Optimal marker placement in hadrontherapy: intelligent optimization strategies with augmented Lagrangian pattern search.

PubMed

Altomare, Cristina; Guglielmann, Raffaella; Riboldi, Marco; Bellazzi, Riccardo; Baroni, Guido

2015-02-01

In high precision photon radiotherapy and in hadrontherapy, it is crucial to minimize the occurrence of geometrical deviations with respect to the treatment plan in each treatment session. To this end, point-based infrared (IR) optical tracking for patient set-up quality assessment is performed. Such tracking depends on external fiducial points placement. The main purpose of our work is to propose a new algorithm based on simulated annealing and augmented Lagrangian pattern search (SAPS), which is able to take into account prior knowledge, such as spatial constraints, during the optimization process. The SAPS algorithm was tested on data related to head and neck and pelvic cancer patients, and that were fitted with external surface markers for IR optical tracking applied for patient set-up preliminary correction. The integrated algorithm was tested considering optimality measures obtained with Computed Tomography (CT) images (i.e. the ratio between the so-called target registration error and fiducial registration error, TRE/FRE) and assessing the marker spatial distribution. Comparison has been performed with randomly selected marker configuration and with the GETS algorithm (Genetic Evolutionary Taboo Search), also taking into account the presence of organs at risk. The results obtained with SAPS highlight improvements with respect to the other approaches: (i) TRE/FRE ratio decreases; (ii) marker distribution satisfies both marker visibility and spatial constraints. We have also investigated how the TRE/FRE ratio is influenced by the number of markers, obtaining significant TRE/FRE reduction with respect to the random configurations, when a high number of markers is used. The SAPS algorithm is a valuable strategy for fiducial configuration optimization in IR optical tracking applied for patient set-up error detection and correction in radiation therapy, showing that taking into account prior knowledge is valuable in this optimization process. Further work will be focused on the computational optimization of the SAPS algorithm toward fast point-of-care applications. Copyright © 2014 Elsevier Inc. All rights reserved.

Supervised local error estimation for nonlinear image registration using convolutional neural networks

NASA Astrophysics Data System (ADS)

Eppenhof, Koen A. J.; Pluim, Josien P. W.

2017-02-01

Error estimation in medical image registration is valuable when validating, comparing, or combining registration methods. To validate a nonlinear image registration method, ideally the registration error should be known for the entire image domain. We propose a supervised method for the estimation of a registration error map for nonlinear image registration. The method is based on a convolutional neural network that estimates the norm of the residual deformation from patches around each pixel in two registered images. This norm is interpreted as the registration error, and is defined for every pixel in the image domain. The network is trained using a set of artificially deformed images. Each training example is a pair of images: the original image, and a random deformation of that image. No manually labeled ground truth error is required. At test time, only the two registered images are required as input. We train and validate the network on registrations in a set of 2D digital subtraction angiography sequences, such that errors up to eight pixels can be estimated. We show that for this range of errors the convolutional network is able to learn the registration error in pairs of 2D registered images at subpixel precision. Finally, we present a proof of principle for the extension to 3D registration problems in chest CTs, showing that the method has the potential to estimate errors in 3D registration problems.

Analysis of the effects of Eye-Tracker performance on the pulse positioning errors during refractive surgery☆

PubMed Central

Arba-Mosquera, Samuel; Aslanides, Ioannis M.

2012-01-01

Purpose To analyze the effects of Eye-Tracker performance on the pulse positioning errors during refractive surgery. Methods A comprehensive model, which directly considers eye movements, including saccades, vestibular, optokinetic, vergence, and miniature, as well as, eye-tracker acquisition rate, eye-tracker latency time, scanner positioning time, laser firing rate, and laser trigger delay have been developed. Results Eye-tracker acquisition rates below 100 Hz correspond to pulse positioning errors above 1.5 mm. Eye-tracker latency times to about 15 ms correspond to pulse positioning errors of up to 3.5 mm. Scanner positioning times to about 9 ms correspond to pulse positioning errors of up to 2 mm. Laser firing rates faster than eye-tracker acquisition rates basically duplicate pulse-positioning errors. Laser trigger delays to about 300 μs have minor to no impact on pulse-positioning errors. Conclusions The proposed model can be used for comparison of laser systems used for ablation processes. Due to the pseudo-random nature of eye movements, positioning errors of single pulses are much larger than observed decentrations in the clinical settings. There is no single parameter that ‘alone’ minimizes the positioning error. It is the optimal combination of the several parameters that minimizes the error. The results of this analysis are important to understand the limitations of correcting very irregular ablation patterns.

A case study of the effects of random errors in rawinsonde data on computations of ageostrophic winds

NASA Technical Reports Server (NTRS)

Moore, J. T.

1985-01-01

Data input for the AVE-SESAME I experiment are utilized to describe the effects of random errors in rawinsonde data on the computation of ageostrophic winds. Computer-generated random errors for wind direction and speed and temperature are introduced into the station soundings at 25 mb intervals from which isentropic data sets are created. Except for the isallobaric and the local wind tendency, all winds are computed for Apr. 10, 1979 at 2000 GMT. Divergence fields reveal that the isallobaric and inertial-geostrophic-advective divergences are less affected by rawinsonde random errors than the divergence of the local wind tendency or inertial-advective winds.

A comparative study of set up variations and bowel volumes in supine versus prone positions of patients treated with external beam radiation for carcinoma rectum.

PubMed

Rajeev, K R; Menon, Smrithy S; Beena, K; Holla, Raghavendra; Kumar, R Rajaneesh; Dinesh, M

2014-01-01

A prospective study was undertaken to evaluate the influence of patient positioning on the set up variations to determine the planning target volume (PTV) margins and to evaluate the clinical relevance volume assessment of the small bowel (SB) within the irradiated volume. During the period of months from December 2011 to April 2012, a computed tomography (CT) scan was done either in supine position or in prone position using a belly board (BB) for 20 consecutive patients. All the patients had histologically proven rectal cancer and received either post- or pre-operative pelvic irradiation. Using a three-dimensional planning system, the dose-volume histogram for SB was defined in each axial CT slice. Total dose was 46-50 Gy (2 Gy/fraction), delivered using the 4-field box technique. The set up variation of the study group was assessed from the data received from the electronic portal imaging device in the linear accelerator. The shift along X, Y, and Z directions were noted. Both systematic and random errors were calculated and using both these values the PTV margin was calculated. The systematic errors of patients treated in the supine position were 0.87 (X-mm), 0.66 (Y-mm), 1.6 (Z-mm) and in the prone position were 1.3 (X-mm), 0.59 (Y-mm), 1.17 (Z-mm). The random errors of patients treated in the supine positions were 1.81 (X-mm), 1.73 (Y-mm), 1.83 (Z-mm) and in prone position were 2.02 (X-mm), 1.21 (Y-mm), 3.05 (Z-mm). The calculated PTV margins in the supine position were 3.45 (X-mm), 2.87 (Y-mm), 5.31 (Z-mm) and in the prone position were 4.91 (X-mm), 2.32 (Y-mm), 5.08 (Z-mm). The mean volume of the peritoneal cavity was 648.65 cm 3 in the prone position and 1197.37 cm 3 in the supine position. The prone position using BB device was more effective in reducing irradiated SB volume in rectal cancer patients. There were no significant variations in the daily set up for patients treated in both supine and prone positions.

Iterative random vs. Kennard-Stone sampling for IR spectrum-based classification task using PLS2-DA

NASA Astrophysics Data System (ADS)

Lee, Loong Chuen; Liong, Choong-Yeun; Jemain, Abdul Aziz

2018-04-01

External testing (ET) is preferred over auto-prediction (AP) or k-fold-cross-validation in estimating more realistic predictive ability of a statistical model. With IR spectra, Kennard-stone (KS) sampling algorithm is often used to split the data into training and test sets, i.e. respectively for model construction and for model testing. On the other hand, iterative random sampling (IRS) has not been the favored choice though it is theoretically more likely to produce reliable estimation. The aim of this preliminary work is to compare performances of KS and IRS in sampling a representative training set from an attenuated total reflectance - Fourier transform infrared spectral dataset (of four varieties of blue gel pen inks) for PLS2-DA modeling. The `best' performance achievable from the dataset is estimated with AP on the full dataset (APF, error). Both IRS (n = 200) and KS were used to split the dataset in the ratio of 7:3. The classic decision rule (i.e. maximum value-based) is employed for new sample prediction via partial least squares - discriminant analysis (PLS2-DA). Error rate of each model was estimated repeatedly via: (a) AP on full data (APF, error); (b) AP on training set (APS, error); and (c) ET on the respective test set (ETS, error). A good PLS2-DA model is expected to produce APS, error and EVS, error that is similar to the APF, error. Bearing that in mind, the similarities between (a) APS, error vs. APF, error; (b) ETS, error vs. APF, error and; (c) APS, error vs. ETS, error were evaluated using correlation tests (i.e. Pearson and Spearman's rank test), using series of PLS2-DA models computed from KS-set and IRS-set, respectively. Overall, models constructed from IRS-set exhibits more similarities between the internal and external error rates than the respective KS-set, i.e. less risk of overfitting. In conclusion, IRS is more reliable than KS in sampling representative training set.

Automatic image registration performance for two different CBCT systems; variation with imaging dose

NASA Astrophysics Data System (ADS)

Barber, J.; Sykes, J. R.; Holloway, L.; Thwaites, D. I.

2014-03-01

The performance of an automatic image registration algorithm was compared on image sets collected with two commercial CBCT systems, and the relationship with imaging dose was explored. CBCT images of a CIRS Virtually Human Male Pelvis phantom (VHMP) were collected on Varian TrueBeam/OBI and Elekta Synergy/XVI linear accelerators, across a range of mAs settings. Each CBCT image was registered 100 times, with random initial offsets introduced. Image registration was performed using the grey value correlation ratio algorithm in the Elekta XVI software, to a mask of the prostate volume with 5 mm expansion. Residual registration errors were calculated after correcting for the initial introduced phantom set-up error. Registration performance with the OBI images was similar to that of XVI. There was a clear dependence on imaging dose for the XVI images with residual errors increasing below 4mGy. It was not possible to acquire images with doses lower than ~5mGy with the OBI system and no evidence of reduced performance was observed at this dose. Registration failures (maximum target registration error > 3.6 mm on the surface of a 30mm sphere) occurred in 5% to 9% of registrations except for the lowest dose XVI scan (31%). The uncertainty in automatic image registration with both OBI and XVI images was found to be adequate for clinical use within a normal range of acquisition settings.

HyDEn: A Hybrid Steganocryptographic Approach for Data Encryption Using Randomized Error-Correcting DNA Codes

PubMed Central

Regoui, Chaouki; Durand, Guillaume; Belliveau, Luc; Léger, Serge

2013-01-01

This paper presents a novel hybrid DNA encryption (HyDEn) approach that uses randomized assignments of unique error-correcting DNA Hamming code words for single characters in the extended ASCII set. HyDEn relies on custom-built quaternary codes and a private key used in the randomized assignment of code words and the cyclic permutations applied on the encoded message. Along with its ability to detect and correct errors, HyDEn equals or outperforms existing cryptographic methods and represents a promising in silico DNA steganographic approach. PMID:23984392

Teaching Cancer Patients the Value of Correct Positioning During Radiotherapy Using Visual Aids and Practical Exercises.

PubMed

Hansen, Helle; Nielsen, Berit Kjærside; Boejen, Annette; Vestergaard, Anne

2018-06-01

The aim of this study was to investigate if teaching patients about positioning before radiotherapy treatment would (a) reduce the residual rotational set-up errors, (b) reduce the number of repositionings and (c) improve patients' sense of control by increasing self-efficacy and reducing distress. Patients were randomized to either standard care (control group) or standard care and a teaching session combining visual aids and practical exercises (intervention group). Daily images from the treatment sessions were evaluated off-line. Both groups filled in a questionnaire before and at the end of the treatment course on various aspects of cooperation with the staff regarding positioning. Comparisons of residual rotational set-up errors showed an improvement in the intervention group compared to the control group. No significant differences were found in number of repositionings, self-efficacy or distress. Results show that it is possible to teach patients about positioning and thereby improve precision in positioning. Teaching patients about positioning did not seem to affect self-efficacy or distress scores at baseline and at the end of the treatment course.

Discovery of error-tolerant biclusters from noisy gene expression data.

PubMed

Gupta, Rohit; Rao, Navneet; Kumar, Vipin

2011-11-24

An important analysis performed on microarray gene-expression data is to discover biclusters, which denote groups of genes that are coherently expressed for a subset of conditions. Various biclustering algorithms have been proposed to find different types of biclusters from these real-valued gene-expression data sets. However, these algorithms suffer from several limitations such as inability to explicitly handle errors/noise in the data; difficulty in discovering small bicliusters due to their top-down approach; inability of some of the approaches to find overlapping biclusters, which is crucial as many genes participate in multiple biological processes. Association pattern mining also produce biclusters as their result and can naturally address some of these limitations. However, traditional association mining only finds exact biclusters, which limits its applicability in real-life data sets where the biclusters may be fragmented due to random noise/errors. Moreover, as they only work with binary or boolean attributes, their application on gene-expression data require transforming real-valued attributes to binary attributes, which often results in loss of information. Many past approaches have tried to address the issue of noise and handling real-valued attributes independently but there is no systematic approach that addresses both of these issues together. In this paper, we first propose a novel error-tolerant biclustering model, 'ET-bicluster', and then propose a bottom-up heuristic-based mining algorithm to sequentially discover error-tolerant biclusters directly from real-valued gene-expression data. The efficacy of our proposed approach is illustrated by comparing it with a recent approach RAP in the context of two biological problems: discovery of functional modules and discovery of biomarkers. For the first problem, two real-valued S.Cerevisiae microarray gene-expression data sets are used to demonstrate that the biclusters obtained from ET-bicluster approach not only recover larger set of genes as compared to those obtained from RAP approach but also have higher functional coherence as evaluated using the GO-based functional enrichment analysis. The statistical significance of the discovered error-tolerant biclusters as estimated by using two randomization tests, reveal that they are indeed biologically meaningful and statistically significant. For the second problem of biomarker discovery, we used four real-valued Breast Cancer microarray gene-expression data sets and evaluate the biomarkers obtained using MSigDB gene sets. The results obtained for both the problems: functional module discovery and biomarkers discovery, clearly signifies the usefulness of the proposed ET-bicluster approach and illustrate the importance of explicitly incorporating noise/errors in discovering coherent groups of genes from gene-expression data.

What Randomized Benchmarking Actually Measures

DOE PAGES

Proctor, Timothy; Rudinger, Kenneth; Young, Kevin; ...

2017-09-28

Randomized benchmarking (RB) is widely used to measure an error rate of a set of quantum gates, by performing random circuits that would do nothing if the gates were perfect. In the limit of no finite-sampling error, the exponential decay rate of the observable survival probabilities, versus circuit length, yields a single error metric r. For Clifford gates with arbitrary small errors described by process matrices, r was believed to reliably correspond to the mean, over all Clifford gates, of the average gate infidelity between the imperfect gates and their ideal counterparts. We show that this quantity is not amore » well-defined property of a physical gate set. It depends on the representations used for the imperfect and ideal gates, and the variant typically computed in the literature can differ from r by orders of magnitude. We present new theories of the RB decay that are accurate for all small errors describable by process matrices, and show that the RB decay curve is a simple exponential for all such errors. Here, these theories allow explicit computation of the error rate that RB measures (r), but as far as we can tell it does not correspond to the infidelity of a physically allowed (completely positive) representation of the imperfect gates.« less

Virtual reality robotic surgery warm-up improves task performance in a dry laboratory environment: a prospective randomized controlled study.

PubMed

Lendvay, Thomas S; Brand, Timothy C; White, Lee; Kowalewski, Timothy; Jonnadula, Saikiran; Mercer, Laina D; Khorsand, Derek; Andros, Justin; Hannaford, Blake; Satava, Richard M

2013-06-01

Preoperative simulation warm-up has been shown to improve performance and reduce errors in novice and experienced surgeons, yet existing studies have only investigated conventional laparoscopy. We hypothesized that a brief virtual reality (VR) robotic warm-up would enhance robotic task performance and reduce errors. In a 2-center randomized trial, 51 residents and experienced minimally invasive surgery faculty in General Surgery, Urology, and Gynecology underwent a validated robotic surgery proficiency curriculum on a VR robotic simulator and on the da Vinci surgical robot (Intuitive Surgical Inc). Once they successfully achieved performance benchmarks, surgeons were randomized to either receive a 3- to 5-minute VR simulator warm-up or read a leisure book for 10 minutes before performing similar and dissimilar (intracorporeal suturing) robotic surgery tasks. The primary outcomes compared were task time, tool path length, economy of motion, technical, and cognitive errors. Task time (-29.29 seconds, p = 0.001; 95% CI, -47.03 to -11.56), path length (-79.87 mm; p = 0.014; 95% CI, -144.48 to -15.25), and cognitive errors were reduced in the warm-up group compared with the control group for similar tasks. Global technical errors in intracorporeal suturing (0.32; p = 0.020; 95% CI, 0.06-0.59) were reduced after the dissimilar VR task. When surgeons were stratified by earlier robotic and laparoscopic clinical experience, the more experienced surgeons (n = 17) demonstrated significant improvements from warm-up in task time (-53.5 seconds; p = 0.001; 95% CI, -83.9 to -23.0) and economy of motion (0.63 mm/s; p = 0.007; 95% CI, 0.18-1.09), and improvement in these metrics was not statistically significantly appreciated in the less-experienced cohort (n = 34). We observed significant performance improvement and error reduction rates among surgeons of varying experience after VR warm-up for basic robotic surgery tasks. In addition, the VR warm-up reduced errors on a more complex task (robotic suturing), suggesting the generalizability of the warm-up. Copyright © 2013 American College of Surgeons. All rights reserved.

Decorrelation of the true and estimated classifier errors in high-dimensional settings.

PubMed

Hanczar, Blaise; Hua, Jianping; Dougherty, Edward R

2007-01-01

The aim of many microarray experiments is to build discriminatory diagnosis and prognosis models. Given the huge number of features and the small number of examples, model validity which refers to the precision of error estimation is a critical issue. Previous studies have addressed this issue via the deviation distribution (estimated error minus true error), in particular, the deterioration of cross-validation precision in high-dimensional settings where feature selection is used to mitigate the peaking phenomenon (overfitting). Because classifier design is based upon random samples, both the true and estimated errors are sample-dependent random variables, and one would expect a loss of precision if the estimated and true errors are not well correlated, so that natural questions arise as to the degree of correlation and the manner in which lack of correlation impacts error estimation. We demonstrate the effect of correlation on error precision via a decomposition of the variance of the deviation distribution, observe that the correlation is often severely decreased in high-dimensional settings, and show that the effect of high dimensionality on error estimation tends to result more from its decorrelating effects than from its impact on the variance of the estimated error. We consider the correlation between the true and estimated errors under different experimental conditions using both synthetic and real data, several feature-selection methods, different classification rules, and three error estimators commonly used (leave-one-out cross-validation, k-fold cross-validation, and .632 bootstrap). Moreover, three scenarios are considered: (1) feature selection, (2) known-feature set, and (3) all features. Only the first is of practical interest; however, the other two are needed for comparison purposes. We will observe that the true and estimated errors tend to be much more correlated in the case of a known feature set than with either feature selection or using all features, with the better correlation between the latter two showing no general trend, but differing for different models.

A multiobserver study of the effects of including point-of-care patient photographs with portable radiography: a means to detect wrong-patient errors.

PubMed

Tridandapani, Srini; Ramamurthy, Senthil; Provenzale, James; Obuchowski, Nancy A; Evanoff, Michael G; Bhatti, Pamela

2014-08-01

To evaluate whether the presence of facial photographs obtained at the point-of-care of portable radiography leads to increased detection of wrong-patient errors. In this institutional review board-approved study, 166 radiograph-photograph combinations were obtained from 30 patients. Consecutive radiographs from the same patients resulted in 83 unique pairs (ie, a new radiograph and prior, comparison radiograph) for interpretation. To simulate wrong-patient errors, mismatched pairs were generated by pairing radiographs from different patients chosen randomly from the sample. Ninety radiologists each interpreted a unique randomly chosen set of 10 radiographic pairs, containing up to 10% mismatches (ie, error pairs). Radiologists were randomly assigned to interpret radiographs with or without photographs. The number of mismatches was identified, and interpretation times were recorded. Ninety radiologists with 21 ± 10 (mean ± standard deviation) years of experience were recruited to participate in this observer study. With the introduction of photographs, the proportion of errors detected increased from 31% (9 of 29) to 77% (23 of 30; P = .006). The odds ratio for detection of error with photographs to detection without photographs was 7.3 (95% confidence interval: 2.29-23.18). Observer qualifications, training, or practice in cardiothoracic radiology did not influence sensitivity for error detection. There is no significant difference in interpretation time for studies without photographs and those with photographs (60 ± 22 vs. 61 ± 25 seconds; P = .77). In this observer study, facial photographs obtained simultaneously with portable chest radiographs increased the identification of any wrong-patient errors, without substantial increase in interpretation time. This technique offers a potential means to increase patient safety through correct patient identification. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

SU-F-P-18: Development of the Technical Training System for Patient Set-Up Considering Rotational Correction in the Virtual Environment Using Three-Dimensional Computer Graphic Engine

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

Imura, K; Fujibuchi, T; Hirata, H

Purpose: Patient set-up skills in radiotherapy treatment room have a great influence on treatment effect for image guided radiotherapy. In this study, we have developed the training system for improving practical set-up skills considering rotational correction in the virtual environment away from the pressure of actual treatment room by using three-dimensional computer graphic (3DCG) engine. Methods: The treatment room for external beam radiotherapy was reproduced in the virtual environment by using 3DCG engine (Unity). The viewpoints to perform patient set-up in the virtual treatment room were arranged in both sides of the virtual operable treatment couch to assume actual performancemore » by two clinical staffs. The position errors to mechanical isocenter considering alignment between skin marker and laser on the virtual patient model were displayed by utilizing numerical values expressed in SI units and the directions of arrow marks. The rotational errors calculated with a point on the virtual body axis as the center of each rotation axis for the virtual environment were corrected by adjusting rotational position of the body phantom wound the belt with gyroscope preparing on table in a real space. These rotational errors were evaluated by describing vector outer product operations and trigonometric functions in the script for patient set-up technique. Results: The viewpoints in the virtual environment allowed individual user to visually recognize the position discrepancy to mechanical isocenter until eliminating the positional errors of several millimeters. The rotational errors between the two points calculated with the center point could be efficiently corrected to display the minimum technique mathematically by utilizing the script. Conclusion: By utilizing the script to correct the rotational errors as well as accurate positional recognition for patient set-up technique, the training system developed for improving patient set-up skills enabled individual user to indicate efficient positional correction methods easily.« less

Virtual Reality Robotic Surgery Warm-Up Improves Task Performance in a Dry Lab Environment: A Prospective Randomized Controlled Study

PubMed Central

Lendvay, Thomas S.; Brand, Timothy C.; White, Lee; Kowalewski, Timothy; Jonnadula, Saikiran; Mercer, Laina; Khorsand, Derek; Andros, Justin; Hannaford, Blake; Satava, Richard M.

2014-01-01

Background Pre-operative simulation “warm-up” has been shown to improve performance and reduce errors in novice and experienced surgeons, yet existing studies have only investigated conventional laparoscopy. We hypothesized a brief virtual reality (VR) robotic warm-up would enhance robotic task performance and reduce errors. Study Design In a two-center randomized trial, fifty-one residents and experienced minimally invasive surgery faculty in General Surgery, Urology, and Gynecology underwent a validated robotic surgery proficiency curriculum on a VR robotic simulator and on the da Vinci surgical robot. Once successfully achieving performance benchmarks, surgeons were randomized to either receive a 3-5 minute VR simulator warm-up or read a leisure book for 10 minutes prior to performing similar and dissimilar (intracorporeal suturing) robotic surgery tasks. The primary outcomes compared were task time, tool path length, economy of motion, technical and cognitive errors. Results Task time (-29.29sec, p=0.001, 95%CI-47.03,-11.56), path length (-79.87mm, p=0.014, 95%CI -144.48,-15.25), and cognitive errors were reduced in the warm-up group compared to the control group for similar tasks. Global technical errors in intracorporeal suturing (0.32, p=0.020, 95%CI 0.06,0.59) were reduced after the dissimilar VR task. When surgeons were stratified by prior robotic and laparoscopic clinical experience, the more experienced surgeons(n=17) demonstrated significant improvements from warm-up in task time (-53.5sec, p=0.001, 95%CI -83.9,-23.0) and economy of motion (0.63mm/sec, p=0.007, 95%CI 0.18,1.09), whereas improvement in these metrics was not statistically significantly appreciated in the less experienced cohort(n=34). Conclusions We observed a significant performance improvement and error reduction rate among surgeons of varying experience after VR warm-up for basic robotic surgery tasks. In addition, the VR warm-up reduced errors on a more complex task (robotic suturing) suggesting the generalizability of the warm-up. PMID:23583618

Determination of the precision error of the pulmonary artery thermodilution catheter using an in vitro continuous flow test rig.

PubMed

Yang, Xiao-Xing; Critchley, Lester A; Joynt, Gavin M

2011-01-01

Thermodilution cardiac output using a pulmonary artery catheter is the reference method against which all new methods of cardiac output measurement are judged. However, thermodilution lacks precision and has a quoted precision error of ± 20%. There is uncertainty about its true precision and this causes difficulty when validating new cardiac output technology. Our aim in this investigation was to determine the current precision error of thermodilution measurements. A test rig through which water circulated at different constant rates with ports to insert catheters into a flow chamber was assembled. Flow rate was measured by an externally placed transonic flowprobe and meter. The meter was calibrated by timed filling of a cylinder. Arrow and Edwards 7Fr thermodilution catheters, connected to a Siemens SC9000 cardiac output monitor, were tested. Thermodilution readings were made by injecting 5 mL of ice-cold water. Precision error was divided into random and systematic components, which were determined separately. Between-readings (random) variability was determined for each catheter by taking sets of 10 readings at different flow rates. Coefficient of variation (CV) was calculated for each set and averaged. Between-catheter systems (systematic) variability was derived by plotting calibration lines for sets of catheters. Slopes were used to estimate the systematic component. Performances of 3 cardiac output monitors were compared: Siemens SC9000, Siemens Sirecust 1261, and Philips MP50. Five Arrow and 5 Edwards catheters were tested using the Siemens SC9000 monitor. Flow rates between 0.7 and 7.0 L/min were studied. The CV (random error) for Arrow was 5.4% and for Edwards was 4.8%. The random precision error was ± 10.0% (95% confidence limits). CV (systematic error) was 5.8% and 6.0%, respectively. The systematic precision error was ± 11.6%. The total precision error of a single thermodilution reading was ± 15.3% and ± 13.0% for triplicate readings. Precision error increased by 45% when using the Sirecust monitor and 100% when using the Philips monitor. In vitro testing of pulmonary artery catheters enabled us to measure both the random and systematic error components of thermodilution cardiac output measurement, and thus calculate the precision error. Using the Siemens monitor, we established a precision error of ± 15.3% for single and ± 13.0% for triplicate reading, which was similar to the previous estimate of ± 20%. However, this precision error was significantly worsened by using the Sirecust and Philips monitors. Clinicians should recognize that the precision error of thermodilution cardiac output is dependent on the selection of catheter and monitor model.

Smooth empirical Bayes estimation of observation error variances in linear systems

NASA Technical Reports Server (NTRS)

Martz, H. F., Jr.; Lian, M. W.

1972-01-01

A smooth empirical Bayes estimator was developed for estimating the unknown random scale component of each of a set of observation error variances. It is shown that the estimator possesses a smaller average squared error loss than other estimators for a discrete time linear system.

An investigation of error correcting techniques for OMV and AXAF

NASA Technical Reports Server (NTRS)

Ingels, Frank; Fryer, John

1991-01-01

The original objectives of this project were to build a test system for the NASA 255/223 Reed/Solomon encoding/decoding chip set and circuit board. This test system was then to be interfaced with a convolutional system at MSFC to examine the performance of the concantinated codes. After considerable work, it was discovered that the convolutional system could not function as needed. This report documents the design, construction, and testing of the test apparatus for the R/S chip set. The approach taken was to verify the error correcting behavior of the chip set by injecting known error patterns onto data and observing the results. Error sequences were generated using pseudo-random number generator programs, with Poisson time distribution between errors and Gaussian burst lengths. Sample means, variances, and number of un-correctable errors were calculated for each data set before testing.

MO-F-CAMPUS-T-05: Correct Or Not to Correct for Rotational Patient Set-Up Errors in Stereotactic Radiosurgery

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

Briscoe, M; Ploquin, N; Voroney, JP

2015-06-15

Purpose: To quantify the effect of patient rotation in stereotactic radiation therapy and establish a threshold where rotational patient set-up errors have a significant impact on target coverage. Methods: To simulate rotational patient set-up errors, a Matlab code was created to rotate the patient dose distribution around the treatment isocentre, located centrally in the lesion, while keeping the structure contours in the original locations on the CT and MRI. Rotations of 1°, 3°, and 5° for each of the pitch, roll, and yaw, as well as simultaneous rotations of 1°, 3°, and 5° around all three axes were applied tomore » two types of brain lesions: brain metastasis and acoustic neuroma. In order to analyze multiple tumour shapes, these plans included small spherical (metastasis), elliptical (acoustic neuroma), and large irregular (metastasis) tumour structures. Dose-volume histograms and planning target volumes were compared between the planned patient positions and those with simulated rotational set-up errors. The RTOG conformity index for patient rotation was also investigated. Results: Examining the tumour volumes that received 80% of the prescription dose in the planned and rotated patient positions showed decreases in prescription dose coverage of up to 2.3%. Conformity indices for treatments with simulated rotational errors showed decreases of up to 3% compared to the original plan. For irregular lesions, degradation of 1% of the target coverage can be seen for rotations as low as 3°. Conclusions: This data shows that for elliptical or spherical targets, rotational patient set-up errors less than 3° around any or all axes do not have a significant impact on the dose delivered to the target volume or the conformity index of the plan. However the same rotational errors would have an impact on plans for irregular tumours.« less

Improving Exercise Performance with an Accelerometer-Based Smartphone App: A Randomized Controlled Trial.

PubMed

Bittel, Daniel C; Bittel, Adam J; Williams, Christine; Elazzazi, Ashraf

2017-05-01

Proper exercise form is critical for the safety and efficacy of therapeutic exercise. This research examines if a novel smartphone application, designed to monitor and provide real-time corrections during resistance training, can reduce performance errors and elicit a motor learning response. Forty-two participants aged 18 to 65 years were randomly assigned to treatment and control groups. Both groups were tested for the number of movement errors made during a 10-repetition set completed at baseline, immediately after, and 1 to 2 weeks after a single training session of knee extensions. The treatment group trained with real-time, smartphone-generated feedback, whereas the control subjects did not. Group performance (number of errors) was compared across test sets using a 2-factor mixed-model analysis of variance. No differences were observed between groups for age, sex, or resistance training experience. There was a significant interaction between test set and group. The treatment group demonstrated fewer errors on posttests 1 and 2 compared with pretest (P < 0.05). There was no reduction in the number of errors on any posttest for control subjects. Smartphone apps, such as the one used in this study, may enhance patient supervision, safety, and exercise efficacy across rehabilitation settings. A single training session with the app promoted motor learning and improved exercise performance.

Free kick instead of cross-validation in maximum-likelihood refinement of macromolecular crystal structures

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

Pražnikar, Jure; University of Primorska,; Turk, Dušan, E-mail: dusan.turk@ijs.si

2014-12-01

The maximum-likelihood free-kick target, which calculates model error estimates from the work set and a randomly displaced model, proved superior in the accuracy and consistency of refinement of crystal structures compared with the maximum-likelihood cross-validation target, which calculates error estimates from the test set and the unperturbed model. The refinement of a molecular model is a computational procedure by which the atomic model is fitted to the diffraction data. The commonly used target in the refinement of macromolecular structures is the maximum-likelihood (ML) function, which relies on the assessment of model errors. The current ML functions rely on cross-validation. Theymore » utilize phase-error estimates that are calculated from a small fraction of diffraction data, called the test set, that are not used to fit the model. An approach has been developed that uses the work set to calculate the phase-error estimates in the ML refinement from simulating the model errors via the random displacement of atomic coordinates. It is called ML free-kick refinement as it uses the ML formulation of the target function and is based on the idea of freeing the model from the model bias imposed by the chemical energy restraints used in refinement. This approach for the calculation of error estimates is superior to the cross-validation approach: it reduces the phase error and increases the accuracy of molecular models, is more robust, provides clearer maps and may use a smaller portion of data for the test set for the calculation of R{sub free} or may leave it out completely.« less

Error Model and Compensation of Bell-Shaped Vibratory Gyro

PubMed Central

Su, Zhong; Liu, Ning; Li, Qing

2015-01-01

A bell-shaped vibratory angular velocity gyro (BVG), inspired by the Chinese traditional bell, is a type of axisymmetric shell resonator gyroscope. This paper focuses on development of an error model and compensation of the BVG. A dynamic equation is firstly established, based on a study of the BVG working mechanism. This equation is then used to evaluate the relationship between the angular rate output signal and bell-shaped resonator character, analyze the influence of the main error sources and set up an error model for the BVG. The error sources are classified from the error propagation characteristics, and the compensation method is presented based on the error model. Finally, using the error model and compensation method, the BVG is calibrated experimentally including rough compensation, temperature and bias compensation, scale factor compensation and noise filter. The experimentally obtained bias instability is from 20.5°/h to 4.7°/h, the random walk is from 2.8°/h1/2 to 0.7°/h1/2 and the nonlinearity is from 0.2% to 0.03%. Based on the error compensation, it is shown that there is a good linear relationship between the sensing signal and the angular velocity, suggesting that the BVG is a good candidate for the field of low and medium rotational speed measurement. PMID:26393593

Minimum savings requirements in shared savings provider payment.

PubMed

Pope, Gregory C; Kautter, John

2012-11-01

Payer (insurer) sharing of savings is a way of motivating providers of medical services to reduce cost growth. A Medicare shared savings program is established for accountable care organizations in the 2010 Patient Protection and Affordable Care Act. However, savings created by providers cannot be distinguished from the normal (random) variation in medical claims costs, setting up a classic principal-agent problem. To lessen the likelihood of paying undeserved bonuses, payers may pay bonuses only if observed savings exceed minimum levels. We study the trade-off between two types of errors in setting minimum savings requirements: paying bonuses when providers do not create savings and not paying bonuses when providers create savings. Copyright © 2011 John Wiley & Sons, Ltd.

The effect of rainfall measurement uncertainties on rainfall-runoff processes modelling.

PubMed

Stransky, D; Bares, V; Fatka, P

2007-01-01

Rainfall data are a crucial input for various tasks concerning the wet weather period. Nevertheless, their measurement is affected by random and systematic errors that cause an underestimation of the rainfall volume. Therefore, the general objective of the presented work was to assess the credibility of measured rainfall data and to evaluate the effect of measurement errors on urban drainage modelling tasks. Within the project, the methodology of the tipping bucket rain gauge (TBR) was defined and assessed in terms of uncertainty analysis. A set of 18 TBRs was calibrated and the results were compared to the previous calibration. This enables us to evaluate the ageing of TBRs. A propagation of calibration and other systematic errors through the rainfall-runoff model was performed on experimental catchment. It was found that the TBR calibration is important mainly for tasks connected with the assessment of peak values and high flow durations. The omission of calibration leads to up to 30% underestimation and the effect of other systematic errors can add a further 15%. The TBR calibration should be done every two years in order to catch up the ageing of TBR mechanics. Further, the authors recommend to adjust the dynamic test duration proportionally to generated rainfall intensity.

The dependence of crowding on flanker complexity and target-flanker similarity

PubMed Central

Bernard, Jean-Baptiste; Chung, Susana T.L.

2013-01-01

We examined the effects of the spatial complexity of flankers and target-flanker similarity on the performance of identifying crowded letters. On each trial, observers identified the middle character of random strings of three characters (“trigrams”) briefly presented at 10° below fixation. We tested the 26 lowercase letters of the Times-Roman and Courier fonts, a set of 79 characters (letters and non-letters) of the Times-Roman font, and the uppercase letters of two highly complex ornamental fonts, Edwardian and Aristocrat. Spatial complexity of characters was quantified by the length of the morphological skeleton of each character, and target-flanker similarity was defined based on a psychometric similarity matrix. Our results showed that (1) letter identification error rate increases with flanker complexity up to a certain value, beyond which error rate becomes independent of flanker complexity; (2) the increase of error rate is slower for high-complexity target letters; (3) error rate increases with target-flanker similarity; and (4) mislocation error rate increases with target-flanker similarity. These findings, combined with the current understanding of the faulty feature integration account of crowding, provide some constraints of how the feature integration process could cause perceptual errors. PMID:21730225

Dissecting random and systematic differences between noisy composite data sets.

PubMed

Diederichs, Kay

2017-04-01

Composite data sets measured on different objects are usually affected by random errors, but may also be influenced by systematic (genuine) differences in the objects themselves, or the experimental conditions. If the individual measurements forming each data set are quantitative and approximately normally distributed, a correlation coefficient is often used to compare data sets. However, the relations between data sets are not obvious from the matrix of pairwise correlations since the numerical value of the correlation coefficient is lowered by both random and systematic differences between the data sets. This work presents a multidimensional scaling analysis of the pairwise correlation coefficients which places data sets into a unit sphere within low-dimensional space, at a position given by their CC* values [as defined by Karplus & Diederichs (2012), Science, 336, 1030-1033] in the radial direction and by their systematic differences in one or more angular directions. This dimensionality reduction can not only be used for classification purposes, but also to derive data-set relations on a continuous scale. Projecting the arrangement of data sets onto the subspace spanned by systematic differences (the surface of a unit sphere) allows, irrespective of the random-error levels, the identification of clusters of closely related data sets. The method gains power with increasing numbers of data sets. It is illustrated with an example from low signal-to-noise ratio image processing, and an application in macromolecular crystallography is shown, but the approach is completely general and thus should be widely applicable.

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

Proctor, Timothy; Rudinger, Kenneth; Young, Kevin

Randomized benchmarking (RB) is widely used to measure an error rate of a set of quantum gates, by performing random circuits that would do nothing if the gates were perfect. In the limit of no finite-sampling error, the exponential decay rate of the observable survival probabilities, versus circuit length, yields a single error metric r. For Clifford gates with arbitrary small errors described by process matrices, r was believed to reliably correspond to the mean, over all Clifford gates, of the average gate infidelity between the imperfect gates and their ideal counterparts. We show that this quantity is not amore » well-defined property of a physical gate set. It depends on the representations used for the imperfect and ideal gates, and the variant typically computed in the literature can differ from r by orders of magnitude. We present new theories of the RB decay that are accurate for all small errors describable by process matrices, and show that the RB decay curve is a simple exponential for all such errors. Here, these theories allow explicit computation of the error rate that RB measures (r), but as far as we can tell it does not correspond to the infidelity of a physically allowed (completely positive) representation of the imperfect gates.« less

Resampling-Based Empirical Bayes Multiple Testing Procedures for Controlling Generalized Tail Probability and Expected Value Error Rates: Focus on the False Discovery Rate and Simulation Study

PubMed Central

Dudoit, Sandrine; Gilbert, Houston N.; van der Laan, Mark J.

2014-01-01

Summary This article proposes resampling-based empirical Bayes multiple testing procedures for controlling a broad class of Type I error rates, defined as generalized tail probability (gTP) error rates, gTP(q, g) = Pr(g(Vn, Sn) > q), and generalized expected value (gEV) error rates, gEV(g) = E[g(Vn, Sn)], for arbitrary functions g(Vn, Sn) of the numbers of false positives Vn and true positives Sn. Of particular interest are error rates based on the proportion g(Vn, Sn) = Vn/(Vn + Sn) of Type I errors among the rejected hypotheses, such as the false discovery rate (FDR), FDR = E[Vn/(Vn + Sn)]. The proposed procedures offer several advantages over existing methods. They provide Type I error control for general data generating distributions, with arbitrary dependence structures among variables. Gains in power are achieved by deriving rejection regions based on guessed sets of true null hypotheses and null test statistics randomly sampled from joint distributions that account for the dependence structure of the data. The Type I error and power properties of an FDR-controlling version of the resampling-based empirical Bayes approach are investigated and compared to those of widely-used FDR-controlling linear step-up procedures in a simulation study. The Type I error and power trade-off achieved by the empirical Bayes procedures under a variety of testing scenarios allows this approach to be competitive with or outperform the Storey and Tibshirani (2003) linear step-up procedure, as an alternative to the classical Benjamini and Hochberg (1995) procedure. PMID:18932138

Can the BMS Algorithm Decode Up to \\lfloor \\frac{d_G-g-1}{2}\\rfloor Errors? Yes, but with Some Additional Remarks

NASA Astrophysics Data System (ADS)

Sakata, Shojiro; Fujisawa, Masaya

It is a well-known fact [7], [9] that the BMS algorithm with majority voting can decode up to half the Feng-Rao designed distance dFR. Since dFR is not smaller than the Goppa designed distance dG, that algorithm can correct up to \\lfloor \\frac{d_G-1}{2}\\rfloor errors. On the other hand, it has been considered to be evident that the original BMS algorithm (without voting) [1], [2] can correct up to \\lfloor \\frac{d_G-g-1}{2}\\rfloor errors similarly to the basic algorithm by Skorobogatov-Vladut. But, is it true? In this short paper, we show that it is true, although we need a few remarks and some additional procedures for determining the Groebner basis of the error locator ideal exactly. In fact, as the basic algorithm gives a set of polynomials whose zero set contains the error locators as a subset, it cannot always give the exact error locators, unless the syndrome equation is solved to find the error values in addition.

Continuous Glucose Monitoring in Newborn Infants

PubMed Central

Thomas, Felicity; Signal, Mathew; Harris, Deborah L.; Weston, Philip J.; Harding, Jane E.; Shaw, Geoffrey M.

2014-01-01

Neonatal hypoglycemia is common and can cause serious brain injury. Continuous glucose monitoring (CGM) could improve hypoglycemia detection, while reducing blood glucose (BG) measurements. Calibration algorithms use BG measurements to convert sensor signals into CGM data. Thus, inaccuracies in calibration BG measurements directly affect CGM values and any metrics calculated from them. The aim was to quantify the effect of timing delays and calibration BG measurement errors on hypoglycemia metrics in newborn infants. Data from 155 babies were used. Two timing and 3 BG meter error models (Abbott Optium Xceed, Roche Accu-Chek Inform II, Nova Statstrip) were created using empirical data. Monte-Carlo methods were employed, and each simulation was run 1000 times. Each set of patient data in each simulation had randomly selected timing and/or measurement error added to BG measurements before CGM data were calibrated. The number of hypoglycemic events, duration of hypoglycemia, and hypoglycemic index were then calculated using the CGM data and compared to baseline values. Timing error alone had little effect on hypoglycemia metrics, but measurement error caused substantial variation. Abbott results underreported the number of hypoglycemic events by up to 8 and Roche overreported by up to 4 where the original number reported was 2. Nova results were closest to baseline. Similar trends were observed in the other hypoglycemia metrics. Errors in blood glucose concentration measurements used for calibration of CGM devices can have a clinically important impact on detection of hypoglycemia. If CGM devices are going to be used for assessing hypoglycemia it is important to understand of the impact of these errors on CGM data. PMID:24876618

Health plan auditing: 100-percent-of-claims vs. random-sample audits.

PubMed

Sillup, George P; Klimberg, Ronald K

2011-01-01

The objective of this study was to examine the relative efficacy of two different methodologies for auditing self-funded medical claim expenses: 100-percent-of-claims auditing versus random-sampling auditing. Multiple data sets of claim errors or 'exceptions' from two Fortune-100 corporations were analysed and compared to 100 simulated audits of 300- and 400-claim random samples. Random-sample simulations failed to identify a significant number and amount of the errors that ranged from $200,000 to $750,000. These results suggest that health plan expenses of corporations could be significantly reduced if they audited 100% of claims and embraced a zero-defect approach.

Discrepancy-based error estimates for Quasi-Monte Carlo III. Error distributions and central limits

NASA Astrophysics Data System (ADS)

Hoogland, Jiri; Kleiss, Ronald

1997-04-01

In Quasi-Monte Carlo integration, the integration error is believed to be generally smaller than in classical Monte Carlo with the same number of integration points. Using an appropriate definition of an ensemble of quasi-random point sets, we derive various results on the probability distribution of the integration error, which can be compared to the standard Central Limit Theorem for normal stochastic sampling. In many cases, a Gaussian error distribution is obtained.

Impact of patient-specific factors, irradiated left ventricular volume, and treatment set-up errors on the development of myocardial perfusion defects after radiation therapy for left-sided breast cancer

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

Evans, Elizabeth S.; Prosnitz, Robert G.; Yu Xiaoli

2006-11-15

Purpose: The aim of this study was to assess the impact of patient-specific factors, left ventricle (LV) volume, and treatment set-up errors on the rate of perfusion defects 6 to 60 months post-radiation therapy (RT) in patients receiving tangential RT for left-sided breast cancer. Methods and Materials: Between 1998 and 2005, a total of 153 patients were enrolled onto an institutional review board-approved prospective study and had pre- and serial post-RT (6-60 months) cardiac perfusion scans to assess for perfusion defects. Of the patients, 108 had normal pre-RT perfusion scans and available follow-up data. The impact of patient-specific factors onmore » the rate of perfusion defects was assessed at various time points using univariate and multivariate analysis. The impact of set-up errors on the rate of perfusion defects was also analyzed using a one-tailed Fisher's Exact test. Results: Consistent with our prior results, the volume of LV in the RT field was the most significant predictor of perfusion defects on both univariate (p = 0.0005 to 0.0058) and multivariate analysis (p = 0.0026 to 0.0029). Body mass index (BMI) was the only significant patient-specific factor on both univariate (p = 0.0005 to 0.022) and multivariate analysis (p = 0.0091 to 0.05). In patients with very small volumes of LV in the planned RT fields, the rate of perfusion defects was significantly higher when the fields set-up 'too deep' (83% vs. 30%, p = 0.059). The frequency of deep set-up errors was significantly higher among patients with BMI {>=}25 kg/m{sup 2} compared with patients of normal weight (47% vs. 28%, p = 0.068). Conclusions: BMI {>=}25 kg/m{sup 2} may be a significant risk factor for cardiac toxicity after RT for left-sided breast cancer, possibly because of more frequent deep set-up errors resulting in the inclusion of additional heart in the RT fields. Further study is necessary to better understand the impact of patient-specific factors and set-up errors on the development of RT-induced perfusion defects.« less

Error free physically unclonable function with programmed resistive random access memory using reliable resistance states by specific identification-generation method

NASA Astrophysics Data System (ADS)

Tseng, Po-Hao; Hsu, Kai-Chieh; Lin, Yu-Yu; Lee, Feng-Min; Lee, Ming-Hsiu; Lung, Hsiang-Lan; Hsieh, Kuang-Yeu; Chung Wang, Keh; Lu, Chih-Yuan

2018-04-01

A high performance physically unclonable function (PUF) implemented with WO3 resistive random access memory (ReRAM) is presented in this paper. This robust ReRAM-PUF can eliminated bit flipping problem at very high temperature (up to 250 °C) due to plentiful read margin by using initial resistance state and set resistance state. It is also promised 10 years retention at the temperature range of 210 °C. These two stable resistance states enable stable operation at automotive environments from -40 to 125 °C without need of temperature compensation circuit. The high uniqueness of PUF can be achieved by implementing a proposed identification (ID)-generation method. Optimized forming condition can move 50% of the cells to low resistance state and the remaining 50% remain at initial high resistance state. The inter- and intra-PUF evaluations with unlimited separation of hamming distance (HD) are successfully demonstrated even under the corner condition. The number of reproduction was measured to exceed 107 times with 0% bit error rate (BER) at read voltage from 0.4 to 0.7 V.

Statistical models for estimating daily streamflow in Michigan

USGS Publications Warehouse

Holtschlag, D.J.; Salehi, Habib

1992-01-01

Statistical models for estimating daily streamflow were analyzed for 25 pairs of streamflow-gaging stations in Michigan. Stations were paired by randomly choosing a station operated in 1989 at which 10 or more years of continuous flow data had been collected and at which flow is virtually unregulated; a nearby station was chosen where flow characteristics are similar. Streamflow data from the 25 randomly selected stations were used as the response variables; streamflow data at the nearby stations were used to generate a set of explanatory variables. Ordinary-least squares regression (OLSR) equations, autoregressive integrated moving-average (ARIMA) equations, and transfer function-noise (TFN) equations were developed to estimate the log transform of flow for the 25 randomly selected stations. The precision of each type of equation was evaluated on the basis of the standard deviation of the estimation errors. OLSR equations produce one set of estimation errors; ARIMA and TFN models each produce l sets of estimation errors corresponding to the forecast lead. The lead-l forecast is the estimate of flow l days ahead of the most recent streamflow used as a response variable in the estimation. In this analysis, the standard deviation of lead l ARIMA and TFN forecast errors were generally lower than the standard deviation of OLSR errors for l < 2 days and l < 9 days, respectively. Composite estimates were computed as a weighted average of forecasts based on TFN equations and backcasts (forecasts of the reverse-ordered series) based on ARIMA equations. The standard deviation of composite errors varied throughout the length of the estimation interval and generally was at maximum near the center of the interval. For comparison with OLSR errors, the mean standard deviation of composite errors were computed for intervals of length 1 to 40 days. The mean standard deviation of length-l composite errors were generally less than the standard deviation of the OLSR errors for l < 32 days. In addition, the composite estimates ensure a gradual transition between periods of estimated and measured flows. Model performance among stations of differing model error magnitudes were compared by computing ratios of the mean standard deviation of the length l composite errors to the standard deviation of OLSR errors. The mean error ratio for the set of 25 selected stations was less than 1 for intervals l < 32 days. Considering the frequency characteristics of the length of intervals of estimated record in Michigan, the effective mean error ratio for intervals < 30 days was 0.52. Thus, for intervals of estimation of 1 month or less, the error of the composite estimate is substantially lower than error of the OLSR estimate.

A novel optical fiber displacement sensor of wider measurement range based on neural network

NASA Astrophysics Data System (ADS)

Guo, Yuan; Dai, Xue Feng; Wang, Yu Tian

2006-02-01

By studying on the output characteristics of random type optical fiber sensor and semicircular type optical fiber sensor, the ratio of the two output signals was used as the output signal of the whole system. Then the measurement range was enlarged, the linearity was improved, and the errors of reflective and absorbent changing of target surface are automatically compensated. Meantime, an optical fiber sensor model of correcting static error based on BP artificial neural network(ANN) is set up. So the intrinsic errors such as effects of fluctuations in the light, circuit excursion, the intensity losses in the fiber lines and the additional losses in the receiving fiber caused by bends are eliminated. By discussing in theory and experiment, the error of nonlinear is 2.9%, the measuring range reaches to 5-6mm and the relative accuracy is 2%.And this sensor has such characteristics as no electromagnetic interference, simple construction, high sensitivity, good accuracy and stability. Also the multi-point sensor system can be used to on-line and non-touch monitor in working locales.

Measuring Data Quality Through a Source Data Verification Audit in a Clinical Research Setting.

PubMed

Houston, Lauren; Probst, Yasmine; Humphries, Allison

2015-01-01

Health data has long been scrutinised in relation to data quality and integrity problems. Currently, no internationally accepted or "gold standard" method exists measuring data quality and error rates within datasets. We conducted a source data verification (SDV) audit on a prospective clinical trial dataset. An audit plan was applied to conduct 100% manual verification checks on a 10% random sample of participant files. A quality assurance rule was developed, whereby if >5% of data variables were incorrect a second 10% random sample would be extracted from the trial data set. Error was coded: correct, incorrect (valid or invalid), not recorded or not entered. Audit-1 had a total error of 33% and audit-2 36%. The physiological section was the only audit section to have <5% error. Data not recorded to case report forms had the greatest impact on error calculations. A significant association (p=0.00) was found between audit-1 and audit-2 and whether or not data was deemed correct or incorrect. Our study developed a straightforward method to perform a SDV audit. An audit rule was identified and error coding was implemented. Findings demonstrate that monitoring data quality by a SDV audit can identify data quality and integrity issues within clinical research settings allowing quality improvement to be made. The authors suggest this approach be implemented for future research.

Continuous glucose monitoring in newborn infants: how do errors in calibration measurements affect detected hypoglycemia?

PubMed

Thomas, Felicity; Signal, Mathew; Harris, Deborah L; Weston, Philip J; Harding, Jane E; Shaw, Geoffrey M; Chase, J Geoffrey

2014-05-01

Neonatal hypoglycemia is common and can cause serious brain injury. Continuous glucose monitoring (CGM) could improve hypoglycemia detection, while reducing blood glucose (BG) measurements. Calibration algorithms use BG measurements to convert sensor signals into CGM data. Thus, inaccuracies in calibration BG measurements directly affect CGM values and any metrics calculated from them. The aim was to quantify the effect of timing delays and calibration BG measurement errors on hypoglycemia metrics in newborn infants. Data from 155 babies were used. Two timing and 3 BG meter error models (Abbott Optium Xceed, Roche Accu-Chek Inform II, Nova Statstrip) were created using empirical data. Monte-Carlo methods were employed, and each simulation was run 1000 times. Each set of patient data in each simulation had randomly selected timing and/or measurement error added to BG measurements before CGM data were calibrated. The number of hypoglycemic events, duration of hypoglycemia, and hypoglycemic index were then calculated using the CGM data and compared to baseline values. Timing error alone had little effect on hypoglycemia metrics, but measurement error caused substantial variation. Abbott results underreported the number of hypoglycemic events by up to 8 and Roche overreported by up to 4 where the original number reported was 2. Nova results were closest to baseline. Similar trends were observed in the other hypoglycemia metrics. Errors in blood glucose concentration measurements used for calibration of CGM devices can have a clinically important impact on detection of hypoglycemia. If CGM devices are going to be used for assessing hypoglycemia it is important to understand of the impact of these errors on CGM data. © 2014 Diabetes Technology Society.

Models for H₃ receptor antagonist activity of sulfonylurea derivatives.

PubMed

Khatri, Naveen; Madan, A K

2014-03-01

The histamine H₃ receptor has been perceived as an auspicious target for the treatment of various central and peripheral nervous system diseases. In present study, a wide variety of 60 2D and 3D molecular descriptors (MDs) were successfully utilized for the development of models for the prediction of antagonist activity of sulfonylurea derivatives for histamine H₃ receptors. Models were developed through decision tree (DT), random forest (RF) and moving average analysis (MAA). Dragon software version 6.0.28 was employed for calculation of values of diverse MDs of each analogue involved in the data set. The DT classified and correctly predicted the input data with an impressive non-error rate of 94% in the training set and 82.5% during cross validation. RF correctly classified the analogues into active and inactive with a non-error rate of 79.3%. The MAA based models predicted the antagonist histamine H₃ receptor activity with non-error rate up to 90%. Active ranges of the proposed MAA based models not only exhibited high potency but also showed improved safety as indicated by relatively high values of selectivity index. The statistical significance of the models was assessed through sensitivity, specificity, non-error rate, Matthew's correlation coefficient and intercorrelation analysis. Proposed models offer vast potential for providing lead structures for development of potent but safe H₃ receptor antagonist sulfonylurea derivatives. Copyright © 2013 Elsevier Inc. All rights reserved.

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty

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

Lu, Ning; Diao, Ruisheng; Hafen, Ryan P.

2013-12-18

This paper presents four algorithms to generate random forecast error time series, including a truncated-normal distribution model, a state-space based Markov model, a seasonal autoregressive moving average (ARMA) model, and a stochastic-optimization based model. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets, used for variable generation integration studies. A comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics. This paper discusses and comparesmore » the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.« less

Technical Note: Millimeter precision in ultrasound based patient positioning: Experimental quantification of inherent technical limitations

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

Ballhausen, Hendrik, E-mail: hendrik.ballhausen@med.uni-muenchen.de; Hieber, Sheila; Li, Minglun

2014-08-15

Purpose: To identify the relevant technical sources of error of a system based on three-dimensional ultrasound (3D US) for patient positioning in external beam radiotherapy. To quantify these sources of error in a controlled laboratory setting. To estimate the resulting end-to-end geometric precision of the intramodality protocol. Methods: Two identical free-hand 3D US systems at both the planning-CT and the treatment room were calibrated to the laboratory frame of reference. Every step of the calibration chain was repeated multiple times to estimate its contribution to overall systematic and random error. Optimal margins were computed given the identified and quantified systematicmore » and random errors. Results: In descending order of magnitude, the identified and quantified sources of error were: alignment of calibration phantom to laser marks 0.78 mm, alignment of lasers in treatment vs planning room 0.51 mm, calibration and tracking of 3D US probe 0.49 mm, alignment of stereoscopic infrared camera to calibration phantom 0.03 mm. Under ideal laboratory conditions, these errors are expected to limit ultrasound-based positioning to an accuracy of 1.05 mm radially. Conclusions: The investigated 3D ultrasound system achieves an intramodal accuracy of about 1 mm radially in a controlled laboratory setting. The identified systematic and random errors require an optimal clinical tumor volume to planning target volume margin of about 3 mm. These inherent technical limitations do not prevent clinical use, including hypofractionation or stereotactic body radiation therapy.« less

Accelerating Convolutional Sparse Coding for Curvilinear Structures Segmentation by Refining SCIRD-TS Filter Banks.

PubMed

Annunziata, Roberto; Trucco, Emanuele

2016-11-01

Deep learning has shown great potential for curvilinear structure (e.g., retinal blood vessels and neurites) segmentation as demonstrated by a recent auto-context regression architecture based on filter banks learned by convolutional sparse coding. However, learning such filter banks is very time-consuming, thus limiting the amount of filters employed and the adaptation to other data sets (i.e., slow re-training). We address this limitation by proposing a novel acceleration strategy to speed-up convolutional sparse coding filter learning for curvilinear structure segmentation. Our approach is based on a novel initialisation strategy (warm start), and therefore it is different from recent methods improving the optimisation itself. Our warm-start strategy is based on carefully designed hand-crafted filters (SCIRD-TS), modelling appearance properties of curvilinear structures which are then refined by convolutional sparse coding. Experiments on four diverse data sets, including retinal blood vessels and neurites, suggest that the proposed method reduces significantly the time taken to learn convolutional filter banks (i.e., up to -82%) compared to conventional initialisation strategies. Remarkably, this speed-up does not worsen performance; in fact, filters learned with the proposed strategy often achieve a much lower reconstruction error and match or exceed the segmentation performance of random and DCT-based initialisation, when used as input to a random forest classifier.

SU-E-J-29: Automatic Image Registration Performance of Three IGRT Systems for Prostate Radiotherapy

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

Barber, J; University of Sydney, Sydney, NSW; Sykes, J

Purpose: To compare the performance of an automatic image registration algorithm on image sets collected on three commercial image guidance systems, and explore its relationship with imaging parameters such as dose and sharpness. Methods: Images of a CIRS Virtually Human Male Pelvis phantom (VHMP) were collected on the CBCT systems of Varian TrueBeam/OBI and Elekta Synergy/XVI linear accelerators, across a range of mAs settings; and MVCT on a Tomotherapy Hi-ART accelerator with a range of pitch. Using the 6D correlation ratio algorithm of XVI, each image was registered to a mask of the prostate volume with a 5 mm expansion.more » Registrations were repeated 100 times, with random initial offsets introduced to simulate daily matching. Residual registration errors were calculated by correcting for the initial phantom set-up error. Automatic registration was also repeated after reconstructing images with different sharpness filters. Results: All three systems showed good registration performance, with residual translations <0.5mm (1σ) for typical clinical dose and reconstruction settings. Residual rotational error had larger range, with 0.8°, 1.2° and 1.9° for 1σ in XVI, OBI and Tomotherapy respectively. The registration accuracy of XVI images showed a strong dependence on imaging dose, particularly below 4mGy. No evidence of reduced performance was observed at the lowest dose settings for OBI and Tomotherapy, but these were above 4mGy. Registration failures (maximum target registration error > 3.6 mm on the surface of a 30mm sphere) occurred in 5% to 10% of registrations. Changing the sharpness of image reconstruction had no significant effect on registration performance. Conclusions: Using the present automatic image registration algorithm, all IGRT systems tested provided satisfactory registrations for clinical use, within a normal range of acquisition settings.« less

Query construction, entropy, and generalization in neural-network models

NASA Astrophysics Data System (ADS)

Sollich, Peter

1994-05-01

We study query construction algorithms, which aim at improving the generalization ability of systems that learn from examples by choosing optimal, nonredundant training sets. We set up a general probabilistic framework for deriving such algorithms from the requirement of optimizing a suitable objective function; specifically, we consider the objective functions entropy (or information gain) and generalization error. For two learning scenarios, the high-low game and the linear perceptron, we evaluate the generalization performance obtained by applying the corresponding query construction algorithms and compare it to training on random examples. We find qualitative differences between the two scenarios due to the different structure of the underlying rules (nonlinear and ``noninvertible'' versus linear); in particular, for the linear perceptron, random examples lead to the same generalization ability as a sequence of queries in the limit of an infinite number of examples. We also investigate learning algorithms which are ill matched to the learning environment and find that, in this case, minimum entropy queries can in fact yield a lower generalization ability than random examples. Finally, we study the efficiency of single queries and its dependence on the learning history, i.e., on whether the previous training examples were generated randomly or by querying, and the difference between globally and locally optimal query construction.

A service evaluation of on-line image-guided radiotherapy to lower extremity sarcoma: Investigating the workload implications of a 3 mm action level for image assessment and correction prior to delivery.

PubMed

Taylor, C; Parker, J; Stratford, J; Warren, M

2018-05-01

Although all systematic and random positional setup errors can be corrected for in entirety during on-line image-guided radiotherapy, the use of a specified action level, below which no correction occurs, is also an option. The following service evaluation aimed to investigate the use of this 3 mm action level for on-line image assessment and correction (online, systematic set-up error and weekly evaluation) for lower extremity sarcoma, and understand the impact on imaging frequency and patient positioning error within one cancer centre. All patients were immobilised using a thermoplastic shell attached to a plastic base and an individual moulded footrest. A retrospective analysis of 30 patients was performed. Patient setup and correctional data derived from cone beam CT analysis was retrieved. The timing, frequency and magnitude of corrections were evaluated. The population systematic and random error was derived. 20% of patients had no systematic corrections over the duration of treatment, and 47% had one. The maximum number of systematic corrections per course of radiotherapy was 4, which occurred for 2 patients. 34% of episodes occurred within the first 5 fractions. All patients had at least one observed translational error during their treatment greater than 0.3 cm, and 80% of patients had at least one observed translational error during their treatment greater than 0.5 cm. The population systematic error was 0.14 cm, 0.10 cm, 0.14 cm and random error was 0.27 cm, 0.22 cm, 0.23 cm in the lateral, caudocranial and anteroposterial directions. The required Planning Target Volume margin for the study population was 0.55 cm, 0.41 cm and 0.50 cm in the lateral, caudocranial and anteroposterial directions. The 3 mm action level for image assessment and correction prior to delivery reduced the imaging burden and focussed intervention on patients that exhibited greater positional variability. This strategy could be an efficient deployment of departmental resources if full daily correction of positional setup error is not possible. Copyright © 2017. Published by Elsevier Ltd.

Demonstration of qubit operations below a rigorous fault tolerance threshold with gate set tomography

DOE PAGES

Blume-Kohout, Robin; Gamble, John King; Nielsen, Erik; ...

2017-02-15

Quantum information processors promise fast algorithms for problems inaccessible to classical computers. But since qubits are noisy and error-prone, they will depend on fault-tolerant quantum error correction (FTQEC) to compute reliably. Quantum error correction can protect against general noise if—and only if—the error in each physical qubit operation is smaller than a certain threshold. The threshold for general errors is quantified by their diamond norm. Until now, qubits have been assessed primarily by randomized benchmarking, which reports a different error rate that is not sensitive to all errors, and cannot be compared directly to diamond norm thresholds. Finally, we usemore » gate set tomography to completely characterize operations on a trapped-Yb +-ion qubit and demonstrate with greater than 95% confidence that they satisfy a rigorous threshold for FTQEC (diamond norm ≤6.7 × 10 -4).« less

Demonstration of qubit operations below a rigorous fault tolerance threshold with gate set tomography

PubMed Central

Blume-Kohout, Robin; Gamble, John King; Nielsen, Erik; Rudinger, Kenneth; Mizrahi, Jonathan; Fortier, Kevin; Maunz, Peter

2017-01-01

Quantum information processors promise fast algorithms for problems inaccessible to classical computers. But since qubits are noisy and error-prone, they will depend on fault-tolerant quantum error correction (FTQEC) to compute reliably. Quantum error correction can protect against general noise if—and only if—the error in each physical qubit operation is smaller than a certain threshold. The threshold for general errors is quantified by their diamond norm. Until now, qubits have been assessed primarily by randomized benchmarking, which reports a different error rate that is not sensitive to all errors, and cannot be compared directly to diamond norm thresholds. Here we use gate set tomography to completely characterize operations on a trapped-Yb+-ion qubit and demonstrate with greater than 95% confidence that they satisfy a rigorous threshold for FTQEC (diamond norm ≤6.7 × 10−4). PMID:28198466

Demonstration of qubit operations below a rigorous fault tolerance threshold with gate set tomography

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

Blume-Kohout, Robin; Gamble, John King; Nielsen, Erik

Quantum information processors promise fast algorithms for problems inaccessible to classical computers. But since qubits are noisy and error-prone, they will depend on fault-tolerant quantum error correction (FTQEC) to compute reliably. Quantum error correction can protect against general noise if—and only if—the error in each physical qubit operation is smaller than a certain threshold. The threshold for general errors is quantified by their diamond norm. Until now, qubits have been assessed primarily by randomized benchmarking, which reports a different error rate that is not sensitive to all errors, and cannot be compared directly to diamond norm thresholds. Finally, we usemore » gate set tomography to completely characterize operations on a trapped-Yb +-ion qubit and demonstrate with greater than 95% confidence that they satisfy a rigorous threshold for FTQEC (diamond norm ≤6.7 × 10 -4).« less

SU-F-J-47: Inherent Uncertainty in the Positional Shifts Determined by a Volumetric Cone Beam Imaging System

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

Giri, U; Ganesh, T; Saini, V

2016-06-15

Purpose: To quantify inherent uncertainty associated with a volumetric imaging system in its determination of positional shifts. Methods: The study was performed on an Elekta Axesse™ linac’s XVI cone beam computed tomography (CBCT) system. A CT image data set of a Penta- Guide phantom was used as reference image by placing isocenter at the center of the phantom.The phantom was placed arbitrarily on the couch close to isocenter and CBCT images were obtained. The CBCT dataset was matched with the reference image using XVI software and the shifts were determined in 6-dimensions. Without moving the phantom, this process was repeatedmore » 20 times consecutively within 30 minutes on a single day. Mean shifts and their standard deviations in all 6-dimensions were determined for all the 20 instances of imaging. For any given day, the first set of shifts obtained was kept as reference and the deviations of the subsequent 19 sets from the reference set were scored. Mean differences and their standard deviations were determined. In this way, data were obtained for 30 consecutive working days. Results: Tabulating the mean deviations and their standard deviations observed on each day for the 30 measurement days, systematic and random errors in the determination of shifts by XVI software were calculated. The systematic errors were found to be 0.03, 0.04 and 0.03 mm while random errors were 0.05, 0.06 and 0.06 mm in lateral, craniocaudal and anterio-posterior directions respectively. For rotational shifts, the systematic errors were 0.02°, 0.03° and 0.03° and random errors were 0.06°, 0.05° and 0.05° in pitch, roll and yaw directions respectively. Conclusion: The inherent uncertainties in every image guidance system should be assessed and baseline values established at the time of its commissioning. These shall be periodically tested as part of the QA protocol.« less

Estimation of reliable range of electron temperature measurements with sets of given optical bandpass filters for KSTAR Thomson scattering system based on synthetic Thomson data

NASA Astrophysics Data System (ADS)

Kim, K.-h.; Oh, T.-s.; Park, K.-r.; Lee, J. H.; Ghim, Y.-c.

2017-11-01

One factor determining the reliability of measurements of electron temperature using a Thomson scattering (TS) system is transmittance of the optical bandpass filters in polychromators. We investigate the system performance as a function of electron temperature to determine reliable range of measurements for a given set of the optical bandpass filters. We show that such a reliability, i.e., both bias and random errors, can be obtained by building a forward model of the KSTAR TS system to generate synthetic TS data with the prescribed electron temperature and density profiles. The prescribed profiles are compared with the estimated ones to quantify both bias and random errors.

Capsule Performance Optimization in the National Ignition Campaign

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

Landen, O L; MacGowan, B J; Haan, S W

2009-10-13

A capsule performance optimization campaign will be conducted at the National Ignition Facility to substantially increase the probability of ignition. The campaign will experimentally correct for residual uncertainties in the implosion and hohlraum physics used in our radiation-hydrodynamic computational models before proceeding to cryogenic-layered implosions and ignition attempts. The required tuning techniques using a variety of ignition capsule surrogates have been demonstrated at the Omega facility under scaled hohlraum and capsule conditions relevant to the ignition design and shown to meet the required sensitivity and accuracy. In addition, a roll-up of all expected random and systematic uncertainties in setting themore » key ignition laser and target parameters due to residual measurement, calibration, cross-coupling, surrogacy, and scale-up errors has been derived that meets the required budget.« less

Capsule performance optimization in the national ignition campaign

NASA Astrophysics Data System (ADS)

Landen, O. L.; MacGowan, B. J.; Haan, S. W.; Edwards, J.

2010-08-01

A capsule performance optimization campaign will be conducted at the National Ignition Facility [1] to substantially increase the probability of ignition. The campaign will experimentally correct for residual uncertainties in the implosion and hohlraum physics used in our radiation-hydrodynamic computational models before proceeding to cryogenic-layered implosions and ignition attempts. The required tuning techniques using a variety of ignition capsule surrogates have been demonstrated at the Omega facility under scaled hohlraum and capsule conditions relevant to the ignition design and shown to meet the required sensitivity and accuracy. In addition, a roll-up of all expected random and systematic uncertainties in setting the key ignition laser and target parameters due to residual measurement, calibration, cross-coupling, surrogacy, and scale-up errors has been derived that meets the required budget.

Experimental Errors in QSAR Modeling Sets: What We Can Do and What We Cannot Do.

PubMed

Zhao, Linlin; Wang, Wenyi; Sedykh, Alexander; Zhu, Hao

2017-06-30

Numerous chemical data sets have become available for quantitative structure-activity relationship (QSAR) modeling studies. However, the quality of different data sources may be different based on the nature of experimental protocols. Therefore, potential experimental errors in the modeling sets may lead to the development of poor QSAR models and further affect the predictions of new compounds. In this study, we explored the relationship between the ratio of questionable data in the modeling sets, which was obtained by simulating experimental errors, and the QSAR modeling performance. To this end, we used eight data sets (four continuous endpoints and four categorical endpoints) that have been extensively curated both in-house and by our collaborators to create over 1800 various QSAR models. Each data set was duplicated to create several new modeling sets with different ratios of simulated experimental errors (i.e., randomizing the activities of part of the compounds) in the modeling process. A fivefold cross-validation process was used to evaluate the modeling performance, which deteriorates when the ratio of experimental errors increases. All of the resulting models were also used to predict external sets of new compounds, which were excluded at the beginning of the modeling process. The modeling results showed that the compounds with relatively large prediction errors in cross-validation processes are likely to be those with simulated experimental errors. However, after removing a certain number of compounds with large prediction errors in the cross-validation process, the external predictions of new compounds did not show improvement. Our conclusion is that the QSAR predictions, especially consensus predictions, can identify compounds with potential experimental errors. But removing those compounds by the cross-validation procedure is not a reasonable means to improve model predictivity due to overfitting.

Experimental Errors in QSAR Modeling Sets: What We Can Do and What We Cannot Do

PubMed Central

2017-01-01

Numerous chemical data sets have become available for quantitative structure–activity relationship (QSAR) modeling studies. However, the quality of different data sources may be different based on the nature of experimental protocols. Therefore, potential experimental errors in the modeling sets may lead to the development of poor QSAR models and further affect the predictions of new compounds. In this study, we explored the relationship between the ratio of questionable data in the modeling sets, which was obtained by simulating experimental errors, and the QSAR modeling performance. To this end, we used eight data sets (four continuous endpoints and four categorical endpoints) that have been extensively curated both in-house and by our collaborators to create over 1800 various QSAR models. Each data set was duplicated to create several new modeling sets with different ratios of simulated experimental errors (i.e., randomizing the activities of part of the compounds) in the modeling process. A fivefold cross-validation process was used to evaluate the modeling performance, which deteriorates when the ratio of experimental errors increases. All of the resulting models were also used to predict external sets of new compounds, which were excluded at the beginning of the modeling process. The modeling results showed that the compounds with relatively large prediction errors in cross-validation processes are likely to be those with simulated experimental errors. However, after removing a certain number of compounds with large prediction errors in the cross-validation process, the external predictions of new compounds did not show improvement. Our conclusion is that the QSAR predictions, especially consensus predictions, can identify compounds with potential experimental errors. But removing those compounds by the cross-validation procedure is not a reasonable means to improve model predictivity due to overfitting. PMID:28691113

Positioning accuracy for lung stereotactic body radiotherapy patients determined by on-treatment cone-beam CT imaging

PubMed Central

Richmond, N D; Pilling, K E; Peedell, C; Shakespeare, D; Walker, C P

2012-01-01

Stereotactic body radiotherapy for early stage non-small cell lung cancer is an emerging treatment option in the UK. Since relatively few high-dose ablative fractions are delivered to a small target volume, the consequences of a geometric miss are potentially severe. This paper presents the results of treatment delivery set-up data collected using Elekta Synergy (Elekta, Crawley, UK) cone-beam CT imaging for 17 patients immobilised using the Bodyfix system (Medical Intelligence, Schwabmuenchen, Germany). Images were acquired on the linear accelerator at initial patient treatment set-up, following any position correction adjustments, and post-treatment. These were matched to the localisation CT scan using the Elekta XVI software. In total, 71 fractions were analysed for patient set-up errors. The mean vector error at initial set-up was calculated as 5.3±2.7 mm, which was significantly reduced to 1.4±0.7 mm following image guided correction. Post-treatment the corresponding value was 2.1±1.2 mm. The use of the Bodyfix abdominal compression plate on 5 patients to reduce the range of tumour excursion during respiration produced mean longitudinal set-up corrections of −4.4±4.5 mm compared with −0.7±2.6 mm without compression for the remaining 12 patients. The use of abdominal compression led to a greater variation in set-up errors and a shift in the mean value. PMID:22665927

Error Distribution Evaluation of the Third Vanishing Point Based on Random Statistical Simulation

NASA Astrophysics Data System (ADS)

Li, C.

2012-07-01

POS, integrated by GPS / INS (Inertial Navigation Systems), has allowed rapid and accurate determination of position and attitude of remote sensing equipment for MMS (Mobile Mapping Systems). However, not only does INS have system error, but also it is very expensive. Therefore, in this paper error distributions of vanishing points are studied and tested in order to substitute INS for MMS in some special land-based scene, such as ground façade where usually only two vanishing points can be detected. Thus, the traditional calibration approach based on three orthogonal vanishing points is being challenged. In this article, firstly, the line clusters, which parallel to each others in object space and correspond to the vanishing points, are detected based on RANSAC (Random Sample Consensus) and parallelism geometric constraint. Secondly, condition adjustment with parameters is utilized to estimate nonlinear error equations of two vanishing points (VX, VY). How to set initial weights for the adjustment solution of single image vanishing points is presented. Solving vanishing points and estimating their error distributions base on iteration method with variable weights, co-factor matrix and error ellipse theory. Thirdly, under the condition of known error ellipses of two vanishing points (VX, VY) and on the basis of the triangle geometric relationship of three vanishing points, the error distribution of the third vanishing point (VZ) is calculated and evaluated by random statistical simulation with ignoring camera distortion. Moreover, Monte Carlo methods utilized for random statistical estimation are presented. Finally, experimental results of vanishing points coordinate and their error distributions are shown and analyzed.

Enhanced orbit determination filter sensitivity analysis: Error budget development

NASA Technical Reports Server (NTRS)

Estefan, J. A.; Burkhart, P. D.

1994-01-01

An error budget analysis is presented which quantifies the effects of different error sources in the orbit determination process when the enhanced orbit determination filter, recently developed, is used to reduce radio metric data. The enhanced filter strategy differs from more traditional filtering methods in that nearly all of the principal ground system calibration errors affecting the data are represented as filter parameters. Error budget computations were performed for a Mars Observer interplanetary cruise scenario for cases in which only X-band (8.4-GHz) Doppler data were used to determine the spacecraft's orbit, X-band ranging data were used exclusively, and a combined set in which the ranging data were used in addition to the Doppler data. In all three cases, the filter model was assumed to be a correct representation of the physical world. Random nongravitational accelerations were found to be the largest source of error contributing to the individual error budgets. Other significant contributors, depending on the data strategy used, were solar-radiation pressure coefficient uncertainty, random earth-orientation calibration errors, and Deep Space Network (DSN) station location uncertainty.

Improving Pulse Rate Measurements during Random Motion Using a Wearable Multichannel Reflectance Photoplethysmograph.

PubMed

Warren, Kristen M; Harvey, Joshua R; Chon, Ki H; Mendelson, Yitzhak

2016-03-07

Photoplethysmographic (PPG) waveforms are used to acquire pulse rate (PR) measurements from pulsatile arterial blood volume. PPG waveforms are highly susceptible to motion artifacts (MA), limiting the implementation of PR measurements in mobile physiological monitoring devices. Previous studies have shown that multichannel photoplethysmograms can successfully acquire diverse signal information during simple, repetitive motion, leading to differences in motion tolerance across channels. In this paper, we investigate the performance of a custom-built multichannel forehead-mounted photoplethysmographic sensor under a variety of intense motion artifacts. We introduce an advanced multichannel template-matching algorithm that chooses the channel with the least motion artifact to calculate PR for each time instant. We show that for a wide variety of random motion, channels respond differently to motion artifacts, and the multichannel estimate outperforms single-channel estimates in terms of motion tolerance, signal quality, and PR errors. We have acquired 31 data sets consisting of PPG waveforms corrupted by random motion and show that the accuracy of PR measurements achieved was increased by up to 2.7 bpm when the multichannel-switching algorithm was compared to individual channels. The percentage of PR measurements with error ≤ 5 bpm during motion increased by 18.9% when the multichannel switching algorithm was compared to the mean PR from all channels. Moreover, our algorithm enables automatic selection of the best signal fidelity channel at each time point among the multichannel PPG data.

Verification of unfold error estimates in the unfold operator code

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

Fehl, D.L.; Biggs, F.

Spectral unfolding is an inverse mathematical operation that attempts to obtain spectral source information from a set of response functions and data measurements. Several unfold algorithms have appeared over the past 30 years; among them is the unfold operator (UFO) code written at Sandia National Laboratories. In addition to an unfolded spectrum, the UFO code also estimates the unfold uncertainty (error) induced by estimated random uncertainties in the data. In UFO the unfold uncertainty is obtained from the error matrix. This built-in estimate has now been compared to error estimates obtained by running the code in a Monte Carlo fashionmore » with prescribed data distributions (Gaussian deviates). In the test problem studied, data were simulated from an arbitrarily chosen blackbody spectrum (10 keV) and a set of overlapping response functions. The data were assumed to have an imprecision of 5{percent} (standard deviation). One hundred random data sets were generated. The built-in estimate of unfold uncertainty agreed with the Monte Carlo estimate to within the statistical resolution of this relatively small sample size (95{percent} confidence level). A possible 10{percent} bias between the two methods was unresolved. The Monte Carlo technique is also useful in underdetermined problems, for which the error matrix method does not apply. UFO has been applied to the diagnosis of low energy x rays emitted by Z-pinch and ion-beam driven hohlraums. {copyright} {ital 1997 American Institute of Physics.}« less

Training a whole-book LSTM-based recognizer with an optimal training set

NASA Astrophysics Data System (ADS)

Soheili, Mohammad Reza; Yousefi, Mohammad Reza; Kabir, Ehsanollah; Stricker, Didier

2018-04-01

Despite the recent progress in OCR technologies, whole-book recognition, is still a challenging task, in particular in case of old and historical books, that the unknown font faces or low quality of paper and print contributes to the challenge. Therefore, pre-trained recognizers and generic methods do not usually perform up to required standards, and usually the performance degrades for larger scale recognition tasks, such as of a book. Such reportedly low error-rate methods turn out to require a great deal of manual correction. Generally, such methodologies do not make effective use of concepts such redundancy in whole-book recognition. In this work, we propose to train Long Short Term Memory (LSTM) networks on a minimal training set obtained from the book to be recognized. We show that clustering all the sub-words in the book, and using the sub-word cluster centers as the training set for the LSTM network, we can train models that outperform any identical network that is trained with randomly selected pages of the book. In our experiments, we also show that although the sub-word cluster centers are equivalent to about 8 pages of text for a 101- page book, a LSTM network trained on such a set performs competitively compared to an identical network that is trained on a set of 60 randomly selected pages of the book.

Analysis of space telescope data collection system

NASA Technical Reports Server (NTRS)

Ingels, F. M.; Schoggen, W. O.

1982-01-01

An analysis of the expected performance for the Multiple Access (MA) system is provided. The analysis covers the expected bit error rate performance, the effects of synchronization loss, the problem of self-interference, and the problem of phase ambiguity. The problem of false acceptance of a command word due to data inversion is discussed. A mathematical determination of the probability of accepting an erroneous command word due to a data inversion is presented. The problem is examined for three cases: (1) a data inversion only, (2) a data inversion and a random error within the same command word, and a block (up to 256 48-bit words) containing both a data inversion and a random error.

Keystroke Dynamics-Based Credential Hardening Systems

NASA Astrophysics Data System (ADS)

Bartlow, Nick; Cukic, Bojan

abstract Keystroke dynamics are becoming a well-known method for strengthening username- and password-based credential sets. The familiarity and ease of use of these traditional authentication schemes combined with the increased trustworthiness associated with biometrics makes them prime candidates for application in many web-based scenarios. Our keystroke dynamics system uses Breiman’s random forests algorithm to classify keystroke input sequences as genuine or imposter. The system is capable of operating at various points on a traditional ROC curve depending on application-specific security needs. As a username/password authentication scheme, our approach decreases the system penetration rate associated with compromised passwords up to 99.15%. Beyond presenting results demonstrating the credential hardening effect of our scheme, we look into the notion that a user’s familiarity to components of a credential set can non-trivially impact error rates.

Quantifying errors without random sampling.

PubMed

Phillips, Carl V; LaPole, Luwanna M

2003-06-12

All quantifications of mortality, morbidity, and other health measures involve numerous sources of error. The routine quantification of random sampling error makes it easy to forget that other sources of error can and should be quantified. When a quantification does not involve sampling, error is almost never quantified and results are often reported in ways that dramatically overstate their precision. We argue that the precision implicit in typical reporting is problematic and sketch methods for quantifying the various sources of error, building up from simple examples that can be solved analytically to more complex cases. There are straightforward ways to partially quantify the uncertainty surrounding a parameter that is not characterized by random sampling, such as limiting reported significant figures. We present simple methods for doing such quantifications, and for incorporating them into calculations. More complicated methods become necessary when multiple sources of uncertainty must be combined. We demonstrate that Monte Carlo simulation, using available software, can estimate the uncertainty resulting from complicated calculations with many sources of uncertainty. We apply the method to the current estimate of the annual incidence of foodborne illness in the United States. Quantifying uncertainty from systematic errors is practical. Reporting this uncertainty would more honestly represent study results, help show the probability that estimated values fall within some critical range, and facilitate better targeting of further research.

Far field beam pattern of one MW combined beam of laser diode array amplifiers for space power transmission

NASA Technical Reports Server (NTRS)

Kwon, Jin H.; Lee, Ja H.

1989-01-01

The far-field beam pattern and the power-collection efficiency are calculated for a multistage laser-diode-array amplifier consisting of about 200,000 5-W laser diode arrays with random distributions of phase and orientation errors and random diode failures. From the numerical calculation it is found that the far-field beam pattern is little affected by random failures of up to 20 percent of the laser diodes with reference of 80 percent receiving efficiency in the center spot. The random differences in phases among laser diodes due to probable manufacturing errors is allowed to about 0.2 times the wavelength. The maximum allowable orientation error is about 20 percent of the diffraction angle of a single laser diode aperture (about 1 cm). The preliminary results indicate that the amplifier could be used for space beam-power transmission with an efficiency of about 80 percent for a moderate-size (3-m-diameter) receiver placed at a distance of less than 50,000 km.

Modelling exoplanet detection with the LUVOIR Coronagraph: aberration sensitivity and error tolerances

NASA Astrophysics Data System (ADS)

Juanola-Parramon, Roser; Zimmerman, Neil; Bolcar, Matthew R.; Rizzo, Maxime; Roberge, Aki

2018-01-01

The Coronagraph is a key instrument on the Large UV-Optical-Infrared (LUVOIR) Surveyor mission concept. The Apodized Pupil Lyot Coronagraph (APLC) is one of the baselined mask technologies to enable 1E10 contrast observations in the habitable zones of nearby stars. Both the LUVOIR architectures A and B present a segmented aperture as input pupil, introducing a set of random tip/tilt and piston errors, among others, that greatly affect the performance of the coronagraph instrument by increasing the wavefront errors hence reducing the instrument sensitivity. In this poster we present the latest results of the simulation of these effects for different working angle regions and discuss the achieved contrast for exoplanet detection and characterization, including simulated observations under these circumstances, setting boundaries for the tolerance of such errors.

Meta-analysis in evidence-based healthcare: a paradigm shift away from random effects is overdue.

PubMed

Doi, Suhail A R; Furuya-Kanamori, Luis; Thalib, Lukman; Barendregt, Jan J

2017-12-01

Each year up to 20 000 systematic reviews and meta-analyses are published whose results influence healthcare decisions, thus making the robustness and reliability of meta-analytic methods one of the world's top clinical and public health priorities. The evidence synthesis makes use of either fixed-effect or random-effects statistical methods. The fixed-effect method has largely been replaced by the random-effects method as heterogeneity of study effects led to poor error estimation. However, despite the widespread use and acceptance of the random-effects method to correct this, it too remains unsatisfactory and continues to suffer from defective error estimation, posing a serious threat to decision-making in evidence-based clinical and public health practice. We discuss here the problem with the random-effects approach and demonstrate that there exist better estimators under the fixed-effect model framework that can achieve optimal error estimation. We argue for an urgent return to the earlier framework with updates that address these problems and conclude that doing so can markedly improve the reliability of meta-analytical findings and thus decision-making in healthcare.

Combinatorial neural codes from a mathematical coding theory perspective.

PubMed

Curto, Carina; Itskov, Vladimir; Morrison, Katherine; Roth, Zachary; Walker, Judy L

2013-07-01

Shannon's seminal 1948 work gave rise to two distinct areas of research: information theory and mathematical coding theory. While information theory has had a strong influence on theoretical neuroscience, ideas from mathematical coding theory have received considerably less attention. Here we take a new look at combinatorial neural codes from a mathematical coding theory perspective, examining the error correction capabilities of familiar receptive field codes (RF codes). We find, perhaps surprisingly, that the high levels of redundancy present in these codes do not support accurate error correction, although the error-correcting performance of receptive field codes catches up to that of random comparison codes when a small tolerance to error is introduced. However, receptive field codes are good at reflecting distances between represented stimuli, while the random comparison codes are not. We suggest that a compromise in error-correcting capability may be a necessary price to pay for a neural code whose structure serves not only error correction, but must also reflect relationships between stimuli.

Classification of echolocation clicks from odontocetes in the Southern California Bight.

PubMed

Roch, Marie A; Klinck, Holger; Baumann-Pickering, Simone; Mellinger, David K; Qui, Simon; Soldevilla, Melissa S; Hildebrand, John A

2011-01-01

This study presents a system for classifying echolocation clicks of six species of odontocetes in the Southern California Bight: Visually confirmed bottlenose dolphins, short- and long-beaked common dolphins, Pacific white-sided dolphins, Risso's dolphins, and presumed Cuvier's beaked whales. Echolocation clicks are represented by cepstral feature vectors that are classified by Gaussian mixture models. A randomized cross-validation experiment is designed to provide conditions similar to those found in a field-deployed system. To prevent matched conditions from inappropriately lowering the error rate, echolocation clicks associated with a single sighting are never split across the training and test data. Sightings are randomly permuted before assignment to folds in the experiment. This allows different combinations of the training and test data to be used while keeping data from each sighting entirely in the training or test set. The system achieves a mean error rate of 22% across 100 randomized three-fold cross-validation experiments. Four of the six species had mean error rates lower than the overall mean, with the presumed Cuvier's beaked whale clicks showing the best performance (<2% error rate). Long-beaked common and bottlenose dolphins proved the most difficult to classify, with mean error rates of 53% and 68%, respectively.

The impact of loss to follow-up on hypothesis tests of the treatment effect for several statistical methods in substance abuse clinical trials.

PubMed

Hedden, Sarra L; Woolson, Robert F; Carter, Rickey E; Palesch, Yuko; Upadhyaya, Himanshu P; Malcolm, Robert J

2009-07-01

"Loss to follow-up" can be substantial in substance abuse clinical trials. When extensive losses to follow-up occur, one must cautiously analyze and interpret the findings of a research study. Aims of this project were to introduce the types of missing data mechanisms and describe several methods for analyzing data with loss to follow-up. Furthermore, a simulation study compared Type I error and power of several methods when missing data amount and mechanism varies. Methods compared were the following: Last observation carried forward (LOCF), multiple imputation (MI), modified stratified summary statistics (SSS), and mixed effects models. Results demonstrated nominal Type I error for all methods; power was high for all methods except LOCF. Mixed effect model, modified SSS, and MI are generally recommended for use; however, many methods require that the data are missing at random or missing completely at random (i.e., "ignorable"). If the missing data are presumed to be nonignorable, a sensitivity analysis is recommended.

Special electronic distance meter calibration for precise engineering surveying industrial applications

NASA Astrophysics Data System (ADS)

Braun, Jaroslav; Štroner, Martin; Urban, Rudolf

2015-05-01

All surveying instruments and their measurements suffer from some errors. To refine the measurement results, it is necessary to use procedures restricting influence of the instrument errors on the measured values or to implement numerical corrections. In precise engineering surveying industrial applications the accuracy of the distances usually realized on relatively short distance is a key parameter limiting the resulting accuracy of the determined values (coordinates, etc.). To determine the size of systematic and random errors of the measured distances were made test with the idea of the suppression of the random error by the averaging of the repeating measurement, and reducing systematic errors influence of by identifying their absolute size on the absolute baseline realized in geodetic laboratory at the Faculty of Civil Engineering CTU in Prague. The 16 concrete pillars with forced centerings were set up and the absolute distances between the points were determined with a standard deviation of 0.02 millimetre using a Leica Absolute Tracker AT401. For any distance measured by the calibrated instruments (up to the length of the testing baseline, i.e. 38.6 m) can now be determined the size of error correction of the distance meter in two ways: Firstly by the interpolation on the raw data, or secondly using correction function derived by previous FFT transformation usage. The quality of this calibration and correction procedure was tested on three instruments (Trimble S6 HP, Topcon GPT-7501, Trimble M3) experimentally using Leica Absolute Tracker AT401. By the correction procedure was the standard deviation of the measured distances reduced significantly to less than 0.6 mm. In case of Topcon GPT-7501 is the nominal standard deviation 2 mm, achieved (without corrections) 2.8 mm and after corrections 0.55 mm; in case of Trimble M3 is nominal standard deviation 3 mm, achieved (without corrections) 1.1 mm and after corrections 0.58 mm; and finally in case of Trimble S6 is nominal standard deviation 1 mm, achieved (without corrections) 1.2 mm and after corrections 0.51 mm. Proposed procedure of the calibration and correction is in our opinion very suitable for increasing of the accuracy of the electronic distance measurement and allows the use of the common surveying instrument to achieve uncommonly high precision.

Importance of implementing an analytical quality control system in a core laboratory.

PubMed

Marques-Garcia, F; Garcia-Codesal, M F; Caro-Narros, M R; Contreras-SanFeliciano, T

2015-01-01

The aim of the clinical laboratory is to provide useful information for screening, diagnosis and monitoring of disease. The laboratory should ensure the quality of extra-analytical and analytical process, based on set criteria. To do this, it develops and implements a system of internal quality control, designed to detect errors, and compare its data with other laboratories, through external quality control. In this way it has a tool to detect the fulfillment of the objectives set, and in case of errors, allowing corrective actions to be made, and ensure the reliability of the results. This article sets out to describe the design and implementation of an internal quality control protocol, as well as its periodical assessment intervals (6 months) to determine compliance with pre-determined specifications (Stockholm Consensus(1)). A total of 40 biochemical and 15 immunochemical methods were evaluated using three different control materials. Next, a standard operation procedure was planned to develop a system of internal quality control that included calculating the error of the analytical process, setting quality specifications, and verifying compliance. The quality control data were then statistically depicted as means, standard deviations, and coefficients of variation, as well as systematic, random, and total errors. The quality specifications were then fixed and the operational rules to apply in the analytical process were calculated. Finally, our data were compared with those of other laboratories through an external quality assurance program. The development of an analytical quality control system is a highly structured process. This should be designed to detect errors that compromise the stability of the analytical process. The laboratory should review its quality indicators, systematic, random and total error at regular intervals, in order to ensure that they are meeting pre-determined specifications, and if not, apply the appropriate corrective actions. Copyright © 2015 SECA. Published by Elsevier Espana. All rights reserved.

How large are the consequences of covariate imbalance in cluster randomized trials: a simulation study with a continuous outcome and a binary covariate at the cluster level.

PubMed

Moerbeek, Mirjam; van Schie, Sander

2016-07-11

The number of clusters in a cluster randomized trial is often low. It is therefore likely random assignment of clusters to treatment conditions results in covariate imbalance. There are no studies that quantify the consequences of covariate imbalance in cluster randomized trials on parameter and standard error bias and on power to detect treatment effects. The consequences of covariance imbalance in unadjusted and adjusted linear mixed models are investigated by means of a simulation study. The factors in this study are the degree of imbalance, the covariate effect size, the cluster size and the intraclass correlation coefficient. The covariate is binary and measured at the cluster level; the outcome is continuous and measured at the individual level. The results show covariate imbalance results in negligible parameter bias and small standard error bias in adjusted linear mixed models. Ignoring the possibility of covariate imbalance while calculating the sample size at the cluster level may result in a loss in power of at most 25 % in the adjusted linear mixed model. The results are more severe for the unadjusted linear mixed model: parameter biases up to 100 % and standard error biases up to 200 % may be observed. Power levels based on the unadjusted linear mixed model are often too low. The consequences are most severe for large clusters and/or small intraclass correlation coefficients since then the required number of clusters to achieve a desired power level is smallest. The possibility of covariate imbalance should be taken into account while calculating the sample size of a cluster randomized trial. Otherwise more sophisticated methods to randomize clusters to treatments should be used, such as stratification or balance algorithms. All relevant covariates should be carefully identified, be actually measured and included in the statistical model to avoid severe levels of parameter and standard error bias and insufficient power levels.

Accuracy of modal wavefront estimation from eye transverse aberration measurements

NASA Astrophysics Data System (ADS)

Chyzh, Igor H.; Sokurenko, Vyacheslav M.

2001-01-01

The influence of random errors in measurement of eye transverse aberrations on the accuracy of reconstructing wave aberration as well as ametropia and astigmatism parameters is investigated. The dependence of mentioned errors on a ratio between the number of measurement points and the number of polynomial coefficients is found for different pupil location of measurement points. Recommendations are proposed for setting these ratios.

Effect of Preoperative Warm-up Exercise Before Laparoscopic Gynecological Surgery: A Randomized Trial.

PubMed

Polterauer, Stephan; Husslein, Heinrich; Kranawetter, Marlene; Schwameis, Richard; Reinthaller, Alexander; Heinze, Georg; Grimm, Christoph

2016-01-01

Laparoscopic surgical procedures require a high level of cognitive and psychomotoric skills. Thus, effective training methods to acquire an adequate level of expertise are crucial. The aim of this study was to investigate the effect of preoperative warm up training on surgeon׳s performance during gynecologic laparoscopic surgery. In this randomized controlled trial, surgeons performed a preoperative warm up training using a virtual reality simulator before laparoscopic unilateral salpingo-oophorectomy. Serving as their own controls, each subject performed 2 pairs of laparoscopic cases, each pair consisting of 1 case with and 1 without warm up before surgery. Surgeries were videotaped and psychomotoric skills were rated using objective structured assessment of technical skills (OSATS) and the generic error rating tool by a masked observer. Perioperative complications were assessed. Statistical analysis was performed using a mixed model, and mean OSATS scores were compared between both the groups. In total, data of 10 surgeons and 17 surgeries were available for analysis. No differences between educational level and surgical experiences were observed between the groups. Mean standard error psychomotoric and task-specific OSATS scores of 19.8 (1.7) and 3.7 (0.2) were observed in the warm up group compared with 18.6 (1.7) and 3.8 (0.2) in the no warm up group, respectively (p = 0.51 and p = 0.29). Using generic error rating tool, the total number of errors was 8.75 (2.15) in the warm up group compared with 10.8 (2.18) in the no warm-up group (p = 0.53). Perioperative complications and operating time did not differ between both the groups. The present study suggests that warm-up before laparoscopic salpingo-oophorectomy does not increase psychomotoric skills during surgery. Moreover, it does not influence operating time and complication rates. (Medical University of Vienna-IRB approval number, 1072/2011, ClinicalTrials.gov number, NCT01712607). Copyright © 2016 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Data entry errors and design for model-based tight glycemic control in critical care.

PubMed

Ward, Logan; Steel, James; Le Compte, Aaron; Evans, Alicia; Tan, Chia-Siong; Penning, Sophie; Shaw, Geoffrey M; Desaive, Thomas; Chase, J Geoffrey

2012-01-01

Tight glycemic control (TGC) has shown benefits but has been difficult to achieve consistently. Model-based methods and computerized protocols offer the opportunity to improve TGC quality but require human data entry, particularly of blood glucose (BG) values, which can be significantly prone to error. This study presents the design and optimization of data entry methods to minimize error for a computerized and model-based TGC method prior to pilot clinical trials. To minimize data entry error, two tests were carried out to optimize a method with errors less than the 5%-plus reported in other studies. Four initial methods were tested on 40 subjects in random order, and the best two were tested more rigorously on 34 subjects. The tests measured entry speed and accuracy. Errors were reported as corrected and uncorrected errors, with the sum comprising a total error rate. The first set of tests used randomly selected values, while the second set used the same values for all subjects to allow comparisons across users and direct assessment of the magnitude of errors. These research tests were approved by the University of Canterbury Ethics Committee. The final data entry method tested reduced errors to less than 1-2%, a 60-80% reduction from reported values. The magnitude of errors was clinically significant and was typically by 10.0 mmol/liter or an order of magnitude but only for extreme values of BG < 2.0 mmol/liter or BG > 15.0-20.0 mmol/liter, both of which could be easily corrected with automated checking of extreme values for safety. The data entry method selected significantly reduced data entry errors in the limited design tests presented, and is in use on a clinical pilot TGC study. The overall approach and testing methods are easily performed and generalizable to other applications and protocols. © 2012 Diabetes Technology Society.

Capsule performance optimization in the National Ignition Campaigna)

NASA Astrophysics Data System (ADS)

Landen, O. L.; Boehly, T. R.; Bradley, D. K.; Braun, D. G.; Callahan, D. A.; Celliers, P. M.; Collins, G. W.; Dewald, E. L.; Divol, L.; Glenzer, S. H.; Hamza, A.; Hicks, D. G.; Hoffman, N.; Izumi, N.; Jones, O. S.; Kirkwood, R. K.; Kyrala, G. A.; Michel, P.; Milovich, J.; Munro, D. H.; Nikroo, A.; Olson, R. E.; Robey, H. F.; Spears, B. K.; Thomas, C. A.; Weber, S. V.; Wilson, D. C.; Marinak, M. M.; Suter, L. J.; Hammel, B. A.; Meyerhofer, D. D.; Atherton, J.; Edwards, J.; Haan, S. W.; Lindl, J. D.; MacGowan, B. J.; Moses, E. I.

2010-05-01

A capsule performance optimization campaign will be conducted at the National Ignition Facility [G. H. Miller et al., Nucl. Fusion 44, 228 (2004)] to substantially increase the probability of ignition by laser-driven hohlraums [J. D. Lindl et al., Phys. Plasmas 11, 339 (2004)]. The campaign will experimentally correct for residual uncertainties in the implosion and hohlraum physics used in our radiation-hydrodynamic computational models before proceeding to cryogenic-layered implosions and ignition attempts. The required tuning techniques using a variety of ignition capsule surrogates have been demonstrated at the OMEGA facility under scaled hohlraum and capsule conditions relevant to the ignition design and shown to meet the required sensitivity and accuracy. In addition, a roll-up of all expected random and systematic uncertainties in setting the key ignition laser and target parameters due to residual measurement, calibration, cross-coupling, surrogacy, and scale-up errors has been derived that meets the required budget.

Capsule performance optimization in the National Ignition Campaign

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

Landen, O. L.; Bradley, D. K.; Braun, D. G.

2010-05-15

A capsule performance optimization campaign will be conducted at the National Ignition Facility [G. H. Miller et al., Nucl. Fusion 44, 228 (2004)] to substantially increase the probability of ignition by laser-driven hohlraums [J. D. Lindl et al., Phys. Plasmas 11, 339 (2004)]. The campaign will experimentally correct for residual uncertainties in the implosion and hohlraum physics used in our radiation-hydrodynamic computational models before proceeding to cryogenic-layered implosions and ignition attempts. The required tuning techniques using a variety of ignition capsule surrogates have been demonstrated at the OMEGA facility under scaled hohlraum and capsule conditions relevant to the ignition designmore » and shown to meet the required sensitivity and accuracy. In addition, a roll-up of all expected random and systematic uncertainties in setting the key ignition laser and target parameters due to residual measurement, calibration, cross-coupling, surrogacy, and scale-up errors has been derived that meets the required budget.« less

Role of turbulence fluctuations on uncertainties of acoutic Doppler current profiler discharge measurements

USGS Publications Warehouse

Tarrab, Leticia; Garcia, Carlos M.; Cantero, Mariano I.; Oberg, Kevin

2012-01-01

This work presents a systematic analysis quantifying the role of the presence of turbulence fluctuations on uncertainties (random errors) of acoustic Doppler current profiler (ADCP) discharge measurements from moving platforms. Data sets of three-dimensional flow velocities with high temporal and spatial resolution were generated from direct numerical simulation (DNS) of turbulent open channel flow. Dimensionless functions relating parameters quantifying the uncertainty in discharge measurements due to flow turbulence (relative variance and relative maximum random error) to sampling configuration were developed from the DNS simulations and then validated with field-scale discharge measurements. The validated functions were used to evaluate the role of the presence of flow turbulence fluctuations on uncertainties in ADCP discharge measurements. The results of this work indicate that random errors due to the flow turbulence are significant when: (a) a low number of transects is used for a discharge measurement, and (b) measurements are made in shallow rivers using high boat velocity (short time for the boat to cross a flow turbulence structure).

A unified development of several techniques for the representation of random vectors and data sets

NASA Technical Reports Server (NTRS)

Bundick, W. T.

1973-01-01

Linear vector space theory is used to develop a general representation of a set of data vectors or random vectors by linear combinations of orthonormal vectors such that the mean squared error of the representation is minimized. The orthonormal vectors are shown to be the eigenvectors of an operator. The general representation is applied to several specific problems involving the use of the Karhunen-Loeve expansion, principal component analysis, and empirical orthogonal functions; and the common properties of these representations are developed.

Randomly correcting model errors in the ARPEGE-Climate v6.1 component of CNRM-CM: applications for seasonal forecasts

NASA Astrophysics Data System (ADS)

Batté, Lauriane; Déqué, Michel

2016-06-01

Stochastic methods are increasingly used in global coupled model climate forecasting systems to account for model uncertainties. In this paper, we describe in more detail the stochastic dynamics technique introduced by Batté and Déqué (2012) in the ARPEGE-Climate atmospheric model. We present new results with an updated version of CNRM-CM using ARPEGE-Climate v6.1, and show that the technique can be used both as a means of analyzing model error statistics and accounting for model inadequacies in a seasonal forecasting framework.The perturbations are designed as corrections of model drift errors estimated from a preliminary weakly nudged re-forecast run over an extended reference period of 34 boreal winter seasons. A detailed statistical analysis of these corrections is provided, and shows that they are mainly made of intra-month variance, thereby justifying their use as in-run perturbations of the model in seasonal forecasts. However, the interannual and systematic error correction terms cannot be neglected. Time correlation of the errors is limited, but some consistency is found between the errors of up to 3 consecutive days.These findings encourage us to test several settings of the random draws of perturbations in seasonal forecast mode. Perturbations are drawn randomly but consistently for all three prognostic variables perturbed. We explore the impact of using monthly mean perturbations throughout a given forecast month in a first ensemble re-forecast (SMM, for stochastic monthly means), and test the use of 5-day sequences of perturbations in a second ensemble re-forecast (S5D, for stochastic 5-day sequences). Both experiments are compared in the light of a REF reference ensemble with initial perturbations only. Results in terms of forecast quality are contrasted depending on the region and variable of interest, but very few areas exhibit a clear degradation of forecasting skill with the introduction of stochastic dynamics. We highlight some positive impacts of the method, mainly on Northern Hemisphere extra-tropics. The 500 hPa geopotential height bias is reduced, and improvements project onto the representation of North Atlantic weather regimes. A modest impact on ensemble spread is found over most regions, which suggests that this method could be complemented by other stochastic perturbation techniques in seasonal forecasting mode.

On the accuracy and precision of numerical waveforms: effect of waveform extraction methodology

NASA Astrophysics Data System (ADS)

Chu, Tony; Fong, Heather; Kumar, Prayush; Pfeiffer, Harald P.; Boyle, Michael; Hemberger, Daniel A.; Kidder, Lawrence E.; Scheel, Mark A.; Szilagyi, Bela

2016-08-01

We present a new set of 95 numerical relativity simulations of non-precessing binary black holes (BBHs). The simulations sample comprehensively both black-hole spins up to spin magnitude of 0.9, and cover mass ratios 1-3. The simulations cover on average 24 inspiral orbits, plus merger and ringdown, with low initial orbital eccentricities e\\lt {10}-4. A subset of the simulations extends the coverage of non-spinning BBHs up to mass ratio q = 10. Gravitational waveforms at asymptotic infinity are computed with two independent techniques: extrapolation and Cauchy characteristic extraction. An error analysis based on noise-weighted inner products is performed. We find that numerical truncation error, error due to gravitational wave extraction, and errors due to the Fourier transformation of signals with finite length of the numerical waveforms are of similar magnitude, with gravitational wave extraction errors dominating at noise-weighted mismatches of ˜ 3× {10}-4. This set of waveforms will serve to validate and improve aligned-spin waveform models for gravitational wave science.

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part 1; Method and Uncertainties

NASA Technical Reports Server (NTRS)

Olson, William S.; Kummerow, Christian D.; Yang, Song; Petty, Grant W.; Tao, Wei-Kuo; Bell, Thomas L.; Braun, Scott A.; Wang, Yansen; Lang, Stephen E.; Johnson, Daniel E.

2004-01-01

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating/drying profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and non-convective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud resolving model simulations, and from the Bayesian formulation itself. Synthetic rain rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in instantaneous rain rate estimates at 0.5 deg resolution range from approximately 50% at 1 mm/h to 20% at 14 mm/h. These errors represent about 70-90% of the mean random deviation between collocated passive microwave and spaceborne radar rain rate estimates. The cumulative algorithm error in TMI estimates at monthly, 2.5 deg resolution is relatively small (less than 6% at 5 mm/day) compared to the random error due to infrequent satellite temporal sampling (8-35% at the same rain rate).

Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part I: Effects of Random Error

NASA Technical Reports Server (NTRS)

Duda, David P.; Minnis, Patrick

2009-01-01

Straightforward application of the Schmidt-Appleman contrail formation criteria to diagnose persistent contrail occurrence from numerical weather prediction data is hindered by significant bias errors in the upper tropospheric humidity. Logistic models of contrail occurrence have been proposed to overcome this problem, but basic questions remain about how random measurement error may affect their accuracy. A set of 5000 synthetic contrail observations is created to study the effects of random error in these probabilistic models. The simulated observations are based on distributions of temperature, humidity, and vertical velocity derived from Advanced Regional Prediction System (ARPS) weather analyses. The logistic models created from the simulated observations were evaluated using two common statistical measures of model accuracy, the percent correct (PC) and the Hanssen-Kuipers discriminant (HKD). To convert the probabilistic results of the logistic models into a dichotomous yes/no choice suitable for the statistical measures, two critical probability thresholds are considered. The HKD scores are higher when the climatological frequency of contrail occurrence is used as the critical threshold, while the PC scores are higher when the critical probability threshold is 0.5. For both thresholds, typical random errors in temperature, relative humidity, and vertical velocity are found to be small enough to allow for accurate logistic models of contrail occurrence. The accuracy of the models developed from synthetic data is over 85 percent for both the prediction of contrail occurrence and non-occurrence, although in practice, larger errors would be anticipated.

Performance of correlation receivers in the presence of impulse noise.

NASA Technical Reports Server (NTRS)

Moore, J. D.; Houts, R. C.

1972-01-01

An impulse noise model, which assumes that each noise burst contains a randomly weighted version of a basic waveform, is used to derive the performance equations for a correlation receiver. The expected number of bit errors per noise burst is expressed as a function of the average signal energy, signal-set correlation coefficient, bit time, noise-weighting-factor variance and probability density function, and a time range function which depends on the crosscorrelation of the signal-set basis functions and the noise waveform. Unlike the performance results for additive white Gaussian noise, it is shown that the error performance for impulse noise is affected by the choice of signal-set basis function, and that Orthogonal signaling is not equivalent to On-Off signaling with the same average energy. Furthermore, it is demonstrated that the correlation-receiver error performance can be improved by inserting a properly specified nonlinear device prior to the receiver input.

Auditing the Assignments of Top-Level Semantic Types in the UMLS Semantic Network to UMLS Concepts

PubMed Central

He, Zhe; Perl, Yehoshua; Elhanan, Gai; Chen, Yan; Geller, James; Bian, Jiang

2018-01-01

The Unified Medical Language System (UMLS) is an important terminological system. By the policy of its curators, each concept of the UMLS should be assigned the most specific Semantic Types (STs) in the UMLS Semantic Network (SN). Hence, the Semantic Types of most UMLS concepts are assigned at or near the bottom (leaves) of the UMLS Semantic Network. While most ST assignments are correct, some errors do occur. Therefore, Quality Assurance efforts of UMLS curators for ST assignments should concentrate on automatically detected sets of UMLS concepts with higher error rates than random sets. In this paper, we investigate the assignments of top-level semantic types in the UMLS semantic network to concepts, identify potential erroneous assignments, define four categories of errors, and thus provide assistance to curators of the UMLS to avoid these assignments errors. Human experts analyzed samples of concepts assigned 10 of the top-level semantic types and categorized the erroneous ST assignments into these four logical categories. Two thirds of the concepts assigned these 10 top-level semantic types are erroneous. Our results demonstrate that reviewing top-level semantic type assignments to concepts provides an effective way for UMLS quality assurance, comparing to reviewing a random selection of semantic type assignments. PMID:29375930

Auditing the Assignments of Top-Level Semantic Types in the UMLS Semantic Network to UMLS Concepts.

PubMed

He, Zhe; Perl, Yehoshua; Elhanan, Gai; Chen, Yan; Geller, James; Bian, Jiang

2017-11-01

The Unified Medical Language System (UMLS) is an important terminological system. By the policy of its curators, each concept of the UMLS should be assigned the most specific Semantic Types (STs) in the UMLS Semantic Network (SN). Hence, the Semantic Types of most UMLS concepts are assigned at or near the bottom (leaves) of the UMLS Semantic Network. While most ST assignments are correct, some errors do occur. Therefore, Quality Assurance efforts of UMLS curators for ST assignments should concentrate on automatically detected sets of UMLS concepts with higher error rates than random sets. In this paper, we investigate the assignments of top-level semantic types in the UMLS semantic network to concepts, identify potential erroneous assignments, define four categories of errors, and thus provide assistance to curators of the UMLS to avoid these assignments errors. Human experts analyzed samples of concepts assigned 10 of the top-level semantic types and categorized the erroneous ST assignments into these four logical categories. Two thirds of the concepts assigned these 10 top-level semantic types are erroneous. Our results demonstrate that reviewing top-level semantic type assignments to concepts provides an effective way for UMLS quality assurance, comparing to reviewing a random selection of semantic type assignments.

Second Chance: If at First You Do Not Succeed, Set up a Plan and Try, Try Again

ERIC Educational Resources Information Center

Poulsen, John

2012-01-01

Student teachers make errors in their practicum. Then, they learn and fix those errors. This is the standard arc within a successful practicum. Some students make errors that they do not fix and then make more errors that again remain unfixed. This downward spiral increases in pace until the classroom becomes chaos. These students at the…

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part 1; Improved Method and Uncertainties

NASA Technical Reports Server (NTRS)

Olson, William S.; Kummerow, Christian D.; Yang, Song; Petty, Grant W.; Tao, Wei-Kuo; Bell, Thomas L.; Braun, Scott A.; Wang, Yansen; Lang, Stephen E.; Johnson, Daniel E.;

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.

PubMed

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-12-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.

PubMed

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-09-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules

NASA Astrophysics Data System (ADS)

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-12-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules

NASA Astrophysics Data System (ADS)

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-09-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

The use of a virtual reality simulator to explore and understand the impact of Linac mis-calibrations

NASA Astrophysics Data System (ADS)

Beavis, Andrew W.; Ward, James W.

2014-03-01

Purpose: In recent years there has been interest in using Computer Simulation within Medical training. The VERT (Virtual Environment for Radiotherapy Training) system is a Flight Simulator for Radiation Oncology professionals, wherein fundamental concepts, techniques and problematic scenarios can be safely investigated. Methods: The system provides detailed simulations of several Linacs and the ability to display DICOM treatment plans. Patients can be mis-positioned with 'set-up errors' which can be explored visually, dosimetrically and using IGRT. Similarly, a variety of Linac calibration and configuration parameters can be altered manually or randomly via controlled errors in the simulated 3D Linac and its component parts. The implication of these can be investigated by following through a treatment scenario or using QC devices available within a Physics software module. Results: One resultant exercise is a systematic mis-calibration of 'lateral laser height' by 2mm. The offset in patient alignment is easily identified using IGRT and once corrected by reference to the 'in-room monitor'. The dosimetric implication is demonstrated to be 0.4% by setting a dosimetry phantom by the lasers (and ignoring TSD information). Finally, the need for recalibration can be shown by the Laser Alignment Phantom or by reference to the front pointer. Conclusions: The VERT system provides a realistic environment for training and enhancing understanding of radiotherapy concepts and techniques. Linac error conditions can be explored in this context and valuable experience gained in a controlled manner in a compressed period of time.

Reference List Accuracy in Social Work Journals: A Follow-Up Analysis

ERIC Educational Resources Information Center

Mitchell-Williams, Missy T.; Skipper, Antonius D.; Alexander, Marvin C.; Wilks, Scott E.

2017-01-01

Purpose: Following up an "Research on Social Work Practice" article published a decade ago, this study aimed to examine reference error rates among five, widely circulated social work journals. Methods: A stratified random sample of references was selected from the year 2013 (N = 500, 100/journal). Each was verified against the original…

Effects of Systematic and Random Errors on the Retrieval of Particle Microphysical Properties from Multiwavelength Lidar Measurements Using Inversion with Regularization

NASA Technical Reports Server (NTRS)

Ramirez, Daniel Perez; Whiteman, David N.; Veselovskii, Igor; Kolgotin, Alexei; Korenskiy, Michael; Alados-Arboledas, Lucas

2013-01-01

In this work we study the effects of systematic and random errors on the inversion of multiwavelength (MW) lidar data using the well-known regularization technique to obtain vertically resolved aerosol microphysical properties. The software implementation used here was developed at the Physics Instrumentation Center (PIC) in Troitsk (Russia) in conjunction with the NASA/Goddard Space Flight Center. Its applicability to Raman lidar systems based on backscattering measurements at three wavelengths (355, 532 and 1064 nm) and extinction measurements at two wavelengths (355 and 532 nm) has been demonstrated widely. The systematic error sensitivity is quantified by first determining the retrieved parameters for a given set of optical input data consistent with three different sets of aerosol physical parameters. Then each optical input is perturbed by varying amounts and the inversion is repeated. Using bimodal aerosol size distributions, we find a generally linear dependence of the retrieved errors in the microphysical properties on the induced systematic errors in the optical data. For the retrievals of effective radius, number/surface/volume concentrations and fine-mode radius and volume, we find that these results are not significantly affected by the range of the constraints used in inversions. But significant sensitivity was found to the allowed range of the imaginary part of the particle refractive index. Our results also indicate that there exists an additive property for the deviations induced by the biases present in the individual optical data. This property permits the results here to be used to predict deviations in retrieved parameters when multiple input optical data are biased simultaneously as well as to study the influence of random errors on the retrievals. The above results are applied to questions regarding lidar design, in particular for the spaceborne multiwavelength lidar under consideration for the upcoming ACE mission.

How well does multiple OCR error correction generalize?

NASA Astrophysics Data System (ADS)

Lund, William B.; Ringger, Eric K.; Walker, Daniel D.

2013-12-01

As the digitization of historical documents, such as newspapers, becomes more common, the need of the archive patron for accurate digital text from those documents increases. Building on our earlier work, the contributions of this paper are: 1. in demonstrating the applicability of novel methods for correcting optical character recognition (OCR) on disparate data sets, including a new synthetic training set, 2. enhancing the correction algorithm with novel features, and 3. assessing the data requirements of the correction learning method. First, we correct errors using conditional random fields (CRF) trained on synthetic training data sets in order to demonstrate the applicability of the methodology to unrelated test sets. Second, we show the strength of lexical features from the training sets on two unrelated test sets, yielding a relative reduction in word error rate on the test sets of 6.52%. New features capture the recurrence of hypothesis tokens and yield an additional relative reduction in WER of 2.30%. Further, we show that only 2.0% of the full training corpus of over 500,000 feature cases is needed to achieve correction results comparable to those using the entire training corpus, effectively reducing both the complexity of the training process and the learned correction model.

Stochastic characterization of phase detection algorithms in phase-shifting interferometry

DOE PAGES

Munteanu, Florin

2016-11-01

Phase-shifting interferometry (PSI) is the preferred non-contact method for profiling sub-nanometer surfaces. Based on monochromatic light interference, the method computes the surface profile from a set of interferograms collected at separate stepping positions. Errors in the estimated profile are introduced when these positions are not located correctly. In order to cope with this problem, various algorithms that minimize the effects of certain types of stepping errors (linear, sinusoidal, etc.) have been developed. Despite the relatively large number of algorithms suggested in the literature, there is no unified way of characterizing their performance when additional unaccounted random errors are present. Here,more » we suggest a procedure for quantifying the expected behavior of each algorithm in the presence of independent and identically distributed (i.i.d.) random stepping errors, which can occur in addition to the systematic errors for which the algorithm has been designed. As a result, the usefulness of this method derives from the fact that it can guide the selection of the best algorithm for specific measurement situations.« less

A Comparison of Fuzzy Models in Similarity Assessment of Misregistered Area Class Maps

NASA Astrophysics Data System (ADS)

Brown, Scott

Spatial uncertainty refers to unknown error and vagueness in geographic data. It is relevant to land change and urban growth modelers, soil and biome scientists, geological surveyors and others, who must assess thematic maps for similarity, or categorical agreement. In this paper I build upon prior map comparison research, testing the effectiveness of similarity measures on misregistered data. Though several methods compare uncertain thematic maps, few methods have been tested on misregistration. My objective is to test five map comparison methods for sensitivity to misregistration, including sub-pixel errors in both position and rotation. Methods included four fuzzy categorical models: fuzzy kappa's model, fuzzy inference, cell aggregation, and the epsilon band. The fifth method used conventional crisp classification. I applied these methods to a case study map and simulated data in two sets: a test set with misregistration error, and a control set with equivalent uniform random error. For all five methods, I used raw accuracy or the kappa statistic to measure similarity. Rough-set epsilon bands report the most similarity increase in test maps relative to control data. Conversely, the fuzzy inference model reports a decrease in test map similarity.

An automatic microseismic or acoustic emission arrival identification scheme with deep recurrent neural networks

NASA Astrophysics Data System (ADS)

Zheng, Jing; Lu, Jiren; Peng, Suping; Jiang, Tianqi

2018-02-01

The conventional arrival pick-up algorithms cannot avoid the manual modification of the parameters for the simultaneous identification of multiple events under different signal-to-noise ratios (SNRs). Therefore, in order to automatically obtain the arrivals of multiple events with high precision under different SNRs, in this study an algorithm was proposed which had the ability to pick up the arrival of microseismic or acoustic emission events based on deep recurrent neural networks. The arrival identification was performed using two important steps, which included a training phase and a testing phase. The training process was mathematically modelled by deep recurrent neural networks using Long Short-Term Memory architecture. During the testing phase, the learned weights were utilized to identify the arrivals through the microseismic/acoustic emission data sets. The data sets were obtained by rock physics experiments of the acoustic emission. In order to obtain the data sets under different SNRs, this study added random noise to the raw experiments' data sets. The results showed that the outcome of the proposed method was able to attain an above 80 per cent hit-rate at SNR 0 dB, and an approximately 70 per cent hit-rate at SNR -5 dB, with an absolute error in 10 sampling points. These results indicated that the proposed method had high selection precision and robustness.

Eddy-covariance data with low signal-to-noise ratio: time-lag determination, uncertainties and limit of detection

NASA Astrophysics Data System (ADS)

Langford, B.; Acton, W.; Ammann, C.; Valach, A.; Nemitz, E.

2015-10-01

All eddy-covariance flux measurements are associated with random uncertainties which are a combination of sampling error due to natural variability in turbulence and sensor noise. The former is the principal error for systems where the signal-to-noise ratio of the analyser is high, as is usually the case when measuring fluxes of heat, CO2 or H2O. Where signal is limited, which is often the case for measurements of other trace gases and aerosols, instrument uncertainties dominate. Here, we are applying a consistent approach based on auto- and cross-covariance functions to quantify the total random flux error and the random error due to instrument noise separately. As with previous approaches, the random error quantification assumes that the time lag between wind and concentration measurement is known. However, if combined with commonly used automated methods that identify the individual time lag by looking for the maximum in the cross-covariance function of the two entities, analyser noise additionally leads to a systematic bias in the fluxes. Combining data sets from several analysers and using simulations, we show that the method of time-lag determination becomes increasingly important as the magnitude of the instrument error approaches that of the sampling error. The flux bias can be particularly significant for disjunct data, whereas using a prescribed time lag eliminates these effects (provided the time lag does not fluctuate unduly over time). We also demonstrate that when sampling at higher elevations, where low frequency turbulence dominates and covariance peaks are broader, both the probability and magnitude of bias are magnified. We show that the statistical significance of noisy flux data can be increased (limit of detection can be decreased) by appropriate averaging of individual fluxes, but only if systematic biases are avoided by using a prescribed time lag. Finally, we make recommendations for the analysis and reporting of data with low signal-to-noise and their associated errors.

On the Estimation of Errors in Sparse Bathymetric Geophysical Data Sets

NASA Astrophysics Data System (ADS)

Jakobsson, M.; Calder, B.; Mayer, L.; Armstrong, A.

2001-05-01

There is a growing demand in the geophysical community for better regional representations of the world ocean's bathymetry. However, given the vastness of the oceans and the relative limited coverage of even the most modern mapping systems, it is likely that many of the older data sets will remain part of our cumulative database for several more decades. Therefore, regional bathymetrical compilations that are based on a mixture of historic and contemporary data sets will have to remain the standard. This raises the problem of assembling bathymetric compilations and utilizing data sets not only with a heterogeneous cover but also with a wide range of accuracies. In combining these data to regularly spaced grids of bathymetric values, which the majority of numerical procedures in earth sciences require, we are often forced to use a complex interpolation scheme due to the sparseness and irregularity of the input data points. Consequently, we are faced with the difficult task of assessing the confidence that we can assign to the final grid product, a task that is not usually addressed in most bathymetric compilations. We approach the problem of assessing the confidence via a direct-simulation Monte Carlo method. We start with a small subset of data from the International Bathymetric Chart of the Arctic Ocean (IBCAO) grid model [Jakobsson et al., 2000]. This grid is compiled from a mixture of data sources ranging from single beam soundings with available metadata to spot soundings with no available metadata, to digitized contours; the test dataset shows examples of all of these types. From this database, we assign a priori error variances based on available meta-data, and when this is not available, based on a worst-case scenario in an essentially heuristic manner. We then generate a number of synthetic datasets by randomly perturbing the base data using normally distributed random variates, scaled according to the predicted error model. These datasets are then re-gridded using the same methodology as the original product, generating a set of plausible grid models of the regional bathymetry that we can use for standard error estimates. Finally, we repeat the entire random estimation process and analyze each run's standard error grids in order to examine sampling bias and variance in the predictions. The final products of the estimation are a collection of standard error grids, which we combine with the source data density in order to create a grid that contains information about the bathymetry model's reliability. Jakobsson, M., Cherkis, N., Woodward, J., Coakley, B., and Macnab, R., 2000, A new grid of Arctic bathymetry: A significant resource for scientists and mapmakers, EOS Transactions, American Geophysical Union, v. 81, no. 9, p. 89, 93, 96.

A Randomized Controlled Trial Translating the Diabetes Prevention Program to a University Worksite, Ohio, 2012–2014

PubMed Central

Weinhold, Kellie R.; Marrero, David G.; Nagaraja, Haikady N.; Focht, Brian C.; Gascon, Gregg M.

2015-01-01

Introduction Working adults spend much time at the workplace, an ideal setting for wellness programs targeting weight loss and disease prevention. Few randomized trials have evaluated the efficacy of worksite diabetes prevention programs.This study evaluated the efficacy of a worksite lifestyle intervention on metabolic and behavioral risk factors compared with usual care. Methods A pretest–posttest control group design with 3-month follow-up was used. Participants with prediabetes were recruited from a university worksite and randomized to receive a 16-week lifestyle intervention (n = 35) or usual care (n = 34). Participants were evaluated at baseline, postintervention, and 3-month follow-up. Dietary intake was measured by a food frequency questionnaire and level of physical activity by accelerometers. Repeated measures analysis of variance compared the change in outcomes between and within groups. Results Mean (standard error [SE]) weight loss was greater in the intervention (−5.5% [0.6%]) than in the control (−0.4% [0.5%]) group (P < .001) postintervention and was sustained at 3-month follow-up (P < .001). Mean (SE) reductions in fasting glucose were greater in the intervention (−8.6 [1.6] mg/dL) than in the control (−3.7 [1.6] mg/dL) group (P = .02) postintervention; both groups had significant glucose reductions at 3-month follow-up (P < .001). In the intervention group, the intake of total energy and the percentage of energy from all fats, saturated fats, and trans fats decreased, and the intake of dietary fiber increased (all P < .01) postintervention. Conclusion The worksite intervention improved metabolic and behavioral risk factors among employees with prediabetes. The long-term impact on diabetes prevention and program sustainability warrant further investigation. PMID:26605710

A Randomized Controlled Trial Translating the Diabetes Prevention Program to a University Worksite, Ohio, 2012-2014.

PubMed

Weinhold, Kellie R; Miller, Carla K; Marrero, David G; Nagaraja, Haikady N; Focht, Brian C; Gascon, Gregg M

2015-11-25

Working adults spend much time at the workplace, an ideal setting for wellness programs targeting weight loss and disease prevention. Few randomized trials have evaluated the efficacy of worksite diabetes prevention programs. This study evaluated the efficacy of a worksite lifestyle intervention on metabolic and behavioral risk factors compared with usual care. A pretest-posttest control group design with 3-month follow-up was used. Participants with prediabetes were recruited from a university worksite and randomized to receive a 16-week lifestyle intervention (n = 35) or usual care (n = 34). Participants were evaluated at baseline, postintervention, and 3-month follow-up. Dietary intake was measured by a food frequency questionnaire and level of physical activity by accelerometers. Repeated measures analysis of variance compared the change in outcomes between and within groups. Mean (standard error [SE]) weight loss was greater in the intervention (-5.5% [0.6%]) than in the control (-0.4% [0.5%]) group (P < .001) postintervention and was sustained at 3-month follow-up (P < .001). Mean (SE) reductions in fasting glucose were greater in the intervention (-8.6 [1.6] mg/dL) than in the control (-3.7 [1.6] mg/dL) group (P = .02) postintervention; both groups had significant glucose reductions at 3-month follow-up (P < .001). In the intervention group, the intake of total energy and the percentage of energy from all fats, saturated fats, and trans fats decreased, and the intake of dietary fiber increased (all P < .01) postintervention. The worksite intervention improved metabolic and behavioral risk factors among employees with prediabetes. The long-term impact on diabetes prevention and program sustainability warrant further investigation.

A technique for reducing patient setup uncertainties by aligning and verifying daily positioning of a moving tumor using implanted fiducials

PubMed Central

Balter, Peter; Morice, Rodolfo C.; Choi, Bum; Kudchadker, Rajat J.; Bucci, Kara; Chang, Joe Y.; Dong, Lei; Tucker, Susan; Vedam, Sastry; Briere, Tina; Starkschall, George

2008-01-01

This study aimed to validate and implement a methodology in which fiducials implanted in the periphery of lung tumors can be used to reduce uncertainties in tumor location. Alignment software that matches marker positions on two‐dimensional (2D) kilovoltage portal images to positions on three‐dimensional (3D) computed tomography data sets was validated using static and moving phantoms. This software also was used to reduce uncertainties in tumor location in a patient with fiducials implanted in the periphery of a lung tumor. Alignment of fiducial locations in orthogonal projection images with corresponding fiducial locations in 3D data sets can position both static and moving phantoms with an accuracy of 1 mm. In a patient, alignment based on fiducial locations reduced systematic errors in the left–right direction by 3 mm and random errors by 2 mm, and random errors in the superior–inferior direction by 3 mm as measured by anterior–posterior cine images. Software that matches fiducial markers on 2D and 3D images is effective for aligning both static and moving fiducials before treatment and can be implemented to reduce patient setup uncertainties. PACS number: 81.40.Wx

Quantifying Errors in TRMM-Based Multi-Sensor QPE Products Over Land in Preparation for GPM

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.; Tian, Yudong

2011-01-01

Determining uncertainties in satellite-based multi-sensor quantitative precipitation estimates over land of fundamental importance to both data producers and hydro climatological applications. ,Evaluating TRMM-era products also lays the groundwork and sets the direction for algorithm and applications development for future missions including GPM. QPE uncertainties result mostly from the interplay of systematic errors and random errors. In this work, we will synthesize our recent results quantifying the error characteristics of satellite-based precipitation estimates. Both systematic errors and total uncertainties have been analyzed for six different TRMM-era precipitation products (3B42, 3B42RT, CMORPH, PERSIANN, NRL and GSMap). For systematic errors, we devised an error decomposition scheme to separate errors in precipitation estimates into three independent components, hit biases, missed precipitation and false precipitation. This decomposition scheme reveals hydroclimatologically-relevant error features and provides a better link to the error sources than conventional analysis, because in the latter these error components tend to cancel one another when aggregated or averaged in space or time. For the random errors, we calculated the measurement spread from the ensemble of these six quasi-independent products, and thus produced a global map of measurement uncertainties. The map yields a global view of the error characteristics and their regional and seasonal variations, reveals many undocumented error features over areas with no validation data available, and provides better guidance to global assimilation of satellite-based precipitation data. Insights gained from these results and how they could help with GPM will be highlighted.

Generating moment matching scenarios using optimization techniques

DOE PAGES

Mehrotra, Sanjay; Papp, Dávid

2013-05-16

An optimization based method is proposed to generate moment matching scenarios for numerical integration and its use in stochastic programming. The main advantage of the method is its flexibility: it can generate scenarios matching any prescribed set of moments of the underlying distribution rather than matching all moments up to a certain order, and the distribution can be defined over an arbitrary set. This allows for a reduction in the number of scenarios and allows the scenarios to be better tailored to the problem at hand. The method is based on a semi-infinite linear programming formulation of the problem thatmore » is shown to be solvable with polynomial iteration complexity. A practical column generation method is implemented. The column generation subproblems are polynomial optimization problems; however, they need not be solved to optimality. It is found that the columns in the column generation approach can be efficiently generated by random sampling. The number of scenarios generated matches a lower bound of Tchakaloff's. The rate of convergence of the approximation error is established for continuous integrands, and an improved bound is given for smooth integrands. Extensive numerical experiments are presented in which variants of the proposed method are compared to Monte Carlo and quasi-Monte Carlo methods on both numerical integration problems and stochastic optimization problems. The benefits of being able to match any prescribed set of moments, rather than all moments up to a certain order, is also demonstrated using optimization problems with 100-dimensional random vectors. Here, empirical results show that the proposed approach outperforms Monte Carlo and quasi-Monte Carlo based approaches on the tested problems.« less

Optical digital to analog conversion performance analysis for indoor set-up conditions

NASA Astrophysics Data System (ADS)

Dobesch, Aleš; Alves, Luis Nero; Wilfert, Otakar; Ribeiro, Carlos Gaspar

2017-10-01

In visible light communication (VLC) the optical digital to analog conversion (ODAC) approach was proposed as a suitable driving technique able to overcome light-emitting diode's (LED) non-linear characteristic. This concept is analogous to an electrical digital-to-analog converter (EDAC). In other words, digital bits are binary weighted to represent an analog signal. The method supports elementary on-off based modulations able to exploit the essence of LED's non-linear characteristic allowing simultaneous lighting and communication. In the ODAC concept the reconstruction error does not simply rely upon the converter bit depth as in case of EDAC. It rather depends on communication system set-up and geometrical relation between emitter and receiver as well. The paper describes simulation results presenting the ODAC's error performance taking into account: the optical channel, the LED's half power angle (HPA) and the receiver field of view (FOV). The set-up under consideration examines indoor conditions for a square room with 4 m length and 3 m height, operating with one dominant wavelength (blue) and having walls with a reflection coefficient of 0.8. The achieved results reveal that reconstruction error increases for higher data rates as a result of interference due to multipath propagation.

Two-dimensional confocal laser scanning microscopy image correlation for nanoparticle flow velocimetry

NASA Astrophysics Data System (ADS)

Jun, Brian; Giarra, Matthew; Golz, Brian; Main, Russell; Vlachos, Pavlos

2016-11-01

We present a methodology to mitigate the major sources of error associated with two-dimensional confocal laser scanning microscopy (CLSM) images of nanoparticles flowing through a microfluidic channel. The correlation-based velocity measurements from CLSM images are subject to random error due to the Brownian motion of nanometer-sized tracer particles, and a bias error due to the formation of images by raster scanning. Here, we develop a novel ensemble phase correlation with dynamic optimal filter that maximizes the correlation strength, which diminishes the random error. In addition, we introduce an analytical model of CLSM measurement bias error correction due to two-dimensional image scanning of tracer particles. We tested our technique using both synthetic and experimental images of nanoparticles flowing through a microfluidic channel. We observed that our technique reduced the error by up to a factor of ten compared to ensemble standard cross correlation (SCC) for the images tested in the present work. Subsequently, we will assess our framework further, by interrogating nanoscale flow in the cell culture environment (transport within the lacunar-canalicular system) to demonstrate our ability to accurately resolve flow measurements in a biological system.

Weighting by Inverse Variance or by Sample Size in Random-Effects Meta-Analysis

ERIC Educational Resources Information Center

Marin-Martinez, Fulgencio; Sanchez-Meca, Julio

2010-01-01

Most of the statistical procedures in meta-analysis are based on the estimation of average effect sizes from a set of primary studies. The optimal weight for averaging a set of independent effect sizes is the inverse variance of each effect size, but in practice these weights have to be estimated, being affected by sampling error. When assuming a…

Highly correlated configuration interaction calculations on water with large orbital bases

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

Almora-Díaz, César X., E-mail: xalmora@fisica.unam.mx

2014-05-14

A priori selected configuration interaction (SCI) with truncation energy error [C. F. Bunge, J. Chem. Phys. 125, 014107 (2006)] and CI by parts [C. F. Bunge and R. Carbó-Dorca, J. Chem. Phys. 125, 014108 (2006)] are used to approximate the total nonrelativistic electronic ground state energy of water at fixed experimental geometry with CI up to sextuple excitations. Correlation-consistent polarized core-valence basis sets (cc-pCVnZ) up to sextuple zeta and augmented correlation-consistent polarized core-valence basis sets (aug-cc-pCVnZ) up to quintuple zeta quality are employed. Truncation energy errors range between less than 1 μhartree, and 100 μhartree for the largest orbital set. Coupledmore » cluster CCSD and CCSD(T) calculations are also obtained for comparison. Our best upper bound, −76.4343 hartree, obtained by SCI with up to sextuple excitations with a cc-pCV6Z basis recovers more than 98.8% of the correlation energy of the system, and it is only about 3 kcal/mol above the “experimental” value. Despite that the present energy upper bounds are far below all previous ones, comparatively large dispersion errors in the determination of the extrapolated energies to the complete basis set do not allow to determine a reliable estimation of the full CI energy with an accuracy better than 0.6 mhartree (0.4 kcal/mol)« less

Tolerance analysis of optical telescopes using coherent addition of wavefront errors

NASA Technical Reports Server (NTRS)

Davenport, J. W.

1982-01-01

A near diffraction-limited telescope requires that tolerance analysis be done on the basis of system wavefront error. One method of analyzing the wavefront error is to represent the wavefront error function in terms of its Zernike polynomial expansion. A Ramsey-Korsch ray trace package, a computer program that simulates the tracing of rays through an optical telescope system, was expanded to include the Zernike polynomial expansion up through the fifth-order spherical term. An option to determine a 3 dimensional plot of the wavefront error function was also included in the Ramsey-Korsch package. Several assimulation runs were analyzed to determine the particular set of coefficients in the Zernike expansion that are effected by various errors such as tilt, decenter and despace. A 3 dimensional plot of each error up through the fifth-order spherical term was also included in the study. Tolerance analysis data are presented.

Human factors analysis for a 2D enroute moving map application

NASA Astrophysics Data System (ADS)

Pschierer, Christian; Wipplinger, Patrick; Schiefele, Jens; Cromer, Scot; Laurin, John; Haffner, Skip

2005-05-01

The paper describes flight trials performed in Centennial, CO with a Piper Cheyenne from Marinvent. Six pilots flew the Cheyenne in twelve enroute segments between Denver Centennial and Colorado Springs. Two different settings (paper chart, enroute moving map) were evaluated with randomized settings. The flight trial goal was to evaluate the objective performance of pilots compared among the different settings. As dependent variables, positional accuracy and situational awareness probe (SAP) were measured. Analysis was conducted by an ANOVA test. In parallel, all pilots answered subjective Cooper-Harper, NASA TLX, situation awareness rating technique (SART), Display Readability Rating and debriefing questionnaires. The tested enroute moving map application has Jeppesen chart compliant symbologies for high-enroute and low-enroute. It has a briefing mode were all information found on today"s enroute paper chart together with a loaded flight plan are displayed in a north-up orientation. The execution mode displays a loaded flight plan routing together with only pertinent flight route relevant information in either a track up or north up orientation. Depiction of an own ship symbol is possible in both modes. All text and symbols are deconflicted. Additional information can be obtained by clicking on symbols. Terrain and obstacle data can be displayed for enhanced situation awareness. The result shows that pilots flying the 2D enroute moving map display perform no worse than pilots with conventional systems. Flight technical error and workload are equivalent or lower, situational awareness is higher than on conventional paper charts.

Quantum Steering Inequality with Tolerance for Measurement-Setting Errors: Experimentally Feasible Signature of Unbounded Violation

NASA Astrophysics Data System (ADS)

Rutkowski, Adam; Buraczewski, Adam; Horodecki, Paweł; Stobińska, Magdalena

2017-01-01

Quantum steering is a relatively simple test for proving that the values of quantum-mechanical measurement outcomes come into being only in the act of measurement. By exploiting quantum correlations, Alice can influence—steer—Bob's physical system in a way that is impossible in classical mechanics, as shown by the violation of steering inequalities. Demonstrating this and similar quantum effects for systems of increasing size, approaching even the classical limit, is a long-standing challenging problem. Here, we prove an experimentally feasible unbounded violation of a steering inequality. We derive its universal form where tolerance for measurement-setting errors is explicitly built in by means of the Deutsch-Maassen-Uffink entropic uncertainty relation. Then, generalizing the mutual unbiasedness, we apply the inequality to the multisinglet and multiparticle bipartite Bell state. However, the method is general and opens the possibility of employing multiparticle bipartite steering for randomness certification and development of quantum technologies, e.g., random access codes.

A general method for the definition of margin recipes depending on the treatment technique applied in helical tomotherapy prostate plans.

PubMed

Sevillano, David; Mínguez, Cristina; Sánchez, Alicia; Sánchez-Reyes, Alberto

2016-01-01

To obtain specific margin recipes that take into account the dosimetric characteristics of the treatment plans used in a single institution. We obtained dose-population histograms (DPHs) of 20 helical tomotherapy treatment plans for prostate cancer by simulating the effects of different systematic errors (Σ) and random errors (σ) on these plans. We obtained dosimetric margins and margin reductions due to random errors (random margins) by fitting the theoretical results of coverages for Gaussian distributions with coverages of the planned D99% obtained from the DPHs. The dosimetric margins obtained for helical tomotherapy prostate treatments were 3.3 mm, 3 mm, and 1 mm in the lateral (Lat), anterior-posterior (AP), and superior-inferior (SI) directions. Random margins showed parabolic dependencies, yielding expressions of 0.16σ(2), 0.13σ(2), and 0.15σ(2) for the Lat, AP, and SI directions, respectively. When focusing on values up to σ = 5 mm, random margins could be fitted considering Gaussian penumbras with standard deviations (σp) equal to 4.5 mm Lat, 6 mm AP, and 5.5 mm SI. Despite complex dose distributions in helical tomotherapy treatment plans, we were able to simplify the behaviour of our plans against treatment errors to single values of dosimetric and random margins for each direction. These margins allowed us to develop specific margin recipes for the respective treatment technique. The method is general and could be used for any treatment technique provided that DPHs can be obtained. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

A finite element-based machine learning approach for modeling the mechanical behavior of the breast tissues under compression in real-time.

PubMed

Martínez-Martínez, F; Rupérez-Moreno, M J; Martínez-Sober, M; Solves-Llorens, J A; Lorente, D; Serrano-López, A J; Martínez-Sanchis, S; Monserrat, C; Martín-Guerrero, J D

2017-11-01

This work presents a data-driven method to simulate, in real-time, the biomechanical behavior of the breast tissues in some image-guided interventions such as biopsies or radiotherapy dose delivery as well as to speed up multimodal registration algorithms. Ten real breasts were used for this work. Their deformation due to the displacement of two compression plates was simulated off-line using the finite element (FE) method. Three machine learning models were trained with the data from those simulations. Then, they were used to predict in real-time the deformation of the breast tissues during the compression. The models were a decision tree and two tree-based ensemble methods (extremely randomized trees and random forest). Two different experimental setups were designed to validate and study the performance of these models under different conditions. The mean 3D Euclidean distance between nodes predicted by the models and those extracted from the FE simulations was calculated to assess the performance of the models in the validation set. The experiments proved that extremely randomized trees performed better than the other two models. The mean error committed by the three models in the prediction of the nodal displacements was under 2 mm, a threshold usually set for clinical applications. The time needed for breast compression prediction is sufficiently short to allow its use in real-time (<0.2 s). Copyright © 2017 Elsevier Ltd. All rights reserved.

Efficient Z gates for quantum computing

NASA Astrophysics Data System (ADS)

McKay, David C.; Wood, Christopher J.; Sheldon, Sarah; Chow, Jerry M.; Gambetta, Jay M.

2017-08-01

For superconducting qubits, microwave pulses drive rotations around the Bloch sphere. The phase of these drives can be used to generate zero-duration arbitrary virtual Z gates, which, combined with two Xπ /2 gates, can generate any SU(2) gate. Here we show how to best utilize these virtual Z gates to both improve algorithms and correct pulse errors. We perform randomized benchmarking using a Clifford set of Hadamard and Z gates and show that the error per Clifford is reduced versus a set consisting of standard finite-duration X and Y gates. Z gates can correct unitary rotation errors for weakly anharmonic qubits as an alternative to pulse-shaping techniques such as derivative removal by adiabatic gate (DRAG). We investigate leakage and show that a combination of DRAG pulse shaping to minimize leakage and Z gates to correct rotation errors realizes a 13.3 ns Xπ /2 gate characterized by low error [1.95 (3 ) ×10-4] and low leakage [3.1 (6 ) ×10-6] . Ultimately leakage is limited by the finite temperature of the qubit, but this limit is two orders of magnitude smaller than pulse errors due to decoherence.

Error decomposition and estimation of inherent optical properties.

PubMed

Salama, Mhd Suhyb; Stein, Alfred

2009-09-10

We describe a methodology to quantify and separate the errors of inherent optical properties (IOPs) derived from ocean-color model inversion. Their total error is decomposed into three different sources, namely, model approximations and inversion, sensor noise, and atmospheric correction. Prior information on plausible ranges of observation, sensor noise, and inversion goodness-of-fit are employed to derive the posterior probability distribution of the IOPs. The relative contribution of each error component to the total error budget of the IOPs, all being of stochastic nature, is then quantified. The method is validated with the International Ocean Colour Coordinating Group (IOCCG) data set and the NASA bio-Optical Marine Algorithm Data set (NOMAD). The derived errors are close to the known values with correlation coefficients of 60-90% and 67-90% for IOCCG and NOMAD data sets, respectively. Model-induced errors inherent to the derived IOPs are between 10% and 57% of the total error, whereas atmospheric-induced errors are in general above 43% and up to 90% for both data sets. The proposed method is applied to synthesized and in situ measured populations of IOPs. The mean relative errors of the derived values are between 2% and 20%. A specific error table to the Medium Resolution Imaging Spectrometer (MERIS) sensor is constructed. It serves as a benchmark to evaluate the performance of the atmospheric correction method and to compute atmospheric-induced errors. Our method has a better performance and is more appropriate to estimate actual errors of ocean-color derived products than the previously suggested methods. Moreover, it is generic and can be applied to quantify the error of any derived biogeophysical parameter regardless of the used derivation.

Effects of hair, clothing, and headgear on localization of three-dimensional sounds Part IIb

NASA Astrophysics Data System (ADS)

Riederer, Klaus A. J.

2003-10-01

Seven 20-25-year-old normal hearing (<=20 dBHL) native male-undergraduates listened twice to treatments of 85 virtual source locations in a large dark anechoic chamber. The 3-D-stimuli were anew-calculated white noise bursts, amplitude modulated (40-Hz sine), repeated after a pause (total duration 3×275=825 ms), HRTF-convolved and headphone-equalized (Sennheiser HD580). The HRTFs were measured from a Cortex dummy head wearing different garments: 1=alpaca pullover only; 2=1+curly pony-tailed thick-hair+eye-glasses 3=1+long thin-hair (ear-covering) 4=1+mens trilby; 5=2+bicycle helmet+jacket [Riederer, J. Acoust. Soc. Am., this issue]. Perceived directions were signified by placing a tailored digitizer-stylus over an illuminated ball darkened after the response. Subjects did the experiments during three days, each consisting of a 2-h session of several randomized sets with multiple breaks. Azimuth and elevation errors were investigated separately in factorial within-subjects ANOVA showing strong dependence p(<=0.004) on all main effects and interactions (garment, elevation, azimuth). The grand mean errors were approximately 16°-19°. Confused angles were retained around the +/-90°-interaural axis and cos(elev)-weighting was applied to azimuth errors. The total front-back/back-front confusion rate was 18.38% and up-down/down-up 12.21%. The confusions (except left-right/right-left, 2.07%) and reaction times depended strongly on azimuth (main effect) and garment (interaction). [Work supported by Graduate School of Electronics, Telecommunication and Automation.

Bandwagon effects and error bars in particle physics

NASA Astrophysics Data System (ADS)

Jeng, Monwhea

2007-02-01

We study historical records of experiments on particle masses, lifetimes, and widths, both for signs of expectation bias, and to compare actual errors with reported error bars. We show that significant numbers of particle properties exhibit "bandwagon effects": reported values show trends and clustering as a function of the year of publication, rather than random scatter about the mean. While the total amount of clustering is significant, it is also fairly small; most individual particle properties do not display obvious clustering. When differences between experiments are compared with the reported error bars, the deviations do not follow a normal distribution, but instead follow an exponential distribution for up to ten standard deviations.

Coding for reliable satellite communications

NASA Technical Reports Server (NTRS)

Gaarder, N. T.; Lin, S.

1986-01-01

This research project was set up to study various kinds of coding techniques for error control in satellite and space communications for NASA Goddard Space Flight Center. During the project period, researchers investigated the following areas: (1) decoding of Reed-Solomon codes in terms of dual basis; (2) concatenated and cascaded error control coding schemes for satellite and space communications; (3) use of hybrid coding schemes (error correction and detection incorporated with retransmission) to improve system reliability and throughput in satellite communications; (4) good codes for simultaneous error correction and error detection, and (5) error control techniques for ring and star networks.

ATM QoS Experiments Using TCP Applications: Performance of TCP/IP Over ATM in a Variety of Errored Links

NASA Technical Reports Server (NTRS)

Frantz, Brian D.; Ivancic, William D.

2001-01-01

Asynchronous Transfer Mode (ATM) Quality of Service (QoS) experiments using the Transmission Control Protocol/Internet Protocol (TCP/IP) were performed for various link delays. The link delay was set to emulate a Wide Area Network (WAN) and a Satellite Link. The purpose of these experiments was to evaluate the ATM QoS requirements for applications that utilize advance TCP/IP protocols implemented with large windows and Selective ACKnowledgements (SACK). The effects of cell error, cell loss, and random bit errors on throughput were reported. The detailed test plan and test results are presented herein.

Quantification and characterization of leakage errors

NASA Astrophysics Data System (ADS)

Wood, Christopher J.; Gambetta, Jay M.

2018-03-01

We present a general framework for the quantification and characterization of leakage errors that result when a quantum system is encoded in the subspace of a larger system. To do this we introduce metrics for quantifying the coherent and incoherent properties of the resulting errors and we illustrate this framework with several examples relevant to superconducting qubits. In particular, we propose two quantities, the leakage and seepage rates, which together with average gate fidelity allow for characterizing the average performance of quantum gates in the presence of leakage and show how the randomized benchmarking protocol can be modified to enable the robust estimation of all three quantities for a Clifford gate set.

A General Method for Predicting Amino Acid Residues Experiencing Hydrogen Exchange

PubMed Central

Wang, Boshen; Perez-Rathke, Alan; Li, Renhao; Liang, Jie

2018-01-01

Information on protein hydrogen exchange can help delineate key regions involved in protein-protein interactions and provides important insight towards determining functional roles of genetic variants and their possible mechanisms in disease processes. Previous studies have shown that the degree of hydrogen exchange is affected by hydrogen bond formations, solvent accessibility, proximity to other residues, and experimental conditions. However, a general predictive method for identifying residues capable of hydrogen exchange transferable to a broad set of proteins is lacking. We have developed a machine learning method based on random forest that can predict whether a residue experiences hydrogen exchange. Using data from the Start2Fold database, which contains information on 13,306 residues (3,790 of which experience hydrogen exchange and 9,516 which do not exchange), our method achieves good performance. Specifically, we achieve an overall out-of-bag (OOB) error, an unbiased estimate of the test set error, of 20.3 percent. Using a randomly selected test data set consisting of 500 residues experiencing hydrogen exchange and 500 which do not, our method achieves an accuracy of 0.79, a recall of 0.74, a precision of 0.82, and an F1 score of 0.78.

Research on correction algorithm of laser positioning system based on four quadrant detector

NASA Astrophysics Data System (ADS)

Gao, Qingsong; Meng, Xiangyong; Qian, Weixian; Cai, Guixia

2018-02-01

This paper first introduces the basic principle of the four quadrant detector, and a set of laser positioning experiment system is built based on the four quadrant detector. Four quadrant laser positioning system in the actual application, not only exist interference of background light and detector dark current noise, and the influence of random noise, system stability, spot equivalent error can't be ignored, so it is very important to system calibration and correction. This paper analyzes the various factors of system positioning error, and then propose an algorithm for correcting the system error, the results of simulation and experiment show that the modified algorithm can improve the effect of system error on positioning and improve the positioning accuracy.

A preliminary taxonomy of medical errors in family practice

PubMed Central

Dovey, S; Meyers, D; Phillips, R; Green, L; Fryer, G; Galliher, J; Kappus, J; Grob, P

2002-01-01

Objective: To develop a preliminary taxonomy of primary care medical errors. Design: Qualitative analysis to identify categories of error reported during a randomized controlled trial of computer and paper reporting methods. Setting: The National Network for Family Practice and Primary Care Research. Participants: Family physicians. Main outcome measures: Medical error category, context, and consequence. Results: Forty two physicians made 344 reports: 284 (82.6%) arose from healthcare systems dysfunction; 46 (13.4%) were errors due to gaps in knowledge or skills; and 14 (4.1%) were reports of adverse events, not errors. The main subcategories were: administrative failures (102; 30.9% of errors), investigation failures (82; 24.8%), treatment delivery lapses (76; 23.0%), miscommunication (19; 5.8%), payment systems problems (4; 1.2%), error in the execution of a clinical task (19; 5.8%), wrong treatment decision (14; 4.2%), and wrong diagnosis (13; 3.9%). Most reports were of errors that were recognized and occurred in reporters' practices. Affected patients ranged in age from 8 months to 100 years, were of both sexes, and represented all major US ethnic groups. Almost half the reports were of events which had adverse consequences. Ten errors resulted in patients being admitted to hospital and one patient died. Conclusions: This medical error taxonomy, developed from self-reports of errors observed by family physicians during their routine clinical practice, emphasizes problems in healthcare processes and acknowledges medical errors arising from shortfalls in clinical knowledge and skills. Patient safety strategies with most effect in primary care settings need to be broader than the current focus on medication errors. PMID:12486987

Radiometric properties of the NS001 Thematic Mapper Simulator aircraft multispectral scanner

NASA Technical Reports Server (NTRS)

Markham, Brian L.; Ahmad, Suraiya P.

1990-01-01

Laboratory tests of the NS001 TM are described emphasizing absolute calibration to determine the radiometry of the simulator's reflective channels. In-flight calibration of the data is accomplished with the NS001 internal integrating-sphere source because instabilities in the source can limit the absolute calibration. The data from 1987-89 indicate uncertainties of up to 25 percent with an apparent average uncertainty of about 15 percent. Also identified are dark current drift and sensitivity changes along the scan line, random noise, and nonlinearity which contribute errors of 1-2 percent. Uncertainties similar to hysteresis are also noted especially in the 2.08-2.35-micron range which can reduce sensitivity and cause errors. The NS001 TM Simulator demonstrates a polarization sensitivity that can generate errors of up to about 10 percent depending on the wavelength.

The patterns of refractive errors among the school children of rural and urban settings in Nepal.

PubMed

Pokharel, A; Pokharel, P K; Das, H; Adhikari, S

2010-01-01

The uncorrected refractive error is an important cause of childhood blindness and visual impairment. To study the patterns of refractive errors among the urban and rural school going children of Nepal. A total of 440 school children of urban and rural schools within the age range of 7-15 years were selected for this study using multi-stage randomization technique. The overall prevalance of refractive error in school children was 19.8 %. The commonest refractive error among the students was myopia (59.8 %), followed by hypermetropia (31.0 %). The children of age group 12-15 years had the higher prevalence of myopia as compared to the younger counterparts (42.5 % vs 17.2 %). The prevalence of myopia was 15.5 % among the urban students as compared to 8.2 % among the rural ones (RR = 1.89, 95 % CI = 1.1-3.24). The hypermetropia was more common in urban students than in rural ones (6.4 %) vs 5.9 %, RR = 1.08 (95 % CI: 0.52-2.24). The prevalence of refractive error in the school children of Nepal is 19.8 %. The students from urban settings are more likely to have refractive error than their rural counterparts. © Nepal Ophthalmic Society.

SU-G-BRB-03: Assessing the Sensitivity and False Positive Rate of the Integrated Quality Monitor (IQM) Large Area Ion Chamber to MLC Positioning Errors

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

Boehnke, E McKenzie; DeMarco, J; Steers, J

2016-06-15

Purpose: To examine both the IQM’s sensitivity and false positive rate to varying MLC errors. By balancing these two characteristics, an optimal tolerance value can be derived. Methods: An un-modified SBRT Liver IMRT plan containing 7 fields was randomly selected as a representative clinical case. The active MLC positions for all fields were perturbed randomly from a square distribution of varying width (±1mm to ±5mm). These unmodified and modified plans were measured multiple times each by the IQM (a large area ion chamber mounted to a TrueBeam linac head). Measurements were analyzed relative to the initial, unmodified measurement. IQM readingsmore » are analyzed as a function of control points. In order to examine sensitivity to errors along a field’s delivery, each measured field was divided into 5 groups of control points, and the maximum error in each group was recorded. Since the plans have known errors, we compared how well the IQM is able to differentiate between unmodified and error plans. ROC curves and logistic regression were used to analyze this, independent of thresholds. Results: A likelihood-ratio Chi-square test showed that the IQM could significantly predict whether a plan had MLC errors, with the exception of the beginning and ending control points. Upon further examination, we determined there was ramp-up occurring at the beginning of delivery. Once the linac AFC was tuned, the subsequent measurements (relative to a new baseline) showed significant (p <0.005) abilities to predict MLC errors. Using the area under the curve, we show the IQM’s ability to detect errors increases with increasing MLC error (Spearman’s Rho=0.8056, p<0.0001). The optimal IQM count thresholds from the ROC curves are ±3%, ±2%, and ±7% for the beginning, middle 3, and end segments, respectively. Conclusion: The IQM has proven to be able to detect not only MLC errors, but also differences in beam tuning (ramp-up). Partially supported by the Susan Scott Foundation.« less

Description of a Quality Assurance Process for a Surface Wind Database in Eastern Canada

NASA Astrophysics Data System (ADS)

Lucio-Eceiza, E. E.; Gonzalez-Rouco, F. J.; Navarro, J.; Beltrami, H.; García-Bustamante, E.; Hidalgo; Jiménez, P. A.

2011-12-01

Meteorological data of good quality are important for understanding both global and regional climates. The data are subject to different types of measurement errors that can be roughly classified into three groups: random, systematic and rough errors. Random errors are unavoidable and inherent to the very nature of the measurements as instrumental responses to real physical phenomena, as they are an approximate representation of the reality. Systematic errors are produced by instrumental scale shifts and drifts or by some more or less persistent factors that are not taken into account (changes in the sensor, recalibrations or location displacements). Rough errors are associated with sensor malfunction or mismanagement arising during data processing, transmission, reception or storage. It is essential to develop procedures that allow to identify, and correct if possible, the errors in observed series, in order to improve the quality of the data sets and reach solid conclusions in the studies. This work summarizes the evaluation made to date of the quality assurance process of wind speed and direction data acquired over a wide area in Eastern Canada (including the provinces of Quebec, Prince Edward Island, New Brunswick, Nova Scotia, and Newfoundland and Labrador), a region of the adjacent maritime areas and a region of the north-eastern U.S. (Maine, New Hampshire, Massachusetts, New York and Vermont). The data set consists of 527 stations, it spans the period 1940-2009 and has been compiled from three different sources: a set of 344 land sites obtained from Environment Canada (1940-2009), a subset of 40 buoys distributed over the East Coast and the Canadian Great Lakes (1988-2008) provided by Fisheries and Oceans, and a subset of 143 land sites combining both eastern Canada and north-eastern U.S. provided by the National Center of Atmospheric Research (1975-2007). The data have been compiled and subsequently a set of quality assurance techniques have been applied to explore the detection and later treatment of errors within measurements. These techniques involve, among others, detection of manipulation errors, limit checks to avoid unrealistic records and temporal consistency checks to suppress abnormally low/high variations. There are other issues specifically related to the heterogeneous nature of this data set such as unit-conversion and changes in recording times or direction resolution over time. Ensuring the quality of wind observations is essential for the later analysis that will focus in exploring the wind field behaviour at the regional scale, with a special interest over the area of Nova Scotia. The wind behaviour will be examined attending to the specific features of the regional topography and to the influence of changes in the large scale atmospheric circulation. Subsequent steps will involve a simulation of the wind field with high spatial resolution using a mesoscale model (such as WRF) and its validation with the observational data set presented herein.

Effect of rater training on reliability and accuracy of mini-CEX scores: a randomized, controlled trial.

PubMed

Cook, David A; Dupras, Denise M; Beckman, Thomas J; Thomas, Kris G; Pankratz, V Shane

2009-01-01

Mini-CEX scores assess resident competence. Rater training might improve mini-CEX score interrater reliability, but evidence is lacking. Evaluate a rater training workshop using interrater reliability and accuracy. Randomized trial (immediate versus delayed workshop) and single-group pre/post study (randomized groups combined). Academic medical center. Fifty-two internal medicine clinic preceptors (31 randomized and 21 additional workshop attendees). The workshop included rater error training, performance dimension training, behavioral observation training, and frame of reference training using lecture, video, and facilitated discussion. Delayed group received no intervention until after posttest. Mini-CEX ratings at baseline (just before workshop for workshop group), and four weeks later using videotaped resident-patient encounters; mini-CEX ratings of live resident-patient encounters one year preceding and one year following the workshop; rater confidence using mini-CEX. Among 31 randomized participants, interrater reliabilities in the delayed group (baseline intraclass correlation coefficient [ICC] 0.43, follow-up 0.53) and workshop group (baseline 0.40, follow-up 0.43) were not significantly different (p = 0.19). Mean ratings were similar at baseline (delayed 4.9 [95% confidence interval 4.6-5.2], workshop 4.8 [4.5-5.1]) and follow-up (delayed 5.4 [5.0-5.7], workshop 5.3 [5.0-5.6]; p = 0.88 for interaction). For the entire cohort, rater confidence (1 = not confident, 6 = very confident) improved from mean (SD) 3.8 (1.4) to 4.4 (1.0), p = 0.018. Interrater reliability for ratings of live encounters (entire cohort) was higher after the workshop (ICC 0.34) than before (ICC 0.18) but the standard error of measurement was similar for both periods. Rater training did not improve interrater reliability or accuracy of mini-CEX scores. clinicaltrials.gov identifier NCT00667940

Considerations for analysis of time-to-event outcomes measured with error: Bias and correction with SIMEX.

PubMed

Oh, Eric J; Shepherd, Bryan E; Lumley, Thomas; Shaw, Pamela A

2018-04-15

For time-to-event outcomes, a rich literature exists on the bias introduced by covariate measurement error in regression models, such as the Cox model, and methods of analysis to address this bias. By comparison, less attention has been given to understanding the impact or addressing errors in the failure time outcome. For many diseases, the timing of an event of interest (such as progression-free survival or time to AIDS progression) can be difficult to assess or reliant on self-report and therefore prone to measurement error. For linear models, it is well known that random errors in the outcome variable do not bias regression estimates. With nonlinear models, however, even random error or misclassification can introduce bias into estimated parameters. We compare the performance of 2 common regression models, the Cox and Weibull models, in the setting of measurement error in the failure time outcome. We introduce an extension of the SIMEX method to correct for bias in hazard ratio estimates from the Cox model and discuss other analysis options to address measurement error in the response. A formula to estimate the bias induced into the hazard ratio by classical measurement error in the event time for a log-linear survival model is presented. Detailed numerical studies are presented to examine the performance of the proposed SIMEX method under varying levels and parametric forms of the error in the outcome. We further illustrate the method with observational data on HIV outcomes from the Vanderbilt Comprehensive Care Clinic. Copyright © 2017 John Wiley & Sons, Ltd.

Fourier series of atomic radial distribution functions: A molecular fingerprint for machine learning models of quantum chemical properties

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

von Lilienfeld, O. Anatole; Ramakrishnan, Raghunathan; Rupp, Matthias

We introduce a fingerprint representation of molecules based on a Fourier series of atomic radial distribution functions. This fingerprint is unique (except for chirality), continuous, and differentiable with respect to atomic coordinates and nuclear charges. It is invariant with respect to translation, rotation, and nuclear permutation, and requires no preconceived knowledge about chemical bonding, topology, or electronic orbitals. As such, it meets many important criteria for a good molecular representation, suggesting its usefulness for machine learning models of molecular properties trained across chemical compound space. To assess the performance of this new descriptor, we have trained machine learning models ofmore » molecular enthalpies of atomization for training sets with up to 10 k organic molecules, drawn at random from a published set of 134 k organic molecules with an average atomization enthalpy of over 1770 kcal/mol. We validate the descriptor on all remaining molecules of the 134 k set. For a training set of 10 k molecules, the fingerprint descriptor achieves a mean absolute error of 8.0 kcal/mol. This is slightly worse than the performance attained using the Coulomb matrix, another popular alternative, reaching 6.2 kcal/mol for the same training and test sets. (c) 2015 Wiley Periodicals, Inc.« less

Evaluating data mining algorithms using molecular dynamics trajectories.

PubMed

Tatsis, Vasileios A; Tjortjis, Christos; Tzirakis, Panagiotis

2013-01-01

Molecular dynamics simulations provide a sample of a molecule's conformational space. Experiments on the mus time scale, resulting in large amounts of data, are nowadays routine. Data mining techniques such as classification provide a way to analyse such data. In this work, we evaluate and compare several classification algorithms using three data sets which resulted from computer simulations, of a potential enzyme mimetic biomolecule. We evaluated 65 classifiers available in the well-known data mining toolkit Weka, using 'classification' errors to assess algorithmic performance. Results suggest that: (i) 'meta' classifiers perform better than the other groups, when applied to molecular dynamics data sets; (ii) Random Forest and Rotation Forest are the best classifiers for all three data sets; and (iii) classification via clustering yields the highest classification error. Our findings are consistent with bibliographic evidence, suggesting a 'roadmap' for dealing with such data.

Exploration of DGVM Parameter Solution Space Using Simulated Annealing: Implications for Forecast Uncertainties

NASA Astrophysics Data System (ADS)

Wells, J. R.; Kim, J. B.

2011-12-01

Parameters in dynamic global vegetation models (DGVMs) are thought to be weakly constrained and can be a significant source of errors and uncertainties. DGVMs use between 5 and 26 plant functional types (PFTs) to represent the average plant life form in each simulated plot, and each PFT typically has a dozen or more parameters that define the way it uses resource and responds to the simulated growing environment. Sensitivity analysis explores how varying parameters affects the output, but does not do a full exploration of the parameter solution space. The solution space for DGVM parameter values are thought to be complex and non-linear; and multiple sets of acceptable parameters may exist. In published studies, PFT parameters are estimated from published literature, and often a parameter value is estimated from a single published value. Further, the parameters are "tuned" using somewhat arbitrary, "trial-and-error" methods. BIOMAP is a new DGVM created by fusing MAPSS biogeography model with Biome-BGC. It represents the vegetation of North America using 26 PFTs. We are using simulated annealing, a global search method, to systematically and objectively explore the solution space for the BIOMAP PFTs and system parameters important for plant water use. We defined the boundaries of the solution space by obtaining maximum and minimum values from published literature, and where those were not available, using +/-20% of current values. We used stratified random sampling to select a set of grid cells representing the vegetation of the conterminous USA. Simulated annealing algorithm is applied to the parameters for spin-up and a transient run during the historical period 1961-1990. A set of parameter values is considered acceptable if the associated simulation run produces a modern potential vegetation distribution map that is as accurate as one produced by trial-and-error calibration. We expect to confirm that the solution space is non-linear and complex, and that multiple acceptable parameter sets exist. Further we expect to demonstrate that the multiple parameter sets produce significantly divergent future forecasts in NEP, C storage, and ET and runoff; and thereby identify a highly important source of DGVM uncertainty

25+ Years of the Hubble Space Telescope and a Simple Error That Cost Millions

ERIC Educational Resources Information Center

Shakerin, Said

2016-01-01

A simple mistake in properly setting up a measuring device caused millions of dollars to be spent in correcting the initial optical failure of the Hubble Space Telescope (HST). This short article is intended as a lesson for a physics laboratory and discussion of errors in measurement.

Is it possible to minimize overdrainage complications with gravitational units in patients with idiopathic normal pressure hydrocephalus? Protocol of the randomized controlled SVASONA Trial (ISRCTN51046698).

PubMed

Lemcke, J; Meier, U; Müller, C; Fritsch, M; Eymann, R; Kiefer, M; Kehler, U; Langer, N; Rohde, V; Ludwig, H-Ch; Weber, F; Remenez, V; Schuhmann, M; Stengel, D

2010-01-01

Overdrainage is a common complication observed after shunting patients with idiopathic normal-pressure hydrocephalus (iNPH), with an estimated incidence up to 25%. Gravitational units that counterbalance intracranial pressure changes were developed to overcome this problem. We will set out to investigate whether the combination of a programmable valve and a gravitational unit (proGAV, Aesculap/Miethke, Germany) is capable of reducing the incidence of overdrainage and improving patient-centered outcomes compared to a conventional programmable valve (Medos-Codman, Johnson & Johnson, Germany). SVASONA is a pragmatic randomized controlled trial conducted at seven centers in Germany. Patients with a high probability of iNPH (based on clinical signs and symptoms, lumbar infusion and/or tap test, cranial computed tomography [CCT]) and no contraindications for surgical drainage will randomly be assigned to receive (1) a shunt assistant valve (proGAV) or (2) a conventional, programmable shunt valve (programmable Medos-Codman).We will test the primary hypothesis that the experimental device reduces the rate of overdrainage from 25% to 10%. As secondary analyses, we will measure iNPH-specific outcomes (i.e., the Black grading scale and the NPH Recovery Rate), generic quality of life (Short Form 36), and complications and serious adverse events (SAE). One planned interim analysis for safety and efficacy will be performed halfway through the study. To detect the hypothesized difference in the incidence of overdrainage with a type I error of 5% and a type II error of 20%, correcting for multiple testing and an anticipated dropout rate of 10%, 200 patients will be enrolled.The presented trial is currently recruiting patients, with the first results predicted to be available in late 2008.

Improvements in GRACE Gravity Field Determination through Stochastic Observation Modeling

NASA Astrophysics Data System (ADS)

McCullough, C.; Bettadpur, S. V.

2016-12-01

Current unconstrained Release 05 GRACE gravity field solutions from the Center for Space Research (CSR RL05) assume random observation errors following an independent multivariate Gaussian distribution. This modeling of observations, a simplifying assumption, fails to account for long period, correlated errors arising from inadequacies in the background force models. Fully modeling the errors inherent in the observation equations, through the use of a full observation covariance (modeling colored noise), enables optimal combination of GPS and inter-satellite range-rate data and obviates the need for estimating kinematic empirical parameters during the solution process. Most importantly, fully modeling the observation errors drastically improves formal error estimates of the spherical harmonic coefficients, potentially enabling improved uncertainty quantification of scientific results derived from GRACE and optimizing combinations of GRACE with independent data sets and a priori constraints.

The Systematics of Strong Lens Modeling Quantified: The Effects of Constraint Selection and Redshift Information on Magnification, Mass, and Multiple Image Predictability

NASA Astrophysics Data System (ADS)

Johnson, Traci L.; Sharon, Keren

2016-11-01

Until now, systematic errors in strong gravitational lens modeling have been acknowledged but have never been fully quantified. Here, we launch an investigation into the systematics induced by constraint selection. We model the simulated cluster Ares 362 times using random selections of image systems with and without spectroscopic redshifts and quantify the systematics using several diagnostics: image predictability, accuracy of model-predicted redshifts, enclosed mass, and magnification. We find that for models with >15 image systems, the image plane rms does not decrease significantly when more systems are added; however, the rms values quoted in the literature may be misleading as to the ability of a model to predict new multiple images. The mass is well constrained near the Einstein radius in all cases, and systematic error drops to <2% for models using >10 image systems. Magnification errors are smallest along the straight portions of the critical curve, and the value of the magnification is systematically lower near curved portions. For >15 systems, the systematic error on magnification is ∼2%. We report no trend in magnification error with the fraction of spectroscopic image systems when selecting constraints at random; however, when using the same selection of constraints, increasing this fraction up to ∼0.5 will increase model accuracy. The results suggest that the selection of constraints, rather than quantity alone, determines the accuracy of the magnification. We note that spectroscopic follow-up of at least a few image systems is crucial because models without any spectroscopic redshifts are inaccurate across all of our diagnostics.

A method to estimate the additional uncertainty in gap-filled NEE resulting from long gaps in the CO2 flux record

Treesearch

Andrew D. Richardson; David Y. Hollinger

2007-01-01

Missing values in any data set create problems for researchers. The process by which missing values are replaced, and the data set is made complete, is generally referred to as imputation. Within the eddy flux community, the term "gap filling" is more commonly applied. A major challenge is that random errors in measured data result in uncertainty in the gap-...

Noise-enhanced convolutional neural networks.

PubMed

Audhkhasi, Kartik; Osoba, Osonde; Kosko, Bart

2016-06-01

Injecting carefully chosen noise can speed convergence in the backpropagation training of a convolutional neural network (CNN). The Noisy CNN algorithm speeds training on average because the backpropagation algorithm is a special case of the generalized expectation-maximization (EM) algorithm and because such carefully chosen noise always speeds up the EM algorithm on average. The CNN framework gives a practical way to learn and recognize images because backpropagation scales with training data. It has only linear time complexity in the number of training samples. The Noisy CNN algorithm finds a special separating hyperplane in the network's noise space. The hyperplane arises from the likelihood-based positivity condition that noise-boosts the EM algorithm. The hyperplane cuts through a uniform-noise hypercube or Gaussian ball in the noise space depending on the type of noise used. Noise chosen from above the hyperplane speeds training on average. Noise chosen from below slows it on average. The algorithm can inject noise anywhere in the multilayered network. Adding noise to the output neurons reduced the average per-iteration training-set cross entropy by 39% on a standard MNIST image test set of handwritten digits. It also reduced the average per-iteration training-set classification error by 47%. Adding noise to the hidden layers can also reduce these performance measures. The noise benefit is most pronounced for smaller data sets because the largest EM hill-climbing gains tend to occur in the first few iterations. This noise effect can assist random sampling from large data sets because it allows a smaller random sample to give the same or better performance than a noiseless sample gives. Copyright © 2015 Elsevier Ltd. All rights reserved.

[Efficacy of motivational interviewing for reducing medication errors in chronic patients over 65 years with polypharmacy: Results of a cluster randomized trial].

PubMed

Pérula de Torres, Luis Angel; Pulido Ortega, Laura; Pérula de Torres, Carlos; González Lama, Jesús; Olaya Caro, Inmaculada; Ruiz Moral, Roger

2014-10-21

To evaluate the effectiveness of an intervention based on motivational interviewing to reduce medication errors in chronic patients over 65 with polypharmacy. Cluster randomized trial that included doctors and nurses of 16 Primary Care centers and chronic patients with polypharmacy over 65 years. The professionals were assigned to the experimental or the control group using stratified randomization. Interventions consisted of training of professionals and revision of patient treatments, application of motivational interviewing in the experimental group and also the usual approach in the control group. The primary endpoint (medication error) was analyzed at individual level, and was estimated with the absolute risk reduction (ARR), relative risk reduction (RRR), number of subjects to treat (NNT) and by multiple logistic regression analysis. Thirty-two professionals were randomized (19 doctors and 13 nurses), 27 of them recruited 154 patients consecutively (13 professionals in the experimental group recruited 70 patients and 14 professionals recruited 84 patients in the control group) and completed 6 months of follow-up. The mean age of patients was 76 years (68.8% women). A decrease in the average of medication errors was observed along the period. The reduction was greater in the experimental than in the control group (F=5.109, P=.035). RRA 29% (95% confidence interval [95% CI] 15.0-43.0%), RRR 0.59 (95% CI:0.31-0.76), and NNT 3.5 (95% CI 2.3-6.8). Motivational interviewing is more efficient than the usual approach to reduce medication errors in patients over 65 with polypharmacy. Copyright © 2013 Elsevier España, S.L.U. All rights reserved.

Random safety auditing, root cause analysis, failure mode and effects analysis.

PubMed

Ursprung, Robert; Gray, James

2010-03-01

Improving quality and safety in health care is a major concern for health care providers, the general public, and policy makers. Errors and quality issues are leading causes of morbidity and mortality across the health care industry. There is evidence that patients in the neonatal intensive care unit (NICU) are at high risk for serious medical errors. To facilitate compliance with safe practices, many institutions have established quality-assurance monitoring procedures. Three techniques that have been found useful in the health care setting are failure mode and effects analysis, root cause analysis, and random safety auditing. When used together, these techniques are effective tools for system analysis and redesign focused on providing safe delivery of care in the complex NICU system. Copyright 2010 Elsevier Inc. All rights reserved.

Catch-up saccades in head-unrestrained conditions reveal that saccade amplitude is corrected using an internal model of target movement

PubMed Central

Daye, Pierre M.; Blohm, Gunnar; Lefèvre, Phillippe

2014-01-01

This study analyzes how human participants combine saccadic and pursuit gaze movements when they track an oscillating target moving along a randomly oriented straight line with the head free to move. We found that to track the moving target appropriately, participants triggered more saccades with increasing target oscillation frequency to compensate for imperfect tracking gains. Our sinusoidal paradigm allowed us to show that saccade amplitude was better correlated with internal estimates of position and velocity error at saccade onset than with those parameters 100 ms before saccade onset as head-restrained studies have shown. An analysis of saccadic onset time revealed that most of the saccades were triggered when the target was accelerating. Finally, we found that most saccades were triggered when small position errors were combined with large velocity errors at saccade onset. This could explain why saccade amplitude was better correlated with velocity error than with position error. Therefore, our results indicate that the triggering mechanism of head-unrestrained catch-up saccades combines position and velocity error at saccade onset to program and correct saccade amplitude rather than using sensory information 100 ms before saccade onset. PMID:24424378

A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring

NASA Astrophysics Data System (ADS)

Zimmerman, Naomi; Presto, Albert A.; Kumar, Sriniwasa P. N.; Gu, Jason; Hauryliuk, Aliaksei; Robinson, Ellis S.; Robinson, Allen L.; Subramanian, R.

2018-01-01

Low-cost sensing strategies hold the promise of denser air quality monitoring networks, which could significantly improve our understanding of personal air pollution exposure. Additionally, low-cost air quality sensors could be deployed to areas where limited monitoring exists. However, low-cost sensors are frequently sensitive to environmental conditions and pollutant cross-sensitivities, which have historically been poorly addressed by laboratory calibrations, limiting their utility for monitoring. In this study, we investigated different calibration models for the Real-time Affordable Multi-Pollutant (RAMP) sensor package, which measures CO, NO2, O3, and CO2. We explored three methods: (1) laboratory univariate linear regression, (2) empirical multiple linear regression, and (3) machine-learning-based calibration models using random forests (RF). Calibration models were developed for 16-19 RAMP monitors (varied by pollutant) using training and testing windows spanning August 2016 through February 2017 in Pittsburgh, PA, US. The random forest models matched (CO) or significantly outperformed (NO2, CO2, O3) the other calibration models, and their accuracy and precision were robust over time for testing windows of up to 16 weeks. Following calibration, average mean absolute error on the testing data set from the random forest models was 38 ppb for CO (14 % relative error), 10 ppm for CO2 (2 % relative error), 3.5 ppb for NO2 (29 % relative error), and 3.4 ppb for O3 (15 % relative error), and Pearson r versus the reference monitors exceeded 0.8 for most units. Model performance is explored in detail, including a quantification of model variable importance, accuracy across different concentration ranges, and performance in a range of monitoring contexts including the National Ambient Air Quality Standards (NAAQS) and the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. A key strength of the RF approach is that it accounts for pollutant cross-sensitivities. This highlights the importance of developing multipollutant sensor packages (as opposed to single-pollutant monitors); we determined this is especially critical for NO2 and CO2. The evaluation reveals that only the RF-calibrated sensors meet the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. We also demonstrate that the RF-model-calibrated sensors could detect differences in NO2 concentrations between a near-road site and a suburban site less than 1.5 km away. From this study, we conclude that combining RF models with carefully controlled state-of-the-art multipollutant sensor packages as in the RAMP monitors appears to be a very promising approach to address the poor performance that has plagued low-cost air quality sensors.

An agent-based model of dialect evolution in killer whales.

PubMed

Filatova, Olga A; Miller, Patrick J O

2015-05-21

The killer whale is one of the few animal species with vocal dialects that arise from socially learned group-specific call repertoires. We describe a new agent-based model of killer whale populations and test a set of vocal-learning rules to assess which mechanisms may lead to the formation of dialect groupings observed in the wild. We tested a null model with genetic transmission and no learning, and ten models with learning rules that differ by template source (mother or matriline), variation type (random errors or innovations) and type of call change (no divergence from kin vs. divergence from kin). The null model without vocal learning did not produce the pattern of group-specific call repertoires we observe in nature. Learning from either mother alone or the entire matriline with calls changing by random errors produced a graded distribution of the call phenotype, without the discrete call types observed in nature. Introducing occasional innovation or random error proportional to matriline variance yielded more or less discrete and stable call types. A tendency to diverge from the calls of related matrilines provided fast divergence of loose call clusters. A pattern resembling the dialect diversity observed in the wild arose only when rules were applied in combinations and similar outputs could arise from different learning rules and their combinations. Our results emphasize the lack of information on quantitative features of wild killer whale dialects and reveal a set of testable questions that can draw insights into the cultural evolution of killer whale dialects. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty

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

Lu, Ning; Diao, Ruisheng; Hafen, Ryan P.

2013-07-25

This paper presents four algorithms to generate random forecast error time series. The performance of four algorithms is compared. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets used in power grid operation to study the net load balancing need in variable generation integration studies. The four algorithms are truncated-normal distribution models, state-space based Markov models, seasonal autoregressive moving average (ARMA) models, and a stochastic-optimization based approach. The comparison is made using historical DA load forecast and actual load valuesmore » to generate new sets of DA forecasts with similar stoical forecast error characteristics (i.e., mean, standard deviation, autocorrelation, and cross-correlation). The results show that all methods generate satisfactory results. One method may preserve one or two required statistical characteristics better the other methods, but may not preserve other statistical characteristics as well compared with the other methods. Because the wind and load forecast error generators are used in wind integration studies to produce wind and load forecasts time series for stochastic planning processes, it is sometimes critical to use multiple methods to generate the error time series to obtain a statistically robust result. Therefore, this paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.« less

POLICY IMPLICATIONS OF ADJUSTING RANDOMIZED TRIAL DATA FOR ECONOMIC EVALUATIONS: A DEMONSTRATION FROM THE ASCUS-LSIL TRIAGE STUDY

PubMed Central

Campos, Nicole G.; Castle, Philip E.; Schiffman, Mark; Kim, Jane J.

2013-01-01

Background Although the randomized controlled trial (RCT) is widely considered the most reliable method for evaluation of health care interventions, challenges to both internal and external validity exist. Thus, the efficacy of an intervention in a trial setting does not necessarily represent the real-world performance that decision makers seek to inform comparative effectiveness studies and economic evaluations. Methods Using data from the ASCUS-LSIL Triage Study (ALTS), we performed a simplified economic evaluation of age-based management strategies to detect cervical intraepithelial neoplasia grade 3 (CIN3) among women who were referred to the study with low-grade squamous intraepithelial lesions (LSIL). We used data from the trial itself to adjust for 1) potential lead time bias and random error that led to variation in the observed prevalence of CIN3 by study arm, and 2) potential ascertainment bias among providers in the most aggressive management arm. Results We found that using unadjusted RCT data may result in counterintuitive cost-effectiveness results when random error and/or bias are present. Following adjustment, the rank order of management strategies changed for two of the three age groups we considered. Conclusion Decision analysts need to examine study design, available trial data and cost-effectiveness results closely in order to detect evidence of potential bias. Adjustment for random error and bias in RCTs may yield different policy conclusions relative to unadjusted trial data. PMID:22147881

Virtual occlusal definition for orthognathic surgery.

PubMed

Liu, X J; Li, Q Q; Zhang, Z; Li, T T; Xie, Z; Zhang, Y

2016-03-01

Computer-assisted surgical simulation is being used increasingly in orthognathic surgery. However, occlusal definition is still undertaken using model surgery with subsequent digitization via surface scanning or cone beam computed tomography. A software tool has been developed and a workflow set up in order to achieve a virtual occlusal definition. The results of a validation study carried out on 60 models of normal occlusion are presented. Inter- and intra-user correlation tests were used to investigate the reproducibility of the manual setting point procedure. The errors between the virtually set positions (test) and the digitized manually set positions (gold standard) were compared. The consistency in virtual set positions performed by three individual users was investigated by one way analysis of variance test. Inter- and intra-observer correlation coefficients for manual setting points were all greater than 0.95. Overall, the median error between the test and the gold standard positions was 1.06mm. Errors did not differ among teeth (F=0.371, P>0.05). The errors were not significantly different from 1mm (P>0.05). There were no significant differences in the errors made by the three independent users (P>0.05). In conclusion, this workflow for virtual occlusal definition was found to be reliable and accurate. Copyright © 2015 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Quantifying Uncertainties in Land Surface Microwave Emissivity Retrievals

NASA Technical Reports Server (NTRS)

Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Prigent, Catherine; Norouzi, Hamidreza; Aires, Filipe; Boukabara, Sid-Ahmed; Furuzawa, Fumie A.; Masunaga, Hirohiko

2012-01-01

Uncertainties in the retrievals of microwave land surface emissivities were quantified over two types of land surfaces: desert and tropical rainforest. Retrievals from satellite-based microwave imagers, including SSM/I, TMI and AMSR-E, were studied. Our results show that there are considerable differences between the retrievals from different sensors and from different groups over these two land surface types. In addition, the mean emissivity values show different spectral behavior across the frequencies. With the true emissivity assumed largely constant over both of the two sites throughout the study period, the differences are largely attributed to the systematic and random errors in the retrievals. Generally these retrievals tend to agree better at lower frequencies than at higher ones, with systematic differences ranging 14% (312 K) over desert and 17% (320 K) over rainforest. The random errors within each retrieval dataset are in the range of 0.52% (26 K). In particular, at 85.0/89.0 GHz, there are very large differences between the different retrieval datasets, and within each retrieval dataset itself. Further investigation reveals that these differences are mostly likely caused by rain/cloud contamination, which can lead to random errors up to 1017 K under the most severe conditions.

Error-Transparent Quantum Gates for Small Logical Qubit Architectures

NASA Astrophysics Data System (ADS)

Kapit, Eliot

2018-02-01

One of the largest obstacles to building a quantum computer is gate error, where the physical evolution of the state of a qubit or group of qubits during a gate operation does not match the intended unitary transformation. Gate error stems from a combination of control errors and random single qubit errors from interaction with the environment. While great strides have been made in mitigating control errors, intrinsic qubit error remains a serious problem that limits gate fidelity in modern qubit architectures. Simultaneously, recent developments of small error-corrected logical qubit devices promise significant increases in logical state lifetime, but translating those improvements into increases in gate fidelity is a complex challenge. In this Letter, we construct protocols for gates on and between small logical qubit devices which inherit the parent device's tolerance to single qubit errors which occur at any time before or during the gate. We consider two such devices, a passive implementation of the three-qubit bit flip code, and the author's own [E. Kapit, Phys. Rev. Lett. 116, 150501 (2016), 10.1103/PhysRevLett.116.150501] very small logical qubit (VSLQ) design, and propose error-tolerant gate sets for both. The effective logical gate error rate in these models displays superlinear error reduction with linear increases in single qubit lifetime, proving that passive error correction is capable of increasing gate fidelity. Using a standard phenomenological noise model for superconducting qubits, we demonstrate a realistic, universal one- and two-qubit gate set for the VSLQ, with error rates an order of magnitude lower than those for same-duration operations on single qubits or pairs of qubits. These developments further suggest that incorporating small logical qubits into a measurement based code could substantially improve code performance.

The impact of 3D volume of interest definition on accuracy and precision of activity estimation in quantitative SPECT and planar processing methods

NASA Astrophysics Data System (ADS)

He, Bin; Frey, Eric C.

2010-06-01

Accurate and precise estimation of organ activities is essential for treatment planning in targeted radionuclide therapy. We have previously evaluated the impact of processing methodology, statistical noise and variability in activity distribution and anatomy on the accuracy and precision of organ activity estimates obtained with quantitative SPECT (QSPECT) and planar (QPlanar) processing. Another important factor impacting the accuracy and precision of organ activity estimates is accuracy of and variability in the definition of organ regions of interest (ROI) or volumes of interest (VOI). The goal of this work was thus to systematically study the effects of VOI definition on the reliability of activity estimates. To this end, we performed Monte Carlo simulation studies using randomly perturbed and shifted VOIs to assess the impact on organ activity estimates. The 3D NCAT phantom was used with activities that modeled clinically observed 111In ibritumomab tiuxetan distributions. In order to study the errors resulting from misdefinitions due to manual segmentation errors, VOIs of the liver and left kidney were first manually defined. Each control point was then randomly perturbed to one of the nearest or next-nearest voxels in three ways: with no, inward or outward directional bias, resulting in random perturbation, erosion or dilation, respectively, of the VOIs. In order to study the errors resulting from the misregistration of VOIs, as would happen, e.g. in the case where the VOIs were defined using a misregistered anatomical image, the reconstructed SPECT images or projections were shifted by amounts ranging from -1 to 1 voxels in increments of with 0.1 voxels in both the transaxial and axial directions. The activity estimates from the shifted reconstructions or projections were compared to those from the originals, and average errors were computed for the QSPECT and QPlanar methods, respectively. For misregistration, errors in organ activity estimations were linear in the shift for both the QSPECT and QPlanar methods. QPlanar was less sensitive to object definition perturbations than QSPECT, especially for dilation and erosion cases. Up to 1 voxel misregistration or misdefinition resulted in up to 8% error in organ activity estimates, with the largest errors for small or low uptake organs. Both types of VOI definition errors produced larger errors in activity estimates for a small and low uptake organs (i.e. -7.5% to 5.3% for the left kidney) than for a large and high uptake organ (i.e. -2.9% to 2.1% for the liver). We observed that misregistration generally had larger effects than misdefinition, with errors ranging from -7.2% to 8.4%. The different imaging methods evaluated responded differently to the errors from misregistration and misdefinition. We found that QSPECT was more sensitive to misdefinition errors, but less sensitive to misregistration errors, as compared to the QPlanar method. Thus, sensitivity to VOI definition errors should be an important criterion in evaluating quantitative imaging methods.

Calibration of Predictor Models Using Multiple Validation Experiments

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2015-01-01

This paper presents a framework for calibrating computational models using data from several and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncertainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of observations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it casts the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain.

Effect of patient setup errors on simultaneously integrated boost head and neck IMRT treatment plans

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

Siebers, Jeffrey V.; Keall, Paul J.; Wu Qiuwen

2005-10-01

Purpose: The purpose of this study is to determine dose delivery errors that could result from random and systematic setup errors for head-and-neck patients treated using the simultaneous integrated boost (SIB)-intensity-modulated radiation therapy (IMRT) technique. Methods and Materials: Twenty-four patients who participated in an intramural Phase I/II parotid-sparing IMRT dose-escalation protocol using the SIB treatment technique had their dose distributions reevaluated to assess the impact of random and systematic setup errors. The dosimetric effect of random setup error was simulated by convolving the two-dimensional fluence distribution of each beam with the random setup error probability density distribution. Random setup errorsmore » of {sigma} = 1, 3, and 5 mm were simulated. Systematic setup errors were simulated by randomly shifting the patient isocenter along each of the three Cartesian axes, with each shift selected from a normal distribution. Systematic setup error distributions with {sigma} = 1.5 and 3.0 mm along each axis were simulated. Combined systematic and random setup errors were simulated for {sigma} = {sigma} = 1.5 and 3.0 mm along each axis. For each dose calculation, the gross tumor volume (GTV) received by 98% of the volume (D{sub 98}), clinical target volume (CTV) D{sub 90}, nodes D{sub 90}, cord D{sub 2}, and parotid D{sub 50} and parotid mean dose were evaluated with respect to the plan used for treatment for the structure dose and for an effective planning target volume (PTV) with a 3-mm margin. Results: Simultaneous integrated boost-IMRT head-and-neck treatment plans were found to be less sensitive to random setup errors than to systematic setup errors. For random-only errors, errors exceeded 3% only when the random setup error {sigma} exceeded 3 mm. Simulated systematic setup errors with {sigma} = 1.5 mm resulted in approximately 10% of plan having more than a 3% dose error, whereas a {sigma} = 3.0 mm resulted in half of the plans having more than a 3% dose error and 28% with a 5% dose error. Combined random and systematic dose errors with {sigma} = {sigma} = 3.0 mm resulted in more than 50% of plans having at least a 3% dose error and 38% of the plans having at least a 5% dose error. Evaluation with respect to a 3-mm expanded PTV reduced the observed dose deviations greater than 5% for the {sigma} = {sigma} = 3.0 mm simulations to 5.4% of the plans simulated. Conclusions: Head-and-neck SIB-IMRT dosimetric accuracy would benefit from methods to reduce patient systematic setup errors. When GTV, CTV, or nodal volumes are used for dose evaluation, plans simulated including the effects of random and systematic errors deviate substantially from the nominal plan. The use of PTVs for dose evaluation in the nominal plan improves agreement with evaluated GTV, CTV, and nodal dose values under simulated setup errors. PTV concepts should be used for SIB-IMRT head-and-neck squamous cell carcinoma patients, although the size of the margins may be less than those used with three-dimensional conformal radiation therapy.« less

Contact Versus Non-Contact Measurement of a Helicopter Main Rotor Composite Blade

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

Luczak, Marcin; Dziedziech, Kajetan; Peeters, Bart

2010-05-28

The dynamic characterization of lightweight structures is particularly complex as the impact of the weight of sensors and instrumentation (cables, mounting of exciters...) can distort the results. Varying mass loading or constraint effects between partial measurements may determine several errors on the final conclusions. Frequency shifts can lead to erroneous interpretations of the dynamics parameters. Typically these errors remain limited to a few percent. Inconsistent data sets however can result in major processing errors, with all related consequences towards applications based on the consistency assumption, such as global modal parameter identification, model-based damage detection and FRF-based matrix inversion in substructuring,more » load identification and transfer path analysis [1]. This paper addresses the subject of accuracy in the context of the measurement of the dynamic properties of a particular lightweight structure. It presents a comprehensive comparative study between the use of accelerometer, laser vibrometer (scanning LDV) and PU-probe (acoustic particle velocity and pressure) measurements to measure the structural responses, with as final aim the comparison of modal model quality assessment. The object of the investigation is a composite material blade from the main rotor of a helicopter. The presented results are part of an extensive test campaign performed with application of SIMO, MIMO, random and harmonic excitation, and the use of the mentioned contact and non-contact measurement techniques. The advantages and disadvantages of the applied instrumentation are discussed. Presented are real-life measurement problems related to the different set up conditions. Finally an analysis of estimated models is made in view of assessing the applicability of the various measurement approaches for successful fault detection based on modal parameters observation as well as in uncertain non-deterministic numerical model updating.« less

Contact Versus Non-Contact Measurement of a Helicopter Main Rotor Composite Blade

NASA Astrophysics Data System (ADS)

Luczak, Marcin; Dziedziech, Kajetan; Vivolo, Marianna; Desmet, Wim; Peeters, Bart; Van der Auweraer, Herman

2010-05-01

The dynamic characterization of lightweight structures is particularly complex as the impact of the weight of sensors and instrumentation (cables, mounting of exciters…) can distort the results. Varying mass loading or constraint effects between partial measurements may determine several errors on the final conclusions. Frequency shifts can lead to erroneous interpretations of the dynamics parameters. Typically these errors remain limited to a few percent. Inconsistent data sets however can result in major processing errors, with all related consequences towards applications based on the consistency assumption, such as global modal parameter identification, model-based damage detection and FRF-based matrix inversion in substructuring, load identification and transfer path analysis [1]. This paper addresses the subject of accuracy in the context of the measurement of the dynamic properties of a particular lightweight structure. It presents a comprehensive comparative study between the use of accelerometer, laser vibrometer (scanning LDV) and PU-probe (acoustic particle velocity and pressure) measurements to measure the structural responses, with as final aim the comparison of modal model quality assessment. The object of the investigation is a composite material blade from the main rotor of a helicopter. The presented results are part of an extensive test campaign performed with application of SIMO, MIMO, random and harmonic excitation, and the use of the mentioned contact and non-contact measurement techniques. The advantages and disadvantages of the applied instrumentation are discussed. Presented are real-life measurement problems related to the different set up conditions. Finally an analysis of estimated models is made in view of assessing the applicability of the various measurement approaches for successful fault detection based on modal parameters observation as well as in uncertain non-deterministic numerical model updating.

Precision assessment of model-based RSA for a total knee prosthesis in a biplanar set-up.

PubMed

Trozzi, C; Kaptein, B L; Garling, E H; Shelyakova, T; Russo, A; Bragonzoni, L; Martelli, S

2008-10-01

Model-based Roentgen Stereophotogrammetric Analysis (RSA) was recently developed for the measurement of prosthesis micromotion. Its main advantage is that markers do not need to be attached to the implants as traditional marker-based RSA requires. Model-based RSA has only been tested in uniplanar radiographic set-ups. A biplanar set-up would theoretically facilitate the pose estimation algorithm, since radiographic projections would show more different shape features of the implants than in uniplanar images. We tested the precision of model-based RSA and compared it with that of the traditional marker-based method in a biplanar set-up. Micromotions of both tibial and femoral components were measured with both the techniques from double examinations of patients participating in a clinical study. The results showed that in the biplanar set-up model-based RSA presents a homogeneous distribution of precision for all the translation directions, but an inhomogeneous error for rotations, especially internal-external rotation presented higher errors than rotations about the transverse and sagittal axes. Model-based RSA was less precise than the marker-based method, although the differences were not significant for the translations and rotations of the tibial component, with the exception of the internal-external rotations. For both prosthesis components the precisions of model-based RSA were below 0.2 mm for all the translations, and below 0.3 degrees for rotations about transverse and sagittal axes. These values are still acceptable for clinical studies aimed at evaluating total knee prosthesis micromotion. In a biplanar set-up model-based RSA is a valid alternative to traditional marker-based RSA where marking of the prosthesis is an enormous disadvantage.

Interval sampling methods and measurement error: a computer simulation.

PubMed

Wirth, Oliver; Slaven, James; Taylor, Matthew A

2014-01-01

A simulation study was conducted to provide a more thorough account of measurement error associated with interval sampling methods. A computer program simulated the application of momentary time sampling, partial-interval recording, and whole-interval recording methods on target events randomly distributed across an observation period. The simulation yielded measures of error for multiple combinations of observation period, interval duration, event duration, and cumulative event duration. The simulations were conducted up to 100 times to yield measures of error variability. Although the present simulation confirmed some previously reported characteristics of interval sampling methods, it also revealed many new findings that pertain to each method's inherent strengths and weaknesses. The analysis and resulting error tables can help guide the selection of the most appropriate sampling method for observation-based behavioral assessments. © Society for the Experimental Analysis of Behavior.

Medication errors in home care: a qualitative focus group study.

PubMed

Berland, Astrid; Bentsen, Signe Berit

2017-11-01

To explore registered nurses' experiences of medication errors and patient safety in home care. The focus of care for older patients has shifted from institutional care towards a model of home care. Medication errors are common in this situation and can result in patient morbidity and mortality. An exploratory qualitative design with focus group interviews was used. Four focus group interviews were conducted with 20 registered nurses in home care. The data were analysed using content analysis. Five categories were identified as follows: lack of information, lack of competence, reporting medication errors, trade name products vs. generic name products, and improving routines. Medication errors occur frequently in home care and can threaten the safety of patients. Insufficient exchange of information and poor communication between the specialist and home-care health services, and between general practitioners and healthcare workers can lead to medication errors. A lack of competence in healthcare workers can also lead to medication errors. To prevent these, it is important that there should be up-to-date information and communication between healthcare workers during the transfer of patients from specialist to home care. Ensuring competence among healthcare workers with regard to medication is also important. In addition, there should be openness and accurate reporting of medication errors, as well as in setting routines for the preparation, alteration and administration of medicines. To prevent medication errors in home care, up-to-date information and communication between healthcare workers is important when patients are transferred from specialist to home care. It is also important to ensure adequate competence with regard to medication, and that there should be openness when medication errors occur, as well as in setting routines for the preparation, alteration and administration of medications. © 2017 John Wiley & Sons Ltd.

Impacts of uncertainties in European gridded precipitation observations on regional climate analysis

PubMed Central

Gobiet, Andreas

2016-01-01

ABSTRACT Gridded precipitation data sets are frequently used to evaluate climate models or to remove model output biases. Although precipitation data are error prone due to the high spatio‐temporal variability of precipitation and due to considerable measurement errors, relatively few attempts have been made to account for observational uncertainty in model evaluation or in bias correction studies. In this study, we compare three types of European daily data sets featuring two Pan‐European data sets and a set that combines eight very high‐resolution station‐based regional data sets. Furthermore, we investigate seven widely used, larger scale global data sets. Our results demonstrate that the differences between these data sets have the same magnitude as precipitation errors found in regional climate models. Therefore, including observational uncertainties is essential for climate studies, climate model evaluation, and statistical post‐processing. Following our results, we suggest the following guidelines for regional precipitation assessments. (1) Include multiple observational data sets from different sources (e.g. station, satellite, reanalysis based) to estimate observational uncertainties. (2) Use data sets with high station densities to minimize the effect of precipitation undersampling (may induce about 60% error in data sparse regions). The information content of a gridded data set is mainly related to its underlying station density and not to its grid spacing. (3) Consider undercatch errors of up to 80% in high latitudes and mountainous regions. (4) Analyses of small‐scale features and extremes are especially uncertain in gridded data sets. For higher confidence, use climate‐mean and larger scale statistics. In conclusion, neglecting observational uncertainties potentially misguides climate model development and can severely affect the results of climate change impact assessments. PMID:28111497

Impacts of uncertainties in European gridded precipitation observations on regional climate analysis.

PubMed

Prein, Andreas F; Gobiet, Andreas

2017-01-01

Gridded precipitation data sets are frequently used to evaluate climate models or to remove model output biases. Although precipitation data are error prone due to the high spatio-temporal variability of precipitation and due to considerable measurement errors, relatively few attempts have been made to account for observational uncertainty in model evaluation or in bias correction studies. In this study, we compare three types of European daily data sets featuring two Pan-European data sets and a set that combines eight very high-resolution station-based regional data sets. Furthermore, we investigate seven widely used, larger scale global data sets. Our results demonstrate that the differences between these data sets have the same magnitude as precipitation errors found in regional climate models. Therefore, including observational uncertainties is essential for climate studies, climate model evaluation, and statistical post-processing. Following our results, we suggest the following guidelines for regional precipitation assessments. (1) Include multiple observational data sets from different sources (e.g. station, satellite, reanalysis based) to estimate observational uncertainties. (2) Use data sets with high station densities to minimize the effect of precipitation undersampling (may induce about 60% error in data sparse regions). The information content of a gridded data set is mainly related to its underlying station density and not to its grid spacing. (3) Consider undercatch errors of up to 80% in high latitudes and mountainous regions. (4) Analyses of small-scale features and extremes are especially uncertain in gridded data sets. For higher confidence, use climate-mean and larger scale statistics. In conclusion, neglecting observational uncertainties potentially misguides climate model development and can severely affect the results of climate change impact assessments.

Maximum type I error rate inflation from sample size reassessment when investigators are blind to treatment labels.

PubMed

Żebrowska, Magdalena; Posch, Martin; Magirr, Dominic

2016-05-30

Consider a parallel group trial for the comparison of an experimental treatment to a control, where the second-stage sample size may depend on the blinded primary endpoint data as well as on additional blinded data from a secondary endpoint. For the setting of normally distributed endpoints, we demonstrate that this may lead to an inflation of the type I error rate if the null hypothesis holds for the primary but not the secondary endpoint. We derive upper bounds for the inflation of the type I error rate, both for trials that employ random allocation and for those that use block randomization. We illustrate the worst-case sample size reassessment rule in a case study. For both randomization strategies, the maximum type I error rate increases with the effect size in the secondary endpoint and the correlation between endpoints. The maximum inflation increases with smaller block sizes if information on the block size is used in the reassessment rule. Based on our findings, we do not question the well-established use of blinded sample size reassessment methods with nuisance parameter estimates computed from the blinded interim data of the primary endpoint. However, we demonstrate that the type I error rate control of these methods relies on the application of specific, binding, pre-planned and fully algorithmic sample size reassessment rules and does not extend to general or unplanned sample size adjustments based on blinded data. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Modelling and Predicting Backstroke Start Performance Using Non-Linear and Linear Models.

PubMed

de Jesus, Karla; Ayala, Helon V H; de Jesus, Kelly; Coelho, Leandro Dos S; Medeiros, Alexandre I A; Abraldes, José A; Vaz, Mário A P; Fernandes, Ricardo J; Vilas-Boas, João Paulo

2018-03-01

Our aim was to compare non-linear and linear mathematical model responses for backstroke start performance prediction. Ten swimmers randomly completed eight 15 m backstroke starts with feet over the wedge, four with hands on the highest horizontal and four on the vertical handgrip. Swimmers were videotaped using a dual media camera set-up, with the starts being performed over an instrumented block with four force plates. Artificial neural networks were applied to predict 5 m start time using kinematic and kinetic variables and to determine the accuracy of the mean absolute percentage error. Artificial neural networks predicted start time more robustly than the linear model with respect to changing training to the validation dataset for the vertical handgrip (3.95 ± 1.67 vs. 5.92 ± 3.27%). Artificial neural networks obtained a smaller mean absolute percentage error than the linear model in the horizontal (0.43 ± 0.19 vs. 0.98 ± 0.19%) and vertical handgrip (0.45 ± 0.19 vs. 1.38 ± 0.30%) using all input data. The best artificial neural network validation revealed a smaller mean absolute error than the linear model for the horizontal (0.007 vs. 0.04 s) and vertical handgrip (0.01 vs. 0.03 s). Artificial neural networks should be used for backstroke 5 m start time prediction due to the quite small differences among the elite level performances.

Analytical quality goals derived from the total deviation from patients' homeostatic set points, with a margin for analytical errors.

PubMed

Bolann, B J; Asberg, A

2004-01-01

The deviation of test results from patients' homeostatic set points in steady-state conditions may complicate interpretation of the results and the comparison of results with clinical decision limits. In this study the total deviation from the homeostatic set point is defined as the maximum absolute deviation for 95% of measurements, and we present analytical quality requirements that prevent analytical error from increasing this deviation to more than about 12% above the value caused by biology alone. These quality requirements are: 1) The stable systematic error should be approximately 0, and 2) a systematic error that will be detected by the control program with 90% probability, should not be larger than half the value of the combined analytical and intra-individual standard deviation. As a result, when the most common control rules are used, the analytical standard deviation may be up to 0.15 times the intra-individual standard deviation. Analytical improvements beyond these requirements have little impact on the interpretability of measurement results.

Universal quantum gate set approaching fault-tolerant thresholds with superconducting qubits.

PubMed

Chow, Jerry M; Gambetta, Jay M; Córcoles, A D; Merkel, Seth T; Smolin, John A; Rigetti, Chad; Poletto, S; Keefe, George A; Rothwell, Mary B; Rozen, J R; Ketchen, Mark B; Steffen, M

2012-08-10

We use quantum process tomography to characterize a full universal set of all-microwave gates on two superconducting single-frequency single-junction transmon qubits. All extracted gate fidelities, including those for Clifford group generators, single-qubit π/4 and π/8 rotations, and a two-qubit controlled-not, exceed 95% (98%), without (with) subtracting state preparation and measurement errors. Furthermore, we introduce a process map representation in the Pauli basis which is visually efficient and informative. This high-fidelity gate set serves as a critical building block towards scalable architectures of superconducting qubits for error correction schemes and pushes up on the known limits of quantum gate characterization.

Universal Quantum Gate Set Approaching Fault-Tolerant Thresholds with Superconducting Qubits

NASA Astrophysics Data System (ADS)

Chow, Jerry M.; Gambetta, Jay M.; Córcoles, A. D.; Merkel, Seth T.; Smolin, John A.; Rigetti, Chad; Poletto, S.; Keefe, George A.; Rothwell, Mary B.; Rozen, J. R.; Ketchen, Mark B.; Steffen, M.

2012-08-01

We use quantum process tomography to characterize a full universal set of all-microwave gates on two superconducting single-frequency single-junction transmon qubits. All extracted gate fidelities, including those for Clifford group generators, single-qubit π/4 and π/8 rotations, and a two-qubit controlled-not, exceed 95% (98%), without (with) subtracting state preparation and measurement errors. Furthermore, we introduce a process map representation in the Pauli basis which is visually efficient and informative. This high-fidelity gate set serves as a critical building block towards scalable architectures of superconducting qubits for error correction schemes and pushes up on the known limits of quantum gate characterization.

Setup deviations for whole-breast radiotherapy with TomoDirect: A comparison of weekly and biweekly image-guided protocols

NASA Astrophysics Data System (ADS)

Jung, Jae Hong; Jung, Joo-Young; Bae, Sun Hyun; Moon, Seong Kwon; Cho, Kwang Hwan

2016-10-01

The purpose of this study was to compare patient setup deviations for different image-guided protocols (weekly vs. biweekly) that are used in TomoDirect three-dimensional conformal radiotherapy (TD-3DCRT) for whole-breast radiation therapy (WBRT). A total of 138 defined megavoltage computed tomography (MVCT) image sets from 46 breast cancer cases were divided into two groups based on the imaging acquisition times: weekly or biweekly. The mean error, three-dimensional setup displacement error (3D-error), systematic error (Σ), and random error (σ) were calculated for each group. The 3D-errors were 4.29 ± 1.11 mm and 5.02 ± 1.85 mm for the weekly and biweekly groups, respectively; the biweekly error was 14.6% higher than the weekly error. The systematic errors in the roll angle and the x, y, and z directions were 0.48°, 1.72 mm, 2.18 mm, and 1.85 mm for the weekly protocol and 0.21°, 1.24 mm, 1.39 mm, and 1.85 mm for the biweekly protocol. Random errors in the roll angle and the x, y, and z directions were 25.7%, 40.6%, 40.0%, and 40.8% higher in the biweekly group than in the weekly group. For the x, y, and z directions, the distributions of the treatment frequency at less than 5 mm were 98.6%, 91.3%, and 94.2% in the weekly group and 94.2%, 89.9%, and 82.6% in the biweekly group. Moreover, the roll angles with 0 - 1° were 79.7% and 89.9% in the weekly and the biweekly groups, respectively. Overall, the evaluation of setup deviations for the two protocols revealed no significant differences (p > 0.05). Reducing the frequency of MVCT imaging could have promising effects on imaging doses and machine times during treatment. However, the biweekly protocol was associated with increased random setup deviations in the treatment. We have demonstrated a biweekly protocol of TD-3DCRT for WBRT, and we anticipate that our method may provide an alternative approach for considering the uncertainties in the patient setup.

Predicting Coastal Flood Severity using Random Forest Algorithm

NASA Astrophysics Data System (ADS)

Sadler, J. M.; Goodall, J. L.; Morsy, M. M.; Spencer, K.

2017-12-01

Coastal floods have become more common recently and are predicted to further increase in frequency and severity due to sea level rise. Predicting floods in coastal cities can be difficult due to the number of environmental and geographic factors which can influence flooding events. Built stormwater infrastructure and irregular urban landscapes add further complexity. This paper demonstrates the use of machine learning algorithms in predicting street flood occurrence in an urban coastal setting. The model is trained and evaluated using data from Norfolk, Virginia USA from September 2010 - October 2016. Rainfall, tide levels, water table levels, and wind conditions are used as input variables. Street flooding reports made by city workers after named and unnamed storm events, ranging from 1-159 reports per event, are the model output. Results show that Random Forest provides predictive power in estimating the number of flood occurrences given a set of environmental conditions with an out-of-bag root mean squared error of 4.3 flood reports and a mean absolute error of 0.82 flood reports. The Random Forest algorithm performed much better than Poisson regression. From the Random Forest model, total daily rainfall was by far the most important factor in flood occurrence prediction, followed by daily low tide and daily higher high tide. The model demonstrated here could be used to predict flood severity based on forecast rainfall and tide conditions and could be further enhanced using more complete street flooding data for model training.

Spatio-temporal filtering for determination of common mode error in regional GNSS networks

NASA Astrophysics Data System (ADS)

Bogusz, Janusz; Gruszczynski, Maciej; Figurski, Mariusz; Klos, Anna

2015-04-01

The spatial correlation between different stations for individual components in the regional GNSS networks seems to be significant. The mismodelling in satellite orbits, the Earth orientation parameters (EOP), largescale atmospheric effects or satellite antenna phase centre corrections can all cause the regionally correlated errors. This kind of GPS time series errors are referred to as common mode errors (CMEs). They are usually estimated with the regional spatial filtering, such as the "stacking". In this paper, we show the stacking approach for the set of ASG-EUPOS permanent stations, assuming that spatial distribution of the CME is uniform over the whole region of Poland (more than 600 km extent). The ASG-EUPOS is a multifunctional precise positioning system based on the reference network designed for Poland. We used a 5- year span time series (2008-2012) of daily solutions in the ITRF2008 from Bernese 5.0 processed by the Military University of Technology EPN Local Analysis Centre (MUT LAC). At the beginning of our analyses concerning spatial dependencies, the correlation coefficients between each pair of the stations in the GNSS network were calculated. This analysis shows that spatio-temporal behaviour of the GPS-derived time series is not purely random, but there is the evident uniform spatial response. In order to quantify the influence of filtering using CME, the norms L1 and L2 were determined. The values of these norms were calculated for the North, East and Up components twice: before performing the filtration and after stacking. The observed reduction of the L1 and L2 norms was up to 30% depending on the dimension of the network. However, the question how to define an optimal size of CME-analysed subnetwork remains unanswered in this research, due to the fact that our network is not extended enough.

Single molecule counting and assessment of random molecular tagging errors with transposable giga-scale error-correcting barcodes.

PubMed

Lau, Billy T; Ji, Hanlee P

2017-09-21

RNA-Seq measures gene expression by counting sequence reads belonging to unique cDNA fragments. Molecular barcodes commonly in the form of random nucleotides were recently introduced to improve gene expression measures by detecting amplification duplicates, but are susceptible to errors generated during PCR and sequencing. This results in false positive counts, leading to inaccurate transcriptome quantification especially at low input and single-cell RNA amounts where the total number of molecules present is minuscule. To address this issue, we demonstrated the systematic identification of molecular species using transposable error-correcting barcodes that are exponentially expanded to tens of billions of unique labels. We experimentally showed random-mer molecular barcodes suffer from substantial and persistent errors that are difficult to resolve. To assess our method's performance, we applied it to the analysis of known reference RNA standards. By including an inline random-mer molecular barcode, we systematically characterized the presence of sequence errors in random-mer molecular barcodes. We observed that such errors are extensive and become more dominant at low input amounts. We described the first study to use transposable molecular barcodes and its use for studying random-mer molecular barcode errors. Extensive errors found in random-mer molecular barcodes may warrant the use of error correcting barcodes for transcriptome analysis as input amounts decrease.

Quantification of errors induced by temporal resolution on Lagrangian particles in an eddy-resolving model

NASA Astrophysics Data System (ADS)

Qin, Xuerong; van Sebille, Erik; Sen Gupta, Alexander

2014-04-01

Lagrangian particle tracking within ocean models is an important tool for the examination of ocean circulation, ventilation timescales and connectivity and is increasingly being used to understand ocean biogeochemistry. Lagrangian trajectories are obtained by advecting particles within velocity fields derived from hydrodynamic ocean models. For studies of ocean flows on scales ranging from mesoscale up to basin scales, the temporal resolution of the velocity fields should ideally not be more than a few days to capture the high frequency variability that is inherent in mesoscale features. However, in reality, the model output is often archived at much lower temporal resolutions. Here, we quantify the differences in the Lagrangian particle trajectories embedded in velocity fields of varying temporal resolution. Particles are advected from 3-day to 30-day averaged fields in a high-resolution global ocean circulation model. We also investigate whether adding lateral diffusion to the particle movement can compensate for the reduced temporal resolution. Trajectory errors reveal the expected degradation of accuracy in the trajectory positions when decreasing the temporal resolution of the velocity field. Divergence timescales associated with averaging velocity fields up to 30 days are faster than the intrinsic dispersion of the velocity fields but slower than the dispersion caused by the interannual variability of the velocity fields. In experiments focusing on the connectivity along major currents, including western boundary currents, the volume transport carried between two strategically placed sections tends to increase with increased temporal averaging. Simultaneously, the average travel times tend to decrease. Based on these two bulk measured diagnostics, Lagrangian experiments that use temporal averaging of up to nine days show no significant degradation in the flow characteristics for a set of six currents investigated in more detail. The addition of random-walk-style diffusion does not mitigate the errors introduced by temporal averaging for large-scale open ocean Lagrangian simulations.

Analytical model and error analysis of arbitrary phasing technique for bunch length measurement

NASA Astrophysics Data System (ADS)

Chen, Qushan; Qin, Bin; Chen, Wei; Fan, Kuanjun; Pei, Yuanji

2018-05-01

An analytical model of an RF phasing method using arbitrary phase scanning for bunch length measurement is reported. We set up a statistical model instead of a linear chirp approximation to analyze the energy modulation process. It is found that, assuming a short bunch (σφ / 2 π → 0) and small relative energy spread (σγ /γr → 0), the energy spread (Y =σγ 2) at the exit of the traveling wave linac has a parabolic relationship with the cosine value of the injection phase (X = cosφr|z=0), i.e., Y = AX2 + BX + C. Analogous to quadrupole strength scanning for emittance measurement, this phase scanning method can be used to obtain the bunch length by measuring the energy spread at different injection phases. The injection phases can be randomly chosen, which is significantly different from the commonly used zero-phasing method. Further, the systematic error of the reported method, such as the influence of the space charge effect, is analyzed. This technique will be especially useful at low energies when the beam quality is dramatically degraded and is hard to measure using the zero-phasing method.

The systematic component of phylogenetic error as a function of taxonomic sampling under parsimony.

PubMed

Debry, Ronald W

2005-06-01

The effect of taxonomic sampling on phylogenetic accuracy under parsimony is examined by simulating nucleotide sequence evolution. Random error is minimized by using very large numbers of simulated characters. This allows estimation of the consistency behavior of parsimony, even for trees with up to 100 taxa. Data were simulated on 8 distinct 100-taxon model trees and analyzed as stratified subsets containing either 25 or 50 taxa, in addition to the full 100-taxon data set. Overall accuracy decreased in a majority of cases when taxa were added. However, the magnitude of change in the cases in which accuracy increased was larger than the magnitude of change in the cases in which accuracy decreased, so, on average, overall accuracy increased as more taxa were included. A stratified sampling scheme was used to assess accuracy for an initial subsample of 25 taxa. The 25-taxon analyses were compared to 50- and 100-taxon analyses that were pruned to include only the original 25 taxa. On average, accuracy for the 25 taxa was improved by taxon addition, but there was considerable variation in the degree of improvement among the model trees and across different rates of substitution.

A probabilistic approach to remote compositional analysis of planetary surfaces

USGS Publications Warehouse

Lapotre, Mathieu G.A.; Ehlmann, Bethany L.; Minson, Sarah E.

2017-01-01

Reflected light from planetary surfaces provides information, including mineral/ice compositions and grain sizes, by study of albedo and absorption features as a function of wavelength. However, deconvolving the compositional signal in spectra is complicated by the nonuniqueness of the inverse problem. Trade-offs between mineral abundances and grain sizes in setting reflectance, instrument noise, and systematic errors in the forward model are potential sources of uncertainty, which are often unquantified. Here we adopt a Bayesian implementation of the Hapke model to determine sets of acceptable-fit mineral assemblages, as opposed to single best fit solutions. We quantify errors and uncertainties in mineral abundances and grain sizes that arise from instrument noise, compositional end members, optical constants, and systematic forward model errors for two suites of ternary mixtures (olivine-enstatite-anorthite and olivine-nontronite-basaltic glass) in a series of six experiments in the visible-shortwave infrared (VSWIR) wavelength range. We show that grain sizes are generally poorly constrained from VSWIR spectroscopy. Abundance and grain size trade-offs lead to typical abundance errors of ≤1 wt % (occasionally up to ~5 wt %), while ~3% noise in the data increases errors by up to ~2 wt %. Systematic errors further increase inaccuracies by a factor of 4. Finally, phases with low spectral contrast or inaccurate optical constants can further increase errors. Overall, typical errors in abundance are <10%, but sometimes significantly increase for specific mixtures, prone to abundance/grain-size trade-offs that lead to high unmixing uncertainties. These results highlight the need for probabilistic approaches to remote determination of planetary surface composition.

Resolving Transition Metal Chemical Space: Feature Selection for Machine Learning and Structure-Property Relationships.

PubMed

Janet, Jon Paul; Kulik, Heather J

2017-11-22

Machine learning (ML) of quantum mechanical properties shows promise for accelerating chemical discovery. For transition metal chemistry where accurate calculations are computationally costly and available training data sets are small, the molecular representation becomes a critical ingredient in ML model predictive accuracy. We introduce a series of revised autocorrelation functions (RACs) that encode relationships of the heuristic atomic properties (e.g., size, connectivity, and electronegativity) on a molecular graph. We alter the starting point, scope, and nature of the quantities evaluated in standard ACs to make these RACs amenable to inorganic chemistry. On an organic molecule set, we first demonstrate superior standard AC performance to other presently available topological descriptors for ML model training, with mean unsigned errors (MUEs) for atomization energies on set-aside test molecules as low as 6 kcal/mol. For inorganic chemistry, our RACs yield 1 kcal/mol ML MUEs on set-aside test molecules in spin-state splitting in comparison to 15-20× higher errors for feature sets that encode whole-molecule structural information. Systematic feature selection methods including univariate filtering, recursive feature elimination, and direct optimization (e.g., random forest and LASSO) are compared. Random-forest- or LASSO-selected subsets 4-5× smaller than the full RAC set produce sub- to 1 kcal/mol spin-splitting MUEs, with good transferability to metal-ligand bond length prediction (0.004-5 Å MUE) and redox potential on a smaller data set (0.2-0.3 eV MUE). Evaluation of feature selection results across property sets reveals the relative importance of local, electronic descriptors (e.g., electronegativity, atomic number) in spin-splitting and distal, steric effects in redox potential and bond lengths.

Bias in error estimation when using cross-validation for model selection.

PubMed

Varma, Sudhir; Simon, Richard

2006-02-23

Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers by choosing classifier parameter values that minimize the CV error estimate. We have evaluated the validity of using the CV error estimate of the optimized classifier as an estimate of the true error expected on independent data. We used CV to optimize the classification parameters for two kinds of classifiers; Shrunken Centroids and Support Vector Machines (SVM). Random training datasets were created, with no difference in the distribution of the features between the two classes. Using these "null" datasets, we selected classifier parameter values that minimized the CV error estimate. 10-fold CV was used for Shrunken Centroids while Leave-One-Out-CV (LOOCV) was used for the SVM. Independent test data was created to estimate the true error. With "null" and "non null" (with differential expression between the classes) data, we also tested a nested CV procedure, where an inner CV loop is used to perform the tuning of the parameters while an outer CV is used to compute an estimate of the error. The CV error estimate for the classifier with the optimal parameters was found to be a substantially biased estimate of the true error that the classifier would incur on independent data. Even though there is no real difference between the two classes for the "null" datasets, the CV error estimate for the Shrunken Centroid with the optimal parameters was less than 30% on 18.5% of simulated training data-sets. For SVM with optimal parameters the estimated error rate was less than 30% on 38% of "null" data-sets. Performance of the optimized classifiers on the independent test set was no better than chance. The nested CV procedure reduces the bias considerably and gives an estimate of the error that is very close to that obtained on the independent testing set for both Shrunken Centroids and SVM classifiers for "null" and "non-null" data distributions. We show that using CV to compute an error estimate for a classifier that has itself been tuned using CV gives a significantly biased estimate of the true error. Proper use of CV for estimating true error of a classifier developed using a well defined algorithm requires that all steps of the algorithm, including classifier parameter tuning, be repeated in each CV loop. A nested CV procedure provides an almost unbiased estimate of the true error.

Applications and error correction for adiabatic quantum optimization

NASA Astrophysics Data System (ADS)

Pudenz, Kristen

Adiabatic quantum optimization (AQO) is a fast-developing subfield of quantum information processing which holds great promise in the relatively near future. Here we develop an application, quantum anomaly detection, and an error correction code, Quantum Annealing Correction (QAC), for use with AQO. The motivation for the anomaly detection algorithm is the problematic nature of classical software verification and validation (V&V). The number of lines of code written for safety-critical applications such as cars and aircraft increases each year, and with it the cost of finding errors grows exponentially (the cost of overlooking errors, which can be measured in human safety, is arguably even higher). We approach the V&V problem by using a quantum machine learning algorithm to identify charateristics of software operations that are implemented outside of specifications, then define an AQO to return these anomalous operations as its result. Our error correction work is the first large-scale experimental demonstration of quantum error correcting codes. We develop QAC and apply it to USC's equipment, the first and second generation of commercially available D-Wave AQO processors. We first show comprehensive experimental results for the code's performance on antiferromagnetic chains, scaling the problem size up to 86 logical qubits (344 physical qubits) and recovering significant encoded success rates even when the unencoded success rates drop to almost nothing. A broader set of randomized benchmarking problems is then introduced, for which we observe similar behavior to the antiferromagnetic chain, specifically that the use of QAC is almost always advantageous for problems of sufficient size and difficulty. Along the way, we develop problem-specific optimizations for the code and gain insight into the various on-chip error mechanisms (most prominently thermal noise, since the hardware operates at finite temperature) and the ways QAC counteracts them. We finish by showing that the scheme is robust to qubit loss on-chip, a significant benefit when considering an implemented system.

THE SYSTEMATICS OF STRONG LENS MODELING QUANTIFIED: THE EFFECTS OF CONSTRAINT SELECTION AND REDSHIFT INFORMATION ON MAGNIFICATION, MASS, AND MULTIPLE IMAGE PREDICTABILITY

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

Johnson, Traci L.; Sharon, Keren, E-mail: tljohn@umich.edu

Until now, systematic errors in strong gravitational lens modeling have been acknowledged but have never been fully quantified. Here, we launch an investigation into the systematics induced by constraint selection. We model the simulated cluster Ares 362 times using random selections of image systems with and without spectroscopic redshifts and quantify the systematics using several diagnostics: image predictability, accuracy of model-predicted redshifts, enclosed mass, and magnification. We find that for models with >15 image systems, the image plane rms does not decrease significantly when more systems are added; however, the rms values quoted in the literature may be misleading asmore » to the ability of a model to predict new multiple images. The mass is well constrained near the Einstein radius in all cases, and systematic error drops to <2% for models using >10 image systems. Magnification errors are smallest along the straight portions of the critical curve, and the value of the magnification is systematically lower near curved portions. For >15 systems, the systematic error on magnification is ∼2%. We report no trend in magnification error with the fraction of spectroscopic image systems when selecting constraints at random; however, when using the same selection of constraints, increasing this fraction up to ∼0.5 will increase model accuracy. The results suggest that the selection of constraints, rather than quantity alone, determines the accuracy of the magnification. We note that spectroscopic follow-up of at least a few image systems is crucial because models without any spectroscopic redshifts are inaccurate across all of our diagnostics.« less

A critical issue in model-based inference for studying trait-based community assembly and a solution.

PubMed

Ter Braak, Cajo J F; Peres-Neto, Pedro; Dray, Stéphane

2017-01-01

Statistical testing of trait-environment association from data is a challenge as there is no common unit of observation: the trait is observed on species, the environment on sites and the mediating abundance on species-site combinations. A number of correlation-based methods, such as the community weighted trait means method (CWM), the fourth-corner correlation method and the multivariate method RLQ, have been proposed to estimate such trait-environment associations. In these methods, valid statistical testing proceeds by performing two separate resampling tests, one site-based and the other species-based and by assessing significance by the largest of the two p -values (the p max test). Recently, regression-based methods using generalized linear models (GLM) have been proposed as a promising alternative with statistical inference via site-based resampling. We investigated the performance of this new approach along with approaches that mimicked the p max test using GLM instead of fourth-corner. By simulation using models with additional random variation in the species response to the environment, the site-based resampling tests using GLM are shown to have severely inflated type I error, of up to 90%, when the nominal level is set as 5%. In addition, predictive modelling of such data using site-based cross-validation very often identified trait-environment interactions that had no predictive value. The problem that we identify is not an "omitted variable bias" problem as it occurs even when the additional random variation is independent of the observed trait and environment data. Instead, it is a problem of ignoring a random effect. In the same simulations, the GLM-based p max test controlled the type I error in all models proposed so far in this context, but still gave slightly inflated error in more complex models that included both missing (but important) traits and missing (but important) environmental variables. For screening the importance of single trait-environment combinations, the fourth-corner test is shown to give almost the same results as the GLM-based tests in far less computing time.

Error sensitivity analysis in 10-30-day extended range forecasting by using a nonlinear cross-prediction error model

NASA Astrophysics Data System (ADS)

Xia, Zhiye; Xu, Lisheng; Chen, Hongbin; Wang, Yongqian; Liu, Jinbao; Feng, Wenlan

2017-06-01

Extended range forecasting of 10-30 days, which lies between medium-term and climate prediction in terms of timescale, plays a significant role in decision-making processes for the prevention and mitigation of disastrous meteorological events. The sensitivity of initial error, model parameter error, and random error in a nonlinear crossprediction error (NCPE) model, and their stability in the prediction validity period in 10-30-day extended range forecasting, are analyzed quantitatively. The associated sensitivity of precipitable water, temperature, and geopotential height during cases of heavy rain and hurricane is also discussed. The results are summarized as follows. First, the initial error and random error interact. When the ratio of random error to initial error is small (10-6-10-2), minor variation in random error cannot significantly change the dynamic features of a chaotic system, and therefore random error has minimal effect on the prediction. When the ratio is in the range of 10-1-2 (i.e., random error dominates), attention should be paid to the random error instead of only the initial error. When the ratio is around 10-2-10-1, both influences must be considered. Their mutual effects may bring considerable uncertainty to extended range forecasting, and de-noising is therefore necessary. Second, in terms of model parameter error, the embedding dimension m should be determined by the factual nonlinear time series. The dynamic features of a chaotic system cannot be depicted because of the incomplete structure of the attractor when m is small. When m is large, prediction indicators can vanish because of the scarcity of phase points in phase space. A method for overcoming the cut-off effect ( m > 4) is proposed. Third, for heavy rains, precipitable water is more sensitive to the prediction validity period than temperature or geopotential height; however, for hurricanes, geopotential height is most sensitive, followed by precipitable water.

Performance of a visuomotor walking task in an augmented reality training setting.

PubMed

Haarman, Juliet A M; Choi, Julia T; Buurke, Jaap H; Rietman, Johan S; Reenalda, Jasper

2017-12-01

Visual cues can be used to train walking patterns. Here, we studied the performance and learning capacities of healthy subjects executing a high-precision visuomotor walking task, in an augmented reality training set-up. A beamer was used to project visual stepping targets on the walking surface of an instrumented treadmill. Two speeds were used to manipulate task difficulty. All participants (n = 20) had to change their step length to hit visual stepping targets with a specific part of their foot, while walking on a treadmill over seven consecutive training blocks, each block composed of 100 stepping targets. Distance between stepping targets was varied between short, medium and long steps. Training blocks could either be composed of random stepping targets (no fixed sequence was present in the distance between the stepping targets) or sequenced stepping targets (repeating fixed sequence was present). Random training blocks were used to measure non-specific learning and sequenced training blocks were used to measure sequence-specific learning. Primary outcome measures were performance (% of correct hits), and learning effects (increase in performance over the training blocks: both sequence-specific and non-specific). Secondary outcome measures were the performance and stepping-error in relation to the step length (distance between stepping target). Subjects were able to score 76% and 54% at first try for lower speed (2.3 km/h) and higher speed (3.3 km/h) trials, respectively. Performance scores did not increase over the course of the trials, nor did the subjects show the ability to learn a sequenced walking task. Subjects were better able to hit targets while increasing their step length, compared to shortening it. In conclusion, augmented reality training by use of the current set-up was intuitive for the user. Suboptimal feedback presentation might have limited the learning effects of the subjects. Copyright © 2017 Elsevier B.V. All rights reserved.

Compressed/reconstructed test images for CRAF/Cassini

NASA Technical Reports Server (NTRS)

Dolinar, S.; Cheung, K.-M.; Onyszchuk, I.; Pollara, F.; Arnold, S.

1991-01-01

A set of compressed, then reconstructed, test images submitted to the Comet Rendezvous Asteroid Flyby (CRAF)/Cassini project is presented as part of its evaluation of near lossless high compression algorithms for representing image data. A total of seven test image files were provided by the project. The seven test images were compressed, then reconstructed with high quality (root mean square error of approximately one or two gray levels on an 8 bit gray scale), using discrete cosine transforms or Hadamard transforms and efficient entropy coders. The resulting compression ratios varied from about 2:1 to about 10:1, depending on the activity or randomness in the source image. This was accomplished without any special effort to optimize the quantizer or to introduce special postprocessing to filter the reconstruction errors. A more complete set of measurements, showing the relative performance of the compression algorithms over a wide range of compression ratios and reconstruction errors, shows that additional compression is possible at a small sacrifice in fidelity.

Jackknifing Techniques for Evaluation of Equating Accuracy. Research Report. ETS RR-09-39

ERIC Educational Resources Information Center

Haberman, Shelby J.; Lee, Yi-Hsuan; Qian, Jiahe

2009-01-01

Grouped jackknifing may be used to evaluate the stability of equating procedures with respect to sampling error and with respect to changes in anchor selection. Properties of grouped jackknifing are reviewed for simple-random and stratified sampling, and its use is described for comparisons of anchor sets. Application is made to examples of item…

Parkinson's Disease Is Associated with Goal Setting Deficits during Task Switching

ERIC Educational Resources Information Center

Meiran, Nachshon; Friedman, Gilad; Yehene, Eynat

2004-01-01

Ten Parkinson's Disease (PD) patients and 10 control participants were tested using a task-switching paradigm in which there was a random task sequence, and the task was cued in every trial. Five PD patients showed a unique error profile. Their performance approximated guessing when accuracy was dependent on correct task identification, and was…

Animal social networks as substrate for cultural behavioural diversity.

PubMed

Whitehead, Hal; Lusseau, David

2012-02-07

We used individual-based stochastic models to examine how social structure influences the diversity of socially learned behaviour within a non-human population. For continuous behavioural variables we modelled three forms of dyadic social learning, averaging the behavioural value of the two individuals, random transfer of information from one individual to the other, and directional transfer from the individual with highest behavioural value to the other. Learning had potential error. We also examined the transfer of categorical behaviour between individuals with random directionality and two forms of error, the adoption of a randomly chosen existing behavioural category or the innovation of a new type of behaviour. In populations without social structuring the diversity of culturally transmitted behaviour increased with learning error and population size. When the populations were structured socially either by making individuals members of permanent social units or by giving them overlapping ranges, behavioural diversity increased with network modularity under all scenarios, although the proportional increase varied considerably between continuous and categorical behaviour, with transmission mechanism, and population size. Although functions of the form e(c)¹(m)⁻(c)² + (c)³(Log(N)) predicted the mean increase in diversity with modularity (m) and population size (N), behavioural diversity could be highly unpredictable both between simulations with the same set of parameters, and within runs. Errors in social learning and social structuring generally promote behavioural diversity. Consequently, social learning may be considered to produce culture in populations whose social structure is sufficiently modular. Copyright © 2011 Elsevier Ltd. All rights reserved.

Assessing the statistical significance of the achieved classification error of classifiers constructed using serum peptide profiles, and a prescription for random sampling repeated studies for massive high-throughput genomic and proteomic studies.

PubMed

Lyons-Weiler, James; Pelikan, Richard; Zeh, Herbert J; Whitcomb, David C; Malehorn, David E; Bigbee, William L; Hauskrecht, Milos

2005-01-01

Peptide profiles generated using SELDI/MALDI time of flight mass spectrometry provide a promising source of patient-specific information with high potential impact on the early detection and classification of cancer and other diseases. The new profiling technology comes, however, with numerous challenges and concerns. Particularly important are concerns of reproducibility of classification results and their significance. In this work we describe a computational validation framework, called PACE (Permutation-Achieved Classification Error), that lets us assess, for a given classification model, the significance of the Achieved Classification Error (ACE) on the profile data. The framework compares the performance statistic of the classifier on true data samples and checks if these are consistent with the behavior of the classifier on the same data with randomly reassigned class labels. A statistically significant ACE increases our belief that a discriminative signal was found in the data. The advantage of PACE analysis is that it can be easily combined with any classification model and is relatively easy to interpret. PACE analysis does not protect researchers against confounding in the experimental design, or other sources of systematic or random error. We use PACE analysis to assess significance of classification results we have achieved on a number of published data sets. The results show that many of these datasets indeed possess a signal that leads to a statistically significant ACE.

Design of a robust baseband LPC coder for speech transmission over 9.6 kbit/s noisy channels

NASA Astrophysics Data System (ADS)

Viswanathan, V. R.; Russell, W. H.; Higgins, A. L.

1982-04-01

This paper describes the design of a baseband Linear Predictive Coder (LPC) which transmits speech over 9.6 kbit/sec synchronous channels with random bit errors of up to 1%. Presented are the results of our investigation of a number of aspects of the baseband LPC coder with the goal of maximizing the quality of the transmitted speech. Important among these aspects are: bandwidth of the baseband, coding of the baseband residual, high-frequency regeneration, and error protection of important transmission parameters. The paper discusses these and other issues, presents the results of speech-quality tests conducted during the various stages of optimization, and describes the details of the optimized speech coder. This optimized speech coding algorithm has been implemented as a real-time full-duplex system on an array processor. Informal listening tests of the real-time coder have shown that the coder produces good speech quality in the absence of channel bit errors and introduces only a slight degradation in quality for channel bit error rates of up to 1%.

Overlay improvement by exposure map based mask registration optimization

NASA Astrophysics Data System (ADS)

Shi, Irene; Guo, Eric; Chen, Ming; Lu, Max; Li, Gordon; Li, Rivan; Tian, Eric

2015-03-01

Along with the increased miniaturization of semiconductor electronic devices, the design rules of advanced semiconductor devices shrink dramatically. [1] One of the main challenges of lithography step is the layer-to-layer overlay control. Furthermore, DPT (Double Patterning Technology) has been adapted for the advanced technology node like 28nm and 14nm, corresponding overlay budget becomes even tighter. [2][3] After the in-die mask registration (pattern placement) measurement is introduced, with the model analysis of a KLA SOV (sources of variation) tool, it's observed that registration difference between masks is a significant error source of wafer layer-to-layer overlay at 28nm process. [4][5] Mask registration optimization would highly improve wafer overlay performance accordingly. It was reported that a laser based registration control (RegC) process could be applied after the pattern generation or after pellicle mounting and allowed fine tuning of the mask registration. [6] In this paper we propose a novel method of mask registration correction, which can be applied before mask writing based on mask exposure map, considering the factors of mask chip layout, writing sequence, and pattern density distribution. Our experiment data show if pattern density on the mask keeps at a low level, in-die mask registration residue error in 3sigma could be always under 5nm whatever blank type and related writer POSCOR (position correction) file was applied; it proves random error induced by material or equipment would occupy relatively fixed error budget as an error source of mask registration. On the real production, comparing the mask registration difference through critical production layers, it could be revealed that registration residue error of line space layers with higher pattern density is always much larger than the one of contact hole layers with lower pattern density. Additionally, the mask registration difference between layers with similar pattern density could also achieve under 5nm performance. We assume mask registration excluding random error is mostly induced by charge accumulation during mask writing, which may be calculated from surrounding exposed pattern density. Multi-loading test mask registration result shows that with x direction writing sequence, mask registration behavior in x direction is mainly related to sequence direction, but mask registration in y direction would be highly impacted by pattern density distribution map. It proves part of mask registration error is due to charge issue from nearby environment. If exposure sequence is chip by chip for normal multi chip layout case, mask registration of both x and y direction would be impacted analogously, which has also been proved by real data. Therefore, we try to set up a simple model to predict the mask registration error based on mask exposure map, and correct it with the given POSCOR (position correction) file for advanced mask writing if needed.

A Random Variable Related to the Inversion Vector of a Partial Random Permutation

ERIC Educational Resources Information Center

Laghate, Kavita; Deshpande, M. N.

2005-01-01

In this article, we define the inversion vector of a permutation of the integers 1, 2,..., n. We set up a particular kind of permutation, called a partial random permutation. The sum of the elements of the inversion vector of such a permutation is a random variable of interest.

Cardiorespiratory fitness and cognitive functioning following short-term interventions in chronic stroke survivors with cognitive impairment: a pilot study.

PubMed

Blanchet, Sophie; Richards, Carol L; Leblond, Jean; Olivier, Charles; Maltais, Désirée B

2016-06-01

This study, a quasi-experimental, one-group pretest-post-test design, evaluated the effects on cognitive functioning and cardiorespiratory fitness of 8-week interventions (aerobic exercise alone and aerobic exercise and cognitive training combined) in patients with chronic stroke and cognitive impairment living in the community (participants: n=14, 61.93±9.90 years old, 51.50±38.22 months after stroke, n=7 per intervention group). Cognitive functions and cardiorespiratory fitness were evaluated before and after intervention, and at a 3-month follow-up visit (episodic memory: revised-Hopkins Verbal Learning Test; working memory: Brown-Peterson paradigm; attention omission and commission errors: Continuous Performance Test; cardiorespiratory fitness: peak oxygen uptake during a symptom-limited, graded exercise test performed on a semirecumbent ergometer). Friedman's two-way analysis of variance by ranks evaluated differences in score distributions related to time (for the two groups combined). Post-hoc testing was adjusted for multiple comparisons. Compared with before the intervention, there was a significant reduction in attention errors immediately following the intervention (omission errors: 14.6±21.5 vs. 8±13.9, P=0.01; commission errors: 16.4±6.3 vs. 10.9±7.2, P=0.04), and in part at follow-up (omission errors on follow-up: 3.4±4.3, P=0.03; commission errors on follow-up: 13.2±7.6, P=0.42). These results suggest that attention may improve in chronic stroke survivors with cognitive impairment following short-term training that includes an aerobic component, without a change in cardiorespiratory fitness. Randomized-controlled studies are required to confirm these findings.

Blessing of dimensionality: mathematical foundations of the statistical physics of data.

PubMed

Gorban, A N; Tyukin, I Y

2018-04-28

The concentrations of measure phenomena were discovered as the mathematical background to statistical mechanics at the end of the nineteenth/beginning of the twentieth century and have been explored in mathematics ever since. At the beginning of the twenty-first century, it became clear that the proper utilization of these phenomena in machine learning might transform the curse of dimensionality into the blessing of dimensionality This paper summarizes recently discovered phenomena of measure concentration which drastically simplify some machine learning problems in high dimension, and allow us to correct legacy artificial intelligence systems. The classical concentration of measure theorems state that i.i.d. random points are concentrated in a thin layer near a surface (a sphere or equators of a sphere, an average or median-level set of energy or another Lipschitz function, etc.). The new stochastic separation theorems describe the thin structure of these thin layers: the random points are not only concentrated in a thin layer but are all linearly separable from the rest of the set, even for exponentially large random sets. The linear functionals for separation of points can be selected in the form of the linear Fisher's discriminant. All artificial intelligence systems make errors. Non-destructive correction requires separation of the situations (samples) with errors from the samples corresponding to correct behaviour by a simple and robust classifier. The stochastic separation theorems provide us with such classifiers and determine a non-iterative (one-shot) procedure for their construction.This article is part of the theme issue 'Hilbert's sixth problem'. © 2018 The Author(s).

Blessing of dimensionality: mathematical foundations of the statistical physics of data

NASA Astrophysics Data System (ADS)

Gorban, A. N.; Tyukin, I. Y.

2018-04-01

The concentrations of measure phenomena were discovered as the mathematical background to statistical mechanics at the end of the nineteenth/beginning of the twentieth century and have been explored in mathematics ever since. At the beginning of the twenty-first century, it became clear that the proper utilization of these phenomena in machine learning might transform the curse of dimensionality into the blessing of dimensionality. This paper summarizes recently discovered phenomena of measure concentration which drastically simplify some machine learning problems in high dimension, and allow us to correct legacy artificial intelligence systems. The classical concentration of measure theorems state that i.i.d. random points are concentrated in a thin layer near a surface (a sphere or equators of a sphere, an average or median-level set of energy or another Lipschitz function, etc.). The new stochastic separation theorems describe the thin structure of these thin layers: the random points are not only concentrated in a thin layer but are all linearly separable from the rest of the set, even for exponentially large random sets. The linear functionals for separation of points can be selected in the form of the linear Fisher's discriminant. All artificial intelligence systems make errors. Non-destructive correction requires separation of the situations (samples) with errors from the samples corresponding to correct behaviour by a simple and robust classifier. The stochastic separation theorems provide us with such classifiers and determine a non-iterative (one-shot) procedure for their construction. This article is part of the theme issue `Hilbert's sixth problem'.

A Systematic Error Correction Method for TOVS Radiances

NASA Technical Reports Server (NTRS)

Joiner, Joanna; Rokke, Laurie; Einaudi, Franco (Technical Monitor)

2000-01-01

Treatment of systematic errors is crucial for the successful use of satellite data in a data assimilation system. Systematic errors in TOVS radiance measurements and radiative transfer calculations can be as large or larger than random instrument errors. The usual assumption in data assimilation is that observational errors are unbiased. If biases are not effectively removed prior to assimilation, the impact of satellite data will be lessened and can even be detrimental. Treatment of systematic errors is important for short-term forecast skill as well as the creation of climate data sets. A systematic error correction algorithm has been developed as part of a 1D radiance assimilation. This scheme corrects for spectroscopic errors, errors in the instrument response function, and other biases in the forward radiance calculation for TOVS. Such algorithms are often referred to as tuning of the radiances. The scheme is able to account for the complex, air-mass dependent biases that are seen in the differences between TOVS radiance observations and forward model calculations. We will show results of systematic error correction applied to the NOAA 15 Advanced TOVS as well as its predecessors. We will also discuss the ramifications of inter-instrument bias with a focus on stratospheric measurements.

Tolerance Studies of the Mu2e Solenoid System

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

Lopes, M. L.; Ambrosio, G.; Buehler, M.

2014-01-01

The muon-to-electron conversion experiment at Fermilab is designed to explore charged lepton flavor violation. It is composed of three large superconducting solenoids, namely, the production solenoid, the transport solenoid, and the detector solenoid. Each subsystem has a set of field requirements. Tolerance sensitivity studies of the magnet system were performed with the objective of demonstrating that the present magnet design meets all the field requirements. Systematic and random errors were considered on the position and alignment of the coils. The study helps to identify the critical sources of errors and which are translated to coil manufacturing and mechanical support tolerances.

Power collection reduction by mirror surface nonflatness and tracking error for a central receiver solar power system.

PubMed

McFee, R H

1975-07-01

The effects of random waviness, curvature, and tracking error of plane-mirror heliostats in a rectangular array around a central-receiver solar power system are determined by subdividing each mirror into 484 elements, assuming the slope of each element to be representative of the surface slope average at its location, and summing the contributions of all elements and then of all mirrors in the array. Total received power and flux density distribution are computed for a given sun location and set of array parameter values. Effects of shading and blocking by adjacent mirrors are included in the calculation. Alt-azimuth mounting of the heliostats is assumed. Representative curves for two receiver diameters and two sun locations indicate a power loss of 20% for random waviness, curvature, and tracking error of 0.1 degrees rms, 0.002 m(-1), and 0.5 degrees , 3sigma, respectively, for an 18.2-m diam receiver and 0.3 degrees rms, 0.005 m(-1), and greater than 1 degrees , respectively, for a 30.4-m diam receiver.

The Number of Patients and Events Required to Limit the Risk of Overestimation of Intervention Effects in Meta-Analysis—A Simulation Study

PubMed Central

Thorlund, Kristian; Imberger, Georgina; Walsh, Michael; Chu, Rong; Gluud, Christian; Wetterslev, Jørn; Guyatt, Gordon; Devereaux, Philip J.; Thabane, Lehana

2011-01-01

Background Meta-analyses including a limited number of patients and events are prone to yield overestimated intervention effect estimates. While many assume bias is the cause of overestimation, theoretical considerations suggest that random error may be an equal or more frequent cause. The independent impact of random error on meta-analyzed intervention effects has not previously been explored. It has been suggested that surpassing the optimal information size (i.e., the required meta-analysis sample size) provides sufficient protection against overestimation due to random error, but this claim has not yet been validated. Methods We simulated a comprehensive array of meta-analysis scenarios where no intervention effect existed (i.e., relative risk reduction (RRR) = 0%) or where a small but possibly unimportant effect existed (RRR = 10%). We constructed different scenarios by varying the control group risk, the degree of heterogeneity, and the distribution of trial sample sizes. For each scenario, we calculated the probability of observing overestimates of RRR>20% and RRR>30% for each cumulative 500 patients and 50 events. We calculated the cumulative number of patients and events required to reduce the probability of overestimation of intervention effect to 10%, 5%, and 1%. We calculated the optimal information size for each of the simulated scenarios and explored whether meta-analyses that surpassed their optimal information size had sufficient protection against overestimation of intervention effects due to random error. Results The risk of overestimation of intervention effects was usually high when the number of patients and events was small and this risk decreased exponentially over time as the number of patients and events increased. The number of patients and events required to limit the risk of overestimation depended considerably on the underlying simulation settings. Surpassing the optimal information size generally provided sufficient protection against overestimation. Conclusions Random errors are a frequent cause of overestimation of intervention effects in meta-analyses. Surpassing the optimal information size will provide sufficient protection against overestimation. PMID:22028777

Robustly Aligning a Shape Model and Its Application to Car Alignment of Unknown Pose.

PubMed

Li, Yan; Gu, Leon; Kanade, Takeo

2011-09-01

Precisely localizing in an image a set of feature points that form a shape of an object, such as car or face, is called alignment. Previous shape alignment methods attempted to fit a whole shape model to the observed data, based on the assumption of Gaussian observation noise and the associated regularization process. However, such an approach, though able to deal with Gaussian noise in feature detection, turns out not to be robust or precise because it is vulnerable to gross feature detection errors or outliers resulting from partial occlusions or spurious features from the background or neighboring objects. We address this problem by adopting a randomized hypothesis-and-test approach. First, a Bayesian inference algorithm is developed to generate a shape-and-pose hypothesis of the object from a partial shape or a subset of feature points. For alignment, a large number of hypotheses are generated by randomly sampling subsets of feature points, and then evaluated to find the one that minimizes the shape prediction error. This method of randomized subset-based matching can effectively handle outliers and recover the correct object shape. We apply this approach on a challenging data set of over 5,000 different-posed car images, spanning a wide variety of car types, lighting, background scenes, and partial occlusions. Experimental results demonstrate favorable improvements over previous methods on both accuracy and robustness.

Why not? - Communicating stochastic information by use of unsorted frequency pictograms - a randomised controlled trial.

PubMed

Kasper, Jürgen; Heesen, Christoph; Köpke, Sascha; Mühlhauser, Ingrid; Lenz, Matthias

2011-01-01

Statistical health risk information has been proven confusing and difficult to understand. While existing research indicates that presenting risk information in frequency formats is superior to relative risk and probability formats, the optimal design of frequency formats is still unclear. The aim of this study was to compare presentation of multi-figure pictographs in consecutive and random arrangements regarding accuracy in perception and vulnerability for cognitive bias. A total of 111 patients with multiple sclerosis were randomly assigned to two experimental conditions: patient information using 100 figure pictographs in 1) unsorted (UP group) or 2) consecutive arrangement (CP group).The study experiment was framed as patient information on how risks and benefit could be explained. The information comprised two scenarios of a treatment decision with varying levels of emotional relevance. Primary outcome measure was accuracy of information recall (errors made when recalling previously presented frequencies of benefits and side effects). Cognitive bias was measured as additional error appearing with higher emotional involvement. The uncertainty tolerance scale and a set of items to assess risk attribution were surveyed. The study groups did not differ in their accuracy of recalling benefits, but recall of side effects was more accurate in the CP-group. Cognitive bias when recalling benefits was higher in the UP-group than in the CP-group and equal for side effects in both groups. RESULTS were similar in subgroup analyses of patients 1) with highly irrational risk attribution 2) with experience regarding the hypothetical contents or 3) with experience regarding pictograph presentation of frequencies. Overall, benefit was overestimated by more than 100% and variance of recall was extremely high. Consecutive arrangement as commonly used seems not clearly superior to unsorted arrangement which is more close to reality. General poor performance and the corresponding high variance of recall might have clouded existing effects of the arrangement types. More research is needed with varying proportions and other samples.

Effectiveness of Goal-Setting Telephone Follow-Up on Health Behaviors of Patients with Ischemic Stroke: A Randomized Controlled Trial.

PubMed

Wan, Li-Hong; Zhang, Xiao-Pei; Mo, Miao-Miao; Xiong, Xiao-Ni; Ou, Cui-Ling; You, Li-Ming; Chen, Shao-Xian; Zhang, Min

2016-09-01

Adopting healthy behaviors is critical for secondary stroke prevention, but many patients fail to follow national guidelines regarding diet, exercise, and abstinence from risk factors. Compliance often decreases with time after hospital discharge, yet few studies have examined programs promoting long-term adherence to health behaviors. Goal setting and telephone follow-up have been proven to be effective in other areas of medicine, so this study evaluated the effectiveness of a guideline-based, goal-setting telephone follow-up program for patients with ischemic stroke. This was a multicenter, assessor-blinded, parallel-group, randomized controlled trial. Ninety-one stroke patients were randomized to either a control group or an intervention group. Intervention consisted of predischarge education and 3 goal-setting follow-up sessions conducted by phone. Data were collected at baseline and during the third and sixth months after hospital discharge. Six months after discharge, patients in the intervention group exhibited significantly higher medication adherence than patients in the control group. There were no statistically significant differences in physical activity, nutrition, low-salt diet adherence, blood pressure monitoring, smoking abstinence, unhealthy use of alcohol, and modified Rankin Scale (mRS) scores between the 2 groups. Goal-setting telephone follow-up intervention for ischemic stroke patients is feasible and leads to improved medication adherence. However, the lack of group differences in other health behavior subcategories and in themRS score indicates a need for more effective intervention strategies to help patients reach guideline-recommended targets. Copyright © 2016 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Paediatric Refractive Errors in an Eye Clinic in Osogbo, Nigeria.

PubMed

Michaeline, Isawumi; Sheriff, Agboola; Bimbo, Ayegoro

2016-03-01

Paediatric ophthalmology is an emerging subspecialty in Nigeria and as such there is paucity of data on refractive errors in the country. This study set out to determine the pattern of refractive errors in children attending an eye clinic in South West Nigeria. A descriptive study of 180 consecutive subjects seen over a 2-year period. Presenting complaints, presenting visual acuity (PVA), age and sex were recorded. Clinical examination of the anterior and posterior segments of the eyes, extraocular muscle assessment and refraction were done. The types of refractive errors and their grades were determined. Corrected VA was obtained. Data was analysed using descriptive statistics in proportions, chi square with p value <0.05. The age range of subjects was between 3 and 16 years with mean age = 11.7 and SD = 0.51; with males making up 33.9%.The commonest presenting complaint was blurring of distant vision (40%), presenting visual acuity 6/9 (33.9%), normal vision constituted >75.0%, visual impairment20% and low vision 23.3%. Low grade spherical and cylindrical errors occurred most frequently (35.6% and 59.9% respectively). Regular astigmatism was significantly more common, P <0.001. The commonest diagnosis was simple myopic astigmatism (41.1%). Four cases of strabismus were seen. Simple spherical and cylindrical errors were the commonest types of refractive errors seen. Visual impairment and low vision occurred and could be a cause of absenteeism from school. Low-cost spectacle production or dispensing unit and health education are advocated for the prevention of visual impairment in a hospital set-up.

Epinephrine Auto-Injector Versus Drawn Up Epinephrine for Anaphylaxis Management: A Scoping Review.

PubMed

Chime, Nnenna O; Riese, Victoria G; Scherzer, Daniel J; Perretta, Julianne S; McNamara, LeAnn; Rosen, Michael A; Hunt, Elizabeth A

2017-08-01

Anaphylaxis is a life-threatening event. Most clinical symptoms of anaphylaxis can be reversed by prompt intramuscular administration of epinephrine using an auto-injector or epinephrine drawn up in a syringe and delays and errors may be fatal. The aim of this scoping review is to identify and compare errors associated with use of epinephrine drawn up in a syringe versus epinephrine auto-injectors in order to assist hospitals as they choose which approach minimizes risk of adverse events for their patients. PubMed, Embase, CINAHL, Web of Science, and the Cochrane Library were searched using terms agreed to a priori. We reviewed human and simulation studies reporting errors associated with the use of epinephrine in anaphylaxis. There were multiple screening stages with evolving feedback. Each study was independently assessed by two reviewers for eligibility. Data were extracted using an instrument modeled from the Zaza et al instrument and grouped into themes. Three main themes were noted: 1) ergonomics, 2) dosing errors, and 3) errors due to route of administration. Significant knowledge gaps in the operation of epinephrine auto-injectors among healthcare providers, patients, and caregivers were identified. For epinephrine in a syringe, there were more frequent reports of incorrect dosing and erroneous IV administration with associated adverse cardiac events. For the epinephrine auto-injector, unintentional administration to the digit was an error reported on multiple occasions. This scoping review highlights knowledge gaps and a diverse set of errors regardless of the approach to epinephrine preparation during management of anaphylaxis. There are more potentially life-threatening errors reported for epinephrine drawn up in a syringe than with the auto-injectors. The impact of these knowledge gaps and potentially fatal errors on patient outcomes, cost, and quality of care is worthy of further investigation.

Complementary nonparametric analysis of covariance for logistic regression in a randomized clinical trial setting.

PubMed

Tangen, C M; Koch, G G

1999-03-01

In the randomized clinical trial setting, controlling for covariates is expected to produce variance reduction for the treatment parameter estimate and to adjust for random imbalances of covariates between the treatment groups. However, for the logistic regression model, variance reduction is not obviously obtained. This can lead to concerns about the assumptions of the logistic model. We introduce a complementary nonparametric method for covariate adjustment. It provides results that are usually compatible with expectations for analysis of covariance. The only assumptions required are based on randomization and sampling arguments. The resulting treatment parameter is a (unconditional) population average log-odds ratio that has been adjusted for random imbalance of covariates. Data from a randomized clinical trial are used to compare results from the traditional maximum likelihood logistic method with those from the nonparametric logistic method. We examine treatment parameter estimates, corresponding standard errors, and significance levels in models with and without covariate adjustment. In addition, we discuss differences between unconditional population average treatment parameters and conditional subpopulation average treatment parameters. Additional features of the nonparametric method, including stratified (multicenter) and multivariate (multivisit) analyses, are illustrated. Extensions of this methodology to the proportional odds model are also made.

On Time/Space Aggregation of Fine-Scale Error Estimates (Invited)

NASA Astrophysics Data System (ADS)

Huffman, G. J.

2013-12-01

Estimating errors inherent in fine time/space-scale satellite precipitation data sets is still an on-going problem and a key area of active research. Complicating features of these data sets include the intrinsic intermittency of the precipitation in space and time and the resulting highly skewed distribution of precipitation rates. Additional issues arise from the subsampling errors that satellites introduce, the errors due to retrieval algorithms, and the correlated error that retrieval and merger algorithms sometimes introduce. Several interesting approaches have been developed recently that appear to make progress on these long-standing issues. At the same time, the monthly averages over 2.5°x2.5° grid boxes in the Global Precipitation Climatology Project (GPCP) Satellite-Gauge (SG) precipitation data set follow a very simple sampling-based error model (Huffman 1997) with coefficients that are set using coincident surface and GPCP SG data. This presentation outlines the unsolved problem of how to aggregate the fine-scale errors (discussed above) to an arbitrary time/space averaging volume for practical use in applications, reducing in the limit to simple Gaussian expressions at the monthly 2.5°x2.5° scale. Scatter diagrams with different time/space averaging show that the relationship between the satellite and validation data improves due to the reduction in random error. One of the key, and highly non-linear, issues is that fine-scale estimates tend to have large numbers of cases with points near the axes on the scatter diagram (one of the values is exactly or nearly zero, while the other value is higher). Averaging 'pulls' the points away from the axes and towards the 1:1 line, which usually happens for higher precipitation rates before lower rates. Given this qualitative observation of how aggregation affects error, we observe that existing aggregation rules, such as the Steiner et al. (2003) power law, only depend on the aggregated precipitation rate. Is this sufficient, or is it necessary to aggregate the precipitation error estimates across the time/space data cube used for averaging? At least for small time/space data cubes it would seem that the detailed variables that affect each precipitation error estimate in the aggregation, such as sensor type, land/ocean surface type, convective/stratiform type, and so on, drive variations that must be accounted for explicitly.

Verification of unfold error estimates in the UFO code

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

Fehl, D.L.; Biggs, F.

Spectral unfolding is an inverse mathematical operation which attempts to obtain spectral source information from a set of tabulated response functions and data measurements. Several unfold algorithms have appeared over the past 30 years; among them is the UFO (UnFold Operator) code. In addition to an unfolded spectrum, UFO also estimates the unfold uncertainty (error) induced by running the code in a Monte Carlo fashion with prescribed data distributions (Gaussian deviates). In the problem studied, data were simulated from an arbitrarily chosen blackbody spectrum (10 keV) and a set of overlapping response functions. The data were assumed to have anmore » imprecision of 5% (standard deviation). 100 random data sets were generated. The built-in estimate of unfold uncertainty agreed with the Monte Carlo estimate to within the statistical resolution of this relatively small sample size (95% confidence level). A possible 10% bias between the two methods was unresolved. The Monte Carlo technique is also useful in underdetemined problems, for which the error matrix method does not apply. UFO has been applied to the diagnosis of low energy x rays emitted by Z-Pinch and ion-beam driven hohlraums.« less

Prediction of protein tertiary structure from sequences using a very large back-propagation neural network

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

Liu, X.; Wilcox, G.L.

1993-12-31

We have implemented large scale back-propagation neural networks on a 544 node Connection Machine, CM-5, using the C language in MIMD mode. The program running on 512 processors performs backpropagation learning at 0.53 Gflops, which provides 76 million connection updates per second. We have applied the network to the prediction of protein tertiary structure from sequence information alone. A neural network with one hidden layer and 40 million connections is trained to learn the relationship between sequence and tertiary structure. The trained network yields predicted structures of some proteins on which it has not been trained given only their sequences.more » Presentation of the Fourier transform of the sequences accentuates periodicity in the sequence and yields good generalization with greatly increased training efficiency. Training simulations with a large, heterologous set of protein structures (111 proteins from CM-5 time) to solutions with under 2% RMS residual error within the training set (random responses give an RMS error of about 20%). Presentation of 15 sequences of related proteins in a testing set of 24 proteins yields predicted structures with less than 8% RMS residual error, indicating good apparent generalization.« less

Comparison of community and hospital pharmacists' attitudes and behaviors on medication error disclosure to the patient: A pilot study.

PubMed

Kim, ChungYun; Mazan, Jennifer L; Quiñones-Boex, Ana C

To determine pharmacists' attitudes and behaviors on medication errors and their disclosure and to compare community and hospital pharmacists on such views. An online questionnaire was developed from previous studies on physicians' disclosure of errors. Questionnaire items included demographics, environment, personal experiences, and attitudes on medication errors and the disclosure process. An invitation to participate along with the link to the questionnaire was electronically distributed to members of two Illinois pharmacy associations. A follow-up reminder was sent 4 weeks after the original message. Data were collected for 3 months, and statistical analyses were performed with the use of IBM SPSS version 22.0. The overall response rate was 23.3% (n = 422). The average employed respondent was a 51-year-old white woman with a BS Pharmacy degree working in a hospital pharmacy as a clinical staff member. Regardless of practice settings, pharmacist respondents agreed that medication errors were inevitable and that a disclosure process is necessary. Respondents from community and hospital settings were further analyzed to assess any differences. Community pharmacist respondents were more likely to agree that medication errors were inevitable and that pharmacists should address the patient's emotions when disclosing an error. Community pharmacist respondents were also more likely to agree that the health care professional most closely involved with the error should disclose the error to the patient and thought that it was the pharmacists' responsibility to disclose the error. Hospital pharmacist respondents were more likely to agree that it was important to include all details in a disclosure process and more likely to disagree on putting a "positive spin" on the event. Regardless of practice setting, responding pharmacists generally agreed that errors should be disclosed to patients. There were, however, significant differences in their attitudes and behaviors depending on their particular practice setting. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Effect of Error Augmentation on Brain Activation and Motor Learning of a Complex Locomotor Task

PubMed Central

Marchal-Crespo, Laura; Michels, Lars; Jaeger, Lukas; López-Olóriz, Jorge; Riener, Robert

2017-01-01

Up to date, the functional gains obtained after robot-aided gait rehabilitation training are limited. Error augmenting strategies have a great potential to enhance motor learning of simple motor tasks. However, little is known about the effect of these error modulating strategies on complex tasks, such as relearning to walk after a neurologic accident. Additionally, neuroimaging evaluation of brain regions involved in learning processes could provide valuable information on behavioral outcomes. We investigated the effect of robotic training strategies that augment errors—error amplification and random force disturbance—and training without perturbations on brain activation and motor learning of a complex locomotor task. Thirty-four healthy subjects performed the experiment with a robotic stepper (MARCOS) in a 1.5 T MR scanner. The task consisted in tracking a Lissajous figure presented on a display by coordinating the legs in a gait-like movement pattern. Behavioral results showed that training without perturbations enhanced motor learning in initially less skilled subjects, while error amplification benefited better-skilled subjects. Training with error amplification, however, hampered transfer of learning. Randomly disturbing forces induced learning and promoted transfer in all subjects, probably because the unexpected forces increased subjects' attention. Functional MRI revealed main effects of training strategy and skill level during training. A main effect of training strategy was seen in brain regions typically associated with motor control and learning, such as, the basal ganglia, cerebellum, intraparietal sulcus, and angular gyrus. Especially, random disturbance and no perturbation lead to stronger brain activation in similar brain regions than error amplification. Skill-level related effects were observed in the IPS, in parts of the superior parietal lobe (SPL), i.e., precuneus, and temporal cortex. These neuroimaging findings indicate that gait-like motor learning depends on interplay between subcortical, cerebellar, and fronto-parietal brain regions. An interesting observation was the low activation observed in the brain's reward system after training with error amplification compared to training without perturbations. Our results suggest that to enhance learning of a locomotor task, errors should be augmented based on subjects' skill level. The impacts of these strategies on motor learning, brain activation, and motivation in neurological patients need further investigation. PMID:29021739

The interaction of the flux errors and transport errors in modeled atmospheric carbon dioxide concentrations

NASA Astrophysics Data System (ADS)

Feng, S.; Lauvaux, T.; Butler, M. P.; Keller, K.; Davis, K. J.; Jacobson, A. R.; Schuh, A. E.; Basu, S.; Liu, J.; Baker, D.; Crowell, S.; Zhou, Y.; Williams, C. A.

2017-12-01

Regional estimates of biogenic carbon fluxes over North America from top-down atmospheric inversions and terrestrial biogeochemical (or bottom-up) models remain inconsistent at annual and sub-annual time scales. While top-down estimates are impacted by limited atmospheric data, uncertain prior flux estimates and errors in the atmospheric transport models, bottom-up fluxes are affected by uncertain driver data, uncertain model parameters and missing mechanisms across ecosystems. This study quantifies both flux errors and transport errors, and their interaction in the CO2 atmospheric simulation. These errors are assessed by an ensemble approach. The WRF-Chem model is set up with 17 biospheric fluxes from the Multiscale Synthesis and Terrestrial Model Intercomparison Project, CarbonTracker-Near Real Time, and the Simple Biosphere model. The spread of the flux ensemble members represents the flux uncertainty in the modeled CO2 concentrations. For the transport errors, WRF-Chem is run using three physical model configurations with three stochastic perturbations to sample the errors from both the physical parameterizations of the model and the initial conditions. Additionally, the uncertainties from boundary conditions are assessed using four CO2 global inversion models which have assimilated tower and satellite CO2 observations. The error structures are assessed in time and space. The flux ensemble members overall overestimate CO2 concentrations. They also show larger temporal variability than the observations. These results suggest that the flux ensemble is overdispersive. In contrast, the transport ensemble is underdispersive. The averaged spatial distribution of modeled CO2 shows strong positive biogenic signal in the southern US and strong negative signals along the eastern coast of Canada. We hypothesize that the former is caused by the 3-hourly downscaling algorithm from which the nighttime respiration dominates the daytime modeled CO2 signals and that the latter is mainly caused by the large-scale transport associated with the jet stream that carries the negative biogenic CO2 signals to the northeastern coast. We apply comprehensive statistics to eliminate outliers. We generate a set of flux perturbations based on pre-calibrated flux ensemble members and apply them to the simulations.

Prediction skill of tropical synoptic scale transients from ECMWF and NCEP ensemble prediction systems

DOE PAGES

Taraphdar, S.; Mukhopadhyay, P.; Leung, L. Ruby; ...

2016-12-05

The prediction skill of tropical synoptic scale transients (SSTR) such as monsoon low and depression during the boreal summer of 2007–2009 are assessed using high resolution ECMWF and NCEP TIGGE forecasts data. By analyzing 246 forecasts for lead times up to 10 days, it is found that the models have good skills in forecasting the planetary scale means but the skills of SSTR remain poor, with the latter showing no skill beyond 2 days for the global tropics and Indian region. Consistent forecast skills among precipitation, velocity potential, and vorticity provide evidence that convection is the primary process responsible formore » precipitation. The poor skills of SSTR can be attributed to the larger random error in the models as they fail to predict the locations and timings of SSTR. Strong correlation between the random error and synoptic precipitation suggests that the former starts to develop from regions of convection. As the NCEP model has larger biases of synoptic scale precipitation, it has a tendency to generate more random error that ultimately reduces the prediction skill of synoptic systems in that model. Finally, the larger biases in NCEP may be attributed to the model moist physics and/or coarser horizontal resolution compared to ECMWF.« less

Quantifying Uncertainties in Land-Surface Microwave Emissivity Retrievals

NASA Technical Reports Server (NTRS)

Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Prigent, Catherine; Norouzi, Hamidreza; Aires, Filipe; Boukabara, Sid-Ahmed; Furuzawa, Fumie A.; Masunaga, Hirohiko

2013-01-01

Uncertainties in the retrievals of microwaveland-surface emissivities are quantified over two types of land surfaces: desert and tropical rainforest. Retrievals from satellite-based microwave imagers, including the Special Sensor Microwave Imager, the Tropical Rainfall Measuring Mission Microwave Imager, and the Advanced Microwave Scanning Radiometer for Earth Observing System, are studied. Our results show that there are considerable differences between the retrievals from different sensors and from different groups over these two land-surface types. In addition, the mean emissivity values show different spectral behavior across the frequencies. With the true emissivity assumed largely constant over both of the two sites throughout the study period, the differences are largely attributed to the systematic and random errors inthe retrievals. Generally, these retrievals tend to agree better at lower frequencies than at higher ones, with systematic differences ranging 1%-4% (3-12 K) over desert and 1%-7% (3-20 K) over rainforest. The random errors within each retrieval dataset are in the range of 0.5%-2% (2-6 K). In particular, at 85.5/89.0 GHz, there are very large differences between the different retrieval datasets, and within each retrieval dataset itself. Further investigation reveals that these differences are most likely caused by rain/cloud contamination, which can lead to random errors up to 10-17 K under the most severe conditions.

Prediction skill of tropical synoptic scale transients from ECMWF and NCEP ensemble prediction systems

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

Taraphdar, S.; Mukhopadhyay, P.; Leung, L. Ruby

The prediction skill of tropical synoptic scale transients (SSTR) such as monsoon low and depression during the boreal summer of 2007–2009 are assessed using high resolution ECMWF and NCEP TIGGE forecasts data. By analyzing 246 forecasts for lead times up to 10 days, it is found that the models have good skills in forecasting the planetary scale means but the skills of SSTR remain poor, with the latter showing no skill beyond 2 days for the global tropics and Indian region. Consistent forecast skills among precipitation, velocity potential, and vorticity provide evidence that convection is the primary process responsible formore » precipitation. The poor skills of SSTR can be attributed to the larger random error in the models as they fail to predict the locations and timings of SSTR. Strong correlation between the random error and synoptic precipitation suggests that the former starts to develop from regions of convection. As the NCEP model has larger biases of synoptic scale precipitation, it has a tendency to generate more random error that ultimately reduces the prediction skill of synoptic systems in that model. Finally, the larger biases in NCEP may be attributed to the model moist physics and/or coarser horizontal resolution compared to ECMWF.« less

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.

Effects of errors and gaps in spatial data sets on assessment of conservation progress.

PubMed

Visconti, P; Di Marco, M; Álvarez-Romero, J G; Januchowski-Hartley, S R; Pressey, R L; Weeks, R; Rondinini, C

2013-10-01

Data on the location and extent of protected areas, ecosystems, and species' distributions are essential for determining gaps in biodiversity protection and identifying future conservation priorities. However, these data sets always come with errors in the maps and associated metadata. Errors are often overlooked in conservation studies, despite their potential negative effects on the reported extent of protection of species and ecosystems. We used 3 case studies to illustrate the implications of 3 sources of errors in reporting progress toward conservation objectives: protected areas with unknown boundaries that are replaced by buffered centroids, propagation of multiple errors in spatial data, and incomplete protected-area data sets. As of 2010, the frequency of protected areas with unknown boundaries in the World Database on Protected Areas (WDPA) caused the estimated extent of protection of 37.1% of the terrestrial Neotropical mammals to be overestimated by an average 402.8% and of 62.6% of species to be underestimated by an average 10.9%. Estimated level of protection of the world's coral reefs was 25% higher when using recent finer-resolution data on coral reefs as opposed to globally available coarse-resolution data. Accounting for additional data sets not yet incorporated into WDPA contributed up to 6.7% of additional protection to marine ecosystems in the Philippines. We suggest ways for data providers to reduce the errors in spatial and ancillary data and ways for data users to mitigate the effects of these errors on biodiversity assessments. © 2013 Society for Conservation Biology.

Forecasting Space Weather-Induced GPS Performance Degradation Using Random Forest

NASA Astrophysics Data System (ADS)

Filjar, R.; Filic, M.; Milinkovic, F.

2017-12-01

Space weather and ionospheric dynamics have a profound effect on positioning performance of the Global Satellite Navigation System (GNSS). However, the quantification of that effect is still the subject of scientific activities around the world. In the latest contribution to the understanding of the space weather and ionospheric effects on satellite-based positioning performance, we conducted a study of several candidates for forecasting method for space weather-induced GPS positioning performance deterioration. First, a 5-days set of experimentally collected data was established, encompassing the space weather and ionospheric activity indices (including: the readings of the Sudden Ionospheric Disturbance (SID) monitors, components of geomagnetic field strength, global Kp index, Dst index, GPS-derived Total Electron Content (TEC) samples, standard deviation of TEC samples, and sunspot number) and observations of GPS positioning error components (northing, easting, and height positioning error) derived from the Adriatic Sea IGS reference stations' RINEX raw pseudorange files in quiet space weather periods. This data set was split into the training and test sub-sets. Then, a selected set of supervised machine learning methods based on Random Forest was applied to the experimentally collected data set in order to establish the appropriate regional (the Adriatic Sea) forecasting models for space weather-induced GPS positioning performance deterioration. The forecasting models were developed in the R/rattle statistical programming environment. The forecasting quality of the regional forecasting models developed was assessed, and the conclusions drawn on the advantages and shortcomings of the regional forecasting models for space weather-caused GNSS positioning performance deterioration.

Three-dimensional analysis of the surface registration accuracy of electromagnetic navigation systems in live endoscopic sinus surgery.

PubMed

Chang, C M; Fang, K M; Huang, T W; Wang, C T; Cheng, P W

2013-12-01

Studies on the performance of surface registration with electromagnetic tracking systems are lacking in both live surgery and the laboratory setting. This study presents the efficiency in time of the system preparation as well as the navigational accuracy of surface registration using electromagnetic tracking systems. Forty patients with bilateral chronic paranasal pansinusitis underwent endoscopic sinus surgery after undergoing sinus computed tomography scans. The surgeries were performed under electromagnetic navigation guidance after the surface registration had been carried out on all of the patients. The intraoperative measurements indicate the time taken for equipment set-up, surface registration and surgical procedure, as well as the degree of navigation error along 3 axes. The time taken for equipment set-up, surface registration and the surgical procedure was 179 +- 23 seconds, 39 +- 4.8 seconds and 114 +- 36 minutes, respectively. A comparison of the navigation error along the 3 axes showed that the deviation in the medial-lateral direction was significantly less than that in the anterior-posterior and cranial-caudal directions. The procedures of equipment set-up and surface registration in electromagnetic navigation tracking are efficient, convenient and easy to manipulate. The system accuracy is within the acceptable ranges, especially on the medial-lateral axis.

Analysis of F-16 radar discrepancies

NASA Astrophysics Data System (ADS)

Riche, K. A.

1982-12-01

One hundred and eight aircraft were randomly selected from three USAF F-16 bases and examined. These aircraft included 63 single-seat F-16As and 45 two-seat F-16Bs and encompassed 8,525 sorties and 748 radar system write-ups. Programs supported by the Statistical Package for the Social Sciences (SPSS) were run on the data. Of the 748 discrepancies, over one-third of them occurred within three sorties of each other and half within six sorties. Sixteen percent of all aircraft which had a discrepancy within three sorties had another write-up within the next three sorties. Designated repeat/recurring write-ups represented one-third of all the instances in which the write-up separation interval was three sorties or less. This is an indication that maintenance is unable to correct equipment failures as they occur, most likely because the false alarm rate is too high and maintenance is unable to duplicate the error conditions on the ground for correct error diagnosis.

Confidence, Concentration, and Competitive Performance of Elite Athletes: A Natural Experiment in Olympic Gymnastics.

ERIC Educational Resources Information Center

Grandjean, Burke D.; Taylor, Patricia A.; Weiner, Jay

2002-01-01

During the women's all-around gymnastics final at the 2000 Olympics, the vault was inadvertently set 5 cm too low for a random half of the gymnasts. The error was widely viewed as undermining their confidence and subsequent performance. However, data from pretest and posttest scores on the vault, bars, beam, and floor indicated that the vault…

Type I and Type II Error Rates and Overall Accuracy of the Revised Parallel Analysis Method for Determining the Number of Factors

ERIC Educational Resources Information Center

Green, Samuel B.; Thompson, Marilyn S.; Levy, Roy; Lo, Wen-Juo

2015-01-01

Traditional parallel analysis (T-PA) estimates the number of factors by sequentially comparing sample eigenvalues with eigenvalues for randomly generated data. Revised parallel analysis (R-PA) sequentially compares the "k"th eigenvalue for sample data to the "k"th eigenvalue for generated data sets, conditioned on"k"-…

Covariance analyses of satellite-derived mesoscale wind fields

NASA Technical Reports Server (NTRS)

Maddox, R. A.; Vonder Haar, T. H.

1979-01-01

Statistical structure functions have been computed independently for nine satellite-derived mesoscale wind fields that were obtained on two different days. Small cumulus clouds were tracked at 5 min intervals, but since these clouds occurred primarily in the warm sectors of midlatitude cyclones the results cannot be considered representative of the circulations within cyclones in general. The field structure varied considerably with time and was especially affected if mesoscale features were observed. The wind fields on the 2 days studied were highly anisotropic with large gradients in structure occurring approximately normal to the mean flow. Structure function calculations for the combined set of satellite winds were used to estimate random error present in the fields. It is concluded for these data that the random error in vector winds derived from cumulus cloud tracking using high-frequency satellite data is less than 1.75 m/s. Spatial correlation functions were also computed for the nine data sets. Normalized correlation functions were considerably different for u and v components and decreased rapidly as data point separation increased for both components. The correlation functions for transverse and longitudinal components decreased less rapidly as data point separation increased.

TU-H-CAMPUS-JeP3-01: Towards Robust Adaptive Radiation Therapy Strategies

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

Boeck, M; KTH Royal Institute of Technology, Stockholm; Eriksson, K

Purpose: To set up a framework combining robust treatment planning with adaptive reoptimization in order to maintain high treatment quality, to respond to interfractional variations and to identify those patients who will benefit the most from an adaptive fractionation schedule. Methods: We propose adaptive strategies based on stochastic minimax optimization for a series of simulated treatments on a one-dimensional patient phantom. The plan should be able to handle anticipated systematic and random errors and is applied during the first fractions. Information on the individual geometric variations is gathered at each fraction. At scheduled fractions, the impact of the measured errorsmore » on the delivered dose distribution is evaluated. For a patient that receives a dose that does not satisfy specified plan quality criteria, the plan is reoptimized based on these individual measurements using one of three different adaptive strategies. The reoptimized plan is then applied during future fractions until a new scheduled adaptation becomes necessary. In the first adaptive strategy the measured systematic and random error scenarios and their assigned probabilities are updated to guide the robust reoptimization. The focus of the second strategy lies on variation of the fraction of the worst scenarios taken into account during robust reoptimization. In the third strategy the uncertainty margins around the target are recalculated with the measured errors. Results: By studying the effect of the three adaptive strategies combined with various adaptation schedules on the same patient population, the group which benefits from adaptation is identified together with the most suitable strategy and schedule. Preliminary computational results indicate when and how best to adapt for the three different strategies. Conclusion: A workflow is presented that provides robust adaptation of the treatment plan throughout the course of treatment and useful measures to identify patients in need for an adaptive treatment strategy.« less

[Detection and classification of medication errors at Joan XXIII University Hospital].

PubMed

Jornet Montaña, S; Canadell Vilarrasa, L; Calabuig Mũoz, M; Riera Sendra, G; Vuelta Arce, M; Bardají Ruiz, A; Gallart Mora, M J

2004-01-01

Medication errors are multifactorial and multidisciplinary, and may originate in processes such as drug prescription, transcription, dispensation, preparation and administration. The goal of this work was to measure the incidence of detectable medication errors that arise within a unit dose drug distribution and control system, from drug prescription to drug administration, by means of an observational method confined to the Pharmacy Department, as well as a voluntary, anonymous report system. The acceptance of this voluntary report system's implementation was also assessed. A prospective descriptive study was conducted. Data collection was performed at the Pharmacy Department from a review of prescribed medical orders, a review of pharmaceutical transcriptions, a review of dispensed medication and a review of medication returned in unit dose medication carts. A voluntary, anonymous report system centralized in the Pharmacy Department was also set up to detect medication errors. Prescription errors were the most frequent (1.12%), closely followed by dispensation errors (1.04%). Transcription errors (0.42%) and administration errors (0.69%) had the lowest overall incidence. Voluntary report involved only 4.25% of all detected errors, whereas unit dose medication cart review contributed the most to error detection. Recognizing the incidence and types of medication errors that occur in a health-care setting allows us to analyze their causes and effect changes in different stages of the process in order to ensure maximal patient safety.

On the use of inexact, pruned hardware in atmospheric modelling

PubMed Central

Düben, Peter D.; Joven, Jaume; Lingamneni, Avinash; McNamara, Hugh; De Micheli, Giovanni; Palem, Krishna V.; Palmer, T. N.

2014-01-01

Inexact hardware design, which advocates trading the accuracy of computations in exchange for significant savings in area, power and/or performance of computing hardware, has received increasing prominence in several error-tolerant application domains, particularly those involving perceptual or statistical end-users. In this paper, we evaluate inexact hardware for its applicability in weather and climate modelling. We expand previous studies on inexact techniques, in particular probabilistic pruning, to floating point arithmetic units and derive several simulated set-ups of pruned hardware with reasonable levels of error for applications in atmospheric modelling. The set-up is tested on the Lorenz ‘96 model, a toy model for atmospheric dynamics, using software emulation for the proposed hardware. The results show that large parts of the computation tolerate the use of pruned hardware blocks without major changes in the quality of short- and long-time diagnostics, such as forecast errors and probability density functions. This could open the door to significant savings in computational cost and to higher resolution simulations with weather and climate models. PMID:24842031

CURE-SMOTE algorithm and hybrid algorithm for feature selection and parameter optimization based on random forests.

PubMed

Ma, Li; Fan, Suohai

2017-03-14

The random forests algorithm is a type of classifier with prominent universality, a wide application range, and robustness for avoiding overfitting. But there are still some drawbacks to random forests. Therefore, to improve the performance of random forests, this paper seeks to improve imbalanced data processing, feature selection and parameter optimization. We propose the CURE-SMOTE algorithm for the imbalanced data classification problem. Experiments on imbalanced UCI data reveal that the combination of Clustering Using Representatives (CURE) enhances the original synthetic minority oversampling technique (SMOTE) algorithms effectively compared with the classification results on the original data using random sampling, Borderline-SMOTE1, safe-level SMOTE, C-SMOTE, and k-means-SMOTE. Additionally, the hybrid RF (random forests) algorithm has been proposed for feature selection and parameter optimization, which uses the minimum out of bag (OOB) data error as its objective function. Simulation results on binary and higher-dimensional data indicate that the proposed hybrid RF algorithms, hybrid genetic-random forests algorithm, hybrid particle swarm-random forests algorithm and hybrid fish swarm-random forests algorithm can achieve the minimum OOB error and show the best generalization ability. The training set produced from the proposed CURE-SMOTE algorithm is closer to the original data distribution because it contains minimal noise. Thus, better classification results are produced from this feasible and effective algorithm. Moreover, the hybrid algorithm's F-value, G-mean, AUC and OOB scores demonstrate that they surpass the performance of the original RF algorithm. Hence, this hybrid algorithm provides a new way to perform feature selection and parameter optimization.

A Test for Anchoring and Yea-Saying in Experimental Consumption Data.

PubMed

van Soest, Arthur; Hurd, Michael

2008-01-01

We analyze experimental survey data, with a random split into respondents who get an open-ended question on the amount of total family consumption (with follow-up unfolding brackets of the form "Is consumption $X or more?" for those who answer "don't know" or "refuse") and respondents who are immediately directed to unfolding brackets. In both cases, the entry point of the unfolding bracket sequence is randomized. Allowing for any type of selection into answering the open-ended or bracket questions, a nonparametric test is developed for errors in the answers to the first bracket question that are different from the usual reporting errors that will also affect open-ended answers. Two types of errors are considered explicitly: anchoring and yea-saying. Data are collected in the 1995 wave of the Assets and Health Dynamics survey, which is representative of the population in the United States that is 70 years and older. We reject the joint hypothesis of no anchoring and no yea-saying. Once yea-saying is taken into account, we find no evidence of anchoring at the entry point.

A Test for Anchoring and Yea-Saying in Experimental Consumption Data

PubMed Central

van Soest, Arthur; Hurd, Michael

2017-01-01

We analyze experimental survey data, with a random split into respondents who get an open-ended question on the amount of total family consumption (with follow-up unfolding brackets of the form “Is consumption $X or more?” for those who answer “don’t know” or “refuse”) and respondents who are immediately directed to unfolding brackets. In both cases, the entry point of the unfolding bracket sequence is randomized. Allowing for any type of selection into answering the open-ended or bracket questions, a nonparametric test is developed for errors in the answers to the first bracket question that are different from the usual reporting errors that will also affect open-ended answers. Two types of errors are considered explicitly: anchoring and yea-saying. Data are collected in the 1995 wave of the Assets and Health Dynamics survey, which is representative of the population in the United States that is 70 years and older. We reject the joint hypothesis of no anchoring and no yea-saying. Once yea-saying is taken into account, we find no evidence of anchoring at the entry point. PMID:29056797

Peak-locking error reduction by birefringent optical diffusers

NASA Astrophysics Data System (ADS)

Kislaya, Ankur; Sciacchitano, Andrea

2018-02-01

The use of optical diffusers for the reduction of peak-locking errors in particle image velocimetry is investigated. The working principle of the optical diffusers is based on the concept of birefringence, where the incoming rays are subject to different deflections depending on the light direction and polarization. The performances of the diffusers are assessed via wind tunnel measurements in uniform flow and wall-bounded turbulence. Comparison with best-practice image defocusing is also conducted. It is found that the optical diffusers yield an increase of the particle image diameter up to 10 µm in the sensor plane. Comparison with reference measurements showed a reduction of both random and systematic errors by a factor of 3, even at low imaging signal-to-noise ratio.

Survival analysis with error-prone time-varying covariates: a risk set calibration approach

PubMed Central

Liao, Xiaomei; Zucker, David M.; Li, Yi; Spiegelman, Donna

2010-01-01

Summary Occupational, environmental, and nutritional epidemiologists are often interested in estimating the prospective effect of time-varying exposure variables such as cumulative exposure or cumulative updated average exposure, in relation to chronic disease endpoints such as cancer incidence and mortality. From exposure validation studies, it is apparent that many of the variables of interest are measured with moderate to substantial error. Although the ordinary regression calibration approach is approximately valid and efficient for measurement error correction of relative risk estimates from the Cox model with time-independent point exposures when the disease is rare, it is not adaptable for use with time-varying exposures. By re-calibrating the measurement error model within each risk set, a risk set regression calibration method is proposed for this setting. An algorithm for a bias-corrected point estimate of the relative risk using an RRC approach is presented, followed by the derivation of an estimate of its variance, resulting in a sandwich estimator. Emphasis is on methods applicable to the main study/external validation study design, which arises in important applications. Simulation studies under several assumptions about the error model were carried out, which demonstrated the validity and efficiency of the method in finite samples. The method was applied to a study of diet and cancer from Harvard’s Health Professionals Follow-up Study (HPFS). PMID:20486928

Meta-analysis inside and outside particle physics: two traditions that should converge?

PubMed

Baker, Rose D; Jackson, Dan

2013-06-01

The use of meta-analysis in medicine and epidemiology really took off in the 1970s. However, in high-energy physics, the Particle Data Group has been carrying out meta-analyses of measurements of particle masses and other properties since 1957. Curiously, there has been virtually no interaction between those working inside and outside particle physics. In this paper, we use statistical models to study two major differences in practice. The first is the usefulness of systematic errors, which physicists are now beginning to quote in addition to statistical errors. The second is whether it is better to treat heterogeneity by scaling up errors as do the Particle Data Group or by adding a random effect as does the rest of the community. Besides fitting models, we derive and use an exact test of the error-scaling hypothesis. We also discuss the other methodological differences between the two streams of meta-analysis. Our conclusion is that systematic errors are not currently very useful and that the conventional random effects model, as routinely used in meta-analysis, has a useful role to play in particle physics. The moral we draw for statisticians is that we should be more willing to explore 'grassroots' areas of statistical application, so that good statistical practice can flow both from and back to the statistical mainstream. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.

CORRELATED AND ZONAL ERRORS OF GLOBAL ASTROMETRIC MISSIONS: A SPHERICAL HARMONIC SOLUTION

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

Makarov, V. V.; Dorland, B. N.; Gaume, R. A.

We propose a computer-efficient and accurate method of estimating spatially correlated errors in astrometric positions, parallaxes, and proper motions obtained by space- and ground-based astrometry missions. In our method, the simulated observational equations are set up and solved for the coefficients of scalar and vector spherical harmonics representing the output errors rather than for individual objects in the output catalog. Both accidental and systematic correlated errors of astrometric parameters can be accurately estimated. The method is demonstrated on the example of the JMAPS mission, but can be used for other projects in space astrometry, such as SIM or JASMINE.

Correlated and Zonal Errors of Global Astrometric Missions: A Spherical Harmonic Solution

NASA Astrophysics Data System (ADS)

Makarov, V. V.; Dorland, B. N.; Gaume, R. A.; Hennessy, G. S.; Berghea, C. T.; Dudik, R. P.; Schmitt, H. R.

2012-07-01

We propose a computer-efficient and accurate method of estimating spatially correlated errors in astrometric positions, parallaxes, and proper motions obtained by space- and ground-based astrometry missions. In our method, the simulated observational equations are set up and solved for the coefficients of scalar and vector spherical harmonics representing the output errors rather than for individual objects in the output catalog. Both accidental and systematic correlated errors of astrometric parameters can be accurately estimated. The method is demonstrated on the example of the JMAPS mission, but can be used for other projects in space astrometry, such as SIM or JASMINE.

Some practical problems in implementing randomization.

PubMed

Downs, Matt; Tucker, Kathryn; Christ-Schmidt, Heidi; Wittes, Janet

2010-06-01

While often theoretically simple, implementing randomization to treatment in a masked, but confirmable, fashion can prove difficult in practice. At least three categories of problems occur in randomization: (1) bad judgment in the choice of method, (2) design and programming errors in implementing the method, and (3) human error during the conduct of the trial. This article focuses on these latter two types of errors, dealing operationally with what can go wrong after trial designers have selected the allocation method. We offer several case studies and corresponding recommendations for lessening the frequency of problems in allocating treatment or for mitigating the consequences of errors. Recommendations include: (1) reviewing the randomization schedule before starting a trial, (2) being especially cautious of systems that use on-demand random number generators, (3) drafting unambiguous randomization specifications, (4) performing thorough testing before entering a randomization system into production, (5) maintaining a dataset that captures the values investigators used to randomize participants, thereby allowing the process of treatment allocation to be reproduced and verified, (6) resisting the urge to correct errors that occur in individual treatment assignments, (7) preventing inadvertent unmasking to treatment assignments in kit allocations, and (8) checking a sample of study drug kits to allow detection of errors in drug packaging and labeling. Although we performed a literature search of documented randomization errors, the examples that we provide and the resultant recommendations are based largely on our own experience in industry-sponsored clinical trials. We do not know how representative our experience is or how common errors of the type we have seen occur. Our experience underscores the importance of verifying the integrity of the treatment allocation process before and during a trial. Clinical Trials 2010; 7: 235-245. http://ctj.sagepub.com.

Modelling and Predicting Backstroke Start Performance Using Non-Linear and Linear Models

PubMed Central

de Jesus, Karla; Ayala, Helon V. H.; de Jesus, Kelly; Coelho, Leandro dos S.; Medeiros, Alexandre I.A.; Abraldes, José A.; Vaz, Mário A.P.; Fernandes, Ricardo J.; Vilas-Boas, João Paulo

2018-01-01

Abstract Our aim was to compare non-linear and linear mathematical model responses for backstroke start performance prediction. Ten swimmers randomly completed eight 15 m backstroke starts with feet over the wedge, four with hands on the highest horizontal and four on the vertical handgrip. Swimmers were videotaped using a dual media camera set-up, with the starts being performed over an instrumented block with four force plates. Artificial neural networks were applied to predict 5 m start time using kinematic and kinetic variables and to determine the accuracy of the mean absolute percentage error. Artificial neural networks predicted start time more robustly than the linear model with respect to changing training to the validation dataset for the vertical handgrip (3.95 ± 1.67 vs. 5.92 ± 3.27%). Artificial neural networks obtained a smaller mean absolute percentage error than the linear model in the horizontal (0.43 ± 0.19 vs. 0.98 ± 0.19%) and vertical handgrip (0.45 ± 0.19 vs. 1.38 ± 0.30%) using all input data. The best artificial neural network validation revealed a smaller mean absolute error than the linear model for the horizontal (0.007 vs. 0.04 s) and vertical handgrip (0.01 vs. 0.03 s). Artificial neural networks should be used for backstroke 5 m start time prediction due to the quite small differences among the elite level performances. PMID:29599857

Impact of uncertainties in free stream conditions on the aerodynamics of a rectangular cylinder

NASA Astrophysics Data System (ADS)

Mariotti, Alessandro; Shoeibi Omrani, Pejman; Witteveen, Jeroen; Salvetti, Maria Vittoria

2015-11-01

The BARC benchmark deals with the flow around a rectangular cylinder with chord-to-depth ratio equal to 5. This flow configuration is of practical interest for civil and industrial structures and it is characterized by massively separated flow and unsteadiness. In a recent review of BARC results, significant dispersion was observed both in experimental and numerical predictions of some flow quantities, which are extremely sensitive to various uncertainties, which may be present in experiments and simulations. Besides modeling and numerical errors, in simulations it is difficult to exactly reproduce the experimental conditions due to uncertainties in the set-up parameters, which sometimes cannot be exactly controlled or characterized. Probabilistic methods and URANS simulations are used to investigate the impact of the uncertainties in the following set-up parameters: the angle of incidence, the free stream longitudinal turbulence intensity and length scale. Stochastic collocation is employed to perform the probabilistic propagation of the uncertainty. The discretization and modeling errors are estimated by repeating the same analysis for different grids and turbulence models. The results obtained for different assumed PDF of the set-up parameters are also compared.

UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy

PubMed Central

2017-01-01

Unique Molecular Identifiers (UMIs) are random oligonucleotide barcodes that are increasingly used in high-throughput sequencing experiments. Through a UMI, identical copies arising from distinct molecules can be distinguished from those arising through PCR amplification of the same molecule. However, bioinformatic methods to leverage the information from UMIs have yet to be formalized. In particular, sequencing errors in the UMI sequence are often ignored or else resolved in an ad hoc manner. We show that errors in the UMI sequence are common and introduce network-based methods to account for these errors when identifying PCR duplicates. Using these methods, we demonstrate improved quantification accuracy both under simulated conditions and real iCLIP and single-cell RNA-seq data sets. Reproducibility between iCLIP replicates and single-cell RNA-seq clustering are both improved using our proposed network-based method, demonstrating the value of properly accounting for errors in UMIs. These methods are implemented in the open source UMI-tools software package. PMID:28100584

Sun compass error model

NASA Technical Reports Server (NTRS)

Blucker, T. J.; Ferry, W. W.

1971-01-01

An error model is described for the Apollo 15 sun compass, a contingency navigational device. Field test data are presented along with significant results of the test. The errors reported include a random error resulting from tilt in leveling the sun compass, a random error because of observer sighting inaccuracies, a bias error because of mean tilt in compass leveling, a bias error in the sun compass itself, and a bias error because the device is leveled to the local terrain slope.

Characterization of impulse noise and analysis of its effect upon correlation receivers

NASA Technical Reports Server (NTRS)

Houts, R. C.; Moore, J. D.

1971-01-01

A noise model is formulated to describe the impulse noise in many digital systems. A simplified model, which assumes that each noise burst contains a randomly weighted version of the same basic waveform, is used to derive the performance equations for a correlation receiver. The expected number of bit errors per noise burst is expressed as a function of the average signal energy, signal-set correlation coefficient, bit time, noise-weighting-factor variance and probability density function, and a time range function which depends on the crosscorrelation of the signal-set basis functions and the noise waveform. A procedure is established for extending the results for the simplified noise model to the general model. Unlike the performance results for Gaussian noise, it is shown that for impulse noise the error performance is affected by the choice of signal-set basis functions and that Orthogonal signaling is not equivalent to On-Off signaling with the same average energy.

Discretisation Schemes for Level Sets of Planar Gaussian Fields

NASA Astrophysics Data System (ADS)

Beliaev, D.; Muirhead, S.

2018-01-01

Smooth random Gaussian functions play an important role in mathematical physics, a main example being the random plane wave model conjectured by Berry to give a universal description of high-energy eigenfunctions of the Laplacian on generic compact manifolds. Our work is motivated by questions about the geometry of such random functions, in particular relating to the structure of their nodal and level sets. We study four discretisation schemes that extract information about level sets of planar Gaussian fields. Each scheme recovers information up to a different level of precision, and each requires a maximum mesh-size in order to be valid with high probability. The first two schemes are generalisations and enhancements of similar schemes that have appeared in the literature (Beffara and Gayet in Publ Math IHES, 2017. https://doi.org/10.1007/s10240-017-0093-0; Mischaikow and Wanner in Ann Appl Probab 17:980-1018, 2007); these give complete topological information about the level sets on either a local or global scale. As an application, we improve the results in Beffara and Gayet (2017) on Russo-Seymour-Welsh estimates for the nodal set of positively-correlated planar Gaussian fields. The third and fourth schemes are, to the best of our knowledge, completely new. The third scheme is specific to the nodal set of the random plane wave, and provides global topological information about the nodal set up to `visible ambiguities'. The fourth scheme gives a way to approximate the mean number of excursion domains of planar Gaussian fields.

Ensemble-type numerical uncertainty information from single model integrations

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

Rauser, Florian, E-mail: florian.rauser@mpimet.mpg.de; Marotzke, Jochem; Korn, Peter

2015-07-01

We suggest an algorithm that quantifies the discretization error of time-dependent physical quantities of interest (goals) for numerical models of geophysical fluid dynamics. The goal discretization error is estimated using a sum of weighted local discretization errors. The key feature of our algorithm is that these local discretization errors are interpreted as realizations of a random process. The random process is determined by the model and the flow state. From a class of local error random processes we select a suitable specific random process by integrating the model over a short time interval at different resolutions. The weights of themore » influences of the local discretization errors on the goal are modeled as goal sensitivities, which are calculated via automatic differentiation. The integration of the weighted realizations of local error random processes yields a posterior ensemble of goal approximations from a single run of the numerical model. From the posterior ensemble we derive the uncertainty information of the goal discretization error. This algorithm bypasses the requirement of detailed knowledge about the models discretization to generate numerical error estimates. The algorithm is evaluated for the spherical shallow-water equations. For two standard test cases we successfully estimate the error of regional potential energy, track its evolution, and compare it to standard ensemble techniques. The posterior ensemble shares linear-error-growth properties with ensembles of multiple model integrations when comparably perturbed. The posterior ensemble numerical error estimates are of comparable size as those of a stochastic physics ensemble.« less

Impact of spot charge inaccuracies in IMPT treatments.

PubMed

Kraan, Aafke C; Depauw, Nicolas; Clasie, Ben; Giunta, Marina; Madden, Tom; Kooy, Hanne M

2017-08-01

Spot charge is one parameter of pencil-beam scanning dose delivery system whose accuracy is typically high but whose required value has not been investigated. In this work we quantify the dose impact of spot charge inaccuracies on the dose distribution in patients. Knowing the effect of charge errors is relevant for conventional proton machines, as well as for new generation proton machines, where ensuring accurate charge may be challenging. Through perturbation of spot charge in treatment plans for seven patients and a phantom, we evaluated the dose impact of absolute (up to 5× 10 6 protons) and relative (up to 30%) charge errors. We investigated the dependence on beam width by studying scenarios with small, medium and large beam sizes. Treatment plan statistics included the Γ passing rate, dose-volume-histograms and dose differences. The allowable absolute charge error for small spot plans was about 2× 10 6 protons. Larger limits would be allowed if larger spots were used. For relative errors, the maximum allowable error size for small, medium and large spots was about 13%, 8% and 6% for small, medium and large spots, respectively. Dose distributions turned out to be surprisingly robust against random spot charge perturbation. Our study suggests that ensuring spot charge errors as small as 1-2% as is commonly aimed at in conventional proton therapy machines, is clinically not strictly needed. © 2017 American Association of Physicists in Medicine.

SU-E-T-195: Gantry Angle Dependency of MLC Leaf Position Error

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

Ju, S; Hong, C; Kim, M

Purpose: The aim of this study was to investigate the gantry angle dependency of the multileaf collimator (MLC) leaf position error. Methods: An automatic MLC quality assurance system (AutoMLCQA) was developed to evaluate the gantry angle dependency of the MLC leaf position error using an electronic portal imaging device (EPID). To eliminate the EPID position error due to gantry rotation, we designed a reference maker (RM) that could be inserted into the wedge mount. After setting up the EPID, a reference image was taken of the RM using an open field. Next, an EPID-based picket-fence test (PFT) was performed withoutmore » the RM. These procedures were repeated at every 45° intervals of the gantry angle. A total of eight reference images and PFT image sets were analyzed using in-house software. The average MLC leaf position error was calculated at five pickets (-10, -5, 0, 5, and 10 cm) in accordance with general PFT guidelines using in-house software. This test was carried out for four linear accelerators. Results: The average MLC leaf position errors were within the set criterion of <1 mm (actual errors ranged from -0.7 to 0.8 mm) for all gantry angles, but significant gantry angle dependency was observed in all machines. The error was smaller at a gantry angle of 0° but increased toward the positive direction with gantry angle increments in the clockwise direction. The error reached a maximum value at a gantry angle of 90° and then gradually decreased until 180°. In the counter-clockwise rotation of the gantry, the same pattern of error was observed but the error increased in the negative direction. Conclusion: The AutoMLCQA system was useful to evaluate the MLC leaf position error for various gantry angles without the EPID position error. The Gantry angle dependency should be considered during MLC leaf position error analysis.« less

Quantification of errors in ordinal outcome scales using shannon entropy: effect on sample size calculations.

PubMed

Mandava, Pitchaiah; Krumpelman, Chase S; Shah, Jharna N; White, Donna L; Kent, Thomas A

2013-01-01

Clinical trial outcomes often involve an ordinal scale of subjective functional assessments but the optimal way to quantify results is not clear. In stroke, the most commonly used scale, the modified Rankin Score (mRS), a range of scores ("Shift") is proposed as superior to dichotomization because of greater information transfer. The influence of known uncertainties in mRS assessment has not been quantified. We hypothesized that errors caused by uncertainties could be quantified by applying information theory. Using Shannon's model, we quantified errors of the "Shift" compared to dichotomized outcomes using published distributions of mRS uncertainties and applied this model to clinical trials. We identified 35 randomized stroke trials that met inclusion criteria. Each trial's mRS distribution was multiplied with the noise distribution from published mRS inter-rater variability to generate an error percentage for "shift" and dichotomized cut-points. For the SAINT I neuroprotectant trial, considered positive by "shift" mRS while the larger follow-up SAINT II trial was negative, we recalculated sample size required if classification uncertainty was taken into account. Considering the full mRS range, error rate was 26.1%±5.31 (Mean±SD). Error rates were lower for all dichotomizations tested using cut-points (e.g. mRS 1; 6.8%±2.89; overall p<0.001). Taking errors into account, SAINT I would have required 24% more subjects than were randomized. We show when uncertainty in assessments is considered, the lowest error rates are with dichotomization. While using the full range of mRS is conceptually appealing, a gain of information is counter-balanced by a decrease in reliability. The resultant errors need to be considered since sample size may otherwise be underestimated. In principle, we have outlined an approach to error estimation for any condition in which there are uncertainties in outcome assessment. We provide the user with programs to calculate and incorporate errors into sample size estimation.

Specificity of Atmosphere Correction of Satellite Ocean Color Data in Far-Eastern Region

NASA Astrophysics Data System (ADS)

Trusenkova, O.; Kachur, V.; Aleksanin, A. I.

2016-02-01

It was carried out an error analysis of satellite reflectance coefficients (Rrs) of MODIS/AQUA colour data for two atmospheric correction algorithms (NIR, MUMM) in the Far-Eastern region. Some sets of unique data of in situ and satellite measurements have been analysed. A set has some measurements with ASD spectroradiometer for each satellite pass. The measurement allocations were selected so the Chlorophyll-a concentration has high variability. Analysis of arbitrary set demonstrated that the main error component is systematic error, and it has simple relations on Rrs values. The reasons of such error behavior are considered. The most probable explanation of the large errors of oceanic color parameters in the Far-Eastern region is the ability of high concentrations of continental aerosol. A comparison of satellite and in situ measurements at AERONET stations of USA and South Korea regions has been made. It was shown that for NIR-correction of the atmosphere influence the error values in these two regions have differences up to 10 times for almost the same water turbidity and relatively good accuracy of computation of aerosol optical thickness. The study was supported by grant Russian Scientific Foundation No. 14-50-00034, by grant of Russian Foundation of Basic Research No.15-35-21032-mol-a-ved, and by Program of Basic Research "Far East" of Far Eastern Branch of Russian Academy of Sciences.

Animation and radiobiological analysis of 3D motion in conformal radiotherapy.

PubMed

MacKay, R I; Graham, P A; Moore, C J; Logue, J P; Sharrock, P J

1999-07-01

To allow treatment plans to be evaluated against the range of expected organ motion and set up error anticipated during treatment. Planning tools have been developed to allow concurrent animation and radiobiological analysis of three dimensional (3D) target and organ motion in conformal radiotherapy. Surfaces fitted to structures outlined on CT studies are projected onto pre-treatment images or onto megavoltage images collected during the patient treatment. Visual simulation of tumour and normal tissue movement is then performed by the application of three dimensional affine transformations, to the selected surface. Concurrent registration of the surface motion with the 3D dose distribution allows calculation of the change in dose to the volume. Realistic patterns of motion can be applied to the structure to simulate inter-fraction motion and set-up error. The biologically effective dose for the structure is calculated for each fraction as the surface moves over the course of the treatment and is used to calculate the normal tissue complication probability (NTCP) or tumour control probability (TCP) for the moving structure. The tool has been used to evaluate conformal therapy plans against set up measurements recorded during patient treatments. NTCP and TCP were calculated for a patient whose set up had been corrected after systematic deviations from plan geometry were measured during treatment, the effect of not making the correction were also assessed. TCP for the moving tumour was reduced if inadequate margins were set for the treatment. Modelling suggests that smaller margins could have been set for the set up corrected during the course of the treatment. The NTCP for the rectum was also higher for the uncorrected set up due to a more rectal tissue falling in the high dose region. This approach provides a simple way for clinical users to utilise information incrementally collected throughout the whole of a patient's treatment. In particular it is possible to test the robustness of a patient plan against a range of possible motion patterns. The methods described represent a move from the inspection of static pre-treatment plans to a review of the dynamic treatment.

Random errors in interferometry with the least-squares method

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

Wang Qi

2011-01-20

This investigation analyzes random errors in interferometric surface profilers using the least-squares method when random noises are present. Two types of random noise are considered here: intensity noise and position noise. Two formulas have been derived for estimating the standard deviations of the surface height measurements: one is for estimating the standard deviation when only intensity noise is present, and the other is for estimating the standard deviation when only position noise is present. Measurements on simulated noisy interferometric data have been performed, and standard deviations of the simulated measurements have been compared with those theoretically derived. The relationships havemore » also been discussed between random error and the wavelength of the light source and between random error and the amplitude of the interference fringe.« less

Multiple Intravenous Infusions Phase 2b: Laboratory Study

PubMed Central

Pinkney, Sonia; Fan, Mark; Chan, Katherine; Koczmara, Christine; Colvin, Christopher; Sasangohar, Farzan; Masino, Caterina; Easty, Anthony; Trbovich, Patricia

2014-01-01

Background Administering multiple intravenous (IV) infusions to a single patient via infusion pump occurs routinely in health care, but there has been little empirical research examining the risks associated with this practice or ways to mitigate those risks. Objectives To identify the risks associated with multiple IV infusions and assess the impact of interventions on nurses’ ability to safely administer them. Data Sources and Review Methods Forty nurses completed infusion-related tasks in a simulated adult intensive care unit, with and without interventions (i.e., repeated-measures design). Results Errors were observed in completing common tasks associated with the administration of multiple IV infusions, including the following (all values from baseline, which was current practice): setting up and programming multiple primary continuous IV infusions (e.g., 11.7% programming errors) identifying IV infusions (e.g., 7.7% line-tracing errors) managing dead volume (e.g., 96.0% flush rate errors following IV syringe dose administration) setting up a secondary intermittent IV infusion (e.g., 11.3% secondary clamp errors) administering an IV pump bolus (e.g., 11.5% programming errors) Of 10 interventions tested, 6 (1 practice, 3 technology, and 2 educational) significantly decreased or even eliminated errors compared to baseline. Limitations The simulation of an adult intensive care unit at 1 hospital limited the ability to generalize results. The study results were representative of nurses who received training in the interventions but had little experience using them. The longitudinal effects of the interventions were not studied. Conclusions Administering and managing multiple IV infusions is a complex and risk-prone activity. However, when a patient requires multiple IV infusions, targeted interventions can reduce identified risks. A combination of standardized practice, technology improvements, and targeted education is required. PMID:26316919

Gram-negative and -positive bacteria differentiation in blood culture samples by headspace volatile compound analysis.

PubMed

Dolch, Michael E; Janitza, Silke; Boulesteix, Anne-Laure; Graßmann-Lichtenauer, Carola; Praun, Siegfried; Denzer, Wolfgang; Schelling, Gustav; Schubert, Sören

2016-12-01

Identification of microorganisms in positive blood cultures still relies on standard techniques such as Gram staining followed by culturing with definite microorganism identification. Alternatively, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry or the analysis of headspace volatile compound (VC) composition produced by cultures can help to differentiate between microorganisms under experimental conditions. This study assessed the efficacy of volatile compound based microorganism differentiation into Gram-negatives and -positives in unselected positive blood culture samples from patients. Headspace gas samples of positive blood culture samples were transferred to sterilized, sealed, and evacuated 20 ml glass vials and stored at -30 °C until batch analysis. Headspace gas VC content analysis was carried out via an auto sampler connected to an ion-molecule reaction mass spectrometer (IMR-MS). Measurements covered a mass range from 16 to 135 u including CO2, H2, N2, and O2. Prediction rules for microorganism identification based on VC composition were derived using a training data set and evaluated using a validation data set within a random split validation procedure. One-hundred-fifty-two aerobic samples growing 27 Gram-negatives, 106 Gram-positives, and 19 fungi and 130 anaerobic samples growing 37 Gram-negatives, 91 Gram-positives, and two fungi were analysed. In anaerobic samples, ten discriminators were identified by the random forest method allowing for bacteria differentiation into Gram-negative and -positive (error rate: 16.7 % in validation data set). For aerobic samples the error rate was not better than random. In anaerobic blood culture samples of patients IMR-MS based headspace VC composition analysis facilitates bacteria differentiation into Gram-negative and -positive.

3D statistical shape models incorporating 3D random forest regression voting for robust CT liver segmentation

NASA Astrophysics Data System (ADS)

Norajitra, Tobias; Meinzer, Hans-Peter; Maier-Hein, Klaus H.

2015-03-01

During image segmentation, 3D Statistical Shape Models (SSM) usually conduct a limited search for target landmarks within one-dimensional search profiles perpendicular to the model surface. In addition, landmark appearance is modeled only locally based on linear profiles and weak learners, altogether leading to segmentation errors from landmark ambiguities and limited search coverage. We present a new method for 3D SSM segmentation based on 3D Random Forest Regression Voting. For each surface landmark, a Random Regression Forest is trained that learns a 3D spatial displacement function between the according reference landmark and a set of surrounding sample points, based on an infinite set of non-local randomized 3D Haar-like features. Landmark search is then conducted omni-directionally within 3D search spaces, where voxelwise forest predictions on landmark position contribute to a common voting map which reflects the overall position estimate. Segmentation experiments were conducted on a set of 45 CT volumes of the human liver, of which 40 images were randomly chosen for training and 5 for testing. Without parameter optimization, using a simple candidate selection and a single resolution approach, excellent results were achieved, while faster convergence and better concavity segmentation were observed, altogether underlining the potential of our approach in terms of increased robustness from distinct landmark detection and from better search coverage.

Accelerated 1 H MRSI using randomly undersampled spiral-based k-space trajectories.

PubMed

Chatnuntawech, Itthi; Gagoski, Borjan; Bilgic, Berkin; Cauley, Stephen F; Setsompop, Kawin; Adalsteinsson, Elfar

2014-07-30

To develop and evaluate the performance of an acquisition and reconstruction method for accelerated MR spectroscopic imaging (MRSI) through undersampling of spiral trajectories. A randomly undersampled spiral acquisition and sensitivity encoding (SENSE) with total variation (TV) regularization, random SENSE+TV, is developed and evaluated on single-slice numerical phantom, in vivo single-slice MRSI, and in vivo three-dimensional (3D)-MRSI at 3 Tesla. Random SENSE+TV was compared with five alternative methods for accelerated MRSI. For the in vivo single-slice MRSI, random SENSE+TV yields up to 2.7 and 2 times reduction in root-mean-square error (RMSE) of reconstructed N-acetyl aspartate (NAA), creatine, and choline maps, compared with the denoised fully sampled and uniformly undersampled SENSE+TV methods with the same acquisition time, respectively. For the in vivo 3D-MRSI, random SENSE+TV yields up to 1.6 times reduction in RMSE, compared with uniform SENSE+TV. Furthermore, by using random SENSE+TV, we have demonstrated on the in vivo single-slice and 3D-MRSI that acceleration factors of 4.5 and 4 are achievable with the same quality as the fully sampled data, as measured by RMSE of reconstructed NAA map, respectively. With the same scan time, random SENSE+TV yields lower RMSEs of metabolite maps than other methods evaluated. Random SENSE+TV achieves up to 4.5-fold acceleration with comparable data quality as the fully sampled acquisition. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc. © 2014 Wiley Periodicals, Inc.

Previous Estimates of Mitochondrial DNA Mutation Level Variance Did Not Account for Sampling Error: Comparing the mtDNA Genetic Bottleneck in Mice and Humans

PubMed Central

Wonnapinij, Passorn; Chinnery, Patrick F.; Samuels, David C.

2010-01-01

In cases of inherited pathogenic mitochondrial DNA (mtDNA) mutations, a mother and her offspring generally have large and seemingly random differences in the amount of mutated mtDNA that they carry. Comparisons of measured mtDNA mutation level variance values have become an important issue in determining the mechanisms that cause these large random shifts in mutation level. These variance measurements have been made with samples of quite modest size, which should be a source of concern because higher-order statistics, such as variance, are poorly estimated from small sample sizes. We have developed an analysis of the standard error of variance from a sample of size n, and we have defined error bars for variance measurements based on this standard error. We calculate variance error bars for several published sets of measurements of mtDNA mutation level variance and show how the addition of the error bars alters the interpretation of these experimental results. We compare variance measurements from human clinical data and from mouse models and show that the mutation level variance is clearly higher in the human data than it is in the mouse models at both the primary oocyte and offspring stages of inheritance. We discuss how the standard error of variance can be used in the design of experiments measuring mtDNA mutation level variance. Our results show that variance measurements based on fewer than 20 measurements are generally unreliable and ideally more than 50 measurements are required to reliably compare variances with less than a 2-fold difference. PMID:20362273

A gamma-ray testing technique for spacecraft. [considering cosmic radiation effects

NASA Technical Reports Server (NTRS)

Gribov, B. S.; Repin, N. N.; Sakovich, V. A.; Sakharov, V. M.

1977-01-01

The simulated cosmic radiation effect on a spacecraft structure is evaluated by gamma ray testing in relation to structural thickness. A drawing of the test set-up is provided and measurement errors are discussed.

Acceptability of Home-Assessment Post Medical Abortion and Medical Abortion in a Low-Resource Setting in Rajasthan, India. Secondary Outcome Analysis of a Non-Inferiority Randomized Controlled Trial

PubMed Central

Paul, Mandira; Iyengar, Kirti; Essén, Birgitta; Gemzell-Danielsson, Kristina; Iyengar, Sharad D.; Bring, Johan; Soni, Sunita; Klingberg-Allvin, Marie

2015-01-01

Background Studies evaluating acceptability of simplified follow-up after medical abortion have focused on high-resource or urban settings where telephones, road connections, and modes of transport are available and where women have formal education. Objective To investigate women’s acceptability of home-assessment of abortion and whether acceptability of medical abortion differs by in-clinic or home-assessment of abortion outcome in a low-resource setting in India. Design Secondary outcome of a randomised, controlled, non-inferiority trial. Setting Outpatient primary health care clinics in rural and urban Rajasthan, India. Population Women were eligible if they sought abortion with a gestation up to 9 weeks, lived within defined study area and agreed to follow-up. Women were ineligible if they had known contraindications to medical abortion, haemoglobin < 85mg/l and were below 18 years. Methods Abortion outcome assessment through routine clinic follow-up by a doctor was compared with home-assessment using a low-sensitivity pregnancy test and a pictorial instruction sheet. A computerized random number generator generated the randomisation sequence (1:1) in blocks of six. Research assistants randomly allocated eligible women who opted for medical abortion (mifepristone and misoprostol), using opaque sealed envelopes. Blinding during outcome assessment was not possible. Main Outcome Measures Women’s acceptability of home-assessment was measured as future preference of follow-up. Overall satisfaction, expectations, and comparison with previous abortion experiences were compared between study groups. Results 731 women were randomized to the clinic follow-up group (n = 353) or home-assessment group (n = 378). 623 (85%) women were successfully followed up, of those 597 (96%) were satisfied and 592 (95%) found the abortion better or as expected, with no difference between study groups. The majority, 355 (57%) women, preferred home-assessment in the event of a future abortion. Significantly more women, 284 (82%), in the home-assessment group preferred home-assessment in the future, as compared with 188 (70%) of women in the clinic follow-up group, who preferred clinic follow-up in the future (p < 0.001). Conclusion Home-assessment is highly acceptable among women in low-resource, and rural, settings. The choice to follow-up an early medical abortion according to women’s preference should be offered to foster women’s reproductive autonomy. Trial Registration ClinicalTrials.gov NCT01827995 PMID:26327217

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

Meyer, Jeff, E-mail: jmeye3@utsouthwestern.ed; Bluett, Jaques; Amos, Richard

Purpose: Conventional proton therapy with passively scattered beams is used to treat a number of tumor sites, including prostate cancer. Spot scanning proton therapy is a treatment delivery means that improves conformal coverage of the clinical target volume (CTV). Placement of individual spots within a target is dependent on traversed tissue density. Errors in patient alignment perturb dose distributions. Moreover, there is a need for a rational planning approach that can mitigate the dosimetric effect of random alignment errors. We propose a treatment planning approach and then analyze the consequences of various simulated alignment errors on prostate treatments. Methods andmore » Materials: Ten control patients with localized prostate cancer underwent treatment planning for spot scanning proton therapy. After delineation of the clinical target volume, a scanning target volume (STV) was created to guide dose coverage. Errors in patient alignment in two axes (rotational and yaw) as well as translational errors in the anteroposterior direction were then simulated, and dose to the CTV and normal tissues were reanalyzed. Results: Coverage of the CTV remained high even in the setting of extreme rotational and yaw misalignments. Changes in the rectum and bladder V45 and V70 were similarly minimal, except in the case of translational errors, where, as a result of opposed lateral beam arrangements, much larger dosimetric perturbations were observed. Conclusions: The concept of the STV as applied to spot scanning radiation therapy and as presented in this report leads to robust coverage of the CTV even in the setting of extreme patient misalignments.« less

Error modeling for surrogates of dynamical systems using machine learning: Machine-learning-based error model for surrogates of dynamical systems

DOE PAGES

Trehan, Sumeet; Carlberg, Kevin T.; Durlofsky, Louis J.

2017-07-14

A machine learning–based framework for modeling the error introduced by surrogate models of parameterized dynamical systems is proposed. The framework entails the use of high-dimensional regression techniques (eg, random forests, and LASSO) to map a large set of inexpensively computed “error indicators” (ie, features) produced by the surrogate model at a given time instance to a prediction of the surrogate-model error in a quantity of interest (QoI). This eliminates the need for the user to hand-select a small number of informative features. The methodology requires a training set of parameter instances at which the time-dependent surrogate-model error is computed bymore » simulating both the high-fidelity and surrogate models. Using these training data, the method first determines regression-model locality (via classification or clustering) and subsequently constructs a “local” regression model to predict the time-instantaneous error within each identified region of feature space. We consider 2 uses for the resulting error model: (1) as a correction to the surrogate-model QoI prediction at each time instance and (2) as a way to statistically model arbitrary functions of the time-dependent surrogate-model error (eg, time-integrated errors). We then apply the proposed framework to model errors in reduced-order models of nonlinear oil-water subsurface flow simulations, with time-varying well-control (bottom-hole pressure) parameters. The reduced-order models used in this work entail application of trajectory piecewise linearization in conjunction with proper orthogonal decomposition. Moreover, when the first use of the method is considered, numerical experiments demonstrate consistent improvement in accuracy in the time-instantaneous QoI prediction relative to the original surrogate model, across a large number of test cases. When the second use is considered, results show that the proposed method provides accurate statistical predictions of the time- and well-averaged errors.« less

Error modeling for surrogates of dynamical systems using machine learning: Machine-learning-based error model for surrogates of dynamical systems

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

Trehan, Sumeet; Carlberg, Kevin T.; Durlofsky, Louis J.

A machine learning–based framework for modeling the error introduced by surrogate models of parameterized dynamical systems is proposed. The framework entails the use of high-dimensional regression techniques (eg, random forests, and LASSO) to map a large set of inexpensively computed “error indicators” (ie, features) produced by the surrogate model at a given time instance to a prediction of the surrogate-model error in a quantity of interest (QoI). This eliminates the need for the user to hand-select a small number of informative features. The methodology requires a training set of parameter instances at which the time-dependent surrogate-model error is computed bymore » simulating both the high-fidelity and surrogate models. Using these training data, the method first determines regression-model locality (via classification or clustering) and subsequently constructs a “local” regression model to predict the time-instantaneous error within each identified region of feature space. We consider 2 uses for the resulting error model: (1) as a correction to the surrogate-model QoI prediction at each time instance and (2) as a way to statistically model arbitrary functions of the time-dependent surrogate-model error (eg, time-integrated errors). We then apply the proposed framework to model errors in reduced-order models of nonlinear oil-water subsurface flow simulations, with time-varying well-control (bottom-hole pressure) parameters. The reduced-order models used in this work entail application of trajectory piecewise linearization in conjunction with proper orthogonal decomposition. Moreover, when the first use of the method is considered, numerical experiments demonstrate consistent improvement in accuracy in the time-instantaneous QoI prediction relative to the original surrogate model, across a large number of test cases. When the second use is considered, results show that the proposed method provides accurate statistical predictions of the time- and well-averaged errors.« less

A description of medication errors reported by pharmacists in a neonatal intensive care unit.

PubMed

Pawluk, Shane; Jaam, Myriam; Hazi, Fatima; Al Hail, Moza Sulaiman; El Kassem, Wessam; Khalifa, Hanan; Thomas, Binny; Abdul Rouf, Pallivalappila

2017-02-01

Background Patients in the Neonatal Intensive Care Unit (NICU) are at an increased risk for medication errors. Objective The objective of this study is to describe the nature and setting of medication errors occurring in patients admitted to an NICU in Qatar based on a standard electronic system reported by pharmacists. Setting Neonatal intensive care unit, Doha, Qatar. Method This was a retrospective cross-sectional study on medication errors reported electronically by pharmacists in the NICU between January 1, 2014 and April 30, 2015. Main outcome measure Data collected included patient information, and incident details including error category, medications involved, and follow-up completed. Results A total of 201 NICU pharmacists-reported medication errors were submitted during the study period. All reported errors did not reach the patient and did not cause harm. Of the errors reported, 98.5% occurred in the prescribing phase of the medication process with 58.7% being due to calculation errors. Overall, 53 different medications were documented in error reports with the anti-infective agents being the most frequently cited. The majority of incidents indicated that the primary prescriber was contacted and the error was resolved before reaching the next phase of the medication process. Conclusion Medication errors reported by pharmacists occur most frequently in the prescribing phase of the medication process. Our data suggest that error reporting systems need to be specific to the population involved. Special attention should be paid to frequently used medications in the NICU as these were responsible for the greatest numbers of medication errors.

Estimation After a Group Sequential Trial.

PubMed

Milanzi, Elasma; Molenberghs, Geert; Alonso, Ariel; Kenward, Michael G; Tsiatis, Anastasios A; Davidian, Marie; Verbeke, Geert

2015-10-01

Group sequential trials are one important instance of studies for which the sample size is not fixed a priori but rather takes one of a finite set of pre-specified values, dependent on the observed data. Much work has been devoted to the inferential consequences of this design feature. Molenberghs et al (2012) and Milanzi et al (2012) reviewed and extended the existing literature, focusing on a collection of seemingly disparate, but related, settings, namely completely random sample sizes, group sequential studies with deterministic and random stopping rules, incomplete data, and random cluster sizes. They showed that the ordinary sample average is a viable option for estimation following a group sequential trial, for a wide class of stopping rules and for random outcomes with a distribution in the exponential family. Their results are somewhat surprising in the sense that the sample average is not optimal, and further, there does not exist an optimal, or even, unbiased linear estimator. However, the sample average is asymptotically unbiased, both conditionally upon the observed sample size as well as marginalized over it. By exploiting ignorability they showed that the sample average is the conventional maximum likelihood estimator. They also showed that a conditional maximum likelihood estimator is finite sample unbiased, but is less efficient than the sample average and has the larger mean squared error. Asymptotically, the sample average and the conditional maximum likelihood estimator are equivalent. This previous work is restricted, however, to the situation in which the the random sample size can take only two values, N = n or N = 2 n . In this paper, we consider the more practically useful setting of sample sizes in a the finite set { n 1 , n 2 , …, n L }. It is shown that the sample average is then a justifiable estimator , in the sense that it follows from joint likelihood estimation, and it is consistent and asymptotically unbiased. We also show why simulations can give the false impression of bias in the sample average when considered conditional upon the sample size. The consequence is that no corrections need to be made to estimators following sequential trials. When small-sample bias is of concern, the conditional likelihood estimator provides a relatively straightforward modification to the sample average. Finally, it is shown that classical likelihood-based standard errors and confidence intervals can be applied, obviating the need for technical corrections.

Extension of sonic anemometry to high subsonic Mach number flows

NASA Astrophysics Data System (ADS)

Otero, R.; Lowe, K. T.; Ng, W. F.

2017-03-01

In the literature, the application of sonic anemometry has been limited to low subsonic Mach number, near-incompressible flow conditions. To the best of the authors’ knowledge, this paper represents the first time a sonic anemometry approach has been used to characterize flow velocity beyond Mach 0.3. Using a high speed jet, flow velocity was measured using a modified sonic anemometry technique in flow conditions up to Mach 0.83. A numerical study was conducted to identify the effects of microphone placement on the accuracy of the measured velocity. Based on estimated error strictly due to uncertainty in time-of-acoustic flight, a random error of +/- 4 m s-1 was identified for the configuration used in this experiment. Comparison with measurements from a Pitot probe indicated a velocity RMS error of +/- 9 m s-1. The discrepancy in error is attributed to a systematic error which may be calibrated out in future work. Overall, the experimental results from this preliminary study support the use of acoustics for high subsonic flow characterization.

Ketamine Effects on Memory Reconsolidation Favor a Learning Model of Delusions

PubMed Central

Gardner, Jennifer M.; Piggot, Jennifer S.; Turner, Danielle C.; Everitt, Jessica C.; Arana, Fernando Sergio; Morgan, Hannah L.; Milton, Amy L.; Lee, Jonathan L.; Aitken, Michael R. F.; Dickinson, Anthony; Everitt, Barry J.; Absalom, Anthony R.; Adapa, Ram; Subramanian, Naresh; Taylor, Jane R.; Krystal, John H.; Fletcher, Paul C.

2013-01-01

Delusions are the persistent and often bizarre beliefs that characterise psychosis. Previous studies have suggested that their emergence may be explained by disturbances in prediction error-dependent learning. Here we set up complementary studies in order to examine whether such a disturbance also modulates memory reconsolidation and hence explains their remarkable persistence. First, we quantified individual brain responses to prediction error in a causal learning task in 18 human subjects (8 female). Next, a placebo-controlled within-subjects study of the impact of ketamine was set up on the same individuals. We determined the influence of this NMDA receptor antagonist (previously shown to induce aberrant prediction error signal and lead to transient alterations in perception and belief) on the evolution of a fear memory over a 72 hour period: they initially underwent Pavlovian fear conditioning; 24 hours later, during ketamine or placebo administration, the conditioned stimulus (CS) was presented once, without reinforcement; memory strength was then tested again 24 hours later. Re-presentation of the CS under ketamine led to a stronger subsequent memory than under placebo. Moreover, the degree of strengthening correlated with individual vulnerability to ketamine's psychotogenic effects and with prediction error brain signal. This finding was partially replicated in an independent sample with an appetitive learning procedure (in 8 human subjects, 4 female). These results suggest a link between altered prediction error, memory strength and psychosis. They point to a core disruption that may explain not only the emergence of delusional beliefs but also their persistence. PMID:23776445

Accounting for hardware imperfections in EIT image reconstruction algorithms.

PubMed

Hartinger, Alzbeta E; Gagnon, Hervé; Guardo, Robert

2007-07-01

Electrical impedance tomography (EIT) is a non-invasive technique for imaging the conductivity distribution of a body section. Different types of EIT images can be reconstructed: absolute, time difference and frequency difference. Reconstruction algorithms are sensitive to many errors which translate into image artefacts. These errors generally result from incorrect modelling or inaccurate measurements. Every reconstruction algorithm incorporates a model of the physical set-up which must be as accurate as possible since any discrepancy with the actual set-up will cause image artefacts. Several methods have been proposed in the literature to improve the model realism, such as creating anatomical-shaped meshes, adding a complete electrode model and tracking changes in electrode contact impedances and positions. Absolute and frequency difference reconstruction algorithms are particularly sensitive to measurement errors and generally assume that measurements are made with an ideal EIT system. Real EIT systems have hardware imperfections that cause measurement errors. These errors translate into image artefacts since the reconstruction algorithm cannot properly discriminate genuine measurement variations produced by the medium under study from those caused by hardware imperfections. We therefore propose a method for eliminating these artefacts by integrating a model of the system hardware imperfections into the reconstruction algorithms. The effectiveness of the method has been evaluated by reconstructing absolute, time difference and frequency difference images with and without the hardware model from data acquired on a resistor mesh phantom. Results have shown that artefacts are smaller for images reconstructed with the model, especially for frequency difference imaging.

Why a simulation system doesn`t match the plant

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

Sowell, R.

1998-03-01

Process simulations, or mathematical models, are widely used by plant engineers and planners to obtain a better understanding of a particular process. These simulations are used to answer questions such as how can feed rate be increased, how can yields be improved, how can energy consumption be decreased, or how should the available independent variables be set to maximize profit? Although current process simulations are greatly improved over those of the `70s and `80s, there are many reasons why a process simulation doesn`t match the plant. Understanding these reasons can assist in using simulations to maximum advantage. The reasons simulationsmore » do not match the plant may be placed in three main categories: simulation effects or inherent error, sampling and analysis effects of measurement error, and misapplication effects or set-up error.« less

Random forests of interaction trees for estimating individualized treatment effects in randomized trials.

PubMed

Su, Xiaogang; Peña, Annette T; Liu, Lei; Levine, Richard A

2018-04-29

Assessing heterogeneous treatment effects is a growing interest in advancing precision medicine. Individualized treatment effects (ITEs) play a critical role in such an endeavor. Concerning experimental data collected from randomized trials, we put forward a method, termed random forests of interaction trees (RFIT), for estimating ITE on the basis of interaction trees. To this end, we propose a smooth sigmoid surrogate method, as an alternative to greedy search, to speed up tree construction. The RFIT outperforms the "separate regression" approach in estimating ITE. Furthermore, standard errors for the estimated ITE via RFIT are obtained with the infinitesimal jackknife method. We assess and illustrate the use of RFIT via both simulation and the analysis of data from an acupuncture headache trial. Copyright © 2018 John Wiley & Sons, Ltd.

Incorporating a prediction of postgrazing herbage mass into a whole-farm model for pasture-based dairy systems.

PubMed

Gregorini, P; Galli, J; Romera, A J; Levy, G; Macdonald, K A; Fernandez, H H; Beukes, P C

2014-07-01

The DairyNZ whole-farm model (WFM; DairyNZ, Hamilton, New Zealand) consists of a framework that links component models for animal, pastures, crops, and soils. The model was developed to assist with analysis and design of pasture-based farm systems. New (this work) and revised (e.g., cow, pasture, crops) component models can be added to the WFM, keeping the model flexible and up to date. Nevertheless, the WFM does not account for plant-animal relationships determining herbage-depletion dynamics. The user has to preset the maximum allowable level of herbage depletion [i.e., postgrazing herbage mass (residuals)] throughout the year. Because residuals have a direct effect on herbage regrowth, the WFM in its current form does not dynamically simulate the effect of grazing pressure on herbage depletion and consequent effect on herbage regrowth. The management of grazing pressure is a key component of pasture-based dairy systems. Thus, the main objective of the present work was to develop a new version of the WFM able to predict residuals, and thereby simulate related effects of grazing pressure dynamically at the farm scale. This objective was accomplished by incorporating a new component model into the WFM. This model represents plant-animal relationships, for example sward structure and herbage intake rate, and resulting level of herbage depletion. The sensitivity of the new version of the WFM was evaluated and then the new WFM was tested against an experimental data set previously used to evaluate the WFM and to illustrate the adequacy and improvement of the model development. Key outputs variables of the new version pertinent to this work (milk production, herbage dry matter intake, intake rate, harvesting efficiency, and residuals) responded acceptably to a range of input variables. The relative prediction errors for monthly and mean annual residual predictions were 20 and 5%, respectively. Monthly predictions of residuals had a line bias (1.5%), with a proportion of square root of mean square prediction error (RMSPE) due to random error of 97.5%. Predicted monthly herbage growth rates had a line bias of 2%, a proportion of RMSPE due to random error of 96%, and a concordance correlation coefficient of 0.87. Annual herbage production was predicted with an RMSPE of 531 (kg of herbage dry matter/ha per year), a line bias of 11%, a proportion of RMSPE due to random error of 80%, and relative prediction errors of 2%. Annual herbage dry matter intake per cow and hectare, both per year, were predicted with RMSPE, relative prediction error, and concordance correlation coefficient of 169 and 692kg of dry matter, 3 and 4%, and 0.91 and 0.87, respectively. These results indicate that predictions of the new WFM are relatively accurate and precise, with a conclusion that incorporating a plant-animal relationship model into the WFM allows for dynamic predictions of residuals and more realistic simulations of the effect of grazing pressure on herbage production and intake at the farm level without the intervention from the user. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Finite-time synchronization of stochastic coupled neural networks subject to Markovian switching and input saturation.

PubMed

Selvaraj, P; Sakthivel, R; Kwon, O M

2018-06-07

This paper addresses the problem of finite-time synchronization of stochastic coupled neural networks (SCNNs) subject to Markovian switching, mixed time delay, and actuator saturation. In addition, coupling strengths of the SCNNs are characterized by mutually independent random variables. By utilizing a simple linear transformation, the problem of stochastic finite-time synchronization of SCNNs is converted into a mean-square finite-time stabilization problem of an error system. By choosing a suitable mode dependent switched Lyapunov-Krasovskii functional, a new set of sufficient conditions is derived to guarantee the finite-time stability of the error system. Subsequently, with the help of anti-windup control scheme, the actuator saturation risks could be mitigated. Moreover, the derived conditions help to optimize estimation of the domain of attraction by enlarging the contractively invariant set. Furthermore, simulations are conducted to exhibit the efficiency of proposed control scheme. Copyright © 2018 Elsevier Ltd. All rights reserved.

A comparison of methods for estimating the random effects distribution of a linear mixed model.

PubMed

Ghidey, Wendimagegn; Lesaffre, Emmanuel; Verbeke, Geert

2010-12-01

This article reviews various recently suggested approaches to estimate the random effects distribution in a linear mixed model, i.e. (1) the smoothing by roughening approach of Shen and Louis,(1) (2) the semi-non-parametric approach of Zhang and Davidian,(2) (3) the heterogeneity model of Verbeke and Lesaffre( 3) and (4) a flexible approach of Ghidey et al. (4) These four approaches are compared via an extensive simulation study. We conclude that for the considered cases, the approach of Ghidey et al. (4) often shows to have the smallest integrated mean squared error for estimating the random effects distribution. An analysis of a longitudinal dental data set illustrates the performance of the methods in a practical example.

Random measurement error: Why worry? An example of cardiovascular risk factors.

PubMed

Brakenhoff, Timo B; van Smeden, Maarten; Visseren, Frank L J; Groenwold, Rolf H H

2018-01-01

With the increased use of data not originally recorded for research, such as routine care data (or 'big data'), measurement error is bound to become an increasingly relevant problem in medical research. A common view among medical researchers on the influence of random measurement error (i.e. classical measurement error) is that its presence leads to some degree of systematic underestimation of studied exposure-outcome relations (i.e. attenuation of the effect estimate). For the common situation where the analysis involves at least one exposure and one confounder, we demonstrate that the direction of effect of random measurement error on the estimated exposure-outcome relations can be difficult to anticipate. Using three example studies on cardiovascular risk factors, we illustrate that random measurement error in the exposure and/or confounder can lead to underestimation as well as overestimation of exposure-outcome relations. We therefore advise medical researchers to refrain from making claims about the direction of effect of measurement error in their manuscripts, unless the appropriate inferential tools are used to study or alleviate the impact of measurement error from the analysis.

Preliminary Studies for a CBCT Imaging Protocol for Offline Organ Motion Analysis: Registration Software Validation and CTDI Measurements

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

Falco, Maria Daniela, E-mail: mdanielafalco@hotmail.co; Fontanarosa, Davide; Miceli, Roberto

2011-04-01

Cone-beam X-ray volumetric imaging in the treatment room, allows online correction of set-up errors and offline assessment of residual set-up errors and organ motion. In this study the registration algorithm of the X-ray volume imaging software (XVI, Elekta, Crawley, United Kingdom), which manages a commercial cone-beam computed tomography (CBCT)-based positioning system, has been tested using a homemade and an anthropomorphic phantom to: (1) assess its performance in detecting known translational and rotational set-up errors and (2) transfer the transformation matrix of its registrations into a commercial treatment planning system (TPS) for offline organ motion analysis. Furthermore, CBCT dose index hasmore » been measured for a particular site (prostate: 120 kV, 1028.8 mAs, approximately 640 frames) using a standard Perspex cylindrical body phantom (diameter 32 cm, length 15 cm) and a 10-cm-long pencil ionization chamber. We have found that known displacements were correctly calculated by the registration software to within 1.3 mm and 0.4{sup o}. For the anthropomorphic phantom, only translational displacements have been considered. Both studies have shown errors within the intrinsic uncertainty of our system for translational displacements (estimated as 0.87 mm) and rotational displacements (estimated as 0.22{sup o}). The resulting table translations proposed by the system to correct the displacements were also checked with portal images and found to place the isocenter of the plan on the linac isocenter within an error of 1 mm, which is the dimension of the spherical lead marker inserted at the center of the homemade phantom. The registration matrix translated into the TPS image fusion module correctly reproduced the alignment between planning CT scans and CBCT scans. Finally, measurements on the CBCT dose index indicate that CBCT acquisition delivers less dose than conventional CT scans and electronic portal imaging device portals. The registration software was found to be accurate, and its registration matrix can be easily translated into the TPS and a low dose is delivered to the patient during image acquisition. These results can help in designing imaging protocols for offline evaluations.« less

A concept for a visual computer interface to make error taxonomies useful at the point of primary care.

PubMed

Singh, Ranjit; Pace, Wilson; Singh, Sonjoy; Singh, Ashok; Singh, Gurdev

2007-01-01

Evidence suggests that the quality of care delivered by the healthcare industry currently falls far short of its capabilities. Whilst most patient safety and quality improvement work to date has focused on inpatient settings, some estimates suggest that outpatient settings are equally important, with up to 200,000 avoidable deaths annually in the United States of America (USA) alone. There is currently a need for improved error reporting and taxonomy systems that are useful at the point of care. This provides an opportunity to harness the benefits of computer visualisation to help structure and illustrate the 'stories' behind errors. In this paper we present a concept for a visual taxonomy of errors, based on visual models of the healthcare system at both macrosystem and microsystem levels (previously published in this journal), and describe how this could be used to create a visual database of errors. In an alphatest in a US context, we were able to code a sample of 20 errors from an existing error database using the visual taxonomy. The approach is designed to capture and disseminate patient safety information in an unambiguous format that is useful to all members of the healthcare team (including the patient) at the point of care as well as at the policy-making level.

Impact of Internally Developed Electronic Prescription on Prescribing Errors at Discharge from the Emergency Department

PubMed Central

Hitti, Eveline; Tamim, Hani; Bakhti, Rinad; Zebian, Dina; Mufarrij, Afif

2017-01-01

Introduction Medication errors are common, with studies reporting at least one error per patient encounter. At hospital discharge, medication errors vary from 15%–38%. However, studies assessing the effect of an internally developed electronic (E)-prescription system at discharge from an emergency department (ED) are comparatively minimal. Additionally, commercially available electronic solutions are cost-prohibitive in many resource-limited settings. We assessed the impact of introducing an internally developed, low-cost E-prescription system, with a list of commonly prescribed medications, on prescription error rates at discharge from the ED, compared to handwritten prescriptions. Methods We conducted a pre- and post-intervention study comparing error rates in a randomly selected sample of discharge prescriptions (handwritten versus electronic) five months pre and four months post the introduction of the E-prescription. The internally developed, E-prescription system included a list of 166 commonly prescribed medications with the generic name, strength, dose, frequency and duration. We included a total of 2,883 prescriptions in this study: 1,475 in the pre-intervention phase were handwritten (HW) and 1,408 in the post-intervention phase were electronic. We calculated rates of 14 different errors and compared them between the pre- and post-intervention period. Results Overall, E-prescriptions included fewer prescription errors as compared to HW-prescriptions. Specifically, E-prescriptions reduced missing dose (11.3% to 4.3%, p <0.0001), missing frequency (3.5% to 2.2%, p=0.04), missing strength errors (32.4% to 10.2%, p <0.0001) and legibility (0.7% to 0.2%, p=0.005). E-prescriptions, however, were associated with a significant increase in duplication errors, specifically with home medication (1.7% to 3%, p=0.02). Conclusion A basic, internally developed E-prescription system, featuring commonly used medications, effectively reduced medication errors in a low-resource setting where the costs of sophisticated commercial electronic solutions are prohibitive. PMID:28874948

Impact of Internally Developed Electronic Prescription on Prescribing Errors at Discharge from the Emergency Department.

PubMed

Hitti, Eveline; Tamim, Hani; Bakhti, Rinad; Zebian, Dina; Mufarrij, Afif

2017-08-01

Medication errors are common, with studies reporting at least one error per patient encounter. At hospital discharge, medication errors vary from 15%-38%. However, studies assessing the effect of an internally developed electronic (E)-prescription system at discharge from an emergency department (ED) are comparatively minimal. Additionally, commercially available electronic solutions are cost-prohibitive in many resource-limited settings. We assessed the impact of introducing an internally developed, low-cost E-prescription system, with a list of commonly prescribed medications, on prescription error rates at discharge from the ED, compared to handwritten prescriptions. We conducted a pre- and post-intervention study comparing error rates in a randomly selected sample of discharge prescriptions (handwritten versus electronic) five months pre and four months post the introduction of the E-prescription. The internally developed, E-prescription system included a list of 166 commonly prescribed medications with the generic name, strength, dose, frequency and duration. We included a total of 2,883 prescriptions in this study: 1,475 in the pre-intervention phase were handwritten (HW) and 1,408 in the post-intervention phase were electronic. We calculated rates of 14 different errors and compared them between the pre- and post-intervention period. Overall, E-prescriptions included fewer prescription errors as compared to HW-prescriptions. Specifically, E-prescriptions reduced missing dose (11.3% to 4.3%, p <0.0001), missing frequency (3.5% to 2.2%, p=0.04), missing strength errors (32.4% to 10.2%, p <0.0001) and legibility (0.7% to 0.2%, p=0.005). E-prescriptions, however, were associated with a significant increase in duplication errors, specifically with home medication (1.7% to 3%, p=0.02). A basic, internally developed E-prescription system, featuring commonly used medications, effectively reduced medication errors in a low-resource setting where the costs of sophisticated commercial electronic solutions are prohibitive.

Immobilisation precision in VMAT for oral cancer patients

NASA Astrophysics Data System (ADS)

Norfadilah, M. N.; Ahmad, R.; Heng, S. P.; Lam, K. S.; Radzi, A. B. Ahmad; John, L. S. H.

2017-05-01

A study was conducted to evaluate and quantify a precision of the interfraction setup with different immobilisation devices throughout the treatment time. Local setup accuracy was analysed for 8 oral cancer patients receiving radiotherapy; 4 with HeadFIX® mouthpiece moulded with wax (HFW) and 4 with 10 ml/cc syringe barrel (SYR). Each patients underwent Image Guided Radiotherapy (IGRT) with total of 209 cone-beam computed tomography (CBCT) data sets for position set up errors measurement. The setup variations in the mediolateral (ML), craniocaudal (CC), and anteroposterior (AP) dimensions were measured. Overall mean displacement (M), the population systematic (Σ) and random (σ) errors and the 3D vector length were calculated. Clinical target volume to planning target volume (CTV-PTV) margins were calculated according to the van Herk formula (2.5Σ+0.7σ). The M values for both group were < 1 mm and < 1° in all translational and rotational directions. This indicate there is no significant imprecision in the equipment (lasers) and during procedure. The interfraction translational 3 dimension vector for HFW and SYR were 1.93±0.66mm and 3.84±1.34mm, respectively. The interfraction average rotational error were 0.00°±0.65° and 0.34°±0.59°, respectively. CTV-PTV margins along the 3 translational axis (Right-Left, Superior-Inferior, Anterior-Posterior) calculated were 3.08, 2.22 and 0.81 mm for HFW and 3.76, 6.24 and 5.06 mm for SYR. The results of this study have demonstrated that HFW more precise in reproducing patient position compared to conventionally used SYR (p<0.001). All margin calculated did not exceed hospital protocol (5mm) except S-I and A-P axes using syringe. For this reason, a daily IGRT is highly recommended to improve the immobilisation precision.

Correcting for deformation in skin-based marker systems.

PubMed

Alexander, E J; Andriacchi, T P

2001-03-01

A new technique is described that reduces error due to skin movement artifact in the opto-electronic measurement of in vivo skeletal motion. This work builds on a previously described point cluster technique marker set and estimation algorithm by extending the transformation equations to the general deformation case using a set of activity-dependent deformation models. Skin deformation during activities of daily living are modeled as consisting of a functional form defined over the observation interval (the deformation model) plus additive noise (modeling error). The method is described as an interval deformation technique. The method was tested using simulation trials with systematic and random components of deformation error introduced into marker position vectors. The technique was found to substantially outperform methods that require rigid-body assumptions. The method was tested in vivo on a patient fitted with an external fixation device (Ilizarov). Simultaneous measurements from markers placed on the Ilizarov device (fixed to bone) were compared to measurements derived from skin-based markers. The interval deformation technique reduced the errors in limb segment pose estimate by 33 and 25% compared to the classic rigid-body technique for position and orientation, respectively. This newly developed method has demonstrated that by accounting for the changing shape of the limb segment, a substantial improvement in the estimates of in vivo skeletal movement can be achieved.

Investigation of spectral analysis techniques for randomly sampled velocimetry data

NASA Technical Reports Server (NTRS)

Sree, Dave

1993-01-01

It is well known that velocimetry (LV) generates individual realization velocity data that are randomly or unevenly sampled in time. Spectral analysis of such data to obtain the turbulence spectra, and hence turbulence scales information, requires special techniques. The 'slotting' technique of Mayo et al, also described by Roberts and Ajmani, and the 'Direct Transform' method of Gaster and Roberts are well known in the LV community. The slotting technique is faster than the direct transform method in computation. There are practical limitations, however, as to how a high frequency and accurate estimate can be made for a given mean sampling rate. These high frequency estimates are important in obtaining the microscale information of turbulence structure. It was found from previous studies that reliable spectral estimates can be made up to about the mean sampling frequency (mean data rate) or less. If the data were evenly samples, the frequency range would be half the sampling frequency (i.e. up to Nyquist frequency); otherwise, aliasing problem would occur. The mean data rate and the sample size (total number of points) basically limit the frequency range. Also, there are large variabilities or errors associated with the high frequency estimates from randomly sampled signals. Roberts and Ajmani proposed certain pre-filtering techniques to reduce these variabilities, but at the cost of low frequency estimates. The prefiltering acts as a high-pass filter. Further, Shapiro and Silverman showed theoretically that, for Poisson sampled signals, it is possible to obtain alias-free spectral estimates far beyond the mean sampling frequency. But the question is, how far? During his tenure under 1993 NASA-ASEE Summer Faculty Fellowship Program, the author investigated from his studies on the spectral analysis techniques for randomly sampled signals that the spectral estimates can be enhanced or improved up to about 4-5 times the mean sampling frequency by using a suitable prefiltering technique. But, this increased bandwidth comes at the cost of the lower frequency estimates. The studies further showed that large data sets of the order of 100,000 points, or more, high data rates, and Poisson sampling are very crucial for obtaining reliable spectral estimates from randomly sampled data, such as LV data. Some of the results of the current study are presented.

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

Chengqiang, L; Yin, Y; Chen, L

Purpose: To investigate the impact of MLC position errors on simultaneous integrated boost intensity-modulated radiotherapy (SIB-IMRT) for patients with nasopharyngeal carcinoma. Methods: To compare the dosimetric differences between the simulated plans and the clinical plans, ten patients with locally advanced NPC treated with SIB-IMRT were enrolled in this study. All plans were calculated with an inverse planning system (Pinnacle3, Philips Medical System{sub )}. Random errors −2mm to 2mm{sub )},shift errors{sub (} 2mm,1mm and 0.5mm) and systematic extension/ contraction errors (±2mm, ±1mm and ±0.5mm) of the MLC leaf position were introduced respectively into the original plans to create the simulated plans.more » Dosimetry factors were compared between the original and the simulated plans. Results: The dosimetric impact of the random and system shift errors of MLC position was insignificant within 2mm, the maximum changes in D95% of PGTV,PTV1,PTV2 were-0.92±0.51%,1.00±0.24% and 0.62±0.17%, the maximum changes in the D0.1cc of spinal cord and brainstem were 1.90±2.80% and −1.78±1.42%, the maximum changes in the Dmean of parotids were1.36±1.23% and −2.25±2.04%.However,the impact of MLC extension or contraction errors was found significant. For 2mm leaf extension errors, the average changes in D95% of PGTV,PTV1,PTV2 were 4.31±0.67%,4.29±0.65% and 4.79±0.82%, the averaged value of the D0.1cc to spinal cord and brainstem were increased by 7.39±5.25% and 6.32±2.28%,the averaged value of the mean dose to left and right parotid were increased by 12.75±2.02%,13.39±2.17% respectively. Conclusion: The dosimetric effect was insignificant for random MLC leaf position errors up to 2mm. There was a high sensitivity to dose distribution for MLC extension or contraction errors.We should pay attention to the anatomic changes in target organs and anatomical structures during the course,individual radiotherapy was recommended to ensure adaptive doses.« less

A Practical Methodology for Quantifying Random and Systematic Components of Unexplained Variance in a Wind Tunnel

NASA Technical Reports Server (NTRS)

Deloach, Richard; Obara, Clifford J.; Goodman, Wesley L.

2012-01-01

This paper documents a check standard wind tunnel test conducted in the Langley 0.3-Meter Transonic Cryogenic Tunnel (0.3M TCT) that was designed and analyzed using the Modern Design of Experiments (MDOE). The test designed to partition the unexplained variance of typical wind tunnel data samples into two constituent components, one attributable to ordinary random error, and one attributable to systematic error induced by covariate effects. Covariate effects in wind tunnel testing are discussed, with examples. The impact of systematic (non-random) unexplained variance on the statistical independence of sequential measurements is reviewed. The corresponding correlation among experimental errors is discussed, as is the impact of such correlation on experimental results generally. The specific experiment documented herein was organized as a formal test for the presence of unexplained variance in representative samples of wind tunnel data, in order to quantify the frequency with which such systematic error was detected, and its magnitude relative to ordinary random error. Levels of systematic and random error reported here are representative of those quantified in other facilities, as cited in the references.

A class of optimum digital phase locked loops for the DSN advanced receiver

NASA Technical Reports Server (NTRS)

Hurd, W. J.; Kumar, R.

1985-01-01

A class of optimum digital filters for digital phase locked loop of the deep space network advanced receiver is discussed. The filter minimizes a weighted combination of the variance of the random component of the phase error and the sum square of the deterministic dynamic component of phase error at the output of the numerically controlled oscillator (NCO). By varying the weighting coefficient over a suitable range of values, a wide set of filters are obtained such that, for any specified value of the equivalent loop-noise bandwidth, there corresponds a unique filter in this class. This filter thus has the property of having the best transient response over all possible filters of the same bandwidth and type. The optimum filters are also evaluated in terms of their gain margin for stability and their steady-state error performance.

Efficiently characterizing the total error in quantum circuits

NASA Astrophysics Data System (ADS)

Carignan-Dugas, Arnaud; Wallman, Joel J.; Emerson, Joseph

A promising technological advancement meant to enlarge our computational means is the quantum computer. Such a device would harvest the quantum complexity of the physical world in order to unfold concrete mathematical problems more efficiently. However, the errors emerging from the implementation of quantum operations are likewise quantum, and hence share a similar level of intricacy. Fortunately, randomized benchmarking protocols provide an efficient way to characterize the operational noise within quantum devices. The resulting figures of merit, like the fidelity and the unitarity, are typically attached to a set of circuit components. While important, this doesn't fulfill the main goal: determining if the error rate of the total circuit is small enough in order to trust its outcome. In this work, we fill the gap by providing an optimal bound on the total fidelity of a circuit in terms of component-wise figures of merit. Our bound smoothly interpolates between the classical regime, in which the error rate grows linearly in the circuit's length, and the quantum regime, which can naturally allow quadratic growth. Conversely, our analysis substantially improves the bounds on single circuit element fidelities obtained through techniques such as interleaved randomized benchmarking. This research was supported by the U.S. Army Research Office through Grant W911NF- 14-1-0103, CIFAR, the Government of Ontario, and the Government of Canada through NSERC and Industry Canada.

Using EHR Data to Detect Prescribing Errors in Rapidly Discontinued Medication Orders.

PubMed

Burlison, Jonathan D; McDaniel, Robert B; Baker, Donald K; Hasan, Murad; Robertson, Jennifer J; Howard, Scott C; Hoffman, James M

2018-01-01

Previous research developed a new method for locating prescribing errors in rapidly discontinued electronic medication orders. Although effective, the prospective design of that research hinders its feasibility for regular use. Our objectives were to assess a method to retrospectively detect prescribing errors, to characterize the identified errors, and to identify potential improvement opportunities. Electronically submitted medication orders from 28 randomly selected days that were discontinued within 120 minutes of submission were reviewed and categorized as most likely errors, nonerrors, or not enough information to determine status. Identified errors were evaluated by amount of time elapsed from original submission to discontinuation, error type, staff position, and potential clinical significance. Pearson's chi-square test was used to compare rates of errors across prescriber types. In all, 147 errors were identified in 305 medication orders. The method was most effective for orders that were discontinued within 90 minutes. Duplicate orders were most common; physicians in training had the highest error rate ( p  < 0.001), and 24 errors were potentially clinically significant. None of the errors were voluntarily reported. It is possible to identify prescribing errors in rapidly discontinued medication orders by using retrospective methods that do not require interrupting prescribers to discuss order details. Future research could validate our methods in different clinical settings. Regular use of this measure could help determine the causes of prescribing errors, track performance, and identify and evaluate interventions to improve prescribing systems and processes. Schattauer GmbH Stuttgart.

Free variable selection QSPR study to predict 19F chemical shifts of some fluorinated organic compounds using Random Forest and RBF-PLS methods

NASA Astrophysics Data System (ADS)

Goudarzi, Nasser

2016-04-01

In this work, two new and powerful chemometrics methods are applied for the modeling and prediction of the 19F chemical shift values of some fluorinated organic compounds. The radial basis function-partial least square (RBF-PLS) and random forest (RF) are employed to construct the models to predict the 19F chemical shifts. In this study, we didn't used from any variable selection method and RF method can be used as variable selection and modeling technique. Effects of the important parameters affecting the ability of the RF prediction power such as the number of trees (nt) and the number of randomly selected variables to split each node (m) were investigated. The root-mean-square errors of prediction (RMSEP) for the training set and the prediction set for the RBF-PLS and RF models were 44.70, 23.86, 29.77, and 23.69, respectively. Also, the correlation coefficients of the prediction set for the RBF-PLS and RF models were 0.8684 and 0.9313, respectively. The results obtained reveal that the RF model can be used as a powerful chemometrics tool for the quantitative structure-property relationship (QSPR) studies.

The Effect of Random Error on Diagnostic Accuracy Illustrated with the Anthropometric Diagnosis of Malnutrition

PubMed Central

2016-01-01

Background It is often thought that random measurement error has a minor effect upon the results of an epidemiological survey. Theoretically, errors of measurement should always increase the spread of a distribution. Defining an illness by having a measurement outside an established healthy range will lead to an inflated prevalence of that condition if there are measurement errors. Methods and results A Monte Carlo simulation was conducted of anthropometric assessment of children with malnutrition. Random errors of increasing magnitude were imposed upon the populations and showed that there was an increase in the standard deviation with each of the errors that became exponentially greater with the magnitude of the error. The potential magnitude of the resulting error of reported prevalence of malnutrition were compared with published international data and found to be of sufficient magnitude to make a number of surveys and the numerous reports and analyses that used these data unreliable. Conclusions The effect of random error in public health surveys and the data upon which diagnostic cut-off points are derived to define “health” has been underestimated. Even quite modest random errors can more than double the reported prevalence of conditions such as malnutrition. Increasing sample size does not address this problem, and may even result in less accurate estimates. More attention needs to be paid to the selection, calibration and maintenance of instruments, measurer selection, training & supervision, routine estimation of the likely magnitude of errors using standardization tests, use of statistical likelihood of error to exclude data from analysis and full reporting of these procedures in order to judge the reliability of survey reports. PMID:28030627

Intelligent error correction method applied on an active pixel sensor based star tracker

NASA Astrophysics Data System (ADS)

Schmidt, Uwe

2005-10-01

Star trackers are opto-electronic sensors used on-board of satellites for the autonomous inertial attitude determination. During the last years star trackers became more and more important in the field of the attitude and orbit control system (AOCS) sensors. High performance star trackers are based up today on charge coupled device (CCD) optical camera heads. The active pixel sensor (APS) technology, introduced in the early 90-ties, allows now the beneficial replacement of CCD detectors by APS detectors with respect to performance, reliability, power, mass and cost. The company's heritage in star tracker design started in the early 80-ties with the launch of the worldwide first fully autonomous star tracker system ASTRO1 to the Russian MIR space station. Jena-Optronik recently developed an active pixel sensor based autonomous star tracker "ASTRO APS" as successor of the CCD based star tracker product series ASTRO1, ASTRO5, ASTRO10 and ASTRO15. Key features of the APS detector technology are, a true xy-address random access, the multiple windowing read out and the on-chip signal processing including the analogue to digital conversion. These features can be used for robust star tracking at high slew rates and under worse conditions like stray light and solar flare induced single event upsets. A special algorithm have been developed to manage the typical APS detector error contributors like fixed pattern noise (FPN), dark signal non-uniformity (DSNU) and white spots. The algorithm works fully autonomous and adapts to e.g. increasing DSNU and up-coming white spots automatically without ground maintenance or re-calibration. In contrast to conventional correction methods the described algorithm does not need calibration data memory like full image sized calibration data sets. The application of the presented algorithm managing the typical APS detector error contributors is a key element for the design of star trackers for long term satellite applications like geostationary telecom platforms.

Effects of learning with explicit elaboration on implicit transfer of visuomotor sequence learning.

PubMed

Tanaka, Kanji; Watanabe, Katsumi

2013-08-01

Intervals between stimuli and/or responses have significant influences on sequential learning. In the present study, we investigated whether transfer would occur even when the intervals and the visual configurations in a sequence were drastically changed so that participants did not notice that the required sequences of responses were identical. In the experiment, two (or three) sequential button presses comprised a "set," and nine (or six) consecutive sets comprised a "hyperset." In the first session, participants learned either a 2 × 9 or 3 × 6 hyperset by trial and error until they completed it 20 times without error. In the second block, the 2 × 9 (3 × 6) hyperset was changed into the 3 × 6 (2 × 9) hyperset, resulting in different visual configurations and intervals between stimuli and responses. Participants were assigned into two groups: the Identical and Random groups. In the Identical group, the sequence (i.e., the buttons to be pressed) in the second block was identical to that in the first block. In the Random group, a new hyperset was learned. Even in the Identical group, no participants noticed that the sequences were identical. Nevertheless, a significant transfer of performance occurred. However, in the subsequent experiment that did not require explicit trial-and-error learning in the first session, implicit transfer in the second session did not occur. These results indicate that learning with explicit elaboration strengthens the implicit representation of the sequence order as a whole; this might occur independently of the intervals between elements and enable implicit transfer.

Detection of digital FSK using a phase-locked loop

NASA Technical Reports Server (NTRS)

Lindsey, W. C.; Simon, M. K.

1975-01-01

A theory is presented for the design of a digital FSK receiver which employs a phase-locked loop to set up the desired matched filter as the arriving signal frequency switches. The developed mathematical model makes it possible to establish the error probability performance of systems which employ a class of digital FM modulations. The noise mechanism which accounts for decision errors is modeled on the basis of the Meyr distribution and renewal Markov process theory.

On the assimilation set-up of ASCAT soil moisture data for improving streamflow catchment simulation

NASA Astrophysics Data System (ADS)

Loizu, Javier; Massari, Christian; Álvarez-Mozos, Jesús; Tarpanelli, Angelica; Brocca, Luca; Casalí, Javier

2018-01-01

Assimilation of remotely sensed surface soil moisture (SSM) data into hydrological catchment models has been identified as a means to improve streamflow simulations, but reported results vary markedly depending on the particular model, catchment and assimilation procedure used. In this study, the influence of key aspects, such as the type of model, re-scaling technique and SSM observation error considered, were evaluated. For this aim, Advanced SCATterometer ASCAT-SSM observations were assimilated through the ensemble Kalman filter into two hydrological models of different complexity (namely MISDc and TOPLATS) run on two Mediterranean catchments of similar size (750 km2). Three different re-scaling techniques were evaluated (linear re-scaling, variance matching and cumulative distribution function matching), and SSM observation error values ranging from 0.01% to 20% were considered. Four different efficiency measures were used for evaluating the results. Increases in Nash-Sutcliffe efficiency (0.03-0.15) and efficiency indices (10-45%) were obtained, especially when linear re-scaling and observation errors within 4-6% were considered. This study found out that there is a potential to improve streamflow prediction through data assimilation of remotely sensed SSM in catchments of different characteristics and with hydrological models of different conceptualizations schemes, but for that, a careful evaluation of the observation error and re-scaling technique set-up utilized is required.

Low power and type II errors in recent ophthalmology research.

PubMed

Khan, Zainab; Milko, Jordan; Iqbal, Munir; Masri, Moness; Almeida, David R P

2016-10-01

To investigate the power of unpaired t tests in prospective, randomized controlled trials when these tests failed to detect a statistically significant difference and to determine the frequency of type II errors. Systematic review and meta-analysis. We examined all prospective, randomized controlled trials published between 2010 and 2012 in 4 major ophthalmology journals (Archives of Ophthalmology, British Journal of Ophthalmology, Ophthalmology, and American Journal of Ophthalmology). Studies that used unpaired t tests were included. Power was calculated using the number of subjects in each group, standard deviations, and α = 0.05. The difference between control and experimental means was set to be (1) 20% and (2) 50% of the absolute value of the control's initial conditions. Power and Precision version 4.0 software was used to carry out calculations. Finally, the proportion of articles with type II errors was calculated. β = 0.3 was set as the largest acceptable value for the probability of type II errors. In total, 280 articles were screened. Final analysis included 50 prospective, randomized controlled trials using unpaired t tests. The median power of tests to detect a 50% difference between means was 0.9 and was the same for all 4 journals regardless of the statistical significance of the test. The median power of tests to detect a 20% difference between means ranged from 0.26 to 0.9 for the 4 journals. The median power of these tests to detect a 50% and 20% difference between means was 0.9 and 0.5 for tests that did not achieve statistical significance. A total of 14% and 57% of articles with negative unpaired t tests contained results with β > 0.3 when power was calculated for differences between means of 50% and 20%, respectively. A large portion of studies demonstrate high probabilities of type II errors when detecting small differences between means. The power to detect small difference between means varies across journals. It is, therefore, worthwhile for authors to mention the minimum clinically important difference for individual studies. Journals can consider publishing statistical guidelines for authors to use. Day-to-day clinical decisions rely heavily on the evidence base formed by the plethora of studies available to clinicians. Prospective, randomized controlled clinical trials are highly regarded as a robust study and are used to make important clinical decisions that directly affect patient care. The quality of study designs and statistical methods in major clinical journals is improving overtime, 1 and researchers and journals are being more attentive to statistical methodologies incorporated by studies. The results of well-designed ophthalmic studies with robust methodologies, therefore, have the ability to modify the ways in which diseases are managed. Copyright © 2016 Canadian Ophthalmological Society. Published by Elsevier Inc. All rights reserved.

How to derive biological information from the value of the normalization constant in allometric equations.

PubMed

Kaitaniemi, Pekka

2008-04-09

Allometric equations are widely used in many branches of biological science. The potential information content of the normalization constant b in allometric equations of the form Y = bX(a) has, however, remained largely neglected. To demonstrate the potential for utilizing this information, I generated a large number of artificial datasets that resembled those that are frequently encountered in biological studies, i.e., relatively small samples including measurement error or uncontrolled variation. The value of X was allowed to vary randomly within the limits describing different data ranges, and a was set to a fixed theoretical value. The constant b was set to a range of values describing the effect of a continuous environmental variable. In addition, a normally distributed random error was added to the values of both X and Y. Two different approaches were then used to model the data. The traditional approach estimated both a and b using a regression model, whereas an alternative approach set the exponent a at its theoretical value and only estimated the value of b. Both approaches produced virtually the same model fit with less than 0.3% difference in the coefficient of determination. Only the alternative approach was able to precisely reproduce the effect of the environmental variable, which was largely lost among noise variation when using the traditional approach. The results show how the value of b can be used as a source of valuable biological information if an appropriate regression model is selected.

IMRT QA: Selecting gamma criteria based on error detection sensitivity.

PubMed

Steers, Jennifer M; Fraass, Benedick A

2016-04-01

The gamma comparison is widely used to evaluate the agreement between measurements and treatment planning system calculations in patient-specific intensity modulated radiation therapy (IMRT) quality assurance (QA). However, recent publications have raised concerns about the lack of sensitivity when employing commonly used gamma criteria. Understanding the actual sensitivity of a wide range of different gamma criteria may allow the definition of more meaningful gamma criteria and tolerance limits in IMRT QA. We present a method that allows the quantitative determination of gamma criteria sensitivity to induced errors which can be applied to any unique combination of device, delivery technique, and software utilized in a specific clinic. A total of 21 DMLC IMRT QA measurements (ArcCHECK®, Sun Nuclear) were compared to QA plan calculations with induced errors. Three scenarios were studied: MU errors, multi-leaf collimator (MLC) errors, and the sensitivity of the gamma comparison to changes in penumbra width. Gamma comparisons were performed between measurements and error-induced calculations using a wide range of gamma criteria, resulting in a total of over 20 000 gamma comparisons. Gamma passing rates for each error class and case were graphed against error magnitude to create error curves in order to represent the range of missed errors in routine IMRT QA using 36 different gamma criteria. This study demonstrates that systematic errors and case-specific errors can be detected by the error curve analysis. Depending on the location of the error curve peak (e.g., not centered about zero), 3%/3 mm threshold = 10% at 90% pixels passing may miss errors as large as 15% MU errors and ±1 cm random MLC errors for some cases. As the dose threshold parameter was increased for a given %Diff/distance-to-agreement (DTA) setting, error sensitivity was increased by up to a factor of two for select cases. This increased sensitivity with increasing dose threshold was consistent across all studied combinations of %Diff/DTA. Criteria such as 2%/3 mm and 3%/2 mm with a 50% threshold at 90% pixels passing are shown to be more appropriately sensitive without being overly strict. However, a broadening of the penumbra by as much as 5 mm in the beam configuration was difficult to detect with commonly used criteria, as well as with the previously mentioned criteria utilizing a threshold of 50%. We have introduced the error curve method, an analysis technique which allows the quantitative determination of gamma criteria sensitivity to induced errors. The application of the error curve method using DMLC IMRT plans measured on the ArcCHECK® device demonstrated that large errors can potentially be missed in IMRT QA with commonly used gamma criteria (e.g., 3%/3 mm, threshold = 10%, 90% pixels passing). Additionally, increasing the dose threshold value can offer dramatic increases in error sensitivity. This approach may allow the selection of more meaningful gamma criteria for IMRT QA and is straightforward to apply to other combinations of devices and treatment techniques.

A review of uncertainty in in situ measurements and data sets of sea surface temperature

NASA Astrophysics Data System (ADS)

Kennedy, John J.

2014-03-01

Archives of in situ sea surface temperature (SST) measurements extend back more than 160 years. Quality of the measurements is variable, and the area of the oceans they sample is limited, especially early in the record and during the two world wars. Measurements of SST and the gridded data sets that are based on them are used in many applications so understanding and estimating the uncertainties are vital. The aim of this review is to give an overview of the various components that contribute to the overall uncertainty of SST measurements made in situ and of the data sets that are derived from them. In doing so, it also aims to identify current gaps in understanding. Uncertainties arise at the level of individual measurements with both systematic and random effects and, although these have been extensively studied, refinement of the error models continues. Recent improvements have been made in the understanding of the pervasive systematic errors that affect the assessment of long-term trends and variability. However, the adjustments applied to minimize these systematic errors are uncertain and these uncertainties are higher before the 1970s and particularly large in the period surrounding the Second World War owing to a lack of reliable metadata. The uncertainties associated with the choice of statistical methods used to create globally complete SST data sets have been explored using different analysis techniques, but they do not incorporate the latest understanding of measurement errors, and they want for a fair benchmark against which their skill can be objectively assessed. These problems can be addressed by the creation of new end-to-end SST analyses and by the recovery and digitization of data and metadata from ship log books and other contemporary literature.

A dual-phantom system for validation of velocity measurements in stenosis models under steady flow.

PubMed

Blake, James R; Easson, William J; Hoskins, Peter R

2009-09-01

A dual-phantom system is developed for validation of velocity measurements in stenosis models. Pairs of phantoms with identical geometry and flow conditions are manufactured, one for ultrasound and one for particle image velocimetry (PIV). The PIV model is made from silicone rubber, and a new PIV fluid is made that matches the refractive index of 1.41 of silicone. Dynamic scaling was performed to correct for the increased viscosity of the PIV fluid compared with that of the ultrasound blood mimic. The degree of stenosis in the models pairs agreed to less than 1%. The velocities in the laminar flow region up to the peak velocity location agreed to within 15%, and the difference could be explained by errors in ultrasound velocity estimation. At low flow rates and in mild stenoses, good agreement was observed in the distal flow fields, excepting the maximum velocities. At high flow rates, there was considerable difference in velocities in the poststenosis flow field (maximum centreline differences of 30%), which would seem to represent real differences in hydrodynamic behavior between the two models. Sources of error included: variation of viscosity because of temperature (random error, which could account for differences of up to 7%); ultrasound velocity estimation errors (systematic errors); and geometry effects in each model, particularly because of imperfect connectors and corners (systematic errors, potentially affecting the inlet length and flow stability). The current system is best placed to investigate measurement errors in the laminar flow region rather than the poststenosis turbulent flow region.

Error monitoring issues for common channel signaling

NASA Astrophysics Data System (ADS)

Hou, Victor T.; Kant, Krishna; Ramaswami, V.; Wang, Jonathan L.

1994-04-01

Motivated by field data which showed a large number of link changeovers and incidences of link oscillations between in-service and out-of-service states in common channel signaling (CCS) networks, a number of analyses of the link error monitoring procedures in the SS7 protocol were performed by the authors. This paper summarizes the results obtained thus far and include the following: (1) results of an exact analysis of the performance of the error monitoring procedures under both random and bursty errors; (2) a demonstration that there exists a range of error rates within which the error monitoring procedures of SS7 may induce frequent changeovers and changebacks; (3) an analysis of the performance ofthe SS7 level-2 transmission protocol to determine the tolerable error rates within which the delay requirements can be met; (4) a demonstration that the tolerable error rate depends strongly on various link and traffic characteristics, thereby implying that a single set of error monitor parameters will not work well in all situations; (5) some recommendations on a customizable/adaptable scheme of error monitoring with a discussion on their implementability. These issues may be particularly relevant in the presence of anticipated increases in SS7 traffic due to widespread deployment of Advanced Intelligent Network (AIN) and Personal Communications Service (PCS) as well as for developing procedures for high-speed SS7 links currently under consideration by standards bodies.

A comparison of advanced overlay technologies

NASA Astrophysics Data System (ADS)

Dasari, Prasad; Smith, Nigel; Goelzer, Gary; Liu, Zhuan; Li, Jie; Tan, Asher; Koh, Chin Hwee

2010-03-01

The extension of optical lithography to 22nm and beyond by Double Patterning Technology is often challenged by CDU and overlay control. With reduced overlay measurement error budgets in the sub-nm range, relying on traditional Total Measurement Uncertainty (TMU) estimates alone is no longer sufficient. In this paper we will report scatterometry overlay measurements data from a set of twelve test wafers, using four different target designs. The TMU of these measurements is under 0.4nm, within the process control requirements for the 22nm node. Comparing the measurement differences between DBO targets (using empirical and model based analysis) and with image-based overlay data indicates the presence of systematic and random measurement errors that exceeds the TMU estimate.

A randomized trial comparing INR monitoring devices in patients with anticoagulation self-management: evaluation of a novel error-grid approach.

PubMed

Hemkens, Lars G; Hilden, Kristian M; Hartschen, Stephan; Kaiser, Thomas; Didjurgeit, Ulrike; Hansen, Roland; Bender, Ralf; Sawicki, Peter T

2008-08-01

In addition to the metrological quality of international normalized ratio (INR) monitoring devices used in patients' self-management of long-term anticoagulation, the effectiveness of self-monitoring with such devices has to be evaluated under real-life conditions with a focus on clinical implications. An approach to evaluate the clinical significance of inaccuracies is the error-grid analysis as already established in self-monitoring of blood glucose. Two anticoagulation monitors were compared in a real-life setting and a novel error-grid instrument for oral anticoagulation has been evaluated. In a randomized crossover study 16 patients performed self-management of anticoagulation using the INRatio and the CoaguChek S system. Main outcome measures were clinically relevant INR differences according to established criteria and to the error-grid approach. A lower rate of clinically relevant disagreements according to Anderson's criteria was found with CoaguChek S than with INRatio without statistical significance (10.77% vs. 12.90%; P = 0.787). Using the error-grid we found principally consistent results: More measurement pairs with discrepancies of no or low clinical relevance were found with CoaguChek S, whereas with INRatio we found more differences with a moderate clinical relevance. A high rate of patients' satisfaction with both of the point of care devices was found with only marginal differences. A principal appropriateness of the investigated point-of-care devices to adequately monitor the INR is shown. The error-grid is useful for comparing monitoring methods with a focus on clinical relevance under real-life conditions beyond assessing the pure metrological quality, but we emphasize that additional trials using this instrument with larger patient populations are needed to detect differences in clinically relevant disagreements.

An Emprical Point Error Model for Tls Derived Point Clouds

NASA Astrophysics Data System (ADS)

Ozendi, Mustafa; Akca, Devrim; Topan, Hüseyin

2016-06-01

The random error pattern of point clouds has significant effect on the quality of final 3D model. The magnitude and distribution of random errors should be modelled numerically. This work aims at developing such an anisotropic point error model, specifically for the terrestrial laser scanner (TLS) acquired 3D point clouds. A priori precisions of basic TLS observations, which are the range, horizontal angle and vertical angle, are determined by predefined and practical measurement configurations, performed at real-world test environments. A priori precision of horizontal (𝜎𝜃) and vertical (𝜎𝛼) angles are constant for each point of a data set, and can directly be determined through the repetitive scanning of the same environment. In our practical tests, precisions of the horizontal and vertical angles were found as 𝜎𝜃=±36.6𝑐𝑐 and 𝜎𝛼=±17.8𝑐𝑐, respectively. On the other hand, a priori precision of the range observation (𝜎𝜌) is assumed to be a function of range, incidence angle of the incoming laser ray, and reflectivity of object surface. Hence, it is a variable, and computed for each point individually by employing an empirically developed formula varying as 𝜎𝜌=±2-12 𝑚𝑚 for a FARO Focus X330 laser scanner. This procedure was followed by the computation of error ellipsoids of each point using the law of variance-covariance propagation. The direction and size of the error ellipsoids were computed by the principal components transformation. The usability and feasibility of the model was investigated in real world scenarios. These investigations validated the suitability and practicality of the proposed method.

Assessment of the global monthly mean surface insolation estimated from satellite measurements using global energy balance archive data

NASA Technical Reports Server (NTRS)

Li, Zhanqing; Whitlock, Charles H.; Charlock, Thomas P.

1995-01-01

Global sets of surface radiation budget (SRB) have been obtained from satellite programs. These satellite-based estimates need validation with ground-truth observations. This study validates the estimates of monthly mean surface insolation contained in two satellite-based SRB datasets with the surface measurements made at worldwide radiation stations from the Global Energy Balance Archive (GEBA). One dataset was developed from the Earth Radiation Budget Experiment (ERBE) using the algorithm of Li et al. (ERBE/SRB), and the other from the International Satellite Cloud Climatology Project (ISCCP) using the algorithm of Pinker and Laszlo and that of Staylor (GEWEX/SRB). Since the ERBE/SRB data contain the surface net solar radiation only, the values of surface insolation were derived by making use of the surface albedo data contained GEWEX/SRB product. The resulting surface insolation has a bias error near zero and a root-mean-square error (RMSE) between 8 and 28 W/sq m. The RMSE is mainly associated with poor representation of surface observations within a grid cell. When the number of surface observations are sufficient, the random error is estimated to be about 5 W/sq m with present satellite-based estimates. In addition to demonstrating the strength of the retrieving method, the small random error demonstrates how well the ERBE derives from the monthly mean fluxes at the top of the atmosphere (TOA). A larger scatter is found for the comparison of transmissivity than for that of insolation. Month to month comparison of insolation reveals a weak seasonal trend in bias error with an amplitude of about 3 W/sq m. As for the insolation data from the GEWEX/SRB, larger bias errors of 5-10 W/sq m are evident with stronger seasonal trends and almost identical RMSEs.

Estimating errors in least-squares fitting

NASA Technical Reports Server (NTRS)

Richter, P. H.

1995-01-01

While least-squares fitting procedures are commonly used in data analysis and are extensively discussed in the literature devoted to this subject, the proper assessment of errors resulting from such fits has received relatively little attention. The present work considers statistical errors in the fitted parameters, as well as in the values of the fitted function itself, resulting from random errors in the data. Expressions are derived for the standard error of the fit, as a function of the independent variable, for the general nonlinear and linear fitting problems. Additionally, closed-form expressions are derived for some examples commonly encountered in the scientific and engineering fields, namely ordinary polynomial and Gaussian fitting functions. These results have direct application to the assessment of the antenna gain and system temperature characteristics, in addition to a broad range of problems in data analysis. The effects of the nature of the data and the choice of fitting function on the ability to accurately model the system under study are discussed, and some general rules are deduced to assist workers intent on maximizing the amount of information obtained form a given set of measurements.

A fiber optic sensor for on-line non-touch monitoring of roll shape

NASA Astrophysics Data System (ADS)

Guo, Yuan; Qu, Weijian; Yuan, Qi

2009-07-01

Basing on the principle of reflective displacement fibre-optic sensor, a high accuracy non-touch on-line optical fibre sensor for detecting roll shape is presented. The principle and composition of the detection system and the operation process are expatiated also. By using a novel probe of three optical fibres in equal transverse space, the effects of fluctuations in the light source, reflective changing of target surface and the intensity losses in the fibre lines are automatically compensated. Meantime, an optical fibre sensor model of correcting static error based on BP artificial neural network (ANN) is set up. Also by using interpolation method and value filtering to process the signals, effectively reduce the influence of random noise and the vibration of the roll bearing. So the accuracy and resolution were enhanced remarkably. Experiment proves that the resolution is 1μm and the precision can reach to 0.1%. So the system reaches to the demand of practical production process.

Optical Fiber On-Line Detection System for Non-Touch Monitoring Roller Shape

NASA Astrophysics Data System (ADS)

Guo, Y.; Wang, Y. T.

2006-10-01

Basing on the principle of reflective displacement fiber-optic sensor, a high accuracy non-touch on-line optical fiber measurement system for roller shape is presented. The principle and composition of the detection system and the operation process are expatiated also. By using a novel probe of three optical fibers in equal transverse space, the effects of fluctuations in the light source, reflective changing of target surface and the intensity losses in the fiber lines are automatically compensated. Meantime, an optical fiber sensor model of correcting static error based on BP artificial neural network (ANN) is set up. Also by using interpolation method and value filtering to process the signals, effectively reduce the influence of random noise and the vibration of the roller bearing. So enhance the accuracy and resolution remarkably. Experiment proves that the accuracy of the system reach to the demand of practical production process, it provides a new method for the high speed, accurate and automatic on line detection of the mill roller shape.

Efficient calculation of beyond RPA correlation energies in the dielectric matrix formalism

NASA Astrophysics Data System (ADS)

Beuerle, Matthias; Graf, Daniel; Schurkus, Henry F.; Ochsenfeld, Christian

2018-05-01

We present efficient methods to calculate beyond random phase approximation (RPA) correlation energies for molecular systems with up to 500 atoms. To reduce the computational cost, we employ the resolution-of-the-identity and a double-Laplace transform of the non-interacting polarization propagator in conjunction with an atomic orbital formalism. Further improvements are achieved using integral screening and the introduction of Cholesky decomposed densities. Our methods are applicable to the dielectric matrix formalism of RPA including second-order screened exchange (RPA-SOSEX), the RPA electron-hole time-dependent Hartree-Fock (RPA-eh-TDHF) approximation, and RPA renormalized perturbation theory using an approximate exchange kernel (RPA-AXK). We give an application of our methodology by presenting RPA-SOSEX benchmark results for the L7 test set of large, dispersion dominated molecules, yielding a mean absolute error below 1 kcal/mol. The present work enables calculating beyond RPA correlation energies for significantly larger molecules than possible to date, thereby extending the applicability of these methods to a wider range of chemical systems.

Brief Alcohol Interventions for Adolescents and Young Adults: A Systematic Review and Meta-analysis

PubMed Central

Tanner-Smith, Emily E.; Lipsey, Mark W.

2014-01-01

This study reports findings from a meta-analysis summarizing the effectiveness of brief alcohol interventions for adolescents (age 11-18) and young adults (age 19-30). We identified 185 eligible study samples using a comprehensive literature search and synthesized findings using random-effects meta-analyses with robust standard errors. Overall, brief alcohol interventions led to significant reductions in alcohol consumption and alcohol-related problems among adolescents (ḡ = 0.27 and ḡ = 0.19) and young adults (ḡ = 0.17 and ḡ = 0.11). These effects persisted for up to one year after intervention and did not vary across participant demographics, intervention length, or intervention format. However, certain intervention modalities (e.g., motivational interviewing) and components (e.g., decisional balance, goal-setting exercises) were associated with larger effects. We conclude that brief alcohol interventions yield beneficial effects on alcohol-related outcomes for adolescents and young adults that are modest but potentially worthwhile given their brevity and low cost. PMID:25300577

A top-down manner-based DCNN architecture for semantic image segmentation.

PubMed

Qiao, Kai; Chen, Jian; Wang, Linyuan; Zeng, Lei; Yan, Bin

2017-01-01

Given their powerful feature representation for recognition, deep convolutional neural networks (DCNNs) have been driving rapid advances in high-level computer vision tasks. However, their performance in semantic image segmentation is still not satisfactory. Based on the analysis of visual mechanism, we conclude that DCNNs in a bottom-up manner are not enough, because semantic image segmentation task requires not only recognition but also visual attention capability. In the study, superpixels containing visual attention information are introduced in a top-down manner, and an extensible architecture is proposed to improve the segmentation results of current DCNN-based methods. We employ the current state-of-the-art fully convolutional network (FCN) and FCN with conditional random field (DeepLab-CRF) as baselines to validate our architecture. Experimental results of the PASCAL VOC segmentation task qualitatively show that coarse edges and error segmentation results are well improved. We also quantitatively obtain about 2%-3% intersection over union (IOU) accuracy improvement on the PASCAL VOC 2011 and 2012 test sets.

Game-Based Learning as a Vehicle to Teach First Aid Content: A Randomized Experiment

ERIC Educational Resources Information Center

Charlier, Nathalie; De Fraine, Bieke

2013-01-01

Background: Knowledge of first aid (FA), which constitutes lifesaving treatments for injuries or illnesses, is important for every individual. In this study, we have set up a group-randomized controlled trial to assess the effectiveness of a board game for learning FA. Methods: Four class groups (120 students) were randomly assigned to 2…

Network problem threshold

NASA Technical Reports Server (NTRS)

Gejji, Raghvendra, R.

1992-01-01

Network transmission errors such as collisions, CRC errors, misalignment, etc. are statistical in nature. Although errors can vary randomly, a high level of errors does indicate specific network problems, e.g. equipment failure. In this project, we have studied the random nature of collisions theoretically as well as by gathering statistics, and established a numerical threshold above which a network problem is indicated with high probability.

Reference-free error estimation for multiple measurement methods.

PubMed

Madan, Hennadii; Pernuš, Franjo; Špiclin, Žiga

2018-01-01

We present a computational framework to select the most accurate and precise method of measurement of a certain quantity, when there is no access to the true value of the measurand. A typical use case is when several image analysis methods are applied to measure the value of a particular quantitative imaging biomarker from the same images. The accuracy of each measurement method is characterized by systematic error (bias), which is modeled as a polynomial in true values of measurand, and the precision as random error modeled with a Gaussian random variable. In contrast to previous works, the random errors are modeled jointly across all methods, thereby enabling the framework to analyze measurement methods based on similar principles, which may have correlated random errors. Furthermore, the posterior distribution of the error model parameters is estimated from samples obtained by Markov chain Monte-Carlo and analyzed to estimate the parameter values and the unknown true values of the measurand. The framework was validated on six synthetic and one clinical dataset containing measurements of total lesion load, a biomarker of neurodegenerative diseases, which was obtained with four automatic methods by analyzing brain magnetic resonance images. The estimates of bias and random error were in a good agreement with the corresponding least squares regression estimates against a reference.

The Effect of Adenotonsillectomy for Childhood Sleep Apnea on Cardiometabolic Measures

PubMed Central

Quante, Mirja; Wang, Rui; Weng, Jia; Rosen, Carol L.; Amin, Raouf; Garetz, Susan L.; Katz, Eliot; Paruthi, Shalini; Arens, Raanan; Muzumdar, Hiren; Marcus, Carole L.; Ellenberg, Susan; Redline, Susan

2015-01-01

Study Objectives: Obstructive sleep apnea syndrome (OSAS) has been associated with cardiometabolic disease in adults. In children, this association is unclear. We evaluated the effect of early adenotonsillectomy (eAT) for treatment of OSAS on blood pressure, heart rate, lipids, glucose, insulin, and C-reactive protein. We also analyzed whether these parameters at baseline and changes at follow-up correlated with polysomnographic indices. Design: Data collected at baseline and 7-mo follow-up were analyzed from a randomized controlled trial, the Childhood Adenotonsillectomy Trial (CHAT). Setting: Clinical referral setting from multiple centers. Participants: There were 464 children, ages 5 to 9.9 y with OSAS without severe hypoxemia. Interventions: Randomization to eAT or Watchful Waiting with Supportive Care (WWSC). Measurements and Results: There was no significant change of cardiometabolic parameters over the 7-mo interval in the eAT group compared to WWSC group. However, overnight heart rate was incrementally higher in association with baseline OSAS severity (average heart rate increase of 3 beats per minute [bpm] for apnea-hypopnea index [AHI] of 2 versus 10; [standard error = 0.60]). Each 5-unit improvement in AHI and 5 mmHg improvement in peak end-tidal CO2 were estimated to reduce heart rate by 1 and 1.5 bpm, respectively. An increase in N3 sleep also was associated with small reductions in systolic blood pressure percentile. Conclusions: There is little variation in standard cardiometabolic parameters in children with obstructive sleep apnea syndrome (OSAS) but without severe hypoxemia at baseline or after intervention. Of all measures, overnight heart rate emerged as the most sensitive parameter of pediatric OSAS severity. Clinical Trial Registration: Clinicaltrials.gov (#NCT00560859) Citation: Quante M, Wang R, Weng J, Rosen CL, Amin R, Garetz SL, Katz E, Paruthi S, Arens R, Muzumdar H, Marcus CL, Ellenberg S, Redline S. The effect of adenotonsillectomy for childhood sleep apnea on cardiometabolic measures. SLEEP 2015;38(9):1395–1403. PMID:25669177

Errors in radial velocity variance from Doppler wind lidar

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

Wang, H.; Barthelmie, R. J.; Doubrawa, P.

A high-fidelity lidar turbulence measurement technique relies on accurate estimates of radial velocity variance that are subject to both systematic and random errors determined by the autocorrelation function of radial velocity, the sampling rate, and the sampling duration. Our paper quantifies the effect of the volumetric averaging in lidar radial velocity measurements on the autocorrelation function and the dependence of the systematic and random errors on the sampling duration, using both statistically simulated and observed data. For current-generation scanning lidars and sampling durations of about 30 min and longer, during which the stationarity assumption is valid for atmospheric flows, themore » systematic error is negligible but the random error exceeds about 10%.« less

Errors in radial velocity variance from Doppler wind lidar

DOE PAGES

Wang, H.; Barthelmie, R. J.; Doubrawa, P.; ...

2016-08-29

A high-fidelity lidar turbulence measurement technique relies on accurate estimates of radial velocity variance that are subject to both systematic and random errors determined by the autocorrelation function of radial velocity, the sampling rate, and the sampling duration. Our paper quantifies the effect of the volumetric averaging in lidar radial velocity measurements on the autocorrelation function and the dependence of the systematic and random errors on the sampling duration, using both statistically simulated and observed data. For current-generation scanning lidars and sampling durations of about 30 min and longer, during which the stationarity assumption is valid for atmospheric flows, themore » systematic error is negligible but the random error exceeds about 10%.« less

Metrics for Business Process Models

NASA Astrophysics Data System (ADS)

Mendling, Jan

Up until now, there has been little research on why people introduce errors in real-world business process models. In a more general context, Simon [404] points to the limitations of cognitive capabilities and concludes that humans act rationally only to a certain extent. Concerning modeling errors, this argument would imply that human modelers lose track of the interrelations of large and complex models due to their limited cognitive capabilities and introduce errors that they would not insert in a small model. A recent study by Mendling et al. [275] explores in how far certain complexity metrics of business process models have the potential to serve as error determinants. The authors conclude that complexity indeed appears to have an impact on error probability. Before we can test such a hypothesis in a more general setting, we have to establish an understanding of how we can define determinants that drive error probability and how we can measure them.

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.

Detecting and preventing error propagation via competitive learning.

PubMed

Silva, Thiago Christiano; Zhao, Liang

2013-05-01

Semisupervised learning is a machine learning approach which is able to employ both labeled and unlabeled samples in the training process. It is an important mechanism for autonomous systems due to the ability of exploiting the already acquired information and for exploring the new knowledge in the learning space at the same time. In these cases, the reliability of the labels is a crucial factor, because mislabeled samples may propagate wrong labels to a portion of or even the entire data set. This paper has the objective of addressing the error propagation problem originated by these mislabeled samples by presenting a mechanism embedded in a network-based (graph-based) semisupervised learning method. Such a procedure is based on a combined random-preferential walk of particles in a network constructed from the input data set. The particles of the same class cooperate among them, while the particles of different classes compete with each other to propagate class labels to the whole network. Computer simulations conducted on synthetic and real-world data sets reveal the effectiveness of the model. Copyright © 2012 Elsevier Ltd. All rights reserved.

Error detection and data smoothing based on local procedures

NASA Technical Reports Server (NTRS)

Guerra, V. M.

1974-01-01

An algorithm is presented which is able to locate isolated bad points and correct them without contaminating the rest of the good data. This work has been greatly influenced and motivated by what is currently done in the manual loft. It is not within the scope of this work to handle small random errors characteristic of a noisy system, and it is therefore assumed that the bad points are isolated and relatively few when compared with the total number of points. Motivated by the desire to imitate the loftsman a visual experiment was conducted to determine what is considered smooth data. This criterion is used to determine how much the data should be smoothed and to prove that this method produces such data. The method utimately converges to a set of points that lies on the polynomial that interpolates the first and last points; however convergence to such a set is definitely not the purpose of our algorithm. The proof of convergence is necessary to demonstrate that oscillation does not take place and that in a finite number of steps the method produces a set as smooth as desired.

Bias, Confounding, and Interaction: Lions and Tigers, and Bears, Oh My!

PubMed

Vetter, Thomas R; Mascha, Edward J

2017-09-01

Epidemiologists seek to make a valid inference about the causal effect between an exposure and a disease in a specific population, using representative sample data from a specific population. Clinical researchers likewise seek to make a valid inference about the association between an intervention and outcome(s) in a specific population, based upon their randomly collected, representative sample data. Both do so by using the available data about the sample variable to make a valid estimate about its corresponding or underlying, but unknown population parameter. Random error in an experiment can be due to the natural, periodic fluctuation or variation in the accuracy or precision of virtually any data sampling technique or health measurement tool or scale. In a clinical research study, random error can be due to not only innate human variability but also purely chance. Systematic error in an experiment arises from an innate flaw in the data sampling technique or measurement instrument. In the clinical research setting, systematic error is more commonly referred to as systematic bias. The most commonly encountered types of bias in anesthesia, perioperative, critical care, and pain medicine research include recall bias, observational bias (Hawthorne effect), attrition bias, misclassification or informational bias, and selection bias. A confounding variable is a factor associated with both the exposure of interest and the outcome of interest. A confounding variable (confounding factor or confounder) is a variable that correlates (positively or negatively) with both the exposure and outcome. Confounding is typically not an issue in a randomized trial because the randomized groups are sufficiently balanced on all potential confounding variables, both observed and nonobserved. However, confounding can be a major problem with any observational (nonrandomized) study. Ignoring confounding in an observational study will often result in a "distorted" or incorrect estimate of the association or treatment effect. Interaction among variables, also known as effect modification, exists when the effect of 1 explanatory variable on the outcome depends on the particular level or value of another explanatory variable. Bias and confounding are common potential explanations for statistically significant associations between exposure and outcome when the true relationship is noncausal. Understanding interactions is vital to proper interpretation of treatment effects. These complex concepts should be consistently and appropriately considered whenever one is not only designing but also analyzing and interpreting data from a randomized trial or observational study.

Prepopulated radiology report templates: a prospective analysis of error rate and turnaround time.

PubMed

Hawkins, C M; Hall, S; Hardin, J; Salisbury, S; Towbin, A J

2012-08-01

Current speech recognition software allows exam-specific standard reports to be prepopulated into the dictation field based on the radiology information system procedure code. While it is thought that prepopulating reports can decrease the time required to dictate a study and the overall number of errors in the final report, this hypothesis has not been studied in a clinical setting. A prospective study was performed. During the first week, radiologists dictated all studies using prepopulated standard reports. During the second week, all studies were dictated after prepopulated reports had been disabled. Final radiology reports were evaluated for 11 different types of errors. Each error within a report was classified individually. The median time required to dictate an exam was compared between the 2 weeks. There were 12,387 reports dictated during the study, of which, 1,173 randomly distributed reports were analyzed for errors. There was no difference in the number of errors per report between the 2 weeks; however, radiologists overwhelmingly preferred using a standard report both weeks. Grammatical errors were by far the most common error type, followed by missense errors and errors of omission. There was no significant difference in the median dictation time when comparing studies performed each week. The use of prepopulated reports does not alone affect the error rate or dictation time of radiology reports. While it is a useful feature for radiologists, it must be coupled with other strategies in order to decrease errors.

Nurses' behaviors and visual scanning patterns may reduce patient identification errors.

PubMed

Marquard, Jenna L; Henneman, Philip L; He, Ze; Jo, Junghee; Fisher, Donald L; Henneman, Elizabeth A

2011-09-01

Patient identification (ID) errors occurring during the medication administration process can be fatal. The aim of this study is to determine whether differences in nurses' behaviors and visual scanning patterns during the medication administration process influence their capacities to identify patient ID errors. Nurse participants (n = 20) administered medications to 3 patients in a simulated clinical setting, with 1 patient having an embedded ID error. Error-identifying nurses tended to complete more process steps in a similar amount of time than non-error-identifying nurses and tended to scan information across artifacts (e.g., ID band, patient chart, medication label) rather than fixating on several pieces of information on a single artifact before fixating on another artifact. Non-error-indentifying nurses tended to increase their durations of off-topic conversations-a type of process interruption-over the course of the trials; the difference between groups was significant in the trial with the embedded ID error. Error-identifying nurses tended to have their most fixations in a row on the patient's chart, whereas non-error-identifying nurses did not tend to have a single artifact on which they consistently fixated. Finally, error-identifying nurses tended to have predictable eye fixation sequences across artifacts, whereas non-error-identifying nurses tended to have seemingly random eye fixation sequences. This finding has implications for nurse training and the design of tools and technologies that support nurses as they complete the medication administration process. (c) 2011 APA, all rights reserved.

[Qualitative evaluation of blood products records in a hospital].

PubMed

Lartigue, B; Catillon, E

2012-02-01

This study aimed at evaluating the qualitative performance of blood products traceability from paper and electronic medical records in a hospital. Quality of date/time documentation was assessed by detection, for 20minutes or more, of chronological errors and inter-source inconsistencies, in a random sample of 168 blood products transfused during 2009. A receipt date/time was confirmed in 52% of paper records; a data entry error was attested in 25% of paper records, and 21% of electronic records. A transfusion date/time was notified in 93% of paper records, with a data entry error in 26% of paper records and 25% of electronic records. The patient medical record held at least one date/time error in 18% and 17%, for receipt and transfusion respectively. Environmental factors (clinical setting, urgency, blood product category) did not contributed to data error rates. Although blood products traceability has good quantitative results, the recorded documentation is not qualitative. In our study, data entry errors are similar in electronic or paper records, but the global failure rate is lesser in electronic records because omissions are controlled. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Analysis of Wind Tunnel Polar Replicates Using the Modern Design of Experiments

NASA Technical Reports Server (NTRS)

Deloach, Richard; Micol, John R.

2010-01-01

The role of variance in a Modern Design of Experiments analysis of wind tunnel data is reviewed, with distinctions made between explained and unexplained variance. The partitioning of unexplained variance into systematic and random components is illustrated, with examples of the elusive systematic component provided for various types of real-world tests. The importance of detecting and defending against systematic unexplained variance in wind tunnel testing is discussed, and the random and systematic components of unexplained variance are examined for a representative wind tunnel data set acquired in a test in which a missile is used as a test article. The adverse impact of correlated (non-independent) experimental errors is described, and recommendations are offered for replication strategies that facilitate the quantification of random and systematic unexplained variance.

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

Fuangrod, T; Simpson, J; Greer, P

Purpose: A real-time patient treatment delivery verification system using EPID (Watchdog) has been developed as an advanced patient safety tool. In a pilot study data was acquired for 119 prostate and head and neck (HN) IMRT patient deliveries to generate body-site specific action limits using statistical process control. The purpose of this study is to determine the sensitivity of Watchdog to detect clinically significant errors during treatment delivery. Methods: Watchdog utilizes a physics-based model to generate a series of predicted transit cine EPID images as a reference data set, and compares these in real-time to measured transit cine-EPID images acquiredmore » during treatment using chi comparison (4%, 4mm criteria) after the initial 2s of treatment to allow for dose ramp-up. Four study cases were used; dosimetric (monitor unit) errors in prostate (7 fields) and HN (9 fields) IMRT treatments of (5%, 7%, 10%) and positioning (systematic displacement) errors in the same treatments of (5mm, 7mm, 10mm). These errors were introduced by modifying the patient CT scan and re-calculating the predicted EPID data set. The error embedded predicted EPID data sets were compared to the measured EPID data acquired during patient treatment. The treatment delivery percentage (measured from 2s) where Watchdog detected the error was determined. Results: Watchdog detected all simulated errors for all fields during delivery. The dosimetric errors were detected at average treatment delivery percentage of (4%, 0%, 0%) and (7%, 0%, 0%) for prostate and HN respectively. For patient positional errors, the average treatment delivery percentage was (52%, 43%, 25%) and (39%, 16%, 6%). Conclusion: These results suggest that Watchdog can detect significant dosimetric and positioning errors in prostate and HN IMRT treatments in real-time allowing for treatment interruption. Displacements of the patient require longer to detect however incorrect body site or very large geographic misses will be detected rapidly.« less

The Coast Artillery Journal. Volume 68, Number 6, June 1928

DTIC Science & Technology

1928-06-01

text book on the Turkish Army, and two guide books. The maps available were not up to date and contained few details. Writing in his diary under date...The moon shone faintly through the clouds and at 1 :00 A. M. the ships stopped, waiting for the moon to set. While lying here, all six men-of-war...against the firing table value of 63 yards. The prohable error of the prohahle error was then determined in the same manner that we ordinarily compute the

Knowledge of healthcare professionals about medication errors in hospitals

PubMed Central

Abdel-Latif, Mohamed M. M.

2016-01-01

Context: Medication errors are the most common types of medical errors in hospitals and leading cause of morbidity and mortality among patients. Aims: The aim of the present study was to assess the knowledge of healthcare professionals about medication errors in hospitals. Settings and Design: A self-administered questionnaire was distributed to randomly selected healthcare professionals in eight hospitals in Madinah, Saudi Arabia. Subjects and Methods: An 18-item survey was designed and comprised questions on demographic data, knowledge of medication errors, availability of reporting systems in hospitals, attitudes toward error reporting, causes of medication errors. Statistical Analysis Used: Data were analyzed with Statistical Package for the Social Sciences software Version 17. Results: A total of 323 of healthcare professionals completed the questionnaire with 64.6% response rate of 138 (42.72%) physicians, 34 (10.53%) pharmacists, and 151 (46.75%) nurses. A majority of the participants had a good knowledge about medication errors concept and their dangers on patients. Only 68.7% of them were aware of reporting systems in hospitals. Healthcare professionals revealed that there was no clear mechanism available for reporting of errors in most hospitals. Prescribing (46.5%) and administration (29%) errors were the main causes of errors. The most frequently encountered medication errors were anti-hypertensives, antidiabetics, antibiotics, digoxin, and insulin. Conclusions: This study revealed differences in the awareness among healthcare professionals toward medication errors in hospitals. The poor knowledge about medication errors emphasized the urgent necessity to adopt appropriate measures to raise awareness about medication errors in Saudi hospitals. PMID:27330261

Simulation of wave propagation in three-dimensional random media

NASA Astrophysics Data System (ADS)

Coles, Wm. A.; Filice, J. P.; Frehlich, R. G.; Yadlowsky, M.

1995-04-01

Quantitative error analyses for the simulation of wave propagation in three-dimensional random media, when narrow angular scattering is assumed, are presented for plane-wave and spherical-wave geometry. This includes the errors that result from finite grid size, finite simulation dimensions, and the separation of the two-dimensional screens along the propagation direction. Simple error scalings are determined for power-law spectra of the random refractive indices of the media. The effects of a finite inner scale are also considered. The spatial spectra of the intensity errors are calculated and compared with the spatial spectra of

TU-H-207A-02: Relative Importance of the Various Factors Influencing the Accuracy of Monte Carlo Simulated CT Dose Index

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

Marous, L; Muryn, J; Liptak, C

2016-06-15

Purpose: Monte Carlo simulation is a frequently used technique for assessing patient dose in CT. The accuracy of a Monte Carlo program is often validated using the standard CT dose index (CTDI) phantoms by comparing simulated and measured CTDI{sub 100}. To achieve good agreement, many input parameters in the simulation (e.g., energy spectrum and effective beam width) need to be determined. However, not all the parameters have equal importance. Our aim was to assess the relative importance of the various factors that influence the accuracy of simulated CTDI{sub 100}. Methods: A Monte Carlo program previously validated for a clinical CTmore » system was used to simulate CTDI{sub 100}. For the standard CTDI phantoms (32 and 16 cm in diameter), CTDI{sub 100} values from central and four peripheral locations at 70 and 120 kVp were first simulated using a set of reference input parameter values (treated as the truth). To emulate the situation in which the input parameter values used by the researcher may deviate from the truth, additional simulations were performed in which intentional errors were introduced into the input parameters, the effects of which on simulated CTDI{sub 100} were analyzed. Results: At 38.4-mm collimation, errors in effective beam width up to 5.0 mm showed negligible effects on simulated CTDI{sub 100} (<1.0%). Likewise, errors in acrylic density of up to 0.01 g/cm{sup 3} resulted in small CTDI{sub 100} errors (<2.5%). In contrast, errors in spectral HVL produced more significant effects: slight deviations (±0.2 mm Al) produced errors up to 4.4%, whereas more extreme deviations (±1.4 mm Al) produced errors as high as 25.9%. Lastly, ignoring the CT table introduced errors up to 13.9%. Conclusion: Monte Carlo simulated CTDI{sub 100} is insensitive to errors in effective beam width and acrylic density. However, they are sensitive to errors in spectral HVL. To obtain accurate results, the CT table should not be ignored. This work was supported by a Faculty Research and Development Award from Cleveland State University.« less

Design and implementation of a system for treating paediatric patients with stereotactically-guided conformal radiotherapy.

PubMed

Adams, E J; Suter, B L; Warrington, A P; Black, P; Saran, F; Brada, M

2001-09-01

Stereotactically-guided conformal radiotherapy (SCRT) allows the delivery of highly conformal dose distributions to localised brain tumours. This is of particular importance for children, whose often excellent long-term prognosis should be accompanied by low toxicity. The commercial immobilisation system in use at our hospital for adults was felt to be too heavy for children, and precluded the use of anaesthesia, which is sometimes required for paediatric patients. This paper therefore describes the design and implementation of a system for treating children with SCRT. This system needed to be well tolerated by patients, with good access for treating typical childhood malignancies. A lightweight frame was developed for immobilisation, with a shell-based alternative for patients requiring general anaesthetic. Procedures were set up to introduce the patients to the frame system in order to maximise patient co-operation and comfort. Film measurements were made to assess the impact of the frame on transmission and surface dose. The reproducibility of the systems was assessed using electronic portal images. Both frame and shell systems are in clinical use. The frame weighs 0.6 kg and is well tolerated. It has a transmission of 92-96%, and fields which pass through it deliver surface doses of 58-82% of the dose at d(max), compared to 18% when no frame is present. However, the frame is constructed to maximise the availability of unobstructed beam directions. Reproducibility measurements for the frame showed a mean random error of 1.0+/-0.2mm in two dimensions (2D) and 1.4+/-0.7 mm in 3D. The mean systematic error in 3D was 2.2mm, and 90% of all overall 3D errors were less than 3.4mm. For the shell system, the mean 2D random error was 1.5+/-0.2mm. Two well-tolerated immobilisation devices have been developed for fractionated SCRT treatment of paediatric patients. A lightweight frame system gives a wide range of possible unobstructed beam directions, although beams that intersect the frame are not precluded, provided that output corrections are applied. A shell system allows the use of general anaesthesia. Both systems give reproducible immobilisation to complement the high-precision treatment delivery.

An active co-phasing imaging testbed with segmented mirrors

NASA Astrophysics Data System (ADS)

Zhao, Weirui; Cao, Genrui

2011-06-01

An active co-phasing imaging testbed with high accurate optical adjustment and control in nanometer scale was set up to validate the algorithms of piston and tip-tilt error sensing and real-time adjusting. Modularization design was adopted. The primary mirror was spherical and divided into three sub-mirrors. One of them was fixed and worked as reference segment, the others were adjustable respectively related to the fixed segment in three freedoms (piston, tip and tilt) by using sensitive micro-displacement actuators in the range of 15mm with a resolution of 3nm. The method of twodimension dispersed fringe analysis was used to sense the piston error between the adjacent segments in the range of 200μm with a repeatability of 2nm. And the tip-tilt error was gained with the method of centroid sensing. Co-phasing image could be realized by correcting the errors measured above with the sensitive micro-displacement actuators driven by a computer. The process of co-phasing error sensing and correcting could be monitored in real time by a scrutiny module set in this testbed. A FISBA interferometer was introduced to evaluate the co-phasing performance, and finally a total residual surface error of about 50nm rms was achieved.

In-Situ Cameras for Radiometric Correction of Remotely Sensed Data

NASA Astrophysics Data System (ADS)

Kautz, Jess S.

The atmosphere distorts the spectrum of remotely sensed data, negatively affecting all forms of investigating Earth's surface. To gather reliable data, it is vital that atmospheric corrections are accurate. The current state of the field of atmospheric correction does not account well for the benefits and costs of different correction algorithms. Ground spectral data are required to evaluate these algorithms better. This dissertation explores using cameras as radiometers as a means of gathering ground spectral data. I introduce techniques to implement a camera systems for atmospheric correction using off the shelf parts. To aid the design of future camera systems for radiometric correction, methods for estimating the system error prior to construction, calibration and testing of the resulting camera system are explored. Simulations are used to investigate the relationship between the reflectance accuracy of the camera system and the quality of atmospheric correction. In the design phase, read noise and filter choice are found to be the strongest sources of system error. I explain the calibration methods for the camera system, showing the problems of pixel to angle calibration, and adapting the web camera for scientific work. The camera system is tested in the field to estimate its ability to recover directional reflectance from BRF data. I estimate the error in the system due to the experimental set up, then explore how the system error changes with different cameras, environmental set-ups and inversions. With these experiments, I learn about the importance of the dynamic range of the camera, and the input ranges used for the PROSAIL inversion. Evidence that the camera can perform within the specification set for ELM correction in this dissertation is evaluated. The analysis is concluded by simulating an ELM correction of a scene using various numbers of calibration targets, and levels of system error, to find the number of cameras needed for a full-scale implementation.

Robust Adaptive Beamforming with Sensor Position Errors Using Weighted Subspace Fitting-Based Covariance Matrix Reconstruction.

PubMed

Chen, Peng; Yang, Yixin; Wang, Yong; Ma, Yuanliang

2018-05-08

When sensor position errors exist, the performance of recently proposed interference-plus-noise covariance matrix (INCM)-based adaptive beamformers may be severely degraded. In this paper, we propose a weighted subspace fitting-based INCM reconstruction algorithm to overcome sensor displacement for linear arrays. By estimating the rough signal directions, we construct a novel possible mismatched steering vector (SV) set. We analyze the proximity of the signal subspace from the sample covariance matrix (SCM) and the space spanned by the possible mismatched SV set. After solving an iterative optimization problem, we reconstruct the INCM using the estimated sensor position errors. Then we estimate the SV of the desired signal by solving an optimization problem with the reconstructed INCM. The main advantage of the proposed algorithm is its robustness against SV mismatches dominated by unknown sensor position errors. Numerical examples show that even if the position errors are up to half of the assumed sensor spacing, the output signal-to-interference-plus-noise ratio is only reduced by 4 dB. Beam patterns plotted using experiment data show that the interference suppression capability of the proposed beamformer outperforms other tested beamformers.

Evaluation of RSA set-up from a clinical biplane fluoroscopy system for 3D joint kinematic analysis.

PubMed

Bonanzinga, Tommaso; Signorelli, Cecilia; Bontempi, Marco; Russo, Alessandro; Zaffagnini, Stefano; Marcacci, Maurilio; Bragonzoni, Laura

2016-01-01

dinamic roentgen stereophotogrammetric analysis (RSA), a technique currently based only on customized radiographic equipment, has been shown to be a very accurate method for detecting three-dimensional (3D) joint motion. The aim of the present work was to evaluate the applicability of an innovative RSA set-up for in vivo knee kinematic analysis, using a biplane fluoroscopic image system. To this end, the Authors describe the set-up as well as a possible protocol for clinical knee joint evaluation. The accuracy of the kinematic measurements is assessed. the Authors evaluated the accuracy of 3D kinematic analysis of the knee in a new RSA set-up, based on a commercial biplane fluoroscopy system integrated into the clinical environment. The study was organized in three main phases: an in vitro test under static conditions, an in vitro test under dynamic conditions reproducing a flexion-extension range of motion (ROM), and an in vivo analysis of the flexion-extension ROM. For each test, the following were calculated, as an indication of the tracking accuracy: mean, minimum, maximum values and standard deviation of the error of rigid body fitting. in terms of rigid body fitting, in vivo test errors were found to be 0.10±0.05 mm. Phantom tests in static and kinematic conditions showed precision levels, for translations and rotations, of below 0.1 mm/0.2° and below 0.5 mm/0.3° respectively for all directions. the results of this study suggest that kinematic RSA can be successfully performed using a standard clinical biplane fluoroscopy system for the acquisition of slow movements of the lower limb. a kinematic RSA set-up using a clinical biplane fluoroscopy system is potentially applicable and provides a useful method for obtaining better characterization of joint biomechanics.

The effectiveness of computerized order entry at reducing preventable adverse drug events and medication errors in hospital settings: a systematic review and meta-analysis

PubMed Central

2014-01-01

Background The Health Information Technology for Economic and Clinical Health (HITECH) Act subsidizes implementation by hospitals of electronic health records with computerized provider order entry (CPOE), which may reduce patient injuries caused by medication errors (preventable adverse drug events, pADEs). Effects on pADEs have not been rigorously quantified, and effects on medication errors have been variable. The objectives of this analysis were to assess the effectiveness of CPOE at reducing pADEs in hospital-related settings, and examine reasons for heterogeneous effects on medication errors. Methods Articles were identified using MEDLINE, Cochrane Library, Econlit, web-based databases, and bibliographies of previous systematic reviews (September 2013). Eligible studies compared CPOE with paper-order entry in acute care hospitals, and examined diverse pADEs or medication errors. Studies on children or with limited event-detection methods were excluded. Two investigators extracted data on events and factors potentially associated with effectiveness. We used random effects models to pool data. Results Sixteen studies addressing medication errors met pooling criteria; six also addressed pADEs. Thirteen studies used pre-post designs. Compared with paper-order entry, CPOE was associated with half as many pADEs (pooled risk ratio (RR) = 0.47, 95% CI 0.31 to 0.71) and medication errors (RR = 0.46, 95% CI 0.35 to 0.60). Regarding reasons for heterogeneous effects on medication errors, five intervention factors and two contextual factors were sufficiently reported to support subgroup analyses or meta-regression. Differences between commercial versus homegrown systems, presence and sophistication of clinical decision support, hospital-wide versus limited implementation, and US versus non-US studies were not significant, nor was timing of publication. Higher baseline rates of medication errors predicted greater reductions (P < 0.001). Other context and implementation variables were seldom reported. Conclusions In hospital-related settings, implementing CPOE is associated with a greater than 50% decline in pADEs, although the studies used weak designs. Decreases in medication errors are similar and robust to variations in important aspects of intervention design and context. This suggests that CPOE implementation, as subsidized under the HITECH Act, may benefit public health. More detailed reporting of the context and process of implementation could shed light on factors associated with greater effectiveness. PMID:24894078

Scattering from binary optics

NASA Technical Reports Server (NTRS)

Ricks, Douglas W.

1993-01-01

There are a number of sources of scattering in binary optics: etch depth errors, line edge errors, quantization errors, roughness, and the binary approximation to the ideal surface. These sources of scattering can be systematic (deterministic) or random. In this paper, scattering formulas for both systematic and random errors are derived using Fourier optics. These formulas can be used to explain the results of scattering measurements and computer simulations.

Not to put too fine a point on it - does increasing precision of geographic referencing improve species distribution models for a wide-ranging migratory bat?

USGS Publications Warehouse

Hayes, Mark A.; Ozenberger, Katharine; Cryan, Paul M.; Wunder, Michael B.

2015-01-01

Bat specimens held in natural history museum collections can provide insights into the distribution of species. However, there are several important sources of spatial error associated with natural history specimens that may influence the analysis and mapping of bat species distributions. We analyzed the importance of geographic referencing and error correction in species distribution modeling (SDM) using occurrence records of hoary bats (Lasiurus cinereus). This species is known to migrate long distances and is a species of increasing concern due to fatalities documented at wind energy facilities in North America. We used 3,215 museum occurrence records collected from 1950–2000 for hoary bats in North America. We compared SDM performance using five approaches: generalized linear models, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy models. We evaluated results using three SDM performance metrics (AUC, sensitivity, and specificity) and two data sets: one comprised of the original occurrence data, and a second data set consisting of these same records after the locations were adjusted to correct for identifiable spatial errors. The increase in precision improved the mean estimated spatial error associated with hoary bat records from 5.11 km to 1.58 km, and this reduction in error resulted in a slight increase in all three SDM performance metrics. These results provide insights into the importance of geographic referencing and the value of correcting spatial errors in modeling the distribution of a wide-ranging bat species. We conclude that the considerable time and effort invested in carefully increasing the precision of the occurrence locations in this data set was not worth the marginal gains in improved SDM performance, and it seems likely that gains would be similar for other bat species that range across large areas of the continent, migrate, and are habitat generalists.

Correction of stream quality trends for the effects of laboratory measurement bias

USGS Publications Warehouse

Alexander, Richard B.; Smith, Richard A.; Schwarz, Gregory E.

1993-01-01

We present a statistical model relating measurements of water quality to associated errors in laboratory methods. Estimation of the model allows us to correct trends in water quality for long-term and short-term variations in laboratory measurement errors. An illustration of the bias correction method for a large national set of stream water quality and quality assurance data shows that reductions in the bias of estimates of water quality trend slopes are achieved at the expense of increases in the variance of these estimates. Slight improvements occur in the precision of estimates of trend in bias by using correlative information on bias and water quality to estimate random variations in measurement bias. The results of this investigation stress the need for reliable, long-term quality assurance data and efficient statistical methods to assess the effects of measurement errors on the detection of water quality trends.

Statistical Characterization of Environmental Error Sources Affecting Electronically Scanned Pressure Transducers

NASA Technical Reports Server (NTRS)

Green, Del L.; Walker, Eric L.; Everhart, Joel L.

2006-01-01

Minimization of uncertainty is essential to extend the usable range of the 15-psid Electronically Scanned Pressure [ESP) transducer measurements to the low free-stream static pressures found in hypersonic wind tunnels. Statistical characterization of environmental error sources inducing much of this uncertainty requires a well defined and controlled calibration method. Employing such a controlled calibration system, several studies were conducted that provide quantitative information detailing the required controls needed to minimize environmental and human induced error sources. Results of temperature, environmental pressure, over-pressurization, and set point randomization studies for the 15-psid transducers are presented along with a comparison of two regression methods using data acquired with both 0.36-psid and 15-psid transducers. Together these results provide insight into procedural and environmental controls required for long term high-accuracy pressure measurements near 0.01 psia in the hypersonic testing environment using 15-psid ESP transducers.

Statistical Characterization of Environmental Error Sources Affecting Electronically Scanned Pressure Transducers

NASA Technical Reports Server (NTRS)

Green, Del L.; Walker, Eric L.; Everhart, Joel L.

2006-01-01

Minimization of uncertainty is essential to extend the usable range of the 15-psid Electronically Scanned Pressure (ESP) transducer measurements to the low free-stream static pressures found in hypersonic wind tunnels. Statistical characterization of environmental error sources inducing much of this uncertainty requires a well defined and controlled calibration method. Employing such a controlled calibration system, several studies were conducted that provide quantitative information detailing the required controls needed to minimize environmental and human induced error sources. Results of temperature, environmental pressure, over-pressurization, and set point randomization studies for the 15-psid transducers are presented along with a comparison of two regression methods using data acquired with both 0.36-psid and 15-psid transducers. Together these results provide insight into procedural and environmental controls required for long term high-accuracy pressure measurements near 0.01 psia in the hypersonic testing environment using 15-psid ESP transducers.

SU-C-BRD-02: A Team Focused Clinical Implementation and Failure Mode and Effects Analysis of HDR Skin Brachytherapy Using Valencia and Leipzig Surface Applicators

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

Sayler, E; Harrison, A; Eldredge-Hindy, H

Purpose: and Leipzig applicators (VLAs) are single-channel brachytherapy surface applicators used to treat skin lesions up to 2cm diameter. Source dwell times can be calculated and entered manually after clinical set-up or ultrasound. This procedure differs dramatically from CT-based planning; the novelty and unfamiliarity could lead to severe errors. To build layers of safety and ensure quality, a multidisciplinary team created a protocol and applied Failure Modes and Effects Analysis (FMEA) to the clinical procedure for HDR VLA skin treatments. Methods: team including physicists, physicians, nurses, therapists, residents, and administration developed a clinical procedure for VLA treatment. The procedure wasmore » evaluated using FMEA. Failure modes were identified and scored by severity, occurrence, and detection. The clinical procedure was revised to address high-scoring process nodes. Results: Several key components were added to the clinical procedure to minimize risk probability numbers (RPN): -Treatments are reviewed at weekly QA rounds, where physicians discuss diagnosis, prescription, applicator selection, and set-up. Peer review reduces the likelihood of an inappropriate treatment regime. -A template for HDR skin treatments was established in the clinical EMR system to standardize treatment instructions. This reduces the chances of miscommunication between the physician and planning physicist, and increases the detectability of an error during the physics second check. -A screen check was implemented during the second check to increase detectability of an error. -To reduce error probability, the treatment plan worksheet was designed to display plan parameters in a format visually similar to the treatment console display. This facilitates data entry and verification. -VLAs are color-coded and labeled to match the EMR prescriptions, which simplifies in-room selection and verification. Conclusion: Multidisciplinary planning and FMEA increased delectability and reduced error probability during VLA HDR Brachytherapy. This clinical model may be useful to institutions implementing similar procedures.« less

A comparison of error bounds for a nonlinear tracking system with detection probability Pd < 1.

PubMed

Tong, Huisi; Zhang, Hao; Meng, Huadong; Wang, Xiqin

2012-12-14

Error bounds for nonlinear filtering are very important for performance evaluation and sensor management. This paper presents a comparative study of three error bounds for tracking filtering, when the detection probability is less than unity. One of these bounds is the random finite set (RFS) bound, which is deduced within the framework of finite set statistics. The others, which are the information reduction factor (IRF) posterior Cramer-Rao lower bound (PCRLB) and enumeration method (ENUM) PCRLB are introduced within the framework of finite vector statistics. In this paper, we deduce two propositions and prove that the RFS bound is equal to the ENUM PCRLB, while it is tighter than the IRF PCRLB, when the target exists from the beginning to the end. Considering the disappearance of existing targets and the appearance of new targets, the RFS bound is tighter than both IRF PCRLB and ENUM PCRLB with time, by introducing the uncertainty of target existence. The theory is illustrated by two nonlinear tracking applications: ballistic object tracking and bearings-only tracking. The simulation studies confirm the theory and reveal the relationship among the three bounds.

A Comparison of Error Bounds for a Nonlinear Tracking System with Detection Probability Pd < 1

PubMed Central

Tong, Huisi; Zhang, Hao; Meng, Huadong; Wang, Xiqin

2012-01-01

Error bounds for nonlinear filtering are very important for performance evaluation and sensor management. This paper presents a comparative study of three error bounds for tracking filtering, when the detection probability is less than unity. One of these bounds is the random finite set (RFS) bound, which is deduced within the framework of finite set statistics. The others, which are the information reduction factor (IRF) posterior Cramer-Rao lower bound (PCRLB) and enumeration method (ENUM) PCRLB are introduced within the framework of finite vector statistics. In this paper, we deduce two propositions and prove that the RFS bound is equal to the ENUM PCRLB, while it is tighter than the IRF PCRLB, when the target exists from the beginning to the end. Considering the disappearance of existing targets and the appearance of new targets, the RFS bound is tighter than both IRF PCRLB and ENUM PCRLB with time, by introducing the uncertainty of target existence. The theory is illustrated by two nonlinear tracking applications: ballistic object tracking and bearings-only tracking. The simulation studies confirm the theory and reveal the relationship among the three bounds. PMID:23242274

Dosimetric consequences of translational and rotational errors in frame-less image-guided radiosurgery

PubMed Central

2012-01-01

Background To investigate geometric and dosimetric accuracy of frame-less image-guided radiosurgery (IG-RS) for brain metastases. Methods and materials Single fraction IG-RS was practiced in 72 patients with 98 brain metastases. Patient positioning and immobilization used either double- (n = 71) or single-layer (n = 27) thermoplastic masks. Pre-treatment set-up errors (n = 98) were evaluated with cone-beam CT (CBCT) based image-guidance (IG) and were corrected in six degrees of freedom without an action level. CBCT imaging after treatment measured intra-fractional errors (n = 64). Pre- and post-treatment errors were simulated in the treatment planning system and target coverage and dose conformity were evaluated. Three scenarios of 0 mm, 1 mm and 2 mm GTV-to-PTV (gross tumor volume, planning target volume) safety margins (SM) were simulated. Results Errors prior to IG were 3.9 mm ± 1.7 mm (3D vector) and the maximum rotational error was 1.7° ± 0.8° on average. The post-treatment 3D error was 0.9 mm ± 0.6 mm. No differences between double- and single-layer masks were observed. Intra-fractional errors were significantly correlated with the total treatment time with 0.7mm±0.5mm and 1.2mm±0.7mm for treatment times ≤23 minutes and >23 minutes (p<0.01), respectively. Simulation of RS without image-guidance reduced target coverage and conformity to 75% ± 19% and 60% ± 25% of planned values. Each 3D set-up error of 1 mm decreased target coverage and dose conformity by 6% and 10% on average, respectively, with a large inter-patient variability. Pre-treatment correction of translations only but not rotations did not affect target coverage and conformity. Post-treatment errors reduced target coverage by >5% in 14% of the patients. A 1 mm safety margin fully compensated intra-fractional patient motion. Conclusions IG-RS with online correction of translational errors achieves high geometric and dosimetric accuracy. Intra-fractional errors decrease target coverage and conformity unless compensated with appropriate safety margins. PMID:22531060

The effects of recall errors and of selection bias in epidemiologic studies of mobile phone use and cancer risk.

PubMed

Vrijheid, Martine; Deltour, Isabelle; Krewski, Daniel; Sanchez, Marie; Cardis, Elisabeth

2006-07-01

This paper examines the effects of systematic and random errors in recall and of selection bias in case-control studies of mobile phone use and cancer. These sensitivity analyses are based on Monte-Carlo computer simulations and were carried out within the INTERPHONE Study, an international collaborative case-control study in 13 countries. Recall error scenarios simulated plausible values of random and systematic, non-differential and differential recall errors in amount of mobile phone use reported by study subjects. Plausible values for the recall error were obtained from validation studies. Selection bias scenarios assumed varying selection probabilities for cases and controls, mobile phone users, and non-users. Where possible these selection probabilities were based on existing information from non-respondents in INTERPHONE. Simulations used exposure distributions based on existing INTERPHONE data and assumed varying levels of the true risk of brain cancer related to mobile phone use. Results suggest that random recall errors of plausible levels can lead to a large underestimation in the risk of brain cancer associated with mobile phone use. Random errors were found to have larger impact than plausible systematic errors. Differential errors in recall had very little additional impact in the presence of large random errors. Selection bias resulting from underselection of unexposed controls led to J-shaped exposure-response patterns, with risk apparently decreasing at low to moderate exposure levels. The present results, in conjunction with those of the validation studies conducted within the INTERPHONE study, will play an important role in the interpretation of existing and future case-control studies of mobile phone use and cancer risk, including the INTERPHONE study.

Reliability and measurement error of active knee extension range of motion in a modified slump test position: a pilot study.

PubMed

Tucker, Neil; Reid, Duncan; McNair, Peter

2007-01-01

The slump test is a tool to assess the mechanosensitivity of the neuromeningeal structures within the vertebral canal. While some studies have investigated the reliability of aspects of this test within the same day, few have assessed the reliability across days. Therefore, the purpose of this pilot study was to investigate reliability when measuring active knee extension range of motion (AROM) in a modified slump test position within trials on a single day and across days. Ten male and ten female asymptomatic subjects, ages 20-49 (mean age 30.1, SD 6.4) participated in the study. Knee extension AROM in a modified slump position with the cervical spine in a flexed position and then in an extended position was measured via three trials on two separate days. Across three trials, knee extension AROM increased significantly with a mean magnitude of 2 degrees within days for both cervical spine positions (P>0.05). The findings showed that there was no statistically significant difference in knee extension AROM measurements across days (P>0.05). The intraclass correlation coefficients for the mean of the three trials across days were 0.96 (lower limit 95% CI: 0.90) with the cervical spine flexed and 0.93 (lower limit 95% CI: 0.83) with cervical extension. Measurement error was calculated by way of the typical error and 95% limits of agreement, and visually represented in Bland and Altman plots. The typical error for the cervical flexed and extended positions averaged across trials was 2.6 degrees and 3.3 degrees , respectively. The limits of agreement were narrow, and the Bland and Altman plots also showed minimal bias in the joint angles across days with a random distribution of errors across the range of measured angles. This study demonstrated that knee extension AROM could be reliably measured across days in subjects without pathology and that the measurement error was acceptable. Implications of variability over multiple trials are discussed. The modified set-up for the test using the Kincom dynamometer and elevated thigh position may be useful to clinical researchers in determining the mechanosensitivity of the nervous system.

Reliability and Measurement Error of Active Knee Extension Range of Motion in a Modified Slump Test Position: A Pilot Study

PubMed Central

Tucker, Neil; Reid, Duncan; McNair, Peter

2007-01-01

The slump test is a tool to assess the mechanosensitivity of the neuromeningeal structures within the vertebral canal. While some studies have investigated the reliability of aspects of this test within the same day, few have assessed the reliability across days. Therefore, the purpose of this pilot study was to investigate reliability when measuring active knee extension range of motion (AROM) in a modified slump test position within trials on a single day and across days. Ten male and ten female asymptomatic subjects, ages 20–49 (mean age 30.1, SD 6.4) participated in the study. Knee extension AROM in a modified slump position with the cervical spine in a flexed position and then in an extended position was measured via three trials on two separate days. Across three trials, knee extension AROM increased significantly with a mean magnitude of 2° within days for both cervical spine positions (P>0.05). The findings showed that there was no statistically significant difference in knee extension AROM measurements across days (P>0.05). The intraclass correlation coefficients for the mean of the three trials across days were 0.96 (lower limit 95% CI: 0.90) with the cervical spine flexed and 0.93 (lower limit 95% CI: 0.83) with cervical extension. Measurement error was calculated by way of the typical error and 95% limits of agreement, and visually represented in Bland and Altman plots. The typical error for the cervical flexed and extended positions averaged across trials was 2.6° and 3.3°, respectively. The limits of agreement were narrow, and the Bland and Altman plots also showed minimal bias in the joint angles across days with a random distribution of errors across the range of measured angles. This study demonstrated that knee extension AROM could be reliably measured across days in subjects without pathology and that the measurement error was acceptable. Implications of variability over multiple trials are discussed. The modified set-up for the test using the Kincom dynamometer and elevated thigh position may be useful to clinical researchers in determining the mechanosensitivity of the nervous system. PMID:19066666

A preliminary taxonomy of medical errors in family practice.

PubMed

Dovey, S M; Meyers, D S; Phillips, R L; Green, L A; Fryer, G E; Galliher, J M; Kappus, J; Grob, P

2002-09-01

To develop a preliminary taxonomy of primary care medical errors. Qualitative analysis to identify categories of error reported during a randomized controlled trial of computer and paper reporting methods. The National Network for Family Practice and Primary Care Research. Family physicians. Medical error category, context, and consequence. Forty two physicians made 344 reports: 284 (82.6%) arose from healthcare systems dysfunction; 46 (13.4%) were errors due to gaps in knowledge or skills; and 14 (4.1%) were reports of adverse events, not errors. The main subcategories were: administrative failure (102; 30.9% of errors), investigation failures (82; 24.8%), treatment delivery lapses (76; 23.0%), miscommunication (19; 5.8%), payment systems problems (4; 1.2%), error in the execution of a clinical task (19; 5.8%), wrong treatment decision (14; 4.2%), and wrong diagnosis (13; 3.9%). Most reports were of errors that were recognized and occurred in reporters' practices. Affected patients ranged in age from 8 months to 100 years, were of both sexes, and represented all major US ethnic groups. Almost half the reports were of events which had adverse consequences. Ten errors resulted in patients being admitted to hospital and one patient died. This medical error taxonomy, developed from self-reports of errors observed by family physicians during their routine clinical practice, emphasizes problems in healthcare processes and acknowledges medical errors arising from shortfalls in clinical knowledge and skills. Patient safety strategies with most effect in primary care settings need to be broader than the current focus on medication errors.

Use of machine learning methods to reduce predictive error of groundwater models.

PubMed

Xu, Tianfang; Valocchi, Albert J; Choi, Jaesik; Amir, Eyal

2014-01-01

Quantitative analyses of groundwater flow and transport typically rely on a physically-based model, which is inherently subject to error. Errors in model structure, parameter and data lead to both random and systematic error even in the output of a calibrated model. We develop complementary data-driven models (DDMs) to reduce the predictive error of physically-based groundwater models. Two machine learning techniques, the instance-based weighting and support vector regression, are used to build the DDMs. This approach is illustrated using two real-world case studies of the Republican River Compact Administration model and the Spokane Valley-Rathdrum Prairie model. The two groundwater models have different hydrogeologic settings, parameterization, and calibration methods. In the first case study, cluster analysis is introduced for data preprocessing to make the DDMs more robust and computationally efficient. The DDMs reduce the root-mean-square error (RMSE) of the temporal, spatial, and spatiotemporal prediction of piezometric head of the groundwater model by 82%, 60%, and 48%, respectively. In the second case study, the DDMs reduce the RMSE of the temporal prediction of piezometric head of the groundwater model by 77%. It is further demonstrated that the effectiveness of the DDMs depends on the existence and extent of the structure in the error of the physically-based model. © 2013, National GroundWater Association.

Optimising in situ gamma measurements to identify the presence of radioactive particles in land areas.

PubMed

Rostron, Peter D; Heathcote, John A; Ramsey, Michael H

2014-12-01

High-coverage in situ surveys with gamma detectors are the best means of identifying small hotspots of activity, such as radioactive particles, in land areas. Scanning surveys can produce rapid results, but the probabilities of obtaining false positive or false negative errors are often unknown, and they may not satisfy other criteria such as estimation of mass activity concentrations. An alternative is to use portable gamma-detectors that are set up at a series of locations in a systematic sampling pattern, where any positive measurements are subsequently followed up in order to determine the exact location, extent and nature of the target source. The preliminary survey is typically designed using settings of detector height, measurement spacing and counting time that are based on convenience, rather than using settings that have been calculated to meet requirements. This paper introduces the basis of a repeatable method of setting these parameters at the outset of a survey, for pre-defined probabilities of false positive and false negative errors in locating spatially small radioactive particles in land areas. It is shown that an un-collimated detector is more effective than a collimated detector that might typically be used in the field. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Best (but oft-forgotten) practices: designing, analyzing, and reporting cluster randomized controlled trials.

PubMed

Brown, Andrew W; Li, Peng; Bohan Brown, Michelle M; Kaiser, Kathryn A; Keith, Scott W; Oakes, J Michael; Allison, David B

2015-08-01

Cluster randomized controlled trials (cRCTs; also known as group randomized trials and community-randomized trials) are multilevel experiments in which units that are randomly assigned to experimental conditions are sets of grouped individuals, whereas outcomes are recorded at the individual level. In human cRCTs, clusters that are randomly assigned are typically families, classrooms, schools, worksites, or counties. With growing interest in community-based, public health, and policy interventions to reduce obesity or improve nutrition, the use of cRCTs has increased. Errors in the design, analysis, and interpretation of cRCTs are unfortunately all too common. This situation seems to stem in part from investigator confusion about how the unit of randomization affects causal inferences and the statistical procedures required for the valid estimation and testing of effects. In this article, we provide a brief introduction and overview of the importance of cRCTs and highlight and explain important considerations for the design, analysis, and reporting of cRCTs by using published examples. © 2015 American Society for Nutrition.

Demonstrating the robustness of population surveillance data: implications of error rates on demographic and mortality estimates.

PubMed

Fottrell, Edward; Byass, Peter; Berhane, Yemane

2008-03-25

As in any measurement process, a certain amount of error may be expected in routine population surveillance operations such as those in demographic surveillance sites (DSSs). Vital events are likely to be missed and errors made no matter what method of data capture is used or what quality control procedures are in place. The extent to which random errors in large, longitudinal datasets affect overall health and demographic profiles has important implications for the role of DSSs as platforms for public health research and clinical trials. Such knowledge is also of particular importance if the outputs of DSSs are to be extrapolated and aggregated with realistic margins of error and validity. This study uses the first 10-year dataset from the Butajira Rural Health Project (BRHP) DSS, Ethiopia, covering approximately 336,000 person-years of data. Simple programmes were written to introduce random errors and omissions into new versions of the definitive 10-year Butajira dataset. Key parameters of sex, age, death, literacy and roof material (an indicator of poverty) were selected for the introduction of errors based on their obvious importance in demographic and health surveillance and their established significant associations with mortality. Defining the original 10-year dataset as the 'gold standard' for the purposes of this investigation, population, age and sex compositions and Poisson regression models of mortality rate ratios were compared between each of the intentionally erroneous datasets and the original 'gold standard' 10-year data. The composition of the Butajira population was well represented despite introducing random errors, and differences between population pyramids based on the derived datasets were subtle. Regression analyses of well-established mortality risk factors were largely unaffected even by relatively high levels of random errors in the data. The low sensitivity of parameter estimates and regression analyses to significant amounts of randomly introduced errors indicates a high level of robustness of the dataset. This apparent inertia of population parameter estimates to simulated errors is largely due to the size of the dataset. Tolerable margins of random error in DSS data may exceed 20%. While this is not an argument in favour of poor quality data, reducing the time and valuable resources spent on detecting and correcting random errors in routine DSS operations may be justifiable as the returns from such procedures diminish with increasing overall accuracy. The money and effort currently spent on endlessly correcting DSS datasets would perhaps be better spent on increasing the surveillance population size and geographic spread of DSSs and analysing and disseminating research findings.

Multivariate Statistics Applied to Seismic Phase Picking

NASA Astrophysics Data System (ADS)

Velasco, A. A.; Zeiler, C. P.; Anderson, D.; Pingitore, N. E.

2008-12-01

The initial effort of the Seismogram Picking Error from Analyst Review (SPEAR) project has been to establish a common set of seismograms to be picked by the seismological community. Currently we have 13 analysts from 4 institutions that have provided picks on the set of 26 seismograms. In comparing the picks thus far, we have identified consistent biases between picks from different institutions; effects of the experience of analysts; and the impact of signal-to-noise on picks. The institutional bias in picks brings up the important concern that picks will not be the same between different catalogs. This difference means less precision and accuracy when combing picks from multiple institutions. We also note that depending on the experience level of the analyst making picks for a catalog the error could fluctuate dramatically. However, the experience level is based off of number of years in picking seismograms and this may not be an appropriate criterion for determining an analyst's precision. The common data set of seismograms provides a means to test an analyst's level of precision and biases. The analyst is also limited by the quality of the signal and we show that the signal-to-noise ratio and pick error are correlated to the location, size and distance of the event. This makes the standard estimate of picking error based on SNR more complex because additional constraints are needed to accurately constrain the measurement error. We propose to extend the current measurement of error by adding the additional constraints of institutional bias and event characteristics to the standard SNR measurement. We use multivariate statistics to model the data and provide constraints to accurately assess earthquake location and measurement errors.

ELLIPTICAL WEIGHTED HOLICs FOR WEAK LENSING SHEAR MEASUREMENT. III. THE EFFECT OF RANDOM COUNT NOISE ON IMAGE MOMENTS IN WEAK LENSING ANALYSIS

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

Okura, Yuki; Futamase, Toshifumi, E-mail: yuki.okura@nao.ac.jp, E-mail: tof@astr.tohoku.ac.jp

This is the third paper on the improvement of systematic errors in weak lensing analysis using an elliptical weight function, referred to as E-HOLICs. In previous papers, we succeeded in avoiding errors that depend on the ellipticity of the background image. In this paper, we investigate the systematic error that depends on the signal-to-noise ratio of the background image. We find that the origin of this error is the random count noise that comes from the Poisson noise of sky counts. The random count noise makes additional moments and centroid shift error, and those first-order effects are canceled in averaging,more » but the second-order effects are not canceled. We derive the formulae that correct this systematic error due to the random count noise in measuring the moments and ellipticity of the background image. The correction formulae obtained are expressed as combinations of complex moments of the image, and thus can correct the systematic errors caused by each object. We test their validity using a simulated image and find that the systematic error becomes less than 1% in the measured ellipticity for objects with an IMCAT significance threshold of {nu} {approx} 11.7.« less

Ensemble Eclipse: A Process for Prefab Development Environment for the Ensemble Project

NASA Technical Reports Server (NTRS)

Wallick, Michael N.; Mittman, David S.; Shams, Khawaja, S.; Bachmann, Andrew G.; Ludowise, Melissa

2013-01-01

This software simplifies the process of having to set up an Eclipse IDE programming environment for the members of the cross-NASA center project, Ensemble. It achieves this by assembling all the necessary add-ons and custom tools/preferences. This software is unique in that it allows developers in the Ensemble Project (approximately 20 to 40 at any time) across multiple NASA centers to set up a development environment almost instantly and work on Ensemble software. The software automatically has the source code repositories and other vital information and settings included. The Eclipse IDE is an open-source development framework. The NASA (Ensemble-specific) version of the software includes Ensemble-specific plug-ins as well as settings for the Ensemble project. This software saves developers the time and hassle of setting up a programming environment, making sure that everything is set up in the correct manner for Ensemble development. Existing software (i.e., standard Eclipse) requires an intensive setup process that is both time-consuming and error prone. This software is built once by a single user and tested, allowing other developers to simply download and use the software

Evaluation of genomic high-throughput sequencing data generated on Illumina HiSeq and Genome Analyzer systems

PubMed Central

2011-01-01

Background The generation and analysis of high-throughput sequencing data are becoming a major component of many studies in molecular biology and medical research. Illumina's Genome Analyzer (GA) and HiSeq instruments are currently the most widely used sequencing devices. Here, we comprehensively evaluate properties of genomic HiSeq and GAIIx data derived from two plant genomes and one virus, with read lengths of 95 to 150 bases. Results We provide quantifications and evidence for GC bias, error rates, error sequence context, effects of quality filtering, and the reliability of quality values. By combining different filtering criteria we reduced error rates 7-fold at the expense of discarding 12.5% of alignable bases. While overall error rates are low in HiSeq data we observed regions of accumulated wrong base calls. Only 3% of all error positions accounted for 24.7% of all substitution errors. Analyzing the forward and reverse strands separately revealed error rates of up to 18.7%. Insertions and deletions occurred at very low rates on average but increased to up to 2% in homopolymers. A positive correlation between read coverage and GC content was found depending on the GC content range. Conclusions The errors and biases we report have implications for the use and the interpretation of Illumina sequencing data. GAIIx and HiSeq data sets show slightly different error profiles. Quality filtering is essential to minimize downstream analysis artifacts. Supporting previous recommendations, the strand-specificity provides a criterion to distinguish sequencing errors from low abundance polymorphisms. PMID:22067484

Confidence set inference with a prior quadratic bound

NASA Technical Reports Server (NTRS)

Backus, George E.

1988-01-01

In the uniqueness part of a geophysical inverse problem, the observer wants to predict all likely values of P unknown numerical properties z = (z sub 1,...,z sub p) of the earth from measurement of D other numerical properties y(0)=(y sub 1(0),...,y sub D(0)) knowledge of the statistical distribution of the random errors in y(0). The data space Y containing y(0) is D-dimensional, so when the model space X is infinite-dimensional the linear uniqueness problem usually is insoluble without prior information about the correct earth model x. If that information is a quadratic bound on x (e.g., energy or dissipation rate), Bayesian inference (BI) and stochastic inversion (SI) inject spurious structure into x, implied by neither the data nor the quadratic bound. Confidence set inference (CSI) provides an alternative inversion technique free of this objection. CSI is illustrated in the problem of estimating the geomagnetic field B at the core-mantle boundary (CMB) from components of B measured on or above the earth's surface. Neither the heat flow nor the energy bound is strong enough to permit estimation of B(r) at single points on the CMB, but the heat flow bound permits estimation of uniform averages of B(r) over discs on the CMB, and both bounds permit weighted disc-averages with continous weighting kernels. Both bounds also permit estimation of low-degree Gauss coefficients at the CMB. The heat flow bound resolves them up to degree 8 if the crustal field at satellite altitudes must be treated as a systematic error, but can resolve to degree 11 under the most favorable statistical treatment of the crust. These two limits produce circles of confusion on the CMB with diameters of 25 deg and 19 deg respectively.

Medical errors in primary care clinics – a cross sectional study

PubMed Central

2012-01-01

Background Patient safety is vital in patient care. There is a lack of studies on medical errors in primary care settings. The aim of the study is to determine the extent of diagnostic inaccuracies and management errors in public funded primary care clinics. Methods This was a cross-sectional study conducted in twelve public funded primary care clinics in Malaysia. A total of 1753 medical records were randomly selected in 12 primary care clinics in 2007 and were reviewed by trained family physicians for diagnostic, management and documentation errors, potential errors causing serious harm and likelihood of preventability of such errors. Results The majority of patient encounters (81%) were with medical assistants. Diagnostic errors were present in 3.6% (95% CI: 2.2, 5.0) of medical records and management errors in 53.2% (95% CI: 46.3, 60.2). For management errors, medication errors were present in 41.1% (95% CI: 35.8, 46.4) of records, investigation errors in 21.7% (95% CI: 16.5, 26.8) and decision making errors in 14.5% (95% CI: 10.8, 18.2). A total of 39.9% (95% CI: 33.1, 46.7) of these errors had the potential to cause serious harm. Problems of documentation including illegible handwriting were found in 98.0% (95% CI: 97.0, 99.1) of records. Nearly all errors (93.5%) detected were considered preventable. Conclusions The occurrence of medical errors was high in primary care clinics particularly with documentation and medication errors. Nearly all were preventable. Remedial intervention addressing completeness of documentation and prescriptions are likely to yield reduction of errors. PMID:23267547

Comparison of different tree sap flow up-scaling procedures using Monte-Carlo simulations

NASA Astrophysics Data System (ADS)

Tatarinov, Fyodor; Preisler, Yakir; Roahtyn, Shani; Yakir, Dan

2015-04-01

An important task in determining forest ecosystem water balance is the estimation of stand transpiration, allowing separating evapotranspiration into transpiration and soil evaporation. This can be based on up-scaling measurements of sap flow in representative trees (SF), which can be done by different mathematical algorithms. The aim of the present study was to evaluate the error associated with different up-scaling algorithms under different conditions. Other types of errors (such as, measurement error, within tree SF variability, choice of sample plot etc.) were not considered here. A set of simulation experiments using Monte-Carlo technique was carried out and three up-scaling procedures were tested. (1) Multiplying mean stand sap flux density based on unit sapwood cross-section area (SFD) by total sapwood area (Klein et al, 2014); (2) deriving of linear dependence of tree sap flow on tree DBH and calculating SFstand using predicted SF by DBH classes and stand DBH distribution (Cermak et al., 2004); (3) same as method 2 but using non-linear dependency. Simulations were performed under different SFD(DBH) slope (bs, positive, negative, zero); different DBH and SFD standard deviations (Δd and Δs, respectively) and DBH class size. It was assumed that all trees in a unit area are measured and the total SF of all trees in the experimental plot was taken as the reference SFstand value. Under negative bs all models tend to overestimate SFstand and the error increases exponentially with decreasing bs. Under bs >0 all models tend to underestimate SFstand, but the error is much smaller than for bs

Building on crossvalidation for increasing the quality of geostatistical modeling

USGS Publications Warehouse

Olea, R.A.

2012-01-01

The random function is a mathematical model commonly used in the assessment of uncertainty associated with a spatially correlated attribute that has been partially sampled. There are multiple algorithms for modeling such random functions, all sharing the requirement of specifying various parameters that have critical influence on the results. The importance of finding ways to compare the methods and setting parameters to obtain results that better model uncertainty has increased as these algorithms have grown in number and complexity. Crossvalidation has been used in spatial statistics, mostly in kriging, for the analysis of mean square errors. An appeal of this approach is its ability to work with the same empirical sample available for running the algorithms. This paper goes beyond checking estimates by formulating a function sensitive to conditional bias. Under ideal conditions, such function turns into a straight line, which can be used as a reference for preparing measures of performance. Applied to kriging, deviations from the ideal line provide sensitivity to the semivariogram lacking in crossvalidation of kriging errors and are more sensitive to conditional bias than analyses of errors. In terms of stochastic simulation, in addition to finding better parameters, the deviations allow comparison of the realizations resulting from the applications of different methods. Examples show improvements of about 30% in the deviations and approximately 10% in the square root of mean square errors between reasonable starting modelling and the solutions according to the new criteria. ?? 2011 US Government.

Identifying sensitive areas of adaptive observations for prediction of the Kuroshio large meander using a shallow-water model

NASA Astrophysics Data System (ADS)

Zou, Guang'an; Wang, Qiang; Mu, Mu

2016-09-01

Sensitive areas for prediction of the Kuroshio large meander using a 1.5-layer, shallow-water ocean model were investigated using the conditional nonlinear optimal perturbation (CNOP) and first singular vector (FSV) methods. A series of sensitivity experiments were designed to test the sensitivity of sensitive areas within the numerical model. The following results were obtained: (1) the eff ect of initial CNOP and FSV patterns in their sensitive areas is greater than that of the same patterns in randomly selected areas, with the eff ect of the initial CNOP patterns in CNOP sensitive areas being the greatest; (2) both CNOP- and FSV-type initial errors grow more quickly than random errors; (3) the eff ect of random errors superimposed on the sensitive areas is greater than that of random errors introduced into randomly selected areas, and initial errors in the CNOP sensitive areas have greater eff ects on final forecasts. These results reveal that the sensitive areas determined using the CNOP are more sensitive than those of FSV and other randomly selected areas. In addition, ideal hindcasting experiments were conducted to examine the validity of the sensitive areas. The results indicate that reduction (or elimination) of CNOP-type errors in CNOP sensitive areas at the initial time has a greater forecast benefit than the reduction (or elimination) of FSV-type errors in FSV sensitive areas. These results suggest that the CNOP method is suitable for determining sensitive areas in the prediction of the Kuroshio large-meander path.

Portable and Error-Free DNA-Based Data Storage.

PubMed

Yazdi, S M Hossein Tabatabaei; Gabrys, Ryan; Milenkovic, Olgica

2017-07-10

DNA-based data storage is an emerging nonvolatile memory technology of potentially unprecedented density, durability, and replication efficiency. The basic system implementation steps include synthesizing DNA strings that contain user information and subsequently retrieving them via high-throughput sequencing technologies. Existing architectures enable reading and writing but do not offer random-access and error-free data recovery from low-cost, portable devices, which is crucial for making the storage technology competitive with classical recorders. Here we show for the first time that a portable, random-access platform may be implemented in practice using nanopore sequencers. The novelty of our approach is to design an integrated processing pipeline that encodes data to avoid costly synthesis and sequencing errors, enables random access through addressing, and leverages efficient portable sequencing via new iterative alignment and deletion error-correcting codes. Our work represents the only known random access DNA-based data storage system that uses error-prone nanopore sequencers, while still producing error-free readouts with the highest reported information rate/density. As such, it represents a crucial step towards practical employment of DNA molecules as storage media.

Simulation of the Effects of Random Measurement Errors

ERIC Educational Resources Information Center

Kinsella, I. A.; Hannaidh, P. B. O.

1978-01-01

Describes a simulation method for measurement of errors that requires calculators and tables of random digits. Each student simulates the random behaviour of the component variables in the function and by combining the results of all students, the outline of the sampling distribution of the function can be obtained. (GA)

Superconducting quantum circuits at the surface code threshold for fault tolerance.

PubMed

Barends, R; Kelly, J; Megrant, A; Veitia, A; Sank, D; Jeffrey, E; White, T C; Mutus, J; Fowler, A G; Campbell, B; Chen, Y; Chen, Z; Chiaro, B; Dunsworth, A; Neill, C; O'Malley, P; Roushan, P; Vainsencher, A; Wenner, J; Korotkov, A N; Cleland, A N; Martinis, John M

2014-04-24

A quantum computer can solve hard problems, such as prime factoring, database searching and quantum simulation, at the cost of needing to protect fragile quantum states from error. Quantum error correction provides this protection by distributing a logical state among many physical quantum bits (qubits) by means of quantum entanglement. Superconductivity is a useful phenomenon in this regard, because it allows the construction of large quantum circuits and is compatible with microfabrication. For superconducting qubits, the surface code approach to quantum computing is a natural choice for error correction, because it uses only nearest-neighbour coupling and rapidly cycled entangling gates. The gate fidelity requirements are modest: the per-step fidelity threshold is only about 99 per cent. Here we demonstrate a universal set of logic gates in a superconducting multi-qubit processor, achieving an average single-qubit gate fidelity of 99.92 per cent and a two-qubit gate fidelity of up to 99.4 per cent. This places Josephson quantum computing at the fault-tolerance threshold for surface code error correction. Our quantum processor is a first step towards the surface code, using five qubits arranged in a linear array with nearest-neighbour coupling. As a further demonstration, we construct a five-qubit Greenberger-Horne-Zeilinger state using the complete circuit and full set of gates. The results demonstrate that Josephson quantum computing is a high-fidelity technology, with a clear path to scaling up to large-scale, fault-tolerant quantum circuits.

On the statistical assessment of classifiers using DNA microarray data

PubMed Central

Ancona, N; Maglietta, R; Piepoli, A; D'Addabbo, A; Cotugno, R; Savino, M; Liuni, S; Carella, M; Pesole, G; Perri, F

2006-01-01

Background In this paper we present a method for the statistical assessment of cancer predictors which make use of gene expression profiles. The methodology is applied to a new data set of microarray gene expression data collected in Casa Sollievo della Sofferenza Hospital, Foggia – Italy. The data set is made up of normal (22) and tumor (25) specimens extracted from 25 patients affected by colon cancer. We propose to give answers to some questions which are relevant for the automatic diagnosis of cancer such as: Is the size of the available data set sufficient to build accurate classifiers? What is the statistical significance of the associated error rates? In what ways can accuracy be considered dependant on the adopted classification scheme? How many genes are correlated with the pathology and how many are sufficient for an accurate colon cancer classification? The method we propose answers these questions whilst avoiding the potential pitfalls hidden in the analysis and interpretation of microarray data. Results We estimate the generalization error, evaluated through the Leave-K-Out Cross Validation error, for three different classification schemes by varying the number of training examples and the number of the genes used. The statistical significance of the error rate is measured by using a permutation test. We provide a statistical analysis in terms of the frequencies of the genes involved in the classification. Using the whole set of genes, we found that the Weighted Voting Algorithm (WVA) classifier learns the distinction between normal and tumor specimens with 25 training examples, providing e = 21% (p = 0.045) as an error rate. This remains constant even when the number of examples increases. Moreover, Regularized Least Squares (RLS) and Support Vector Machines (SVM) classifiers can learn with only 15 training examples, with an error rate of e = 19% (p = 0.035) and e = 18% (p = 0.037) respectively. Moreover, the error rate decreases as the training set size increases, reaching its best performances with 35 training examples. In this case, RLS and SVM have error rates of e = 14% (p = 0.027) and e = 11% (p = 0.019). Concerning the number of genes, we found about 6000 genes (p < 0.05) correlated with the pathology, resulting from the signal-to-noise statistic. Moreover the performances of RLS and SVM classifiers do not change when 74% of genes is used. They progressively reduce up to e = 16% (p < 0.05) when only 2 genes are employed. The biological relevance of a set of genes determined by our statistical analysis and the major roles they play in colorectal tumorigenesis is discussed. Conclusions The method proposed provides statistically significant answers to precise questions relevant for the diagnosis and prognosis of cancer. We found that, with as few as 15 examples, it is possible to train statistically significant classifiers for colon cancer diagnosis. As for the definition of the number of genes sufficient for a reliable classification of colon cancer, our results suggest that it depends on the accuracy required. PMID:16919171

Time Orientation and 10 Years Risk of Dementia in Elderly Adults: The Three-City Study.

PubMed

Dumurgier, Julien; Dartigues, Jean-François; Gabelle, Audrey; Paquet, Claire; Prevot, Magali; Hugon, Jacques; Tzourio, Christophe

2016-07-01

Time disorientation is commonly observed in dementia, however very little is known about the pathological significance of minor time errors in community-dwelling population. Our objective was to investigate the relationship between time orientation and risk of dementia in a population of older adults. Analyses relies on 8611 dementia-free subjects from the Three-City Study, France. Participants were followed up for 10 years for incident dementia. Time orientation was assessed by asking for the date, the day of the week, the month, the season and the year. At baseline, 905 subjects made at least one error in time orientation. During 57,073 person-years of follow-up, 827 participants developed dementia. After controlling for age, gender and education level, subjects with one error in time had a greater risk of dementia (hazard ratio [HR] 1.44 [1.18-1.77]), while those with at least 2 errors had a more than three-fold increased risk (HR 3.10 [1.98-4.83]). This association was particularly marked for the diagnosis of probable Alzheimer's disease. Time disorientation was associated with an increased risk of dementia in a large population of cognitively normal older people followed during up to 10 years and should not be underestimated in clinical setting.

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

Comparison of updates to the Molly cow model to predict methane production from dairy cows fed pasture.

PubMed

Gregorini, P; Beukes, P C; Hanigan, M D; Waghorn, G; Muetzel, S; McNamara, J P

2013-08-01

Molly is a deterministic, mechanistic, dynamic model representing the digestion, metabolism, and production of a dairy cow. This study compared the predictions of enteric methane production from the original version of Molly (MollyOrigin) and 2 new versions of Molly. Updated versions included new ruminal fiber digestive parameters and animal hormonal parameters (Molly84) and a revised version of digestive and ruminal parameters (Molly85), using 3 different ruminal volatile fatty acid (VFA) stoichiometry constructs to describe the VFA pattern and methane (CH4) production (g of CH4/d). The VFA stoichiometry constructs were the original forage and mixed-diet VFA constructs and a new VFA stoichiometry based on a more recent and larger set of data that includes lactate and valerate production, amylolytic and cellulolytic bacteria, as well as protozoal pools. The models' outputs were challenged using data from 16 dairy cattle 26 mo old [standard error of the mean (SEM)=1.7], 82 (SEM=8.7) d in milk, producing 17 (SEM=0.2) kg of milk/d, and fed fresh-cut ryegrass [dry matter intake=12.3 (SEM=0.3) kg of DM/d] in respiration chambers. Mean observed CH4 production was 266±5.6 SEM (g/d). Mean predicted values for CH4 production were 287 and 258 g/d for MollyOrigin without and with the new VFA construct. Model Molly84 predicted 295 and 288 g of CH4/d with and without the new VFA settings. Model Molly85 predicted the same CH4 production (276 g/d) with or without the new VFA construct. The incorporation of the new VFA construct did not consistently reduce the low prediction error across the versions of Molly evaluated in the present study. The improvements in the Molly versions from MollyOrigin to Molly84 to Molly85 resulted in a decrease in mean square prediction error from 8.6 to 8.3 to 4.3% using the forage diet setting. The majority of the mean square prediction error was apportioned to random bias (e.g., 43, 65, and 70% in MollyOrigin, Molly84, and Molly85, respectively, on the forage setting, showing that with the updated versions a greater proportion of error was random). The slope bias was less than 2% in all cases. We concluded that, of the versions of Molly used for pastoral systems, Molly85 has the capability to predict CH4 production from grass-fed dairy cows with the highest accuracy. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Pitfalls of insulin pump clocks: technical glitches that may potentially affect medical care in patients with diabetes.

PubMed

Aldasouqi, Saleh A; Reed, Amy J

2014-11-01

The objective was to raise awareness about the importance of ensuring that insulin pumps internal clocks are set up correctly at all times. This is a very important safety issue because all commercially available insulin pumps are not GPS-enabled (though this is controversial), nor equipped with automatically adjusting internal clocks. Special attention is paid to how basal and bolus dose errors can be introduced by daylight savings time changes, travel across time zones, and am-pm clock errors. Correct setting of insulin pump internal clock is crucial for appropriate insulin delivery. A comprehensive literature review is provided, as are illustrative cases. Incorrect setting can potentially result in incorrect insulin delivery, with potential harmful consequences, if too much or too little insulin is delivered. Daylight saving time changes may not significantly affect basal insulin delivery, given the triviality of the time difference. However, bolus insulin doses can be dramatically affected. Such problems may occur when pump wearers have large variations in their insulin to carb ratio, especially if they forget to change their pump clock in the spring. More worrisome than daylight saving time change is the am-pm clock setting. If this setting is set up incorrectly, both basal rates and bolus doses will be affected. Appropriate insulin delivery through insulin pumps requires correct correlation between dose settings and internal clock time settings. Because insulin pumps are not GPS-enabled or automatically time-adjusting, extra caution should be practiced by patients to ensure correct time settings at all times. Clinicians and diabetes educators should verify the date/time of insulin pumps during patients' visits, and should remind their patients to always verify these settings. © 2014 Diabetes Technology Society.

Pitfalls of Insulin Pump Clocks

PubMed Central

Reed, Amy J.

2014-01-01

The objective was to raise awareness about the importance of ensuring that insulin pumps internal clocks are set up correctly at all times. This is a very important safety issue because all commercially available insulin pumps are not GPS-enabled (though this is controversial), nor equipped with automatically adjusting internal clocks. Special attention is paid to how basal and bolus dose errors can be introduced by daylight savings time changes, travel across time zones, and am-pm clock errors. Correct setting of insulin pump internal clock is crucial for appropriate insulin delivery. A comprehensive literature review is provided, as are illustrative cases. Incorrect setting can potentially result in incorrect insulin delivery, with potential harmful consequences, if too much or too little insulin is delivered. Daylight saving time changes may not significantly affect basal insulin delivery, given the triviality of the time difference. However, bolus insulin doses can be dramatically affected. Such problems may occur when pump wearers have large variations in their insulin to carb ratio, especially if they forget to change their pump clock in the spring. More worrisome than daylight saving time change is the am-pm clock setting. If this setting is set up incorrectly, both basal rates and bolus doses will be affected. Appropriate insulin delivery through insulin pumps requires correct correlation between dose settings and internal clock time settings. Because insulin pumps are not GPS-enabled or automatically time-adjusting, extra caution should be practiced by patients to ensure correct time settings at all times. Clinicians and diabetes educators should verify the date/time of insulin pumps during patients’ visits, and should remind their patients to always verify these settings. PMID:25355713

Analysis of Vibratory Excitation of Gear Systems as a Contributor to Aircraft Interior Noise. [helicopter cabin noise

NASA Technical Reports Server (NTRS)

Mark, W. D.

1979-01-01

Application of the transfer function approach to predict the resulting interior noise contribution requires gearbox vibration sources and paths to be characterized in the frequency domain. Tooth-face deviations from perfect involute surfaces were represented in terms of Legendre polynomials which may be directly interpreted in terms of tooth-spacing errors, mean and random deviations associated with involute slope and fullness, lead mismatch and crowning, and analogous higher-order components. The contributions of these components to the spectrum of the static transmission error is discussed and illustrated using a set of measurements made on a pair of helicopter spur gears. The general methodology presented is applicable to both spur and helical gears.

Why phase errors affect the electron function more than amplitude errors.

PubMed

Lattman, Eaton; DeRosier, David

2008-03-01

If Fexp(ialpha) are the set of structure factors for a structure f, the amplitudes can be converted to those of an uncorrelated structure g (amplitude swapping) by multiplying each F by the positive number G/F. Correspondingly, the image f is convoluted with k, the Fourier transform of G/F; k has a large peak at the origin, so that f * k approximately f. For swapped phases, the image f is convoluted with l, the Fourier transform of exp(iDeltaalpha), where Deltaalpha, the phase difference between F and G, is a random variable; l does not have a large peak at the origin, so that f * l does not resemble f. The paper provides quantitative descriptions of these arguments.

AFRESh: an adaptive framework for compression of reads and assembled sequences with random access functionality.

PubMed

Paridaens, Tom; Van Wallendael, Glenn; De Neve, Wesley; Lambert, Peter

2017-05-15

The past decade has seen the introduction of new technologies that lowered the cost of genomic sequencing increasingly. We can even observe that the cost of sequencing is dropping significantly faster than the cost of storage and transmission. The latter motivates a need for continuous improvements in the area of genomic data compression, not only at the level of effectiveness (compression rate), but also at the level of functionality (e.g. random access), configurability (effectiveness versus complexity, coding tool set …) and versatility (support for both sequenced reads and assembled sequences). In that regard, we can point out that current approaches mostly do not support random access, requiring full files to be transmitted, and that current approaches are restricted to either read or sequence compression. We propose AFRESh, an adaptive framework for no-reference compression of genomic data with random access functionality, targeting the effective representation of the raw genomic symbol streams of both reads and assembled sequences. AFRESh makes use of a configurable set of prediction and encoding tools, extended by a Context-Adaptive Binary Arithmetic Coding scheme (CABAC), to compress raw genetic codes. To the best of our knowledge, our paper is the first to describe an effective implementation CABAC outside of its' original application. By applying CABAC, the compression effectiveness improves by up to 19% for assembled sequences and up to 62% for reads. By applying AFRESh to the genomic symbols of the MPEG genomic compression test set for reads, a compression gain is achieved of up to 51% compared to SCALCE, 42% compared to LFQC and 44% compared to ORCOM. When comparing to generic compression approaches, a compression gain is achieved of up to 41% compared to GNU Gzip and 22% compared to 7-Zip at the Ultra setting. Additionaly, when compressing assembled sequences of the Human Genome, a compression gain is achieved up to 34% compared to GNU Gzip and 16% compared to 7-Zip at the Ultra setting. A Windows executable version can be downloaded at https://github.com/tparidae/AFresh . tom.paridaens@ugent.be. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Logistic random effects regression models: a comparison of statistical packages for binary and ordinal outcomes.

PubMed

Li, Baoyue; Lingsma, Hester F; Steyerberg, Ewout W; Lesaffre, Emmanuel

2011-05-23

Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. We used individual patient data from 8509 patients in 231 centers with moderate and severe Traumatic Brain Injury (TBI) enrolled in eight Randomized Controlled Trials (RCTs) and three observational studies. We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS) as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. We then compared the implementations of frequentist and Bayesian methods to estimate the fixed and random effects. Frequentist approaches included R (lme4), Stata (GLLAMM), SAS (GLIMMIX and NLMIXED), MLwiN ([R]IGLS) and MIXOR, Bayesian approaches included WinBUGS, MLwiN (MCMC), R package MCMCglmm and SAS experimental procedure MCMC.Three data sets (the full data set and two sub-datasets) were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. For the ordinal outcome in the full data set also a proportional odds model with a random center effect was fitted. The packages gave similar parameter estimates for both the fixed and random effects and for the binary (and ordinal) models for the main study and when based on a relatively large number of level-1 (patient level) data compared to the number of level-2 (hospital level) data. However, when based on relatively sparse data set, i.e. when the numbers of level-1 and level-2 data units were about the same, the frequentist and Bayesian approaches showed somewhat different results. The software implementations differ considerably in flexibility, computation time, and usability. There are also differences in the availability of additional tools for model evaluation, such as diagnostic plots. The experimental SAS (version 9.2) procedure MCMC appeared to be inefficient. On relatively large data sets, the different software implementations of logistic random effects regression models produced similar results. Thus, for a large data set there seems to be no explicit preference (of course if there is no preference from a philosophical point of view) for either a frequentist or Bayesian approach (if based on vague priors). The choice for a particular implementation may largely depend on the desired flexibility, and the usability of the package. For small data sets the random effects variances are difficult to estimate. In the frequentist approaches the MLE of this variance was often estimated zero with a standard error that is either zero or could not be determined, while for Bayesian methods the estimates could depend on the chosen "non-informative" prior of the variance parameter. The starting value for the variance parameter may be also critical for the convergence of the Markov chain.

Exploring Situational Awareness in Diagnostic Errors in Primary Care

PubMed Central

Singh, Hardeep; Giardina, Traber Davis; Petersen, Laura A.; Smith, Michael; Wilson, Lindsey; Dismukes, Key; Bhagwath, Gayathri; Thomas, Eric J.

2013-01-01

Objective Diagnostic errors in primary care are harmful but poorly studied. To facilitate understanding of diagnostic errors in real-world primary care settings using electronic health records (EHRs), this study explored the use of the Situational Awareness (SA) framework from aviation human factors research. Methods A mixed-methods study was conducted involving reviews of EHR data followed by semi-structured interviews of selected providers from two institutions in the US. The study population included 380 consecutive patients with colorectal and lung cancers diagnosed between February 2008 and January 2009. Using a pre-tested data collection instrument, trained physicians identified diagnostic errors, defined as lack of timely action on one or more established indications for diagnostic work-up for lung and colorectal cancers. Twenty-six providers involved in cases with and without errors were interviewed. Interviews probed for providers' lack of SA and how this may have influenced the diagnostic process. Results Of 254 cases meeting inclusion criteria, errors were found in 30 (32.6%) of 92 lung cancer cases and 56 (33.5%) of 167 colorectal cancer cases. Analysis of interviews related to error cases revealed evidence of lack of one of four levels of SA applicable to primary care practice: information perception, information comprehension, forecasting future events, and choosing appropriate action based on the first three levels. In cases without error, the application of the SA framework provided insight into processes involved in attention management. Conclusions A framework of SA can help analyze and understand diagnostic errors in primary care settings that use EHRs. PMID:21890757

Development of multiple-eye PIV using mirror array

NASA Astrophysics Data System (ADS)

Maekawa, Akiyoshi; Sakakibara, Jun

2018-06-01

In order to reduce particle image velocimetry measurement error, we manufactured an ellipsoidal polyhedral mirror and placed it between a camera and flow target to capture n images of identical particles from n (=80 maximum) different directions. The 3D particle positions were determined from the ensemble average of n C2 intersecting points of a pair of line-of-sight back-projected points from a particle found in any combination of two images in the n images. The method was then applied to a rigid-body rotating flow and a turbulent pipe flow. In the former measurement, bias error and random error fell in a range of  ±0.02 pixels and 0.02–0.05 pixels, respectively; additionally, random error decreased in proportion to . In the latter measurement, in which the measured value was compared to direct numerical simulation, bias error was reduced and random error also decreased in proportion to .

Demonstration of Qubit Operations Below a Rigorous Fault Tolerance Threshold With Gate Set Tomography (Open Access, Publisher’s Version)

DTIC Science & Technology

2017-02-15

Maunz2 Quantum information processors promise fast algorithms for problems inaccessible to classical computers. But since qubits are noisy and error-prone...information processors have been demonstrated experimentally using superconducting circuits1–3, electrons in semiconductors4–6, trapped atoms and...qubit quantum information processor has been realized14, and single- qubit gates have demonstrated randomized benchmarking (RB) infidelities as low as 10

Extended observability of linear time-invariant systems under recurrent loss of output data

NASA Technical Reports Server (NTRS)

Luck, Rogelio; Ray, Asok; Halevi, Yoram

1989-01-01

Recurrent loss of sensor data in integrated control systems of an advanced aircraft may occur under different operating conditions that include detected frame errors and queue saturation in computer networks, and bad data suppression in signal processing. This paper presents an extension of the concept of observability based on a set of randomly selected nonconsecutive outputs in finite-dimensional, linear, time-invariant systems. Conditions for testing extended observability have been established.

A two dimensional interface element for coupling of independently modeled three dimensional finite element meshes and extensions to dynamic and non-linear regimes

NASA Technical Reports Server (NTRS)

Aminpour, Mohammad

1995-01-01

The work reported here pertains only to the first year of research for a three year proposal period. As a prelude to this two dimensional interface element, the one dimensional element was tested and errors were discovered in the code for built-up structures and curved interfaces. These errors were corrected and the benchmark Boeing composite crown panel was analyzed successfully. A study of various splines led to the conclusion that cubic B-splines best suit this interface element application. A least squares approach combined with cubic B-splines was constructed to make a smooth function from the noisy data obtained with random error in the coordinate data points of the Boeing crown panel analysis. Preliminary investigations for the formulation of discontinuous 2-D shell and 3-D solid elements were conducted.

The Performance of the Date-Randomization Test in Phylogenetic Analyses of Time-Structured Virus Data.

PubMed

Duchêne, Sebastián; Duchêne, David; Holmes, Edward C; Ho, Simon Y W

2015-07-01

Rates and timescales of viral evolution can be estimated using phylogenetic analyses of time-structured molecular sequences. This involves the use of molecular-clock methods, calibrated by the sampling times of the viral sequences. However, the spread of these sampling times is not always sufficient to allow the substitution rate to be estimated accurately. We conducted Bayesian phylogenetic analyses of simulated virus data to evaluate the performance of the date-randomization test, which is sometimes used to investigate whether time-structured data sets have temporal signal. An estimate of the substitution rate passes this test if its mean does not fall within the 95% credible intervals of rate estimates obtained using replicate data sets in which the sampling times have been randomized. We find that the test sometimes fails to detect rate estimates from data with no temporal signal. This error can be minimized by using a more conservative criterion, whereby the 95% credible interval of the estimate with correct sampling times should not overlap with those obtained with randomized sampling times. We also investigated the behavior of the test when the sampling times are not uniformly distributed throughout the tree, which sometimes occurs in empirical data sets. The test performs poorly in these circumstances, such that a modification to the randomization scheme is needed. Finally, we illustrate the behavior of the test in analyses of nucleotide sequences of cereal yellow dwarf virus. Our results validate the use of the date-randomization test and allow us to propose guidelines for interpretation of its results. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Estimating Root Mean Square Errors in Remotely Sensed Soil Moisture over Continental Scale Domains

NASA Technical Reports Server (NTRS)

Draper, Clara S.; Reichle, Rolf; de Jeu, Richard; Naeimi, Vahid; Parinussa, Robert; Wagner, Wolfgang

2013-01-01

Root Mean Square Errors (RMSE) in the soil moisture anomaly time series obtained from the Advanced Scatterometer (ASCAT) and the Advanced Microwave Scanning Radiometer (AMSR-E; using the Land Parameter Retrieval Model) are estimated over a continental scale domain centered on North America, using two methods: triple colocation (RMSETC ) and error propagation through the soil moisture retrieval models (RMSEEP ). In the absence of an established consensus for the climatology of soil moisture over large domains, presenting a RMSE in soil moisture units requires that it be specified relative to a selected reference data set. To avoid the complications that arise from the use of a reference, the RMSE is presented as a fraction of the time series standard deviation (fRMSE). For both sensors, the fRMSETC and fRMSEEP show similar spatial patterns of relatively highlow errors, and the mean fRMSE for each land cover class is consistent with expectations. Triple colocation is also shown to be surprisingly robust to representativity differences between the soil moisture data sets used, and it is believed to accurately estimate the fRMSE in the remotely sensed soil moisture anomaly time series. Comparing the ASCAT and AMSR-E fRMSETC shows that both data sets have very similar accuracy across a range of land cover classes, although the AMSR-E accuracy is more directly related to vegetation cover. In general, both data sets have good skill up to moderate vegetation conditions.

IMRT QA: Selecting gamma criteria based on error detection sensitivity

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

Steers, Jennifer M.; Fraass, Benedick A., E-mail: benedick.fraass@cshs.org

Purpose: The gamma comparison is widely used to evaluate the agreement between measurements and treatment planning system calculations in patient-specific intensity modulated radiation therapy (IMRT) quality assurance (QA). However, recent publications have raised concerns about the lack of sensitivity when employing commonly used gamma criteria. Understanding the actual sensitivity of a wide range of different gamma criteria may allow the definition of more meaningful gamma criteria and tolerance limits in IMRT QA. We present a method that allows the quantitative determination of gamma criteria sensitivity to induced errors which can be applied to any unique combination of device, delivery technique,more » and software utilized in a specific clinic. Methods: A total of 21 DMLC IMRT QA measurements (ArcCHECK®, Sun Nuclear) were compared to QA plan calculations with induced errors. Three scenarios were studied: MU errors, multi-leaf collimator (MLC) errors, and the sensitivity of the gamma comparison to changes in penumbra width. Gamma comparisons were performed between measurements and error-induced calculations using a wide range of gamma criteria, resulting in a total of over 20 000 gamma comparisons. Gamma passing rates for each error class and case were graphed against error magnitude to create error curves in order to represent the range of missed errors in routine IMRT QA using 36 different gamma criteria. Results: This study demonstrates that systematic errors and case-specific errors can be detected by the error curve analysis. Depending on the location of the error curve peak (e.g., not centered about zero), 3%/3 mm threshold = 10% at 90% pixels passing may miss errors as large as 15% MU errors and ±1 cm random MLC errors for some cases. As the dose threshold parameter was increased for a given %Diff/distance-to-agreement (DTA) setting, error sensitivity was increased by up to a factor of two for select cases. This increased sensitivity with increasing dose threshold was consistent across all studied combinations of %Diff/DTA. Criteria such as 2%/3 mm and 3%/2 mm with a 50% threshold at 90% pixels passing are shown to be more appropriately sensitive without being overly strict. However, a broadening of the penumbra by as much as 5 mm in the beam configuration was difficult to detect with commonly used criteria, as well as with the previously mentioned criteria utilizing a threshold of 50%. Conclusions: We have introduced the error curve method, an analysis technique which allows the quantitative determination of gamma criteria sensitivity to induced errors. The application of the error curve method using DMLC IMRT plans measured on the ArcCHECK® device demonstrated that large errors can potentially be missed in IMRT QA with commonly used gamma criteria (e.g., 3%/3 mm, threshold = 10%, 90% pixels passing). Additionally, increasing the dose threshold value can offer dramatic increases in error sensitivity. This approach may allow the selection of more meaningful gamma criteria for IMRT QA and is straightforward to apply to other combinations of devices and treatment techniques.« less

The Danish Cardiovascular Screening Trial (DANCAVAS): study protocol for a randomized controlled trial.

PubMed

Diederichsen, Axel Cosmus Pyndt; Rasmussen, Lars Melholt; Søgaard, Rikke; Lambrechtsen, Jess; Steffensen, Flemming Hald; Frost, Lars; Egstrup, Kenneth; Urbonaviciene, Grazina; Busk, Martin; Olsen, Michael Hecht; Mickley, Hans; Hallas, Jesper; Lindholt, Jes Sanddal

2015-12-05

The significant increase in the average life expectancy has increased the societal challenge of managing serious age-related diseases, especially cancer and cardiovascular diseases. A routine check by a general practitioner is not sufficient to detect incipient cardiovascular disease. Population-based randomized clinically controlled screening trial. 45,000 Danish men aged 65-74 years living on the Island of Funen, or in the surrounding communities of Vejle and Silkeborg. No exclusion criteria are used. One-third will be invited to cardiovascular seven-faceted screening examinations at one of four locations. The screening will include: (1) low-dose non-contrast CT scan to detect coronary artery calcification and aortic/iliac aneurysms, (2) brachial and ankle blood pressure index to detect peripheral arterial disease and hypertension, (3) a telemetric assessment of the heart rhythm, and (4) a measurement of the cholesterol and plasma glucose levels. Up-to-date cardiovascular preventive treatment is recommended in case of positive findings. To investigate whether advanced cardiovascular screening will prevent death and cardiovascular events, and whether the possible health benefits are cost effective. Registry-based follow-up on all cause death (primary outcome), and costs after 3, 5 and 10 years (secondary outcome). Each of the 45,000 individuals is, by EPIDATA, given a random number from 1-100. Those numbered 67+ will be offered screening; the others will act as a control group. Only those randomized to the screening will be invited to the examination;the remaining participants will not. Numbers randomized: A total of 45,000 men will be randomized 1:2. Recruitment: Enrollment started October 2014. A 5% reduction in overall mortality (HR=0.95), with the risk for a type 1 error=5% and the risk for a type II error=80%, is expected. We expect a 2-year enrollment, a 10-year follow-up, and a median survival of 15 years among the controls. The attendance to screening is assumed to be 70%. The primary aim of this so far stand-alone population-based, randomized trial will be to evaluate the health benefits and costeffectiveness of using non-contrast full truncus computer tomography (CT) scans (to measure coronary artery calcification (CAC) and identify aortic/iliac aneurysms) and measurements of the ankle brachial blood pressure index (ABI) as part of a multifocal screening and intervention program for CVD in men aged 65-74. Attendance rate and compliance to initiated preventive actions must be expected to become of major importance. Current Controlled Trials: ISRCTN12157806 (21 March 2015).

A randomized control trial evaluating fluorescent ink versus dark ink tattoos for breast radiotherapy

PubMed Central

Kirby, Anna M; Lee, Steven F; Bartlett, Freddie; Titmarsh, Kumud; Donovan, Ellen; Griffin, Clare L; Gothard, Lone; Locke, Imogen; McNair, Helen A

2016-01-01

Objective: The purpose of this UK study was to evaluate interfraction reproducibility and body image score when using ultraviolet (UV) tattoos (not visible in ambient lighting) for external references during breast/chest wall radiotherapy and compare with conventional dark ink. Methods: In this non-blinded, single-centre, parallel group, randomized control trial, patients were allocated to receive either conventional dark ink or UV ink tattoos using computer-generated random blocks. Participant assignment was not masked. Systematic (∑) and random (σ) setup errors were determined using electronic portal images. Body image questionnaires were completed at pre-treatment, 1 month and 6 months to determine the impact of tattoo type on body image. The primary end point was to determine that UV tattoo random error (σsetup) was no less accurate than with conventional dark ink tattoos, i.e. <2.8 mm. Results: 46 patients were randomized to receive conventional dark or UV ink tattoos. 45 patients completed treatment (UV: n = 23, dark: n = 22). σsetup for the UV tattoo group was <2.8 mm in the u and v directions (p = 0.001 and p = 0.009, respectively). A larger proportion of patients reported improvement in body image score in the UV tattoo group compared with the dark ink group at 1 month [56% (13/23) vs 14% (3/22), respectively] and 6 months [52% (11/21) vs 38% (8/21), respectively]. Conclusion: UV tattoos were associated with interfraction setup reproducibility comparable with conventional dark ink. Patients reported a more favourable change in body image score up to 6 months following treatment. Advances in knowledge: This study is the first to evaluate UV tattoo external references in a randomized control trial. PMID:27710100

A randomized control trial evaluating fluorescent ink versus dark ink tattoos for breast radiotherapy.

PubMed

Landeg, Steven J; Kirby, Anna M; Lee, Steven F; Bartlett, Freddie; Titmarsh, Kumud; Donovan, Ellen; Griffin, Clare L; Gothard, Lone; Locke, Imogen; McNair, Helen A

2016-12-01

The purpose of this UK study was to evaluate interfraction reproducibility and body image score when using ultraviolet (UV) tattoos (not visible in ambient lighting) for external references during breast/chest wall radiotherapy and compare with conventional dark ink. In this non-blinded, single-centre, parallel group, randomized control trial, patients were allocated to receive either conventional dark ink or UV ink tattoos using computer-generated random blocks. Participant assignment was not masked. Systematic (∑) and random (σ) setup errors were determined using electronic portal images. Body image questionnaires were completed at pre-treatment, 1 month and 6 months to determine the impact of tattoo type on body image. The primary end point was to determine that UV tattoo random error (σ setup ) was no less accurate than with conventional dark ink tattoos, i.e. <2.8 mm. 46 patients were randomized to receive conventional dark or UV ink tattoos. 45 patients completed treatment (UV: n = 23, dark: n = 22). σ setup for the UV tattoo group was <2.8 mm in the u and v directions (p = 0.001 and p = 0.009, respectively). A larger proportion of patients reported improvement in body image score in the UV tattoo group compared with the dark ink group at 1 month [56% (13/23) vs 14% (3/22), respectively] and 6 months [52% (11/21) vs 38% (8/21), respectively]. UV tattoos were associated with interfraction setup reproducibility comparable with conventional dark ink. Patients reported a more favourable change in body image score up to 6 months following treatment. Advances in knowledge: This study is the first to evaluate UV tattoo external references in a randomized control trial.

Mediation of a Preventive Intervention’s Six-Year Effects on Health Risk Behaviors

PubMed Central

Soper, Ana C.; Wolchik, Sharlene A.; Tein, Jenn-Yun; Sandler, Irwin N.

2010-01-01

Using data from a 6-year longitudinal follow-up sample of 240 youth who participated in a randomized experimental trial of a preventive intervention for divorced families with children ages 9 -12, the current study tested mechanisms by which the intervention reduced substance use and risky sexual behavior in mid to late adolescence (15–19 years old). Mechanisms tested included parental monitoring, adaptive coping, and negative errors. Parental monitoring at 6-year follow-up mediated program effects to reduce alcohol and marijuana use, polydrug use, and other drug use for those with high pre-test risk for maladjustment. In the condition that included a program for mothers only, increases in youth adaptive coping at 6-year follow-up mediated program effects on risky sexual behavior for those with high pre-test risk for maladjustment. Contrary to expectation, program participation increased negative errors and decreased adaptive coping among low risk youth in some of the analyses. Ways in which this study furthers our understanding of pathways through which evidence-based preventive interventions affect health risk behaviors are discussed. PMID:20565156

Forecasting Daily Patient Outflow From a Ward Having No Real-Time Clinical Data

PubMed Central

Tran, Truyen; Luo, Wei; Phung, Dinh; Venkatesh, Svetha

2016-01-01

Background: Modeling patient flow is crucial in understanding resource demand and prioritization. We study patient outflow from an open ward in an Australian hospital, where currently bed allocation is carried out by a manager relying on past experiences and looking at demand. Automatic methods that provide a reasonable estimate of total next-day discharges can aid in efficient bed management. The challenges in building such methods lie in dealing with large amounts of discharge noise introduced by the nonlinear nature of hospital procedures, and the nonavailability of real-time clinical information in wards. Objective Our study investigates different models to forecast the total number of next-day discharges from an open ward having no real-time clinical data. Methods We compared 5 popular regression algorithms to model total next-day discharges: (1) autoregressive integrated moving average (ARIMA), (2) the autoregressive moving average with exogenous variables (ARMAX), (3) k-nearest neighbor regression, (4) random forest regression, and (5) support vector regression. Although the autoregressive integrated moving average model relied on past 3-month discharges, nearest neighbor forecasting used median of similar discharges in the past in estimating next-day discharge. In addition, the ARMAX model used the day of the week and number of patients currently in ward as exogenous variables. For the random forest and support vector regression models, we designed a predictor set of 20 patient features and 88 ward-level features. Results Our data consisted of 12,141 patient visits over 1826 days. Forecasting quality was measured using mean forecast error, mean absolute error, symmetric mean absolute percentage error, and root mean square error. When compared with a moving average prediction model, all 5 models demonstrated superior performance with the random forests achieving 22.7% improvement in mean absolute error, for all days in the year 2014. Conclusions In the absence of clinical information, our study recommends using patient-level and ward-level data in predicting next-day discharges. Random forest and support vector regression models are able to use all available features from such data, resulting in superior performance over traditional autoregressive methods. An intelligent estimate of available beds in wards plays a crucial role in relieving access block in emergency departments. PMID:27444059

Error control techniques for satellite and space communications

NASA Technical Reports Server (NTRS)

Costello, Daniel J., Jr.

1989-01-01

The performance of bandwidth efficient trellis codes on channels with phase jitter, or those disturbed by jamming and impulse noise is analyzed. An heuristic algorithm for construction of bandwidth efficient trellis codes with any constraint length up to about 30, any signal constellation, and any code rate was developed. Construction of good distance profile trellis codes for sequential decoding and comparison of random coding bounds of trellis coded modulation schemes are also discussed.

Ranked set sampling: cost and optimal set size.

PubMed

Nahhas, Ramzi W; Wolfe, Douglas A; Chen, Haiying

2002-12-01

McIntyre (1952, Australian Journal of Agricultural Research 3, 385-390) introduced ranked set sampling (RSS) as a method for improving estimation of a population mean in settings where sampling and ranking of units from the population are inexpensive when compared with actual measurement of the units. Two of the major factors in the usefulness of RSS are the set size and the relative costs of the various operations of sampling, ranking, and measurement. In this article, we consider ranking error models and cost models that enable us to assess the effect of different cost structures on the optimal set size for RSS. For reasonable cost structures, we find that the optimal RSS set sizes are generally larger than had been anticipated previously. These results will provide a useful tool for determining whether RSS is likely to lead to an improvement over simple random sampling in a given setting and, if so, what RSS set size is best to use in this case.

Refractive error in school children in an urban and rural setting in Cambodia.

PubMed

Gao, Zoe; Meng, Ngy; Muecke, James; Chan, Weng Onn; Piseth, Horm; Kong, Aimee; Jnguyenphamhh, Theresa; Dehghan, Yalda; Selva, Dinesh; Casson, Robert; Ang, Kim

2012-02-01

To assess the prevalence of refractive error in schoolchildren aged 12-14 years in urban and rural settings in Cambodia's Phnom Penh and Kandal provinces. Ten schools from Phnom Penh Province and 26 schools from Kandal Province were randomly selected and surveyed in October 2010. Children were examined by teams of Australian and Cambodian optometrists, ophthalmic nurses and ophthalmologists who performed visual acuity (VA) testing and cycloplegic refraction. A total of 5527 children were included in the study. The prevalence of uncorrected, presenting and best-corrected VA ≤ 6/12 in the better eye were 2.48% (95% confidence interval [CI] 2.02-2.83%), 1.90% (95% CI 1.52-2.24%) and 0.36% (95% CI 0.20-0.52%), respectively; 43 children presented with glasses whilst a total of 315 glasses were dispensed. The total prevalence of refractive error was 6.57% (95% CI 5.91-7.22%), but there was a significant difference between urban (13.7%, 95% CI 12.2-15.2%) and rural (2.5%, 95% CI 2.03-3.07%) schools (P < 0.0001). Refractive error accounted for 91.2% of visually impaired eyes, cataract for 1.7%, and other causes for 7.1%. Myopia (spherical equivalent ≤ -0.50 diopters [D] in either eye) was associated with increased age, female gender and urban schooling. The prevalence of refractive error was significantly higher in urban Phnom Penh schools than rural schools in Kandal Province. The prevalence of refractive error, particularly myopia was relatively low compared to previous reports in Asia. The majority of children did not have appropriate correction with spectacles, highlighting the need for more effective screening and optical intervention.

Best quadrature formula on Sobolev class with Chebyshev weight

NASA Astrophysics Data System (ADS)

Xie, Congcong

2008-05-01

Using best interpolation function based on a given function information, we present a best quadrature rule of function on Sobolev class KWr[-1,1] with Chebyshev weight. The given function information means that the values of a function f[set membership, variant]KWr[-1,1] and its derivatives up to r-1 order at a set of nodes x are given. Error bounds are obtained, and the method is illustrated by some examples.

Effects of Random Circuit Fabrication Errors on Small Signal Gain and on Output Phase In a Traveling Wave Tube

NASA Astrophysics Data System (ADS)

Rittersdorf, I. M.; Antonsen, T. M., Jr.; Chernin, D.; Lau, Y. Y.

2011-10-01

Random fabrication errors may have detrimental effects on the performance of traveling-wave tubes (TWTs) of all types. A new scaling law for the modification in the average small signal gain and in the output phase is derived from the third order ordinary differential equation that governs the forward wave interaction in a TWT in the presence of random error that is distributed along the axis of the tube. Analytical results compare favorably with numerical results, in both gain and phase modifications as a result of random error in the phase velocity of the slow wave circuit. Results on the effect of the reverse-propagating circuit mode will be reported. This work supported by AFOSR, ONR, L-3 Communications Electron Devices, and Northrop Grumman Corporation.

Improving UK Air Quality Modelling Through Exploitation of Satellite Observations

NASA Astrophysics Data System (ADS)

Pope, Richard; Chipperfield, Martyn; Savage, Nick

2014-05-01

In this work the applicability of satellite observations to evaluate the operational UK Met Office Air Quality in the Unified Model (AQUM) have been investigated. The main focus involved the AQUM validation against satellite observations, investigation of satellite retrieval error types and of synoptic meteorological-atmospheric chemistry relationships simulated/seen by the AQUM/satellite. The AQUM is a short range forecast model of atmospheric chemistry and aerosols up to 5 days. It has been designed to predict potentially hazardous air pollution events, e.g. high concentrations of surface ozone. The AQUM has only been validated against UK atmospheric chemistry recording surface stations. Therefore, satellite observations of atmospheric chemistry have been used to further validate the model, taking advantage of better satellite spatial coverage. Observations of summer and winter 2006 tropospheric column NO2 from both OMI and SCIAMACHY show that the AQUM generally compares well with the observations. However, in northern England positive biases (AQUM - satellite) suggest that the AQUM overestimates column NO2; we present results of sensitivity experiments on UK emissions datasets suspected to be the cause. In winter, the AQUM over predicts background column NO2 when compared to both satellite instruments. We hypothesise that the cause is the AQUM winter night-time chemistry, where the NO2 sinks are not substantially defined. Satellite data are prone to errors/uncertainty such as random, systematic and smoothing errors. We have investigated these error types and developed an algorithm to calculate and reduce the random error component of DOAS NO2 retrievals, giving more robust seasonal satellite composites. The Lamb Weather Types (LWT), an objective method of classifying the daily synoptic weather over the UK, were used to create composite satellite maps of column NO2 under different synoptic conditions. Under cyclonic conditions, satellite observed UK column NO2 is reduced as the indicative south-westerly flow transports it away from the UK over the North Sea. However, under anticyclonic conditions, the satellite shows that the stable conditions enhance the build-up of column NO2 over source regions. The influence of wind direction on column NO2 can also be seen from space with transport leeward of the source regions.

Improved PPP Ambiguity Resolution Considering the Stochastic Characteristics of Atmospheric Corrections from Regional Networks

PubMed Central

Li, Yihe; Li, Bofeng; Gao, Yang

2015-01-01

With the increased availability of regional reference networks, Precise Point Positioning (PPP) can achieve fast ambiguity resolution (AR) and precise positioning by assimilating the satellite fractional cycle biases (FCBs) and atmospheric corrections derived from these networks. In such processing, the atmospheric corrections are usually treated as deterministic quantities. This is however unrealistic since the estimated atmospheric corrections obtained from the network data are random and furthermore the interpolated corrections diverge from the realistic corrections. This paper is dedicated to the stochastic modelling of atmospheric corrections and analyzing their effects on the PPP AR efficiency. The random errors of the interpolated corrections are processed as two components: one is from the random errors of estimated corrections at reference stations, while the other arises from the atmospheric delay discrepancies between reference stations and users. The interpolated atmospheric corrections are then applied by users as pseudo-observations with the estimated stochastic model. Two data sets are processed to assess the performance of interpolated corrections with the estimated stochastic models. The results show that when the stochastic characteristics of interpolated corrections are properly taken into account, the successful fix rate reaches 93.3% within 5 min for a medium inter-station distance network and 80.6% within 10 min for a long inter-station distance network. PMID:26633400

Improved PPP Ambiguity Resolution Considering the Stochastic Characteristics of Atmospheric Corrections from Regional Networks.

PubMed

Li, Yihe; Li, Bofeng; Gao, Yang

2015-11-30

With the increased availability of regional reference networks, Precise Point Positioning (PPP) can achieve fast ambiguity resolution (AR) and precise positioning by assimilating the satellite fractional cycle biases (FCBs) and atmospheric corrections derived from these networks. In such processing, the atmospheric corrections are usually treated as deterministic quantities. This is however unrealistic since the estimated atmospheric corrections obtained from the network data are random and furthermore the interpolated corrections diverge from the realistic corrections. This paper is dedicated to the stochastic modelling of atmospheric corrections and analyzing their effects on the PPP AR efficiency. The random errors of the interpolated corrections are processed as two components: one is from the random errors of estimated corrections at reference stations, while the other arises from the atmospheric delay discrepancies between reference stations and users. The interpolated atmospheric corrections are then applied by users as pseudo-observations with the estimated stochastic model. Two data sets are processed to assess the performance of interpolated corrections with the estimated stochastic models. The results show that when the stochastic characteristics of interpolated corrections are properly taken into account, the successful fix rate reaches 93.3% within 5 min for a medium inter-station distance network and 80.6% within 10 min for a long inter-station distance network.

Capsule Performance Optimization for the National Ignition Facility

NASA Astrophysics Data System (ADS)

Landen, Otto

2009-11-01

The overall goal of the capsule performance optimization campaign is to maximize the probability of ignition by experimentally correcting for likely residual uncertainties in the implosion and hohlraum physics used in our radiation-hydrodynamic computational models before proceeding to cryogenic-layered implosions and ignition attempts. This will be accomplished using a variety of targets that will set key laser, hohlraum and capsule parameters to maximize ignition capsule implosion velocity, while minimizing fuel adiabat, core shape asymmetry and ablator-fuel mix. The targets include high Z re-emission spheres setting foot symmetry through foot cone power balance [1], liquid Deuterium-filled ``keyhole'' targets setting shock speed and timing through the laser power profile [2], symmetry capsules setting peak cone power balance and hohlraum length [3], and streaked x-ray backlit imploding capsules setting ablator thickness [4]. We will show how results from successful tuning technique demonstration shots performed at the Omega facility under scaled hohlraum and capsule conditions relevant to the ignition design meet the required sensitivity and accuracy. We will also present estimates of all expected random and systematic uncertainties in setting the key ignition laser and target parameters due to residual measurement, calibration, cross-coupling, surrogacy, and scale-up errors, and show that these get reduced after a number of shots and iterations to meet an acceptable level of residual uncertainty. Finally, we will present results from upcoming tuning technique validation shots performed at NIF at near full-scale. Prepared by LLNL under Contract DE-AC52-07NA27344. [4pt] [1] E. Dewald, et. al. Rev. Sci. Instrum. 79 (2008) 10E903. [0pt] [2] T.R. Boehly, et. al., Phys. Plasmas 16 (2009) 056302. [0pt] [3] G. Kyrala, et. al., BAPS 53 (2008) 247. [0pt] [4] D. Hicks, et. al., BAPS 53 (2008) 2.

At least some errors are randomly generated (Freud was wrong)

NASA Technical Reports Server (NTRS)

Sellen, A. J.; Senders, J. W.

1986-01-01

An experiment was carried out to expose something about human error generating mechanisms. In the context of the experiment, an error was made when a subject pressed the wrong key on a computer keyboard or pressed no key at all in the time allotted. These might be considered, respectively, errors of substitution and errors of omission. Each of seven subjects saw a sequence of three digital numbers, made an easily learned binary judgement about each, and was to press the appropriate one of two keys. Each session consisted of 1,000 presentations of randomly permuted, fixed numbers broken into 10 blocks of 100. One of two keys should have been pressed within one second of the onset of each stimulus. These data were subjected to statistical analyses in order to probe the nature of the error generating mechanisms. Goodness of fit tests for a Poisson distribution for the number of errors per 50 trial interval and for an exponential distribution of the length of the intervals between errors were carried out. There is evidence for an endogenous mechanism that may best be described as a random error generator. Furthermore, an item analysis of the number of errors produced per stimulus suggests the existence of a second mechanism operating on task driven factors producing exogenous errors. Some errors, at least, are the result of constant probability generating mechanisms with error rate idiosyncratically determined for each subject.

On the Calculation of Uncertainty Statistics with Error Bounds for CFD Calculations Containing Random Parameters and Fields

NASA Technical Reports Server (NTRS)

Barth, Timothy J.

2016-01-01

This chapter discusses the ongoing development of combined uncertainty and error bound estimates for computational fluid dynamics (CFD) calculations subject to imposed random parameters and random fields. An objective of this work is the construction of computable error bound formulas for output uncertainty statistics that guide CFD practitioners in systematically determining how accurately CFD realizations should be approximated and how accurately uncertainty statistics should be approximated for output quantities of interest. Formal error bounds formulas for moment statistics that properly account for the presence of numerical errors in CFD calculations and numerical quadrature errors in the calculation of moment statistics have been previously presented in [8]. In this past work, hierarchical node-nested dense and sparse tensor product quadratures are used to calculate moment statistics integrals. In the present work, a framework has been developed that exploits the hierarchical structure of these quadratures in order to simplify the calculation of an estimate of the quadrature error needed in error bound formulas. When signed estimates of realization error are available, this signed error may also be used to estimate output quantity of interest probability densities as a means to assess the impact of realization error on these density estimates. Numerical results are presented for CFD problems with uncertainty to demonstrate the capabilities of this framework.

Fast quantifying collision strength index of ethylene-vinyl acetate copolymer coverings on the fields based on near infrared hyperspectral imaging techniques

PubMed Central

Chen, Y. M.; Lin, P.; He, Y.; He, J. Q.; Zhang, J.; Li, X. L.

2016-01-01

A novel strategy based on the near infrared hyperspectral imaging techniques and chemometrics were explored for fast quantifying the collision strength index of ethylene-vinyl acetate copolymer (EVAC) coverings on the fields. The reflectance spectral data of EVAC coverings was obtained by using the near infrared hyperspectral meter. The collision analysis equipment was employed to measure the collision intensity of EVAC materials. The preprocessing algorithms were firstly performed before the calibration. The algorithms of random frog and successive projection (SP) were applied to extracting the fingerprint wavebands. A correlation model between the significant spectral curves which reflected the cross-linking attributions of the inner organic molecules and the degree of collision strength was set up by taking advantage of the support vector machine regression (SVMR) approach. The SP-SVMR model attained the residual predictive deviation of 3.074, the square of percentage of correlation coefficient of 93.48% and 93.05% and the root mean square error of 1.963 and 2.091 for the calibration and validation sets, respectively, which exhibited the best forecast performance. The results indicated that the approaches of integrating the near infrared hyperspectral imaging techniques with the chemometrics could be utilized to rapidly determine the degree of collision strength of EVAC. PMID:26875544

Quantitative estimation of localization errors of 3d transition metal pseudopotentials in diffusion Monte Carlo

DOE PAGES

Dzubak, Allison L.; Krogel, Jaron T.; Reboredo, Fernando A.

2017-07-10

The necessarily approximate evaluation of non-local pseudopotentials in diffusion Monte Carlo (DMC) introduces localization errors. In this paper, we estimate these errors for two families of non-local pseudopotentials for the first-row transition metal atoms Sc–Zn using an extrapolation scheme and multideterminant wavefunctions. Sensitivities of the error in the DMC energies to the Jastrow factor are used to estimate the quality of two sets of pseudopotentials with respect to locality error reduction. The locality approximation and T-moves scheme are also compared for accuracy of total energies. After estimating the removal of the locality and T-moves errors, we present the range ofmore » fixed-node energies between a single determinant description and a full valence multideterminant complete active space expansion. The results for these pseudopotentials agree with previous findings that the locality approximation is less sensitive to changes in the Jastrow than T-moves yielding more accurate total energies, however not necessarily more accurate energy differences. For both the locality approximation and T-moves, we find decreasing Jastrow sensitivity moving left to right across the series Sc–Zn. The recently generated pseudopotentials of Krogel et al. reduce the magnitude of the locality error compared with the pseudopotentials of Burkatzki et al. by an average estimated 40% using the locality approximation. The estimated locality error is equivalent for both sets of pseudopotentials when T-moves is used. Finally, for the Sc–Zn atomic series with these pseudopotentials, and using up to three-body Jastrow factors, our results suggest that the fixed-node error is dominant over the locality error when a single determinant is used.« less

The Refurbishment and Upgrade of the Atmospheric Radiation Measurement Raman Lidar

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

Turner, D.D.; Goldsmith, J.E.M.

The Atmospheric Radiation Measurement Program (ARM) Climate Research Facility (ACRF) Raman lidar (CARL) is an autonomous, turn-key system that profiles water vapor, aerosols, and clouds throughout the diurnal cycle for days without attention (Goldsmith et al. 1998). CARL was first deployed to the Southern Great Plains CRF during the summer of 1996 and participated in the 1996 and 1997 water vapor intensive operational periods (IOPs). Since February 1998, the system has collected over 38,000 hrs of data (equivalent of almost 4.4 years), with an average monthly uptime of 62% during this time period. This unprecedented performance by CARL makes itmore » the premier operational Raman lidar in the world. Unfortunately, CARL began degrading in early 2002. This loss of sensitivity, which affected all observed variables, was very gradual and thus was not identified until the autumn of 2003. Analysis of the data suggested the problem was not associated with the laser or transmit portion of the system, but rather in the detection subsystem, as both the background values and the peak signals showed a marked decreases over this time period. The loss of sensitivity of a factor of 2-4, depending on the channel, resulted in higher random error in the retrieved products, such as the aerosol backscatter coefficient and water vapor mixing ratio. Figure 1 shows the random error at 2 km for aerosol backscatter coefficient (top) and water vapor mixing ratio (middle), in terms of percent of the signal for both average daytime (red) and nighttime (blue) data from 1998 to 2005. The seasonal variation of water vapor is easily seen in the random error in the water vapor mixing ratio data. The loss of sensitivity also affected the maximum range of the usable data, as illustrated by the dramatic decrease in the maximum height seen in the water vapor mixing ratio data (bottom). This degradation, which results in much larger random errors, greatly hinders the analysis of data sets such as the Aerosol IOP (March 2003) and the AIRS Water Vapor Experiment (December 2003). The degradation and its impact on the Aerosol IOP analysis are reported in Ferrare et al. 2005.« less

Honest Importance Sampling with Multiple Markov Chains

PubMed Central

Tan, Aixin; Doss, Hani; Hobert, James P.

2017-01-01

Importance sampling is a classical Monte Carlo technique in which a random sample from one probability density, π1, is used to estimate an expectation with respect to another, π. The importance sampling estimator is strongly consistent and, as long as two simple moment conditions are satisfied, it obeys a central limit theorem (CLT). Moreover, there is a simple consistent estimator for the asymptotic variance in the CLT, which makes for routine computation of standard errors. Importance sampling can also be used in the Markov chain Monte Carlo (MCMC) context. Indeed, if the random sample from π1 is replaced by a Harris ergodic Markov chain with invariant density π1, then the resulting estimator remains strongly consistent. There is a price to be paid however, as the computation of standard errors becomes more complicated. First, the two simple moment conditions that guarantee a CLT in the iid case are not enough in the MCMC context. Second, even when a CLT does hold, the asymptotic variance has a complex form and is difficult to estimate consistently. In this paper, we explain how to use regenerative simulation to overcome these problems. Actually, we consider a more general set up, where we assume that Markov chain samples from several probability densities, π1, …, πk, are available. We construct multiple-chain importance sampling estimators for which we obtain a CLT based on regeneration. We show that if the Markov chains converge to their respective target distributions at a geometric rate, then under moment conditions similar to those required in the iid case, the MCMC-based importance sampling estimator obeys a CLT. Furthermore, because the CLT is based on a regenerative process, there is a simple consistent estimator of the asymptotic variance. We illustrate the method with two applications in Bayesian sensitivity analysis. The first concerns one-way random effects models under different priors. The second involves Bayesian variable selection in linear regression, and for this application, importance sampling based on multiple chains enables an empirical Bayes approach to variable selection. PMID:28701855

Honest Importance Sampling with Multiple Markov Chains.

PubMed

Tan, Aixin; Doss, Hani; Hobert, James P

2015-01-01

Importance sampling is a classical Monte Carlo technique in which a random sample from one probability density, π 1 , is used to estimate an expectation with respect to another, π . The importance sampling estimator is strongly consistent and, as long as two simple moment conditions are satisfied, it obeys a central limit theorem (CLT). Moreover, there is a simple consistent estimator for the asymptotic variance in the CLT, which makes for routine computation of standard errors. Importance sampling can also be used in the Markov chain Monte Carlo (MCMC) context. Indeed, if the random sample from π 1 is replaced by a Harris ergodic Markov chain with invariant density π 1 , then the resulting estimator remains strongly consistent. There is a price to be paid however, as the computation of standard errors becomes more complicated. First, the two simple moment conditions that guarantee a CLT in the iid case are not enough in the MCMC context. Second, even when a CLT does hold, the asymptotic variance has a complex form and is difficult to estimate consistently. In this paper, we explain how to use regenerative simulation to overcome these problems. Actually, we consider a more general set up, where we assume that Markov chain samples from several probability densities, π 1 , …, π k , are available. We construct multiple-chain importance sampling estimators for which we obtain a CLT based on regeneration. We show that if the Markov chains converge to their respective target distributions at a geometric rate, then under moment conditions similar to those required in the iid case, the MCMC-based importance sampling estimator obeys a CLT. Furthermore, because the CLT is based on a regenerative process, there is a simple consistent estimator of the asymptotic variance. We illustrate the method with two applications in Bayesian sensitivity analysis. The first concerns one-way random effects models under different priors. The second involves Bayesian variable selection in linear regression, and for this application, importance sampling based on multiple chains enables an empirical Bayes approach to variable selection.

Integrating photo-stimulable phosphor plates into dental and dental hygiene radiography curricula.

PubMed

Tax, Cara L; Robb, Christine L; Brillant, Martha G S; Doucette, Heather J

2013-11-01

It is not known whether the integration of photo-stimulable phosphor (PSP) plates into dental and dental hygiene curricula creates unique learning challenges for students. The purpose of this two-year study was to determine if dental hygiene students had more and/or different types of errors when using PSP plates compared to film and whether the PSP imaging plates had any particular characteristics that needed to be addressed in the learning process. Fifty-nine first-year dental hygiene students at one Canadian dental school were randomly assigned to two groups (PSP or film) before exposing their initial full mouth series on a teaching manikin using the parallel technique. The principal investigator determined the number and types of errors based on a specific set of performance criteria. The two groups (PSP vs. film) were compared for total number and type of errors made. Results of the study indicated the difference in the total number of errors made using PSP or film was not statistically significant; however, there was a difference in the types of errors made, with the PSP group having more horizontal errors than the film group. In addition, the study identified a number of unique characteristics of the PSP plates that required special consideration for teaching this technology.

A hybrid method for synthetic aperture ladar phase-error compensation

NASA Astrophysics Data System (ADS)

Hua, Zhili; Li, Hongping; Gu, Yongjian

2009-07-01

As a high resolution imaging sensor, synthetic aperture ladar data contain phase-error whose source include uncompensated platform motion and atmospheric turbulence distortion errors. Two previously devised methods, rank one phase-error estimation algorithm and iterative blind deconvolution are reexamined, of which a hybrid method that can recover both the images and PSF's without any a priori information on the PSF is built to speed up the convergence rate by the consideration in the choice of initialization. To be integrated into spotlight mode SAL imaging model respectively, three methods all can effectively reduce the phase-error distortion. For each approach, signal to noise ratio, root mean square error and CPU time are computed, from which we can see the convergence rate of the hybrid method can be improved because a more efficient initialization set of blind deconvolution. Moreover, by making a further discussion of the hybrid method, the weight distribution of ROPE and IBD is found to be an important factor that affects the final result of the whole compensation process.

Bayesian estimation of Karhunen–Loève expansions; A random subspace approach

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

Chowdhary, Kenny; Najm, Habib N.

One of the most widely-used statistical procedures for dimensionality reduction of high dimensional random fields is Principal Component Analysis (PCA), which is based on the Karhunen-Lo eve expansion (KLE) of a stochastic process with finite variance. The KLE is analogous to a Fourier series expansion for a random process, where the goal is to find an orthogonal transformation for the data such that the projection of the data onto this orthogonal subspace is optimal in the L 2 sense, i.e, which minimizes the mean square error. In practice, this orthogonal transformation is determined by performing an SVD (Singular Value Decomposition)more » on the sample covariance matrix or on the data matrix itself. Sampling error is typically ignored when quantifying the principal components, or, equivalently, basis functions of the KLE. Furthermore, it is exacerbated when the sample size is much smaller than the dimension of the random field. In this paper, we introduce a Bayesian KLE procedure, allowing one to obtain a probabilistic model on the principal components, which can account for inaccuracies due to limited sample size. The probabilistic model is built via Bayesian inference, from which the posterior becomes the matrix Bingham density over the space of orthonormal matrices. We use a modified Gibbs sampling procedure to sample on this space and then build a probabilistic Karhunen-Lo eve expansions over random subspaces to obtain a set of low-dimensional surrogates of the stochastic process. We illustrate this probabilistic procedure with a finite dimensional stochastic process inspired by Brownian motion.« less

Bayesian estimation of Karhunen–Loève expansions; A random subspace approach

DOE PAGES

Chowdhary, Kenny; Najm, Habib N.

2016-04-13

One of the most widely-used statistical procedures for dimensionality reduction of high dimensional random fields is Principal Component Analysis (PCA), which is based on the Karhunen-Lo eve expansion (KLE) of a stochastic process with finite variance. The KLE is analogous to a Fourier series expansion for a random process, where the goal is to find an orthogonal transformation for the data such that the projection of the data onto this orthogonal subspace is optimal in the L 2 sense, i.e, which minimizes the mean square error. In practice, this orthogonal transformation is determined by performing an SVD (Singular Value Decomposition)more » on the sample covariance matrix or on the data matrix itself. Sampling error is typically ignored when quantifying the principal components, or, equivalently, basis functions of the KLE. Furthermore, it is exacerbated when the sample size is much smaller than the dimension of the random field. In this paper, we introduce a Bayesian KLE procedure, allowing one to obtain a probabilistic model on the principal components, which can account for inaccuracies due to limited sample size. The probabilistic model is built via Bayesian inference, from which the posterior becomes the matrix Bingham density over the space of orthonormal matrices. We use a modified Gibbs sampling procedure to sample on this space and then build a probabilistic Karhunen-Lo eve expansions over random subspaces to obtain a set of low-dimensional surrogates of the stochastic process. We illustrate this probabilistic procedure with a finite dimensional stochastic process inspired by Brownian motion.« less

Capsule implosion optimization during the indirect-drive National Ignition Campaign

NASA Astrophysics Data System (ADS)

Landen, O. L.; Edwards, J.; Haan, S. W.; Robey, H. F.; Milovich, J.; Spears, B. K.; Weber, S. V.; Clark, D. S.; Lindl, J. D.; MacGowan, B. J.; Moses, E. I.; Atherton, J.; Amendt, P. A.; Boehly, T. R.; Bradley, D. K.; Braun, D. G.; Callahan, D. A.; Celliers, P. M.; Collins, G. W.; Dewald, E. L.; Divol, L.; Frenje, J. A.; Glenzer, S. H.; Hamza, A.; Hammel, B. A.; Hicks, D. G.; Hoffman, N.; Izumi, N.; Jones, O. S.; Kilkenny, J. D.; Kirkwood, R. K.; Kline, J. L.; Kyrala, G. A.; Marinak, M. M.; Meezan, N.; Meyerhofer, D. D.; Michel, P.; Munro, D. H.; Olson, R. E.; Nikroo, A.; Regan, S. P.; Suter, L. J.; Thomas, C. A.; Wilson, D. C.

2011-05-01

Capsule performance optimization campaigns will be conducted at the National Ignition Facility [G. H. Miller, E. I. Moses, and C. R. Wuest, Nucl. Fusion 44, 228 (2004)] to substantially increase the probability of ignition. The campaigns will experimentally correct for residual uncertainties in the implosion and hohlraum physics used in our radiation-hydrodynamic computational models using a variety of ignition capsule surrogates before proceeding to cryogenic-layered implosions and ignition experiments. The quantitative goals and technique options and down selections for the tuning campaigns are first explained. The computationally derived sensitivities to key laser and target parameters are compared to simple analytic models to gain further insight into the physics of the tuning techniques. The results of the validation of the tuning techniques at the OMEGA facility [J. M. Soures et al., Phys. Plasmas 3, 2108 (1996)] under scaled hohlraum and capsule conditions relevant to the ignition design are shown to meet the required sensitivity and accuracy. A roll-up of all expected random and systematic uncertainties in setting the key ignition laser and target parameters due to residual measurement, calibration, cross-coupling, surrogacy, and scale-up errors has been derived that meets the required budget. Finally, we show how the tuning precision will be improved after a number of shots and iterations to meet an acceptable level of residual uncertainty.

Comparison of SVM, RF and ELM on an Electronic Nose for the Intelligent Evaluation of Paraffin Samples.

PubMed

Men, Hong; Fu, Songlin; Yang, Jialin; Cheng, Meiqi; Shi, Yan; Liu, Jingjing

2018-01-18

Paraffin odor intensity is an important quality indicator when a paraffin inspection is performed. Currently, paraffin odor level assessment is mainly dependent on an artificial sensory evaluation. In this paper, we developed a paraffin odor analysis system to classify and grade four kinds of paraffin samples. The original feature set was optimized using Principal Component Analysis (PCA) and Partial Least Squares (PLS). Support Vector Machine (SVM), Random Forest (RF), and Extreme Learning Machine (ELM) were applied to three different feature data sets for classification and level assessment of paraffin. For classification, the model based on SVM, with an accuracy rate of 100%, was superior to that based on RF, with an accuracy rate of 98.33-100%, and ELM, with an accuracy rate of 98.01-100%. For level assessment, the R² related to the training set was above 0.97 and the R² related to the test set was above 0.87. Through comprehensive comparison, the generalization of the model based on ELM was superior to those based on SVM and RF. The scoring errors for the three models were 0.0016-0.3494, lower than the error of 0.5-1.0 measured by industry standard experts, meaning these methods have a higher prediction accuracy for scoring paraffin level.

Modeling error PDF optimization based wavelet neural network modeling of dynamic system and its application in blast furnace ironmaking

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

Zhou, Ping; Wang, Chenyu; Li, Mingjie

In general, the modeling errors of dynamic system model are a set of random variables. The traditional performance index of modeling such as means square error (MSE) and root means square error (RMSE) can not fully express the connotation of modeling errors with stochastic characteristics both in the dimension of time domain and space domain. Therefore, the probability density function (PDF) is introduced to completely describe the modeling errors in both time scales and space scales. Based on it, a novel wavelet neural network (WNN) modeling method is proposed by minimizing the two-dimensional (2D) PDF shaping of modeling errors. First,more » the modeling error PDF by the tradional WNN is estimated using data-driven kernel density estimation (KDE) technique. Then, the quadratic sum of 2D deviation between the modeling error PDF and the target PDF is utilized as performance index to optimize the WNN model parameters by gradient descent method. Since the WNN has strong nonlinear approximation and adaptive capability, and all the parameters are well optimized by the proposed method, the developed WNN model can make the modeling error PDF track the target PDF, eventually. Simulation example and application in a blast furnace ironmaking process show that the proposed method has a higher modeling precision and better generalization ability compared with the conventional WNN modeling based on MSE criteria. Furthermore, the proposed method has more desirable estimation for modeling error PDF that approximates to a Gaussian distribution whose shape is high and narrow.« less

Modeling error PDF optimization based wavelet neural network modeling of dynamic system and its application in blast furnace ironmaking

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

Zhou, Ping; Wang, Chenyu; Li, Mingjie

In general, the modeling errors of dynamic system model are a set of random variables. The traditional performance index of modeling such as means square error (MSE) and root means square error (RMSE) cannot fully express the connotation of modeling errors with stochastic characteristics both in the dimension of time domain and space domain. Therefore, the probability density function (PDF) is introduced to completely describe the modeling errors in both time scales and space scales. Based on it, a novel wavelet neural network (WNN) modeling method is proposed by minimizing the two-dimensional (2D) PDF shaping of modeling errors. First, themore » modeling error PDF by the traditional WNN is estimated using data-driven kernel density estimation (KDE) technique. Then, the quadratic sum of 2D deviation between the modeling error PDF and the target PDF is utilized as performance index to optimize the WNN model parameters by gradient descent method. Since the WNN has strong nonlinear approximation and adaptive capability, and all the parameters are well optimized by the proposed method, the developed WNN model can make the modeling error PDF track the target PDF, eventually. Simulation example and application in a blast furnace ironmaking process show that the proposed method has a higher modeling precision and better generalization ability compared with the conventional WNN modeling based on MSE criteria. However, the proposed method has more desirable estimation for modeling error PDF that approximates to a Gaussian distribution whose shape is high and narrow.« less

Modeling error PDF optimization based wavelet neural network modeling of dynamic system and its application in blast furnace ironmaking

DOE PAGES

Zhou, Ping; Wang, Chenyu; Li, Mingjie; ...

2018-01-31

In general, the modeling errors of dynamic system model are a set of random variables. The traditional performance index of modeling such as means square error (MSE) and root means square error (RMSE) cannot fully express the connotation of modeling errors with stochastic characteristics both in the dimension of time domain and space domain. Therefore, the probability density function (PDF) is introduced to completely describe the modeling errors in both time scales and space scales. Based on it, a novel wavelet neural network (WNN) modeling method is proposed by minimizing the two-dimensional (2D) PDF shaping of modeling errors. First, themore » modeling error PDF by the traditional WNN is estimated using data-driven kernel density estimation (KDE) technique. Then, the quadratic sum of 2D deviation between the modeling error PDF and the target PDF is utilized as performance index to optimize the WNN model parameters by gradient descent method. Since the WNN has strong nonlinear approximation and adaptive capability, and all the parameters are well optimized by the proposed method, the developed WNN model can make the modeling error PDF track the target PDF, eventually. Simulation example and application in a blast furnace ironmaking process show that the proposed method has a higher modeling precision and better generalization ability compared with the conventional WNN modeling based on MSE criteria. However, the proposed method has more desirable estimation for modeling error PDF that approximates to a Gaussian distribution whose shape is high and narrow.« less

Efficient error correction for next-generation sequencing of viral amplicons

PubMed Central

2012-01-01

Background Next-generation sequencing allows the analysis of an unprecedented number of viral sequence variants from infected patients, presenting a novel opportunity for understanding virus evolution, drug resistance and immune escape. However, sequencing in bulk is error prone. Thus, the generated data require error identification and correction. Most error-correction methods to date are not optimized for amplicon analysis and assume that the error rate is randomly distributed. Recent quality assessment of amplicon sequences obtained using 454-sequencing showed that the error rate is strongly linked to the presence and size of homopolymers, position in the sequence and length of the amplicon. All these parameters are strongly sequence specific and should be incorporated into the calibration of error-correction algorithms designed for amplicon sequencing. Results In this paper, we present two new efficient error correction algorithms optimized for viral amplicons: (i) k-mer-based error correction (KEC) and (ii) empirical frequency threshold (ET). Both were compared to a previously published clustering algorithm (SHORAH), in order to evaluate their relative performance on 24 experimental datasets obtained by 454-sequencing of amplicons with known sequences. All three algorithms show similar accuracy in finding true haplotypes. However, KEC and ET were significantly more efficient than SHORAH in removing false haplotypes and estimating the frequency of true ones. Conclusions Both algorithms, KEC and ET, are highly suitable for rapid recovery of error-free haplotypes obtained by 454-sequencing of amplicons from heterogeneous viruses. The implementations of the algorithms and data sets used for their testing are available at: http://alan.cs.gsu.edu/NGS/?q=content/pyrosequencing-error-correction-algorithm PMID:22759430

Efficient error correction for next-generation sequencing of viral amplicons.

PubMed

Skums, Pavel; Dimitrova, Zoya; Campo, David S; Vaughan, Gilberto; Rossi, Livia; Forbi, Joseph C; Yokosawa, Jonny; Zelikovsky, Alex; Khudyakov, Yury

2012-06-25

Next-generation sequencing allows the analysis of an unprecedented number of viral sequence variants from infected patients, presenting a novel opportunity for understanding virus evolution, drug resistance and immune escape. However, sequencing in bulk is error prone. Thus, the generated data require error identification and correction. Most error-correction methods to date are not optimized for amplicon analysis and assume that the error rate is randomly distributed. Recent quality assessment of amplicon sequences obtained using 454-sequencing showed that the error rate is strongly linked to the presence and size of homopolymers, position in the sequence and length of the amplicon. All these parameters are strongly sequence specific and should be incorporated into the calibration of error-correction algorithms designed for amplicon sequencing. In this paper, we present two new efficient error correction algorithms optimized for viral amplicons: (i) k-mer-based error correction (KEC) and (ii) empirical frequency threshold (ET). Both were compared to a previously published clustering algorithm (SHORAH), in order to evaluate their relative performance on 24 experimental datasets obtained by 454-sequencing of amplicons with known sequences. All three algorithms show similar accuracy in finding true haplotypes. However, KEC and ET were significantly more efficient than SHORAH in removing false haplotypes and estimating the frequency of true ones. Both algorithms, KEC and ET, are highly suitable for rapid recovery of error-free haplotypes obtained by 454-sequencing of amplicons from heterogeneous viruses.The implementations of the algorithms and data sets used for their testing are available at: http://alan.cs.gsu.edu/NGS/?q=content/pyrosequencing-error-correction-algorithm.

Warm-up for Sprint Swimming: Race-Pace or Aerobic Stimulation? A Randomized Study.

PubMed

Neiva, Henrique P; Marques, Mário C; Barbosa, Tiago M; Izquierdo, Mikel; Viana, João L; Teixeira, Ana M; Marinho, Daniel A

2017-09-01

Neiva, HP, Marques, MC, Barbosa, TM, Izquierdo, M, Viana, JL, Teixeira, AM, and Marinho, DA. Warm-up for sprint swimming: race-pace or aerobic stimulation? A randomized study. J Strength Cond Res 31(9): 2423-2431, 2017-The aim of this study was to compare the effects of 2 different warm-up intensities on 100-m swimming performance in a randomized controlled trial. Thirteen competitive swimmers performed two 100-m freestyle time-trials on separate days after either control or experimental warm-up in a randomized design. The control warm-up included a typical race-pace set (4 × 25 m), whereas the experimental warm-up included an aerobic set (8 × 50 m at 98-102% of critical velocity). Cortisol, testosterone, blood lactate ([La]), oxygen uptake (V[Combining Dot Above]O2), heart rate, core (Tcore and Tcorenet) and tympanic temperatures, and rating of perceived exertion (RPE) were monitored. Stroke length (SL), stroke frequency (SF), stroke index (SI), and propelling efficiency (ηp) were assessed for each 50-m lap. We found that V[Combining Dot Above]O2, heart rate, and Tcorenet were higher after experimental warm-up (d > 0.73), but only the positive effect for Tcorenet was maintained until the trial. Performance was not different between conditions (d = 0.07). Experimental warm-up was found to slow SF (mean change ±90% CL = 2.06 ± 1.48%) and increase SL (1.65 ± 1.40%) and ηp (1.87 ± 1.33%) in the first lap. After the time-trials, this warm-up had a positive effect on Tcorenet (d = 0.69) and a negative effect on [La] (d = 0.56). Although the warm-ups had similar outcomes in the 100-m freestyle, performance was achieved through different biomechanical strategies. Stroke length and efficiency were higher in the first lap after the experimental warm-up, whereas SF was higher after control warm-up. Physiological adaptations were observed mainly through an increased Tcore after experimental warm-up. In this condition, the lower [La] after the trial suggests lower dependency on anaerobic metabolism.

Cognitive-Behavioral Family Treatment for Suicide Attempt Prevention: A Randomized Controlled Trial.

PubMed

Asarnow, Joan Rosenbaum; Hughes, Jennifer L; Babeva, Kalina N; Sugar, Catherine A

2017-06-01

Suicide is a leading cause of death. New data indicate alarming increases in suicide death rates, yet no treatments with replicated efficacy or effectiveness exist for youths with self-harm presentations, a high-risk group for both fatal and nonfatal suicide attempts. We addressed this gap by evaluating Safe Alternatives for Teens and Youths (SAFETY), a cognitive-behavioral, dialectical behavior therapy-informed family treatment designed to promote safety. Randomized controlled trial for adolescents (12-18 years of age) with recent (past 3 months) suicide attempts or other self-harm. Youth were randomized either to SAFETY or to treatment as usual enhanced by parent education and support accessing community treatment (E-TAU). Outcomes were evaluated at baseline, 3 months, or end of treatment period, and were followed up through 6 to 12 months. The primary outcome was youth-reported incident suicide attempts through the 3-month follow-up. Survival analyses indicated a significantly higher probability of survival without a suicide attempt by the 3-month follow-up point among SAFETY youths (cumulative estimated probability of survival without suicide attempt = 1.00, standard error = 0), compared to E-TAU youths (cumulative estimated probability of survival without suicide attempt = 0.67, standard error = 0.14; z = 2.45, p = .02, number needed to treat = 3) and for the overall survival curves (Wilcoxon χ 2 1  = 5.81, p = .02). Sensitivity analyses using parent report when youth report was unavailable and conservative assumptions regarding missing data yielded similar results for 3-month outcomes. Results support the efficacy of SAFETY for preventing suicide attempts in adolescents presenting with recent self-harm. This is the second randomized trial to demonstrate that treatment including cognitive-behavioral and family components can provide some protection from suicide attempt risk in these high-risk youths. Clinical trial registration information-Effectiveness of a Family-Based Intervention for Adolescent Suicide Attempters (The SAFETY Study); http://clinicaltrials.gov/; NCT00692302. Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

NHash: Randomized N-Gram Hashing for Distributed Generation of Validatable Unique Study Identifiers in Multicenter Research.

PubMed

Zhang, Guo-Qiang; Tao, Shiqiang; Xing, Guangming; Mozes, Jeno; Zonjy, Bilal; Lhatoo, Samden D; Cui, Licong

2015-11-10

A unique study identifier serves as a key for linking research data about a study subject without revealing protected health information in the identifier. While sufficient for single-site and limited-scale studies, the use of common unique study identifiers has several drawbacks for large multicenter studies, where thousands of research participants may be recruited from multiple sites. An important property of study identifiers is error tolerance (or validatable), in that inadvertent editing mistakes during their transmission and use will most likely result in invalid study identifiers. This paper introduces a novel method called "Randomized N-gram Hashing (NHash)," for generating unique study identifiers in a distributed and validatable fashion, in multicenter research. NHash has a unique set of properties: (1) it is a pseudonym serving the purpose of linking research data about a study participant for research purposes; (2) it can be generated automatically in a completely distributed fashion with virtually no risk for identifier collision; (3) it incorporates a set of cryptographic hash functions based on N-grams, with a combination of additional encryption techniques such as a shift cipher; (d) it is validatable (error tolerant) in the sense that inadvertent edit errors will mostly result in invalid identifiers. NHash consists of 2 phases. First, an intermediate string using randomized N-gram hashing is generated. This string consists of a collection of N-gram hashes f1, f2, ..., fk. The input for each function fi has 3 components: a random number r, an integer n, and input data m. The result, fi(r, n, m), is an n-gram of m with a starting position s, which is computed as (r mod |m|), where |m| represents the length of m. The output for Step 1 is the concatenation of the sequence f1(r1, n1, m1), f2(r2, n2, m2), ..., fk(rk, nk, mk). In the second phase, the intermediate string generated in Phase 1 is encrypted using techniques such as shift cipher. The result of the encryption, concatenated with the random number r, is the final NHash study identifier. We performed experiments using a large synthesized dataset comparing NHash with random strings, and demonstrated neglegible probability for collision. We implemented NHash for the Center for SUDEP Research (CSR), a National Institute for Neurological Disorders and Stroke-funded Center Without Walls for Collaborative Research in the Epilepsies. This multicenter collaboration involves 14 institutions across the United States and Europe, bringing together extensive and diverse expertise to understand sudden unexpected death in epilepsy patients (SUDEP). The CSR Data Repository has successfully used NHash to link deidentified multimodal clinical data collected in participating CSR institutions, meeting all desired objectives of NHash.

Adaptive use of research aircraft data sets for hurricane forecasts

NASA Astrophysics Data System (ADS)

Biswas, M. K.; Krishnamurti, T. N.

2008-02-01

This study uses an adaptive observational strategy for hurricane forecasting. It shows the impacts of Lidar Atmospheric Sensing Experiment (LASE) and dropsonde data sets from Convection and Moisture Experiment (CAMEX) field campaigns on hurricane track and intensity forecasts. The following cases are used in this study: Bonnie, Danielle and Georges of 1998 and Erin, Gabrielle and Humberto of 2001. A single model run for each storm is carried out using the Florida State University Global Spectral Model (FSUGSM) with the European Center for Medium Range Weather Forecasts (ECMWF) analysis as initial conditions, in addition to 50 other model runs where the analysis is randomly perturbed for each storm. The centers of maximum variance of the DLM heights are located from the forecast error variance fields at the 84-hr forecast. Back correlations are then performed using the centers of these maximum variances and the fields at the 36-hr forecast. The regions having the highest correlations in the vicinity of the hurricanes are indicative of regions from where the error growth emanates and suggests the need for additional observations. Data sets are next assimilated in those areas that contain high correlations. Forecasts are computed using the new initial conditions for the storm cases, and track and intensity skills are then examined with respect to the control forecast. The adaptive strategy is capable of identifying sensitive areas where additional observations can help in reducing the hurricane track forecast errors. A reduction of position error by approximately 52% for day 3 of forecast (averaged over 7 storm cases) over the control runs is observed. The intensity forecast shows only a slight positive impact due to the model’s coarse resolution.

Random Error in Judgment: The Contribution of Encoding and Retrieval Processes

ERIC Educational Resources Information Center

Pleskac, Timothy J.; Dougherty, Michael R.; Rivadeneira, A. Walkyria; Wallsten, Thomas S.

2009-01-01

Theories of confidence judgments have embraced the role random error plays in influencing responses. An important next step is to identify the source(s) of these random effects. To do so, we used the stochastic judgment model (SJM) to distinguish the contribution of encoding and retrieval processes. In particular, we investigated whether dividing…

The random coding bound is tight for the average code.

NASA Technical Reports Server (NTRS)

Gallager, R. G.

1973-01-01

The random coding bound of information theory provides a well-known upper bound to the probability of decoding error for the best code of a given rate and block length. The bound is constructed by upperbounding the average error probability over an ensemble of codes. The bound is known to give the correct exponential dependence of error probability on block length for transmission rates above the critical rate, but it gives an incorrect exponential dependence at rates below a second lower critical rate. Here we derive an asymptotic expression for the average error probability over the ensemble of codes used in the random coding bound. The result shows that the weakness of the random coding bound at rates below the second critical rate is due not to upperbounding the ensemble average, but rather to the fact that the best codes are much better than the average at low rates.

Relative Proportion Of Different Types Of Refractive Errors In Subjects Seeking Laser Vision Correction.

PubMed

Althomali, Talal A

2018-01-01

Refractive errors are a form of optical defect affecting more than 2.3 billion people worldwide. As refractive errors are a major contributor of mild to moderate vision impairment, assessment of their relative proportion would be helpful in the strategic planning of health programs. To determine the pattern of the relative proportion of types of refractive errors among the adult candidates seeking laser assisted refractive correction in a private clinic setting in Saudi Arabia. The clinical charts of 687 patients (1374 eyes) with mean age 27.6 ± 7.5 years who desired laser vision correction and underwent a pre-LASIK work-up were reviewed retrospectively. Refractive errors were classified as myopia, hyperopia and astigmatism. Manifest refraction spherical equivalent (MRSE) was applied to define refractive errors. Distribution percentage of different types of refractive errors; myopia, hyperopia and astigmatism. The mean spherical equivalent for 1374 eyes was -3.11 ± 2.88 D. Of the total 1374 eyes, 91.8% (n = 1262) eyes had myopia, 4.7% (n = 65) eyes had hyperopia and 3.4% (n = 47) had emmetropia with astigmatism. Distribution percentage of astigmatism (cylinder error of ≥ 0.50 D) was 78.5% (1078/1374 eyes); of which % 69.1% (994/1374) had low to moderate astigmatism and 9.4% (129/1374) had high astigmatism. Of the adult candidates seeking laser refractive correction in a private setting in Saudi Arabia, myopia represented greatest burden with more than 90% myopic eyes, compared to hyperopia in nearly 5% eyes. Astigmatism was present in more than 78% eyes.

High-speed receiver based on waveguide germanium photodetector wire-bonded to 90nm SOI CMOS amplifier.

PubMed

Pan, Huapu; Assefa, Solomon; Green, William M J; Kuchta, Daniel M; Schow, Clint L; Rylyakov, Alexander V; Lee, Benjamin G; Baks, Christian W; Shank, Steven M; Vlasov, Yurii A

2012-07-30

The performance of a receiver based on a CMOS amplifier circuit designed with 90nm ground rules wire-bonded to a waveguide germanium photodetector is characterized at data rates up to 40Gbps. Both chips were fabricated through the IBM Silicon CMOS Integrated Nanophotonics process on specialty photonics-enabled SOI wafers. At the data rate of 28Gbps which is relevant to the new generation of optical interconnects, a sensitivity of -7.3dBm average optical power is demonstrated with 3.4pJ/bit power-efficiency and 0.6UI horizontal eye opening at a bit-error-rate of 10(-12). The receiver operates error-free (bit-error-rate < 10(-12)) up to 40Gbps with optimized power supply settings demonstrating an energy efficiency of 1.4pJ/bit and 4pJ/bit at data rates of 32Gbps and 40Gbps, respectively, with an average optical power of -0.8dBm.

Uncertainty Analysis of Sonic Boom Levels Measured in a Simulator at NASA Langley

NASA Technical Reports Server (NTRS)

Rathsam, Jonathan; Ely, Jeffry W.

2012-01-01

A sonic boom simulator has been constructed at NASA Langley Research Center for testing the human response to sonic booms heard indoors. Like all measured quantities, sonic boom levels in the simulator are subject to systematic and random errors. To quantify these errors, and their net influence on the measurement result, a formal uncertainty analysis is conducted. Knowledge of the measurement uncertainty, or range of values attributable to the quantity being measured, enables reliable comparisons among measurements at different locations in the simulator as well as comparisons with field data or laboratory data from other simulators. The analysis reported here accounts for acoustic excitation from two sets of loudspeakers: one loudspeaker set at the facility exterior that reproduces the exterior sonic boom waveform and a second set of interior loudspeakers for reproducing indoor rattle sounds. The analysis also addresses the effect of pressure fluctuations generated when exterior doors of the building housing the simulator are opened. An uncertainty budget is assembled to document each uncertainty component, its sensitivity coefficient, and the combined standard uncertainty. The latter quantity will be reported alongside measurement results in future research reports to indicate data reliability.

Performance of quantum annealing on random Ising problems implemented using the D-Wave Two

NASA Astrophysics Data System (ADS)

Wang, Zhihui; Job, Joshua; Rønnow, Troels F.; Troyer, Matthias; Lidar, Daniel A.; USC Collaboration; ETH Collaboration

2014-03-01

Detecting a possible speedup of quantum annealing compared to classical algorithms is a pressing task in experimental adiabatic quantum computing. In this talk, we discuss the performance of the D-Wave Two quantum annealing device on Ising spin glass problems. The expected time to solution for the device to solve random instances with up to 503 spins and with specified coupling ranges is evaluated while carefully addressing the issue of statistical errors. We perform a systematic comparison of the expected time to solution between the D-Wave Two and classical stochastic solvers, specifically simulated annealing, and simulated quantum annealing based on quantum Monte Carlo, and discuss the question of speedup.

An innovative method for coordinate measuring machine one-dimensional self-calibration with simplified experimental process.

PubMed

Fang, Cheng; Butler, David Lee

2013-05-01

In this paper, an innovative method for CMM (Coordinate Measuring Machine) self-calibration is proposed. In contrast to conventional CMM calibration that relies heavily on a high precision reference standard such as a laser interferometer, the proposed calibration method is based on a low-cost artefact which is fabricated with commercially available precision ball bearings. By optimizing the mathematical model and rearranging the data sampling positions, the experimental process and data analysis can be simplified. In mathematical expression, the samples can be minimized by eliminating the redundant equations among those configured by the experimental data array. The section lengths of the artefact are measured at arranged positions, with which an equation set can be configured to determine the measurement errors at the corresponding positions. With the proposed method, the equation set is short of one equation, which can be supplemented by either measuring the total length of the artefact with a higher-precision CMM or calibrating the single point error at the extreme position with a laser interferometer. In this paper, the latter is selected. With spline interpolation, the error compensation curve can be determined. To verify the proposed method, a simple calibration system was set up on a commercial CMM. Experimental results showed that with the error compensation curve uncertainty of the measurement can be reduced to 50%.

The dissociation energy of N2

NASA Technical Reports Server (NTRS)

Almloef, Jan; Deleeuw, Bradley J.; Taylor, Peter R.; Bauschlicher, Charles W., Jr.; Siegbahn, Per

1989-01-01

The requirements for very accurate ab initio quantum chemical prediction of dissociation energies are examined using a detailed investigation of the nitrogen molecule. Although agreement with experiment to within 1 kcal/mol is not achieved even with the most elaborate multireference CI (configuration interaction) wave functions and largest basis sets currently feasible, it is possible to obtain agreement to within about 2 kcal/mol, or 1 percent of the dissociation energy. At this level it is necessary to account for core-valence correlation effects and to include up to h-type functions in the basis. The effect of i-type functions, the use of different reference configuration spaces, and basis set superposition error were also investigated. After discussing these results, the remaining sources of error in our best calculations are examined.

Influence of surgeon behavior on trainee willingness to speak up: a randomized controlled trial.

PubMed

Barzallo Salazar, Marco J; Minkoff, Howard; Bayya, Jyothshna; Gillett, Brian; Onoriode, Helen; Weedon, Jeremy; Altshuler, Lisa; Fisher, Nelli

2014-11-01

Our aim was to determine if a surgeon's behaviors can encourage or discourage trainees from speaking up when they witness a surgical mistake. A randomized clinical trial in which medical students (n = 55) were randomly assigned to an "encouraged" (n = 28) or "discouraged" (n = 27) group. Participants underwent personality tests to assess decision-making styles, and were then trained on basic tasks ("burn" then "cut") on a laparoscopic surgery simulator. After randomization, students assisted at a simulated laparoscopic salpingectomy. The senior surgeon used either an "encourage" script (eg, "Your opinion is important.") or a "discourage" script (eg, "Do what I say. Save questions for next time."). Otherwise, the surgery was conducted identically. Subsequently, a surgical mistake was made by the senior surgeon when he instructed students to cut without burning. Students were considered to have spoken up if they questioned the instruction and did not cut. Potential personality bias was assessed with two validated personality tests before simulation. Data were processed with Mann-Whitney and Fisher exact tests. The students in the encouraged group were significantly more likely to speak up (23 of 28 [82%] vs 8 of 27 [30%]; p < 0.001). There was no statistically significant difference between the two groups in personality traits, student training level (p = 1.0), or sex (p = 0.53). A discouraging environment decreases the frequency with which trainees speak up when witnessing a surgical error. The senior surgeon plays an important role in improving intraoperative communication between junior and senior clinicians and can enhance patient safety. Copyright © 2014 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Bayesian randomized clinical trials: From fixed to adaptive design.

PubMed

Yin, Guosheng; Lam, Chi Kin; Shi, Haolun

2017-08-01

Randomized controlled studies are the gold standard for phase III clinical trials. Using α-spending functions to control the overall type I error rate, group sequential methods are well established and have been dominating phase III studies. Bayesian randomized design, on the other hand, can be viewed as a complement instead of competitive approach to the frequentist methods. For the fixed Bayesian design, the hypothesis testing can be cast in the posterior probability or Bayes factor framework, which has a direct link to the frequentist type I error rate. Bayesian group sequential design relies upon Bayesian decision-theoretic approaches based on backward induction, which is often computationally intensive. Compared with the frequentist approaches, Bayesian methods have several advantages. The posterior predictive probability serves as a useful and convenient tool for trial monitoring, and can be updated at any time as the data accrue during the trial. The Bayesian decision-theoretic framework possesses a direct link to the decision making in the practical setting, and can be modeled more realistically to reflect the actual cost-benefit analysis during the drug development process. Other merits include the possibility of hierarchical modeling and the use of informative priors, which would lead to a more comprehensive utilization of information from both historical and longitudinal data. From fixed to adaptive design, we focus on Bayesian randomized controlled clinical trials and make extensive comparisons with frequentist counterparts through numerical studies. Copyright © 2017 Elsevier Inc. All rights reserved.

Combined influence of CT random noise and HU-RSP calibration curve nonlinearities on proton range systematic errors

NASA Astrophysics Data System (ADS)

Brousmiche, S.; Souris, K.; Orban de Xivry, J.; Lee, J. A.; Macq, B.; Seco, J.

2017-11-01

Proton range random and systematic uncertainties are the major factors undermining the advantages of proton therapy, namely, a sharp dose falloff and a better dose conformality for lower doses in normal tissues. The influence of CT artifacts such as beam hardening or scatter can easily be understood and estimated due to their large-scale effects on the CT image, like cupping and streaks. In comparison, the effects of weakly-correlated stochastic noise are more insidious and less attention is drawn on them partly due to the common belief that they only contribute to proton range uncertainties and not to systematic errors thanks to some averaging effects. A new source of systematic errors on the range and relative stopping powers (RSP) has been highlighted and proved not to be negligible compared to the 3.5% uncertainty reference value used for safety margin design. Hence, we demonstrate that the angular points in the HU-to-RSP calibration curve are an intrinsic source of proton range systematic error for typical levels of zero-mean stochastic CT noise. Systematic errors on RSP of up to 1% have been computed for these levels. We also show that the range uncertainty does not generally vary linearly with the noise standard deviation. We define a noise-dependent effective calibration curve that better describes, for a given material, the RSP value that is actually used. The statistics of the RSP and the range continuous slowing down approximation (CSDA) have been analytically derived for the general case of a calibration curve obtained by the stoichiometric calibration procedure. These models have been validated against actual CSDA simulations for homogeneous and heterogeneous synthetical objects as well as on actual patient CTs for prostate and head-and-neck treatment planning situations.

Calculating radiotherapy margins based on Bayesian modelling of patient specific random errors

NASA Astrophysics Data System (ADS)

Herschtal, A.; te Marvelde, L.; Mengersen, K.; Hosseinifard, Z.; Foroudi, F.; Devereux, T.; Pham, D.; Ball, D.; Greer, P. B.; Pichler, P.; Eade, T.; Kneebone, A.; Bell, L.; Caine, H.; Hindson, B.; Kron, T.

2015-02-01

Collected real-life clinical target volume (CTV) displacement data show that some patients undergoing external beam radiotherapy (EBRT) demonstrate significantly more fraction-to-fraction variability in their displacement (‘random error’) than others. This contrasts with the common assumption made by historical recipes for margin estimation for EBRT, that the random error is constant across patients. In this work we present statistical models of CTV displacements in which random errors are characterised by an inverse gamma (IG) distribution in order to assess the impact of random error variability on CTV-to-PTV margin widths, for eight real world patient cohorts from four institutions, and for different sites of malignancy. We considered a variety of clinical treatment requirements and penumbral widths. The eight cohorts consisted of a total of 874 patients and 27 391 treatment sessions. Compared to a traditional margin recipe that assumes constant random errors across patients, for a typical 4 mm penumbral width, the IG based margin model mandates that in order to satisfy the common clinical requirement that 90% of patients receive at least 95% of prescribed RT dose to the entire CTV, margins be increased by a median of 10% (range over the eight cohorts -19% to +35%). This substantially reduces the proportion of patients for whom margins are too small to satisfy clinical requirements.

A decision support system for automatic sleep staging from EEG signals using tunable Q-factor wavelet transform and spectral features.

PubMed

Hassan, Ahnaf Rashik; Bhuiyan, Mohammed Imamul Hassan

2016-09-15

Automatic sleep scoring is essential owing to the fact that conventionally a large volume of data have to be analyzed visually by the physicians which is onerous, time-consuming and error-prone. Therefore, there is a dire need of an automated sleep staging scheme. In this work, we decompose sleep-EEG signal segments using tunable-Q factor wavelet transform (TQWT). Various spectral features are then computed from TQWT sub-bands. The performance of spectral features in the TQWT domain has been determined by intuitive and graphical analyses, statistical validation, and Fisher criteria. Random forest is used to perform classification. Optimal choices and the effects of TQWT and random forest parameters have been determined and expounded. Experimental outcomes manifest the efficacy of our feature generation scheme in terms of p-values of ANOVA analysis and Fisher criteria. The proposed scheme yields 90.38%, 91.50%, 92.11%, 94.80%, 97.50% for 6-stage to 2-stage classification of sleep states on the benchmark Sleep-EDF data-set. In addition, its performance on DREAMS Subjects Data-set is also promising. The performance of the proposed method is significantly better than the existing ones in terms of accuracy and Cohen's kappa coefficient. Additionally, the proposed scheme gives high detection accuracy for sleep stages non-REM 1 and REM. Spectral features in the TQWT domain can discriminate sleep-EEG signals corresponding to various sleep states efficaciously. The proposed scheme will alleviate the burden of the physicians, speed-up sleep disorder diagnosis, and expedite sleep research. Copyright © 2016 Elsevier B.V. All rights reserved.

Questionnaire-based person trip visualization and its integration to quantitative measurements in Myanmar

NASA Astrophysics Data System (ADS)

Kimijiama, S.; Nagai, M.

2016-06-01

With telecommunication development in Myanmar, person trip survey is supposed to shift from conversational questionnaire to GPS survey. Integration of both historical questionnaire data to GPS survey and visualizing them are very important to evaluate chronological trip changes with socio-economic and environmental events. The objectives of this paper are to: (a) visualize questionnaire-based person trip data, (b) compare the errors between questionnaire and GPS data sets with respect to sex and age and (c) assess the trip behaviour in time-series. Totally, 345 individual respondents were selected through random stratification to assess person trip using a questionnaire and GPS survey for each. Conversion of trip information such as a destination from the questionnaires was conducted by using GIS. The results show that errors between the two data sets in the number of trips, total trip distance and total trip duration are 25.5%, 33.2% and 37.2%, respectively. The smaller errors are found among working-age females mainly employed with the project-related activities generated by foreign investment. The trip distant was yearly increased. The study concluded that visualization of questionnaire-based person trip data and integrating them to current quantitative measurements are very useful to explore historical trip changes and understand impacts from socio-economic events.

Evaluation of single-point sampling strategies for the estimation of moclobemide exposure in depressive patients.

PubMed

Ignjatovic, Anita Rakic; Miljkovic, Branislava; Todorovic, Dejan; Timotijevic, Ivana; Pokrajac, Milena

2011-05-01

Because moclobemide pharmacokinetics vary considerably among individuals, monitoring of plasma concentrations lends insight into its pharmacokinetic behavior and enhances its rational use in clinical practice. The aim of this study was to evaluate whether single concentration-time points could adequately predict moclobemide systemic exposure. Pharmacokinetic data (full 7-point pharmacokinetic profiles), obtained from 21 depressive inpatients receiving moclobemide (150 mg 3 times daily), were randomly split into development (n = 18) and validation (n = 16) sets. Correlations between the single concentration-time points and the area under the concentration-time curve within a 6-hour dosing interval at steady-state (AUC(0-6)) were assessed by linear regression analyses. The predictive performance of single-point sampling strategies was evaluated in the validation set by mean prediction error, mean absolute error, and root mean square error. Plasma concentrations in the absorption phase yielded unsatisfactory predictions of moclobemide AUC(0-6). The best estimation of AUC(0-6) was achieved from concentrations at 4 and 6 hours following dosing. As the most reliable surrogate for moclobemide systemic exposure, concentrations at 4 and 6 hours should be used instead of predose trough concentrations as an indicator of between-patient variability and a guide for dose adjustments in specific clinical situations.

Particle Tracking on the BNL Relativistic Heavy Ion Collider

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

Dell, G. F.

1986-08-07

Tracking studies including the effects of random multipole errors as well as the effects of random and systematic multipole errors have been made for RHIC. Initial results for operating at an off diagonal working point are discussed.

Synthetic Spike-in Standards Improve Run-Specific Systematic Error Analysis for DNA and RNA Sequencing

PubMed Central

Zook, Justin M.; Samarov, Daniel; McDaniel, Jennifer; Sen, Shurjo K.; Salit, Marc

2012-01-01

While the importance of random sequencing errors decreases at higher DNA or RNA sequencing depths, systematic sequencing errors (SSEs) dominate at high sequencing depths and can be difficult to distinguish from biological variants. These SSEs can cause base quality scores to underestimate the probability of error at certain genomic positions, resulting in false positive variant calls, particularly in mixtures such as samples with RNA editing, tumors, circulating tumor cells, bacteria, mitochondrial heteroplasmy, or pooled DNA. Most algorithms proposed for correction of SSEs require a data set used to calculate association of SSEs with various features in the reads and sequence context. This data set is typically either from a part of the data set being “recalibrated” (Genome Analysis ToolKit, or GATK) or from a separate data set with special characteristics (SysCall). Here, we combine the advantages of these approaches by adding synthetic RNA spike-in standards to human RNA, and use GATK to recalibrate base quality scores with reads mapped to the spike-in standards. Compared to conventional GATK recalibration that uses reads mapped to the genome, spike-ins improve the accuracy of Illumina base quality scores by a mean of 5 Phred-scaled quality score units, and by as much as 13 units at CpG sites. In addition, since the spike-in data used for recalibration are independent of the genome being sequenced, our method allows run-specific recalibration even for the many species without a comprehensive and accurate SNP database. We also use GATK with the spike-in standards to demonstrate that the Illumina RNA sequencing runs overestimate quality scores for AC, CC, GC, GG, and TC dinucleotides, while SOLiD has less dinucleotide SSEs but more SSEs for certain cycles. We conclude that using these DNA and RNA spike-in standards with GATK improves base quality score recalibration. PMID:22859977

Underestimation of Variance of Predicted Health Utilities Derived from Multiattribute Utility Instruments.

PubMed

Chan, Kelvin K W; Xie, Feng; Willan, Andrew R; Pullenayegum, Eleanor M

2017-04-01

Parameter uncertainty in value sets of multiattribute utility-based instruments (MAUIs) has received little attention previously. This false precision leads to underestimation of the uncertainty of the results of cost-effectiveness analyses. The aim of this study is to examine the use of multiple imputation as a method to account for this uncertainty of MAUI scoring algorithms. We fitted a Bayesian model with random effects for respondents and health states to the data from the original US EQ-5D-3L valuation study, thereby estimating the uncertainty in the EQ-5D-3L scoring algorithm. We applied these results to EQ-5D-3L data from the Commonwealth Fund (CWF) Survey for Sick Adults ( n = 3958), comparing the standard error of the estimated mean utility in the CWF population using the predictive distribution from the Bayesian mixed-effect model (i.e., incorporating parameter uncertainty in the value set) with the standard error of the estimated mean utilities based on multiple imputation and the standard error using the conventional approach of using MAUI (i.e., ignoring uncertainty in the value set). The mean utility in the CWF population based on the predictive distribution of the Bayesian model was 0.827 with a standard error (SE) of 0.011. When utilities were derived using the conventional approach, the estimated mean utility was 0.827 with an SE of 0.003, which is only 25% of the SE based on the full predictive distribution of the mixed-effect model. Using multiple imputation with 20 imputed sets, the mean utility was 0.828 with an SE of 0.011, which is similar to the SE based on the full predictive distribution. Ignoring uncertainty of the predicted health utilities derived from MAUIs could lead to substantial underestimation of the variance of mean utilities. Multiple imputation corrects for this underestimation so that the results of cost-effectiveness analyses using MAUIs can report the correct degree of uncertainty.

Measurement of electromagnetic tracking error in a navigated breast surgery setup

NASA Astrophysics Data System (ADS)

Harish, Vinyas; Baksh, Aidan; Ungi, Tamas; Lasso, Andras; Baum, Zachary; Gauvin, Gabrielle; Engel, Jay; Rudan, John; Fichtinger, Gabor

2016-03-01

PURPOSE: The measurement of tracking error is crucial to ensure the safety and feasibility of electromagnetically tracked, image-guided procedures. Measurement should occur in a clinical environment because electromagnetic field distortion depends on positioning relative to the field generator and metal objects. However, we could not find an accessible and open-source system for calibration, error measurement, and visualization. We developed such a system and tested it in a navigated breast surgery setup. METHODS: A pointer tool was designed for concurrent electromagnetic and optical tracking. Software modules were developed for automatic calibration of the measurement system, real-time error visualization, and analysis. The system was taken to an operating room to test for field distortion in a navigated breast surgery setup. Positional and rotational electromagnetic tracking errors were then calculated using optical tracking as a ground truth. RESULTS: Our system is quick to set up and can be rapidly deployed. The process from calibration to visualization also only takes a few minutes. Field distortion was measured in the presence of various surgical equipment. Positional and rotational error in a clean field was approximately 0.90 mm and 0.31°. The presence of a surgical table, an electrosurgical cautery, and anesthesia machine increased the error by up to a few tenths of a millimeter and tenth of a degree. CONCLUSION: In a navigated breast surgery setup, measurement and visualization of tracking error defines a safe working area in the presence of surgical equipment. Our system is available as an extension for the open-source 3D Slicer platform.

Optimization of Error-Bounded Lossy Compression for Hard-to-Compress HPC Data

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

Di, Sheng; Cappello, Franck

Since today’s scientific applications are producing vast amounts of data, compressing them before storage/transmission is critical. Results of existing compressors show two types of HPC data sets: highly compressible and hard to compress. In this work, we carefully design and optimize the error-bounded lossy compression for hard-tocompress scientific data. We propose an optimized algorithm that can adaptively partition the HPC data into best-fit consecutive segments each having mutually close data values, such that the compression condition can be optimized. Another significant contribution is the optimization of shifting offset such that the XOR-leading-zero length between two consecutive unpredictable data points canmore » be maximized. We finally devise an adaptive method to select the best-fit compressor at runtime for maximizing the compression factor. We evaluate our solution using 13 benchmarks based on real-world scientific problems, and we compare it with 9 other state-of-the-art compressors. Experiments show that our compressor can always guarantee the compression errors within the user-specified error bounds. Most importantly, our optimization can improve the compression factor effectively, by up to 49% for hard-tocompress data sets with similar compression/decompression time cost.« less

Simulation of wave propagation in three-dimensional random media

NASA Technical Reports Server (NTRS)

Coles, William A.; Filice, J. P.; Frehlich, R. G.; Yadlowsky, M.

1993-01-01

Quantitative error analysis for simulation of wave propagation in three dimensional random media assuming narrow angular scattering are presented for the plane wave and spherical wave geometry. This includes the errors resulting from finite grid size, finite simulation dimensions, and the separation of the two-dimensional screens along the propagation direction. Simple error scalings are determined for power-law spectra of the random refractive index of the media. The effects of a finite inner scale are also considered. The spatial spectra of the intensity errors are calculated and compared to the spatial spectra of intensity. The numerical requirements for a simulation of given accuracy are determined for realizations of the field. The numerical requirements for accurate estimation of higher moments of the field are less stringent.

Excimer Laser Versus Phakic Intraocular Lenses for Myopia and Astigmatism: A Meta-Analysis of Randomized Controlled Trials.

PubMed

Chen, Haiting; Liu, Yu; Niu, Guangzeng; Ma, Jingxue

2018-05-01

Meta-analysis of randomized controlled trials (RCTs) which compared excimer laser refractive surgery and phakic intraocular lenses (PIOLs) for the treatment of myopia and astigmatism. An electronic literature search was performed using the PubMed, EBSCO, CNKI, and Cochrane Library database to identify prospective RCTs which compared excimer laser refractive surgery and PIOL with a follow-up time of at least 12 months. Efficacy, accuracy, safety outcomes, and complications were analyzed by standardized mean difference, risk ratio, and the pooled estimates according to a fixed effect model or random effect model. This review included 5 RCTs with a sum of 405 eyes. The range of myopia was 6.0 to 20.0 D with up to 4.0 D of astigmatism. The PIOL group was more likely to achieve a spherical equivalence within±1.0 D of target refraction at 12 months postoperatively (P=0.009), and was less likely to lose one or more lines of best spectacle corrected visual acuity than the LASER group (P=0.002). On the whole, there is no significant difference in efficacy and complications between the two kinds of surgeries. This meta-analysis indicated that PIOLs were safer and more accurate within 12 months of follow-up compared with excimer laser surgical for refractive errors.

Regionalized PM2.5 Community Multiscale Air Quality model performance evaluation across a continuous spatiotemporal domain.

PubMed

Reyes, Jeanette M; Xu, Yadong; Vizuete, William; Serre, Marc L

2017-01-01

The regulatory Community Multiscale Air Quality (CMAQ) model is a means to understanding the sources, concentrations and regulatory attainment of air pollutants within a model's domain. Substantial resources are allocated to the evaluation of model performance. The Regionalized Air quality Model Performance (RAMP) method introduced here explores novel ways of visualizing and evaluating CMAQ model performance and errors for daily Particulate Matter ≤ 2.5 micrometers (PM2.5) concentrations across the continental United States. The RAMP method performs a non-homogenous, non-linear, non-homoscedastic model performance evaluation at each CMAQ grid. This work demonstrates that CMAQ model performance, for a well-documented 2001 regulatory episode, is non-homogeneous across space/time. The RAMP correction of systematic errors outperforms other model evaluation methods as demonstrated by a 22.1% reduction in Mean Square Error compared to a constant domain wide correction. The RAMP method is able to accurately reproduce simulated performance with a correlation of r = 76.1%. Most of the error coming from CMAQ is random error with only a minority of error being systematic. Areas of high systematic error are collocated with areas of high random error, implying both error types originate from similar sources. Therefore, addressing underlying causes of systematic error will have the added benefit of also addressing underlying causes of random error.

Sampling design for groundwater solute transport: Tests of methods and analysis of Cape Cod tracer test data

USGS Publications Warehouse

Knopman, Debra S.; Voss, Clifford I.; Garabedian, Stephen P.

1991-01-01

Tests of a one-dimensional sampling design methodology on measurements of bromide concentration collected during the natural gradient tracer test conducted by the U.S. Geological Survey on Cape Cod, Massachusetts, demonstrate its efficacy for field studies of solute transport in groundwater and the utility of one-dimensional analysis. The methodology was applied to design of sparse two-dimensional networks of fully screened wells typical of those often used in engineering practice. In one-dimensional analysis, designs consist of the downstream distances to rows of wells oriented perpendicular to the groundwater flow direction and the timing of sampling to be carried out on each row. The power of a sampling design is measured by its effectiveness in simultaneously meeting objectives of model discrimination, parameter estimation, and cost minimization. One-dimensional models of solute transport, differing in processes affecting the solute and assumptions about the structure of the flow field, were considered for description of tracer cloud migration. When fitting each model using nonlinear regression, additive and multiplicative error forms were allowed for the residuals which consist of both random and model errors. The one-dimensional single-layer model of a nonreactive solute with multiplicative error was judged to be the best of those tested. Results show the efficacy of the methodology in designing sparse but powerful sampling networks. Designs that sample five rows of wells at five or fewer times in any given row performed as well for model discrimination as the full set of samples taken up to eight times in a given row from as many as 89 rows. Also, designs for parameter estimation judged to be good by the methodology were as effective in reducing the variance of parameter estimates as arbitrary designs with many more samples. Results further showed that estimates of velocity and longitudinal dispersivity in one-dimensional models based on data from only five rows of fully screened wells each sampled five or fewer times were practically equivalent to values determined from moments analysis of the complete three-dimensional set of 29,285 samples taken during 16 sampling times.

Phobos laser ranging: Numerical Geodesy experiments for Martian system science

NASA Astrophysics Data System (ADS)

Dirkx, D.; Vermeersen, L. L. A.; Noomen, R.; Visser, P. N. A. M.

2014-09-01

Laser ranging is emerging as a technology for use over (inter)planetary distances, having the advantage of high (mm-cm) precision and accuracy and low mass and power consumption. We have performed numerical simulations to assess the science return in terms of geodetic observables of a hypothetical Phobos lander performing active two-way laser ranging with Earth-based stations. We focus our analysis on the estimation of Phobos and Mars gravitational, tidal and rotational parameters. We explicitly include systematic error sources in addition to uncorrelated random observation errors. This is achieved through the use of consider covariance parameters, specifically the ground station position and observation biases. Uncertainties for the consider parameters are set at 5 mm and at 1 mm for the Gaussian uncorrelated observation noise (for an observation integration time of 60 s). We perform the analysis for a mission duration up to 5 years. It is shown that a Phobos Laser Ranging (PLR) can contribute to a better understanding of the Martian system, opening the possibility for improved determination of a variety of physical parameters of Mars and Phobos. The simulations show that the mission concept is especially suited for estimating Mars tidal deformation parameters, estimating degree 2 Love numbers with absolute uncertainties at the 10-2 to 10-4 level after 1 and 4 years, respectively and providing separate estimates for the Martian quality factors at Sun and Phobos-forced frequencies. The estimation of Phobos libration amplitudes and gravity field coefficients provides an estimate of Phobos' relative equatorial and polar moments of inertia with an absolute uncertainty of 10-4 and 10-7, respectively, after 1 year. The observation of Phobos tidal deformation will be able to differentiate between a rubble pile and monolithic interior within 2 years. For all parameters, systematic errors have a much stronger influence (per unit uncertainty) than the uncorrelated Gaussian observation noise. This indicates the need for the inclusion of systematic errors in simulation studies and special attention to the mitigation of these errors in mission and system design.

Design the RS(255,239) encoder and interleaving in the space laser communication system

NASA Astrophysics Data System (ADS)

Lang, Yue; Tong, Shou-feng

2013-08-01

Space laser communication is researched by more and more countries. Space laser communication deserves to be researched. We can acquire higher transmission speed and better transmission quality between satellite and satellite, satellite and earth by setting up laser link. But in the space laser communication system，the reliability is under influences of many factors of atmosphere，detector noise, optical platform jitter and other factors. The intensity of the signal which is attenuated because of the long transmission distance is demanded to have higher intensity to acquire low BER. The channel code technology can enhance the anti-interference ability of the system. The theory of channel coding technology is that some redundancies is added to information codes. So it can make use of the checkout polynomial to correct errors at the sink port. It help the system to get low BER rate and coding gain. Reed-Solomon (RS) code is one of the channel code, and it is one kind of multi-ary BCH code, and it can correct both burst errors and random errors, and it is widely used in the error-control schemes. The new method of the RS encoder and interleaving based on the FPGA is proposed, aiming at satisfying the needs of the widely-used error control technology in the space laser communication field. An improved method for Finite Galois Field multiplier of encoding is proposed, and it is suitable for FPGA implementation. Comparison of the XOR gates cost between the optimization and original, the number of XOR gates is lessen more than 40% .Then give a new structure of interleaving by using the FPGA. By controlling the in-data stream and out-data stream of encoder, the asynchronous process of the whole frame is accomplished, while by using multi-level pipeline, the real-time transfer of the data is achieved. By controlling the read-address and write-address of the block RAM, the interleaving operation of the arbitrary depth is synchronously implemented. Compared with the normal method, it could reduce the complexity of the channel encoder and the hardware requirement effectively.

The Effect of Health Information Technology on Hospital Quality of Care

ERIC Educational Resources Information Center

Sun, Ruirui

2016-01-01

Health Information Technology (Health IT) is designed to store patients' records safely and clearly, to reduce input errors and missing records, and to make communications more efficiently. Concerned with the relatively lower adoption rate among the US hospitals compared to most developed countries, the Bush Administration set up the Office of…

Amperometric Glucose Sensors: Sources of Error and Potential Benefit of Redundancy

PubMed Central

Castle, Jessica R.; Kenneth Ward, W.

2010-01-01

Amperometric glucose sensors have advanced the care of patients with diabetes and are being studied to control insulin delivery in the research setting. However, at times, currently available sensors demonstrate suboptimal accuracy, which can result from calibration error, sensor drift, or lag. Inaccuracy can be particularly problematic in a closed-loop glycemic control system. In such a system, the use of two sensors allows selection of the more accurate sensor as the input to the controller. In our studies in subjects with type 1 diabetes, the accuracy of the better of two sensors significantly exceeded the accuracy of a single, randomly selected sensor. If an array with three or more sensors were available, it would likely allow even better accuracy with the use of voting. PMID:20167187

Learning in the Machine: Random Backpropagation and the Deep Learning Channel.

PubMed

Baldi, Pierre; Sadowski, Peter; Lu, Zhiqin

2018-07-01

Random backpropagation (RBP) is a variant of the backpropagation algorithm for training neural networks, where the transpose of the forward matrices are replaced by fixed random matrices in the calculation of the weight updates. It is remarkable both because of its effectiveness, in spite of using random matrices to communicate error information, and because it completely removes the taxing requirement of maintaining symmetric weights in a physical neural system. To better understand random backpropagation, we first connect it to the notions of local learning and learning channels. Through this connection, we derive several alternatives to RBP, including skipped RBP (SRPB), adaptive RBP (ARBP), sparse RBP, and their combinations (e.g. ASRBP) and analyze their computational complexity. We then study their behavior through simulations using the MNIST and CIFAR-10 bechnmark datasets. These simulations show that most of these variants work robustly, almost as well as backpropagation, and that multiplication by the derivatives of the activation functions is important. As a follow-up, we study also the low-end of the number of bits required to communicate error information over the learning channel. We then provide partial intuitive explanations for some of the remarkable properties of RBP and its variations. Finally, we prove several mathematical results, including the convergence to fixed points of linear chains of arbitrary length, the convergence to fixed points of linear autoencoders with decorrelated data, the long-term existence of solutions for linear systems with a single hidden layer and convergence in special cases, and the convergence to fixed points of non-linear chains, when the derivative of the activation functions is included.

Scientific Impacts of Wind Direction Errors

NASA Technical Reports Server (NTRS)

Liu, W. Timothy; Kim, Seung-Bum; Lee, Tong; Song, Y. Tony; Tang, Wen-Qing; Atlas, Robert

2004-01-01

An assessment on the scientific impact of random errors in wind direction (less than 45 deg) retrieved from space-based observations under weak wind (less than 7 m/s ) conditions was made. averages, and these weak winds cover most of the tropical, sub-tropical, and coastal oceans. Introduction of these errors in the semi-daily winds causes, on average, 5% changes of the yearly mean Ekman and Sverdrup volume transports computed directly from the winds, respectively. These poleward movements of water are the main mechanisms to redistribute heat from the warmer tropical region to the colder high- latitude regions, and they are the major manifestations of the ocean's function in modifying Earth's climate. Simulation by an ocean general circulation model shows that the wind errors introduce a 5% error in the meridional heat transport at tropical latitudes. The simulation also shows that the erroneous winds cause a pile-up of warm surface water in the eastern tropical Pacific, similar to the conditions during El Nino episode. Similar wind directional errors cause significant change in sea-surface temperature and sea-level patterns in coastal oceans in a coastal model simulation. Previous studies have shown that assimilation of scatterometer winds improves 3-5 day weather forecasts in the Southern Hemisphere. When directional information below 7 m/s was withheld, approximately 40% of the improvement was lost

Analysis of uncertainties in Monte Carlo simulated organ dose for chest CT

NASA Astrophysics Data System (ADS)

Muryn, John S.; Morgan, Ashraf G.; Segars, W. P.; Liptak, Chris L.; Dong, Frank F.; Primak, Andrew N.; Li, Xiang

2015-03-01

In Monte Carlo simulation of organ dose for a chest CT scan, many input parameters are required (e.g., half-value layer of the x-ray energy spectrum, effective beam width, and anatomical coverage of the scan). The input parameter values are provided by the manufacturer, measured experimentally, or determined based on typical clinical practices. The goal of this study was to assess the uncertainties in Monte Carlo simulated organ dose as a result of using input parameter values that deviate from the truth (clinical reality). Organ dose from a chest CT scan was simulated for a standard-size female phantom using a set of reference input parameter values (treated as the truth). To emulate the situation in which the input parameter values used by the researcher may deviate from the truth, additional simulations were performed in which errors were purposefully introduced into the input parameter values, the effects of which on organ dose per CTDIvol were analyzed. Our study showed that when errors in half value layer were within ± 0.5 mm Al, the errors in organ dose per CTDIvol were less than 6%. Errors in effective beam width of up to 3 mm had negligible effect (< 2.5%) on organ dose. In contrast, when the assumed anatomical center of the patient deviated from the true anatomical center by 5 cm, organ dose errors of up to 20% were introduced. Lastly, when the assumed extra scan length was longer by 4 cm than the true value, dose errors of up to 160% were found. The results answer the important question: to what level of accuracy each input parameter needs to be determined in order to obtain accurate organ dose results.

Shuttle program: Ground tracking data program document shuttle OFT launch/landing

NASA Technical Reports Server (NTRS)

Lear, W. M.

1977-01-01

The equations for processing ground tracking data during a space shuttle ascent or entry, or any nonfree flight phase of a shuttle mission are given. The resulting computer program processes data from up to three stations simultaneously: C-band station number 1; C-band station number 2; and an S-band station. The C-band data consists of range, azimuth, and elevation angle measurements. The S-band data consists of range, two angles, and integrated Doppler data in the form of cycle counts. A nineteen element state vector is used in Kalman filter to process the measurements. The acceleration components of the shuttle are taken to be independent exponentially-correlated random variables. Nine elements of the state vector are the measurement bias errors associated with range and two angles for each tracking station. The biases are all modeled as exponentially-correlated random variables with a typical time constant of 108 seconds. All time constants are taken to be the same for all nine state variables. This simplifies the logic in propagating the state error covariance matrix ahead in time.

Accuracy of Robotic Radiosurgical Liver Treatment Throughout the Respiratory Cycle

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

Winter, Jeff D.; Wong, Raimond; Swaminath, Anand

Purpose: To quantify random uncertainties in robotic radiosurgical treatment of liver lesions with real-time respiratory motion management. Methods and Materials: We conducted a retrospective analysis of 27 liver cancer patients treated with robotic radiosurgery over 118 fractions. The robotic radiosurgical system uses orthogonal x-ray images to determine internal target position and correlates this position with an external surrogate to provide robotic corrections of linear accelerator positioning. Verification and update of this internal–external correlation model was achieved using periodic x-ray images collected throughout treatment. To quantify random uncertainties in targeting, we analyzed logged tracking information and isolated x-ray images collected immediately beforemore » beam delivery. For translational correlation errors, we quantified the difference between correlation model–estimated target position and actual position determined by periodic x-ray imaging. To quantify prediction errors, we computed the mean absolute difference between the predicted coordinates and actual modeled position calculated 115 milliseconds later. We estimated overall random uncertainty by quadratically summing correlation, prediction, and end-to-end targeting errors. We also investigated relationships between tracking errors and motion amplitude using linear regression. Results: The 95th percentile absolute correlation errors in each direction were 2.1 mm left–right, 1.8 mm anterior–posterior, 3.3 mm cranio–caudal, and 3.9 mm 3-dimensional radial, whereas 95th percentile absolute radial prediction errors were 0.5 mm. Overall 95th percentile random uncertainty was 4 mm in the radial direction. Prediction errors were strongly correlated with modeled target amplitude (r=0.53-0.66, P<.001), whereas only weak correlations existed for correlation errors. Conclusions: Study results demonstrate that model correlation errors are the primary random source of uncertainty in Cyberknife liver treatment and, unlike prediction errors, are not strongly correlated with target motion amplitude. Aggregate 3-dimensional radial position errors presented here suggest the target will be within 4 mm of the target volume for 95% of the beam delivery.« less

Prevention of hospital payment errors and implications for case management: a study of nine hospitals with a high proportion of short-term admissions over time.

PubMed

Hightower, Rebecca E

2008-01-01

Since the publication of the first analysis of Medicare payment error rates in 1998, the Office of Inspector General and the Centers for Medicare & Medicaid Services have focused resources on Medicare payment error prevention programs, now referred to as the Hospital Payment Monitoring Program. The purpose of the Hospital Payment Monitoring Program is to educate providers of Medicare Part A services in strategies to improve medical record documentation and decrease the potential for payment errors through appropriate claims completion. Although the payment error rates by state (and dollars paid in error) have decreased significantly, opportunities for improvement remain as demonstrated in this study of nine hospitals with a high proportion of short-term admissions over time. Previous studies by the Quality Improvement Organization had focused on inpatient stays of 1 day or less, a primary target due to the large amount of Medicare dollars spent on these admissions. Random review of Louisiana Medicare admissions revealed persistent medical record documentation and process issues regardless of length of stay as well as the opportunity for significant future savings to the Medicare Trust Fund. The purpose of this study was to determine whether opportunities for improvement in reduction of payment error continue to exist for inpatient admissions of greater than 1 day, despite focused education provided by Louisiana Health Care Review, the Louisiana Medicare Quality Improvement Organization, from 1999 to 2005, and to work individually with the nine selected hospitals to assist them in reducing the number of unnecessary short-term admissions and billing errors in each hospital by a minimum of 50% by the end of the study period. Inpatient Short-Term Acute Care Hospitals. A sample of claims for short-term stays (defined as an inpatient admission with a length of stay of 3 days or less excluding deaths, interim bills for those still a patient and those who left against medical advice) occurring during the baseline and remeasurement time frames was examined. The baseline period consisted of 1 month's claims-the complete month just prior to the start of approved project activities. Remeasurement was performed by each hospital and reported to the Quality Improvement Organization on a monthly basis following implementation of the hospital's quality improvement plan. Each hospital was required to provide a monthly remeasurement report by indicator until it had met its stated goal(s) for improvement for 2 consecutive months; therefore, each hospital completed its required monthly reporting for a specific indicator in a different month. Results were calculated for the following indicators: INDICATOR 1: Proportion of unnecessary short-term admissions = number of unnecessary short-term inpatient admissions/total short-term inpatient admissions in time frame. INDICATOR 2: Proportion of errors in billed treatment setting, that is, outpatient observation billed as inpatient = number of errors in billed treatment setting/total short-term admissions in time frame.Six of the 9 hospitals were able to accomplish reduction of their error rates within 6 months from the beginning of the study. The seventh hospital reached its goals in the 7th month, with the 2 remaining hospitals making progress toward their goals by the conclusion of the study. 1 Case managers must be up-to-date with payor requirements regarding medical record documentation for medical necessity of services and timing of inpatient admission, e.g., for Medicare, the date and time of the written physician's order for admission to the inpatient care setting is the date and time of inpatient admission. 2 The balancing of clinical decisions and financial considerations required of case managers in hospital settings remains an ongoing challenge. 3 Senior leadership must be engaged in ensuring the success of the case management program by providing the resources required. 4 Managers of case management programs must have in place an effective process to address compliance with changes in federal and state regulations and maintain collaborative relationships with senior leaders responsible for clinical, financial, and strategic plans and goals for the organization. 5 The case management process must include all related services, e.g., admissions, nursing services, health information management, finance/business services, contracting, medical staff, etc.

The Effect of Adenotonsillectomy for Childhood Sleep Apnea on Cardiometabolic Measures.

PubMed

Quante, Mirja; Wang, Rui; Weng, Jia; Rosen, Carol L; Amin, Raouf; Garetz, Susan L; Katz, Eliot; Paruthi, Shalini; Arens, Raanan; Muzumdar, Hiren; Marcus, Carole L; Ellenberg, Susan; Redline, Susan

2015-09-01

Obstructive sleep apnea syndrome (OSAS) has been associated with cardiometabolic disease in adults. In children, this association is unclear. We evaluated the effect of early adenotonsillectomy (eAT) for treatment of OSAS on blood pressure, heart rate, lipids, glucose, insulin, and C-reactive protein. We also analyzed whether these parameters at baseline and changes at follow-up correlated with polysomnographic indices. Data collected at baseline and 7-mo follow-up were analyzed from a randomized controlled trial, the Childhood Adenotonsillectomy Trial (CHAT). Clinical referral setting from multiple centers. There were 464 children, ages 5 to 9.9 y with OSAS without severe hypoxemia. Randomization to eAT or Watchful Waiting with Supportive Care (WWSC). There was no significant change of cardiometabolic parameters over the 7-mo interval in the eAT group compared to WWSC group. However, overnight heart rate was incrementally higher in association with baseline OSAS severity (average heart rate increase of 3 beats per minute [bpm] for apnea-hypopnea index [AHI] of 2 versus 10; [standard error = 0.60]). Each 5-unit improvement in AHI and 5 mmHg improvement in peak end-tidal CO2 were estimated to reduce heart rate by 1 and 1.5 bpm, respectively. An increase in N3 sleep also was associated with small reductions in systolic blood pressure percentile. There is little variation in standard cardiometabolic parameters in children with obstructive sleep apnea syndrome (OSAS) but without severe hypoxemia at baseline or after intervention. Of all measures, overnight heart rate emerged as the most sensitive parameter of pediatric OSAS severity. Clinicaltrials.gov (#NCT00560859). © 2015 Associated Professional Sleep Societies, LLC.

Effect of Dynamic Light Application on Cognitive Performance and Well-being of Intensive Care Nurses.

PubMed

Simons, Koen S; Boeijen, Enzio R K; Mertens, Marlies C; Rood, Paul; de Jager, Cornelis P C; van den Boogaard, Mark

2018-05-01

Exposure to bright light has alerting effects. In nurses, alertness may be decreased because of shift work and high work pressure, potentially reducing work performance and increasing the risk for medical errors. To determine whether high-intensity dynamic light improves cognitive performance, self-reported depressive signs and symptoms, fatigue, alertness, and well-being in intensive care unit nurses. In a single-center crossover study in an intensive care unit of a teaching hospital in the Netherlands, 10 registered nurses were randomly divided into 2 groups. Each group worked alternately for 3 to 4 days in patients' rooms with dynamic light and 3 to 4 days in control lighting settings. High-intensity dynamic light was administered through ceiling-mounted fluorescent tubes that delivered bluish white light up to 1700 lux during the daytime, versus 300 lux in control settings. Cognitive performance, self-reported depressive signs and symptoms, fatigue, and well-being before and after each period were assessed by using validated cognitive tests and questionnaires. Cognitive performance, self-reported depressive signs and symptoms, and fatigue did not differ significantly between the 2 light settings. Scores of subjective well-being were significantly lower after a period of working in dynamic light. Daytime lighting conditions did not affect intensive care unit nurses' cognitive performance, perceived depressive signs and symptoms, or fatigue. Perceived quality of life, predominantly in the psychological and environmental domains, was lower for nurses working in dynamic light. © 2018 American Association of Critical-Care Nurses.

Intelligent Predictor of Energy Expenditure with the Use of Patch-Type Sensor Module

PubMed Central

Li, Meina; Kwak, Keun-Chang; Kim, Youn-Tae

2012-01-01

This paper is concerned with an intelligent predictor of energy expenditure (EE) using a developed patch-type sensor module for wireless monitoring of heart rate (HR) and movement index (MI). For this purpose, an intelligent predictor is designed by an advanced linguistic model (LM) with interval prediction based on fuzzy granulation that can be realized by context-based fuzzy c-means (CFCM) clustering. The system components consist of a sensor board, the rubber case, and the communication module with built-in analysis algorithm. This sensor is patched onto the user's chest to obtain physiological data in indoor and outdoor environments. The prediction performance was demonstrated by root mean square error (RMSE). The prediction performance was obtained as the number of contexts and clusters increased from 2 to 6, respectively. Thirty participants were recruited from Chosun University to take part in this study. The data sets were recorded during normal walking, brisk walking, slow running, and jogging in an outdoor environment and treadmill running in an indoor environment, respectively. We randomly divided the data set into training (60%) and test data set (40%) in the normalized space during 10 iterations. The training data set is used for model construction, while the test set is used for model validation. The experimental results revealed that the prediction error on treadmill running simulation was improved by about 51% and 12% in comparison to conventional LM for training and checking data set, respectively. PMID:23202166

Logistic random effects regression models: a comparison of statistical packages for binary and ordinal outcomes

PubMed Central

2011-01-01

Background Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. Methods We used individual patient data from 8509 patients in 231 centers with moderate and severe Traumatic Brain Injury (TBI) enrolled in eight Randomized Controlled Trials (RCTs) and three observational studies. We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS) as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. We then compared the implementations of frequentist and Bayesian methods to estimate the fixed and random effects. Frequentist approaches included R (lme4), Stata (GLLAMM), SAS (GLIMMIX and NLMIXED), MLwiN ([R]IGLS) and MIXOR, Bayesian approaches included WinBUGS, MLwiN (MCMC), R package MCMCglmm and SAS experimental procedure MCMC. Three data sets (the full data set and two sub-datasets) were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. For the ordinal outcome in the full data set also a proportional odds model with a random center effect was fitted. Results The packages gave similar parameter estimates for both the fixed and random effects and for the binary (and ordinal) models for the main study and when based on a relatively large number of level-1 (patient level) data compared to the number of level-2 (hospital level) data. However, when based on relatively sparse data set, i.e. when the numbers of level-1 and level-2 data units were about the same, the frequentist and Bayesian approaches showed somewhat different results. The software implementations differ considerably in flexibility, computation time, and usability. There are also differences in the availability of additional tools for model evaluation, such as diagnostic plots. The experimental SAS (version 9.2) procedure MCMC appeared to be inefficient. Conclusions On relatively large data sets, the different software implementations of logistic random effects regression models produced similar results. Thus, for a large data set there seems to be no explicit preference (of course if there is no preference from a philosophical point of view) for either a frequentist or Bayesian approach (if based on vague priors). The choice for a particular implementation may largely depend on the desired flexibility, and the usability of the package. For small data sets the random effects variances are difficult to estimate. In the frequentist approaches the MLE of this variance was often estimated zero with a standard error that is either zero or could not be determined, while for Bayesian methods the estimates could depend on the chosen "non-informative" prior of the variance parameter. The starting value for the variance parameter may be also critical for the convergence of the Markov chain. PMID:21605357

Structured Set Intra Prediction With Discriminative Learning in a Max-Margin Markov Network for High Efficiency Video Coding

PubMed Central

Dai, Wenrui; Xiong, Hongkai; Jiang, Xiaoqian; Chen, Chang Wen

2014-01-01

This paper proposes a novel model on intra coding for High Efficiency Video Coding (HEVC), which simultaneously predicts blocks of pixels with optimal rate distortion. It utilizes the spatial statistical correlation for the optimal prediction based on 2-D contexts, in addition to formulating the data-driven structural interdependences to make the prediction error coherent with the probability distribution, which is desirable for successful transform and coding. The structured set prediction model incorporates a max-margin Markov network (M3N) to regulate and optimize multiple block predictions. The model parameters are learned by discriminating the actual pixel value from other possible estimates to maximize the margin (i.e., decision boundary bandwidth). Compared to existing methods that focus on minimizing prediction error, the M3N-based model adaptively maintains the coherence for a set of predictions. Specifically, the proposed model concurrently optimizes a set of predictions by associating the loss for individual blocks to the joint distribution of succeeding discrete cosine transform coefficients. When the sample size grows, the prediction error is asymptotically upper bounded by the training error under the decomposable loss function. As an internal step, we optimize the underlying Markov network structure to find states that achieve the maximal energy using expectation propagation. For validation, we integrate the proposed model into HEVC for optimal mode selection on rate-distortion optimization. The proposed prediction model obtains up to 2.85% bit rate reduction and achieves better visual quality in comparison to the HEVC intra coding. PMID:25505829

Evaluation of malaria rapid diagnostic test (RDT) use by community health workers: a longitudinal study in western Kenya.

PubMed

Boyce, Matthew R; Menya, Diana; Turner, Elizabeth L; Laktabai, Jeremiah; Prudhomme-O'Meara, Wendy

2018-05-18

Malaria rapid diagnostic tests (RDTs) are a simple, point-of-care technology that can improve the diagnosis and subsequent treatment of malaria. They are an increasingly common diagnostic tool, but concerns remain about their use by community health workers (CHWs). These concerns regard the long-term trends relating to infection prevention measures, the interpretation of test results and adherence to treatment protocols. This study assessed whether CHWs maintained their competency at conducting RDTs over a 12-month timeframe, and if this competency varied with specific CHW characteristics. From June to September, 2015, CHWs (n = 271) were trained to conduct RDTs using a 3-day validated curriculum and a baseline assessment was completed. Between June and August, 2016, CHWs (n = 105) were randomly selected and recruited for follow-up assessments using a 20-step checklist that classified steps as relating to safety, accuracy, and treatment; 103 CHWs participated in follow-up assessments. Poisson regressions were used to test for associations between error count data at follow-up and Poisson regression models fit using generalized estimating equations were used to compare data across time-points. At both baseline and follow-up observations, at least 80% of CHWs correctly completed 17 of the 20 steps. CHWs being 50 years of age or older was associated with increased total errors and safety errors at baseline and follow-up. At follow-up, prior experience conducting RDTs was associated with fewer errors. Performance, as it related to the correct completion of all checklist steps and safety steps, did not decline over the 12 months and performance of accuracy steps improved (mean error ratio: 0.51; 95% CI 0.40-0.63). Visual interpretation of RDT results yielded a CHW sensitivity of 92.0% and a specificity of 97.3% when compared to interpretation by the research team. None of the characteristics investigated was found to be significantly associated with RDT interpretation. With training, most CHWs performing RDTs maintain diagnostic testing competency over at least 12 months. CHWs generally perform RDTs safely and accurately interpret results. Younger age and prior experiences with RDTs were associated with better testing performance. Future research should investigate the mode by which CHW characteristics impact RDT procedures.

Inversion of surface parameters using fast learning neural networks

NASA Technical Reports Server (NTRS)

Dawson, M. S.; Olvera, J.; Fung, A. K.; Manry, M. T.

1992-01-01

A neural network approach to the inversion of surface scattering parameters is presented. Simulated data sets based on a surface scattering model are used so that the data may be viewed as taken from a completely known randomly rough surface. The fast learning (FL) neural network and a multilayer perceptron (MLP) trained with backpropagation learning (BP network) are tested on the simulated backscattering data. The RMS error of training the FL network is found to be less than one half the error of the BP network while requiring one to two orders of magnitude less CPU time. When applied to inversion of parameters from a statistically rough surface, the FL method is successful at recovering the surface permittivity, the surface correlation length, and the RMS surface height in less time and with less error than the BP network. Further applications of the FL neural network to the inversion of parameters from backscatter measurements of an inhomogeneous layer above a half space are shown.

Analytical N beam position monitor method

NASA Astrophysics Data System (ADS)

Wegscheider, A.; Langner, A.; Tomás, R.; Franchi, A.

2017-11-01

Measurement and correction of focusing errors is of great importance for performance and machine protection of circular accelerators. Furthermore LHC needs to provide equal luminosities to the experiments ATLAS and CMS. High demands are also set on the speed of the optics commissioning, as the foreseen operation with β*-leveling on luminosity will require many operational optics. A fast measurement of the β -function around a storage ring is usually done by using the measured phase advance between three consecutive beam position monitors (BPMs). A recent extension of this established technique, called the N-BPM method, was successfully applied for optics measurements at CERN, ALBA, and ESRF. We present here an improved algorithm that uses analytical calculations for both random and systematic errors and takes into account the presence of quadrupole, sextupole, and BPM misalignments, in addition to quadrupolar field errors. This new scheme, called the analytical N-BPM method, is much faster, further improves the measurement accuracy, and is applicable to very pushed beam optics where the existing numerical N-BPM method tends to fail.

REGRES: A FORTRAN-77 program to calculate nonparametric and ``structural'' parametric solutions to bivariate regression equations

NASA Astrophysics Data System (ADS)

Rock, N. M. S.; Duffy, T. R.

REGRES allows a range of regression equations to be calculated for paired sets of data values in which both variables are subject to error (i.e. neither is the "independent" variable). Nonparametric regressions, based on medians of all possible pairwise slopes and intercepts, are treated in detail. Estimated slopes and intercepts are output, along with confidence limits, Spearman and Kendall rank correlation coefficients. Outliers can be rejected with user-determined stringency. Parametric regressions can be calculated for any value of λ (the ratio of the variances of the random errors for y and x)—including: (1) major axis ( λ = 1); (2) reduced major axis ( λ = variance of y/variance of x); (3) Y on Xλ = infinity; or (4) X on Y ( λ = 0) solutions. Pearson linear correlation coefficients also are output. REGRES provides an alternative to conventional isochron assessment techniques where bivariate normal errors cannot be assumed, or weighting methods are inappropriate.

Driving Intervention for Returning Combat Veterans.

PubMed

Classen, Sherrilene; Winter, Sandra; Monahan, Miriam; Yarney, Abraham; Link Lutz, Amanda; Platek, Kyle; Levy, Charles

2017-04-01

Increased crash incidence following deployment and veterans' reports of driving difficulty spurred traffic safety research for this population. We conducted an interim analysis on the efficacy of a simulator-based occupational therapy driving intervention (OT-DI) compared with traffic safety education (TSE) in a randomized controlled trial. During baseline and post-testing, OT-Driver Rehabilitation Specialists and one OT-Certified Driver Rehabilitation Specialist measured driving performance errors on a DriveSafety CDS-250 high-fidelity simulator. The intervention group ( n = 13) received three OT-DI sessions addressing driving errors and visual-search retraining. The control group ( n = 13) received three TSE sessions addressing personal factors and defensive driving. Based on Wilcoxon rank-sum analysis, the OT-DI group's errors were significantly reduced when comparing baseline with Post-Test 1 ( p < .0001) and comparing the OT-DI group with the TSE group at Post-Test 1 ( p = .01). These findings provide support for the efficacy of the OT-DI and set the stage for a future effectiveness study.

Software Validation via Model Animation

NASA Technical Reports Server (NTRS)

Dutle, Aaron M.; Munoz, Cesar A.; Narkawicz, Anthony J.; Butler, Ricky W.

2015-01-01

This paper explores a new approach to validating software implementations that have been produced from formally-verified algorithms. Although visual inspection gives some confidence that the implementations faithfully reflect the formal models, it does not provide complete assurance that the software is correct. The proposed approach, which is based on animation of formal specifications, compares the outputs computed by the software implementations on a given suite of input values to the outputs computed by the formal models on the same inputs, and determines if they are equal up to a given tolerance. The approach is illustrated on a prototype air traffic management system that computes simple kinematic trajectories for aircraft. Proofs for the mathematical models of the system's algorithms are carried out in the Prototype Verification System (PVS). The animation tool PVSio is used to evaluate the formal models on a set of randomly generated test cases. Output values computed by PVSio are compared against output values computed by the actual software. This comparison improves the assurance that the translation from formal models to code is faithful and that, for example, floating point errors do not greatly affect correctness and safety properties.

Quantum Optimization of Fully Connected Spin Glasses

NASA Astrophysics Data System (ADS)

Venturelli, Davide; Mandrà, Salvatore; Knysh, Sergey; O'Gorman, Bryan; Biswas, Rupak; Smelyanskiy, Vadim

2015-07-01

Many NP-hard problems can be seen as the task of finding a ground state of a disordered highly connected Ising spin glass. If solutions are sought by means of quantum annealing, it is often necessary to represent those graphs in the annealer's hardware by means of the graph-minor embedding technique, generating a final Hamiltonian consisting of coupled chains of ferromagnetically bound spins, whose binding energy is a free parameter. In order to investigate the effect of embedding on problems of interest, the fully connected Sherrington-Kirkpatrick model with random ±1 couplings is programmed on the D-Wave TwoTM annealer using up to 270 qubits interacting on a Chimera-type graph. We present the best embedding prescriptions for encoding the Sherrington-Kirkpatrick problem in the Chimera graph. The results indicate that the optimal choice of embedding parameters could be associated with the emergence of the spin-glass phase of the embedded problem, whose presence was previously uncertain. This optimal parameter setting allows the performance of the quantum annealer to compete with (and potentially outperform, in the absence of analog control errors) optimized simulated annealing algorithms.

Impact of Uncertainty in the Drop Size Distribution on Oceanic Rainfall Retrievals From Passive Microwave Observations

NASA Technical Reports Server (NTRS)

Wilheit, Thomas T.; Chandrasekar, V.; Li, Wanyu

2007-01-01

The variability of the drop size distribution (DSD) is one of the factors that must be considered in understanding the uncertainties in the retrieval of oceanic precipitation from passive microwave observations. Here, we have used observations from the Precipitation Radar on the Tropical Rainfall Measuring Mission spacecraft to infer the relationship between the DSD and the rain rate and the variability in this relationship. The impact on passive microwave rain rate retrievals varies with the frequency and rain rate. The total uncertainty for a given pixel can be slightly larger than 10% at the low end (ca. 10 GHz) of frequencies commonly used for this purpose and smaller at higher frequencies (up to 37 GHz). Since the error is not totally random, averaging many pixels, as in a monthly rainfall total, should roughly halve this uncertainty. The uncertainty may be lower at rain rates less than about 30 mm/h, but the lack of sensitivity of the surface reference technique to low rain rates makes it impossible to tell from the present data set.

Empirical constrained Bayes predictors accounting for non-detects among repeated measures.

PubMed

Moore, Reneé H; Lyles, Robert H; Manatunga, Amita K

2010-11-10

When the prediction of subject-specific random effects is of interest, constrained Bayes predictors (CB) have been shown to reduce the shrinkage of the widely accepted Bayes predictor while still maintaining desirable properties, such as optimizing mean-square error subsequent to matching the first two moments of the random effects of interest. However, occupational exposure and other epidemiologic (e.g. HIV) studies often present a further challenge because data may fall below the measuring instrument's limit of detection. Although methodology exists in the literature to compute Bayes estimates in the presence of non-detects (Bayes(ND)), CB methodology has not been proposed in this setting. By combining methodologies for computing CBs and Bayes(ND), we introduce two novel CBs that accommodate an arbitrary number of observable and non-detectable measurements per subject. Based on application to real data sets (e.g. occupational exposure, HIV RNA) and simulation studies, these CB predictors are markedly superior to the Bayes predictor and to alternative predictors computed using ad hoc methods in terms of meeting the goal of matching the first two moments of the true random effects distribution. Copyright © 2010 John Wiley & Sons, Ltd.

Gossip and Distributed Kalman Filtering: Weak Consensus Under Weak Detectability

NASA Astrophysics Data System (ADS)

Kar, Soummya; Moura, José M. F.

2011-04-01

The paper presents the gossip interactive Kalman filter (GIKF) for distributed Kalman filtering for networked systems and sensor networks, where inter-sensor communication and observations occur at the same time-scale. The communication among sensors is random; each sensor occasionally exchanges its filtering state information with a neighbor depending on the availability of the appropriate network link. We show that under a weak distributed detectability condition: 1. the GIKF error process remains stochastically bounded, irrespective of the instability properties of the random process dynamics; and 2. the network achieves \\emph{weak consensus}, i.e., the conditional estimation error covariance at a (uniformly) randomly selected sensor converges in distribution to a unique invariant measure on the space of positive semi-definite matrices (independent of the initial state.) To prove these results, we interpret the filtered states (estimates and error covariances) at each node in the GIKF as stochastic particles with local interactions. We analyze the asymptotic properties of the error process by studying as a random dynamical system the associated switched (random) Riccati equation, the switching being dictated by a non-stationary Markov chain on the network graph.

An example of complex modelling in dentistry using Markov chain Monte Carlo (MCMC) simulation.

PubMed

Helfenstein, Ulrich; Menghini, Giorgio; Steiner, Marcel; Murati, Francesca

2002-09-01

In the usual regression setting one regression line is computed for a whole data set. In a more complex situation, each person may be observed for example at several points in time and thus a regression line might be calculated for each person. Additional complexities, such as various forms of errors in covariables may make a straightforward statistical evaluation difficult or even impossible. During recent years methods have been developed allowing convenient analysis of problems where the data and the corresponding models show these and many other forms of complexity. The methodology makes use of a Bayesian approach and Markov chain Monte Carlo (MCMC) simulations. The methods allow the construction of increasingly elaborate models by building them up from local sub-models. The essential structure of the models can be represented visually by directed acyclic graphs (DAG). This attractive property allows communication and discussion of the essential structure and the substantial meaning of a complex model without needing algebra. After presentation of the statistical methods an example from dentistry is presented in order to demonstrate their application and use. The dataset of the example had a complex structure; each of a set of children was followed up over several years. The number of new fillings in permanent teeth had been recorded at several ages. The dependent variables were markedly different from the normal distribution and could not be transformed to normality. In addition, explanatory variables were assumed to be measured with different forms of error. Illustration of how the corresponding models can be estimated conveniently via MCMC simulation, in particular, 'Gibbs sampling', using the freely available software BUGS is presented. In addition, how the measurement error may influence the estimates of the corresponding coefficients is explored. It is demonstrated that the effect of the independent variable on the dependent variable may be markedly underestimated if the measurement error is not taken into account ('regression dilution bias'). Markov chain Monte Carlo methods may be of great value to dentists in allowing analysis of data sets which exhibit a wide range of different forms of complexity.

What errors do peer reviewers detect, and does training improve their ability to detect them?

PubMed

Schroter, Sara; Black, Nick; Evans, Stephen; Godlee, Fiona; Osorio, Lyda; Smith, Richard

2008-10-01

To analyse data from a trial and report the frequencies with which major and minor errors are detected at a general medical journal, the types of errors missed and the impact of training on error detection. 607 peer reviewers at the BMJ were randomized to two intervention groups receiving different types of training (face-to-face training or a self-taught package) and a control group. Each reviewer was sent the same three test papers over the study period, each of which had nine major and five minor methodological errors inserted. BMJ peer reviewers. The quality of review, assessed using a validated instrument, and the number and type of errors detected before and after training. The number of major errors detected varied over the three papers. The interventions had small effects. At baseline (Paper 1) reviewers found an average of 2.58 of the nine major errors, with no notable difference between the groups. The mean number of errors reported was similar for the second and third papers, 2.71 and 3.0, respectively. Biased randomization was the error detected most frequently in all three papers, with over 60% of reviewers rejecting the papers identifying this error. Reviewers who did not reject the papers found fewer errors and the proportion finding biased randomization was less than 40% for each paper. Editors should not assume that reviewers will detect most major errors, particularly those concerned with the context of study. Short training packages have only a slight impact on improving error detection.

Robust prediction of three-dimensional spinal curve from back surface for non-invasive follow-up of scoliosis

NASA Astrophysics Data System (ADS)

Bergeron, Charles; Labelle, Hubert; Ronsky, Janet; Zernicke, Ronald

2005-04-01

Spinal curvature progression in scoliosis patients is monitored from X-rays, and this serial exposure to harmful radiation increases the incidence of developing cancer. With the aim of reducing the invasiveness of follow-up, this study seeks to relate the three-dimensional external surface to the internal geometry, having assumed that that the physiological links between these are sufficiently regular across patients. A database was used of 194 quasi-simultaneous acquisitions of two X-rays and a 3D laser scan of the entire trunk. Data was processed to sets of datapoints representing the trunk surface and spinal curve. Functional data analyses were performed using generalized Fourier series using a Haar basis and functional minimum noise fractions. The resulting coefficients became inputs and outputs, respectively, to an array of support vector regression (SVR) machines. SVR parameters were set based on theoretical results, and cross-validation increased confidence in the system's performance. Predicted lateral and frontal views of the spinal curve from the back surface demonstrated average L2-errors of 6.13 and 4.38 millimetres, respectively, across the test set; these compared favourably with measurement error in data. This constitutes a first robust prediction of the 3D spinal curve from external data using learning techniques.

An analytic technique for statistically modeling random atomic clock errors in estimation

NASA Technical Reports Server (NTRS)

Fell, P. J.

1981-01-01

Minimum variance estimation requires that the statistics of random observation errors be modeled properly. If measurements are derived through the use of atomic frequency standards, then one source of error affecting the observable is random fluctuation in frequency. This is the case, for example, with range and integrated Doppler measurements from satellites of the Global Positioning and baseline determination for geodynamic applications. An analytic method is presented which approximates the statistics of this random process. The procedure starts with a model of the Allan variance for a particular oscillator and develops the statistics of range and integrated Doppler measurements. A series of five first order Markov processes is used to approximate the power spectral density obtained from the Allan variance.

Construction and application of a new dual-hybrid random phase approximation.

PubMed

Mezei, Pál D; Csonka, Gábor I; Ruzsinszky, Adrienn; Kállay, Mihály

2015-10-13

The direct random phase approximation (dRPA) combined with Kohn-Sham reference orbitals is among the most promising tools in computational chemistry and applicable in many areas of chemistry and physics. The reason for this is that it scales as N(4) with the system size, which is a considerable advantage over the accurate ab initio wave function methods like standard coupled-cluster. dRPA also yields a considerably more accurate description of thermodynamic and electronic properties than standard density-functional theory methods. It is also able to describe strong static electron correlation effects even in large systems with a small or vanishing band gap missed by common single-reference methods. However, dRPA has several flaws due to its self-correlation error. In order to obtain accurate and precise reaction energies, barriers and noncovalent intra- and intermolecular interactions, we construct a new dual-hybrid dRPA (hybridization of exact and semilocal exchange in both the energy and the orbitals) and test the performance of this new functional on isogyric, isodesmic, hypohomodesmotic, homodesmotic, and hyperhomodesmotic reaction classes. We also use a test set of 14 Diels-Alder reactions, six atomization energies (AE6), 38 hydrocarbon atomization energies, and 100 reaction barrier heights (DBH24, HT-BH38, and NHT-BH38). For noncovalent complexes, we use the NCCE31 and S22 test sets. To test the intramolecular interactions, we use a set of alkane, cysteine, phenylalanine-glycine-glycine tripeptide, and monosaccharide conformers. We also discuss the delocalization and static correlation errors. We show that a universally accurate description of chemical properties can be provided by a large, 75% exact exchange mixing both in the calculation of the reference orbitals and the final energy.

Errors in radiation oncology: A study in pathways and dosimetric impact

PubMed Central

Drzymala, Robert E.; Purdy, James A.; Michalski, Jeff

2005-01-01

As complexity for treating patients increases, so does the risk of error. Some publications have suggested that record and verify (R&V) systems may contribute in propagating errors. Direct data transfer has the potential to eliminate most, but not all, errors. And although the dosimetric consequences may be obvious in some cases, a detailed study does not exist. In this effort, we examined potential errors in terms of scenarios, pathways of occurrence, and dosimetry. Our goal was to prioritize error prevention according to likelihood of event and dosimetric impact. For conventional photon treatments, we investigated errors of incorrect source‐to‐surface distance (SSD), energy, omitted wedge (physical, dynamic, or universal) or compensating filter, incorrect wedge or compensating filter orientation, improper rotational rate for arc therapy, and geometrical misses due to incorrect gantry, collimator or table angle, reversed field settings, and setup errors. For electron beam therapy, errors investigated included incorrect energy, incorrect SSD, along with geometric misses. For special procedures we examined errors for total body irradiation (TBI, incorrect field size, dose rate, treatment distance) and LINAC radiosurgery (incorrect collimation setting, incorrect rotational parameters). Likelihood of error was determined and subsequently rated according to our history of detecting such errors. Dosimetric evaluation was conducted by using dosimetric data, treatment plans, or measurements. We found geometric misses to have the highest error probability. They most often occurred due to improper setup via coordinate shift errors or incorrect field shaping. The dosimetric impact is unique for each case and depends on the proportion of fields in error and volume mistreated. These errors were short‐lived due to rapid detection via port films. The most significant dosimetric error was related to a reversed wedge direction. This may occur due to incorrect collimator angle or wedge orientation. For parallel‐opposed 60° wedge fields, this error could be as high as 80% to a point off‐axis. Other examples of dosimetric impact included the following: SSD, ~2%/cm for photons or electrons; photon energy (6 MV vs. 18 MV), on average 16% depending on depth, electron energy, ~0.5cm of depth coverage per MeV (mega‐electron volt). Of these examples, incorrect distances were most likely but rapidly detected by in vivo dosimetry. Errors were categorized by occurrence rate, methods and timing of detection, longevity, and dosimetric impact. Solutions were devised according to these criteria. To date, no one has studied the dosimetric impact of global errors in radiation oncology. Although there is heightened awareness that with increased use of ancillary devices and automation, there must be a parallel increase in quality check systems and processes, errors do and will continue to occur. This study has helped us identify and prioritize potential errors in our clinic according to frequency and dosimetric impact. For example, to reduce the use of an incorrect wedge direction, our clinic employs off‐axis in vivo dosimetry. To avoid a treatment distance setup error, we use both vertical table settings and optical distance indicator (ODI) values to properly set up fields. As R&V systems become more automated, more accurate and efficient data transfer will occur. This will require further analysis. Finally, we have begun examining potential intensity‐modulated radiation therapy (IMRT) errors according to the same criteria. PACS numbers: 87.53.Xd, 87.53.St PMID:16143793

On the multivariate total least-squares approach to empirical coordinate transformations. Three algorithms

NASA Astrophysics Data System (ADS)

Schaffrin, Burkhard; Felus, Yaron A.

2008-06-01

The multivariate total least-squares (MTLS) approach aims at estimating a matrix of parameters, Ξ, from a linear model ( Y- E Y = ( X- E X ) · Ξ) that includes an observation matrix, Y, another observation matrix, X, and matrices of randomly distributed errors, E Y and E X . Two special cases of the MTLS approach include the standard multivariate least-squares approach where only the observation matrix, Y, is perturbed by random errors and, on the other hand, the data least-squares approach where only the coefficient matrix X is affected by random errors. In a previous contribution, the authors derived an iterative algorithm to solve the MTLS problem by using the nonlinear Euler-Lagrange conditions. In this contribution, new lemmas are developed to analyze the iterative algorithm, modify it, and compare it with a new ‘closed form’ solution that is based on the singular-value decomposition. For an application, the total least-squares approach is used to estimate the affine transformation parameters that convert cadastral data from the old to the new Israeli datum. Technical aspects of this approach, such as scaling the data and fixing the columns in the coefficient matrix are investigated. This case study illuminates the issue of “symmetry” in the treatment of two sets of coordinates for identical point fields, a topic that had already been emphasized by Teunissen (1989, Festschrift to Torben Krarup, Geodetic Institute Bull no. 58, Copenhagen, Denmark, pp 335-342). The differences between the standard least-squares and the TLS approach are analyzed in terms of the estimated variance component and a first-order approximation of the dispersion matrix of the estimated parameters.

A study of digital holographic filters generation. Phase 2: Digital data communication system, volume 1

NASA Technical Reports Server (NTRS)

Ingels, F. M.; Mo, C. D.

1978-01-01

An empirical study of the performance of the Viterbi decoders in bursty channels was carried out and an improved algebraic decoder for nonsystematic codes was developed. The hybrid algorithm was simulated for the (2,1), k = 7 code on a computer using 20 channels having various error statistics, ranging from pure random error to pure bursty channels. The hybrid system outperformed both the algebraic and the Viterbi decoders in every case, except the 1% random error channel where the Viterbi decoder had one bit less decoding error.

Error threshold for color codes and random three-body Ising models.

PubMed

Katzgraber, Helmut G; Bombin, H; Martin-Delgado, M A

2009-08-28

We study the error threshold of color codes, a class of topological quantum codes that allow a direct implementation of quantum Clifford gates suitable for entanglement distillation, teleportation, and fault-tolerant quantum computation. We map the error-correction process onto a statistical mechanical random three-body Ising model and study its phase diagram via Monte Carlo simulations. The obtained error threshold of p(c) = 0.109(2) is very close to that of Kitaev's toric code, showing that enhanced computational capabilities do not necessarily imply lower resistance to noise.

Effect of random errors in planar PIV data on pressure estimation in vortex dominated flows

NASA Astrophysics Data System (ADS)

McClure, Jeffrey; Yarusevych, Serhiy

2015-11-01

The sensitivity of pressure estimation techniques from Particle Image Velocimetry (PIV) measurements to random errors in measured velocity data is investigated using the flow over a circular cylinder as a test case. Direct numerical simulations are performed for ReD = 100, 300 and 1575, spanning laminar, transitional, and turbulent wake regimes, respectively. A range of random errors typical for PIV measurements is applied to synthetic PIV data extracted from numerical results. A parametric study is then performed using a number of common pressure estimation techniques. Optimal temporal and spatial resolutions are derived based on the sensitivity of the estimated pressure fields to the simulated random error in velocity measurements, and the results are compared to an optimization model derived from error propagation theory. It is shown that the reductions in spatial and temporal scales at higher Reynolds numbers leads to notable changes in the optimal pressure evaluation parameters. The effect of smaller scale wake structures is also quantified. The errors in the estimated pressure fields are shown to depend significantly on the pressure estimation technique employed. The results are used to provide recommendations for the use of pressure and force estimation techniques from experimental PIV measurements in vortex dominated laminar and turbulent wake flows.

Does user-centred design affect the efficiency, usability and safety of CPOE order sets?

PubMed Central

Chan, Julie; Shojania, Kaveh G; Easty, Anthony C

2011-01-01

Background Application of user-centred design principles to Computerized provider order entry (CPOE) systems may improve task efficiency, usability or safety, but there is limited evaluative research of its impact on CPOE systems. Objective We evaluated the task efficiency, usability, and safety of three order set formats: our hospital's planned CPOE order sets (CPOE Test), computer order sets based on user-centred design principles (User Centred Design), and existing pre-printed paper order sets (Paper). Participants 27staff physicians, residents and medical students. Setting Sunnybrook Health Sciences Centre, an academic hospital in Toronto, Canada. Methods Participants completed four simulated order set tasks with three order set formats (two CPOE Test tasks, one User Centred Design, and one Paper). Order of presentation of order set formats and tasks was randomized. Users received individual training for the CPOE Test format only. Main Measures Completion time (efficiency), requests for assistance (usability), and errors in the submitted orders (safety). Results 27 study participants completed 108 order sets. Mean task times were: User Centred Design format 273 s, Paper format 293 s (p=0.73 compared to UCD format), and CPOE Test format 637 s (p<0.0001 compared to UCD format). Users requested assistance in 31% of the CPOE Test format tasks, whereas no assistance was needed for the other formats (p<0.01). There were no significant differences in number of errors between formats. Conclusions The User Centred Design format was more efficient and usable than the CPOE Test format even though training was provided for the latter. We conclude that application of user-centred design principles can enhance task efficiency and usability, increasing the likelihood of successful implementation. PMID:21486886

Neural Network Burst Pressure Prediction in Graphite/Epoxy Pressure Vessels from Acoustic Emission Amplitude Data

NASA Technical Reports Server (NTRS)

Hill, Eric v. K.; Walker, James L., II; Rowell, Ginger H.

1995-01-01

Acoustic emission (AE) data were taken during hydroproof for three sets of ASTM standard 5.75 inch diameter filament wound graphite/epoxy bottles. All three sets of bottles had the same design and were wound from the same graphite fiber; the only difference was in the epoxies used. Two of the epoxies had similar mechanical properties, and because the acoustic properties of materials are a function of their stiffnesses, it was thought that the AE data from the two sets might also be similar; however, this was not the case. Therefore, the three resin types were categorized using dummy variables, which allowed the prediction of burst pressures all three sets of bottles using a single neural network. Three bottles from each set were used to train the network. The resin category, the AE amplitude distribution data taken up to 25 % of the expected burst pressure, and the actual burst pressures were used as inputs. Architecturally, the network consisted of a forty-three neuron input layer (a single categorical variable defining the resin type plus forty-two continuous variables for the AE amplitude frequencies), a fifteen neuron hidden layer for mapping, and a single output neuron for burst pressure prediction. The network trained on all three bottle sets was able to predict burst pressures in the remaining bottles with a worst case error of + 6.59%, slightly greater than the desired goal of + 5%. This larger than desired error was due to poor resolution in the amplitude data for the third bottle set. When the third set of bottles was eliminated from consideration, only four hidden layer neurons were necessary to generate a worst case prediction error of - 3.43%, well within the desired goal.

WE-AB-207A-04: Random Undersampled Cone Beam CT: Theoretical Analysis and a Novel Reconstruction Method

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

Shen, C; Chen, L; Jia, X

2016-06-15

Purpose: Reducing x-ray exposure and speeding up data acquisition motived studies on projection data undersampling. It is an important question that for a given undersampling ratio, what the optimal undersampling approach is. In this study, we propose a new undersampling scheme: random-ray undersampling. We will mathematically analyze its projection matrix properties and demonstrate its advantages. We will also propose a new reconstruction method that simultaneously performs CT image reconstruction and projection domain data restoration. Methods: By representing projection operator under the basis of singular vectors of full projection operator, matrix representations for an undersampling case can be generated and numericalmore » singular value decomposition can be performed. We compared properties of matrices among three undersampling approaches: regular-view undersampling, regular-ray undersampling, and the proposed random-ray undersampling. To accomplish CT reconstruction for random undersampling, we developed a novel method that iteratively performs CT reconstruction and missing projection data restoration via regularization approaches. Results: For a given undersampling ratio, random-ray undersampling preserved mathematical properties of full projection operator better than the other two approaches. This translates to advantages of reconstructing CT images at lower errors. Different types of image artifacts were observed depending on undersampling strategies, which were ascribed to the unique singular vectors of the sampling operators in the image domain. We tested the proposed reconstruction algorithm on a Forbid phantom with only 30% of the projection data randomly acquired. Reconstructed image error was reduced from 9.4% in a TV method to 7.6% in the proposed method. Conclusion: The proposed random-ray undersampling is mathematically advantageous over other typical undersampling approaches. It may permit better image reconstruction at the same undersampling ratio. The novel algorithm suitable for this random-ray undersampling was able to reconstruct high-quality images.« less

Using computational modeling of river flow with remotely sensed data to infer channel bathymetry

USGS Publications Warehouse

Nelson, Jonathan M.; McDonald, Richard R.; Kinzel, Paul J.; Shimizu, Y.

2012-01-01

As part of an ongoing investigation into the use of computational river flow and morphodynamic models for the purpose of correcting and extending remotely sensed river datasets, a simple method for inferring channel bathymetry is developed and discussed. The method is based on an inversion of the equations expressing conservation of mass and momentum to develop equations that can be solved for depth given known values of vertically-averaged velocity and water-surface elevation. The ultimate goal of this work is to combine imperfect remotely sensed data on river planform, water-surface elevation and water-surface velocity in order to estimate depth and other physical parameters of river channels. In this paper, the technique is examined using synthetic data sets that are developed directly from the application of forward two-and three-dimensional flow models. These data sets are constrained to satisfy conservation of mass and momentum, unlike typical remotely sensed field data sets. This provides a better understanding of the process and also allows assessment of how simple inaccuracies in remotely sensed estimates might propagate into depth estimates. The technique is applied to three simple cases: First, depth is extracted from a synthetic dataset of vertically averaged velocity and water-surface elevation; second, depth is extracted from the same data set but with a normally-distributed random error added to the water-surface elevation; third, depth is extracted from a synthetic data set for the same river reach using computed water-surface velocities (in place of depth-integrated values) and water-surface elevations. In each case, the extracted depths are compared to the actual measured depths used to construct the synthetic data sets (with two- and three-dimensional flow models). Errors in water-surface elevation and velocity that are very small degrade depth estimates and cannot be recovered. Errors in depth estimates associated with assuming water-surface velocities equal to depth-integrated velocities are substantial, but can be reduced with simple corrections.

Random Measurement Error as a Source of Discrepancies between the Reports of Wives and Husbands Concerning Marital Power and Task Allocation.

ERIC Educational Resources Information Center

Quarm, Daisy

1981-01-01

Findings for couples (N=119) show wife's work, money, and spare time low between-spouse correlations are due in part to random measurement error. Suggests that increasing reliability of measures by creating multi-item indices can also increase correlations. Car purchase, vacation, and child discipline were not accounted for by random measurement…

Distinguishing Error from Chaos in Ecological Time Series

NASA Astrophysics Data System (ADS)

Sugihara, George; Grenfell, Bryan; May, Robert M.

1990-11-01

Over the years, there has been much discussion about the relative importance of environmental and biological factors in regulating natural populations. Often it is thought that environmental factors are associated with stochastic fluctuations in population density, and biological ones with deterministic regulation. We revisit these ideas in the light of recent work on chaos and nonlinear systems. We show that completely deterministic regulatory factors can lead to apparently random fluctuations in population density, and we then develop a new method (that can be applied to limited data sets) to make practical distinctions between apparently noisy dynamics produced by low-dimensional chaos and population variation that in fact derives from random (high-dimensional)noise, such as environmental stochasticity or sampling error. To show its practical use, the method is first applied to models where the dynamics are known. We then apply the method to several sets of real data, including newly analysed data on the incidence of measles in the United Kingdom. Here the additional problems of secular trends and spatial effects are explored. In particular, we find that on a city-by-city scale measles exhibits low-dimensional chaos (as has previously been found for measles in New York City), whereas on a larger, country-wide scale the dynamics appear as a noisy two-year cycle. In addition to shedding light on the basic dynamics of some nonlinear biological systems, this work dramatizes how the scale on which data is collected and analysed can affect the conclusions drawn.

To image analysis in computed tomography

NASA Astrophysics Data System (ADS)

Chukalina, Marina; Nikolaev, Dmitry; Ingacheva, Anastasia; Buzmakov, Alexey; Yakimchuk, Ivan; Asadchikov, Victor

2017-03-01

The presence of errors in tomographic image may lead to misdiagnosis when computed tomography (CT) is used in medicine, or the wrong decision about parameters of technological processes when CT is used in the industrial applications. Two main reasons produce these errors. First, the errors occur on the step corresponding to the measurement, e.g. incorrect calibration and estimation of geometric parameters of the set-up. The second reason is the nature of the tomography reconstruction step. At the stage a mathematical model to calculate the projection data is created. Applied optimization and regularization methods along with their numerical implementations of the method chosen have their own specific errors. Nowadays, a lot of research teams try to analyze these errors and construct the relations between error sources. In this paper, we do not analyze the nature of the final error, but present a new approach for the calculation of its distribution in the reconstructed volume. We hope that the visualization of the error distribution will allow experts to clarify the medical report impression or expert summary given by them after analyzing of CT results. To illustrate the efficiency of the proposed approach we present both the simulation and real data processing results.

Identification and estimation of survivor average causal effects.

PubMed

Tchetgen Tchetgen, Eric J

2014-09-20

In longitudinal studies, outcomes ascertained at follow-up are typically undefined for individuals who die prior to the follow-up visit. In such settings, outcomes are said to be truncated by death and inference about the effects of a point treatment or exposure, restricted to individuals alive at the follow-up visit, could be biased even if as in experimental studies, treatment assignment were randomized. To account for truncation by death, the survivor average causal effect (SACE) defines the effect of treatment on the outcome for the subset of individuals who would have survived regardless of exposure status. In this paper, the author nonparametrically identifies SACE by leveraging post-exposure longitudinal correlates of survival and outcome that may also mediate the exposure effects on survival and outcome. Nonparametric identification is achieved by supposing that the longitudinal data arise from a certain nonparametric structural equations model and by making the monotonicity assumption that the effect of exposure on survival agrees in its direction across individuals. A novel weighted analysis involving a consistent estimate of the survival process is shown to produce consistent estimates of SACE. A data illustration is given, and the methods are extended to the context of time-varying exposures. We discuss a sensitivity analysis framework that relaxes assumptions about independent errors in the nonparametric structural equations model and may be used to assess the extent to which inference may be altered by a violation of key identifying assumptions. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd.

Identification and estimation of survivor average causal effects

PubMed Central

Tchetgen, Eric J Tchetgen

2014-01-01

In longitudinal studies, outcomes ascertained at follow-up are typically undefined for individuals who die prior to the follow-up visit. In such settings, outcomes are said to be truncated by death and inference about the effects of a point treatment or exposure, restricted to individuals alive at the follow-up visit, could be biased even if as in experimental studies, treatment assignment were randomized. To account for truncation by death, the survivor average causal effect (SACE) defines the effect of treatment on the outcome for the subset of individuals who would have survived regardless of exposure status. In this paper, the author nonparametrically identifies SACE by leveraging post-exposure longitudinal correlates of survival and outcome that may also mediate the exposure effects on survival and outcome. Nonparametric identification is achieved by supposing that the longitudinal data arise from a certain nonparametric structural equations model and by making the monotonicity assumption that the effect of exposure on survival agrees in its direction across individuals. A novel weighted analysis involving a consistent estimate of the survival process is shown to produce consistent estimates of SACE. A data illustration is given, and the methods are extended to the context of time-varying exposures. We discuss a sensitivity analysis framework that relaxes assumptions about independent errors in the nonparametric structural equations model and may be used to assess the extent to which inference may be altered by a violation of key identifying assumptions. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:24889022

Applications of random forest feature selection for fine-scale genetic population assignment.

PubMed

Sylvester, Emma V A; Bentzen, Paul; Bradbury, Ian R; Clément, Marie; Pearce, Jon; Horne, John; Beiko, Robert G

2018-02-01

Genetic population assignment used to inform wildlife management and conservation efforts requires panels of highly informative genetic markers and sensitive assignment tests. We explored the utility of machine-learning algorithms (random forest, regularized random forest and guided regularized random forest) compared with F ST ranking for selection of single nucleotide polymorphisms (SNP) for fine-scale population assignment. We applied these methods to an unpublished SNP data set for Atlantic salmon ( Salmo salar ) and a published SNP data set for Alaskan Chinook salmon ( Oncorhynchus tshawytscha ). In each species, we identified the minimum panel size required to obtain a self-assignment accuracy of at least 90% using each method to create panels of 50-700 markers Panels of SNPs identified using random forest-based methods performed up to 7.8 and 11.2 percentage points better than F ST -selected panels of similar size for the Atlantic salmon and Chinook salmon data, respectively. Self-assignment accuracy ≥90% was obtained with panels of 670 and 384 SNPs for each data set, respectively, a level of accuracy never reached for these species using F ST -selected panels. Our results demonstrate a role for machine-learning approaches in marker selection across large genomic data sets to improve assignment for management and conservation of exploited populations.

Internal consistency tests for evaluation of measurements of anthropogenic hydrocarbons in the troposphere

NASA Astrophysics Data System (ADS)

Parrish, D. D.; Trainer, M.; Young, V.; Goldan, P. D.; Kuster, W. C.; Jobson, B. T.; Fehsenfeld, F. C.; Lonneman, W. A.; Zika, R. D.; Farmer, C. T.; Riemer, D. D.; Rodgers, M. O.

1998-09-01

Measurements of tropospheric nonmethane hydrocarbons (NMHCs) made in continental North America should exhibit a common pattern determined by photochemical removal and dilution acting upon the typical North American urban emissions. We analyze 11 data sets collected in the United States in the context of this hypothesis, in most cases by analyzing the geometric mean and standard deviations of ratios of selected NMHCs. In the analysis we attribute deviations from the common pattern to plausible systematic and random experimental errors. In some cases the errors have been independently verified and the specific causes identified. Thus this common pattern provides a check for internal consistency in NMHC data sets. Specific tests are presented which should provide useful diagnostics for all data sets of anthropogenic NMHC measurements collected in the United States. Similar tests, based upon the perhaps different emission patterns of other regions, presumably could be developed. The specific tests include (1) a lower limit for ethane concentrations, (2) specific NMHCs that should be detected if any are, (3) the relatively constant mean ratios of the longer-lived NMHCs with similar atmospheric lifetimes, (4) the constant relative patterns of families of NMHCs, and (5) limits on the ambient variability of the NMHC ratios. Many experimental problems are identified in the literature and the Southern Oxidant Study data sets. The most important conclusion of this paper is that a rigorous field intercomparison of simultaneous measurements of ambient NMHCs by different techniques and researchers is of crucial importance to the field of atmospheric chemistry. The tests presented here are suggestive of errors but are not definitive; only a field intercomparison can resolve the uncertainties.

Obligation towards medical errors disclosure at a tertiary care hospital in Dubai, UAE

PubMed Central

Zaghloul, Ashraf Ahmad; Rahman, Syed Azizur; Abou El-Enein, Nagwa Younes

2016-01-01

OBJECTIVE: The study aimed to identify healthcare providers’ obligation towards medical errors disclosure as well as to study the association between the severity of the medical error and the intention to disclose the error to the patients and their families. DESIGN: A cross-sectional study design was followed to identify the magnitude of disclosure among healthcare providers in different departments at a randomly selected tertiary care hospital in Dubai. SETTING AND PARTICIPANTS: The total sample size accounted for 106 respondents. Data were collected using a questionnaire composed of two sections namely; demographic variables of the respondents and a section which included variables relevant to medical error disclosure. RESULTS: Statistical analysis yielded significant association between the obligation to disclose medical errors with male healthcare providers (X2 = 5.1), and being a physician (X2 = 19.3). Obligation towards medical errors disclosure was significantly associated with those healthcare providers who had not committed any medical errors during the past year (X2 = 9.8), and any type of medical error regardless the cause, extent of harm (X2 = 8.7). Variables included in the binary logistic regression model were; status (Exp β (Physician) = 0.39, 95% CI 0.16–0.97), gender (Exp β (Male) = 4.81, 95% CI 1.84–12.54), and medical errors during the last year (Exp β (None) = 2.11, 95% CI 0.6–2.3). CONCLUSION: Education and training of physicians about disclosure conversations needs to start as early as medical school. Like the training in other competencies required of physicians, education in communicating about medical errors could help reduce physicians’ apprehension and make them more comfortable with disclosure conversations. PMID:27567766

Modeling Errors in Daily Precipitation Measurements: Additive or Multiplicative?

NASA Technical Reports Server (NTRS)

Tian, Yudong; Huffman, George J.; Adler, Robert F.; Tang, Ling; Sapiano, Matthew; Maggioni, Viviana; Wu, Huan

2013-01-01

The definition and quantification of uncertainty depend on the error model used. For uncertainties in precipitation measurements, two types of error models have been widely adopted: the additive error model and the multiplicative error model. This leads to incompatible specifications of uncertainties and impedes intercomparison and application.In this letter, we assess the suitability of both models for satellite-based daily precipitation measurements in an effort to clarify the uncertainty representation. Three criteria were employed to evaluate the applicability of either model: (1) better separation of the systematic and random errors; (2) applicability to the large range of variability in daily precipitation; and (3) better predictive skills. It is found that the multiplicative error model is a much better choice under all three criteria. It extracted the systematic errors more cleanly, was more consistent with the large variability of precipitation measurements, and produced superior predictions of the error characteristics. The additive error model had several weaknesses, such as non constant variance resulting from systematic errors leaking into random errors, and the lack of prediction capability. Therefore, the multiplicative error model is a better choice.