred to psychiatry from the adult emergency department or primary care clinics. The patients were audio-recorded as they read a standardized passage in a nearly closed-room environment. Mean Absolute Error (MAE) between actual and predicted depression scores was used as the primary outcome measure. The average MAE between predicted and actual HAMD scores was approximately two scores for both men and women, and the MAE for the BDI-II scores was approximately one score for men and eight scores for women. Timing features were predictive of HAMD scores in female patients while a combination of timing features and spectral features was predictive of scores in male patients. Timing features were predictive of BDI-II scores in male patients. Voice acoustic features extracted from read speech demonstrated variable effectiveness in predicting clinical depression scores in men and women. Voice features were highly predictive of HAMD scores in men and women, and BDI-II scores in men, respectively. The methodology is feasible for diagnostic applications in diverse clinical settings as it can be implemented during a standard clinical interview in a normal closed room and without strict control on the recording environment. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

  10. Forecasting Emergency Department Crowding: An External, Multi-Center Evaluation

    PubMed Central

    Hoot, Nathan R.; Epstein, Stephen K.; Allen, Todd L.; Jones, Spencer S.; Baumlin, Kevin M.; Chawla, Neal; Lee, Anna T.; Pines, Jesse M.; Klair, Amandeep K.; Gordon, Bradley D.; Flottemesch, Thomas J.; LeBlanc, Larry J.; Jones, Ian; Levin, Scott R.; Zhou, Chuan; Gadd, Cynthia S.; Aronsky, Dominik

    2009-01-01

    Objective To apply a previously described tool to forecast ED crowding at multiple institutions, and to assess its generalizability for predicting the near-future waiting count, occupancy level, and boarding count. Methods The ForecastED tool was validated using historical data from five institutions external to the development site. A sliding-window design separated the data for parameter estimation and forecast validation. Observations were sampled at consecutive 10-minute intervals during 12 months (n = 52,560) at four sites and 10 months (n = 44,064) at the fifth. Three outcome measures – the waiting count, occupancy level, and boarding count – were forecast 2, 4, 6, and 8 hours beyond each observation, and forecasts were compared to observed data at corresponding times. The reliability and calibration were measured following previously described methods. After linear calibration, the forecasting accuracy was measured using the median absolute error (MAE). Results The tool was successfully used for five different sites. Its forecasts were more reliable, better calibrated, and more accurate at 2 hours than at 8 hours. The reliability and calibration of the tool were similar between the original development site and external sites; the boarding count was an exception, which was less reliable at four out of five sites. Some variability in accuracy existed among institutions; when forecasting 4 hours into the future, the MAE of the waiting count ranged between 0.6 and 3.1 patients, the MAE of the occupancy level ranged between 9.0 and 14.5% of beds, and the MAE of the boarding count ranged between 0.9 and 2.7 patients. Conclusion The ForecastED tool generated potentially useful forecasts of input and throughput measures of ED crowding at five external sites, without modifying the underlying assumptions. Noting the limitation that this was not a real-time validation, ongoing research will focus on integrating the tool with ED information systems. PMID:19716629

  11. Groundwater recharge estimation in semi-arid zone: a study case from the region of Djelfa (Algeria)

    NASA Astrophysics Data System (ADS)

    Ali Rahmani, S. E.; Chibane, Brahim; Boucefiène, Abdelkader

    2017-09-01

    Deficiency of surface water resources in semi-arid area makes the groundwater the most preferred resource to assure population increased needs. In this research we are going to quantify the rate of groundwater recharge using new hybrid model tack in interest the annual rainfall and the average annual temperature and the geological characteristics of the area. This hybrid model was tested and calibrated using a chemical tracer method called Chloride mass balance method (CMB). This hybrid model is a combination between general hydrogeological model and a hydrological model. We have tested this model in an aquifer complex in the region of Djelfa (Algeria). Performance of this model was verified by five criteria [Nash, mean absolute error (MAE), Root mean square error (RMSE), the coefficient of determination and the arithmetic mean error (AME)]. These new approximations facilitate the groundwater management in semi-arid areas; this model is a perfection and amelioration of the model developed by Chibane et al. This model gives a very interesting result, with low uncertainty. A new recharge class diagram was established by our model to get rapidly and quickly the groundwater recharge value for any area in semi-arid region, using temperature and rainfall.

  12. The importance of intra-hospital pharmacovigilance in the detection of medication errors

    PubMed

    Villegas, Francisco; Figueroa-Montero, David; Barbero-Becerra, Varenka; Juárez-Hernández, Eva; Uribe, Misael; Chávez-Tapia, Norberto; González-Chon, Octavio

    2018-01-01

    Hospitalized patients are susceptible to medication errors, which represent between the fourth and the sixth cause of death. The department of intra-hospital pharmacovigilance intervenes in the entire process of medication with the purpose to prevent, repair and assess damages. To analyze medication errors reported by Mexican Fundación Clínica Médica Sur pharmacovigilance system and their impact on patients. Prospective study carried out from 2012 to 2015, where medication prescriptions given to patients were recorded. Owing to heterogeneity, data were described as absolute numbers in a logarithmic scale. 292 932 prescriptions of 56 368 patients were analyzed, and 8.9% of medication errors were identified. The treating physician was responsible of 83.32% of medication errors, residents of 6.71% and interns of 0.09%. No error caused permanent damage or death. This is the pharmacovigilance study with the largest sample size reported. Copyright: © 2018 SecretarÍa de Salud.

  13. A rack-mounted precision waveguide-below-cutoff attenuator with an absolute electronic readout

    NASA Technical Reports Server (NTRS)

    Cook, C. C.

    1974-01-01

    A coaxial precision waveguide-below-cutoff attenuator is described which uses an absolute (unambiguous) electronic digital readout of displacement in inches in addition to the usual gear driven mechanical counter-dial readout in decibels. The attenuator is rack-mountable and has the input and output RF connectors in a fixed position. The attenuation rate for 55, 50, and 30 MHz operation is given along with a discussion of sources of errors. In addition, information is included to aid the user in making adjustments on the attenuator should it be damaged or disassembled for any reason.

  14. Prescription errors before and after introduction of electronic medication alert system in a pediatric emergency department.

    PubMed

    Sethuraman, Usha; Kannikeswaran, Nirupama; Murray, Kyle P; Zidan, Marwan A; Chamberlain, James M

    2015-06-01

    Prescription errors occur frequently in pediatric emergency departments (PEDs).The effect of computerized physician order entry (CPOE) with electronic medication alert system (EMAS) on these is unknown. The objective was to compare prescription errors rates before and after introduction of CPOE with EMAS in a PED. The hypothesis was that CPOE with EMAS would significantly reduce the rate and severity of prescription errors in the PED. A prospective comparison of a sample of outpatient, medication prescriptions 5 months before and after CPOE with EMAS implementation (7,268 before and 7,292 after) was performed. Error types and rates, alert types and significance, and physician response were noted. Medication errors were deemed significant if there was a potential to cause life-threatening injury, failure of therapy, or an adverse drug effect. There was a significant reduction in the errors per 100 prescriptions (10.4 before vs. 7.3 after; absolute risk reduction = 3.1, 95% confidence interval [CI] = 2.2 to 4.0). Drug dosing error rates decreased from 8 to 5.4 per 100 (absolute risk reduction = 2.6, 95% CI = 1.8 to 3.4). Alerts were generated for 29.6% of prescriptions, with 45% involving drug dose range checking. The sensitivity of CPOE with EMAS in identifying errors in prescriptions was 45.1% (95% CI = 40.8% to 49.6%), and the specificity was 57% (95% CI = 55.6% to 58.5%). Prescribers modified 20% of the dosing alerts, resulting in the error not reaching the patient. Conversely, 11% of true dosing alerts for medication errors were overridden by the prescribers: 88 (11.3%) resulted in medication errors, and 684 (88.6%) were false-positive alerts. A CPOE with EMAS was associated with a decrease in overall prescription errors in our PED. Further system refinements are required to reduce the high false-positive alert rates. © 2015 by the Society for Academic Emergency Medicine.

  15. Absolute plate motions relative to deep mantle plumes

    NASA Astrophysics Data System (ADS)

    Wang, Shimin; Yu, Hongzheng; Zhang, Qiong; Zhao, Yonghong

    2018-05-01

    Advances in whole waveform seismic tomography have revealed the presence of broad mantle plumes rooted at the base of the Earth's mantle beneath major hotspots. Hotspot tracks associated with these deep mantle plumes provide ideal constraints for inverting absolute plate motions as well as testing the fixed hotspot hypothesis. In this paper, 27 observed hotspot trends associated with 24 deep mantle plumes are used together with the MORVEL model for relative plate motions to determine an absolute plate motion model, in terms of a maximum likelihood optimization for angular data fitting, combined with an outlier data detection procedure based on statistical tests. The obtained T25M model fits 25 observed trends of globally distributed hotspot tracks to the statistically required level, while the other two hotspot trend data (Comores on Somalia and Iceland on Eurasia) are identified as outliers, which are significantly incompatible with other data. For most hotspots with rate data available, T25M predicts plate velocities significantly lower than the observed rates of hotspot volcanic migration, which cannot be fully explained by biased errors in observed rate data. Instead, the apparent hotspot motions derived by subtracting the observed hotspot migration velocities from the T25M plate velocities exhibit a combined pattern of being opposite to plate velocities and moving towards mid-ocean ridges. The newly estimated net rotation of the lithosphere is statistically compatible with three recent estimates, but differs significantly from 30 of 33 prior estimates.

  16. Evaluating MTCLIM for incident daily solar radiation and humidity in diverse meteorological and topographical environments in the main Hawaiian Islands

    NASA Astrophysics Data System (ADS)

    Giambelluca, T. W.; Needham, H.; Longman, R. J.

    2017-12-01

    Continuous and high resolution climatologies are important inputs in determining future scenarios for land processes. In Hawaíi, a lack of continuous meteorological data has been a problem for both ecological and hydrological research of land-surface processes at daily time scales. For downward shortwave radiation (SWdown) and relative humidity (RH) climate variables, the number of surface stations which record daily values are limited and tend to be situated at city airports or in convenient locations leaving large sections of the islands underrepresented. The aim of this study is to evaluate the rationale behind using the mountain microclimate simulator MTCLIM to obtain a gridded observation based ensemble of SWdown and RH data at a daily increment for the period of 1990-2014 for the main Hawaiian Islands. Preliminary results, testing model output with observed data, show mean bias errors (%MBE) of 1.15 W/m2 for SWdown and -0.8% for RH. Mean absolute errors (%MAE) of 32.83 W/m2 SWdown and 14.96% RH, with root mean square errors (%RMSE) of 40.17 W/m2 SWdown and 11.75% RH. Further optimization of the model and additional methods to reduce errors are being investigated to improve the model's functionality with Hawaíi's extreme climate gradients.

  17. A hybrid ARIMA and neural network model applied to forecast catch volumes of Selar crumenophthalmus

    NASA Astrophysics Data System (ADS)

    Aquino, Ronald L.; Alcantara, Nialle Loui Mar T.; Addawe, Rizavel C.

    2017-11-01

    The Selar crumenophthalmus with the English name big-eyed scad fish, locally known as matang-baka, is one of the fishes commonly caught along the waters of La Union, Philippines. The study deals with the forecasting of catch volumes of big-eyed scad fish for commercial consumption. The data used are quarterly caught volumes of big-eyed scad fish from 2002 to first quarter of 2017. This actual data is available from the open stat database published by the Philippine Statistics Authority (PSA)whose task is to collect, compiles, analyzes and publish information concerning different aspects of the Philippine setting. Autoregressive Integrated Moving Average (ARIMA) models, Artificial Neural Network (ANN) model and the Hybrid model consisting of ARIMA and ANN were developed to forecast catch volumes of big-eyed scad fish. Statistical errors such as Mean Absolute Errors (MAE) and Root Mean Square Errors (RMSE) were computed and compared to choose the most suitable model for forecasting the catch volume for the next few quarters. A comparison of the results of each model and corresponding statistical errors reveals that the hybrid model, ARIMA-ANN (2,1,2)(6:3:1), is the most suitable model to forecast the catch volumes of the big-eyed scad fish for the next few quarters.

  18. A new method to calibrate the absolute sensitivity of a soft X-ray streak camera

    NASA Astrophysics Data System (ADS)

    Yu, Jian; Liu, Shenye; Li, Jin; Yang, Zhiwen; Chen, Ming; Guo, Luting; Yao, Li; Xiao, Shali

    2016-12-01

    In this paper, we introduce a new method to calibrate the absolute sensitivity of a soft X-ray streak camera (SXRSC). The calibrations are done in the static mode by using a small laser-produced X-ray source. A calibrated X-ray CCD is used as a secondary standard detector to monitor the X-ray source intensity. In addition, two sets of holographic flat-field grating spectrometers are chosen as the spectral discrimination systems of the SXRSC and the X-ray CCD. The absolute sensitivity of the SXRSC is obtained by comparing the signal counts of the SXRSC to the output counts of the X-ray CCD. Results show that the calibrated spectrum covers the range from 200 eV to 1040 eV. The change of the absolute sensitivity in the vicinity of the K-edge of the carbon can also be clearly seen. The experimental values agree with the calculated values to within 29% error. Compared with previous calibration methods, the proposed method has several advantages: a wide spectral range, high accuracy, and simple data processing. Our calibration results can be used to make quantitative X-ray flux measurements in laser fusion research.

  19. Comparison of different interpolation methods for spatial distribution of soil organic carbon and some soil properties in the Black Sea backward region of Turkey

    NASA Astrophysics Data System (ADS)

    Göl, Ceyhun; Bulut, Sinan; Bolat, Ferhat

    2017-10-01

    The purpose of this research is to compare the spatial variability of soil organic carbon (SOC) in four adjacent land uses including the cultivated area, the grassland area, the plantation area and the natural forest area in the semi - arid region of Black Sea backward region of Turkey. Some of the soil properties, including total nitrogen, SOC, soil organic matter, and bulk density were measured on a grid with a 50 m sampling distance on the top soil (0-15 cm depth). Accordingly, a total of 120 samples were taken from the four adjacent land uses. Data was analyzed using geostatistical methods. The methods used were: Block kriging (BK), co - kriging (CK) with organic matter, total nitrogen and bulk density as auxiliary variables and inverse distance weighting (IDW) methods with the power of 1, 2 and 4. The methods were compared using a performance criteria that included root mean square error (RMSE), mean absolute error (MAE) and the coefficient of correlation (r). The one - way ANOVA test showed that differences between the natural (0.6653 ± 0.2901) - plantation forest (0.7109 ± 0.2729) areas and the grassland (1.3964 ± 0.6828) - cultivated areas (1.5851 ± 0.5541) were statistically significant at 0.05 level (F = 28.462). The best model for describing spatially variation of SOC was CK with the lowest error criteria (RMSE = 0.3342, MAE = 0.2292) and the highest coefficient of correlation (r = 0.84). The spatial structure of SOC could be well described by the spherical model. The nugget effect indicated that SOC was moderately dependent on the study area. The error distributions of the model showed that the improved model was unbiased in predicting the spatial distribution of SOC. This study's results revealed that an explanatory variable linked SOC increased success of spatial interpolation methods. In subsequent studies, this case should be taken into account for reaching more accurate outputs.

  20. Application of a Combined Model with Autoregressive Integrated Moving Average (ARIMA) and Generalized Regression Neural Network (GRNN) in Forecasting Hepatitis Incidence in Heng County, China

    PubMed Central

    Liang, Hao; Gao, Lian; Liang, Bingyu; Huang, Jiegang; Zang, Ning; Liao, Yanyan; Yu, Jun; Lai, Jingzhen; Qin, Fengxiang; Su, Jinming; Ye, Li; Chen, Hui

    2016-01-01

    Background Hepatitis is a serious public health problem with increasing cases and property damage in Heng County. It is necessary to develop a model to predict the hepatitis epidemic that could be useful for preventing this disease. Methods The autoregressive integrated moving average (ARIMA) model and the generalized regression neural network (GRNN) model were used to fit the incidence data from the Heng County CDC (Center for Disease Control and Prevention) from January 2005 to December 2012. Then, the ARIMA-GRNN hybrid model was developed. The incidence data from January 2013 to December 2013 were used to validate the models. Several parameters, including mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE) and mean square error (MSE), were used to compare the performance among the three models. Results The morbidity of hepatitis from Jan 2005 to Dec 2012 has seasonal variation and slightly rising trend. The ARIMA(0,1,2)(1,1,1)12 model was the most appropriate one with the residual test showing a white noise sequence. The smoothing factor of the basic GRNN model and the combined model was 1.8 and 0.07, respectively. The four parameters of the hybrid model were lower than those of the two single models in the validation. The parameters values of the GRNN model were the lowest in the fitting of the three models. Conclusions The hybrid ARIMA-GRNN model showed better hepatitis incidence forecasting in Heng County than the single ARIMA model and the basic GRNN model. It is a potential decision-supportive tool for controlling hepatitis in Heng County. PMID:27258555

  1. Comparison of the CME-associated shock arrival times at the earth using the WSA-ENLIL model with three cone models

    NASA Astrophysics Data System (ADS)

    Jang, S.; Moon, Y.; Na, H.

    2012-12-01

    We have made a comparison of CME-associated shock arrival times at the earth based on the WSA-ENLIL model with three cone models using 29 halo CMEs from 2001 to 2002. These halo CMEs have cone model parameters from Michalek et al. (2007) as well as their associated interplanetary (IP) shocks. For this study we consider three different cone models (an asymmetric cone model, an ice-cream cone model and an elliptical cone model) to determine CME cone parameters (radial velocity, angular width and source location), which are used for input parameters of the WSA-ENLIL model. The mean absolute error (MAE) of the arrival times for the elliptical cone model is 10 hours, which is about 2 hours smaller than those of the other models. However, this value is still larger than that (8.7 hours) of an empirical model by Kim et al. (2007). We are investigating several possibilities on relatively large errors of the WSA-ENLIL cone model, which may be caused by CME-CME interaction, background solar wind speed, and/or CME density enhancement.

  2. Piezocomposite Actuator Arrays for Correcting and Controlling Wavefront Error in Reflectors

    NASA Technical Reports Server (NTRS)

    Bradford, Samuel Case; Peterson, Lee D.; Ohara, Catherine M.; Shi, Fang; Agnes, Greg S.; Hoffman, Samuel M.; Wilkie, William Keats

    2012-01-01

    Three reflectors have been developed and tested to assess the performance of a distributed network of piezocomposite actuators for correcting thermal deformations and total wave-front error. The primary testbed article is an active composite reflector, composed of a spherically curved panel with a graphite face sheet and aluminum honeycomb core composite, and then augmented with a network of 90 distributed piezoelectric composite actuators. The piezoelectric actuator system may be used for correcting as-built residual shape errors, and for controlling low-order, thermally-induced quasi-static distortions of the panel. In this study, thermally-induced surface deformations of 1 to 5 microns were deliberately introduced onto the reflector, then measured using a speckle holography interferometer system. The reflector surface figure was subsequently corrected to a tolerance of 50 nm using the actuators embedded in the reflector's back face sheet. Two additional test articles were constructed: a borosilicate at window at 150 mm diameter with 18 actuators bonded to the back surface; and a direct metal laser sintered reflector with spherical curvature, 230 mm diameter, and 12 actuators bonded to the back surface. In the case of the glass reflector, absolute measurements were performed with an interferometer and the absolute surface was corrected. These test articles were evaluated to determine their absolute surface control capabilities, as well as to assess a multiphysics modeling effort developed under this program for the prediction of active reflector response. This paper will describe the design, construction, and testing of active reflector systems under thermal loads, and subsequent correction of surface shape via distributed peizeoelctric actuation.

  3. Systematic error of the Gaia DR1 TGAS parallaxes from data for the red giant clump

    NASA Astrophysics Data System (ADS)

    Gontcharov, G. A.

    2017-08-01

    Based on the Gaia DR1 TGAS parallaxes and photometry from the Tycho-2, Gaia, 2MASS, andWISE catalogues, we have produced a sample of 100 000 clump red giants within 800 pc of the Sun. The systematic variations of the mode of their absolute magnitude as a function of the distance, magnitude, and other parameters have been analyzed. We show that these variations reach 0.7 mag and cannot be explained by variations in the interstellar extinction or intrinsic properties of stars and by selection. The only explanation seems to be a systematic error of the Gaia DR1 TGAS parallax dependent on the square of the observed distance in kpc: 0.18 R 2 mas. Allowance for this error reduces significantly the systematic dependences of the absolute magnitude mode on all parameters. This error reaches 0.1 mas within 800 pc of the Sun and allows an upper limit for the accuracy of the TGAS parallaxes to be estimated as 0.2 mas. A careful allowance for such errors is needed to use clump red giants as "standard candles." This eliminates all discrepancies between the theoretical and empirical estimates of the characteristics of these stars and allows us to obtain the first estimates of the modes of their absolute magnitudes from the Gaia parallaxes: mode( M H ) = -1.49 m ± 0.04 m , mode( M Ks ) = -1.63 m ± 0.03 m , mode( M W1) = -1.67 m ± 0.05 m mode( M W2) = -1.67 m ± 0.05 m , mode( M W3) = -1.66 m ± 0.02 m , mode( M W4) = -1.73 m ± 0.03 m , as well as the corresponding estimates of their de-reddened colors.

  4. A Hybrid Model for Predicting the Prevalence of Schistosomiasis in Humans of Qianjiang City, China

    PubMed Central

    Wang, Ying; Lu, Zhouqin; Tian, Lihong; Tan, Li; Shi, Yun; Nie, Shaofa; Liu, Li

    2014-01-01

    Backgrounds/Objective Schistosomiasis is still a major public health problem in China, despite the fact that the government has implemented a series of strategies to prevent and control the spread of the parasitic disease. Advanced warning and reliable forecasting can help policymakers to adjust and implement strategies more effectively, which will lead to the control and elimination of schistosomiasis. Our aim is to explore the application of a hybrid forecasting model to track the trends of the prevalence of schistosomiasis in humans, which provides a methodological basis for predicting and detecting schistosomiasis infection in endemic areas. Methods A hybrid approach combining the autoregressive integrated moving average (ARIMA) model and the nonlinear autoregressive neural network (NARNN) model to forecast the prevalence of schistosomiasis in the future four years. Forecasting performance was compared between the hybrid ARIMA-NARNN model, and the single ARIMA or the single NARNN model. Results The modelling mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of the ARIMA-NARNN model was 0.1869×10−4, 0.0029, 0.0419 with a corresponding testing error of 0.9375×10−4, 0.0081, 0.9064, respectively. These error values generated with the hybrid model were all lower than those obtained from the single ARIMA or NARNN model. The forecasting values were 0.75%, 0.80%, 0.76% and 0.77% in the future four years, which demonstrated a no-downward trend. Conclusion The hybrid model has high quality prediction accuracy in the prevalence of schistosomiasis, which provides a methodological basis for future schistosomiasis monitoring and control strategies in the study area. It is worth attempting to utilize the hybrid detection scheme in other schistosomiasis-endemic areas including other infectious diseases. PMID:25119882

  5. Head repositioning accuracy to neutral: a comparative study of error calculation.

    PubMed

    Hill, Robert; Jensen, Pål; Baardsen, Tor; Kulvik, Kristian; Jull, Gwendolen; Treleaven, Julia

    2009-02-01

    Deficits in cervical proprioception have been identified in subjects with neck pain through the measure of head repositioning accuracy (HRA). Nevertheless there appears to be no general consensus regarding the construct of measurement of error used for calculating HRA. This study investigated four different mathematical methods of measurement of error to determine if there were any differences in their ability to discriminate between a control group and subjects with a whiplash associated disorder. The four methods for measuring cervical joint position error were calculated using a previous data set consisting of 50 subjects with whiplash complaining of dizziness (WAD D), 50 subjects with whiplash not complaining of dizziness (WAD ND) and 50 control subjects. The results indicated that no one measure of HRA uniquely detected or defined the differences between the whiplash and control groups. Constant error (CE) was significantly different between the whiplash and control groups from extension (p<0.05). Absolute errors (AEs) and root mean square errors (RMSEs) demonstrated differences between the two WAD groups in rotation trials (p<0.05). No differences were seen with variable error (VE). The results suggest that a combination of AE (or RMSE) and CE are probably the most suitable measures for analysis of HRA.

  6. Design, performance, and calculated error of a Faraday cup for absolute beam current measurements of 600-MeV protons

    NASA Technical Reports Server (NTRS)

    Beck, S. M.

    1975-01-01

    A mobile self-contained Faraday cup system for beam current measurments of nominal 600 MeV protons was designed, constructed, and used at the NASA Space Radiation Effects Laboratory. The cup is of reentrant design with a length of 106.7 cm and an outside diameter of 20.32 cm. The inner diameter is 15.24 cm and the base thickness is 30.48 cm. The primary absorber is commercially available lead hermetically sealed in a 0.32-cm-thick copper jacket. Several possible systematic errors in using the cup are evaluated. The largest source of error arises from high-energy electrons which are ejected from the entrance window and enter the cup. A total systematic error of -0.83 percent is calculated to be the decrease from the true current value. From data obtained in calibrating helium-filled ion chambers with the Faraday cup, the mean energy required to produce one ion pair in helium is found to be 30.76 + or - 0.95 eV for nominal 600 MeV protons. This value agrees well, within experimental error, with reported values of 29.9 eV and 30.2 eV.

  7. Smoothing and gap-filling of high resolution multi-spectral time series: Example of Landsat data

    NASA Astrophysics Data System (ADS)

    Vuolo, Francesco; Ng, Wai-Tim; Atzberger, Clement

    2017-05-01

    This paper introduces a novel methodology for generating 15-day, smoothed and gap-filled time series of high spatial resolution data. The approach is based on templates from high quality observations to fill data gaps that are subsequently filtered. We tested our method for one large contiguous area (Bavaria, Germany) and for nine smaller test sites in different ecoregions of Europe using Landsat data. Overall, our results match the validation dataset to a high degree of accuracy with a mean absolute error (MAE) of 0.01 for visible bands, 0.03 for near-infrared and 0.02 for short-wave-infrared. Occasionally, the reconstructed time series are affected by artefacts due to undetected clouds. Less frequently, larger uncertainties occur as a result of extended periods of missing data. Reliable cloud masks are highly warranted for making full use of time series.

  8. First Absolutely Calibrated Localized Measurements of Ion Velocity in the MST in Locked and Rotating Plasmas

    NASA Astrophysics Data System (ADS)

    Baltzer, M.; Craig, D.; den Hartog, D. J.; Nornberg, M. D.; Munaretto, S.

    2015-11-01

    An Ion Doppler Spectrometer (IDS) is used on MST for high time-resolution passive and active measurements of impurity ion emission. Absolutely calibrated measurements of flow are difficult because the spectrometer records data within 0.3 nm of the C+5 line of interest, and commercial calibration lamps do not produce lines in this narrow range . A novel optical system was designed to absolutely calibrate the IDS. The device uses an UV LED to produce a broad emission curve in the desired region. A Fabry-Perot etalon filters this light, cutting transmittance peaks into the pattern of the LED emission. An optical train of fused silica lenses focuses the light into the IDS with f/4. A holographic diffuser blurs the light cone to increase homogeneity. Using this light source, the absolute Doppler shift of ion emissions can be measured in MST plasmas. In combination with charge exchange recombination spectroscopy, localized ion velocities can now be measured. Previously, a time-averaged measurement along the chord bisecting the poloidal plane was used to calibrate the IDS; the quality of these central chord calibrations can be characterized with our absolute calibration. Calibration errors may also be quantified and minimized by optimizing the curve-fitting process. Preliminary measurements of toroidal velocity in locked and rotating plasmas will be shown. This work has been supported by the US DOE.

  9. Clinical implementation and error sensitivity of a 3D quality assurance protocol for prostate and thoracic IMRT

    PubMed Central

    Cotter, Christopher; Turcotte, Julie Catherine; Crawford, Bruce; Sharp, Gregory; Mah'D, Mufeed

    2015-01-01

    This work aims at three goals: first, to define a set of statistical parameters and plan structures for a 3D pretreatment thoracic and prostate intensity‐modulated radiation therapy (IMRT) quality assurance (QA) protocol; secondly, to test if the 3D QA protocol is able to detect certain clinical errors; and third, to compare the 3D QA method with QA performed with single ion chamber and 2D gamma test in detecting those errors. The 3D QA protocol measurements were performed on 13 prostate and 25 thoracic IMRT patients using IBA's COMPASS system. For each treatment planning structure included in the protocol, the following statistical parameters were evaluated: average absolute dose difference (AADD), percent structure volume with absolute dose difference greater than 6% (ADD6), and 3D gamma test. To test the 3D QA protocol error sensitivity, two prostate and two thoracic step‐and‐shoot IMRT patients were investigated. Errors introduced to each of the treatment plans included energy switched from 6 MV to 10 MV, multileaf collimator (MLC) leaf errors, linac jaws errors, monitor unit (MU) errors, MLC and gantry angle errors, and detector shift errors. QA was performed on each plan using a single ion chamber and 2D array of ion chambers for 2D and 3D QA. Based on the measurements performed, we established a uniform set of tolerance levels to determine if QA passes for each IMRT treatment plan structure: maximum allowed AADD is 6%; maximum 4% of any structure volume can be with ADD6 greater than 6%, and maximum 4% of any structure volume may fail 3D gamma test with test parameters 3%/3 mm DTA. Out of the three QA methods tested the single ion chamber performed the worst by detecting 4 out of 18 introduced errors, 2D QA detected 11 out of 18 errors, and 3D QA detected 14 out of 18 errors. PACS number: 87.56.Fc PMID:26699299

  10. Validation of satellite based precipitation over diverse topography of Pakistan

    NASA Astrophysics Data System (ADS)

    Iqbal, Muhammad Farooq; Athar, H.

    2018-03-01

    This study evaluates the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) product data with 0.25° × 0.25° spatial and post-real-time 3 h temporal resolution using point-based Surface Precipitation Gauge (SPG) data from 40 stations, for the period 1998-2013, and using gridded Asian Precipitation ˗ Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) data abbreviated as APH data with 0.25° × 0.25° spatial and daily temporal resolution for the period 1998-2007, over vulnerable and data sparse regions of Pakistan (24-37° N and 62-75° E). To evaluate the performance of TMPA relative to SPG and APH, four commonly used statistical indicator metrics including Mean Error (ME), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Correlation Coefficient (CC) are employed on daily, monthly, seasonal as well as on annual timescales. The TMPA slightly overestimated both SPG and APH at daily, monthly, and annual timescales, however close results were obtained between TMPA and SPG as compared to those between TMPA and APH, on the same timescale. The TMPA overestimated both SPG and APH during the Pre-Monsoon and Monsoon seasons, whereas it underestimated during the Post-Monsoon and Winter seasons, with different magnitudes. Agreement between TMPA and SPG was good in plain and medium elevation regions, whereas TMPA overestimated APH in 31 stations. The magnitudes of MAE and RMSE were high at daily timescale as compared to monthly and annual timescales. Relatively large MAE was observed in stations located over high elevation regions, whereas minor MAE was recorded in plain area stations at daily, monthly, and annual timescales. A strong positive linear relationship between TMPA and SPG was established at monthly (0.98), seasonal (0.93 to 0.98) and annual (0.97) timescales. Precipitation increased with the increase of elevation, and not only elevation but latitude also affected the

  11. Absolute brightness temperature measurements at 3.5-mm wavelength. [of sun, Venus, Jupiter and Saturn

    NASA Technical Reports Server (NTRS)

    Ulich, B. L.; Rhodes, P. J.; Davis, J. H.; Hollis, J. M.

    1980-01-01

    Careful observations have been made at 86.1 GHz to derive the absolute brightness temperatures of the sun (7914 + or - 192 K), Venus (357.5 + or - 13.1 K), Jupiter (179.4 + or - 4.7 K), and Saturn (153.4 + or - 4.8 K) with a standard error of about three percent. This is a significant improvement in accuracy over previous results at millimeter wavelengths. A stable transmitter and novel superheterodyne receiver were constructed and used to determine the effective collecting area of the Millimeter Wave Observatory (MWO) 4.9-m antenna relative to a previously calibrated standard gain horn. The thermal scale was set by calibrating the radiometer with carefully constructed and tested hot and cold loads. The brightness temperatures may be used to establish an absolute calibration scale and to determine the antenna aperture and beam efficiencies of other radio telescopes at 3.5-mm wavelength.

  12. Absolute Position Sensing Based on a Robust Differential Capacitive Sensor with a Grounded Shield Window

    PubMed Central

    Bai, Yang; Lu, Yunfeng; Hu, Pengcheng; Wang, Gang; Xu, Jinxin; Zeng, Tao; Li, Zhengkun; Zhang, Zhonghua; Tan, Jiubin

    2016-01-01

    A simple differential capacitive sensor is provided in this paper to measure the absolute positions of length measuring systems. By utilizing a shield window inside the differential capacitor, the measurement range and linearity range of the sensor can reach several millimeters. What is more interesting is that this differential capacitive sensor is only sensitive to one translational degree of freedom (DOF) movement, and immune to the vibration along the other two translational DOFs. In the experiment, we used a novel circuit based on an AC capacitance bridge to directly measure the differential capacitance value. The experimental result shows that this differential capacitive sensor has a sensitivity of 2 × 10−4 pF/μm with 0.08 μm resolution. The measurement range of this differential capacitive sensor is 6 mm, and the linearity error are less than 0.01% over the whole absolute position measurement range. PMID:27187393

  13. ACCESS, Absolute Color Calibration Experiment for Standard Stars: Integration, Test, and Ground Performance

    NASA Astrophysics Data System (ADS)

    Kaiser, Mary Elizabeth; Morris, Matthew; Aldoroty, Lauren; Kurucz, Robert; McCandliss, Stephan; Rauscher, Bernard; Kimble, Randy; Kruk, Jeffrey; Wright, Edward L.; Feldman, Paul; Riess, Adam; Gardner, Jonathon; Bohlin, Ralph; Deustua, Susana; Dixon, Van; Sahnow, David J.; Perlmutter, Saul

    2018-01-01

    Establishing improved spectrophotometric standards is important for a broad range of missions and is relevant to many astrophysical problems. Systematic errors associated with astrophysical data used to probe fundamental astrophysical questions, such as SNeIa observations used to constrain dark energy theories, now exceed the statistical errors associated with merged databases of these measurements. ACCESS, “Absolute Color Calibration Experiment for Standard Stars”, is a series of rocket-borne sub-orbital missions and ground-based experiments designed to enable improvements in the precision of the astrophysical flux scale through the transfer of absolute laboratory detector standards from the National Institute of Standards and Technology (NIST) to a network of stellar standards with a calibration accuracy of 1% and a spectral resolving power of 500 across the 0.35‑1.7μm bandpass. To achieve this goal ACCESS (1) observes HST/ Calspec stars (2) above the atmosphere to eliminate telluric spectral contaminants (e.g. OH) (3) using a single optical path and (HgCdTe) detector (4) that is calibrated to NIST laboratory standards and (5) monitored on the ground and in-flight using a on-board calibration monitor. The observations are (6) cross-checked and extended through the generation of stellar atmosphere models for the targets. The ACCESS telescope and spectrograph have been designed, fabricated, and integrated. Subsystems have been tested. Performance results for subsystems, operations testing, and the integrated spectrograph will be presented. NASA sounding rocket grant NNX17AC83G supports this work.

  14. Travel Time Estimation Using Freeway Point Detector Data Based on Evolving Fuzzy Neural Inference System.

    PubMed

    Tang, Jinjun; Zou, Yajie; Ash, John; Zhang, Shen; Liu, Fang; Wang, Yinhai

    2016-01-01

    Travel time is an important measurement used to evaluate the extent of congestion within road networks. This paper presents a new method to estimate the travel time based on an evolving fuzzy neural inference system. The input variables in the system are traffic flow data (volume, occupancy, and speed) collected from loop detectors located at points both upstream and downstream of a given link, and the output variable is the link travel time. A first order Takagi-Sugeno fuzzy rule set is used to complete the inference. For training the evolving fuzzy neural network (EFNN), two learning processes are proposed: (1) a K-means method is employed to partition input samples into different clusters, and a Gaussian fuzzy membership function is designed for each cluster to measure the membership degree of samples to the cluster centers. As the number of input samples increases, the cluster centers are modified and membership functions are also updated; (2) a weighted recursive least squares estimator is used to optimize the parameters of the linear functions in the Takagi-Sugeno type fuzzy rules. Testing datasets consisting of actual and simulated data are used to test the proposed method. Three common criteria including mean absolute error (MAE), root mean square error (RMSE), and mean absolute relative error (MARE) are utilized to evaluate the estimation performance. Estimation results demonstrate the accuracy and effectiveness of the EFNN method through comparison with existing methods including: multiple linear regression (MLR), instantaneous model (IM), linear model (LM), neural network (NN), and cumulative plots (CP).

  15. Travel Time Estimation Using Freeway Point Detector Data Based on Evolving Fuzzy Neural Inference System

    PubMed Central

    Tang, Jinjun; Zou, Yajie; Ash, John; Zhang, Shen; Liu, Fang; Wang, Yinhai

    2016-01-01

    Travel time is an important measurement used to evaluate the extent of congestion within road networks. This paper presents a new method to estimate the travel time based on an evolving fuzzy neural inference system. The input variables in the system are traffic flow data (volume, occupancy, and speed) collected from loop detectors located at points both upstream and downstream of a given link, and the output variable is the link travel time. A first order Takagi-Sugeno fuzzy rule set is used to complete the inference. For training the evolving fuzzy neural network (EFNN), two learning processes are proposed: (1) a K-means method is employed to partition input samples into different clusters, and a Gaussian fuzzy membership function is designed for each cluster to measure the membership degree of samples to the cluster centers. As the number of input samples increases, the cluster centers are modified and membership functions are also updated; (2) a weighted recursive least squares estimator is used to optimize the parameters of the linear functions in the Takagi-Sugeno type fuzzy rules. Testing datasets consisting of actual and simulated data are used to test the proposed method. Three common criteria including mean absolute error (MAE), root mean square error (RMSE), and mean absolute relative error (MARE) are utilized to evaluate the estimation performance. Estimation results demonstrate the accuracy and effectiveness of the EFNN method through comparison with existing methods including: multiple linear regression (MLR), instantaneous model (IM), linear model (LM), neural network (NN), and cumulative plots (CP). PMID:26829639

  16. Reliable estimation of orbit errors in spaceborne SAR interferometry. The network approach

    NASA Astrophysics Data System (ADS)

    Bähr, Hermann; Hanssen, Ramon F.

    2012-12-01

    An approach to improve orbital state vectors by orbit error estimates derived from residual phase patterns in synthetic aperture radar interferograms is presented. For individual interferograms, an error representation by two parameters is motivated: the baseline error in cross-range and the rate of change of the baseline error in range. For their estimation, two alternatives are proposed: a least squares approach that requires prior unwrapping and a less reliable gridsearch method handling the wrapped phase. In both cases, reliability is enhanced by mutual control of error estimates in an overdetermined network of linearly dependent interferometric combinations of images. Thus, systematic biases, e.g., due to unwrapping errors, can be detected and iteratively eliminated. Regularising the solution by a minimum-norm condition results in quasi-absolute orbit errors that refer to particular images. For the 31 images of a sample ENVISAT dataset, orbit corrections with a mutual consistency on the millimetre level have been inferred from 163 interferograms. The method itself qualifies by reliability and rigorous geometric modelling of the orbital error signal but does not consider interfering large scale deformation effects. However, a separation may be feasible in a combined processing with persistent scatterer approaches or by temporal filtering of the estimates.

  17. Error Estimation of Pathfinder Version 5.3 SST Level 3C Using Three-way Error Analysis

    NASA Astrophysics Data System (ADS)

    Saha, K.; Dash, P.; Zhao, X.; Zhang, H. M.

    2017-12-01

    One of the essential climate variables for monitoring as well as detecting and attributing climate change, is Sea Surface Temperature (SST). A long-term record of global SSTs are available with observations obtained from ships in the early days to the more modern observation based on in-situ as well as space-based sensors (satellite/aircraft). There are inaccuracies associated with satellite derived SSTs which can be attributed to the errors associated with spacecraft navigation, sensor calibrations, sensor noise, retrieval algorithms, and leakages due to residual clouds. Thus it is important to estimate accurate errors in satellite derived SST products to have desired results in its applications.Generally for validation purposes satellite derived SST products are compared against the in-situ SSTs which have inaccuracies due to spatio/temporal inhomogeneity between in-situ and satellite measurements. A standard deviation in their difference fields usually have contributions from both satellite as well as the in-situ measurements. A real validation of any geophysical variable must require the knowledge of the "true" value of the said variable. Therefore a one-to-one comparison of satellite based SST with in-situ data does not truly provide us the real error in the satellite SST and there will be ambiguity due to errors in the in-situ measurements and their collocation differences. A Triple collocation (TC) or three-way error analysis using 3 mutually independent error-prone measurements, can be used to estimate root-mean square error (RMSE) associated with each of the measurements with high level of accuracy without treating any one system a perfectly-observed "truth". In this study we are estimating the absolute random errors associated with Pathfinder Version 5.3 Level-3C SST product Climate Data record. Along with the in-situ SST data, the third source of dataset used for this analysis is the AATSR reprocessing of climate (ARC) dataset for the corresponding

  18. Best of both worlds: combining pharma data and state of the art modeling technology to improve in Silico pKa prediction.

    PubMed

    Fraczkiewicz, Robert; Lobell, Mario; Göller, Andreas H; Krenz, Ursula; Schoenneis, Rolf; Clark, Robert D; Hillisch, Alexander

    2015-02-23

    In a unique collaboration between a software company and a pharmaceutical company, we were able to develop a new in silico pKa prediction tool with outstanding prediction quality. An existing pKa prediction method from Simulations Plus based on artificial neural network ensembles (ANNE), microstates analysis, and literature data was retrained with a large homogeneous data set of drug-like molecules from Bayer. The new model was thus built with curated sets of ∼14,000 literature pKa values (∼11,000 compounds, representing literature chemical space) and ∼19,500 pKa values experimentally determined at Bayer Pharma (∼16,000 compounds, representing industry chemical space). Model validation was performed with several test sets consisting of a total of ∼31,000 new pKa values measured at Bayer. For the largest and most difficult test set with >16,000 pKa values that were not used for training, the original model achieved a mean absolute error (MAE) of 0.72, root-mean-square error (RMSE) of 0.94, and squared correlation coefficient (R(2)) of 0.87. The new model achieves significantly improved prediction statistics, with MAE = 0.50, RMSE = 0.67, and R(2) = 0.93. It is commercially available as part of the Simulations Plus ADMET Predictor release 7.0. Good predictions are only of value when delivered effectively to those who can use them. The new pKa prediction model has been integrated into Pipeline Pilot and the PharmacophorInformatics (PIx) platform used by scientists at Bayer Pharma. Different output formats allow customized application by medicinal chemists, physical chemists, and computational chemists.

  19. Respiratory motion prediction and prospective correction for free-breathing arterial spin-labeled perfusion MRI of the kidneys.

    PubMed

    Song, Hao; Ruan, Dan; Liu, Wenyang; Stenger, V Andrew; Pohmann, Rolf; Fernández-Seara, Maria A; Nair, Tejas; Jung, Sungkyu; Luo, Jingqin; Motai, Yuichi; Ma, Jingfei; Hazle, John D; Gach, H Michael

    2017-03-01

    Respiratory motion prediction using an artificial neural network (ANN) was integrated with pseudocontinuous arterial spin labeling (pCASL) MRI to allow free-breathing perfusion measurements in the kidney. In this study, we evaluated the performance of the ANN to accurately predict the location of the kidneys during image acquisition. A pencil-beam navigator was integrated with a pCASL sequence to measure lung/diaphragm motion during ANN training and the pCASL transit delay. The ANN algorithm ran concurrently in the background to predict organ location during the 0.7-s 15-slice acquisition based on the navigator data. The predictions were supplied to the pulse sequence to prospectively adjust the axial slice acquisition to match the predicted organ location. Additional navigators were acquired immediately after the multislice acquisition to assess the performance and accuracy of the ANN. The technique was tested in eight healthy volunteers. The root-mean-square error (RMSE) and mean absolute error (MAE) for the eight volunteers were 1.91 ± 0.17 mm and 1.43 ± 0.17 mm, respectively, for the ANN. The RMSE increased with transit delay. The MAE typically increased from the first to last prediction in the image acquisition. The overshoot was 23.58% ± 3.05% using the target prediction accuracy of ± 1 mm. Respiratory motion prediction with prospective motion correction was successfully demonstrated for free-breathing perfusion MRI of the kidney. The method serves as an alternative to multiple breathholds and requires minimal effort from the patient. © 2017 American Association of Physicists in Medicine.

  20. Novel isotopic N, N-Dimethyl Leucine (iDiLeu) Reagents Enable Absolute Quantification of Peptides and Proteins Using a Standard Curve Approach

    NASA Astrophysics Data System (ADS)

    Greer, Tyler; Lietz, Christopher B.; Xiang, Feng; Li, Lingjun

    2015-01-01

    Absolute quantification of protein targets using liquid chromatography-mass spectrometry (LC-MS) is a key component of candidate biomarker validation. One popular method combines multiple reaction monitoring (MRM) using a triple quadrupole instrument with stable isotope-labeled standards (SIS) for absolute quantification (AQUA). LC-MRM AQUA assays are sensitive and specific, but they are also expensive because of the cost of synthesizing stable isotope peptide standards. While the chemical modification approach using mass differential tags for relative and absolute quantification (mTRAQ) represents a more economical approach when quantifying large numbers of peptides, these reagents are costly and still suffer from lower throughput because only two concentration values per peptide can be obtained in a single LC-MS run. Here, we have developed and applied a set of five novel mass difference reagents, isotopic N, N-dimethyl leucine (iDiLeu). These labels contain an amine reactive group, triazine ester, are cost effective because of their synthetic simplicity, and have increased throughput compared with previous LC-MS quantification methods by allowing construction of a four-point standard curve in one run. iDiLeu-labeled peptides show remarkably similar retention time shifts, slightly lower energy thresholds for higher-energy collisional dissociation (HCD) fragmentation, and high quantification accuracy for trypsin-digested protein samples (median errors <15%). By spiking in an iDiLeu-labeled neuropeptide, allatostatin, into mouse urine matrix, two quantification methods are validated. The first uses one labeled peptide as an internal standard to normalize labeled peptide peak areas across runs (<19% error), whereas the second enables standard curve creation and analyte quantification in one run (<8% error).

  1. A Comparative Assessment of the Influences of Human Impacts on Soil Cd Concentrations Based on Stepwise Linear Regression, Classification and Regression Tree, and Random Forest Models

    PubMed Central

    Qiu, Lefeng; Wang, Kai; Long, Wenli; Wang, Ke; Hu, Wei; Amable, Gabriel S.

    2016-01-01

    Soil cadmium (Cd) contamination has attracted a great deal of attention because of its detrimental effects on animals and humans. This study aimed to develop and compare the performances of stepwise linear regression (SLR), classification and regression tree (CART) and random forest (RF) models in the prediction and mapping of the spatial distribution of soil Cd and to identify likely sources of Cd accumulation in Fuyang County, eastern China. Soil Cd data from 276 topsoil (0–20 cm) samples were collected and randomly divided into calibration (222 samples) and validation datasets (54 samples). Auxiliary data, including detailed land use information, soil organic matter, soil pH, and topographic data, were incorporated into the models to simulate the soil Cd concentrations and further identify the main factors influencing soil Cd variation. The predictive models for soil Cd concentration exhibited acceptable overall accuracies (72.22% for SLR, 70.37% for CART, and 75.93% for RF). The SLR model exhibited the largest predicted deviation, with a mean error (ME) of 0.074 mg/kg, a mean absolute error (MAE) of 0.160 mg/kg, and a root mean squared error (RMSE) of 0.274 mg/kg, and the RF model produced the results closest to the observed values, with an ME of 0.002 mg/kg, an MAE of 0.132 mg/kg, and an RMSE of 0.198 mg/kg. The RF model also exhibited the greatest R2 value (0.772). The CART model predictions closely followed, with ME, MAE, RMSE, and R2 values of 0.013 mg/kg, 0.154 mg/kg, 0.230 mg/kg and 0.644, respectively. The three prediction maps generally exhibited similar and realistic spatial patterns of soil Cd contamination. The heavily Cd-affected areas were primarily located in the alluvial valley plain of the Fuchun River and its tributaries because of the dramatic industrialization and urbanization processes that have occurred there. The most important variable for explaining high levels of soil Cd accumulation was the presence of metal smelting industries. The

  2. Magnetic Resonance–Based Automatic Air Segmentation for Generation of Synthetic Computed Tomography Scans in the Head Region

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zheng, Weili; Kim, Joshua P.; Kadbi, Mo

    2015-11-01

    Purpose: To incorporate a novel imaging sequence for robust air and tissue segmentation using ultrashort echo time (UTE) phase images and to implement an innovative synthetic CT (synCT) solution as a first step toward MR-only radiation therapy treatment planning for brain cancer. Methods and Materials: Ten brain cancer patients were scanned with a UTE/Dixon sequence and other clinical sequences on a 1.0 T open magnet with simulation capabilities. Bone-enhanced images were generated from a weighted combination of water/fat maps derived from Dixon images and inverted UTE images. Automated air segmentation was performed using unwrapped UTE phase maps. Segmentation accuracy was assessedmore » by calculating segmentation errors (true-positive rate, false-positive rate, and Dice similarity indices using CT simulation (CT-SIM) as ground truth. The synCTs were generated using a voxel-based, weighted summation method incorporating T2, fluid attenuated inversion recovery (FLAIR), UTE1, and bone-enhanced images. Mean absolute error (MAE) characterized Hounsfield unit (HU) differences between synCT and CT-SIM. A dosimetry study was conducted, and differences were quantified using γ-analysis and dose-volume histogram analysis. Results: On average, true-positive rate and false-positive rate for the CT and MR-derived air masks were 80.8% ± 5.5% and 25.7% ± 6.9%, respectively. Dice similarity indices values were 0.78 ± 0.04 (range, 0.70-0.83). Full field of view MAE between synCT and CT-SIM was 147.5 ± 8.3 HU (range, 138.3-166.2 HU), with the largest errors occurring at bone–air interfaces (MAE 422.5 ± 33.4 HU for bone and 294.53 ± 90.56 HU for air). Gamma analysis revealed pass rates of 99.4% ± 0.04%, with acceptable treatment plan quality for the cohort. Conclusions: A hybrid MRI phase/magnitude UTE image processing technique was introduced that significantly improved bone and air contrast in MRI. Segmented air masks and bone-enhanced images were

  3. A Comparative Assessment of the Influences of Human Impacts on Soil Cd Concentrations Based on Stepwise Linear Regression, Classification and Regression Tree, and Random Forest Models.

    PubMed

    Qiu, Lefeng; Wang, Kai; Long, Wenli; Wang, Ke; Hu, Wei; Amable, Gabriel S

    2016-01-01

    Soil cadmium (Cd) contamination has attracted a great deal of attention because of its detrimental effects on animals and humans. This study aimed to develop and compare the performances of stepwise linear regression (SLR), classification and regression tree (CART) and random forest (RF) models in the prediction and mapping of the spatial distribution of soil Cd and to identify likely sources of Cd accumulation in Fuyang County, eastern China. Soil Cd data from 276 topsoil (0-20 cm) samples were collected and randomly divided into calibration (222 samples) and validation datasets (54 samples). Auxiliary data, including detailed land use information, soil organic matter, soil pH, and topographic data, were incorporated into the models to simulate the soil Cd concentrations and further identify the main factors influencing soil Cd variation. The predictive models for soil Cd concentration exhibited acceptable overall accuracies (72.22% for SLR, 70.37% for CART, and 75.93% for RF). The SLR model exhibited the largest predicted deviation, with a mean error (ME) of 0.074 mg/kg, a mean absolute error (MAE) of 0.160 mg/kg, and a root mean squared error (RMSE) of 0.274 mg/kg, and the RF model produced the results closest to the observed values, with an ME of 0.002 mg/kg, an MAE of 0.132 mg/kg, and an RMSE of 0.198 mg/kg. The RF model also exhibited the greatest R2 value (0.772). The CART model predictions closely followed, with ME, MAE, RMSE, and R2 values of 0.013 mg/kg, 0.154 mg/kg, 0.230 mg/kg and 0.644, respectively. The three prediction maps generally exhibited similar and realistic spatial patterns of soil Cd contamination. The heavily Cd-affected areas were primarily located in the alluvial valley plain of the Fuchun River and its tributaries because of the dramatic industrialization and urbanization processes that have occurred there. The most important variable for explaining high levels of soil Cd accumulation was the presence of metal smelting industries. The

  4. Prediction of Beck Depression Inventory (BDI-II) Score Using Acoustic Measurements in a Sample of Iium Engineering Students

    NASA Astrophysics Data System (ADS)

    Fikri Zanil, Muhamad; Nur Wahidah Nik Hashim, Nik; Azam, Huda

    2017-11-01

    Psychiatrist currently relies on questionnaires and interviews for psychological assessment. These conservative methods often miss true positives and might lead to death, especially in cases where a patient might be experiencing suicidal predisposition but was only diagnosed as major depressive disorder (MDD). With modern technology, an assessment tool might aid psychiatrist with a more accurate diagnosis and thus hope to reduce casualty. This project will explore on the relationship between speech features of spoken audio signal (reading) in Bahasa Malaysia with the Beck Depression Inventory scores. The speech features used in this project were Power Spectral Density (PSD), Mel-frequency Ceptral Coefficients (MFCC), Transition Parameter, formant and pitch. According to analysis, the optimum combination of speech features to predict BDI-II scores include PSD, MFCC and Transition Parameters. The linear regression approach with sequential forward/backward method was used to predict the BDI-II scores using reading speech. The result showed 0.4096 mean absolute error (MAE) for female reading speech. For male, the BDI-II scores successfully predicted 100% less than 1 scores difference with MAE of 0.098437. A prediction system called Depression Severity Evaluator (DSE) was developed. The DSE managed to predict one out of five subjects. Although the prediction rate was low, the system precisely predict the score within the maximum difference of 4.93 for each person. This demonstrates that the scores are not random numbers.

  5. Multiple regression based imputation for individualizing template human model from a small number of measured dimensions.

    PubMed

    Nohara, Ryuki; Endo, Yui; Murai, Akihiko; Takemura, Hiroshi; Kouchi, Makiko; Tada, Mitsunori

    2016-08-01

    Individual human models are usually created by direct 3D scanning or deforming a template model according to the measured dimensions. In this paper, we propose a method to estimate all the necessary dimensions (full set) for the human model individualization from a small number of measured dimensions (subset) and human dimension database. For this purpose, we solved multiple regression equation from the dimension database given full set dimensions as the objective variable and subset dimensions as the explanatory variables. Thus, the full set dimensions are obtained by simply multiplying the subset dimensions to the coefficient matrix of the regression equation. We verified the accuracy of our method by imputing hand, foot, and whole body dimensions from their dimension database. The leave-one-out cross validation is employed in this evaluation. The mean absolute errors (MAE) between the measured and the estimated dimensions computed from 4 dimensions (hand length, breadth, middle finger breadth at proximal, and middle finger depth at proximal) in the hand, 2 dimensions (foot length, breadth, and lateral malleolus height) in the foot, and 1 dimension (height) and weight in the whole body are computed. The average MAE of non-measured dimensions were 4.58% in the hand, 4.42% in the foot, and 3.54% in the whole body, while that of measured dimensions were 0.00%.

  6. New principle for measuring arterial blood oxygenation, enabling motion-robust remote monitoring.

    PubMed

    van Gastel, Mark; Stuijk, Sander; de Haan, Gerard

    2016-12-07

    Finger-oximeters are ubiquitously used for patient monitoring in hospitals worldwide. Recently, remote measurement of arterial blood oxygenation (SpO 2 ) with a camera has been demonstrated. Both contact and remote measurements, however, require the subject to remain static for accurate SpO 2 values. This is due to the use of the common ratio-of-ratios measurement principle that measures the relative pulsatility at different wavelengths. Since the amplitudes are small, they are easily corrupted by motion-induced variations. We introduce a new principle that allows accurate remote measurements even during significant subject motion. We demonstrate the main advantage of the principle, i.e. that the optimal signature remains the same even when the SNR of the PPG signal drops significantly due to motion or limited measurement area. The evaluation uses recordings with breath-holding events, which induce hypoxemia in healthy moving subjects. The events lead to clinically relevant SpO 2 levels in the range 80-100%. The new principle is shown to greatly outperform current remote ratio-of-ratios based methods. The mean-absolute SpO 2 -error (MAE) is about 2 percentage-points during head movements, where the benchmark method shows a MAE of 24 percentage-points. Consequently, we claim ours to be the first method to reliably measure SpO 2 remotely during significant subject motion.

  7. Application of Multi-task Sparse Lasso Feature Extraction and Support Vector Machine Regression in the Stellar Atmospheric Parameterization

    NASA Astrophysics Data System (ADS)

    Gao, Wei; Li, Xiang-ru

    2017-07-01

    The multi-task learning takes the multiple tasks together to make analysis and calculation, so as to dig out the correlations among them, and therefore to improve the accuracy of the analyzed results. This kind of methods have been widely applied to the machine learning, pattern recognition, computer vision, and other related fields. This paper investigates the application of multi-task learning in estimating the stellar atmospheric parameters, including the surface temperature (Teff), surface gravitational acceleration (lg g), and chemical abundance ([Fe/H]). Firstly, the spectral features of the three stellar atmospheric parameters are extracted by using the multi-task sparse group Lasso algorithm, then the support vector machine is used to estimate the atmospheric physical parameters. The proposed scheme is evaluated on both the Sloan stellar spectra and the theoretical spectra computed from the Kurucz's New Opacity Distribution Function (NEWODF) model. The mean absolute errors (MAEs) on the Sloan spectra are: 0.0064 for lg (Teff /K), 0.1622 for lg (g/(cm · s-2)), and 0.1221 dex for [Fe/H]; the MAEs on the synthetic spectra are 0.0006 for lg (Teff /K), 0.0098 for lg (g/(cm · s-2)), and 0.0082 dex for [Fe/H]. Experimental results show that the proposed scheme has a rather high accuracy for the estimation of stellar atmospheric parameters.

  8. Estimation of size of tropical cyclones in the North Indian Ocean using Oceansat-2 scatterometer high-resolution wind products

    NASA Astrophysics Data System (ADS)

    Jaiswal, Neeru; Ha, Doan Thi Thu; Kishtawal, C. M.

    2018-03-01

    Tropical cyclone (TC) is one of the most intense weather hazards, especially for the coastal regions, as it causes huge devastation through gale winds and torrential floods during landfall. Thus, accurate prediction of TC is of great importance to reduce the loss of life and damage to property. Most of the cyclone track prediction model requires size of TC as an important parameter in order to simulate the vortex. TC size is also required in the impact assessment of TC affected regions. In the present work, the size of TCs formed in the North Indian Ocean (NIO) has been estimated using the high resolution surface wind observations from oceansat-2 scatterometer. The estimated sizes of cyclones were compared to the radius of outermost closed isobar (ROCI) values provided by Joint Typhoon warning Center (JTWC) by plotting their histograms and computing the correlation and mean absolute error (MAE). The correlation and MAE between the OSCAT wind based TC size estimation and JTWC-ROCI values was found 0.69 and 33 km, respectively. The results show that the sizes of cyclones estimated by OSCAT winds are in close agreement to the JTWC-ROCI. The ROCI values of JTWC were analyzed to study the variations in the size of tropical cyclones in NIO during different time of the diurnal cycle and intensity stages.

  9. Very short-term reactive forecasting of the solar ultraviolet index using an extreme learning machine integrated with the solar zenith angle.

    PubMed

    Deo, Ravinesh C; Downs, Nathan; Parisi, Alfio V; Adamowski, Jan F; Quilty, John M

    2017-05-01

    Exposure to erythemally-effective solar ultraviolet radiation (UVR) that contributes to malignant keratinocyte cancers and associated health-risk is best mitigated through innovative decision-support systems, with global solar UV index (UVI) forecast necessary to inform real-time sun-protection behaviour recommendations. It follows that the UVI forecasting models are useful tools for such decision-making. In this study, a model for computationally-efficient data-driven forecasting of diffuse and global very short-term reactive (VSTR) (10-min lead-time) UVI, enhanced by drawing on the solar zenith angle (θ s ) data, was developed using an extreme learning machine (ELM) algorithm. An ELM algorithm typically serves to address complex and ill-defined forecasting problems. UV spectroradiometer situated in Toowoomba, Australia measured daily cycles (0500-1700h) of UVI over the austral summer period. After trialling activations functions based on sine, hard limit, logarithmic and tangent sigmoid and triangular and radial basis networks for best results, an optimal ELM architecture utilising logarithmic sigmoid equation in hidden layer, with lagged combinations of θ s as the predictor data was developed. ELM's performance was evaluated using statistical metrics: correlation coefficient (r), Willmott's Index (WI), Nash-Sutcliffe efficiency coefficient (E NS ), root mean square error (RMSE), and mean absolute error (MAE) between observed and forecasted UVI. Using these metrics, the ELM model's performance was compared to that of existing methods: multivariate adaptive regression spline (MARS), M5 Model Tree, and a semi-empirical (Pro6UV) clear sky model. Based on RMSE and MAE values, the ELM model (0.255, 0.346, respectively) outperformed the MARS (0.310, 0.438) and M5 Model Tree (0.346, 0.466) models. Concurring with these metrics, the Willmott's Index for the ELM, MARS and M5 Model Tree models were 0.966, 0.942 and 0.934, respectively. About 57% of the ELM model

  10. Effect of limbal marking prior to laser ablation on the magnitude of cyclotorsional error.

    PubMed

    Chen, Xiangjun; Stojanovic, Aleksandar; Stojanovic, Filip; Eidet, Jon Roger; Raeder, Sten; Øritsland, Haakon; Utheim, Tor Paaske

    2012-05-01

    To evaluate the residual registration error after limbal-marking-based manual adjustment in cyclotorsional tracker-controlled laser refractive surgery. Two hundred eyes undergoing custom surface ablation with the iVIS Suite (iVIS Technologies) were divided into limbal marked (marked) and non-limbal marked (unmarked) groups. Iris registration information was acquired preoperatively from all eyes. Preoperatively, the horizontal axis was recorded in the marked group for use in manual cyclotorsional alignment prior to surgical iris registration. During iris registration, the preoperative iris information was compared to the eye-tracker captured image. The magnitudes of the registration error angle and cyclotorsional movement during the subsequent laser ablation were recorded and analyzed. Mean magnitude of registration error angle (absolute value) was 1.82°±1.31° (range: 0.00° to 5.50°) and 2.90°±2.40° (range: 0.00° to 13.50°) for the marked and unmarked groups, respectively (P<.001). Mean magnitude of cyclotorsional movement during the laser ablation (absolute value) was 1.15°±1.34° (range: 0.00° to 7.00°) and 0.68°±0.97° (range: 0.00° to 6.00°) for the marked and unmarked groups, respectively (P=.005). Forty-six percent and 60% of eyes had registration error >2°, whereas 22% and 20% of eyes had cyclotorsional movement during ablation >2° in the marked and unmarked groups, respectively. Limbal-marking-based manual alignment prior to laser ablation significantly reduced cyclotorsional registration error. However, residual registration misalignment and cyclotorsional movements remained during ablation. Copyright 2012, SLACK Incorporated.

  11. 20 CFR 404.1205 - Absolute coverage groups.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 20 Employees' Benefits 2 2014-04-01 2014-04-01 false Absolute coverage groups. 404.1205 Section... INSURANCE (1950- ) Coverage of Employees of State and Local Governments What Groups of Employees May Be Covered § 404.1205 Absolute coverage groups. (a) General. An absolute coverage group is a permanent...

  12. 20 CFR 404.1205 - Absolute coverage groups.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 20 Employees' Benefits 2 2013-04-01 2013-04-01 false Absolute coverage groups. 404.1205 Section... INSURANCE (1950- ) Coverage of Employees of State and Local Governments What Groups of Employees May Be Covered § 404.1205 Absolute coverage groups. (a) General. An absolute coverage group is a permanent...

  13. 20 CFR 404.1205 - Absolute coverage groups.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 20 Employees' Benefits 2 2012-04-01 2012-04-01 false Absolute coverage groups. 404.1205 Section... INSURANCE (1950- ) Coverage of Employees of State and Local Governments What Groups of Employees May Be Covered § 404.1205 Absolute coverage groups. (a) General. An absolute coverage group is a permanent...

  14. Uncertainty Analysis of Downscaled CMIP5 Precipitation Data for Louisiana, USA

    NASA Astrophysics Data System (ADS)

    Sumi, S. J.; Tamanna, M.; Chivoiu, B.; Habib, E. H.

    2014-12-01

    The downscaled CMIP3 and CMIP5 Climate and Hydrology Projections dataset contains fine spatial resolution translations of climate projections over the contiguous United States developed using two downscaling techniques (monthly Bias Correction Spatial Disaggregation (BCSD) and daily Bias Correction Constructed Analogs (BCCA)). The objective of this study is to assess the uncertainty of the CMIP5 downscaled general circulation models (GCM). We performed an analysis of the daily, monthly, seasonal and annual variability of precipitation downloaded from the Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections website for the state of Louisiana, USA at 0.125° x 0.125° resolution. A data set of daily gridded observations of precipitation of a rectangular boundary covering Louisiana is used to assess the validity of 21 downscaled GCMs for the 1950-1999 period. The following statistics are computed using the CMIP5 observed dataset with respect to the 21 models: the correlation coefficient, the bias, the normalized bias, the mean absolute error (MAE), the mean absolute percentage error (MAPE), and the root mean square error (RMSE). A measure of variability simulated by each model is computed as the ratio of its standard deviation, in both space and time, to the corresponding standard deviation of the observation. The correlation and MAPE statistics are also computed for each of the nine climate divisions of Louisiana. Some of the patterns that we observed are: 1) Average annual precipitation rate shows similar spatial distribution for all the models within a range of 3.27 to 4.75 mm/day from Northwest to Southeast. 2) Standard deviation of summer (JJA) precipitation (mm/day) for the models maintains lower value than the observation whereas they have similar spatial patterns and range of values in winter (NDJ). 3) Correlation coefficients of annual precipitation of models against observation have a range of -0.48 to 0.36 with variable spatial distribution by model

  15. Impact and quantification of the sources of error in DNA pooling designs.

    PubMed

    Jawaid, A; Sham, P

    2009-01-01

    The analysis of genome wide variation offers the possibility of unravelling the genes involved in the pathogenesis of disease. Genome wide association studies are also particularly useful for identifying and validating targets for therapeutic intervention as well as for detecting markers for drug efficacy and side effects. The cost of such large-scale genetic association studies may be reduced substantially by the analysis of pooled DNA from multiple individuals. However, experimental errors inherent in pooling studies lead to a potential increase in the false positive rate and a loss in power compared to individual genotyping. Here we quantify various sources of experimental error using empirical data from typical pooling experiments and corresponding individual genotyping counts using two statistical methods. We provide analytical formulas for calculating these different errors in the absence of complete information, such as replicate pool formation, and for adjusting for the errors in the statistical analysis. We demonstrate that DNA pooling has the potential of estimating allele frequencies accurately, and adjusting the pooled allele frequency estimates for differential allelic amplification considerably improves accuracy. Estimates of the components of error show that differential allelic amplification is the most important contributor to the error variance in absolute allele frequency estimation, followed by allele frequency measurement and pool formation errors. Our results emphasise the importance of minimising experimental errors and obtaining correct error estimates in genetic association studies.

  16. Linearly Supporting Feature Extraction for Automated Estimation of Stellar Atmospheric Parameters

    NASA Astrophysics Data System (ADS)

    Li, Xiangru; Lu, Yu; Comte, Georges; Luo, Ali; Zhao, Yongheng; Wang, Yongjun

    2015-05-01

    We describe a scheme to extract linearly supporting (LSU) features from stellar spectra to automatically estimate the atmospheric parameters {{T}{\\tt{eff} }}, log g, and [Fe/H]. “Linearly supporting” means that the atmospheric parameters can be accurately estimated from the extracted features through a linear model. The successive steps of the process are as follow: first, decompose the spectrum using a wavelet packet (WP) and represent it by the derived decomposition coefficients; second, detect representative spectral features from the decomposition coefficients using the proposed method Least Absolute Shrinkage and Selection Operator (LARS)bs; third, estimate the atmospheric parameters {{T}{\\tt{eff} }}, log g, and [Fe/H] from the detected features using a linear regression method. One prominent characteristic of this scheme is its ability to evaluate quantitatively the contribution of each detected feature to the atmospheric parameter estimate and also to trace back the physical significance of that feature. This work also shows that the usefulness of a component depends on both the wavelength and frequency. The proposed scheme has been evaluated on both real spectra from the Sloan Digital Sky Survey (SDSS)/SEGUE and synthetic spectra calculated from Kurucz's NEWODF models. On real spectra, we extracted 23 features to estimate {{T}{\\tt{eff} }}, 62 features for log g, and 68 features for [Fe/H]. Test consistencies between our estimates and those provided by the Spectroscopic Parameter Pipeline of SDSS show that the mean absolute errors (MAEs) are 0.0062 dex for log {{T}{\\tt{eff} }} (83 K for {{T}{\\tt{eff} }}), 0.2345 dex for log g, and 0.1564 dex for [Fe/H]. For the synthetic spectra, the MAE test accuracies are 0.0022 dex for log {{T}{\\tt{eff} }} (32 K for {{T}{\\tt{eff} }}), 0.0337 dex for log g, and 0.0268 dex for [Fe/H].

  17. Error and objectivity: cognitive illusions and qualitative research.

    PubMed

    Paley, John

    2005-07-01

    Psychological research has shown that cognitive illusions, of which visual illusions are just a special case, are systematic and pervasive, raising epistemological questions about how error in all forms of research can be identified and eliminated. The quantitative sciences make use of statistical techniques for this purpose, but it is not clear what the qualitative equivalent is, particularly in view of widespread scepticism about validity and objectivity. I argue that, in the light of cognitive psychology, the 'error question' cannot be dismissed as a positivist obsession, and that the concepts of truth and objectivity are unavoidable. However, they constitute only a 'minimal realism', which does not necessarily bring a commitment to 'absolute' truth, certainty, correspondence, causation, reductionism, or universal laws in its wake. The assumption that it does reflects a misreading of positivism and, ironically, precipitates a 'crisis of legitimation and representation', as described by constructivist authors.

  18. The approach of Bayesian model indicates media awareness of medical errors

    NASA Astrophysics Data System (ADS)

    Ravichandran, K.; Arulchelvan, S.

    2016-06-01

    This research study brings out the factors behind the increase in medical malpractices in the Indian subcontinent in the present day environment and impacts of television media awareness towards it. Increased media reporting of medical malpractices and errors lead to hospitals taking corrective action and improve the quality of medical services that they provide. The model of Cultivation Theory can be used to measure the influence of media in creating awareness of medical errors. The patient's perceptions of various errors rendered by the medical industry from different parts of India were taken up for this study. Bayesian method was used for data analysis and it gives absolute values to indicate satisfaction of the recommended values. To find out the impact of maintaining medical records of a family online by the family doctor in reducing medical malpractices which creates the importance of service quality in medical industry through the ICT.

  19. Assessment of heavy metals in sediments of the Don Hoi Lot area in the Mae Klong estuary, Thailand.

    PubMed

    Pengthamkeerati, Patthra; Kornkanitnan, Narumol; Sawangarreruks, Suchat; Wanichacheva, Nantanit; Wainiphithapong, Chantana; Sananwai, Nipawan

    2013-01-01

    The status and seasonal variation of heavy metals in surface sediment were investigated at Don Hoi Lot, located in the Mae Klong estuary, Thailand. Results revealed that all the measured heavy metals, except Zn, in the sediments had lower concentrations than in other nearby estuaries. Only Zn may be of concern for potential negative effects on estuarine biota in the study area. With the exception of Fe, all the studied heavy metals showed seasonal variation, but the patterns were diverse. Organic matter and the clay fraction in sediments were good sinks for heavy metals, excluding Zn, while Fe and Mn were good catchers. Principal component analysis suggested that Zn might have different origins and/or mechanisms of transport, accumulation and circulation, compared with the other heavy metals studied. A better understanding of sources and the behavior of Zn would enhance the efficiency of the estuary management plan in this study area.

  20. Variance computations for functional of absolute risk estimates.

    PubMed

    Pfeiffer, R M; Petracci, E

    2011-07-01

    We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.

  1. Variance computations for functional of absolute risk estimates

    PubMed Central

    Pfeiffer, R.M.; Petracci, E.

    2011-01-01

    We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates. PMID:21643476

  2. Cost Prediction Using a Survival Grouping Algorithm: An Application to Incident Prostate Cancer Cases.

    PubMed

    Onukwugha, Eberechukwu; Qi, Ran; Jayasekera, Jinani; Zhou, Shujia

    2016-02-01

    Prognostic classification approaches are commonly used in clinical practice to predict health outcomes. However, there has been limited focus on use of the general approach for predicting costs. We applied a grouping algorithm designed for large-scale data sets and multiple prognostic factors to investigate whether it improves cost prediction among older Medicare beneficiaries diagnosed with prostate cancer. We analysed the linked Surveillance, Epidemiology and End Results (SEER)-Medicare data, which included data from 2000 through 2009 for men diagnosed with incident prostate cancer between 2000 and 2007. We split the survival data into two data sets (D0 and D1) of equal size. We trained the classifier of the Grouping Algorithm for Cancer Data (GACD) on D0 and tested it on D1. The prognostic factors included cancer stage, age, race and performance status proxies. We calculated the average difference between observed D1 costs and predicted D1 costs at 5 years post-diagnosis with and without the GACD. The sample included 110,843 men with prostate cancer. The median age of the sample was 74 years, and 10% were African American. The average difference (mean absolute error [MAE]) per person between the real and predicted total 5-year cost was US$41,525 (MAE US$41,790; 95% confidence interval [CI] US$41,421-42,158) with the GACD and US$43,113 (MAE US$43,639; 95% CI US$43,062-44,217) without the GACD. The 5-year cost prediction without grouping resulted in a sample overestimate of US$79,544,508. The grouping algorithm developed for complex, large-scale data improves the prediction of 5-year costs. The prediction accuracy could be improved by utilization of a richer set of prognostic factors and refinement of categorical specifications.

  3. Data Fusion of Gridded Snow Products Enhanced with Terrain Covariates and a Simple Snow Model

    NASA Astrophysics Data System (ADS)

    Snauffer, A. M.; Hsieh, W. W.; Cannon, A. J.

    2017-12-01

    Hydrologic planning requires accurate estimates of regional snow water equivalent (SWE), particularly areas with hydrologic regimes dominated by spring melt. While numerous gridded data products provide such estimates, accurate representations are particularly challenging under conditions of mountainous terrain, heavy forest cover and large snow accumulations, contexts which in many ways define the province of British Columbia (BC), Canada. One promising avenue of improving SWE estimates is a data fusion approach which combines field observations with gridded SWE products and relevant covariates. A base artificial neural network (ANN) was constructed using three of the best performing gridded SWE products over BC (ERA-Interim/Land, MERRA and GLDAS-2) and simple location and time covariates. This base ANN was then enhanced to include terrain covariates (slope, aspect and Terrain Roughness Index, TRI) as well as a simple 1-layer energy balance snow model driven by gridded bias-corrected ANUSPLIN temperature and precipitation values. The ANN enhanced with all aforementioned covariates performed better than the base ANN, but most of the skill improvement was attributable to the snow model with very little contribution from the terrain covariates. The enhanced ANN improved station mean absolute error (MAE) by an average of 53% relative to the composing gridded products over the province. Interannual peak SWE correlation coefficient was found to be 0.78, an improvement of 0.05 to 0.18 over the composing products. This nonlinear approach outperformed a comparable multiple linear regression (MLR) model by 22% in MAE and 0.04 in interannual correlation. The enhanced ANN has also been shown to estimate better than the Variable Infiltration Capacity (VIC) hydrologic model calibrated and run for four BC watersheds, improving MAE by 22% and correlation by 0.05. The performance improvements of the enhanced ANN are statistically significant at the 5% level across the province and

  4. Scheimpflug camera combined with placido-disk corneal topography and optical biometry for intraocular lens power calculation.

    PubMed

    Kirgiz, Ahmet; Atalay, Kurşat; Kaldirim, Havva; Cabuk, Kubra Serefoglu; Akdemir, Mehmet Orcun; Taskapili, Muhittin

    2017-08-01

    The purpose of this study was to compare the keratometry (K) values obtained by the Scheimpflug camera combined with placido-disk corneal topography (Sirius) and optical biometry (Lenstar) for intraocular lens (IOL) power calculation before the cataract surgery, and to evaluate the accuracy of postoperative refraction. 50 eyes of 40 patients were scheduled to have phacoemulsification with the implantation of a posterior chamber intraocular lens. The IOL power was calculated using the SRK/T formula with Lenstar K and K readings from Sirius. Simulated K (SimK), K at 3-, 5-, and 7-mm zones from Sirius were compared with Lenstar K readings. The accuracy of these parameters was determined by calculating the mean absolute error (MAE). The mean Lenstar K value was 44.05 diopters (D) ±1.93 (SD) and SimK, K at 3-, 5-, and 7-mm zones were 43.85 ± 1.91, 43.88 ± 1.9, 43.84 ± 1.9, 43.66 ± 1.85 D, respectively. There was no statistically significant difference between the K readings (P = 0.901). When Lenstar was used for the corneal power measurements, MAE was 0.42 ± 0.33 D, but when simK of Sirius was used, it was 0.37 ± 0.32 D (the lowest MAE (0.36 ± 0.32 D) was achieved as a result of 5 mm K measurement), but it was not statistically significant (P = 0.892). Of all the K readings of Sirius and Lenstar, Sirius 5-mm zone K readings were the best in predicting a more precise IOL power. The corneal power measurements with the Scheimpflug camera combined with placido-disk corneal topography can be safely used for IOL power calculation.

  5. Self-attraction effect and correction on the T-1 absolute gravimeter

    NASA Astrophysics Data System (ADS)

    Li, Z.; Hu, H.; Wu, K.; Li, G.; Wang, G.; Wang, L. J.

    2015-12-01

    The self-attraction effect (SAE) in an absolute gravimeter is a kind of systematic error due to the gravitation of the instrument to the falling object. This effect depends on the mass distribution of the gravimeter, and is estimated to be a few microgals (1 μGal  =  10-8 m s-2) for the FG5 gravimeter. In this paper, the SAE of a home-made T-1 absolute gravimeter is analyzed and calculated. Most of the stationary components, including the dropping chamber, the laser interferometer, the vibration isolation device and two tripods, are finely modelled, and the related SAEs are computed. In addition, the SAE of the co-falling carriage inside the dropping chamber is carefully calculated because the distance between the falling object and the co-falling carriage varies during the measurement. In order to get the correction of the SAE, two different methods are compared. One is to linearize the SAE curve, the other one is to calculate the perturbed trajectory. The results from these two methods agree with each other within 0.01 μGal. With an uncertainty analysis, the correction of the SAE of the T-1 gravimeter is estimated to be (-1.9  ±  0.1) μGal.

  6. Absolute and relative emissions analysis in practical combustion systems—effect of water vapor condensation

    NASA Astrophysics Data System (ADS)

    Richter, J. P.; Mollendorf, J. C.; DesJardin, P. E.

    2016-11-01

    Accurate knowledge of the absolute combustion gas composition is necessary in the automotive, aircraft, processing, heating and air conditioning industries where emissions reduction is a major concern. Those industries use a variety of sensor technologies. Many of these sensors are used to analyze the gas by pumping a sample through a system of tubes to reach a remote sensor location. An inherent characteristic with this type of sampling strategy is that the mixture state changes as the sample is drawn towards the sensor. Specifically, temperature and humidity changes can be significant, resulting in a very different gas mixture at the sensor interface compared with the in situ location (water vapor dilution effect). Consequently, the gas concentrations obtained from remotely sampled gas analyzers can be significantly different than in situ values. In this study, inherent errors associated with sampled combustion gas concentration measurements are explored, and a correction methodology is presented to determine the absolute gas composition from remotely measured gas species concentrations. For in situ (wet) measurements a heated zirconium dioxide (ZrO2) oxygen sensor (Bosch LSU 4.9) is used to measure the absolute oxygen concentration. This is used to correct the remotely sampled (dry) measurements taken with an electrochemical sensor within the remote analyzer (Testo 330-2LL). In this study, such a correction is experimentally validated for a specified concentration of carbon monoxide (5020 ppmv).

  7. Method for the fabrication error calibration of the CGH used in the cylindrical interferometry system

    NASA Astrophysics Data System (ADS)

    Wang, Qingquan; Yu, Yingjie; Mou, Kebing

    2016-10-01

    This paper presents a method of absolutely calibrating the fabrication error of the CGH in the cylindrical interferometry system for the measurement of cylindricity error. First, a simulated experimental system is set up in ZEMAX. On one hand, the simulated experimental system has demonstrated the feasibility of the method we proposed. On the other hand, by changing the different positions of the mirror in the simulated experimental system, a misalignment aberration map, consisting of the different interferograms in different positions, is acquired. And it can be acted as a reference for the experimental adjustment in real system. Second, the mathematical polynomial, which describes the relationship between the misalignment aberrations and the possible misalignment errors, is discussed.

  8. Absolute Summ

    NASA Astrophysics Data System (ADS)

    Phillips, Alfred, Jr.

    Summ means the entirety of the multiverse. It seems clear, from the inflation theories of A. Guth and others, that the creation of many universes is plausible. We argue that Absolute cosmological ideas, not unlike those of I. Newton, may be consistent with dynamic multiverse creations. As suggested in W. Heisenberg's uncertainty principle, and with the Anthropic Principle defended by S. Hawking, et al., human consciousness, buttressed by findings of neuroscience, may have to be considered in our models. Predictability, as A. Einstein realized with Invariants and General Relativity, may be required for new ideas to be part of physics. We present here a two postulate model geared to an Absolute Summ. The seedbed of this work is part of Akhnaton's philosophy (see S. Freud, Moses and Monotheism). Most important, however, is that the structure of human consciousness, manifest in Kenya's Rift Valley 200,000 years ago as Homo sapiens, who were the culmination of the six million year co-creation process of Hominins and Nature in Africa, allows us to do the physics that we do. .

  9. Screening of the Antimicrobial Activity against Drug Resistant Bacteria of Photorhabdus and Xenorhabdus Associated with Entomopathogenic Nematodes from Mae Wong National Park, Thailand

    PubMed Central

    Muangpat, Paramaporn; Yooyangket, Temsiri; Fukruksa, Chamaiporn; Suwannaroj, Manawat; Yimthin, Thatcha; Sitthisak, Sutthirat; Chantratita, Narisara; Vitta, Apichat; Tobias, Nicholas J.; Bode, Helge B.; Thanwisai, Aunchalee

    2017-01-01

    Photorhabdus and Xenorhabdus are symbiotic with entomopathogenic nematodes (EPNs) of the genera Heterorhabditis and Steinernema, respectively. These bacteria produce several secondary metabolites including antimicrobial compounds. The objectives of this study were to isolate and identify EPNs and their symbiotic bacteria from Mae Wong National Park, Thailand and to evaluate the antibacterial activities of symbiont extracts against drug resistant bacteria. A total of 550 soil samples from 110 sites were collected between August 2014 and July 2015. A total of EPN isolates were obtained through baiting and White trap methods, which yielded 21 Heterorhabditis and 3 Steinernema isolates. Based on molecular identification and phylogenetic analysis, the most common species found in the present study was P. luminescens subsp. akhurstii associated with H. indica. Notably, two species of EPNs, H. zealandica and S. kushidai, and two species of symbiotic bacteria, X. japonica and P. temperata subsp. temperata represented new recorded organisms in Thailand. Furthermore, the association between P. temperata subsp. temperata and H. zealandica has not previously been reported worldwide. Disk diffusion, minimal inhibitory concentration, and minimal bactericidal concentration analyses demonstrated that the crude compound extracted by ethyl acetate from P. temperata subsp. temperata could inhibit the growth of up to 10 strains of drug resistant bacteria. Based on HPLC-MS analysis, compound classes in bacterial extracts were identified as GameXPeptide, xenoamicin, xenocoumacin, mevalagmapeptide phurealipids derivatives, and isopropylstilbene. Together, the results of this study provide evidence for the diversity of EPNs and their symbiotic bacteria in Mae Wong National Park, Thailand and demonstrate their novel associations. These findings also provide an important foundation for further research regarding the antimicrobial activity of Photorhabdus bacteria. PMID:28702004

  10. Drought forecasting in eastern Australia using multivariate adaptive regression spline, least square support vector machine and M5Tree model

    NASA Astrophysics Data System (ADS)

    Deo, Ravinesh C.; Kisi, Ozgur; Singh, Vijay P.

    2017-02-01

    Drought forecasting using standardized metrics of rainfall is a core task in hydrology and water resources management. Standardized Precipitation Index (SPI) is a rainfall-based metric that caters for different time-scales at which the drought occurs, and due to its standardization, is well-suited for forecasting drought at different periods in climatically diverse regions. This study advances drought modelling using multivariate adaptive regression splines (MARS), least square support vector machine (LSSVM), and M5Tree models by forecasting SPI in eastern Australia. MARS model incorporated rainfall as mandatory predictor with month (periodicity), Southern Oscillation Index, Pacific Decadal Oscillation Index and Indian Ocean Dipole, ENSO Modoki and Nino 3.0, 3.4 and 4.0 data added gradually. The performance was evaluated with root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (r2). Best MARS model required different input combinations, where rainfall, sea surface temperature and periodicity were used for all stations, but ENSO Modoki and Pacific Decadal Oscillation indices were not required for Bathurst, Collarenebri and Yamba, and the Southern Oscillation Index was not required for Collarenebri. Inclusion of periodicity increased the r2 value by 0.5-8.1% and reduced RMSE by 3.0-178.5%. Comparisons showed that MARS superseded the performance of the other counterparts for three out of five stations with lower MAE by 15.0-73.9% and 7.3-42.2%, respectively. For the other stations, M5Tree was better than MARS/LSSVM with lower MAE by 13.8-13.4% and 25.7-52.2%, respectively, and for Bathurst, LSSVM yielded more accurate result. For droughts identified by SPI ≤ - 0.5, accurate forecasts were attained by MARS/M5Tree for Bathurst, Yamba and Peak Hill, whereas for Collarenebri and Barraba, M5Tree was better than LSSVM/MARS. Seasonal analysis revealed disparate results where MARS/M5Tree was better than LSSVM. The results highlight the

  11. Reconstruction of hyperspectral reflectance for optically complex turbid inland lakes: test of a new scheme and implications for inversion algorithms.

    PubMed

    Sun, Deyong; Hu, Chuanmin; Qiu, Zhongfeng; Wang, Shengqiang

    2015-06-01

    A new scheme has been proposed by Lee et al. (2014) to reconstruct hyperspectral (400 - 700 nm, 5 nm resolution) remote sensing reflectance (Rrs(λ), sr-1) of representative global waters using measurements at 15 spectral bands. This study tested its applicability to optically complex turbid inland waters in China, where Rrs(λ) are typically much higher than those used in Lee et al. (2014). Strong interdependence of Rrs(λ) between neighboring bands (≤ 10 nm interval) was confirmed, with Pearson correlation coefficient (PCC) mostly above 0.98. The scheme of Lee et al. (2014) for Rrs(λ) re-construction with its original global parameterization worked well with this data set, while new parameterization showed improvement in reducing uncertainties in the reconstructed Rrs(λ). Mean absolute error (MAERrsi)) in the reconstructed Rrs(λ) was mostly < 0.0002 sr-1 between 400 and 700nm, and mean relative error (MRERrsi)) was < 1% when the comparison was made between reconstructed and measured Rrs(λ) spectra. When Rrs(λ) at the MODIS bands were used to reconstruct the hyperspectral Rrs(λ), MAERrsi) was < 0.001 sr-1 and MRERrsi) was < 3%. When Rrs(λ) at the MERIS bands were used, MAERrsi) in the reconstructed hyperspectral Rrs(λ) was < 0.0004 sr-1 and MRERrsi) was < 1%. These results have significant implications for inversion algorithms to retrieve concentrations of phytoplankton pigments (e.g., chlorophyll-a or Chla, and phycocyanin or PC) and total suspended materials (TSM) as well as absorption coefficient of colored dissolved organic matter (CDOM), as some of the algorithms were developed from in situ Rrs(λ) data using spectral bands that

  12. Dynamic diagnostics of the error fields in tokamaks

    NASA Astrophysics Data System (ADS)

    Pustovitov, V. D.

    2007-07-01

    The error field diagnostics based on magnetic measurements outside the plasma is discussed. The analysed methods rely on measuring the plasma dynamic response to the finite-amplitude external magnetic perturbations, which are the error fields and the pre-programmed probing pulses. Such pulses can be created by the coils designed for static error field correction and for stabilization of the resistive wall modes, the technique developed and applied in several tokamaks, including DIII-D and JET. Here analysis is based on the theory predictions for the resonant field amplification (RFA). To achieve the desired level of the error field correction in tokamaks, the diagnostics must be sensitive to signals of several Gauss. Therefore, part of the measurements should be performed near the plasma stability boundary, where the RFA effect is stronger. While the proximity to the marginal stability is important, the absolute values of plasma parameters are not. This means that the necessary measurements can be done in the diagnostic discharges with parameters below the nominal operating regimes, with the stability boundary intentionally lowered. The estimates for ITER are presented. The discussed diagnostics can be tested in dedicated experiments in existing tokamaks. The diagnostics can be considered as an extension of the 'active MHD spectroscopy' used recently in the DIII-D tokamak and the EXTRAP T2R reversed field pinch.

  13. Absolute optical metrology : nanometers to kilometers

    NASA Technical Reports Server (NTRS)

    Dubovitsky, Serge; Lay, O. P.; Peters, R. D.; Liebe, C. C.

    2005-01-01

    We provide and overview of the developments in the field of high-accuracy absolute optical metrology with emphasis on space-based applications. Specific work on the Modulation Sideband Technology for Absolute Ranging (MSTAR) sensor is described along with novel applications of the sensor.

  14. Oversight of Student Loan Marketing Association (Sallie Mae). Hearing Before the Subcommittee on Education, Arts and Humanities of the Committee on Labor and Human Resources. United States Senate, Ninety-Seventh Congress, Second Session.

    ERIC Educational Resources Information Center

    Congress of the U.S., Washington, DC. Senate Committee on Labor and Human Resources.

    Hearings concerning the activities of the Student Loan Marketing Association (Sallie Mae) are presented. Attention is focused on a request for an exemption under federal priority for recovering money owed the Association in the event that it files for liquidation or reorganization in the future under the Bankruptcy Act. It is noted that two goals…

  15. A global algorithm for estimating Absolute Salinity

    NASA Astrophysics Data System (ADS)

    McDougall, T. J.; Jackett, D. R.; Millero, F. J.; Pawlowicz, R.; Barker, P. M.

    2012-12-01

    The International Thermodynamic Equation of Seawater - 2010 has defined the thermodynamic properties of seawater in terms of a new salinity variable, Absolute Salinity, which takes into account the spatial variation of the composition of seawater. Absolute Salinity more accurately reflects the effects of the dissolved material in seawater on the thermodynamic properties (particularly density) than does Practical Salinity. When a seawater sample has standard composition (i.e. the ratios of the constituents of sea salt are the same as those of surface water of the North Atlantic), Practical Salinity can be used to accurately evaluate the thermodynamic properties of seawater. When seawater is not of standard composition, Practical Salinity alone is not sufficient and the Absolute Salinity Anomaly needs to be estimated; this anomaly is as large as 0.025 g kg-1 in the northernmost North Pacific. Here we provide an algorithm for estimating Absolute Salinity Anomaly for any location (x, y, p) in the world ocean. To develop this algorithm, we used the Absolute Salinity Anomaly that is found by comparing the density calculated from Practical Salinity to the density measured in the laboratory. These estimates of Absolute Salinity Anomaly however are limited to the number of available observations (namely 811). In order to provide a practical method that can be used at any location in the world ocean, we take advantage of approximate relationships between Absolute Salinity Anomaly and silicate concentrations (which are available globally).

  16. EIT Imaging of admittivities with a D-bar method and spatial prior: experimental results for absolute and difference imaging.

    PubMed

    Hamilton, S J

    2017-05-22

    Electrical impedance tomography (EIT) is an emerging imaging modality that uses harmless electrical measurements taken on electrodes at a body's surface to recover information about the internal electrical conductivity and or permittivity. The image reconstruction task of EIT is a highly nonlinear inverse problem that is sensitive to noise and modeling errors making the image reconstruction task challenging. D-bar methods solve the nonlinear problem directly, bypassing the need for detailed and time-intensive forward models, to provide absolute (static) as well as time-difference EIT images. Coupling the D-bar methodology with the inclusion of high confidence a priori data results in a noise-robust regularized image reconstruction method. In this work, the a priori D-bar method for complex admittivities is demonstrated effective on experimental tank data for absolute imaging for the first time. Additionally, the method is adjusted for, and tested on, time-difference imaging scenarios. The ability of the method to be used for conductivity, permittivity, absolute as well as time-difference imaging provides the user with great flexibility without a high computational cost.

  17. Absolute instability of the Gaussian wake profile

    NASA Technical Reports Server (NTRS)

    Hultgren, Lennart S.; Aggarwal, Arun K.

    1987-01-01

    Linear parallel-flow stability theory has been used to investigate the effect of viscosity on the local absolute instability of a family of wake profiles with a Gaussian velocity distribution. The type of local instability, i.e., convective or absolute, is determined by the location of a branch-point singularity with zero group velocity of the complex dispersion relation for the instability waves. The effects of viscosity were found to be weak for values of the wake Reynolds number, based on the center-line velocity defect and the wake half-width, larger than about 400. Absolute instability occurs only for sufficiently large values of the center-line wake defect. The critical value of this parameter increases with decreasing wake Reynolds number, thereby indicating a shrinking region of absolute instability with decreasing wake Reynolds number. If backflow is not allowed, absolute instability does not occur for wake Reynolds numbers smaller than about 38.

  18. The Use of Neural Networks in Identifying Error Sources in Satellite-Derived Tropical SST Estimates

    PubMed Central

    Lee, Yung-Hsiang; Ho, Chung-Ru; Su, Feng-Chun; Kuo, Nan-Jung; Cheng, Yu-Hsin

    2011-01-01

    An neural network model of data mining is used to identify error sources in satellite-derived tropical sea surface temperature (SST) estimates from thermal infrared sensors onboard the Geostationary Operational Environmental Satellite (GOES). By using the Back Propagation Network (BPN) algorithm, it is found that air temperature, relative humidity, and wind speed variation are the major factors causing the errors of GOES SST products in the tropical Pacific. The accuracy of SST estimates is also improved by the model. The root mean square error (RMSE) for the daily SST estimate is reduced from 0.58 K to 0.38 K and mean absolute percentage error (MAPE) is 1.03%. For the hourly mean SST estimate, its RMSE is also reduced from 0.66 K to 0.44 K and the MAPE is 1.3%. PMID:22164030

  19. 49 CFR 236.709 - Block, absolute.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 49 Transportation 4 2010-10-01 2010-10-01 false Block, absolute. 236.709 Section 236.709 Transportation Other Regulations Relating to Transportation (Continued) FEDERAL RAILROAD ADMINISTRATION... Block, absolute. A block in which no train is permitted to enter while it is occupied by another train. ...

  20. 49 CFR 236.709 - Block, absolute.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 49 Transportation 4 2011-10-01 2011-10-01 false Block, absolute. 236.709 Section 236.709 Transportation Other Regulations Relating to Transportation (Continued) FEDERAL RAILROAD ADMINISTRATION... Block, absolute. A block in which no train is permitted to enter while it is occupied by another train. ...

  1. Absolute quantification of microbial taxon abundances.

    PubMed

    Props, Ruben; Kerckhof, Frederiek-Maarten; Rubbens, Peter; De Vrieze, Jo; Hernandez Sanabria, Emma; Waegeman, Willem; Monsieurs, Pieter; Hammes, Frederik; Boon, Nico

    2017-02-01

    High-throughput amplicon sequencing has become a well-established approach for microbial community profiling. Correlating shifts in the relative abundances of bacterial taxa with environmental gradients is the goal of many microbiome surveys. As the abundances generated by this technology are semi-quantitative by definition, the observed dynamics may not accurately reflect those of the actual taxon densities. We combined the sequencing approach (16S rRNA gene) with robust single-cell enumeration technologies (flow cytometry) to quantify the absolute taxon abundances. A detailed longitudinal analysis of the absolute abundances resulted in distinct abundance profiles that were less ambiguous and expressed in units that can be directly compared across studies. We further provide evidence that the enrichment of taxa (increase in relative abundance) does not necessarily relate to the outgrowth of taxa (increase in absolute abundance). Our results highlight that both relative and absolute abundances should be considered for a comprehensive biological interpretation of microbiome surveys.

  2. Spot measurement of heart rate based on morphology of PhotoPlethysmoGraphic (PPG) signals.

    PubMed

    Madhan Mohan, P; Nagarajan, V; Vignesh, J C

    2017-02-01

    Due to increasing health consciousness among people, it is imperative to have low-cost health care devices to measure the vital parameters like heart rate and arterial oxygen saturation (SpO 2 ). In this paper, an efficient heart rate monitoring algorithm based on the morphology of photoplethysmography (PPG) signals to measure the spot heart rate (HR) and its real-time implementation is proposed. The algorithm does pre-processing and detects the onsets and systolic peaks of the PPG signal to estimate the heart rate of the subject. Since the algorithm is based on the morphology of the signal, it works well when the subject is not moving, which is a typical test case. So, this algorithm is developed mainly to measure the heart rate at on-demand applications. Real-time experimental results indicate the heart rate accuracy of 99.5%, mean absolute percentage error (MAPE) of 1.65%, mean absolute error (MAE) of 1.18 BPM and reference closeness factor (RCF) of 0.988. The results further show that the average response time of the algorithm to give the spot HR is 6.85 s, so that the users need not wait longer to see their HR. The hardware implementation results show that the algorithm only requires 18 KBytes of total memory and runs at high speed with 0.85 MIPS. So, this algorithm can be targeted to low-cost embedded platforms.

  3. Dimensional Error in Rapid Prototyping with Open Source Software and Low-cost 3D-printer

    PubMed Central

    Andrade-Delgado, Laura; Telich-Tarriba, Jose E.; Fuente-del-Campo, Antonio; Altamirano-Arcos, Carlos A.

    2018-01-01

    Summary: Rapid prototyping models (RPMs) had been extensively used in craniofacial and maxillofacial surgery, especially in areas such as orthognathic surgery, posttraumatic or oncological reconstructions, and implantology. Economic limitations are higher in developing countries such as Mexico, where resources dedicated to health care are limited, therefore limiting the use of RPM to few selected centers. This article aims to determine the dimensional error of a low-cost fused deposition modeling 3D printer (Tronxy P802MA, Shenzhen, Tronxy Technology Co), with Open source software. An ordinary dry human mandible was scanned with a computed tomography device. The data were processed with open software to build a rapid prototype with a fused deposition machine. Linear measurements were performed to find the mean absolute and relative difference. The mean absolute and relative difference was 0.65 mm and 1.96%, respectively (P = 0.96). Low-cost FDM machines and Open Source Software are excellent options to manufacture RPM, with the benefit of low cost and a similar relative error than other more expensive technologies. PMID:29464171

  4. Dimensional Error in Rapid Prototyping with Open Source Software and Low-cost 3D-printer.

    PubMed

    Rendón-Medina, Marco A; Andrade-Delgado, Laura; Telich-Tarriba, Jose E; Fuente-Del-Campo, Antonio; Altamirano-Arcos, Carlos A

    2018-01-01

    Rapid prototyping models (RPMs) had been extensively used in craniofacial and maxillofacial surgery, especially in areas such as orthognathic surgery, posttraumatic or oncological reconstructions, and implantology. Economic limitations are higher in developing countries such as Mexico, where resources dedicated to health care are limited, therefore limiting the use of RPM to few selected centers. This article aims to determine the dimensional error of a low-cost fused deposition modeling 3D printer (Tronxy P802MA, Shenzhen, Tronxy Technology Co), with Open source software. An ordinary dry human mandible was scanned with a computed tomography device. The data were processed with open software to build a rapid prototype with a fused deposition machine. Linear measurements were performed to find the mean absolute and relative difference. The mean absolute and relative difference was 0.65 mm and 1.96%, respectively ( P = 0.96). Low-cost FDM machines and Open Source Software are excellent options to manufacture RPM, with the benefit of low cost and a similar relative error than other more expensive technologies.

  5. [Prediction of soil nutrients spatial distribution based on neural network model combined with goestatistics].

    PubMed

    Li, Qi-Quan; Wang, Chang-Quan; Zhang, Wen-Jiang; Yu, Yong; Li, Bing; Yang, Juan; Bai, Gen-Chuan; Cai, Yan

    2013-02-01

    In this study, a radial basis function neural network model combined with ordinary kriging (RBFNN_OK) was adopted to predict the spatial distribution of soil nutrients (organic matter and total N) in a typical hilly region of Sichuan Basin, Southwest China, and the performance of this method was compared with that of ordinary kriging (OK) and regression kriging (RK). All the three methods produced the similar soil nutrient maps. However, as compared with those obtained by multiple linear regression model, the correlation coefficients between the measured values and the predicted values of soil organic matter and total N obtained by neural network model increased by 12. 3% and 16. 5% , respectively, suggesting that neural network model could more accurately capture the complicated relationships between soil nutrients and quantitative environmental factors. The error analyses of the prediction values of 469 validation points indicated that the mean absolute error (MAE) , mean relative error (MRE), and root mean squared error (RMSE) of RBFNN_OK were 6.9%, 7.4%, and 5. 1% (for soil organic matter), and 4.9%, 6.1% , and 4.6% (for soil total N) smaller than those of OK (P<0.01), and 2.4%, 2.6% , and 1.8% (for soil organic matter), and 2.1%, 2.8%, and 2.2% (for soil total N) smaller than those of RK, respectively (P<0.05).

  6. Absolute Humidity and the Seasonality of Influenza (Invited)

    NASA Astrophysics Data System (ADS)

    Shaman, J. L.; Pitzer, V.; Viboud, C.; Grenfell, B.; Goldstein, E.; Lipsitch, M.

    2010-12-01

    Much of the observed wintertime increase of mortality in temperate regions is attributed to seasonal influenza. A recent re-analysis of laboratory experiments indicates that absolute humidity strongly modulates the airborne survival and transmission of the influenza virus. Here we show that the onset of increased wintertime influenza-related mortality in the United States is associated with anomalously low absolute humidity levels during the prior weeks. We then use an epidemiological model, in which observed absolute humidity conditions temper influenza transmission rates, to successfully simulate the seasonal cycle of observed influenza-related mortality. The model results indicate that direct modulation of influenza transmissibility by absolute humidity alone is sufficient to produce this observed seasonality. These findings provide epidemiological support for the hypothesis that absolute humidity drives seasonal variations of influenza transmission in temperate regions. In addition, we show that variations of the basic and effective reproductive numbers for influenza, caused by seasonal changes in absolute humidity, are consistent with the general timing of pandemic influenza outbreaks observed for 2009 A/H1N1 in temperate regions. Indeed, absolute humidity conditions correctly identify the region of the United States vulnerable to a third, wintertime wave of pandemic influenza. These findings suggest that the timing of pandemic influenza outbreaks is controlled by a combination of absolute humidity conditions, levels of susceptibility and changes in population mixing and contact rates.

  7. Laboratory Study of Quaternary Sediment Resistivity Related to Groundwater Contamination at Mae-Hia Landfill, Mueang District, Chiang Mai Province

    NASA Astrophysics Data System (ADS)

    Sichan, N.

    2007-12-01

    This study was aimed to understand the nature of the resistivity value of the sediment when it is contaminated, in order to use the information solving the obscure interpretation in the field. The pilot laboratory experiments were designed to simulate various degree of contamination and degree of saturation then observe the resulting changes in resistivity. The study was expected to get a better understanding of how various physical parameters effect the resistivity values in term of mathematic function. And also expected to apply those obtained function to a practical quantitatively interpretation. The sediment underlying the Mae-Hia Landfill consists of clay-rich material, with interfingerings of colluvium and sandy alluvium. A systematic study identified four kinds of sediment, sand, clayey sand, sandy clay, and clay. Representative sediment and leachate samples were taken from the field and returned to the laboratory. Both the physical and chemical properties of the sediments and leachate were analyzed to delineate the necessary parameters that could be used in Archie's equation. Sediment samples were mixed with various concentration of leachate solutions. Then the resistivity values were measured at various controlled steps in the saturation degree in a well- calibrated six-electrode model resistivity box. The measured resistivity values for sand, clayey sand, sandy clay when fully and partly saturated were collected, then plotted and fitted to Archie's equation, to obtain a mathematical relationship between bulk resistivity, porosity, saturation degree and resistivity of pore fluid. The results fit well to Archie's equation, and it was possible to determine all the unknown parameters representative of the sediment samples. For sand, clayey sand, sandy clay, and clay, the formation resistivity factors (F) are 2.90, 5.77, 7.85, and 7.85 with the products of cementation factor (m) and the pore geometry factors (a) (in term of -am) are 1.49, -1.63, -1.92, -2

  8. Modeling the Error of the Medtronic Paradigm Veo Enlite Glucose Sensor.

    PubMed

    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.

  9. Low absolute neutrophil counts in African infants.

    PubMed

    Kourtis, Athena P; Bramson, Brian; van der Horst, Charles; Kazembe, Peter; Ahmed, Yusuf; Chasela, Charles; Hosseinipour, Mina; Knight, Rodney; Lugalia, Lebah; Tegha, Gerald; Joaki, George; Jafali, Robert; Jamieson, Denise J

    2005-07-01

    Infants of African origin have a lower normal range of absolute neutrophil counts than white infants; this fact, however, remains under appreciated by clinical researchers in the United States. During the initial stages of a clinical trial in Malawi, the authors noted an unexpectedly high number of infants with absolute neutrophil counts that would be classifiable as neutropenic using the National Institutes of Health's Division of AIDS toxicity tables. The authors argue that the relevant Division of AIDS table does not take into account the available evidence of low absolute neutrophil counts in African infants and that a systematic collection of data from many African settings might help establish the absolute neutrophil count cutpoints to be used for defining neutropenia in African populations.

  10. Absolute colorimetric characterization of a DSLR camera

    NASA Astrophysics Data System (ADS)

    Guarnera, Giuseppe Claudio; Bianco, Simone; Schettini, Raimondo

    2014-03-01

    A simple but effective technique for absolute colorimetric camera characterization is proposed. It offers a large dynamic range requiring just a single, off-the-shelf target and a commonly available controllable light source for the characterization. The characterization task is broken down in two modules, respectively devoted to absolute luminance estimation and to colorimetric characterization matrix estimation. The characterized camera can be effectively used as a tele-colorimeter, giving an absolute estimation of the XYZ data in cd=m2. The user is only required to vary the f - number of the camera lens or the exposure time t, to better exploit the sensor dynamic range. The estimated absolute tristimulus values closely match the values measured by a professional spectro-radiometer.

  11. Full-Field Calibration of Color Camera Chromatic Aberration using Absolute Phase Maps.

    PubMed

    Liu, Xiaohong; Huang, Shujun; Zhang, Zonghua; Gao, Feng; Jiang, Xiangqian

    2017-05-06

    The refractive index of a lens varies for different wavelengths of light, and thus the same incident light with different wavelengths has different outgoing light. This characteristic of lenses causes images captured by a color camera to display chromatic aberration (CA), which seriously reduces image quality. Based on an analysis of the distribution of CA, a full-field calibration method based on absolute phase maps is proposed in this paper. Red, green, and blue closed sinusoidal fringe patterns are generated, consecutively displayed on an LCD (liquid crystal display), and captured by a color camera from the front viewpoint. The phase information of each color fringe is obtained using a four-step phase-shifting algorithm and optimum fringe number selection method. CA causes the unwrapped phase of the three channels to differ. These pixel deviations can be computed by comparing the unwrapped phase data of the red, blue, and green channels in polar coordinates. CA calibration is accomplished in Cartesian coordinates. The systematic errors introduced by the LCD are analyzed and corrected. Simulated results show the validity of the proposed method and experimental results demonstrate that the proposed full-field calibration method based on absolute phase maps will be useful for practical software-based CA calibration.

  12. Forecasting air quality time series using deep learning.

    PubMed

    Freeman, Brian S; Taylor, Graham; Gharabaghi, Bahram; Thé, Jesse

    2018-04-13

    This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality management relies extensively on time series data captured at air monitoring stations as the basis of identifying population exposure to airborne pollutants and determining compliance with local ambient air standards. In this paper, 8 hr averaged surface ozone (O 3 ) concentrations were predicted using deep learning consisting of a recurrent neural network (RNN) with long short-term memory (LSTM). Hourly air quality and meteorological data were used to train and forecast values up to 72 hours with low error rates. The LSTM was able to forecast the duration of continuous O 3 exceedances as well. Prior to training the network, the dataset was reviewed for missing data and outliers. Missing data were imputed using a novel technique that averaged gaps less than eight time steps with incremental steps based on first-order differences of neighboring time periods. Data were then used to train decision trees to evaluate input feature importance over different time prediction horizons. The number of features used to train the LSTM model was reduced from 25 features to 5 features, resulting in improved accuracy as measured by Mean Absolute Error (MAE). Parameter sensitivity analysis identified look-back nodes associated with the RNN proved to be a significant source of error if not aligned with the prediction horizon. Overall, MAE's less than 2 were calculated for predictions out to 72 hours. Novel deep learning techniques were used to train an 8-hour averaged ozone forecast model. Missing data and outliers within the captured data set were replaced using a new imputation method that generated calculated values closer to the expected value based on the time and season. Decision trees were used to identify input variables with the greatest importance. The methods presented in this paper allow air managers to forecast long range air pollution

  13. The stars: an absolute radiometric reference for the on-orbit calibration of PLEIADES-HR satellites

    NASA Astrophysics Data System (ADS)

    Meygret, Aimé; Blanchet, Gwendoline; Mounier, Flore; Buil, Christian

    2017-09-01

    The accurate on-orbit radiometric calibration of optical sensors has become a challenge for space agencies who gather their effort through international working groups such as CEOS/WGCV or GSICS with the objective to insure the consistency of space measurements and to reach an absolute accuracy compatible with more and more demanding scientific needs. Different targets are traditionally used for calibration depending on the sensor or spacecraft specificities: from on-board calibration systems to ground targets, they all take advantage of our capacity to characterize and model them. But achieving the in-flight stability of a diffuser panel is always a challenge while the calibration over ground targets is often limited by their BDRF characterization and the atmosphere variability. Thanks to their agility, some satellites have the capability to view extra-terrestrial targets such as the moon or stars. The moon is widely used for calibration and its albedo is known through ROLO (RObotic Lunar Observatory) USGS model but with a poor absolute accuracy limiting its use to sensor drift monitoring or cross-calibration. Although the spectral irradiance of some stars is known with a very high accuracy, it was not really shown that they could provide an absolute reference for remote sensors calibration. This paper shows that high resolution optical sensors can be calibrated with a high absolute accuracy using stars. The agile-body PLEIADES 1A satellite is used for this demonstration. The star based calibration principle is described and the results are provided for different stars, each one being acquired several times. These results are compared to the official calibration provided by ground targets and the main error contributors are discussed.

  14. Timing of metamorphism of the Lansang gneiss and implications for left-lateral motion along the Mae Ping (Wang Chao) strike-slip fault, Thailand

    NASA Astrophysics Data System (ADS)

    Palin, R. M.; Searle, M. P.; Morley, C. K.; Charusiri, P.; Horstwood, M. S. A.; Roberts, N. M. W.

    2013-10-01

    The Mae Ping fault (MPF), western Thailand, exhibits dominantly left-lateral strike-slip motion and stretches for >600 km, reportedly branching off the right-lateral Sagaing fault in Myanmar and extending southeast towards Cambodia. Previous studies have suggested that the fault assisted the large-scale extrusion of Sundaland that occurred during the Late Eocene-Early Oligocene, with a geological offset of ˜120-150 km estimated from displaced high-grade gneisses and granites of the Chiang Mai-Lincang belt. Exposures of high-grade orthogneiss in the Lansang National Park, part of this belt, locally contain strong mylonitic textures and are bounded by strike-slip ductile shear zones and brittle faults. Geochronological analysis of monazite from a sample of sheared biotite-K-feldspar orthogneiss suggests two episodes of crystallization, with core regions documenting Th-Pb ages between c. 123 and c. 114 Ma and rim regions documenting a significantly younger age range between c. 45-37 Ma. These data are interpreted to represent possible magmatic protolith emplacement for the Lansang orthogneiss during the Early Cretaceous, with a later episode of metamorphism occurring during the Eocene. Textural relationships provided by in situ analysis suggest that ductile shearing along the MPF occurred during the latter stages of, or after, this metamorphic event. In addition, monazite analyzed from an undeformed garnet-two-mica granite dyke intruding metamorphic units at Bhumipol Lake outside of the Mae Ping shear zone produced a Th-Pb age of 66.2 ± 1.6 Ma. This age is interpreted to date the timing of dyke emplacement, implying that the MPF cuts through earlier formed magmatic and high-grade metamorphic rocks. These new data, when combined with regional mapping and earlier geochronological work, show that neither metamorphism, nor regional cooling, was directly related to strike-slip motion.

  15. Top-of-Climb Matching Method for Reducing Aircraft Trajectory Prediction Errors.

    PubMed

    Thipphavong, David P

    2016-09-01

    The inaccuracies of the aircraft performance models utilized by trajectory predictors with regard to takeoff weight, thrust, climb profile, and other parameters result in altitude errors during the climb phase that often exceed the vertical separation standard of 1000 feet. This study investigates the potential reduction in altitude trajectory prediction errors that could be achieved for climbing flights if just one additional parameter is made available: top-of-climb (TOC) time. The TOC-matching method developed and evaluated in this paper is straightforward: a set of candidate trajectory predictions is generated using different aircraft weight parameters, and the one that most closely matches TOC in terms of time is selected. This algorithm was tested using more than 1000 climbing flights in Fort Worth Center. Compared to the baseline trajectory predictions of a real-time research prototype (Center/TRACON Automation System), the TOC-matching method reduced the altitude root mean square error (RMSE) for a 5-minute prediction time by 38%. It also decreased the percentage of flights with absolute altitude error greater than the vertical separation standard of 1000 ft for the same look-ahead time from 55% to 30%.

  16. Top-of-Climb Matching Method for Reducing Aircraft Trajectory Prediction Errors

    PubMed Central

    Thipphavong, David P.

    2017-01-01

    The inaccuracies of the aircraft performance models utilized by trajectory predictors with regard to takeoff weight, thrust, climb profile, and other parameters result in altitude errors during the climb phase that often exceed the vertical separation standard of 1000 feet. This study investigates the potential reduction in altitude trajectory prediction errors that could be achieved for climbing flights if just one additional parameter is made available: top-of-climb (TOC) time. The TOC-matching method developed and evaluated in this paper is straightforward: a set of candidate trajectory predictions is generated using different aircraft weight parameters, and the one that most closely matches TOC in terms of time is selected. This algorithm was tested using more than 1000 climbing flights in Fort Worth Center. Compared to the baseline trajectory predictions of a real-time research prototype (Center/TRACON Automation System), the TOC-matching method reduced the altitude root mean square error (RMSE) for a 5-minute prediction time by 38%. It also decreased the percentage of flights with absolute altitude error greater than the vertical separation standard of 1000 ft for the same look-ahead time from 55% to 30%. PMID:28684883

  17. Top-of-Climb Matching Method for Reducing Aircraft Trajectory Prediction Errors

    NASA Technical Reports Server (NTRS)

    Thipphavong, David P.

    2016-01-01

    The inaccuracies of the aircraft performance models utilized by trajectory predictors with regard to takeoff weight, thrust, climb profile, and other parameters result in altitude errors during the climb phase that often exceed the vertical separation standard of 1000 feet. This study investigates the potential reduction in altitude trajectory prediction errors that could be achieved for climbing flights if just one additional parameter is made available: top-of-climb (TOC) time. The TOC-matching method developed and evaluated in this paper is straightforward: a set of candidate trajectory predictions is generated using different aircraft weight parameters, and the one that most closely matches TOC in terms of time is selected. This algorithm was tested using more than 1000 climbing flights in Fort Worth Center. Compared to the baseline trajectory predictions of a real-time research prototype (Center/TRACON Automation System), the TOC-matching method reduced the altitude root mean square error (RMSE) for a 5-minute prediction time by 38%. It also decreased the percentage of flights with absolute altitude error greater than the vertical separation standard of 1000 ft for the same look-ahead time from 55% to 30%.

  18. Estimating nonrigid motion from inconsistent intensity with robust shape features

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Liu, Wenyang; Ruan, Dan, E-mail: druan@mednet.ucla.edu; Department of Radiation Oncology, University of California, Los Angeles, California 90095

    2013-12-15

    Purpose: To develop a nonrigid motion estimation method that is robust to heterogeneous intensity inconsistencies amongst the image pairs or image sequence. Methods: Intensity and contrast variations, as in dynamic contrast enhanced magnetic resonance imaging, present a considerable challenge to registration methods based on general discrepancy metrics. In this study, the authors propose and validate a novel method that is robust to such variations by utilizing shape features. The geometry of interest (GOI) is represented with a flexible zero level set, segmented via well-behaved regularized optimization. The optimization energy drives the zero level set to high image gradient regions, andmore » regularizes it with area and curvature priors. The resulting shape exhibits high consistency even in the presence of intensity or contrast variations. Subsequently, a multiscale nonrigid registration is performed to seek a regular deformation field that minimizes shape discrepancy in the vicinity of GOIs. Results: To establish the working principle, realistic 2D and 3D images were subject to simulated nonrigid motion and synthetic intensity variations, so as to enable quantitative evaluation of registration performance. The proposed method was benchmarked against three alternative registration approaches, specifically, optical flow, B-spline based mutual information, and multimodality demons. When intensity consistency was satisfied, all methods had comparable registration accuracy for the GOIs. When intensities among registration pairs were inconsistent, however, the proposed method yielded pronounced improvement in registration accuracy, with an approximate fivefold reduction in mean absolute error (MAE = 2.25 mm, SD = 0.98 mm), compared to optical flow (MAE = 9.23 mm, SD = 5.36 mm), B-spline based mutual information (MAE = 9.57 mm, SD = 8.74 mm) and mutimodality demons (MAE = 10.07 mm, SD = 4.03 mm). Applying the proposed method on a real MR image sequence also

  19. Comparison of Nine Statistical Model Based Warfarin Pharmacogenetic Dosing Algorithms Using the Racially Diverse International Warfarin Pharmacogenetic Consortium Cohort Database

    PubMed Central

    Liu, Rong; Li, Xi; Zhang, Wei; Zhou, Hong-Hao

    2015-01-01

    Objective Multiple linear regression (MLR) and machine learning techniques in pharmacogenetic algorithm-based warfarin dosing have been reported. However, performances of these algorithms in racially diverse group have never been objectively evaluated and compared. In this literature-based study, we compared the performances of eight machine learning techniques with those of MLR in a large, racially-diverse cohort. Methods MLR, artificial neural network (ANN), regression tree (RT), multivariate adaptive regression splines (MARS), boosted regression tree (BRT), support vector regression (SVR), random forest regression (RFR), lasso regression (LAR) and Bayesian additive regression trees (BART) were applied in warfarin dose algorithms in a cohort from the International Warfarin Pharmacogenetics Consortium database. Covariates obtained by stepwise regression from 80% of randomly selected patients were used to develop algorithms. To compare the performances of these algorithms, the mean percentage of patients whose predicted dose fell within 20% of the actual dose (mean percentage within 20%) and the mean absolute error (MAE) were calculated in the remaining 20% of patients. The performances of these techniques in different races, as well as the dose ranges of therapeutic warfarin were compared. Robust results were obtained after 100 rounds of resampling. Results BART, MARS and SVR were statistically indistinguishable and significantly out performed all the other approaches in the whole cohort (MAE: 8.84–8.96 mg/week, mean percentage within 20%: 45.88%–46.35%). In the White population, MARS and BART showed higher mean percentage within 20% and lower mean MAE than those of MLR (all p values < 0.05). In the Asian population, SVR, BART, MARS and LAR performed the same as MLR. MLR and LAR optimally performed among the Black population. When patients were grouped in terms of warfarin dose range, all machine learning techniques except ANN and LAR showed significantly

  20. Estimating nonrigid motion from inconsistent intensity with robust shape features.

    PubMed

    Liu, Wenyang; Ruan, Dan

    2013-12-01

    To develop a nonrigid motion estimation method that is robust to heterogeneous intensity inconsistencies amongst the image pairs or image sequence. Intensity and contrast variations, as in dynamic contrast enhanced magnetic resonance imaging, present a considerable challenge to registration methods based on general discrepancy metrics. In this study, the authors propose and validate a novel method that is robust to such variations by utilizing shape features. The geometry of interest (GOI) is represented with a flexible zero level set, segmented via well-behaved regularized optimization. The optimization energy drives the zero level set to high image gradient regions, and regularizes it with area and curvature priors. The resulting shape exhibits high consistency even in the presence of intensity or contrast variations. Subsequently, a multiscale nonrigid registration is performed to seek a regular deformation field that minimizes shape discrepancy in the vicinity of GOIs. To establish the working principle, realistic 2D and 3D images were subject to simulated nonrigid motion and synthetic intensity variations, so as to enable quantitative evaluation of registration performance. The proposed method was benchmarked against three alternative registration approaches, specifically, optical flow, B-spline based mutual information, and multimodality demons. When intensity consistency was satisfied, all methods had comparable registration accuracy for the GOIs. When intensities among registration pairs were inconsistent, however, the proposed method yielded pronounced improvement in registration accuracy, with an approximate fivefold reduction in mean absolute error (MAE = 2.25 mm, SD = 0.98 mm), compared to optical flow (MAE = 9.23 mm, SD = 5.36 mm), B-spline based mutual information (MAE = 9.57 mm, SD = 8.74 mm) and mutimodality demons (MAE = 10.07 mm, SD = 4.03 mm). Applying the proposed method on a real MR image sequence also provided qualitatively appealing results

  1. Cryogenic, Absolute, High Pressure Sensor

    NASA Technical Reports Server (NTRS)

    Chapman, John J. (Inventor); Shams. Qamar A. (Inventor); Powers, William T. (Inventor)

    2001-01-01

    A pressure sensor is provided for cryogenic, high pressure applications. A highly doped silicon piezoresistive pressure sensor is bonded to a silicon substrate in an absolute pressure sensing configuration. The absolute pressure sensor is bonded to an aluminum nitride substrate. Aluminum nitride has appropriate coefficient of thermal expansion for use with highly doped silicon at cryogenic temperatures. A group of sensors, either two sensors on two substrates or four sensors on a single substrate are packaged in a pressure vessel.

  2. Integrating Satellite and Surface Sensor Networks for Irrigation Management Applications in California

    NASA Astrophysics Data System (ADS)

    Melton, F. S.; Johnson, L.; Post, K. M.; Guzman, A.; Zaragoza, I.; Spellenberg, R.; Rosevelt, C.; Michaelis, A.; Nemani, R. R.; Cahn, M.; Frame, K.; Temesgen, B.; Eching, S.

    2016-12-01

    Satellite mapping of evapotranspiration (ET) from irrigated agricultural lands can provide agricultural producers and water managers with information that can be used to optimize agricultural water use, especially in regions with limited water supplies. The timely delivery of information on agricultural crop water requirements has the potential to make irrigation scheduling more practical, convenient, and accurate. We present a system for irrigation scheduling and management support in California and describe lessons learned from the development and implementation of the system. The Satellite Irrigation Management Support (SIMS) framework integrates satellite data with information from agricultural weather networks to map crop canopy development, basal crop coefficients (Kcb), and basal crop evapotranspiration (ETcb) at the scale of individual fields. Information is distributed to agricultural producers and water managers via a web-based irrigation management decision support system and web data services. SIMS also provides an application programming interface (API) that facilitates integration with other irrigation decision support tools, estimation of total crop evapotranspiration (ETc) and calculation of on-farm water use efficiency metrics. Accuracy assessments conducted in commercial fields for more than a dozen crop types to date have shown that SIMS seasonal ETcb estimates are within 10% mean absolute error (MAE) for well-watered crops and within 15% across all crop types studied, and closely track daily ETc and running totals of ETc measured in each field. Use of a soil water balance model to correct for soil evaporation and crop water stress reduces this error to less than 8% MAE across all crop types studied to date relative to field measurements of ETc. Results from irrigation trials conducted by the project for four vegetable crops have also demonstrated the potential for use of ET-based irrigation management strategies to reduce total applied water by

  3. Pan evaporation modeling using six different heuristic computing methods in different climates of China

    NASA Astrophysics Data System (ADS)

    Wang, Lunche; Kisi, Ozgur; Zounemat-Kermani, Mohammad; Li, Hui

    2017-01-01

    Pan evaporation (Ep) plays important roles in agricultural water resources management. One of the basic challenges is modeling Ep using limited climatic parameters because there are a number of factors affecting the evaporation rate. This study investigated the abilities of six different soft computing methods, multi-layer perceptron (MLP), generalized regression neural network (GRNN), fuzzy genetic (FG), least square support vector machine (LSSVM), multivariate adaptive regression spline (MARS), adaptive neuro-fuzzy inference systems with grid partition (ANFIS-GP), and two regression methods, multiple linear regression (MLR) and Stephens and Stewart model (SS) in predicting monthly Ep. Long-term climatic data at various sites crossing a wide range of climates during 1961-2000 are used for model development and validation. The results showed that the models have different accuracies in different climates and the MLP model performed superior to the other models in predicting monthly Ep at most stations using local input combinations (for example, the MAE (mean absolute errors), RMSE (root mean square errors), and determination coefficient (R2) are 0.314 mm/day, 0.405 mm/day and 0.988, respectively for HEB station), while GRNN model performed better in Tibetan Plateau (MAE, RMSE and R2 are 0.459 mm/day, 0.592 mm/day and 0.932, respectively). The accuracies of above models ranked as: MLP, GRNN, LSSVM, FG, ANFIS-GP, MARS and MLR. The overall results indicated that the soft computing techniques generally performed better than the regression methods, but MLR and SS models can be more preferred at some climatic zones instead of complex nonlinear models, for example, the BJ (Beijing), CQ (Chongqing) and HK (Haikou) stations. Therefore, it can be concluded that Ep could be successfully predicted using above models in hydrological modeling studies.

  4. Mapping CHU9D Utility Scores from the PedsQLTM 4.0 SF-15.

    PubMed

    Mpundu-Kaambwa, Christine; Chen, Gang; Russo, Remo; Stevens, Katherine; Petersen, Karin Dam; Ratcliffe, Julie

    2017-04-01

    The Pediatric Quality of Life Inventory™ 4.0 Short Form 15 Generic Core Scales (hereafter the PedsQL) and the Child Health Utility-9 Dimensions (CHU9D) are two generic instruments designed to measure health-related quality of life in children and adolescents in the general population and paediatric patient groups living with specific health conditions. Although the PedsQL is widely used among paediatric patient populations, presently it is not possible to directly use the scores from the instrument to calculate quality-adjusted life-years (QALYs) for application in economic evaluation because it produces summary scores which are not preference-based. This paper examines different econometric mapping techniques for estimating CHU9D utility scores from the PedsQL for the purpose of calculating QALYs for cost-utility analysis. The PedsQL and the CHU9D were completed by a community sample of 755 Australian adolescents aged 15-17 years. Seven regression models were estimated: ordinary least squares estimator, generalised linear model, robust MM estimator, multivariate factorial polynomial estimator, beta-binomial estimator, finite mixture model and multinomial logistic model. The mean absolute error (MAE) and the mean squared error (MSE) were used to assess predictive ability of the models. The MM estimator with stepwise-selected PedsQL dimension scores as explanatory variables had the best predictive accuracy using MAE and the equivalent beta-binomial model had the best predictive accuracy using MSE. Our mapping algorithm facilitates the estimation of health-state utilities for use within economic evaluations where only PedsQL data is available and is suitable for use in community-based adolescents aged 15-17 years. Applicability of the algorithm in younger populations should be assessed in further research.

  5. Absolute Income, Relative Income, and Happiness

    ERIC Educational Resources Information Center

    Ball, Richard; Chernova, Kateryna

    2008-01-01

    This paper uses data from the World Values Survey to investigate how an individual's self-reported happiness is related to (i) the level of her income in absolute terms, and (ii) the level of her income relative to other people in her country. The main findings are that (i) both absolute and relative income are positively and significantly…

  6. Absolute judgment for one- and two-dimensional stimuli embedded in Gaussian noise

    NASA Technical Reports Server (NTRS)

    Kvalseth, T. O.

    1977-01-01

    This study examines the effect on human performance of adding Gaussian noise or disturbance to the stimuli in absolute judgment tasks involving both one- and two-dimensional stimuli. For each selected stimulus value (both an X-value and a Y-value were generated in the two-dimensional case), 10 values (or 10 pairs of values in the two-dimensional case) were generated from a zero-mean Gaussian variate, added to the selected stimulus value and then served as the coordinate values for the 10 points that were displayed sequentially on a CRT. The results show that human performance, in terms of the information transmitted and rms error as functions of stimulus uncertainty, was significantly reduced as the noise variance increased.

  7. Per-pixel bias-variance decomposition of continuous errors in data-driven geospatial modeling: A case study in environmental remote sensing

    NASA Astrophysics Data System (ADS)

    Gao, Jing; Burt, James E.

    2017-12-01

    This study investigates the usefulness of a per-pixel bias-variance error decomposition (BVD) for understanding and improving spatially-explicit data-driven models of continuous variables in environmental remote sensing (ERS). BVD is a model evaluation method originated from machine learning and have not been examined for ERS applications. Demonstrated with a showcase regression tree model mapping land imperviousness (0-100%) using Landsat images, our results showed that BVD can reveal sources of estimation errors, map how these sources vary across space, reveal the effects of various model characteristics on estimation accuracy, and enable in-depth comparison of different error metrics. Specifically, BVD bias maps can help analysts identify and delineate model spatial non-stationarity; BVD variance maps can indicate potential effects of ensemble methods (e.g. bagging), and inform efficient training sample allocation - training samples should capture the full complexity of the modeled process, and more samples should be allocated to regions with more complex underlying processes rather than regions covering larger areas. Through examining the relationships between model characteristics and their effects on estimation accuracy revealed by BVD for both absolute and squared errors (i.e. error is the absolute or the squared value of the difference between observation and estimate), we found that the two error metrics embody different diagnostic emphases, can lead to different conclusions about the same model, and may suggest different solutions for performance improvement. We emphasize BVD's strength in revealing the connection between model characteristics and estimation accuracy, as understanding this relationship empowers analysts to effectively steer performance through model adjustments.

  8. Universal Cosmic Absolute and Modern Science

    NASA Astrophysics Data System (ADS)

    Kostro, Ludwik

    The official Sciences, especially all natural sciences, respect in their researches the principle of methodic naturalism i.e. they consider all phenomena as entirely natural and therefore in their scientific explanations they do never adduce or cite supernatural entities and forces. The purpose of this paper is to show that Modern Science has its own self-existent, self-acting, and self-sufficient Natural All-in Being or Omni-Being i.e. the entire Nature as a Whole that justifies the scientific methodic naturalism. Since this Natural All-in Being is one and only It should be considered as the own scientifically justified Natural Absolute of Science and should be called, in my opinion, the Universal Cosmic Absolute of Modern Science. It will be also shown that the Universal Cosmic Absolute is ontologically enormously stratified and is in its ultimate i.e. in its most fundamental stratum trans-reistic and trans-personal. It means that in its basic stratum. It is neither a Thing or a Person although It contains in Itself all things and persons with all other sentient and conscious individuals as well, On the turn of the 20th century the Science has begun to look for a theory of everything, for a final theory, for a master theory. In my opinion the natural Universal Cosmic Absolute will constitute in such a theory the radical all penetrating Ultimate Basic Reality and will substitute step by step the traditional supernatural personal Absolute.

  9. A simultaneously calibration approach for installation and attitude errors of an INS/GPS/LDS target tracker.

    PubMed

    Cheng, Jianhua; Chen, Daidai; Sun, Xiangyu; Wang, Tongda

    2015-02-04

    To obtain the absolute position of a target is one of the basic topics for non-cooperated target tracking problems. In this paper, we present a simultaneously calibration method for an Inertial navigation system (INS)/Global position system (GPS)/Laser distance scanner (LDS) integrated system based target positioning approach. The INS/GPS integrated system provides the attitude and position of observer, and LDS offers the distance between the observer and the target. The two most significant errors are taken into jointly consideration and analyzed: (1) the attitude measure error of INS/GPS; (2) the installation error between INS/GPS and LDS subsystems. Consequently, a INS/GPS/LDS based target positioning approach considering these two errors is proposed. In order to improve the performance of this approach, a novel calibration method is designed to simultaneously estimate and compensate these two main errors. Finally, simulations are conducted to access the performance of the proposed target positioning approach and the designed simultaneously calibration method.

  10. Jasminum sambac flower absolutes from India and China--geographic variations.

    PubMed

    Braun, Norbert A; Sim, Sherina

    2012-05-01

    Seven Jasminum sambac flower absolutes from different locations in the southern Indian state of Tamil Nadu were analyzed using GC and GC-MS. Focus was placed on 41 key ingredients to investigate geographic variations in this species. These seven absolutes were compared with an Indian bud absolute and commercially available J. sambac flower absolutes from India and China. All absolutes showed broad variations for the 10 main ingredients between 8% and 96%. In addition, the odor of Indian and Chinese J. sambac flower absolutes were assessed.

  11. Advancing Absolute Calibration for JWST and Other Applications

    NASA Astrophysics Data System (ADS)

    Rieke, George; Bohlin, Ralph; Boyajian, Tabetha; Carey, Sean; Casagrande, Luca; Deustua, Susana; Gordon, Karl; Kraemer, Kathleen; Marengo, Massimo; Schlawin, Everett; Su, Kate; Sloan, Greg; Volk, Kevin

    2017-10-01

    We propose to exploit the unique optical stability of the Spitzer telescope, along with that of IRAC, to (1) transfer the accurate absolute calibration obtained with MSX on very bright stars directly to two reference stars within the dynamic range of the JWST imagers (and of other modern instrumentation); (2) establish a second accurate absolute calibration based on the absolutely calibrated spectrum of the sun, transferred onto the astronomical system via alpha Cen A; and (3) provide accurate infrared measurements for the 11 (of 15) highest priority stars with no such data but with accurate interferometrically measured diameters, allowing us to optimize determinations of effective temperatures using the infrared flux method and thus to extend the accurate absolute calibration spectrally. This program is integral to plans for an accurate absolute calibration of JWST and will also provide a valuable Spitzer legacy.

  12. Absolute radiometric calibration of advanced remote sensing systems

    NASA Technical Reports Server (NTRS)

    Slater, P. N.

    1982-01-01

    The distinction between the uses of relative and absolute spectroradiometric calibration of remote sensing systems is discussed. The advantages of detector-based absolute calibration are described, and the categories of relative and absolute system calibrations are listed. The limitations and problems associated with three common methods used for the absolute calibration of remote sensing systems are addressed. Two methods are proposed for the in-flight absolute calibration of advanced multispectral linear array systems. One makes use of a sun-illuminated panel in front of the sensor, the radiance of which is monitored by a spectrally flat pyroelectric radiometer. The other uses a large, uniform, high-radiance reference ground surface. The ground and atmospheric measurements required as input to a radiative transfer program to predict the radiance level at the entrance pupil of the orbital sensor are discussed, and the ground instrumentation is described.

  13. Forecasting typhoid fever incidence in the Cordillera administrative region in the Philippines using seasonal ARIMA models

    NASA Astrophysics Data System (ADS)

    Cawiding, Olive R.; Natividad, Gina May R.; Bato, Crisostomo V.; Addawe, Rizavel C.

    2017-11-01

    The prevalence of typhoid fever in developing countries such as the Philippines calls for a need for accurate forecasting of the disease. This will be of great assistance in strategic disease prevention. This paper presents a development of useful models that predict the behavior of typhoid fever incidence based on the monthly incidence in the provinces of the Cordillera Administrative Region from 2010 to 2015 using univariate time series analysis. The data used was obtained from the Cordillera Office of the Department of Health (DOH-CAR). Seasonal autoregressive moving average (SARIMA) models were used to incorporate the seasonality of the data. A comparison of the results of the obtained models revealed that the SARIMA (1,1,7)(0,0,1)12 with a fixed coefficient at the seventh lag produces the smallest root mean square error (RMSE), mean absolute error (MAE), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). The model suggested that for the year 2016, the number of cases would increase from the months of July to September and have a drop in December. This was then validated using the data collected from January 2016 to December 2016.

  14. A hybrid approach to estimate the complex motions of clouds in sky images

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong

    Tracking the motion of clouds is essential to forecasting the weather and to predicting the short-term solar energy generation. Existing techniques mainly fall into two categories: variational optical flow, and block matching. In this article, we summarize recent advances in estimating cloud motion using ground-based sky imagers and quantitatively evaluate state-of-the-art approaches. Then we propose a hybrid tracking framework to incorporate the strength of both block matching and optical flow models. To validate the accuracy of the proposed approach, we introduce a series of synthetic images to simulate the cloud movement and deformation, and thereafter comprehensively compare our hybrid approachmore » with several representative tracking algorithms over both simulated and real images collected from various sites/imagers. The results show that our hybrid approach outperforms state-of-the-art models by reducing at least 30% motion estimation errors compared with the ground-truth motions in most of simulated image sequences. Furthermore, our hybrid model demonstrates its superior efficiency in several real cloud image datasets by lowering at least 15% Mean Absolute Error (MAE) between predicted images and ground-truth images.« less

  15. A hybrid approach to estimate the complex motions of clouds in sky images

    DOE PAGES

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; ...

    2016-09-14

    Tracking the motion of clouds is essential to forecasting the weather and to predicting the short-term solar energy generation. Existing techniques mainly fall into two categories: variational optical flow, and block matching. In this article, we summarize recent advances in estimating cloud motion using ground-based sky imagers and quantitatively evaluate state-of-the-art approaches. Then we propose a hybrid tracking framework to incorporate the strength of both block matching and optical flow models. To validate the accuracy of the proposed approach, we introduce a series of synthetic images to simulate the cloud movement and deformation, and thereafter comprehensively compare our hybrid approachmore » with several representative tracking algorithms over both simulated and real images collected from various sites/imagers. The results show that our hybrid approach outperforms state-of-the-art models by reducing at least 30% motion estimation errors compared with the ground-truth motions in most of simulated image sequences. Furthermore, our hybrid model demonstrates its superior efficiency in several real cloud image datasets by lowering at least 15% Mean Absolute Error (MAE) between predicted images and ground-truth images.« less

  16. QSAR modeling for predicting mutagenic toxicity of diverse chemicals for regulatory purposes.

    PubMed

    Basant, Nikita; Gupta, Shikha

    2017-06-01

    The safety assessment process of chemicals requires information on their mutagenic potential. The experimental determination of mutagenicity of a large number of chemicals is tedious and time and cost intensive, thus compelling for alternative methods. We have established local and global QSAR models for discriminating low and high mutagenic compounds and predicting their mutagenic activity in a quantitative manner in Salmonella typhimurium (TA) bacterial strains (TA98 and TA100). The decision treeboost (DTB)-based classification QSAR models discriminated among two categories with accuracies of >96% and the regression QSAR models precisely predicted the mutagenic activity of diverse chemicals yielding high correlations (R 2 ) between the experimental and model-predicted values in the respective training (>0.96) and test (>0.94) sets. The test set root mean squared error (RMSE) and mean absolute error (MAE) values emphasized the usefulness of the developed models for predicting new compounds. Relevant structural features of diverse chemicals that were responsible and influence the mutagenic activity were identified. The applicability domains of the developed models were defined. The developed models can be used as tools for screening new chemicals for their mutagenicity assessment for regulatory purpose.

  17. Estimation of Surface Air Temperature Over Central and Eastern Eurasia from MODIS Land Surface Temperature

    NASA Technical Reports Server (NTRS)

    Shen, Suhung; Leptoukh, Gregory G.

    2011-01-01

    Surface air temperature (T(sub a)) is a critical variable in the energy and water cycle of the Earth.atmosphere system and is a key input element for hydrology and land surface models. This is a preliminary study to evaluate estimation of T(sub a) from satellite remotely sensed land surface temperature (T(sub s)) by using MODIS-Terra data over two Eurasia regions: northern China and fUSSR. High correlations are observed in both regions between station-measured T(sub a) and MODIS T(sub s). The relationships between the maximum T(sub a) and daytime T(sub s) depend significantly on land cover types, but the minimum T(sub a) and nighttime T(sub s) have little dependence on the land cover types. The largest difference between maximum T(sub a) and daytime T(sub s) appears over the barren and sparsely vegetated area during the summer time. Using a linear regression method, the daily maximum T(sub a) were estimated from 1 km resolution MODIS T(sub s) under clear-sky conditions with coefficients calculated based on land cover types, while the minimum T(sub a) were estimated without considering land cover types. The uncertainty, mean absolute error (MAE), of the estimated maximum T(sub a) varies from 2.4 C over closed shrublands to 3.2 C over grasslands, and the MAE of the estimated minimum Ta is about 3.0 C.

  18. DNA methylation-based forensic age prediction using artificial neural networks and next generation sequencing.

    PubMed

    Vidaki, Athina; Ballard, David; Aliferi, Anastasia; Miller, Thomas H; Barron, Leon P; Syndercombe Court, Denise

    2017-05-01

    The ability to estimate the age of the donor from recovered biological material at a crime scene can be of substantial value in forensic investigations. Aging can be complex and is associated with various molecular modifications in cells that accumulate over a person's lifetime including epigenetic patterns. The aim of this study was to use age-specific DNA methylation patterns to generate an accurate model for the prediction of chronological age using data from whole blood. In total, 45 age-associated CpG sites were selected based on their reported age coefficients in a previous extensive study and investigated using publicly available methylation data obtained from 1156 whole blood samples (aged 2-90 years) analysed with Illumina's genome-wide methylation platforms (27K/450K). Applying stepwise regression for variable selection, 23 of these CpG sites were identified that could significantly contribute to age prediction modelling and multiple regression analysis carried out with these markers provided an accurate prediction of age (R 2 =0.92, mean absolute error (MAE)=4.6 years). However, applying machine learning, and more specifically a generalised regression neural network model, the age prediction significantly improved (R 2 =0.96) with a MAE=3.3 years for the training set and 4.4 years for a blind test set of 231 cases. The machine learning approach used 16 CpG sites, located in 16 different genomic regions, with the top 3 predictors of age belonged to the genes NHLRC1, SCGN and CSNK1D. The proposed model was further tested using independent cohorts of 53 monozygotic twins (MAE=7.1 years) and a cohort of 1011 disease state individuals (MAE=7.2 years). Furthermore, we highlighted the age markers' potential applicability in samples other than blood by predicting age with similar accuracy in 265 saliva samples (R 2 =0.96) with a MAE=3.2 years (training set) and 4.0 years (blind test). In an attempt to create a sensitive and accurate age prediction test, a next

  19. Error-related brain activity and error awareness in an error classification paradigm.

    PubMed

    Di Gregorio, Francesco; Steinhauser, Marco; Maier, Martin E

    2016-10-01

    Error-related brain activity has been linked to error detection enabling adaptive behavioral adjustments. However, it is still unclear which role error awareness plays in this process. Here, we show that the error-related negativity (Ne/ERN), an event-related potential reflecting early error monitoring, is dissociable from the degree of error awareness. Participants responded to a target while ignoring two different incongruent distractors. After responding, they indicated whether they had committed an error, and if so, whether they had responded to one or to the other distractor. This error classification paradigm allowed distinguishing partially aware errors, (i.e., errors that were noticed but misclassified) and fully aware errors (i.e., errors that were correctly classified). The Ne/ERN was larger for partially aware errors than for fully aware errors. Whereas this speaks against the idea that the Ne/ERN foreshadows the degree of error awareness, it confirms the prediction of a computational model, which relates the Ne/ERN to post-response conflict. This model predicts that stronger distractor processing - a prerequisite of error classification in our paradigm - leads to lower post-response conflict and thus a smaller Ne/ERN. This implies that the relationship between Ne/ERN and error awareness depends on how error awareness is related to response conflict in a specific task. Our results further indicate that the Ne/ERN but not the degree of error awareness determines adaptive performance adjustments. Taken together, we conclude that the Ne/ERN is dissociable from error awareness and foreshadows adaptive performance adjustments. Our results suggest that the relationship between the Ne/ERN and error awareness is correlative and mediated by response conflict. Copyright © 2016 Elsevier Inc. All rights reserved.

  20. Coherent errors in quantum error correction

    NASA Astrophysics Data System (ADS)

    Greenbaum, Daniel; Dutton, Zachary

    Analysis of quantum error correcting (QEC) codes is typically done using a stochastic, Pauli channel error model for describing the noise on physical qubits. However, it was recently found that coherent errors (systematic rotations) on physical data qubits result in both physical and logical error rates that differ significantly from those predicted by a Pauli model. We present analytic results for the logical error as a function of concatenation level and code distance for coherent errors under the repetition code. For data-only coherent errors, we find that the logical error is partially coherent and therefore non-Pauli. However, the coherent part of the error is negligible after two or more concatenation levels or at fewer than ɛ - (d - 1) error correction cycles. Here ɛ << 1 is the rotation angle error per cycle for a single physical qubit and d is the code distance. These results support the validity of modeling coherent errors using a Pauli channel under some minimum requirements for code distance and/or concatenation. We discuss extensions to imperfect syndrome extraction and implications for general QEC.

  1. On the application of the Principal Component Analysis for an efficient climate downscaling of surface wind fields

    NASA Astrophysics Data System (ADS)

    Chavez, Roberto; Lozano, Sergio; Correia, Pedro; Sanz-Rodrigo, Javier; Probst, Oliver

    2013-04-01

    With the purpose of efficiently and reliably generating long-term wind resource maps for the wind energy industry, the application and verification of a statistical methodology for the climate downscaling of wind fields at surface level is presented in this work. This procedure is based on the combination of the Monte Carlo and the Principal Component Analysis (PCA) statistical methods. Firstly the Monte Carlo method is used to create a huge number of daily-based annual time series, so called climate representative years, by the stratified sampling of a 33-year-long time series corresponding to the available period of the NCAR/NCEP global reanalysis data set (R-2). Secondly the representative years are evaluated such that the best set is chosen according to its capability to recreate the Sea Level Pressure (SLP) temporal and spatial fields from the R-2 data set. The measure of this correspondence is based on the Euclidean distance between the Empirical Orthogonal Functions (EOF) spaces generated by the PCA (Principal Component Analysis) decomposition of the SLP fields from both the long-term and the representative year data sets. The methodology was verified by comparing the selected 365-days period against a 9-year period of wind fields generated by dynamical downscaling the Global Forecast System data with the mesoscale model SKIRON for the Iberian Peninsula. These results showed that, compared to the traditional method of dynamical downscaling any random 365-days period, the error in the average wind velocity by the PCA's representative year was reduced by almost 30%. Moreover the Mean Absolute Errors (MAE) in the monthly and daily wind profiles were also reduced by almost 25% along all SKIRON grid points. These results showed also that the methodology presented maximum error values in the wind speed mean of 0.8 m/s and maximum MAE in the monthly curves of 0.7 m/s. Besides the bulk numbers, this work shows the spatial distribution of the errors across the

  2. Poster - 49: Assessment of Synchrony respiratory compensation error for CyberKnife liver treatment

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Liu, Ming; Cygler,

    The goal of this work is to quantify respiratory motion compensation errors for liver tumor patients treated by the CyberKnife system with Synchrony tracking, to identify patients with the smallest tracking errors and to eventually help coach patient’s breathing patterns to minimize dose delivery errors. The accuracy of CyberKnife Synchrony respiratory motion compensation was assessed for 37 patients treated for liver lesions by analyzing data from system logfiles. A predictive model is used to modulate the direction of individual beams during dose delivery based on the positions of internally implanted fiducials determined using an orthogonal x-ray imaging system and themore » current location of LED external markers. For each x-ray pair acquired, system logfiles report the prediction error, the difference between the measured and predicted fiducial positions, and the delivery error, which is an estimate of the statistical error in the model overcoming the latency between x-ray acquisition and robotic repositioning. The total error was calculated at the time of each x-ray pair, for the number of treatment fractions and the number of patients, giving the average respiratory motion compensation error in three dimensions. The 99{sup th} percentile for the total radial error is 3.85 mm, with the highest contribution of 2.79 mm in superior/inferior (S/I) direction. The absolute mean compensation error is 1.78 mm radially with a 1.27 mm contribution in the S/I direction. Regions of high total error may provide insight into features predicting groups of patients with larger or smaller total errors.« less

  3. Absolute pitch among students at the Shanghai Conservatory of Music: a large-scale direct-test study.

    PubMed

    Deutsch, Diana; Li, Xiaonuo; Shen, Jing

    2013-11-01

    This paper reports a large-scale direct-test study of absolute pitch (AP) in students at the Shanghai Conservatory of Music. Overall note-naming scores were very high, with high scores correlating positively with early onset of musical training. Students who had begun training at age ≤5 yr scored 83% correct not allowing for semitone errors and 90% correct allowing for semitone errors. Performance levels were higher for white key pitches than for black key pitches. This effect was greater for orchestral performers than for pianists, indicating that it cannot be attributed to early training on the piano. Rather, accuracy in identifying notes of different names (C, C#, D, etc.) correlated with their frequency of occurrence in a large sample of music taken from the Western tonal repertoire. There was also an effect of pitch range, so that performance on tones in the two-octave range beginning on Middle C was higher than on tones in the octave below Middle C. In addition, semitone errors tended to be on the sharp side. The evidence also ran counter to the hypothesis, previously advanced by others, that the note A plays a special role in pitch identification judgments.

  4. Input selection and performance optimization of ANN-based streamflow forecasts in the drought-prone Murray Darling Basin region using IIS and MODWT algorithm

    NASA Astrophysics Data System (ADS)

    Prasad, Ramendra; Deo, Ravinesh C.; Li, Yan; Maraseni, Tek

    2017-11-01

    Forecasting streamflow is vital for strategically planning, utilizing and redistributing water resources. In this paper, a wavelet-hybrid artificial neural network (ANN) model integrated with iterative input selection (IIS) algorithm (IIS-W-ANN) is evaluated for its statistical preciseness in forecasting monthly streamflow, and it is then benchmarked against M5 Tree model. To develop hybrid IIS-W-ANN model, a global predictor matrix is constructed for three local hydrological sites (Richmond, Gwydir, and Darling River) in Australia's agricultural (Murray-Darling) Basin. Model inputs comprised of statistically significant lagged combination of streamflow water level, are supplemented by meteorological data (i.e., precipitation, maximum and minimum temperature, mean solar radiation, vapor pressure and evaporation) as the potential model inputs. To establish robust forecasting models, iterative input selection (IIS) algorithm is applied to screen the best data from the predictor matrix and is integrated with the non-decimated maximum overlap discrete wavelet transform (MODWT) applied on the IIS-selected variables. This resolved the frequencies contained in predictor data while constructing a wavelet-hybrid (i.e., IIS-W-ANN and IIS-W-M5 Tree) model. Forecasting ability of IIS-W-ANN is evaluated via correlation coefficient (r), Willmott's Index (WI), Nash-Sutcliffe Efficiency (ENS), root-mean-square-error (RMSE), and mean absolute error (MAE), including the percentage RMSE and MAE. While ANN models are seen to outperform M5 Tree executed for all hydrological sites, the IIS variable selector was efficient in determining the appropriate predictors, as stipulated by the better performance of the IIS coupled (ANN and M5 Tree) models relative to the models without IIS. When IIS-coupled models are integrated with MODWT, the wavelet-hybrid IIS-W-ANN and IIS-W-M5 Tree are seen to attain significantly accurate performance relative to their standalone counterparts. Importantly

  5. Microionization chamber for reference dosimetry in IMRT verification: clinical implications on OAR dosimetric errors

    NASA Astrophysics Data System (ADS)

    Sánchez-Doblado, Francisco; Capote, Roberto; Leal, Antonio; Roselló, Joan V.; Lagares, Juan I.; Arráns, Rafael; Hartmann, Günther H.

    2005-03-01

    Intensity modulated radiotherapy (IMRT) has become a treatment of choice in many oncological institutions. Small fields or beamlets with sizes of 1 to 5 cm2 are now routinely used in IMRT delivery. Therefore small ionization chambers (IC) with sensitive volumes <=0.1 cm3are generally used for dose verification of an IMRT treatment. The measurement conditions during verification may be quite different from reference conditions normally encountered in clinical beam calibration, so dosimetry of these narrow photon beams pertains to the so-called non-reference conditions for beam calibration. This work aims at estimating the error made when measuring the organ at risk's (OAR) absolute dose by a micro ion chamber (μIC) in a typical IMRT treatment. The dose error comes from the assumption that the dosimetric parameters determining the absolute dose are the same as for the reference conditions. We have selected two clinical cases, treated by IMRT, for our dose error evaluations. Detailed geometrical simulation of the μIC and the dose verification set-up was performed. The Monte Carlo (MC) simulation allows us to calculate the dose measured by the chamber as a dose averaged over the air cavity within the ion-chamber active volume (Dair). The absorbed dose to water (Dwater) is derived as the dose deposited inside the same volume, in the same geometrical position, filled and surrounded by water in the absence of the ion chamber. Therefore, the Dwater/Dair dose ratio is the MC estimator of the total correction factor needed to convert the absorbed dose in air into the absorbed dose in water. The dose ratio was calculated for the μIC located at the isocentre within the OARs for both clinical cases. The clinical impact of the calculated dose error was found to be negligible for the studied IMRT treatments.

  6. Linking Comparisons of Absolute Gravimeters: A Proof of Concept for a new Global Absolute Gravity Reference System.

    NASA Astrophysics Data System (ADS)

    Wziontek, H.; Palinkas, V.; Falk, R.; Vaľko, M.

    2016-12-01

    Since decades, absolute gravimeters are compared on a regular basis on an international level, starting at the International Bureau for Weights and Measures (BIPM) in 1981. Usually, these comparisons are based on constant reference values deduced from all accepted measurements acquired during the comparison period. Temporal changes between comparison epochs are usually not considered. Resolution No. 2, adopted by IAG during the IUGG General Assembly in Prague 2015, initiates the establishment of a Global Absolute Gravity Reference System based on key comparisons of absolute gravimeters (AG) under the International Committee for Weights and Measures (CIPM) in order to establish a common level in the microGal range. A stable and unique reference frame can only be achieved, if different AG are taking part in different kind of comparisons. Systematic deviations between the respective comparison reference values can be detected, if the AG can be considered stable over time. The continuous operation of superconducting gravimeters (SG) on selected stations further supports the temporal link of comparison reference values by establishing a reference function over time. By a homogenous reprocessing of different comparison epochs and including AG and SG time series at selected stations, links between several comparisons will be established and temporal comparison reference functions will be derived. By this, comparisons on a regional level can be traced to back to the level of key comparisons, providing a reference for other absolute gravimeters. It will be proved and discussed, how such a concept can be used to support the future absolute gravity reference system.

  7. 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

  8. Zero tolerance prescribing: a strategy to reduce prescribing errors on the paediatric intensive care unit.

    PubMed

    Booth, Rachelle; Sturgess, Emma; Taberner-Stokes, Alison; Peters, Mark

    2012-11-01

    To establish the baseline prescribing error rate in a tertiary paediatric intensive care unit (PICU) and to determine the impact of a zero tolerance prescribing (ZTP) policy incorporating a dedicated prescribing area and daily feedback of prescribing errors. A prospective, non-blinded, observational study was undertaken in a 12-bed tertiary PICU over a period of 134 weeks. Baseline prescribing error data were collected on weekdays for all patients for a period of 32 weeks, following which the ZTP policy was introduced. Daily error feedback was introduced after a further 12 months. Errors were sub-classified as 'clinical', 'non-clinical' and 'infusion prescription' errors and the effects of interventions considered separately. The baseline combined prescribing error rate was 892 (95 % confidence interval (CI) 765-1,019) errors per 1,000 PICU occupied bed days (OBDs), comprising 25.6 % clinical, 44 % non-clinical and 30.4 % infusion prescription errors. The combined interventions of ZTP plus daily error feedback were associated with a reduction in the combined prescribing error rate to 447 (95 % CI 389-504) errors per 1,000 OBDs (p < 0.0001), an absolute risk reduction of 44.5 % (95 % CI 40.8-48.0 %). Introduction of the ZTP policy was associated with a significant decrease in clinical and infusion prescription errors, while the introduction of daily error feedback was associated with a significant reduction in non-clinical prescribing errors. The combined interventions of ZTP and daily error feedback were associated with a significant reduction in prescribing errors in the PICU, in line with Department of Health requirements of a 40 % reduction within 5 years.

  9. Computational fluid dynamics analysis and experimental study of a low measurement error temperature sensor used in climate observation.

    PubMed

    Yang, Jie; Liu, Qingquan; Dai, Wei

    2017-02-01

    To improve the air temperature observation accuracy, a low measurement error temperature sensor is proposed. A computational fluid dynamics (CFD) method is implemented to obtain temperature errors under various environmental conditions. Then, a temperature error correction equation is obtained by fitting the CFD results using a genetic algorithm method. The low measurement error temperature sensor, a naturally ventilated radiation shield, a thermometer screen, and an aspirated temperature measurement platform are characterized in the same environment to conduct the intercomparison. The aspirated platform served as an air temperature reference. The mean temperature errors of the naturally ventilated radiation shield and the thermometer screen are 0.74 °C and 0.37 °C, respectively. In contrast, the mean temperature error of the low measurement error temperature sensor is 0.11 °C. The mean absolute error and the root mean square error between the corrected results and the measured results are 0.008 °C and 0.01 °C, respectively. The correction equation allows the temperature error of the low measurement error temperature sensor to be reduced by approximately 93.8%. The low measurement error temperature sensor proposed in this research may be helpful to provide a relatively accurate air temperature result.

  10. On the sensitivity of TG-119 and IROC credentialing to TPS commissioning errors.

    PubMed

    McVicker, Drew; Yin, Fang-Fang; Adamson, Justus D

    2016-01-08

    We investigate the sensitivity of IMRT commissioning using the TG-119 C-shape phantom and credentialing with the IROC head and neck phantom to treatment planning system commissioning errors. We introduced errors into the various aspects of the commissioning process for a 6X photon energy modeled using the analytical anisotropic algorithm within a commercial treatment planning system. Errors were implemented into the various components of the dose calculation algorithm including primary photons, secondary photons, electron contamination, and MLC parameters. For each error we evaluated the probability that it could be committed unknowingly during the dose algorithm commissioning stage, and the probability of it being identified during the verification stage. The clinical impact of each commissioning error was evaluated using representative IMRT plans including low and intermediate risk prostate, head and neck, mesothelioma, and scalp; the sensitivity of the TG-119 and IROC phantoms was evaluated by comparing dosimetric changes to the dose planes where film measurements occur and change in point doses where dosimeter measurements occur. No commissioning errors were found to have both a low probability of detection and high clinical severity. When errors do occur, the IROC credentialing and TG 119 commissioning criteria are generally effective at detecting them; however, for the IROC phantom, OAR point-dose measurements are the most sensitive despite being currently excluded from IROC analysis. Point-dose measurements with an absolute dose constraint were the most effective at detecting errors, while film analysis using a gamma comparison and the IROC film distance to agreement criteria were less effective at detecting the specific commissioning errors implemented here.

  11. High variability in strain estimation errors when using a commercial ultrasound speckle tracking algorithm on tendon tissue.

    PubMed

    Fröberg, Åsa; Mårtensson, Mattias; Larsson, Matilda; Janerot-Sjöberg, Birgitta; D'Hooge, Jan; Arndt, Anton

    2016-10-01

    Ultrasound speckle tracking offers a non-invasive way of studying strain in the free Achilles tendon where no anatomical landmarks are available for tracking. This provides new possibilities for studying injury mechanisms during sport activity and the effects of shoes, orthotic devices, and rehabilitation protocols on tendon biomechanics. To investigate the feasibility of using a commercial ultrasound speckle tracking algorithm for assessing strain in tendon tissue. A polyvinyl alcohol (PVA) phantom, three porcine tendons, and a human Achilles tendon were mounted in a materials testing machine and loaded to 4% peak strain. Ultrasound long-axis cine-loops of the samples were recorded. Speckle tracking analysis of axial strain was performed using a commercial speckle tracking software. Estimated strain was then compared to reference strain known from the materials testing machine. Two frame rates and two region of interest (ROI) sizes were evaluated. Best agreement between estimated strain and reference strain was found in the PVA phantom (absolute error in peak strain: 0.21 ± 0.08%). The absolute error in peak strain varied between 0.72 ± 0.65% and 10.64 ± 3.40% in the different tendon samples. Strain determined with a frame rate of 39.4 Hz had lower errors than 78.6 Hz as was the case with a 22 mm compared to an 11 mm ROI. Errors in peak strain estimation showed high variability between tendon samples and were large in relation to strain levels previously described in the Achilles tendon. © The Foundation Acta Radiologica 2016.

  12. Investigating Absolute Value: A Real World Application

    ERIC Educational Resources Information Center

    Kidd, Margaret; Pagni, David

    2009-01-01

    Making connections between various representations is important in mathematics. In this article, the authors discuss the numeric, algebraic, and graphical representations of sums of absolute values of linear functions. The initial explanations are accessible to all students who have experience graphing and who understand that absolute value simply…

  13. Stimulus probability effects in absolute identification.

    PubMed

    Kent, Christopher; Lamberts, Koen

    2016-05-01

    This study investigated the effect of stimulus presentation probability on accuracy and response times in an absolute identification task. Three schedules of presentation were used to investigate the interaction between presentation probability and stimulus position within the set. Data from individual participants indicated strong effects of presentation probability on both proportion correct and response times. The effects were moderated by the ubiquitous stimulus position effect. The accuracy and response time data were predicted by an exemplar-based model of perceptual cognition (Kent & Lamberts, 2005). The bow in discriminability was also attenuated when presentation probability for middle items was relatively high, an effect that will constrain future model development. The study provides evidence for item-specific learning in absolute identification. Implications for other theories of absolute identification are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  14. Absolute Position of Targets Measured Through a Chamber Window Using Lidar Metrology Systems

    NASA Technical Reports Server (NTRS)

    Kubalak, David; Hadjimichael, Theodore; Ohl, Raymond; Slotwinski, Anthony; Telfer, Randal; Hayden, Joseph

    2012-01-01

    Lidar is a useful tool for taking metrology measurements without the need for physical contact with the parts under test. Lidar instruments are aimed at a target using azimuth and elevation stages, then focus a beam of coherent, frequency modulated laser energy onto the target, such as the surface of a mechanical structure. Energy from the reflected beam is mixed with an optical reference signal that travels in a fiber path internal to the instrument, and the range to the target is calculated based on the difference in the frequency of the returned and reference signals. In cases when the parts are in extreme environments, additional steps need to be taken to separate the operator and lidar from that environment. A model has been developed that accurately reduces the lidar data to an absolute position and accounts for the three media in the testbed air, fused silica, and vacuum but the approach can be adapted for any environment or material. The accuracy of laser metrology measurements depends upon knowing the parameters of the media through which the measurement beam travels. Under normal conditions, this means knowledge of the temperature, pressure, and humidity of the air in the measurement volume. In the past, chamber windows have been used to separate the measuring device from the extreme environment within the chamber and still permit optical measurement, but, so far, only relative changes have been diagnosed. The ability to make accurate measurements through a window presents a challenge as there are a number of factors to consider. In the case of the lidar, the window will increase the time-of-flight of the laser beam causing a ranging error, and refract the direction of the beam causing angular positioning errors. In addition, differences in pressure, temperature, and humidity on each side of the window will cause slight atmospheric index changes and induce deformation and a refractive index gradient within the window. Also, since the window is a

  15. A Conceptual Approach to Absolute Value Equations and Inequalities

    ERIC Educational Resources Information Center

    Ellis, Mark W.; Bryson, Janet L.

    2011-01-01

    The absolute value learning objective in high school mathematics requires students to solve far more complex absolute value equations and inequalities. When absolute value problems become more complex, students often do not have sufficient conceptual understanding to make any sense of what is happening mathematically. The authors suggest that the…

  16. Regional biases in absolute sea-level estimates from tide gauge data due to residual unmodeled vertical land movement

    NASA Astrophysics Data System (ADS)

    King, Matt A.; Keshin, Maxim; Whitehouse, Pippa L.; Thomas, Ian D.; Milne, Glenn; Riva, Riccardo E. M.

    2012-07-01

    The only vertical land movement signal routinely corrected for when estimating absolute sea-level change from tide gauge data is that due to glacial isostatic adjustment (GIA). We compare modeled GIA uplift (ICE-5G + VM2) with vertical land movement at ˜300 GPS stations located near to a global set of tide gauges, and find regionally coherent differences of commonly ±0.5-2 mm/yr. Reference frame differences and signal due to present-day mass trends cannot reconcile these differences. We examine sensitivity to the GIA Earth model by fitting to a subset of the GPS velocities and find substantial regional sensitivity, but no single Earth model is able to reduce the disagreement in all regions. We suggest errors in ice history and neglected lateral Earth structure dominate model-data differences, and urge caution in the use of modeled GIA uplift alone when interpreting regional- and global- scale absolute (geocentric) sea level from tide gauge data.

  17. Geochemistry and mineralogy of fly-ash from the Mae Moh lignite deposit, Thailand

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hart, B.R.; Powell, M.A.; Fyfe, W.S.

    The concentration of 21 elements in fly ash from three boilers (75 MW, 150 MW, and 300 MW) at the EGAT power plant, Mae Moh, Thailand, were determined by INAA. The concentration of 10 major elements was determined by XRF. As, Co, Cr, Ni, Mo, and Sb generally increase in concentration going from bottom ash (BA) through the sequence of electrostatic precipitator ashes (ESPA) and reach maxima of As (352 ppm), Co (45 ppm), Cr (105 ppm), Mo (32 ppm), Ni (106 ppm), and Sb (15 ppm) in the ESPA. Ce, Cs, Fe, Hf, La, Sc, Ta, Tb, and Ybmore » did not exhibit concentration trends or are variable except in the case of one boiler, which showed an increase going from BA to ESPA. Only Br decreased in composition going from BA to ESPA. Rb, Sm, U, and Th showed marked variation in trends. The major elements identified by EDS were Al, Si, S, K, Ca, Fe, and Ba, with minor amounts of Mg, Na, Ti, Mn, and Sr. Al, Si, K, and Ca occur together and are present in most of the fly-ash particles. Ba was found as a major component with Ca, Al, and Si. Fe and Ca are usually associated with sulfur. Some small spheres (< 5 {mu}m) are comprised almost entirely of Fe (probably as oxide). Symplectite textures are noted in high-Fe phases. All elements except Br are significantly enriched in the fly ash relative to the coal, which contains 35% ash. Particle chemistry is consistent with the major mineral phases identified by XRD, which include: quartz, magnetite, mullite, gehlenite, anorthite, hematite, anhydrite, and clinopyroxene.« less

  18. Absolute pitch in a four-year-old boy with autism.

    PubMed

    Brenton, James N; Devries, Seth P; Barton, Christine; Minnich, Heike; Sokol, Deborah K

    2008-08-01

    Absolute pitch is the ability to identify the pitch of an isolated tone. We report on a 4-year-old boy with autism and absolute pitch, one of the youngest reported in the literature. Absolute pitch is thought to be attributable to a single gene, transmitted in an autosomal-dominant fashion. The association of absolute pitch with autism raises the speculation that this talent could be linked to a genetically distinct subset of children with autism. Further, the identification of absolute pitch in even young children with autism may lead to a lifelong skill.

  19. Reducing errors benefits the field-based learning of a fundamental movement skill in children.

    PubMed

    Capio, C M; Poolton, J M; Sit, C H P; Holmstrom, M; Masters, R S W

    2013-03-01

    Proficient fundamental movement skills (FMS) are believed to form the basis of more complex movement patterns in sports. This study examined the development of the FMS of overhand throwing in children through either an error-reduced (ER) or error-strewn (ES) training program. Students (n = 216), aged 8-12 years (M = 9.16, SD = 0.96), practiced overhand throwing in either a program that reduced errors during practice (ER) or one that was ES. ER program reduced errors by incrementally raising the task difficulty, while the ES program had an incremental lowering of task difficulty. Process-oriented assessment of throwing movement form (Test of Gross Motor Development-2) and product-oriented assessment of throwing accuracy (absolute error) were performed. Changes in performance were examined among children in the upper and lower quartiles of the pretest throwing accuracy scores. ER training participants showed greater gains in movement form and accuracy, and performed throwing more effectively with a concurrent secondary cognitive task. Movement form improved among girls, while throwing accuracy improved among children with low ability. Reduced performance errors in FMS training resulted in greater learning than a program that did not restrict errors. Reduced cognitive processing costs (effective dual-task performance) associated with such approach suggest its potential benefits for children with developmental conditions. © 2011 John Wiley & Sons A/S.

  20. The Absolute Spectrum Polarimeter (ASP)

    NASA Technical Reports Server (NTRS)

    Kogut, A. J.

    2010-01-01

    The Absolute Spectrum Polarimeter (ASP) is an Explorer-class mission to map the absolute intensity and linear polarization of the cosmic microwave background and diffuse astrophysical foregrounds over the full sky from 30 GHz to 5 THz. The principal science goal is the detection and characterization of linear polarization from an inflationary epoch in the early universe, with tensor-to-scalar ratio r much greater than 1O(raised to the power of { -3}) and Compton distortion y < 10 (raised to the power of{-6}). We describe the ASP instrument and mission architecture needed to detect the signature of an inflationary epoch in the early universe using only 4 semiconductor bolometers.

  1. The absolute disparity anomaly and the mechanism of relative disparities.

    PubMed

    Chopin, Adrien; Levi, Dennis; Knill, David; Bavelier, Daphne

    2016-06-01

    There has been a long-standing debate about the mechanisms underlying the perception of stereoscopic depth and the computation of the relative disparities that it relies on. Relative disparities between visual objects could be computed in two ways: (a) using the difference in the object's absolute disparities (Hypothesis 1) or (b) using relative disparities based on the differences in the monocular separations between objects (Hypothesis 2). To differentiate between these hypotheses, we measured stereoscopic discrimination thresholds for lines with different absolute and relative disparities. Participants were asked to judge the depth of two lines presented at the same distance from the fixation plane (absolute disparity) or the depth between two lines presented at different distances (relative disparity). We used a single stimulus method involving a unique memory component for both conditions, and no extraneous references were available. We also measured vergence noise using Nonius lines. Stereo thresholds were substantially worse for absolute disparities than for relative disparities, and the difference could not be explained by vergence noise. We attribute this difference to an absence of conscious readout of absolute disparities, termed the absolute disparity anomaly. We further show that the pattern of correlations between vergence noise and absolute and relative disparity acuities can be explained jointly by the existence of the absolute disparity anomaly and by the assumption that relative disparity information is computed from absolute disparities (Hypothesis 1).

  2. The absolute disparity anomaly and the mechanism of relative disparities

    PubMed Central

    Chopin, Adrien; Levi, Dennis; Knill, David; Bavelier, Daphne

    2016-01-01

    There has been a long-standing debate about the mechanisms underlying the perception of stereoscopic depth and the computation of the relative disparities that it relies on. Relative disparities between visual objects could be computed in two ways: (a) using the difference in the object's absolute disparities (Hypothesis 1) or (b) using relative disparities based on the differences in the monocular separations between objects (Hypothesis 2). To differentiate between these hypotheses, we measured stereoscopic discrimination thresholds for lines with different absolute and relative disparities. Participants were asked to judge the depth of two lines presented at the same distance from the fixation plane (absolute disparity) or the depth between two lines presented at different distances (relative disparity). We used a single stimulus method involving a unique memory component for both conditions, and no extraneous references were available. We also measured vergence noise using Nonius lines. Stereo thresholds were substantially worse for absolute disparities than for relative disparities, and the difference could not be explained by vergence noise. We attribute this difference to an absence of conscious readout of absolute disparities, termed the absolute disparity anomaly. We further show that the pattern of correlations between vergence noise and absolute and relative disparity acuities can be explained jointly by the existence of the absolute disparity anomaly and by the assumption that relative disparity information is computed from absolute disparities (Hypothesis 1). PMID:27248566

  3. Using absolute gravimeter data to determine vertical gravity gradients

    USGS Publications Warehouse

    Robertson, D.S.

    2001-01-01

    The position versus time data from a free-fall absolute gravimeter can be used to estimate the vertical gravity gradient in addition to the gravity value itself. Hipkin has reported success in estimating the vertical gradient value using a data set of unusually good quality. This paper explores techniques that may be applicable to a broader class of data that may be contaminated with "system response" errors of larger magnitude than were evident in the data used by Hipkin. This system response function is usually modelled as a sum of exponentially decaying sinusoidal components. The technique employed here involves combining the x0, v0 and g parameters from all the drops made during a site occupation into a single least-squares solution, and including the value of the vertical gradient and the coefficients of system response function in the same solution. The resulting non-linear equations must be solved iteratively and convergence presents some difficulties. Sparse matrix techniques are used to make the least-squares problem computationally tractable.

  4. Rapid rotators revisited: absolute dimensions of KOI-13

    NASA Astrophysics Data System (ADS)

    Howarth, Ian D.; Morello, Giuseppe

    2017-09-01

    We analyse Kepler light-curves of the exoplanet Kepler Object of Interest no. 13b (KOI-13b) transiting its moderately rapidly rotating (gravity-darkened) parent star. A physical model, with minimal ad hoc free parameters, reproduces the time-averaged light-curve at the ˜10 parts per million level. We demonstrate that this Roche-model solution allows the absolute dimensions of the system to be determined from the star's projected equatorial rotation speed, ve sin I*, without any additional assumptions; we find a planetary radius RP = (1.33 ± 0.05) R♃, stellar polar radius Rp★ = (1.55 ± 0.06) R⊙, combined mass M* + MP( ≃ M*) = (1.47 ± 0.17) M⊙ and distance d ≃ (370 ± 25) pc, where the errors are dominated by uncertainties in relative flux contribution of the visual-binary companion KOI-13B. The implied stellar rotation period is within ˜5 per cent of the non-orbital, 25.43-hr signal found in the Kepler photometry. We show that the model accurately reproduces independent tomographic observations, and yields an offset between orbital and stellar-rotation angular-momentum vectors of 60.25° ± 0.05°.

  5. Preliminary Evidence for Reduced Post-Error Reaction Time Slowing in Hyperactive/Inattentive Preschool Children

    PubMed Central

    Berwid, Olga G.; Halperin, Jeffrey M.; Johnson, Ray E.; Marks, David J.

    2013-01-01

    Background Attention-Deficit/Hyperactivity Disorder has been associated with deficits in self-regulatory cognitive processes, some of which are thought to lie at the heart of the disorder. Slowing of reaction times (RTs) for correct responses following errors made during decision tasks has been interpreted as an indication of intact self-regulatory functioning and has been shown to be attenuated in school-aged children with ADHD. This study attempted to examine whether ADHD symptoms are associated with an early-emerging deficit in post-error slowing. Method A computerized two-choice RT task was administered to an ethnically diverse sample of preschool-aged children classified as either ‘control’ (n = 120) or ‘hyperactive/inattentive’ (HI; n = 148) using parent- and teacher-rated ADHD symptoms. Analyses were conducted to determine whether HI preschoolers exhibit a deficit in this self-regulatory ability. Results HI children exhibited reduced post-error slowing relative to controls on the trials selected for analysis. Supplementary analyses indicated that this may have been due to a reduced proportion of trials following errors on which HI children slowed rather than to a reduction in the absolute magnitude of slowing on all trials following errors. Conclusions High levels of ADHD symptoms in preschoolers may be associated with a deficit in error processing as indicated by post-error slowing. The results of supplementary analyses suggest that this deficit is perhaps more a result of failures to perceive errors than of difficulties with executive control. PMID:23387525

  6. Assessment of Gamma-Ray-Spectra Analysis Method Utilizing the Fireworks Algorithm for Various Error Measures

    DOE PAGES

    Alamaniotis, Miltiadis; Tsoukalas, Lefteri H.

    2018-01-01

    The analysis of measured data plays a significant role in enhancing nuclear nonproliferation mainly by inferring the presence of patterns associated with special nuclear materials. Among various types of measurements, gamma-ray spectra is the widest utilized type of data in nonproliferation applications. In this paper, a method that employs the fireworks algorithm (FWA) for analyzing gamma-ray spectra aiming at detecting gamma signatures is presented. In particular, FWA is utilized to fit a set of known signatures to a measured spectrum by optimizing an objective function, where non-zero coefficients express the detected signatures. FWA is tested on a set of experimentallymore » obtained measurements optimizing various objective functions—MSE, RMSE, Theil-2, MAE, MAPE, MAP—with results exhibiting its potential in providing highly accurate and precise signature detection. Finally and furthermore, FWA is benchmarked against genetic algorithms and multiple linear regression, showing its superiority over those algorithms regarding precision with respect to MAE, MAPE, and MAP measures.« less

  7. Action errors, error management, and learning in organizations.

    PubMed

    Frese, Michael; Keith, Nina

    2015-01-03

    Every organization is confronted with errors. Most errors are corrected easily, but some may lead to negative consequences. Organizations often focus on error prevention as a single strategy for dealing with errors. Our review suggests that error prevention needs to be supplemented by error management--an approach directed at effectively dealing with errors after they have occurred, with the goal of minimizing negative and maximizing positive error consequences (examples of the latter are learning and innovations). After defining errors and related concepts, we review research on error-related processes affected by error management (error detection, damage control). Empirical evidence on positive effects of error management in individuals and organizations is then discussed, along with emotional, motivational, cognitive, and behavioral pathways of these effects. Learning from errors is central, but like other positive consequences, learning occurs under certain circumstances--one being the development of a mind-set of acceptance of human error.

  8. Absolute Density Calibration Cell for Laser Induced Fluorescence Erosion Rate Measurements

    NASA Technical Reports Server (NTRS)

    Domonkos, Matthew T.; Stevens, Richard E.

    2001-01-01

    Flight qualification of ion thrusters typically requires testing on the order of 10,000 hours. Extensive knowledge of wear mechanisms and rates is necessary to establish design confidence prior to long duration tests. Consequently, real-time erosion rate measurements offer the potential both to reduce development costs and to enhance knowledge of the dependency of component wear on operating conditions. Several previous studies have used laser-induced fluorescence (LIF) to measure real-time, in situ erosion rates of ion thruster accelerator grids. Those studies provided only relative measurements of the erosion rate. In the present investigation, a molybdenum tube was resistively heated such that the evaporation rate yielded densities within the tube on the order of those expected from accelerator grid erosion. This work examines the suitability of the density cell as an absolute calibration source for LIF measurements, and the intrinsic error was evaluated.

  9. Applicability of AgMERRA Forcing Dataset to Fill Gaps in Historical in-situ Meteorological Data

    NASA Astrophysics Data System (ADS)

    Bannayan, M.; Lashkari, A.; Zare, H.; Asadi, S.; Salehnia, N.

    2015-12-01

    Integrated assessment studies of food production systems use crop models to simulate the effects of climate and socio-economic changes on food security. Climate forcing data is one of those key inputs of crop models. This study evaluated the performance of AgMERRA climate forcing dataset to fill gaps in historical in-situ meteorological data for different climatic regions of Iran. AgMERRA dataset intercompared with in- situ observational dataset for daily maximum and minimum temperature and precipitation during 1980-2010 periods via Root Mean Square error (RMSE), Mean Absolute Error (MAE) and Mean Bias Error (MBE) for 17 stations in four climatic regions included humid and moderate, cold, dry and arid, hot and humid. Moreover, probability distribution function and cumulative distribution function compared between model and observed data. The results of measures of agreement between AgMERRA data and observed data demonstrated that there are small errors in model data for all stations. Except for stations which are located in cold regions, model data in the other stations illustrated under-prediction for daily maximum temperature and precipitation. However, it was not significant. In addition, probability distribution function and cumulative distribution function showed the same trend for all stations between model and observed data. Therefore, the reliability of AgMERRA dataset is high to fill gaps in historical observations in different climatic regions of Iran as well as it could be applied as a basis for future climate scenarios.

  10. Intranasal Pharmacokinetic Data for Triptans Such as Sumatriptan and Zolmitriptan Can Render Area Under the Curve (AUC) Predictions for the Oral Route: Strategy Development and Application.

    PubMed

    Srinivas, Nuggehally R; Syed, Muzeeb

    2016-01-01

    Limited pharmacokinetic sampling strategy may be useful for predicting the area under the curve (AUC) for triptans and may have clinical utility as a prospective tool for prediction. Using appropriate intranasal pharmacokinetic data, a Cmax vs. AUC relationship was established by linear regression models for sumatriptan and zolmitriptan. The predictions of the AUC values were performed using published mean/median Cmax data and appropriate regression lines. The quotient of observed and predicted values rendered fold-difference calculation. The mean absolute error (MAE), mean positive error (MPE), mean negative error (MNE), root mean square error (RMSE), correlation coefficient (r), and the goodness of the AUC fold prediction were used to evaluate the two triptans. Also, data from the mean concentration profiles at time points of 1 hour (sumatriptan) and 3 hours (zolmitriptan) were used for the AUC prediction. The Cmax vs. AUC models displayed excellent correlation for both sumatriptan (r = .9997; P < .001) and zolmitriptan (r = .9999; P < .001). Irrespective of the two triptans, the majority of the predicted AUCs (83%-85%) were within 0.76-1.25-fold difference using the regression model. The prediction of AUC values for sumatriptan or zolmitriptan using the concentration data that reflected the Tmax occurrence were in the proximity of the reported values. In summary, the Cmax vs. AUC models exhibited strong correlations for sumatriptan and zolmitriptan. The usefulness of the prediction of the AUC values was established by a rigorous statistical approach.

  11. Introducing the Mean Absolute Deviation "Effect" Size

    ERIC Educational Resources Information Center

    Gorard, Stephen

    2015-01-01

    This paper revisits the use of effect sizes in the analysis of experimental and similar results, and reminds readers of the relative advantages of the mean absolute deviation as a measure of variation, as opposed to the more complex standard deviation. The mean absolute deviation is easier to use and understand, and more tolerant of extreme…

  12. Monolithically integrated absolute frequency comb laser system

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wanke, Michael C.

    2016-07-12

    Rather than down-convert optical frequencies, a QCL laser system directly generates a THz frequency comb in a compact monolithically integrated chip that can be locked to an absolute frequency without the need of a frequency-comb synthesizer. The monolithic, absolute frequency comb can provide a THz frequency reference and tool for high-resolution broad band spectroscopy.

  13. Modeling coherent errors in quantum error correction

    NASA Astrophysics Data System (ADS)

    Greenbaum, Daniel; Dutton, Zachary

    2018-01-01

    Analysis of quantum error correcting codes is typically done using a stochastic, Pauli channel error model for describing the noise on physical qubits. However, it was recently found that coherent errors (systematic rotations) on physical data qubits result in both physical and logical error rates that differ significantly from those predicted by a Pauli model. Here we examine the accuracy of the Pauli approximation for noise containing coherent errors (characterized by a rotation angle ɛ) under the repetition code. We derive an analytic expression for the logical error channel as a function of arbitrary code distance d and concatenation level n, in the small error limit. We find that coherent physical errors result in logical errors that are partially coherent and therefore non-Pauli. However, the coherent part of the logical error is negligible at fewer than {ε }-({dn-1)} error correction cycles when the decoder is optimized for independent Pauli errors, thus providing a regime of validity for the Pauli approximation. Above this number of correction cycles, the persistent coherent logical error will cause logical failure more quickly than the Pauli model would predict, and this may need to be combated with coherent suppression methods at the physical level or larger codes.

  14. Semi-empirical model for retrieval of soil moisture using RISAT-1 C-Band SAR data over a sub-tropical semi-arid area of Rewari district, Haryana (India)

    NASA Astrophysics Data System (ADS)

    Rawat, Kishan Singh; Sehgal, Vinay Kumar; Pradhan, Sanatan; Ray, Shibendu S.

    2018-03-01

    We have estimated soil moisture (SM) by using circular horizontal polarization backscattering coefficient (σ o_{RH}), differences of circular vertical and horizontal σ o (σ o_{RV} {-} σ o_{RH}) from FRS-1 data of Radar Imaging Satellite (RISAT-1) and surface roughness in terms of RMS height ({RMS}_{height}). We examined the performance of FRS-1 in retrieving SM under wheat crop at tillering stage. Results revealed that it is possible to develop a good semi-empirical model (SEM) to estimate SM of the upper soil layer using RISAT-1 SAR data rather than using existing empirical model based on only single parameter, i.e., σ o. Near surface SM measurements were related to σ o_{RH}, σ o_{RV} {-} σ o_{RH} derived using 5.35 GHz (C-band) image of RISAT-1 and {RMS}_{height}. The roughness component derived in terms of {RMS}_{height} showed a good positive correlation with σ o_{RV} {-} σ o_{RH} (R2 = 0.65). By considering all the major influencing factors (σ o_{RH}, σ o_{RV} {-} σ o_{RH}, and {RMS}_{height}), an SEM was developed where SM (volumetric) predicted values depend on σ o_{RH}, σ o_{RV} {-} σ o_{RH}, and {RMS}_{height}. This SEM showed R2 of 0.87 and adjusted R2 of 0.85, multiple R=0.94 and with standard error of 0.05 at 95% confidence level. Validation of the SM derived from semi-empirical model with observed measurement ({SM}_{Observed}) showed root mean square error (RMSE) = 0.06, relative-RMSE (R-RMSE) = 0.18, mean absolute error (MAE) = 0.04, normalized RMSE (NRMSE) = 0.17, Nash-Sutcliffe efficiency (NSE) = 0.91 ({≈ } 1), index of agreement (d) = 1, coefficient of determination (R2) = 0.87, mean bias error (MBE) = 0.04, standard error of estimate (SEE) = 0.10, volume error (VE) = 0.15, variance of the distribution of differences ({S}d2) = 0.004. The developed SEM showed better performance in estimating SM than Topp empirical model which is based only on σ o. By using the developed SEM, top soil SM can be estimated with low mean absolute

  15. Modelling hourly dissolved oxygen concentration (DO) using dynamic evolving neural-fuzzy inference system (DENFIS)-based approach: case study of Klamath River at Miller Island Boat Ramp, OR, USA.

    PubMed

    Heddam, Salim

    2014-01-01

    In this study, we present application of an artificial intelligence (AI) technique model called dynamic evolving neural-fuzzy inference system (DENFIS) based on an evolving clustering method (ECM), for modelling dissolved oxygen concentration in a river. To demonstrate the forecasting capability of DENFIS, a one year period from 1 January 2009 to 30 December 2009, of hourly experimental water quality data collected by the United States Geological Survey (USGS Station No: 420853121505500) station at Klamath River at Miller Island Boat Ramp, OR, USA, were used for model development. Two DENFIS-based models are presented and compared. The two DENFIS systems are: (1) offline-based system named DENFIS-OF, and (2) online-based system, named DENFIS-ON. The input variables used for the two models are water pH, temperature, specific conductance, and sensor depth. The performances of the models are evaluated using root mean square errors (RMSE), mean absolute error (MAE), Willmott index of agreement (d) and correlation coefficient (CC) statistics. The lowest root mean square error and highest correlation coefficient values were obtained with the DENFIS-ON method. The results obtained with DENFIS models are compared with linear (multiple linear regression, MLR) and nonlinear (multi-layer perceptron neural networks, MLPNN) methods. This study demonstrates that DENFIS-ON investigated herein outperforms all the proposed techniques for DO modelling.

  16. Modeling of surface dust concentration in snow cover at industrial area using neural networks and kriging

    NASA Astrophysics Data System (ADS)

    Sergeev, A. P.; Tarasov, D. A.; Buevich, A. G.; Shichkin, A. V.; Tyagunov, A. G.; Medvedev, A. N.

    2017-06-01

    Modeling of spatial distribution of pollutants in the urbanized territories is difficult, especially if there are multiple emission sources. When monitoring such territories, it is often impossible to arrange the necessary detailed sampling. Because of this, the usual methods of analysis and forecasting based on geostatistics are often less effective. Approaches based on artificial neural networks (ANNs) demonstrate the best results under these circumstances. This study compares two models based on ANNs, which are multilayer perceptron (MLP) and generalized regression neural networks (GRNNs) with the base geostatistical method - kriging. Models of the spatial dust distribution in the snow cover around the existing copper quarry and in the area of emissions of a nickel factory were created. To assess the effectiveness of the models three indices were used: the mean absolute error (MAE), the root-mean-square error (RMSE), and the relative root-mean-square error (RRMSE). Taking into account all indices the model of GRNN proved to be the most accurate which included coordinates of the sampling points and the distance to the likely emission source as input parameters for the modeling. Maps of spatial dust distribution in the snow cover were created in the study area. It has been shown that the models based on ANNs were more accurate than the kriging, particularly in the context of a limited data set.

  17. Resolution-enhancement and sampling error correction based on molecular absorption line in frequency scanning interferometry

    NASA Astrophysics Data System (ADS)

    Pan, Hao; Qu, Xinghua; Shi, Chunzhao; Zhang, Fumin; Li, Yating

    2018-06-01

    The non-uniform interval resampling method has been widely used in frequency modulated continuous wave (FMCW) laser ranging. In the large-bandwidth and long-distance measurements, the range peak is deteriorated due to the fiber dispersion mismatch. In this study, we analyze the frequency-sampling error caused by the mismatch and measure it using the spectroscopy of molecular frequency references line. By using the adjacent points' replacement and spline interpolation technique, the sampling errors could be eliminated. The results demonstrated that proposed method is suitable for resolution-enhancement and high-precision measurement. Moreover, using the proposed method, we achieved the precision of absolute distance less than 45 μm within 8 m.

  18. Errors in causal inference: an organizational schema for systematic error and random error.

    PubMed

    Suzuki, Etsuji; Tsuda, Toshihide; Mitsuhashi, Toshiharu; Mansournia, Mohammad Ali; Yamamoto, Eiji

    2016-11-01

    To provide an organizational schema for systematic error and random error in estimating causal measures, aimed at clarifying the concept of errors from the perspective of causal inference. We propose to divide systematic error into structural error and analytic error. With regard to random error, our schema shows its four major sources: nondeterministic counterfactuals, sampling variability, a mechanism that generates exposure events and measurement variability. Structural error is defined from the perspective of counterfactual reasoning and divided into nonexchangeability bias (which comprises confounding bias and selection bias) and measurement bias. Directed acyclic graphs are useful to illustrate this kind of error. Nonexchangeability bias implies a lack of "exchangeability" between the selected exposed and unexposed groups. A lack of exchangeability is not a primary concern of measurement bias, justifying its separation from confounding bias and selection bias. Many forms of analytic errors result from the small-sample properties of the estimator used and vanish asymptotically. Analytic error also results from wrong (misspecified) statistical models and inappropriate statistical methods. Our organizational schema is helpful for understanding the relationship between systematic error and random error from a previously less investigated aspect, enabling us to better understand the relationship between accuracy, validity, and precision. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. Electronic Absolute Cartesian Autocollimator

    NASA Technical Reports Server (NTRS)

    Leviton, Douglas B.

    2006-01-01

    An electronic absolute Cartesian autocollimator performs the same basic optical function as does a conventional all-optical or a conventional electronic autocollimator but differs in the nature of its optical target and the manner in which the position of the image of the target is measured. The term absolute in the name of this apparatus reflects the nature of the position measurement, which, unlike in a conventional electronic autocollimator, is based absolutely on the position of the image rather than on an assumed proportionality between the position and the levels of processed analog electronic signals. The term Cartesian in the name of this apparatus reflects the nature of its optical target. Figure 1 depicts the electronic functional blocks of an electronic absolute Cartesian autocollimator along with its basic optical layout, which is the same as that of a conventional autocollimator. Referring first to the optical layout and functions only, this or any autocollimator is used to measure the compound angular deviation of a flat datum mirror with respect to the optical axis of the autocollimator itself. The optical components include an illuminated target, a beam splitter, an objective or collimating lens, and a viewer or detector (described in more detail below) at a viewing plane. The target and the viewing planes are focal planes of the lens. Target light reflected by the datum mirror is imaged on the viewing plane at unit magnification by the collimating lens. If the normal to the datum mirror is parallel to the optical axis of the autocollimator, then the target image is centered on the viewing plane. Any angular deviation of the normal from the optical axis manifests itself as a lateral displacement of the target image from the center. The magnitude of the displacement is proportional to the focal length and to the magnitude (assumed to be small) of the angular deviation. The direction of the displacement is perpendicular to the axis about which the

  20. Estimation of metabolic energy expenditure from core temperature using a human thermoregulatory model.

    PubMed

    Welles, Alexander P; Buller, Mark J; Looney, David P; Rumpler, William V; Gribok, Andrei V; Hoyt, Reed W

    2018-02-01

    Human metabolic energy expenditure is critical to many scientific disciplines but can only be measured using expensive and/or restrictive equipment. The aim of this work is to determine whether the SCENARIO thermoregulatory model can be adapted to estimate metabolic rate (M) from core body temperature (T C ). To validate this method of M estimation, data were collected from fifteen test volunteers (age = 23 ± 3yr, height = 1.73 ± 0.07m, mass = 68.6 ± 8.7kg, body fat = 16.7 ± 7.3%; mean ± SD) who wore long sleeved nylon jackets and pants (I tot,clo = 1.22, I m = 0.41) during treadmill exercise tasks (32 trials; 7.8 ± 0.5km in 1h; air temp. = 22°C, 50% RH, wind speed = 0.35ms -1 ). Core body temperatures were recorded by ingested thermometer pill and M data were measured via whole room indirect calorimetry. Metabolic rate was estimated for 5min epochs in a two-step process. First, for a given epoch, a range of M values were input to the SCENARIO model and a corresponding range of T C values were output. Second, the output T C range value with the lowest absolute error relative to the observed T C for the given epoch was identified and its corresponding M range input was selected as the estimated M for that epoch. This process was then repeated for each subsequent remaining epoch. Root mean square error (RMSE), mean absolute error (MAE), and bias between observed and estimated M were 186W, 130 ± 174W, and 33 ± 183W, respectively. The RMSE for total energy expenditure by exercise period was 0.30 MJ. These results indicate that the SCENARIO model is useful for estimating M from T C when measurement is otherwise impractical. Published by Elsevier Ltd.

  1. Adaptive neuro-fuzzy inference system for temperature and humidity profile retrieval from microwave radiometer observations

    NASA Astrophysics Data System (ADS)

    Ramesh, K.; Kesarkar, A. P.; Bhate, J.; Venkat Ratnam, M.; Jayaraman, A.

    2015-01-01

    The retrieval of accurate profiles of temperature and water vapour is important for the study of atmospheric convection. Recent development in computational techniques motivated us to use adaptive techniques in the retrieval algorithms. In this work, we have used an adaptive neuro-fuzzy inference system (ANFIS) to retrieve profiles of temperature and humidity up to 10 km over the tropical station Gadanki (13.5° N, 79.2° E), India. ANFIS is trained by using observations of temperature and humidity measurements by co-located Meisei GPS radiosonde (henceforth referred to as radiosonde) and microwave brightness temperatures observed by radiometrics multichannel microwave radiometer MP3000 (MWR). ANFIS is trained by considering these observations during rainy and non-rainy days (ANFIS(RD + NRD)) and during non-rainy days only (ANFIS(NRD)). The comparison of ANFIS(RD + NRD) and ANFIS(NRD) profiles with independent radiosonde observations and profiles retrieved using multivariate linear regression (MVLR: RD + NRD and NRD) and artificial neural network (ANN) indicated that the errors in the ANFIS(RD + NRD) are less compared to other retrieval methods. The Pearson product movement correlation coefficient (r) between retrieved and observed profiles is more than 92% for temperature profiles for all techniques and more than 99% for the ANFIS(RD + NRD) technique Therefore this new techniques is relatively better for the retrieval of temperature profiles. The comparison of bias, mean absolute error (MAE), RMSE and symmetric mean absolute percentage error (SMAPE) of retrieved temperature and relative humidity (RH) profiles using ANN and ANFIS also indicated that profiles retrieved using ANFIS(RD + NRD) are significantly better compared to the ANN technique. The analysis of profiles concludes that retrieved profiles using ANFIS techniques have improved the temperature retrievals substantially; however, the retrieval of RH by all techniques considered in this paper (ANN, MVLR and

  2. Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model

    NASA Astrophysics Data System (ADS)

    Yaseen, Zaher Mundher; Ebtehaj, Isa; Bonakdari, Hossein; Deo, Ravinesh C.; Danandeh Mehr, Ali; Mohtar, Wan Hanna Melini Wan; Diop, Lamine; El-shafie, Ahmed; Singh, Vijay P.

    2017-11-01

    The present study proposes a new hybrid evolutionary Adaptive Neuro-Fuzzy Inference Systems (ANFIS) approach for monthly streamflow forecasting. The proposed method is a novel combination of the ANFIS model with the firefly algorithm as an optimizer tool to construct a hybrid ANFIS-FFA model. The results of the ANFIS-FFA model is compared with the classical ANFIS model, which utilizes the fuzzy c-means (FCM) clustering method in the Fuzzy Inference Systems (FIS) generation. The historical monthly streamflow data for Pahang River, which is a major river system in Malaysia that characterized by highly stochastic hydrological patterns, is used in the study. Sixteen different input combinations with one to five time-lagged input variables are incorporated into the ANFIS-FFA and ANFIS models to consider the antecedent seasonal variations in historical streamflow data. The mean absolute error (MAE), root mean square error (RMSE) and correlation coefficient (r) are used to evaluate the forecasting performance of ANFIS-FFA model. In conjunction with these metrics, the refined Willmott's Index (Drefined), Nash-Sutcliffe coefficient (ENS) and Legates and McCabes Index (ELM) are also utilized as the normalized goodness-of-fit metrics. Comparison of the results reveals that the FFA is able to improve the forecasting accuracy of the hybrid ANFIS-FFA model (r = 1; RMSE = 0.984; MAE = 0.364; ENS = 1; ELM = 0.988; Drefined = 0.994) applied for the monthly streamflow forecasting in comparison with the traditional ANFIS model (r = 0.998; RMSE = 3.276; MAE = 1.553; ENS = 0.995; ELM = 0.950; Drefined = 0.975). The results also show that the ANFIS-FFA is not only superior to the ANFIS model but also exhibits a parsimonious modelling framework for streamflow forecasting by incorporating a smaller number of input variables required to yield the comparatively better performance. It is construed that the FFA optimizer can thus surpass the accuracy of the traditional ANFIS model in general

  3. Method of excess fractions with application to absolute distance metrology: wavelength selection and the effects of common error sources.

    PubMed

    Falaggis, Konstantinos; Towers, David P; Towers, Catherine E

    2012-09-20

    Multiwavelength interferometry (MWI) is a well established technique in the field of optical metrology. Previously, we have reported a theoretical analysis of the method of excess fractions that describes the mutual dependence of unambiguous measurement range, reliability, and the measurement wavelengths. In this paper wavelength, selection strategies are introduced that are built on the theoretical description and maximize the reliability in the calculated fringe order for a given measurement range, number of wavelengths, and level of phase noise. Practical implementation issues for an MWI interferometer are analyzed theoretically. It is shown that dispersion compensation is best implemented by use of reference measurements around absolute zero in the interferometer. Furthermore, the effects of wavelength uncertainty allow the ultimate performance of an MWI interferometer to be estimated.

  4. Verification of Pharmacogenetics-Based Warfarin Dosing Algorithms in Han-Chinese Patients Undertaking Mechanic Heart Valve Replacement

    PubMed Central

    Zhao, Li; Chen, Chunxia; Li, Bei; Dong, Li; Guo, Yingqiang; Xiao, Xijun; Zhang, Eryong; Qin, Li

    2014-01-01

    Objective To study the performance of pharmacogenetics-based warfarin dosing algorithms in the initial and the stable warfarin treatment phases in a cohort of Han-Chinese patients undertaking mechanic heart valve replacement. Methods We searched PubMed, Chinese National Knowledge Infrastructure and Wanfang databases for selecting pharmacogenetics-based warfarin dosing models. Patients with mechanic heart valve replacement were consecutively recruited between March 2012 and July 2012. The predicted warfarin dose of each patient was calculated and compared with the observed initial and stable warfarin doses. The percentage of patients whose predicted dose fell within 20% of their actual therapeutic dose (percentage within 20%), and the mean absolute error (MAE) were utilized to evaluate the predictive accuracy of all the selected algorithms. Results A total of 8 algorithms including Du, Huang, Miao, Wei, Zhang, Lou, Gage, and International Warfarin Pharmacogenetics Consortium (IWPC) model, were tested in 181 patients. The MAE of the Gage, IWPC and 6 Han-Chinese pharmacogenetics-based warfarin dosing algorithms was less than 0.6 mg/day in accuracy and the percentage within 20% exceeded 45% in all of the selected models in both the initial and the stable treatment stages. When patients were stratified according to the warfarin dose range, all of the equations demonstrated better performance in the ideal-dose range (1.88–4.38 mg/day) than the low-dose range (<1.88 mg/day). Among the 8 algorithms compared, the algorithms of Wei, Huang, and Miao showed a lower MAE and higher percentage within 20% in both the initial and the stable warfarin dose prediction and in the low-dose and the ideal-dose ranges. Conclusions All of the selected pharmacogenetics-based warfarin dosing regimens performed similarly in our cohort. However, the algorithms of Wei, Huang, and Miao showed a better potential for warfarin prediction in the initial and the stable treatment phases in Han

  5. Verification of pharmacogenetics-based warfarin dosing algorithms in Han-Chinese patients undertaking mechanic heart valve replacement.

    PubMed

    Zhao, Li; Chen, Chunxia; Li, Bei; Dong, Li; Guo, Yingqiang; Xiao, Xijun; Zhang, Eryong; Qin, Li

    2014-01-01

    To study the performance of pharmacogenetics-based warfarin dosing algorithms in the initial and the stable warfarin treatment phases in a cohort of Han-Chinese patients undertaking mechanic heart valve replacement. We searched PubMed, Chinese National Knowledge Infrastructure and Wanfang databases for selecting pharmacogenetics-based warfarin dosing models. Patients with mechanic heart valve replacement were consecutively recruited between March 2012 and July 2012. The predicted warfarin dose of each patient was calculated and compared with the observed initial and stable warfarin doses. The percentage of patients whose predicted dose fell within 20% of their actual therapeutic dose (percentage within 20%), and the mean absolute error (MAE) were utilized to evaluate the predictive accuracy of all the selected algorithms. A total of 8 algorithms including Du, Huang, Miao, Wei, Zhang, Lou, Gage, and International Warfarin Pharmacogenetics Consortium (IWPC) model, were tested in 181 patients. The MAE of the Gage, IWPC and 6 Han-Chinese pharmacogenetics-based warfarin dosing algorithms was less than 0.6 mg/day in accuracy and the percentage within 20% exceeded 45% in all of the selected models in both the initial and the stable treatment stages. When patients were stratified according to the warfarin dose range, all of the equations demonstrated better performance in the ideal-dose range (1.88-4.38 mg/day) than the low-dose range (<1.88 mg/day). Among the 8 algorithms compared, the algorithms of Wei, Huang, and Miao showed a lower MAE and higher percentage within 20% in both the initial and the stable warfarin dose prediction and in the low-dose and the ideal-dose ranges. All of the selected pharmacogenetics-based warfarin dosing regimens performed similarly in our cohort. However, the algorithms of Wei, Huang, and Miao showed a better potential for warfarin prediction in the initial and the stable treatment phases in Han-Chinese patients undertaking mechanic heart

  6. Critical Test of Some Computational Chemistry Methods for Prediction of Gas-Phase Acidities and Basicities.

    PubMed

    Toomsalu, Eve; Koppel, Ilmar A; Burk, Peeter

    2013-09-10

    Gas-phase acidities and basicities were calculated for 64 neutral bases (covering the scale from 139.9 kcal/mol to 251.9 kcal/mol) and 53 neutral acids (covering the scale from 299.5 kcal/mol to 411.7 kcal/mol). The following methods were used: AM1, PM3, PM6, PDDG, G2, G2MP2, G3, G3MP2, G4, G4MP2, CBS-QB3, B1B95, B2PLYP, B2PLYPD, B3LYP, B3PW91, B97D, B98, BLYP, BMK, BP86, CAM-B3LYP, HSEh1PBE, M06, M062X, M06HF, M06L, mPW2PLYP, mPW2PLYPD, O3LYP, OLYP, PBE1PBE, PBEPBE, tHCTHhyb, TPSSh, VSXC, X3LYP. The addition of the Grimmes empirical dispersion correction (D) to B2PLYP and mPW2PLYP was evaluated, and it was found that adding this correction gave more-accurate results when considering acidities. Calculations with B3LYP, B97D, BLYP, B2PLYPD, and PBE1PBE methods were carried out with five basis sets (6-311G**, 6-311+G**, TZVP, cc-pVTZ, and aug-cc-pVTZ) to evaluate the effect of basis sets on the accuracy of calculations. It was found that the best basis sets when considering accuracy of results and needed time were 6-311+G** and TZVP. Among semiempirical methods AM1 had the best ability to reproduce experimental acidities and basicities (the mean absolute error (mae) was 7.3 kcal/mol). Among DFT methods the best method considering accuracy, robustness, and computation time was PBE1PBE/6-311+G** (mae = 2.7 kcal/mol). Four Gaussian-type methods (G2, G2MP2, G4, and G4MP2) gave similar results to each other (mae = 2.3 kcal/mol). Gaussian-type methods are quite accurate, but their downside is the relatively long computational time.

  7. Magnetospheric Multiscale (MMS) Mission Commissioning Phase Orbit Determination Error Analysis

    NASA Technical Reports Server (NTRS)

    Chung, Lauren R.; Novak, Stefan; Long, Anne; Gramling, Cheryl

    2009-01-01

    The Magnetospheric MultiScale (MMS) mission commissioning phase starts in a 185 km altitude x 12 Earth radii (RE) injection orbit and lasts until the Phase 1 mission orbits and orientation to the Earth-Sun li ne are achieved. During a limited time period in the early part of co mmissioning, five maneuvers are performed to raise the perigee radius to 1.2 R E, with a maneuver every other apogee. The current baseline is for the Goddard Space Flight Center Flight Dynamics Facility to p rovide MMS orbit determination support during the early commissioning phase using all available two-way range and Doppler tracking from bo th the Deep Space Network and Space Network. This paper summarizes th e results from a linear covariance analysis to determine the type and amount of tracking data required to accurately estimate the spacecraf t state, plan each perigee raising maneuver, and support thruster cal ibration during this phase. The primary focus of this study is the na vigation accuracy required to plan the first and the final perigee ra ising maneuvers. Absolute and relative position and velocity error hi stories are generated for all cases and summarized in terms of the ma ximum root-sum-square consider and measurement noise error contributi ons over the definitive and predictive arcs and at discrete times inc luding the maneuver planning and execution times. Details of the meth odology, orbital characteristics, maneuver timeline, error models, and error sensitivities are provided.

  8. Hearing on the Reauthorization of the Higher Education Act of 1965; Sallie Mae--Safety and Soundness. Hearing before the Subcommittee on Postsecondary Education of the Committee on Education and Labor. House of Representatives, One Hundred Second Congress, First Session.

    ERIC Educational Resources Information Center

    Congress of the U.S., Washington, DC. House Subcommittee on Postsecondary Education.

    As part of a series of hearings on the reauthorization of the Higher Education Act of 1965, testimony was heard on the safety and soundness of the Student Loan Marketing Association (Sallie Mae). Witnesses discussed many issues surrounding financial oversight of federal agencies and financial risk to the taxpayer through the potential failure of…

  9. Performance of a SiPM based semi-monolithic scintillator PET detector.

    PubMed

    Zhang, Xianming; Wang, Xiaohui; Ren, Ning; Kuang, Zhonghua; Deng, Xinhan; Fu, Xin; Wu, San; Sang, Ziru; Hu, Zhanli; Liang, Dong; Liu, Xin; Zheng, Hairong; Yang, Yongfeng

    2017-09-21

    error (MAE) which is defined as the probability-weighted mean of the absolute value of the positioning error is used to evaluate the spatial resolution. An average MAE spatial resolution of ~1.15 mm was obtained in both y and z directions without rejection of the multiple scattering events. The average MAE spatial resolution was ~0.7 mm in both y and z directions after the multiple scattering events were rejected. The timing resolution of the detector is 575 ps. In the next step, long rectangle detector will be built to reduce edge effects and improve the spatial resolution of the semi-monolithic detector. Thick detector up to 20 mm will be explored and the positioning algorithms will be further optimized.

  10. Performance of a SiPM based semi-monolithic scintillator PET detector

    NASA Astrophysics Data System (ADS)

    Zhang, Xianming; Wang, Xiaohui; Ren, Ning; Kuang, Zhonghua; Deng, Xinhan; Fu, Xin; Wu, San; Sang, Ziru; Hu, Zhanli; Liang, Dong; Liu, Xin; Zheng, Hairong; Yang, Yongfeng

    2017-10-01

    (MAE) which is defined as the probability-weighted mean of the absolute value of the positioning error is used to evaluate the spatial resolution. An average MAE spatial resolution of ~1.15 mm was obtained in both y and z directions without rejection of the multiple scattering events. The average MAE spatial resolution was ~0.7 mm in both y and z directions after the multiple scattering events were rejected. The timing resolution of the detector is 575 ps. In the next step, long rectangle detector will be built to reduce edge effects and improve the spatial resolution of the semi-monolithic detector. Thick detector up to 20 mm will be explored and the positioning algorithms will be further optimized.

  11. Ciliates learn to diagnose and correct classical error syndromes in mating strategies

    PubMed Central

    Clark, Kevin B.

    2013-01-01

    Preconjugal ciliates learn classical repetition error-correction codes to safeguard mating messages and replies from corruption by “rivals” and local ambient noise. Because individual cells behave as memory channels with Szilárd engine attributes, these coding schemes also might be used to limit, diagnose, and correct mating-signal errors due to noisy intracellular information processing. The present study, therefore, assessed whether heterotrich ciliates effect fault-tolerant signal planning and execution by modifying engine performance, and consequently entropy content of codes, during mock cell–cell communication. Socially meaningful serial vibrations emitted from an ambiguous artificial source initiated ciliate behavioral signaling performances known to advertise mating fitness with varying courtship strategies. Microbes, employing calcium-dependent Hebbian-like decision making, learned to diagnose then correct error syndromes by recursively matching Boltzmann entropies between signal planning and execution stages via “power” or “refrigeration” cycles. All eight serial contraction and reversal strategies incurred errors in entropy magnitude by the execution stage of processing. Absolute errors, however, subtended expected threshold values for single bit-flip errors in three-bit replies, indicating coding schemes protected information content throughout signal production. Ciliate preparedness for vibrations selectively and significantly affected the magnitude and valence of Szilárd engine performance during modal and non-modal strategy corrective cycles. But entropy fidelity for all replies mainly improved across learning trials as refinements in engine efficiency. Fidelity neared maximum levels for only modal signals coded in resilient three-bit repetition error-correction sequences. Together, these findings demonstrate microbes can elevate survival/reproductive success by learning to implement classical fault-tolerant information processing in

  12. Dosimetric Implications of Residual Tracking Errors During Robotic SBRT of Liver Metastases

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Chan, Mark; Tuen Mun Hospital, Hong Kong; Grehn, Melanie

    Purpose: Although the metric precision of robotic stereotactic body radiation therapy in the presence of breathing motion is widely known, we investigated the dosimetric implications of breathing phase–related residual tracking errors. Methods and Materials: In 24 patients (28 liver metastases) treated with the CyberKnife, we recorded the residual correlation, prediction, and rotational tracking errors from 90 fractions and binned them into 10 breathing phases. The average breathing phase errors were used to shift and rotate the clinical tumor volume (CTV) and planning target volume (PTV) for each phase to calculate a pseudo 4-dimensional error dose distribution for comparison with themore » original planned dose distribution. Results: The median systematic directional correlation, prediction, and absolute aggregate rotation errors were 0.3 mm (range, 0.1-1.3 mm), 0.01 mm (range, 0.00-0.05 mm), and 1.5° (range, 0.4°-2.7°), respectively. Dosimetrically, 44%, 81%, and 92% of all voxels differed by less than 1%, 3%, and 5% of the planned local dose, respectively. The median coverage reduction for the PTV was 1.1% (range in coverage difference, −7.8% to +0.8%), significantly depending on correlation (P=.026) and rotational (P=.005) error. With a 3-mm PTV margin, the median coverage change for the CTV was 0.0% (range, −1.0% to +5.4%), not significantly depending on any investigated parameter. In 42% of patients, the 3-mm margin did not fully compensate for the residual tracking errors, resulting in a CTV coverage reduction of 0.1% to 1.0%. Conclusions: For liver tumors treated with robotic stereotactic body radiation therapy, a safety margin of 3 mm is not always sufficient to cover all residual tracking errors. Dosimetrically, this translates into only small CTV coverage reductions.« less

  13. Absolute tracer dye concentration using airborne laser-induced water Raman backscatter

    NASA Technical Reports Server (NTRS)

    Hoge, F. E.; Swift, R. N.

    1981-01-01

    The use of simultaneous airborne-laser-induced dye fluorescence and water Raman backscatter to measure the absolute concentration of an ocean-dispersed tracer dye is discussed. Theoretical considerations of the calculation of dye concentration by the numerical comparison of airborne laser-induced fluorescence spectra with laboratory spectra for known dye concentrations using the 3400/cm OH-stretch water Raman scatter as a calibration signal are presented which show that minimum errors are obtained and no data concerning water mass transmission properties are required when the laser wavelength is chosen to yield a Raman signal near the dye emission band. Results of field experiments conducted with an airborne conical scan lidar over a site in New York Bight into which rhodamine dye had been injected in a study of oil spill dispersion are then indicated which resulted in a contour map of dye concentrations, with a minimum detectable dye concentration of approximately 2 ppb by weight.

  14. Dynamic Neural Correlates of Motor Error Monitoring and Adaptation during Trial-to-Trial Learning

    PubMed Central

    Tan, Huiling; Jenkinson, Ned

    2014-01-01

    A basic EEG feature upon voluntary movements in healthy human subjects is a β (13–30 Hz) band desynchronization followed by a postmovement event-related synchronization (ERS) over contralateral sensorimotor cortex. The functional implications of these changes remain unclear. We hypothesized that, because β ERS follows movement, it may reflect the degree of error in that movement, and the salience of that error to the task at hand. As such, the signal might underpin trial-to-trial modifications of the internal model that informs future movements. To test this hypothesis, EEG was recorded in healthy subjects while they moved a joystick-controlled cursor to visual targets on a computer screen, with different rotational perturbations applied between the joystick and cursor. We observed consistently lower β ERS in trials with large error, even when other possible motor confounds, such as reaction time, movement duration, and path length, were controlled, regardless of whether the perturbation was random or constant. There was a negative trial-to-trial correlation between the size of the absolute initial angular error and the amplitude of the β ERS, and this negative correlation was enhanced when other contextual information about the behavioral salience of the angular error, namely, the bias and variance of errors in previous trials, was additionally considered. These same features also had an impact on the behavioral performance. The findings suggest that the β ERS reflects neural processes that evaluate motor error and do so in the context of the prior history of errors. PMID:24741058

  15. Assessing and monitoring semi-arid shrublands using object-based image analysis and multiple endmember spectral mixture analysis.

    PubMed

    Hamada, Yuki; Stow, Douglas A; Roberts, Dar A; Franklin, Janet; Kyriakidis, Phaedon C

    2013-04-01

    Arid and semi-arid shrublands have significant biological and economical values and have been experiencing dramatic changes due to human activities. In California, California sage scrub (CSS) is one of the most endangered plant communities in the US and requires close monitoring in order to conserve this important biological resource. We investigate the utility of remote-sensing approaches--object-based image analysis applied to pansharpened QuickBird imagery (QBPS/OBIA) and multiple endmember spectral mixture analysis (MESMA) applied to SPOT imagery (SPOT/MESMA)--for estimating fractional cover of true shrub, subshrub, herb, and bare ground within CSS communities of southern California. We also explore the effectiveness of life-form cover maps for assessing CSS conditions. Overall and combined shrub cover (i.e., true shrub and subshrub) were estimated more accurately using QBPS/OBIA (mean absolute error or MAE, 8.9 %) than SPOT/MESMA (MAE, 11.4 %). Life-form cover from QBPS/OBIA at a 25 × 25 m grid cell size seems most desirable for assessing CSS because of its higher accuracy and spatial detail in cover estimates and amenability to extracting other vegetation information (e.g., size, shape, and density of shrub patches). Maps derived from SPOT/MESMA at a 50 × 50 m scale are effective for retrospective analysis of life-form cover change because their comparable accuracies to QBPS/OBIA and availability of SPOT archives data dating back to the mid-1980s. The framework in this study can be applied to other physiognomically comparable shrubland communities.

  16. A semi-mechanistic model of dead fine fuel moisture for Temperate and Mediterranean ecosystems

    NASA Astrophysics Data System (ADS)

    Resco de Dios, Víctor; Fellows, Aaron; Boer, Matthias; Bradstock, Ross; Nolan, Rachel; Goulden, Michel

    2014-05-01

    Fire is a major disturbance in terrestrial ecosystems globally. It has an enormous economic and social cost, and leads to fatalities in the worst cases. The moisture content of the vegetation (fuel moisture) is one of the main determinants of fire risk. Predicting the moisture content of dead and fine fuel (< 2.5 cm in diameter) is particularly important, as this is often the most important component of the fuel complex for fire propagation. A variety of drought indices, empirical and mechanistic models have been proposed to model fuel moisture. A commonality across these different approaches is that they have been neither validated across large temporal datasets nor validated across broadly different vegetation types. Here, we present the results of a study performed at 6 locations in California, USA (5 sites) and New South Wales, Australia (1 site), where 10-hours fuel moisture content was continuously measured every 30 minutes during one full year at each site. We observed that drought indices did not accurately predict fuel moisture, and that empirical and mechanistic models both needed site-specific calibrations, which hinders their global application as indices of fuel moisture. We developed a novel, single equation and semi-mechanistic model, based on atmospheric vapor-pressure deficit. Across sites and years, mean absolute error (MAE) of predicted fuel moisture was 4.7%. MAE dropped <1% in the critical range of fuel moisture <10%. The high simplicity, accuracy and precision of our model makes it suitable for a wide range of applications: from operational purposes, to global vegetation models.

  17. Improvement of forecast skill for severe weather by merging radar-based extrapolation and storm-scale NWP corrected forecast

    NASA Astrophysics Data System (ADS)

    Wang, Gaili; Wong, Wai-Kin; Hong, Yang; Liu, Liping; Dong, Jili; Xue, Ming

    2015-03-01

    The primary objective of this study is to improve the performance of deterministic high resolution rainfall forecasts caused by severe storms by merging an extrapolation radar-based scheme with a storm-scale Numerical Weather Prediction (NWP) model. Effectiveness of Multi-scale Tracking and Forecasting Radar Echoes (MTaRE) model was compared with that of a storm-scale NWP model named Advanced Regional Prediction System (ARPS) for forecasting a violent tornado event that developed over parts of western and much of central Oklahoma on May 24, 2011. Then the bias corrections were performed to improve the forecast accuracy of ARPS forecasts. Finally, the corrected ARPS forecast and radar-based extrapolation were optimally merged by using a hyperbolic tangent weight scheme. The comparison of forecast skill between MTaRE and ARPS in high spatial resolution of 0.01° × 0.01° and high temporal resolution of 5 min showed that MTaRE outperformed ARPS in terms of index of agreement and mean absolute error (MAE). MTaRE had a better Critical Success Index (CSI) for less than 20-min lead times and was comparable to ARPS for 20- to 50-min lead times, while ARPS had a better CSI for more than 50-min lead times. Bias correction significantly improved ARPS forecasts in terms of MAE and index of agreement, although the CSI of corrected ARPS forecasts was similar to that of the uncorrected ARPS forecasts. Moreover, optimally merging results using hyperbolic tangent weight scheme further improved the forecast accuracy and became more stable.

  18. CMIP5 downscaling and its uncertainty in China

    NASA Astrophysics Data System (ADS)

    Yue, TianXiang; Zhao, Na; Fan, ZeMeng; Li, Jing; Chen, ChuanFa; Lu, YiMin; Wang, ChenLiang; Xu, Bing; Wilson, John

    2016-11-01

    A comparison between the Coupled Model Intercomparison Project Phase 5 (CMIP5) data and observations at 735 meteorological stations indicated that mean annual temperature (MAT) was underestimated about 1.8 °C while mean annual precipitation (MAP) was overestimated about 263 mm in general across the whole of China. A statistical analysis of China-CMIP5 data demonstrated that MAT exhibits spatial stationarity, while MAP exhibits spatial non-stationarity. MAT and MAP data from the China-CMIP5 dataset were downscaled by combining statistical approaches with a method for high accuracy surface modeling (HASM). A statistical transfer function (STF) of MAT was formulated using minimized residuals output by HASM with an ordinary least squares (OLS) linear equation that used latitude and elevation as independent variables, abbreviated as HASM-OLS. The STF of MAP under a BOX-COX transformation was derived as a combination of minimized residuals output by HASM with a geographically weight regression (GWR) using latitude, longitude, elevation and impact coefficient of aspect as independent variables, abbreviated as HASM-GB. Cross validation, using observational data from the 735 meteorological stations across China for the period 1976 to 2005, indicates that the largest uncertainty occurred on the Tibet plateau with mean absolute errors (MAEs) of MAT and MAP as high as 4.64 °C and 770.51 mm, respectively. The downscaling processes of HASM-OLS and HASM-GB generated MAEs of MAT and MAP that were 67.16% and 77.43% lower, respectively across the whole of China on average, and 88.48% and 97.09% lower for the Tibet plateau.

  19. QSAR modeling of β-lactam binding to human serum proteins

    NASA Astrophysics Data System (ADS)

    Hall, L. Mark; Hall, Lowell H.; Kier, Lemont B.

    2003-02-01

    The binding of beta-lactams to human serum proteins was modeled with topological descriptors of molecular structure. Experimental data was the concentration of protein-bound drug expressed as a percent of the total plasma concentration (percent fraction bound, PFB) for 87 penicillins and for 115 β-lactams. The electrotopological state indices (E-State) and the molecular connectivity chi indices were found to be the basis of two satisfactory models. A data set of 74 penicillins from a drug design series was successfully modeled with statistics: r2=0.80, s = 12.1, q2=0.76, spress=13.4. This model was then used to predict protein binding (PFB) for 13 commercial penicillins, resulting in a very good mean absolute error, MAE = 12.7 and correlation coefficient, q2=0.84. A group of 28 cephalosporins were combined with the penicillin data to create a dataset of 115 beta-lactams that was successfully modeled: r2=0.82, s = 12.7, q2=0.78, spress=13.7. A ten-fold 10% leave-group-out (LGO) cross-validation procedure was implemented, leading to very good statistics: MAE = 10.9, spress=14.0, q2 (or r2 press)=0.78. The models indicate a combination of general and specific structure features that are important for estimating protein binding in this class of antibiotics. For the β-lactams, significant factors that increase binding are presence and electron accessibility of aromatic rings, halogens, methylene groups, and =N- atoms. Significant negative influence on binding comes from amine groups and carbonyl oxygen atoms.

  20. Performance Evaluation of Three Blood Glucose Monitoring Systems Using ISO 15197: 2013 Accuracy Criteria, Consensus and Surveillance Error Grid Analyses, and Insulin Dosing Error Modeling in a Hospital Setting.

    PubMed

    Bedini, José Luis; Wallace, Jane F; Pardo, Scott; Petruschke, Thorsten

    2015-10-07

    Blood glucose monitoring is an essential component of diabetes management. Inaccurate blood glucose measurements can severely impact patients' health. This study evaluated the performance of 3 blood glucose monitoring systems (BGMS), Contour® Next USB, FreeStyle InsuLinx®, and OneTouch® Verio™ IQ, under routine hospital conditions. Venous blood samples (N = 236) obtained for routine laboratory procedures were collected at a Spanish hospital, and blood glucose (BG) concentrations were measured with each BGMS and with the available reference (hexokinase) method. Accuracy of the 3 BGMS was compared according to ISO 15197:2013 accuracy limit criteria, by mean absolute relative difference (MARD), consensus error grid (CEG) and surveillance error grid (SEG) analyses, and an insulin dosing error model. All BGMS met the accuracy limit criteria defined by ISO 15197:2013. While all measurements of the 3 BGMS were within low-risk zones in both error grid analyses, the Contour Next USB showed significantly smaller MARDs between reference values compared to the other 2 BGMS. Insulin dosing errors were lowest for the Contour Next USB than compared to the other systems. All BGMS fulfilled ISO 15197:2013 accuracy limit criteria and CEG criterion. However, taking together all analyses, differences in performance of potential clinical relevance may be observed. Results showed that Contour Next USB had lowest MARD values across the tested glucose range, as compared with the 2 other BGMS. CEG and SEG analyses as well as calculation of the hypothetical bolus insulin dosing error suggest a high accuracy of the Contour Next USB. © 2015 Diabetes Technology Society.

  1. Error begat error: design error analysis and prevention in social infrastructure projects.

    PubMed

    Love, Peter E D; Lopez, Robert; Edwards, David J; Goh, Yang M

    2012-09-01

    Design errors contribute significantly to cost and schedule growth in social infrastructure projects and to engineering failures, which can result in accidents and loss of life. Despite considerable research that has addressed their error causation in construction projects they still remain prevalent. This paper identifies the underlying conditions that contribute to design errors in social infrastructure projects (e.g. hospitals, education, law and order type buildings). A systemic model of error causation is propagated and subsequently used to develop a learning framework for design error prevention. The research suggests that a multitude of strategies should be adopted in congruence to prevent design errors from occurring and so ensure that safety and project performance are ameliorated. Copyright © 2011. Published by Elsevier Ltd.

  2. Legal, ethical and practical considerations in research involving nurses with dyslexia.

    PubMed

    Gillin, Nicola

    2015-09-01

    To discuss the legal, ethical and practical considerations in UK studies involving nurses with dyslexia and medication administration errors (MAEs). Nurses with dyslexia are a vulnerable population as they are susceptible to misrepresentation in research, especially that which involves a sensitive topic such as MAEs. Nurses with dyslexia may be particularly vulnerable to research that could exploit, implicate or attribute unsafe practice to them and their disability. Special consideration should be exercised when researching this population. Despite the potential for legal, ethical and practical issues, MAEs and nurses with dyslexia are under-researched areas and warrant further research. Benefits can be gained, not only by participants but also those with a vested interest in how best to support dyslexic nurses in clinical practice. Through effective design, risks can be identified and minimised, and the research made viable, ethically sound and ultimately beneficial to all those involved.

  3. Using, Seeing, Feeling, and Doing Absolute Value for Deeper Understanding

    ERIC Educational Resources Information Center

    Ponce, Gregorio A.

    2008-01-01

    Using sticky notes and number lines, a hands-on activity is shared that anchors initial student thinking about absolute value. The initial point of reference should help students successfully evaluate numeric problems involving absolute value. They should also be able to solve absolute value equations and inequalities that are typically found in…

  4. Absolute nuclear material assay using count distribution (LAMBDA) space

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Prasad, Mano K.; Snyderman, Neal J.; Rowland, Mark S.

    A method of absolute nuclear material assay of an unknown source comprising counting neutrons from the unknown source and providing an absolute nuclear material assay utilizing a model to optimally compare to the measured count distributions. In one embodiment, the step of providing an absolute nuclear material assay comprises utilizing a random sampling of analytically computed fission chain distributions to generate a continuous time-evolving sequence of event-counts by spreading the fission chain distribution in time.

  5. Planck absolute entropy of a rotating BTZ black hole

    NASA Astrophysics Data System (ADS)

    Riaz, S. M. Jawwad

    2018-04-01

    In this paper, the Planck absolute entropy and the Bekenstein-Smarr formula of the rotating Banados-Teitelboim-Zanelli (BTZ) black hole are presented via a complex thermodynamical system contributed by its inner and outer horizons. The redefined entropy approaches zero as the temperature of the rotating BTZ black hole tends to absolute zero, satisfying the Nernst formulation of a black hole. Hence, it can be regarded as the Planck absolute entropy of the rotating BTZ black hole.

  6. Absolute nuclear material assay using count distribution (LAMBDA) space

    DOEpatents

    Prasad, Manoj K [Pleasanton, CA; Snyderman, Neal J [Berkeley, CA; Rowland, Mark S [Alamo, CA

    2012-06-05

    A method of absolute nuclear material assay of an unknown source comprising counting neutrons from the unknown source and providing an absolute nuclear material assay utilizing a model to optimally compare to the measured count distributions. In one embodiment, the step of providing an absolute nuclear material assay comprises utilizing a random sampling of analytically computed fission chain distributions to generate a continuous time-evolving sequence of event-counts by spreading the fission chain distribution in time.

  7. On the correct representation of bending and axial deformation in the absolute nodal coordinate formulation with an elastic line approach

    NASA Astrophysics Data System (ADS)

    Gerstmayr, Johannes; Irschik, Hans

    2008-12-01

    In finite element methods that are based on position and slope coordinates, a representation of axial and bending deformation by means of an elastic line approach has become popular. Such beam and plate formulations based on the so-called absolute nodal coordinate formulation have not yet been verified sufficiently enough with respect to analytical results or classical nonlinear rod theories. Examining the existing planar absolute nodal coordinate element, which uses a curvature proportional bending strain expression, it turns out that the deformation does not fully agree with the solution of the geometrically exact theory and, even more serious, the normal force is incorrect. A correction based on the classical ideas of the extensible elastica and geometrically exact theories is applied and a consistent strain energy and bending moment relations are derived. The strain energy of the solid finite element formulation of the absolute nodal coordinate beam is based on the St. Venant-Kirchhoff material: therefore, the strain energy is derived for the latter case and compared to classical nonlinear rod theories. The error in the original absolute nodal coordinate formulation is documented by numerical examples. The numerical example of a large deformation cantilever beam shows that the normal force is incorrect when using the previous approach, while a perfect agreement between the absolute nodal coordinate formulation and the extensible elastica can be gained when applying the proposed modifications. The numerical examples show a very good agreement of reference analytical and numerical solutions with the solutions of the proposed beam formulation for the case of large deformation pre-curved static and dynamic problems, including buckling and eigenvalue analysis. The resulting beam formulation does not employ rotational degrees of freedom and therefore has advantages compared to classical beam elements regarding energy-momentum conservation.

  8. The rate of cis-trans conformation errors is increasing in low-resolution crystal structures.

    PubMed

    Croll, Tristan Ian

    2015-03-01

    Cis-peptide bonds (with the exception of X-Pro) are exceedingly rare in native protein structures, yet a check for these is not currently included in the standard workflow for some common crystallography packages nor in the automated quality checks that are applied during submission to the Protein Data Bank. This appears to be leading to a growing rate of inclusion of spurious cis-peptide bonds in low-resolution structures both in absolute terms and as a fraction of solved residues. Most concerningly, it is possible for structures to contain very large numbers (>1%) of spurious cis-peptide bonds while still achieving excellent quality reports from MolProbity, leading to concerns that ignoring such errors is allowing software to overfit maps without producing telltale errors in, for example, the Ramachandran plot.

  9. Comparison of three artificial intelligence techniques for discharge routing

    NASA Astrophysics Data System (ADS)

    Khatibi, Rahman; Ghorbani, Mohammad Ali; Kashani, Mahsa Hasanpour; Kisi, Ozgur

    2011-06-01

    SummaryThe inter-comparison of three artificial intelligence (AI) techniques are presented using the results of river flow/stage timeseries, that are otherwise handled by traditional discharge routing techniques. These models comprise Artificial Neural Network (ANN), Adaptive Nero-Fuzzy Inference System (ANFIS) and Genetic Programming (GP), which are for discharge routing of Kizilirmak River, Turkey. The daily mean river discharge data with a period between 1999 and 2003 were used for training and testing the models. The comparison includes both visual and parametric approaches using such statistic as Coefficient of Correlation (CC), Mean Absolute Error (MAE) and Mean Square Relative Error (MSRE), as well as a basic scoring system. Overall, the results indicate that ANN and ANFIS have mixed fortunes in discharge routing, and both have different abilities in capturing and reproducing some of the observed information. However, the performance of GP displays a better edge over the other two modelling approaches in most of the respects. Attention is given to the information contents of recorded timeseries in terms of their peak values and timings, where one performance measure may capture some of the information contents but be ineffective in others. Thus, this makes a case for compiling knowledge base for various modelling techniques.

  10. An application of seasonal ARIMA models on group commodities to forecast Philippine merchandise exports performance

    NASA Astrophysics Data System (ADS)

    Natividad, Gina May R.; Cawiding, Olive R.; Addawe, Rizavel C.

    2017-11-01

    The increase in the merchandise exports of the country offers information about the Philippines' trading role within the global economy. Merchandise exports statistics are used to monitor the country's overall production that is consumed overseas. This paper investigates the comparison between two models obtained by a) clustering the commodity groups into two based on its proportional contribution to the total exports, and b) treating only the total exports. Different seasonal autoregressive integrated moving average (SARIMA) models were then developed for the clustered commodities and for the total exports based on the monthly merchandise exports of the Philippines from 2011 to 2016. The data set used in this study was retrieved from the Philippine Statistics Authority (PSA) which is the central statistical authority in the country responsible for primary data collection. A test for significance of the difference between means at 0.05 level of significance was then performed on the forecasts produced. The result indicates that there is a significant difference between the mean of the forecasts of the two models. Moreover, upon a comparison of the root mean square error (RMSE) and mean absolute error (MAE) of the models, it was found that the models used for the clustered groups outperform the model for the total exports.

  11. Prediction of the Reference Evapotranspiration Using a Chaotic Approach

    PubMed Central

    Wang, Wei-guang; Zou, Shan; Luo, Zhao-hui; Zhang, Wei; Kong, Jun

    2014-01-01

    Evapotranspiration is one of the most important hydrological variables in the context of water resources management. An attempt was made to understand and predict the dynamics of reference evapotranspiration from a nonlinear dynamical perspective in this study. The reference evapotranspiration data was calculated using the FAO Penman-Monteith equation with the observed daily meteorological data for the period 1966–2005 at four meteorological stations (i.e., Baotou, Zhangbei, Kaifeng, and Shaoguan) representing a wide range of climatic conditions of China. The correlation dimension method was employed to investigate the chaotic behavior of the reference evapotranspiration series. The existence of chaos in the reference evapotranspiration series at the four different locations was proved by the finite and low correlation dimension. A local approximation approach was employed to forecast the daily reference evapotranspiration series. Low root mean square error (RSME) and mean absolute error (MAE) (for all locations lower than 0.31 and 0.24, resp.), high correlation coefficient (CC), and modified coefficient of efficiency (for all locations larger than 0.97 and 0.8, resp.) indicate that the predicted reference evapotranspiration agrees well with the observed one. The encouraging results indicate the suitableness of chaotic approach for understanding and predicting the dynamics of the reference evapotranspiration. PMID:25133221

  12. Prediction of the reference evapotranspiration using a chaotic approach.

    PubMed

    Wang, Wei-guang; Zou, Shan; Luo, Zhao-hui; Zhang, Wei; Chen, Dan; Kong, Jun

    2014-01-01

    Evapotranspiration is one of the most important hydrological variables in the context of water resources management. An attempt was made to understand and predict the dynamics of reference evapotranspiration from a nonlinear dynamical perspective in this study. The reference evapotranspiration data was calculated using the FAO Penman-Monteith equation with the observed daily meteorological data for the period 1966-2005 at four meteorological stations (i.e., Baotou, Zhangbei, Kaifeng, and Shaoguan) representing a wide range of climatic conditions of China. The correlation dimension method was employed to investigate the chaotic behavior of the reference evapotranspiration series. The existence of chaos in the reference evapotranspiration series at the four different locations was proved by the finite and low correlation dimension. A local approximation approach was employed to forecast the daily reference evapotranspiration series. Low root mean square error (RSME) and mean absolute error (MAE) (for all locations lower than 0.31 and 0.24, resp.), high correlation coefficient (CC), and modified coefficient of efficiency (for all locations larger than 0.97 and 0.8, resp.) indicate that the predicted reference evapotranspiration agrees well with the observed one. The encouraging results indicate the suitableness of chaotic approach for understanding and predicting the dynamics of the reference evapotranspiration.

  13. Assessment of Gamma-Ray Spectra Analysis Method Utilizing the Fireworks Algorithm for various Error Measures

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Alamaniotis, Miltiadis; Tsoukalas, Lefteri H.

    2018-01-01

    Significant role in enhancing nuclear nonproliferation plays the analysis of obtained data and the inference of the presence or not of special nuclear materials in them. Among various types of measurements, gamma-ray spectra is the widest used type of data utilized for analysis in nonproliferation. In this chapter, a method that employs the fireworks algorithm (FWA) for analyzing gamma-ray spectra aiming at detecting gamma signatures is presented. In particular FWA is utilized to fit a set of known signatures to a measured spectrum by optimizing an objective function, with non-zero coefficients expressing the detected signatures. FWA is tested on amore » set of experimentally obtained measurements and various objective functions -MSE, RMSE, Theil-2, MAE, MAPE, MAP- with results exhibiting its potential in providing high accuracy and high precision of detected signatures. Furthermore, FWA is benchmarked against genetic algorithms, and multiple linear regression with results exhibiting its superiority over the rest tested algorithms with respect to precision for MAE, MAPE and MAP measures.« less

  14. Design and construction of miniature artificial ecosystem based on dynamic response optimization

    NASA Astrophysics Data System (ADS)

    Hu, Dawei; Liu, Hong; Tong, Ling; Li, Ming; Hu, Enzhu

    The miniature artificial ecosystem (MAES) is a combination of man, silkworm, salad and mi-croalgae to partially regenerate O2 , sanitary water and food, simultaneously dispose CO2 and wastes, therefore it have a fundamental life support function. In order to enhance the safety and reliability of MAES and eliminate the influences of internal variations and external dis-turbances, it was necessary to configure MAES as a closed-loop control system, and it could be considered as a prototype for future bioregenerative life support system. However, MAES is a complex system possessing large numbers of parameters, intricate nonlinearities, time-varying factors as well as uncertainties, hence it is difficult to perfectly design and construct a prototype through merely conducting experiments by trial and error method. Our research presented an effective way to resolve preceding problem by use of dynamic response optimiza-tion. Firstly the mathematical model of MAES with first-order nonlinear ordinary differential equations including parameters was developed based on relevant mechanisms and experimental data, secondly simulation model of MAES was derived on the platform of MatLab/Simulink to perform model validation and further digital simulations, thirdly reference trajectories of de-sired dynamic response of system outputs were specified according to prescribed requirements, and finally optimization for initial values, tuned parameter and independent parameters was carried out using the genetic algorithm, the advanced direct search method along with parallel computing methods through computer simulations. The result showed that all parameters and configurations of MAES were determined after a series of computer experiments, and its tran-sient response performances and steady characteristics closely matched the reference curves. Since the prototype is a physical system that represents the mathematical model with reason-able accuracy, so the process of designing and

  15. Potential errors in optical density measurements due to scanning side in EBT and EBT2 Gafchromic film dosimetry.

    PubMed

    Desroches, Joannie; Bouchard, Hugo; Lacroix, Frédéric

    2010-04-01

    The purpose of this study is to determine the effect on the measured optical density of scanning on either side of a Gafchromic EBT and EBT2 film using an Epson (Epson Canada Ltd., Toronto, Ontario) 10000XL flat bed scanner. Calibration curves were constructed using EBT2 film scanned in landscape orientation in both reflection and transmission mode on an Epson 10000XL scanner. Calibration curves were also constructed using EBT film. Potential errors due to an optical density difference from scanning the film on either side ("face up" or "face down") were simulated. Scanning the film face up or face down on the scanner bed while keeping the film angular orientation constant affects the measured optical density when scanning in reflection mode. In contrast, no statistically significant effect was seen when scanning in transmission mode. This effect can significantly affect relative and absolute dose measurements. As an application example, the authors demonstrate potential errors of 17.8% by inverting the film scanning side on the gamma index for 3%-3 mm criteria on a head and neck intensity modulated radiotherapy plan, and errors in absolute dose measurements ranging from 10% to 35% between 2 and 5 Gy. Process consistency is the key to obtaining accurate and precise results in Gafchromic film dosimetry. When scanning in reflection mode, care must be taken to place the film consistently on the same side on the scanner bed.

  16. Novalis' Poetic Uncertainty: A "Bildung" with the Absolute

    ERIC Educational Resources Information Center

    Mika, Carl

    2016-01-01

    Novalis, the Early German Romantic poet and philosopher, had at the core of his work a mysterious depiction of the "absolute." The absolute is Novalis' name for a substance that defies precise knowledge yet calls for a tentative and sensitive speculation. How one asserts a truth, represents an object, and sets about encountering things…

  17. Population-based absolute risk estimation with survey data

    PubMed Central

    Kovalchik, Stephanie A.; Pfeiffer, Ruth M.

    2013-01-01

    Absolute risk is the probability that a cause-specific event occurs in a given time interval in the presence of competing events. We present methods to estimate population-based absolute risk from a complex survey cohort that can accommodate multiple exposure-specific competing risks. The hazard function for each event type consists of an individualized relative risk multiplied by a baseline hazard function, which is modeled nonparametrically or parametrically with a piecewise exponential model. An influence method is used to derive a Taylor-linearized variance estimate for the absolute risk estimates. We introduce novel measures of the cause-specific influences that can guide modeling choices for the competing event components of the model. To illustrate our methodology, we build and validate cause-specific absolute risk models for cardiovascular and cancer deaths using data from the National Health and Nutrition Examination Survey. Our applications demonstrate the usefulness of survey-based risk prediction models for predicting health outcomes and quantifying the potential impact of disease prevention programs at the population level. PMID:23686614

  18. Absolute marine gravimetry with matter-wave interferometry.

    PubMed

    Bidel, Y; Zahzam, N; Blanchard, C; Bonnin, A; Cadoret, M; Bresson, A; Rouxel, D; Lequentrec-Lalancette, M F

    2018-02-12

    Measuring gravity from an aircraft or a ship is essential in geodesy, geophysics, mineral and hydrocarbon exploration, and navigation. Today, only relative sensors are available for onboard gravimetry. This is a major drawback because of the calibration and drift estimation procedures which lead to important operational constraints. Atom interferometry is a promising technology to obtain onboard absolute gravimeter. But, despite high performances obtained in static condition, no precise measurements were reported in dynamic. Here, we present absolute gravity measurements from a ship with a sensor based on atom interferometry. Despite rough sea conditions, we obtained precision below 10 -5  m s -2 . The atom gravimeter was also compared with a commercial spring gravimeter and showed better performances. This demonstration opens the way to the next generation of inertial sensors (accelerometer, gyroscope) based on atom interferometry which should provide high-precision absolute measurements from a moving platform.

  19. Absolute emission cross sections for electron capture reactions of C2+, N3+, N4+ and O3+ ions in collisions with Li(2s) atoms

    NASA Astrophysics Data System (ADS)

    Rieger, G.; Pinnington, E. H.; Ciubotariu, C.

    2000-12-01

    Absolute photon emission cross sections following electron capture reactions have been measured for C2+, N3+, N4+ and O3+ ions colliding with Li(2s) atoms at keV energies. The results are compared with calculations using the extended classical over-the-barrier model by Niehaus. We explore the limits of our experimental method and present a detailed discussion of experimental errors.

  20. The suitability of remotely sensed soil moisture for improving operational flood forecasting

    NASA Astrophysics Data System (ADS)

    Wanders, N.; Karssenberg, D.; de Roo, A.; de Jong, S. M.; Bierkens, M. F. P.

    2013-11-01

    We evaluate the added value of assimilated remotely sensed soil moisture for the European Flood Awareness System (EFAS) and its potential to improve the prediction of the timing and height of the flood peak and low flows. EFAS is an operational flood forecasting system for Europe and uses a distributed hydrological model for flood predictions with lead times up to 10 days. For this study, satellite-derived soil moisture from ASCAT, AMSR-E and SMOS is assimilated into the EFAS system for the Upper Danube basin and results are compared to assimilation of discharge observations only. To assimilate soil moisture and discharge data into EFAS, an Ensemble Kalman Filter (EnKF) is used. Information on the spatial (cross-) correlation of the errors in the satellite products, is included to ensure optimal performance of the EnKF. For the validation, additional discharge observations not used in the EnKF, are used as an independent validation dataset. Our results show that the accuracy of flood forecasts is increased when more discharge observations are assimilated; the Mean Absolute Error (MAE) of the ensemble mean is reduced by 65%. The additional inclusion of satellite data results in a further increase of the performance: forecasts of base flows are better and the uncertainty in the overall discharge is reduced, shown by a 10% reduction in the MAE. In addition, floods are predicted with a higher accuracy and the Continuous Ranked Probability Score (CRPS) shows a performance increase of 5-10% on average, compared to assimilation of discharge only. When soil moisture data is used, the timing errors in the flood predictions are decreased especially for shorter lead times and imminent floods can be forecasted with more skill. The number of false flood alerts is reduced when more data is assimilated into the system and the best performance is achieved with the assimilation of both discharge and satellite observations. The additional gain is highest when discharge observations