1983-03-01
AN ANALYSIS OF A FINITE ELEMENT METHOD FOR CONVECTION- DIFFUSION PROBLEMS PART II: A POSTERIORI ERROR ESTIMATES AND ADAPTIVITY by W. G. Szymczak Y 6a...PERIOD COVERED AN ANALYSIS OF A FINITE ELEMENT METHOD FOR final life of the contract CONVECTION- DIFFUSION PROBLEM S. Part II: A POSTERIORI ERROR ...Element Method for Convection- Diffusion Problems. Part II: A Posteriori Error Estimates and Adaptivity W. G. Szvmczak and I. Babu~ka# Laboratory for
Technical Note: Introduction of variance component analysis to setup error analysis in radiotherapy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Matsuo, Yukinori, E-mail: ymatsuo@kuhp.kyoto-u.ac.
Purpose: The purpose of this technical note is to introduce variance component analysis to the estimation of systematic and random components in setup error of radiotherapy. Methods: Balanced data according to the one-factor random effect model were assumed. Results: Analysis-of-variance (ANOVA)-based computation was applied to estimate the values and their confidence intervals (CIs) for systematic and random errors and the population mean of setup errors. The conventional method overestimates systematic error, especially in hypofractionated settings. The CI for systematic error becomes much wider than that for random error. The ANOVA-based estimation can be extended to a multifactor model considering multiplemore » causes of setup errors (e.g., interpatient, interfraction, and intrafraction). Conclusions: Variance component analysis may lead to novel applications to setup error analysis in radiotherapy.« less
Error analysis in stereo vision for location measurement of 3D point
NASA Astrophysics Data System (ADS)
Li, Yunting; Zhang, Jun; Tian, Jinwen
2015-12-01
Location measurement of 3D point in stereo vision is subjected to different sources of uncertainty that propagate to the final result. For current methods of error analysis, most of them are based on ideal intersection model to calculate the uncertainty region of point location via intersecting two fields of view of pixel that may produce loose bounds. Besides, only a few of sources of error such as pixel error or camera position are taken into account in the process of analysis. In this paper we present a straightforward and available method to estimate the location error that is taken most of source of error into account. We summed up and simplified all the input errors to five parameters by rotation transformation. Then we use the fast algorithm of midpoint method to deduce the mathematical relationships between target point and the parameters. Thus, the expectations and covariance matrix of 3D point location would be obtained, which can constitute the uncertainty region of point location. Afterwards, we turned back to the error propagation of the primitive input errors in the stereo system and throughout the whole analysis process from primitive input errors to localization error. Our method has the same level of computational complexity as the state-of-the-art method. Finally, extensive experiments are performed to verify the performance of our methods.
An Error Analysis for the Finite Element Method Applied to Convection Diffusion Problems.
1981-03-01
D TFhG-]NOLOGY k 4b 00 \\" ) ’b Technical Note BN-962 AN ERROR ANALYSIS FOR THE FINITE ELEMENT METHOD APPLIED TO CONVECTION DIFFUSION PROBLEM by I...Babu~ka and W. G. Szym’czak March 1981 V.. UNVI I Of- ’i -S AN ERROR ANALYSIS FOR THE FINITE ELEMENT METHOD P. - 0 w APPLIED TO CONVECTION DIFFUSION ...AOAO98 895 MARYLAND UNIVYCOLLEGE PARK INST FOR PHYSICAL SCIENCE--ETC F/G 12/I AN ERROR ANALYIS FOR THE FINITE ELEMENT METHOD APPLIED TO CONV..ETC (U
NASA Astrophysics Data System (ADS)
Zhang, Fan; Liu, Pinkuan
2018-04-01
In order to improve the inspection precision of the H-drive air-bearing stage for wafer inspection, in this paper the geometric error of the stage is analyzed and compensated. The relationship between the positioning errors and error sources are initially modeled, and seven error components are identified that are closely related to the inspection accuracy. The most effective factor that affects the geometric error is identified by error sensitivity analysis. Then, the Spearman rank correlation method is applied to find the correlation between different error components, aiming at guiding the accuracy design and error compensation of the stage. Finally, different compensation methods, including the three-error curve interpolation method, the polynomial interpolation method, the Chebyshev polynomial interpolation method, and the B-spline interpolation method, are employed within the full range of the stage, and their results are compared. Simulation and experiment show that the B-spline interpolation method based on the error model has better compensation results. In addition, the research result is valuable for promoting wafer inspection accuracy and will greatly benefit the semiconductor industry.
NASA Astrophysics Data System (ADS)
Liu, Xing-fa; Cen, Ming
2007-12-01
Neural Network system error correction method is more precise than lest square system error correction method and spheric harmonics function system error correction method. The accuracy of neural network system error correction method is mainly related to the frame of Neural Network. Analysis and simulation prove that both BP neural network system error correction method and RBF neural network system error correction method have high correction accuracy; it is better to use RBF Network system error correction method than BP Network system error correction method for little studying stylebook considering training rate and neural network scale.
Omorczyk, Jarosław; Nosiadek, Leszek; Ambroży, Tadeusz; Nosiadek, Andrzej
2015-01-01
The main aim of this study was to verify the usefulness of selected simple methods of recording and fast biomechanical analysis performed by judges of artistic gymnastics in assessing a gymnast's movement technique. The study participants comprised six artistic gymnastics judges, who assessed back handsprings using two methods: a real-time observation method and a frame-by-frame video analysis method. They also determined flexion angles of knee and hip joints using the computer program. In the case of the real-time observation method, the judges gave a total of 5.8 error points with an arithmetic mean of 0.16 points for the flexion of the knee joints. In the high-speed video analysis method, the total amounted to 8.6 error points and the mean value amounted to 0.24 error points. For the excessive flexion of hip joints, the sum of the error values was 2.2 error points and the arithmetic mean was 0.06 error points during real-time observation. The sum obtained using frame-by-frame analysis method equaled 10.8 and the mean equaled 0.30 error points. Error values obtained through the frame-by-frame video analysis of movement technique were higher than those obtained through the real-time observation method. The judges were able to indicate the number of the frame in which the maximal joint flexion occurred with good accuracy. Using the real-time observation method as well as the high-speed video analysis performed without determining the exact angle for assessing movement technique were found to be insufficient tools for improving the quality of judging.
Error minimization algorithm for comparative quantitative PCR analysis: Q-Anal.
OConnor, William; Runquist, Elizabeth A
2008-07-01
Current methods for comparative quantitative polymerase chain reaction (qPCR) analysis, the threshold and extrapolation methods, either make assumptions about PCR efficiency that require an arbitrary threshold selection process or extrapolate to estimate relative levels of messenger RNA (mRNA) transcripts. Here we describe an algorithm, Q-Anal, that blends elements from current methods to by-pass assumptions regarding PCR efficiency and improve the threshold selection process to minimize error in comparative qPCR analysis. This algorithm uses iterative linear regression to identify the exponential phase for both target and reference amplicons and then selects, by minimizing linear regression error, a fluorescence threshold where efficiencies for both amplicons have been defined. From this defined fluorescence threshold, cycle time (Ct) and the error for both amplicons are calculated and used to determine the expression ratio. Ratios in complementary DNA (cDNA) dilution assays from qPCR data were analyzed by the Q-Anal method and compared with the threshold method and an extrapolation method. Dilution ratios determined by the Q-Anal and threshold methods were 86 to 118% of the expected cDNA ratios, but relative errors for the Q-Anal method were 4 to 10% in comparison with 4 to 34% for the threshold method. In contrast, ratios determined by an extrapolation method were 32 to 242% of the expected cDNA ratios, with relative errors of 67 to 193%. Q-Anal will be a valuable and quick method for minimizing error in comparative qPCR analysis.
Computational Methods for Structural Mechanics and Dynamics, part 1
NASA Technical Reports Server (NTRS)
Stroud, W. Jefferson (Editor); Housner, Jerrold M. (Editor); Tanner, John A. (Editor); Hayduk, Robert J. (Editor)
1989-01-01
The structural analysis methods research has several goals. One goal is to develop analysis methods that are general. This goal of generality leads naturally to finite-element methods, but the research will also include other structural analysis methods. Another goal is that the methods be amenable to error analysis; that is, given a physical problem and a mathematical model of that problem, an analyst would like to know the probable error in predicting a given response quantity. The ultimate objective is to specify the error tolerances and to use automated logic to adjust the mathematical model or solution strategy to obtain that accuracy. A third goal is to develop structural analysis methods that can exploit parallel processing computers. The structural analysis methods research will focus initially on three types of problems: local/global nonlinear stress analysis, nonlinear transient dynamics, and tire modeling.
Small, J R
1993-01-01
This paper is a study into the effects of experimental error on the estimated values of flux control coefficients obtained using specific inhibitors. Two possible techniques for analysing the experimental data are compared: a simple extrapolation method (the so-called graph method) and a non-linear function fitting method. For these techniques, the sources of systematic errors are identified and the effects of systematic and random errors are quantified, using both statistical analysis and numerical computation. It is shown that the graph method is very sensitive to random errors and, under all conditions studied, that the fitting method, even under conditions where the assumptions underlying the fitted function do not hold, outperformed the graph method. Possible ways of designing experiments to minimize the effects of experimental errors are analysed and discussed. PMID:8257434
Automatic Error Analysis Using Intervals
ERIC Educational Resources Information Center
Rothwell, E. J.; Cloud, M. J.
2012-01-01
A technique for automatic error analysis using interval mathematics is introduced. A comparison to standard error propagation methods shows that in cases involving complicated formulas, the interval approach gives comparable error estimates with much less effort. Several examples are considered, and numerical errors are computed using the INTLAB…
Nonparametric Estimation of Standard Errors in Covariance Analysis Using the Infinitesimal Jackknife
ERIC Educational Resources Information Center
Jennrich, Robert I.
2008-01-01
The infinitesimal jackknife provides a simple general method for estimating standard errors in covariance structure analysis. Beyond its simplicity and generality what makes the infinitesimal jackknife method attractive is that essentially no assumptions are required to produce consistent standard error estimates, not even the requirement that the…
Adjusting for multiple prognostic factors in the analysis of randomised trials
2013-01-01
Background When multiple prognostic factors are adjusted for in the analysis of a randomised trial, it is unclear (1) whether it is necessary to account for each of the strata, formed by all combinations of the prognostic factors (stratified analysis), when randomisation has been balanced within each stratum (stratified randomisation), or whether adjusting for the main effects alone will suffice, and (2) the best method of adjustment in terms of type I error rate and power, irrespective of the randomisation method. Methods We used simulation to (1) determine if a stratified analysis is necessary after stratified randomisation, and (2) to compare different methods of adjustment in terms of power and type I error rate. We considered the following methods of analysis: adjusting for covariates in a regression model, adjusting for each stratum using either fixed or random effects, and Mantel-Haenszel or a stratified Cox model depending on outcome. Results Stratified analysis is required after stratified randomisation to maintain correct type I error rates when (a) there are strong interactions between prognostic factors, and (b) there are approximately equal number of patients in each stratum. However, simulations based on real trial data found that type I error rates were unaffected by the method of analysis (stratified vs unstratified), indicating these conditions were not met in real datasets. Comparison of different analysis methods found that with small sample sizes and a binary or time-to-event outcome, most analysis methods lead to either inflated type I error rates or a reduction in power; the lone exception was a stratified analysis using random effects for strata, which gave nominal type I error rates and adequate power. Conclusions It is unlikely that a stratified analysis is necessary after stratified randomisation except in extreme scenarios. Therefore, the method of analysis (accounting for the strata, or adjusting only for the covariates) will not generally need to depend on the method of randomisation used. Most methods of analysis work well with large sample sizes, however treating strata as random effects should be the analysis method of choice with binary or time-to-event outcomes and a small sample size. PMID:23898993
Doytchev, Doytchin E; Szwillus, Gerd
2009-11-01
Understanding the reasons for incident and accident occurrence is important for an organization's safety. Different methods have been developed to achieve this goal. To better understand the human behaviour in incident occurrence we propose an analysis concept that combines Fault Tree Analysis (FTA) and Task Analysis (TA). The former method identifies the root causes of an accident/incident, while the latter analyses the way people perform the tasks in their work environment and how they interact with machines or colleagues. These methods were complemented with the use of the Human Error Identification in System Tools (HEIST) methodology and the concept of Performance Shaping Factors (PSF) to deepen the insight into the error modes of an operator's behaviour. HEIST shows the external error modes that caused the human error and the factors that prompted the human to err. To show the validity of the approach, a case study at a Bulgarian Hydro power plant was carried out. An incident - the flooding of the plant's basement - was analysed by combining the afore-mentioned methods. The case study shows that Task Analysis in combination with other methods can be applied successfully to human error analysis, revealing details about erroneous actions in a realistic situation.
Liu, Yan; Salvendy, Gavriel
2009-05-01
This paper aims to demonstrate the effects of measurement errors on psychometric measurements in ergonomics studies. A variety of sources can cause random measurement errors in ergonomics studies and these errors can distort virtually every statistic computed and lead investigators to erroneous conclusions. The effects of measurement errors on five most widely used statistical analysis tools have been discussed and illustrated: correlation; ANOVA; linear regression; factor analysis; linear discriminant analysis. It has been shown that measurement errors can greatly attenuate correlations between variables, reduce statistical power of ANOVA, distort (overestimate, underestimate or even change the sign of) regression coefficients, underrate the explanation contributions of the most important factors in factor analysis and depreciate the significance of discriminant function and discrimination abilities of individual variables in discrimination analysis. The discussions will be restricted to subjective scales and survey methods and their reliability estimates. Other methods applied in ergonomics research, such as physical and electrophysiological measurements and chemical and biomedical analysis methods, also have issues of measurement errors, but they are beyond the scope of this paper. As there has been increasing interest in the development and testing of theories in ergonomics research, it has become very important for ergonomics researchers to understand the effects of measurement errors on their experiment results, which the authors believe is very critical to research progress in theory development and cumulative knowledge in the ergonomics field.
Interval sampling methods and measurement error: a computer simulation.
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.
Kinematic Analysis of Speech Sound Sequencing Errors Induced by Delayed Auditory Feedback
Lee, Jackson C.; Mittelman, Talia; Stepp, Cara E.; Bohland, Jason W.
2017-01-01
Purpose Delayed auditory feedback (DAF) causes speakers to become disfluent and make phonological errors. Methods for assessing the kinematics of speech errors are lacking, with most DAF studies relying on auditory perceptual analyses, which may be problematic, as errors judged to be categorical may actually represent blends of sounds or articulatory errors. Method Eight typical speakers produced nonsense syllable sequences under normal and DAF (200 ms). Lip and tongue kinematics were captured with electromagnetic articulography. Time-locked acoustic recordings were transcribed, and the kinematics of utterances with and without perceived errors were analyzed with existing and novel quantitative methods. Results New multivariate measures showed that for 5 participants, kinematic variability for productions perceived to be error free was significantly increased under delay; these results were validated by using the spatiotemporal index measure. Analysis of error trials revealed both typical productions of a nontarget syllable and productions with articulatory kinematics that incorporated aspects of both the target and the perceived utterance. Conclusions This study is among the first to characterize articulatory changes under DAF and provides evidence for different classes of speech errors, which may not be perceptually salient. New methods were developed that may aid visualization and analysis of large kinematic data sets. Supplemental Material https://doi.org/10.23641/asha.5103067 PMID:28655038
Lee, Sheila; McMullen, D.; Brown, G. L.; Stokes, A. R.
1965-01-01
1. A theoretical analysis of the errors in multicomponent spectrophotometric analysis of nucleoside mixtures, by a least-squares procedure, has been made to obtain an expression for the error coefficient, relating the error in calculated concentration to the error in extinction measurements. 2. The error coefficients, which depend only on the `library' of spectra used to fit the experimental curves, have been computed for a number of `libraries' containing the following nucleosides found in s-RNA: adenosine, guanosine, cytidine, uridine, 5-ribosyluracil, 7-methylguanosine, 6-dimethylaminopurine riboside, 6-methylaminopurine riboside and thymine riboside. 3. The error coefficients have been used to determine the best conditions for maximum accuracy in the determination of the compositions of nucleoside mixtures. 4. Experimental determinations of the compositions of nucleoside mixtures have been made and the errors found to be consistent with those predicted by the theoretical analysis. 5. It has been demonstrated that, with certain precautions, the multicomponent spectrophotometric method described is suitable as a basis for automatic nucleotide-composition analysis of oligonucleotides containing nine nucleotides. Used in conjunction with continuous chromatography and flow chemical techniques, this method can be applied to the study of the sequence of s-RNA. PMID:14346087
Analysis of measured data of human body based on error correcting frequency
NASA Astrophysics Data System (ADS)
Jin, Aiyan; Peipei, Gao; Shang, Xiaomei
2014-04-01
Anthropometry is to measure all parts of human body surface, and the measured data is the basis of analysis and study of the human body, establishment and modification of garment size and formulation and implementation of online clothing store. In this paper, several groups of the measured data are gained, and analysis of data error is gotten by analyzing the error frequency and using analysis of variance method in mathematical statistics method. Determination of the measured data accuracy and the difficulty of measured parts of human body, further studies of the causes of data errors, and summarization of the key points to minimize errors possibly are also mentioned in the paper. This paper analyses the measured data based on error frequency, and in a way , it provides certain reference elements to promote the garment industry development.
Kim, Haksoo; Park, Samuel B; Monroe, James I; Traughber, Bryan J; Zheng, Yiran; Lo, Simon S; Yao, Min; Mansur, David; Ellis, Rodney; Machtay, Mitchell; Sohn, Jason W
2015-08-01
This article proposes quantitative analysis tools and digital phantoms to quantify intrinsic errors of deformable image registration (DIR) systems and establish quality assurance (QA) procedures for clinical use of DIR systems utilizing local and global error analysis methods with clinically realistic digital image phantoms. Landmark-based image registration verifications are suitable only for images with significant feature points. To address this shortfall, we adapted a deformation vector field (DVF) comparison approach with new analysis techniques to quantify the results. Digital image phantoms are derived from data sets of actual patient images (a reference image set, R, a test image set, T). Image sets from the same patient taken at different times are registered with deformable methods producing a reference DVFref. Applying DVFref to the original reference image deforms T into a new image R'. The data set, R', T, and DVFref, is from a realistic truth set and therefore can be used to analyze any DIR system and expose intrinsic errors by comparing DVFref and DVFtest. For quantitative error analysis, calculating and delineating differences between DVFs, 2 methods were used, (1) a local error analysis tool that displays deformation error magnitudes with color mapping on each image slice and (2) a global error analysis tool that calculates a deformation error histogram, which describes a cumulative probability function of errors for each anatomical structure. Three digital image phantoms were generated from three patients with a head and neck, a lung and a liver cancer. The DIR QA was evaluated using the case with head and neck. © The Author(s) 2014.
Combined proportional and additive residual error models in population pharmacokinetic modelling.
Proost, Johannes H
2017-11-15
In pharmacokinetic modelling, a combined proportional and additive residual error model is often preferred over a proportional or additive residual error model. Different approaches have been proposed, but a comparison between approaches is still lacking. The theoretical background of the methods is described. Method VAR assumes that the variance of the residual error is the sum of the statistically independent proportional and additive components; this method can be coded in three ways. Method SD assumes that the standard deviation of the residual error is the sum of the proportional and additive components. Using datasets from literature and simulations based on these datasets, the methods are compared using NONMEM. The different coding of methods VAR yield identical results. Using method SD, the values of the parameters describing residual error are lower than for method VAR, but the values of the structural parameters and their inter-individual variability are hardly affected by the choice of the method. Both methods are valid approaches in combined proportional and additive residual error modelling, and selection may be based on OFV. When the result of an analysis is used for simulation purposes, it is essential that the simulation tool uses the same method as used during analysis. Copyright © 2017 Elsevier B.V. All rights reserved.
Error Analysis of p-Version Discontinuous Galerkin Method for Heat Transfer in Built-up Structures
NASA Technical Reports Server (NTRS)
Kaneko, Hideaki; Bey, Kim S.
2004-01-01
The purpose of this paper is to provide an error analysis for the p-version of the discontinuous Galerkin finite element method for heat transfer in built-up structures. As a special case of the results in this paper, a theoretical error estimate for the numerical experiments recently conducted by James Tomey is obtained.
Ménard, Richard; Deshaies-Jacques, Martin; Gasset, Nicolas
2016-09-01
An objective analysis is one of the main components of data assimilation. By combining observations with the output of a predictive model we combine the best features of each source of information: the complete spatial and temporal coverage provided by models, with a close representation of the truth provided by observations. The process of combining observations with a model output is called an analysis. To produce an analysis requires the knowledge of observation and model errors, as well as its spatial correlation. This paper is devoted to the development of methods of estimation of these error variances and the characteristic length-scale of the model error correlation for its operational use in the Canadian objective analysis system. We first argue in favor of using compact support correlation functions, and then introduce three estimation methods: the Hollingsworth-Lönnberg (HL) method in local and global form, the maximum likelihood method (ML), and the [Formula: see text] diagnostic method. We perform one-dimensional (1D) simulation studies where the error variance and true correlation length are known, and perform an estimation of both error variances and correlation length where both are non-uniform. We show that a local version of the HL method can capture accurately the error variances and correlation length at each observation site, provided that spatial variability is not too strong. However, the operational objective analysis requires only a single and globally valid correlation length. We examine whether any statistics of the local HL correlation lengths could be a useful estimate, or whether other global estimation methods such as by the global HL, ML, or [Formula: see text] should be used. We found in both 1D simulation and using real data that the ML method is able to capture physically significant aspects of the correlation length, while most other estimates give unphysical and larger length-scale values. This paper describes a proposed improvement of the objective analysis of surface pollutants at Environment and Climate Change Canada (formerly known as Environment Canada). Objective analyses are essentially surface maps of air pollutants that are obtained by combining observations with an air quality model output, and are thought to provide a complete and more accurate representation of the air quality. The highlight of this study is an analysis of methods to estimate the model (or background) error correlation length-scale. The error statistics are an important and critical component to the analysis scheme.
The Infinitesimal Jackknife with Exploratory Factor Analysis
ERIC Educational Resources Information Center
Zhang, Guangjian; Preacher, Kristopher J.; Jennrich, Robert I.
2012-01-01
The infinitesimal jackknife, a nonparametric method for estimating standard errors, has been used to obtain standard error estimates in covariance structure analysis. In this article, we adapt it for obtaining standard errors for rotated factor loadings and factor correlations in exploratory factor analysis with sample correlation matrices. Both…
Chaudhry, Jehanzeb Hameed; Estep, Don; Tavener, Simon; Carey, Varis; Sandelin, Jeff
2016-01-01
We consider numerical methods for initial value problems that employ a two stage approach consisting of solution on a relatively coarse discretization followed by solution on a relatively fine discretization. Examples include adaptive error control, parallel-in-time solution schemes, and efficient solution of adjoint problems for computing a posteriori error estimates. We describe a general formulation of two stage computations then perform a general a posteriori error analysis based on computable residuals and solution of an adjoint problem. The analysis accommodates various variations in the two stage computation and in formulation of the adjoint problems. We apply the analysis to compute "dual-weighted" a posteriori error estimates, to develop novel algorithms for efficient solution that take into account cancellation of error, and to the Parareal Algorithm. We test the various results using several numerical examples.
Agogo, George O; van der Voet, Hilko; van 't Veer, Pieter; Ferrari, Pietro; Muller, David C; Sánchez-Cantalejo, Emilio; Bamia, Christina; Braaten, Tonje; Knüppel, Sven; Johansson, Ingegerd; van Eeuwijk, Fred A; Boshuizen, Hendriek C
2016-10-13
Measurement error in self-reported dietary intakes is known to bias the association between dietary intake and a health outcome of interest such as risk of a disease. The association can be distorted further by mismeasured confounders, leading to invalid results and conclusions. It is, however, difficult to adjust for the bias in the association when there is no internal validation data. We proposed a method to adjust for the bias in the diet-disease association (hereafter, association), due to measurement error in dietary intake and a mismeasured confounder, when there is no internal validation data. The method combines prior information on the validity of the self-report instrument with the observed data to adjust for the bias in the association. We compared the proposed method with the method that ignores the confounder effect, and with the method that ignores measurement errors completely. We assessed the sensitivity of the estimates to various magnitudes of measurement error, error correlations and uncertainty in the literature-reported validation data. We applied the methods to fruits and vegetables (FV) intakes, cigarette smoking (confounder) and all-cause mortality data from the European Prospective Investigation into Cancer and Nutrition study. Using the proposed method resulted in about four times increase in the strength of association between FV intake and mortality. For weakly correlated errors, measurement error in the confounder minimally affected the hazard ratio estimate for FV intake. The effect was more pronounced for strong error correlations. The proposed method permits sensitivity analysis on measurement error structures and accounts for uncertainties in the reported validity coefficients. The method is useful in assessing the direction and quantifying the magnitude of bias in the association due to measurement errors in the confounders.
Human Error Analysis in a Permit to Work System: A Case Study in a Chemical Plant
Jahangiri, Mehdi; Hoboubi, Naser; Rostamabadi, Akbar; Keshavarzi, Sareh; Hosseini, Ali Akbar
2015-01-01
Background A permit to work (PTW) is a formal written system to control certain types of work which are identified as potentially hazardous. However, human error in PTW processes can lead to an accident. Methods This cross-sectional, descriptive study was conducted to estimate the probability of human errors in PTW processes in a chemical plant in Iran. In the first stage, through interviewing the personnel and studying the procedure in the plant, the PTW process was analyzed using the hierarchical task analysis technique. In doing so, PTW was considered as a goal and detailed tasks to achieve the goal were analyzed. In the next step, the standardized plant analysis risk-human (SPAR-H) reliability analysis method was applied for estimation of human error probability. Results The mean probability of human error in the PTW system was estimated to be 0.11. The highest probability of human error in the PTW process was related to flammable gas testing (50.7%). Conclusion The SPAR-H method applied in this study could analyze and quantify the potential human errors and extract the required measures for reducing the error probabilities in PTW system. Some suggestions to reduce the likelihood of errors, especially in the field of modifying the performance shaping factors and dependencies among tasks are provided. PMID:27014485
Ji, Yue; Xu, Mengjie; Li, Xingfei; Wu, Tengfei; Tuo, Weixiao; Wu, Jun; Dong, Jiuzhi
2018-06-13
The magnetohydrodynamic (MHD) angular rate sensor (ARS) with low noise level in ultra-wide bandwidth is developed in lasing and imaging applications, especially the line-of-sight (LOS) system. A modified MHD ARS combined with the Coriolis effect was studied in this paper to expand the sensor’s bandwidth at low frequency (<1 Hz), which is essential for precision LOS pointing and wide-bandwidth LOS jitter suppression. The model and the simulation method were constructed and a comprehensive solving method based on the magnetic and electric interaction methods was proposed. The numerical results on the Coriolis effect and the frequency response of the modified MHD ARS were detailed. In addition, according to the experimental results of the designed sensor consistent with the simulation results, an error analysis of model errors was discussed. Our study provides an error analysis method of MHD ARS combined with the Coriolis effect and offers a framework for future studies to minimize the error.
Error Analysis in Mathematics. Technical Report #1012
ERIC Educational Resources Information Center
Lai, Cheng-Fei
2012-01-01
Error analysis is a method commonly used to identify the cause of student errors when they make consistent mistakes. It is a process of reviewing a student's work and then looking for patterns of misunderstanding. Errors in mathematics can be factual, procedural, or conceptual, and may occur for a number of reasons. Reasons why students make…
2014-04-01
Barrier methods for critical exponent problems in geometric analysis and mathematical physics, J. Erway and M. Holst, Submitted for publication ...TR-14-33 A Posteriori Error Analysis and Uncertainty Quantification for Adaptive Multiscale Operator Decomposition Methods for Multiphysics...Problems Approved for public release, distribution is unlimited. April 2014 HDTRA1-09-1-0036 Donald Estep and Michael
Application of Exactly Linearized Error Transport Equations to AIAA CFD Prediction Workshops
NASA Technical Reports Server (NTRS)
Derlaga, Joseph M.; Park, Michael A.; Rallabhandi, Sriram
2017-01-01
The computational fluid dynamics (CFD) prediction workshops sponsored by the AIAA have created invaluable opportunities in which to discuss the predictive capabilities of CFD in areas in which it has struggled, e.g., cruise drag, high-lift, and sonic boom pre diction. While there are many factors that contribute to disagreement between simulated and experimental results, such as modeling or discretization error, quantifying the errors contained in a simulation is important for those who make decisions based on the computational results. The linearized error transport equations (ETE) combined with a truncation error estimate is a method to quantify one source of errors. The ETE are implemented with a complex-step method to provide an exact linearization with minimal source code modifications to CFD and multidisciplinary analysis methods. The equivalency of adjoint and linearized ETE functional error correction is demonstrated. Uniformly refined grids from a series of AIAA prediction workshops demonstrate the utility of ETE for multidisciplinary analysis with a connection between estimated discretization error and (resolved or under-resolved) flow features.
Binocular optical axis parallelism detection precision analysis based on Monte Carlo method
NASA Astrophysics Data System (ADS)
Ying, Jiaju; Liu, Bingqi
2018-02-01
According to the working principle of the binocular photoelectric instrument optical axis parallelism digital calibration instrument, and in view of all components of the instrument, the various factors affect the system precision is analyzed, and then precision analysis model is established. Based on the error distribution, Monte Carlo method is used to analyze the relationship between the comprehensive error and the change of the center coordinate of the circle target image. The method can further guide the error distribution, optimize control the factors which have greater influence on the comprehensive error, and improve the measurement accuracy of the optical axis parallelism digital calibration instrument.
Optical System Error Analysis and Calibration Method of High-Accuracy Star Trackers
Sun, Ting; Xing, Fei; You, Zheng
2013-01-01
The star tracker is a high-accuracy attitude measurement device widely used in spacecraft. Its performance depends largely on the precision of the optical system parameters. Therefore, the analysis of the optical system parameter errors and a precise calibration model are crucial to the accuracy of the star tracker. Research in this field is relatively lacking a systematic and universal analysis up to now. This paper proposes in detail an approach for the synthetic error analysis of the star tracker, without the complicated theoretical derivation. This approach can determine the error propagation relationship of the star tracker, and can build intuitively and systematically an error model. The analysis results can be used as a foundation and a guide for the optical design, calibration, and compensation of the star tracker. A calibration experiment is designed and conducted. Excellent calibration results are achieved based on the calibration model. To summarize, the error analysis approach and the calibration method are proved to be adequate and precise, and could provide an important guarantee for the design, manufacture, and measurement of high-accuracy star trackers. PMID:23567527
Kinematic Analysis of Speech Sound Sequencing Errors Induced by Delayed Auditory Feedback.
Cler, Gabriel J; Lee, Jackson C; Mittelman, Talia; Stepp, Cara E; Bohland, Jason W
2017-06-22
Delayed auditory feedback (DAF) causes speakers to become disfluent and make phonological errors. Methods for assessing the kinematics of speech errors are lacking, with most DAF studies relying on auditory perceptual analyses, which may be problematic, as errors judged to be categorical may actually represent blends of sounds or articulatory errors. Eight typical speakers produced nonsense syllable sequences under normal and DAF (200 ms). Lip and tongue kinematics were captured with electromagnetic articulography. Time-locked acoustic recordings were transcribed, and the kinematics of utterances with and without perceived errors were analyzed with existing and novel quantitative methods. New multivariate measures showed that for 5 participants, kinematic variability for productions perceived to be error free was significantly increased under delay; these results were validated by using the spatiotemporal index measure. Analysis of error trials revealed both typical productions of a nontarget syllable and productions with articulatory kinematics that incorporated aspects of both the target and the perceived utterance. This study is among the first to characterize articulatory changes under DAF and provides evidence for different classes of speech errors, which may not be perceptually salient. New methods were developed that may aid visualization and analysis of large kinematic data sets. https://doi.org/10.23641/asha.5103067.
MO-FG-202-06: Improving the Performance of Gamma Analysis QA with Radiomics- Based Image Analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wootton, L; Nyflot, M; Ford, E
2016-06-15
Purpose: The use of gamma analysis for IMRT quality assurance has well-known limitations. Traditionally, a simple thresholding technique is used to evaluated passing criteria. However, like any image the gamma distribution is rich in information which thresholding mostly discards. We therefore propose a novel method of analyzing gamma images that uses quantitative image features borrowed from radiomics, with the goal of improving error detection. Methods: 368 gamma images were generated from 184 clinical IMRT beams. For each beam the dose to a phantom was measured with EPID dosimetry and compared to the TPS dose calculated with and without normally distributedmore » (2mm sigma) errors in MLC positions. The magnitude of 17 intensity histogram and size-zone radiomic features were derived from each image. The features that differed most significantly between image sets were determined with ROC analysis. A linear machine-learning model was trained on these features to classify images as with or without errors on 180 gamma images.The model was then applied to an independent validation set of 188 additional gamma distributions, half with and half without errors. Results: The most significant features for detecting errors were histogram kurtosis (p=0.007) and three size-zone metrics (p<1e-6 for each). The sizezone metrics detected clusters of high gamma-value pixels under mispositioned MLCs. The model applied to the validation set had an AUC of 0.8, compared to 0.56 for traditional gamma analysis with the decision threshold restricted to 98% or less. Conclusion: A radiomics-based image analysis method was developed that is more effective in detecting error than traditional gamma analysis. Though the pilot study here considers only MLC position errors, radiomics-based methods for other error types are being developed, which may provide better error detection and useful information on the source of detected errors. This work was partially supported by a grant from the Agency for Healthcare Research and Quality, grant number R18 HS022244-01.« less
Error analysis and correction of discrete solutions from finite element codes
NASA Technical Reports Server (NTRS)
Thurston, G. A.; Stein, P. A.; Knight, N. F., Jr.; Reissner, J. E.
1984-01-01
Many structures are an assembly of individual shell components. Therefore, results for stresses and deflections from finite element solutions for each shell component should agree with the equations of shell theory. This paper examines the problem of applying shell theory to the error analysis and the correction of finite element results. The general approach to error analysis and correction is discussed first. Relaxation methods are suggested as one approach to correcting finite element results for all or parts of shell structures. Next, the problem of error analysis of plate structures is examined in more detail. The method of successive approximations is adapted to take discrete finite element solutions and to generate continuous approximate solutions for postbuckled plates. Preliminary numerical results are included.
Selective Weighted Least Squares Method for Fourier Transform Infrared Quantitative Analysis.
Wang, Xin; Li, Yan; Wei, Haoyun; Chen, Xia
2017-06-01
Classical least squares (CLS) regression is a popular multivariate statistical method used frequently for quantitative analysis using Fourier transform infrared (FT-IR) spectrometry. Classical least squares provides the best unbiased estimator for uncorrelated residual errors with zero mean and equal variance. However, the noise in FT-IR spectra, which accounts for a large portion of the residual errors, is heteroscedastic. Thus, if this noise with zero mean dominates in the residual errors, the weighted least squares (WLS) regression method described in this paper is a better estimator than CLS. However, if bias errors, such as the residual baseline error, are significant, WLS may perform worse than CLS. In this paper, we compare the effect of noise and bias error in using CLS and WLS in quantitative analysis. Results indicated that for wavenumbers with low absorbance, the bias error significantly affected the error, such that the performance of CLS is better than that of WLS. However, for wavenumbers with high absorbance, the noise significantly affected the error, and WLS proves to be better than CLS. Thus, we propose a selective weighted least squares (SWLS) regression that processes data with different wavenumbers using either CLS or WLS based on a selection criterion, i.e., lower or higher than an absorbance threshold. The effects of various factors on the optimal threshold value (OTV) for SWLS have been studied through numerical simulations. These studies reported that: (1) the concentration and the analyte type had minimal effect on OTV; and (2) the major factor that influences OTV is the ratio between the bias error and the standard deviation of the noise. The last part of this paper is dedicated to quantitative analysis of methane gas spectra, and methane/toluene mixtures gas spectra as measured using FT-IR spectrometry and CLS, WLS, and SWLS. The standard error of prediction (SEP), bias of prediction (bias), and the residual sum of squares of the errors (RSS) from the three quantitative analyses were compared. In methane gas analysis, SWLS yielded the lowest SEP and RSS among the three methods. In methane/toluene mixture gas analysis, a modification of the SWLS has been presented to tackle the bias error from other components. The SWLS without modification presents the lowest SEP in all cases but not bias and RSS. The modification of SWLS reduced the bias, which showed a lower RSS than CLS, especially for small components.
Espino-Hernandez, Gabriela; Gustafson, Paul; Burstyn, Igor
2011-05-14
In epidemiological studies explanatory variables are frequently subject to measurement error. The aim of this paper is to develop a Bayesian method to correct for measurement error in multiple continuous exposures in individually matched case-control studies. This is a topic that has not been widely investigated. The new method is illustrated using data from an individually matched case-control study of the association between thyroid hormone levels during pregnancy and exposure to perfluorinated acids. The objective of the motivating study was to examine the risk of maternal hypothyroxinemia due to exposure to three perfluorinated acids measured on a continuous scale. Results from the proposed method are compared with those obtained from a naive analysis. Using a Bayesian approach, the developed method considers a classical measurement error model for the exposures, as well as the conditional logistic regression likelihood as the disease model, together with a random-effect exposure model. Proper and diffuse prior distributions are assigned, and results from a quality control experiment are used to estimate the perfluorinated acids' measurement error variability. As a result, posterior distributions and 95% credible intervals of the odds ratios are computed. A sensitivity analysis of method's performance in this particular application with different measurement error variability was performed. The proposed Bayesian method to correct for measurement error is feasible and can be implemented using statistical software. For the study on perfluorinated acids, a comparison of the inferences which are corrected for measurement error to those which ignore it indicates that little adjustment is manifested for the level of measurement error actually exhibited in the exposures. Nevertheless, a sensitivity analysis shows that more substantial adjustments arise if larger measurement errors are assumed. In individually matched case-control studies, the use of conditional logistic regression likelihood as a disease model in the presence of measurement error in multiple continuous exposures can be justified by having a random-effect exposure model. The proposed method can be successfully implemented in WinBUGS to correct individually matched case-control studies for several mismeasured continuous exposures under a classical measurement error model.
Error of the slanted edge method for measuring the modulation transfer function of imaging systems.
Xie, Xufen; Fan, Hongda; Wang, Hongyuan; Wang, Zebin; Zou, Nianyu
2018-03-01
The slanted edge method is a basic approach for measuring the modulation transfer function (MTF) of imaging systems; however, its measurement accuracy is limited in practice. Theoretical analysis of the slanted edge MTF measurement method performed in this paper reveals that inappropriate edge angles and random noise reduce this accuracy. The error caused by edge angles is analyzed using sampling and reconstruction theory. Furthermore, an error model combining noise and edge angles is proposed. We verify the analyses and model with respect to (i) the edge angle, (ii) a statistical analysis of the measurement error, (iii) the full width at half-maximum of a point spread function, and (iv) the error model. The experimental results verify the theoretical findings. This research can be referential for applications of the slanted edge MTF measurement method.
Generalized Structured Component Analysis with Uniqueness Terms for Accommodating Measurement Error
Hwang, Heungsun; Takane, Yoshio; Jung, Kwanghee
2017-01-01
Generalized structured component analysis (GSCA) is a component-based approach to structural equation modeling (SEM), where latent variables are approximated by weighted composites of indicators. It has no formal mechanism to incorporate errors in indicators, which in turn renders components prone to the errors as well. We propose to extend GSCA to account for errors in indicators explicitly. This extension, called GSCAM, considers both common and unique parts of indicators, as postulated in common factor analysis, and estimates a weighted composite of indicators with their unique parts removed. Adding such unique parts or uniqueness terms serves to account for measurement errors in indicators in a manner similar to common factor analysis. Simulation studies are conducted to compare parameter recovery of GSCAM and existing methods. These methods are also applied to fit a substantively well-established model to real data. PMID:29270146
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.
A study on characteristics of retrospective optimal interpolation with WRF testbed
NASA Astrophysics Data System (ADS)
Kim, S.; Noh, N.; Lim, G.
2012-12-01
This study presents the application of retrospective optimal interpolation (ROI) with Weather Research and Forecasting model (WRF). Song et al. (2009) suggest ROI method which is an optimal interpolation (OI) that gradually assimilates observations over the analysis window for variance-minimum estimate of an atmospheric state at the initial time of the analysis window. Song and Lim (2011) improve the method by incorporating eigen-decomposition and covariance inflation. ROI method assimilates the data at post analysis time using perturbation method (Errico and Raeder, 1999) without adjoint model. In this study, ROI method is applied to WRF model to validate the algorithm and to investigate the capability. The computational costs for ROI can be reduced due to the eigen-decomposition of background error covariance. Using the background error covariance in eigen-space, 1-profile assimilation experiment is performed. The difference between forecast errors with assimilation and without assimilation is obviously increased as time passed, which means the improvement of forecast error by assimilation. The characteristics and strength/weakness of ROI method are investigated by conducting the experiments with other data assimilation method.
Robust Methods for Moderation Analysis with a Two-Level Regression Model.
Yang, Miao; Yuan, Ke-Hai
2016-01-01
Moderation analysis has many applications in social sciences. Most widely used estimation methods for moderation analysis assume that errors are normally distributed and homoscedastic. When these assumptions are not met, the results from a classical moderation analysis can be misleading. For more reliable moderation analysis, this article proposes two robust methods with a two-level regression model when the predictors do not contain measurement error. One method is based on maximum likelihood with Student's t distribution and the other is based on M-estimators with Huber-type weights. An algorithm for obtaining the robust estimators is developed. Consistent estimates of standard errors of the robust estimators are provided. The robust approaches are compared against normal-distribution-based maximum likelihood (NML) with respect to power and accuracy of parameter estimates through a simulation study. Results show that the robust approaches outperform NML under various distributional conditions. Application of the robust methods is illustrated through a real data example. An R program is developed and documented to facilitate the application of the robust methods.
Error analysis of mechanical system and wavelength calibration of monochromator
NASA Astrophysics Data System (ADS)
Zhang, Fudong; Chen, Chen; Liu, Jie; Wang, Zhihong
2018-02-01
This study focuses on improving the accuracy of a grating monochromator on the basis of the grating diffraction equation in combination with an analysis of the mechanical transmission relationship between the grating, the sine bar, and the screw of the scanning mechanism. First, the relationship between the mechanical error in the monochromator with the sine drive and the wavelength error is analyzed. Second, a mathematical model of the wavelength error and mechanical error is developed, and an accurate wavelength calibration method based on the sine bar's length adjustment and error compensation is proposed. Based on the mathematical model and calibration method, experiments using a standard light source with known spectral lines and a pre-adjusted sine bar length are conducted. The model parameter equations are solved, and subsequent parameter optimization simulations are performed to determine the optimal length ratio. Lastly, the length of the sine bar is adjusted. The experimental results indicate that the wavelength accuracy is ±0.3 nm, which is better than the original accuracy of ±2.6 nm. The results confirm the validity of the error analysis of the mechanical system of the monochromator as well as the validity of the calibration method.
Development of WRF-ROI system by incorporating eigen-decomposition
NASA Astrophysics Data System (ADS)
Kim, S.; Noh, N.; Song, H.; Lim, G.
2011-12-01
This study presents the development of WRF-ROI system, which is the implementation of Retrospective Optimal Interpolation (ROI) to the Weather Research and Forecasting model (WRF). ROI is a new data assimilation algorithm introduced by Song et al. (2009) and Song and Lim (2009). The formulation of ROI is similar with that of Optimal Interpolation (OI), but ROI iteratively assimilates an observation set at a post analysis time into a prior analysis, possibly providing the high quality reanalysis data. ROI method assimilates the data at post analysis time using perturbation method (Errico and Raeder, 1999) without adjoint model. In previous study, ROI method is applied to Lorenz 40-variable model (Lorenz, 1996) to validate the algorithm and to investigate the capability. It is therefore required to apply this ROI method into a more realistic and complicated model framework such as WRF. In this research, the reduced-rank formulation of ROI is used instead of a reduced-resolution method. The computational costs can be reduced due to the eigen-decomposition of background error covariance in the reduced-rank method. When single profile of observations is assimilated in the WRF-ROI system by incorporating eigen-decomposition, the analysis error tends to be reduced if compared with the background error. The difference between forecast errors with assimilation and without assimilation is obviously increased as time passed, which means the improvement of forecast error by assimilation.
NASA Technical Reports Server (NTRS)
Puliafito, E.; Bevilacqua, R.; Olivero, J.; Degenhardt, W.
1992-01-01
The formal retrieval error analysis of Rodgers (1990) allows the quantitative determination of such retrieval properties as measurement error sensitivity, resolution, and inversion bias. This technique was applied to five numerical inversion techniques and two nonlinear iterative techniques used for the retrieval of middle atmospheric constituent concentrations from limb-scanning millimeter-wave spectroscopic measurements. It is found that the iterative methods have better vertical resolution, but are slightly more sensitive to measurement error than constrained matrix methods. The iterative methods converge to the exact solution, whereas two of the matrix methods under consideration have an explicit constraint, the sensitivity of the solution to the a priori profile. Tradeoffs of these retrieval characteristics are presented.
Evaluation of Eight Methods for Aligning Orientation of Two Coordinate Systems.
Mecheri, Hakim; Robert-Lachaine, Xavier; Larue, Christian; Plamondon, André
2016-08-01
The aim of this study was to evaluate eight methods for aligning the orientation of two different local coordinate systems. Alignment is very important when combining two different systems of motion analysis. Two of the methods were developed specifically for biomechanical studies, and because there have been at least three decades of algorithm development in robotics, it was decided to include six methods from this field. To compare these methods, an Xsens sensor and two Optotrak clusters were attached to a Plexiglas plate. The first optical marker cluster was fixed on the sensor and 20 trials were recorded. The error of alignment was calculated for each trial, and the mean, the standard deviation, and the maximum values of this error over all trials were reported. One-way repeated measures analysis of variance revealed that the alignment error differed significantly across the eight methods. Post-hoc tests showed that the alignment error from the methods based on angular velocities was significantly lower than for the other methods. The method using angular velocities performed the best, with an average error of 0.17 ± 0.08 deg. We therefore recommend this method, which is easy to perform and provides accurate alignment.
Analysis of case-only studies accounting for genotyping error.
Cheng, K F
2007-03-01
The case-only design provides one approach to assess possible interactions between genetic and environmental factors. It has been shown that if these factors are conditionally independent, then a case-only analysis is not only valid but also very efficient. However, a drawback of the case-only approach is that its conclusions may be biased by genotyping errors. In this paper, our main aim is to propose a method for analysis of case-only studies when these errors occur. We show that the bias can be adjusted through the use of internal validation data, which are obtained by genotyping some sampled individuals twice. Our analysis is based on a simple and yet highly efficient conditional likelihood approach. Simulation studies considered in this paper confirm that the new method has acceptable performance under genotyping errors.
Metering error quantification under voltage and current waveform distortion
NASA Astrophysics Data System (ADS)
Wang, Tao; Wang, Jia; Xie, Zhi; Zhang, Ran
2017-09-01
With integration of more and more renewable energies and distortion loads into power grid, the voltage and current waveform distortion results in metering error in the smart meters. Because of the negative effects on the metering accuracy and fairness, it is an important subject to study energy metering combined error. In this paper, after the comparing between metering theoretical value and real recorded value under different meter modes for linear and nonlinear loads, a quantification method of metering mode error is proposed under waveform distortion. Based on the metering and time-division multiplier principles, a quantification method of metering accuracy error is proposed also. Analyzing the mode error and accuracy error, a comprehensive error analysis method is presented which is suitable for new energy and nonlinear loads. The proposed method has been proved by simulation.
Self-calibration method without joint iteration for distributed small satellite SAR systems
NASA Astrophysics Data System (ADS)
Xu, Qing; Liao, Guisheng; Liu, Aifei; Zhang, Juan
2013-12-01
The performance of distributed small satellite synthetic aperture radar systems degrades significantly due to the unavoidable array errors, including gain, phase, and position errors, in real operating scenarios. In the conventional method proposed in (IEEE T Aero. Elec. Sys. 42:436-451, 2006), the spectrum components within one Doppler bin are considered as calibration sources. However, it is found in this article that the gain error estimation and the position error estimation in the conventional method can interact with each other. The conventional method may converge to suboptimal solutions in large position errors since it requires the joint iteration between gain-phase error estimation and position error estimation. In addition, it is also found that phase errors can be estimated well regardless of position errors when the zero Doppler bin is chosen. In this article, we propose a method obtained by modifying the conventional one, based on these two observations. In this modified method, gain errors are firstly estimated and compensated, which eliminates the interaction between gain error estimation and position error estimation. Then, by using the zero Doppler bin data, the phase error estimation can be performed well independent of position errors. Finally, position errors are estimated based on the Taylor-series expansion. Meanwhile, the joint iteration between gain-phase error estimation and position error estimation is not required. Therefore, the problem of suboptimal convergence, which occurs in the conventional method, can be avoided with low computational method. The modified method has merits of faster convergence and lower estimation error compared to the conventional one. Theoretical analysis and computer simulation results verified the effectiveness of the modified method.
Grinding Method and Error Analysis of Eccentric Shaft Parts
NASA Astrophysics Data System (ADS)
Wang, Zhiming; Han, Qiushi; Li, Qiguang; Peng, Baoying; Li, Weihua
2017-12-01
RV reducer and various mechanical transmission parts are widely used in eccentric shaft parts, The demand of precision grinding technology for eccentric shaft parts now, In this paper, the model of X-C linkage relation of eccentric shaft grinding is studied; By inversion method, the contour curve of the wheel envelope is deduced, and the distance from the center of eccentric circle is constant. The simulation software of eccentric shaft grinding is developed, the correctness of the model is proved, the influence of the X-axis feed error, the C-axis feed error and the wheel radius error on the grinding process is analyzed, and the corresponding error calculation model is proposed. The simulation analysis is carried out to provide the basis for the contour error compensation.
Region of influence regression for estimating the 50-year flood at ungaged sites
Tasker, Gary D.; Hodge, S.A.; Barks, C.S.
1996-01-01
Five methods of developing regional regression models to estimate flood characteristics at ungaged sites in Arkansas are examined. The methods differ in the manner in which the State is divided into subrogions. Each successive method (A to E) is computationally more complex than the previous method. Method A makes no subdivision. Methods B and C define two and four geographic subrogions, respectively. Method D uses cluster/discriminant analysis to define subrogions on the basis of similarities in watershed characteristics. Method E, the new region of influence method, defines a unique subregion for each ungaged site. Split-sample results indicate that, in terms of root-mean-square error, method E (38 percent error) is best. Methods C and D (42 and 41 percent error) were in a virtual tie for second, and methods B (44 percent error) and A (49 percent error) were fourth and fifth best.
System reliability and recovery.
DOT National Transportation Integrated Search
1971-06-01
The paper exhibits a variety of reliability techniques applicable to future ATC data processing systems. Presently envisioned schemes for error detection, error interrupt and error analysis are considered, along with methods of retry, reconfiguration...
Output Error Analysis of Planar 2-DOF Five-bar Mechanism
NASA Astrophysics Data System (ADS)
Niu, Kejia; Wang, Jun; Ting, Kwun-Lon; Tao, Fen; Cheng, Qunchao; Wang, Quan; Zhang, Kaiyang
2018-03-01
Aiming at the mechanism error caused by clearance of planar 2-DOF Five-bar motion pair, the method of equivalent joint clearance of kinematic pair to virtual link is applied. The structural error model of revolute joint clearance is established based on the N-bar rotation laws and the concept of joint rotation space, The influence of the clearance of the moving pair is studied on the output error of the mechanis. and the calculation method and basis of the maximum error are given. The error rotation space of the mechanism under the influence of joint clearance is obtained. The results show that this method can accurately calculate the joint space error rotation space, which provides a new way to analyze the planar parallel mechanism error caused by joint space.
Error analysis of finite element method for Poisson–Nernst–Planck equations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sun, Yuzhou; Sun, Pengtao; Zheng, Bin
A priori error estimates of finite element method for time-dependent Poisson-Nernst-Planck equations are studied in this work. We obtain the optimal error estimates in L∞(H1) and L2(H1) norms, and suboptimal error estimates in L∞(L2) norm, with linear element, and optimal error estimates in L∞(L2) norm with quadratic or higher-order element, for both semi- and fully discrete finite element approximations. Numerical experiments are also given to validate the theoretical results.
NASA Astrophysics Data System (ADS)
Wang, Mi; Fang, Chengcheng; Yang, Bo; Cheng, Yufeng
2016-06-01
The low frequency error is a key factor which has affected uncontrolled geometry processing accuracy of the high-resolution optical image. To guarantee the geometric quality of imagery, this paper presents an on-orbit calibration method for the low frequency error based on geometric calibration field. Firstly, we introduce the overall flow of low frequency error on-orbit analysis and calibration, which includes optical axis angle variation detection of star sensor, relative calibration among star sensors, multi-star sensor information fusion, low frequency error model construction and verification. Secondly, we use optical axis angle change detection method to analyze the law of low frequency error variation. Thirdly, we respectively use the method of relative calibration and information fusion among star sensors to realize the datum unity and high precision attitude output. Finally, we realize the low frequency error model construction and optimal estimation of model parameters based on DEM/DOM of geometric calibration field. To evaluate the performance of the proposed calibration method, a certain type satellite's real data is used. Test results demonstrate that the calibration model in this paper can well describe the law of the low frequency error variation. The uncontrolled geometric positioning accuracy of the high-resolution optical image in the WGS-84 Coordinate Systems is obviously improved after the step-wise calibration.
Covariate Measurement Error Correction Methods in Mediation Analysis with Failure Time Data
Zhao, Shanshan
2014-01-01
Summary Mediation analysis is important for understanding the mechanisms whereby one variable causes changes in another. Measurement error could obscure the ability of the potential mediator to explain such changes. This paper focuses on developing correction methods for measurement error in the mediator with failure time outcomes. We consider a broad definition of measurement error, including technical error and error associated with temporal variation. The underlying model with the ‘true’ mediator is assumed to be of the Cox proportional hazards model form. The induced hazard ratio for the observed mediator no longer has a simple form independent of the baseline hazard function, due to the conditioning event. We propose a mean-variance regression calibration approach and a follow-up time regression calibration approach, to approximate the partial likelihood for the induced hazard function. Both methods demonstrate value in assessing mediation effects in simulation studies. These methods are generalized to multiple biomarkers and to both case-cohort and nested case-control sampling design. We apply these correction methods to the Women's Health Initiative hormone therapy trials to understand the mediation effect of several serum sex hormone measures on the relationship between postmenopausal hormone therapy and breast cancer risk. PMID:25139469
Covariate measurement error correction methods in mediation analysis with failure time data.
Zhao, Shanshan; Prentice, Ross L
2014-12-01
Mediation analysis is important for understanding the mechanisms whereby one variable causes changes in another. Measurement error could obscure the ability of the potential mediator to explain such changes. This article focuses on developing correction methods for measurement error in the mediator with failure time outcomes. We consider a broad definition of measurement error, including technical error, and error associated with temporal variation. The underlying model with the "true" mediator is assumed to be of the Cox proportional hazards model form. The induced hazard ratio for the observed mediator no longer has a simple form independent of the baseline hazard function, due to the conditioning event. We propose a mean-variance regression calibration approach and a follow-up time regression calibration approach, to approximate the partial likelihood for the induced hazard function. Both methods demonstrate value in assessing mediation effects in simulation studies. These methods are generalized to multiple biomarkers and to both case-cohort and nested case-control sampling designs. We apply these correction methods to the Women's Health Initiative hormone therapy trials to understand the mediation effect of several serum sex hormone measures on the relationship between postmenopausal hormone therapy and breast cancer risk. © 2014, The International Biometric Society.
On the use of log-transformation vs. nonlinear regression for analyzing biological power laws.
Xiao, Xiao; White, Ethan P; Hooten, Mevin B; Durham, Susan L
2011-10-01
Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain.
Skylab water balance error analysis
NASA Technical Reports Server (NTRS)
Leonard, J. I.
1977-01-01
Estimates of the precision of the net water balance were obtained for the entire Skylab preflight and inflight phases as well as for the first two weeks of flight. Quantitative estimates of both total sampling errors and instrumentation errors were obtained. It was shown that measurement error is minimal in comparison to biological variability and little can be gained from improvement in analytical accuracy. In addition, a propagation of error analysis demonstrated that total water balance error could be accounted for almost entirely by the errors associated with body mass changes. Errors due to interaction between terms in the water balance equation (covariances) represented less than 10% of the total error. Overall, the analysis provides evidence that daily measurements of body water changes obtained from the indirect balance technique are reasonable, precise, and relaible. The method is not biased toward net retention or loss.
Andrzejewska, Anna; Kaczmarski, Krzysztof; Guiochon, Georges
2009-02-13
The adsorption isotherms of selected compounds are our main source of information on the mechanisms of adsorption processes. Thus, the selection of the methods used to determine adsorption isotherm data and to evaluate the errors made is critical. Three chromatographic methods were evaluated, frontal analysis (FA), frontal analysis by characteristic point (FACP), and the pulse or perturbation method (PM), and their accuracies were compared. Using the equilibrium-dispersive (ED) model of chromatography, breakthrough curves of single components were generated corresponding to three different adsorption isotherm models: the Langmuir, the bi-Langmuir, and the Moreau isotherms. For each breakthrough curve, the best conventional procedures of each method (FA, FACP, PM) were used to calculate the corresponding data point, using typical values of the parameters of each isotherm model, for four different values of the column efficiency (N=500, 1000, 2000, and 10,000). Then, the data points were fitted to each isotherm model and the corresponding isotherm parameters were compared to those of the initial isotherm model. When isotherm data are derived with a chromatographic method, they may suffer from two types of errors: (1) the errors made in deriving the experimental data points from the chromatographic records; (2) the errors made in selecting an incorrect isotherm model and fitting to it the experimental data. Both errors decrease significantly with increasing column efficiency with FA and FACP, but not with PM.
NASA Astrophysics Data System (ADS)
Wang, Jia; Hou, Xi; Wan, Yongjian; Shi, Chunyan
2017-10-01
An optimized method to calculate error correction capability of tool influence function (TIF) in certain polishing conditions will be proposed based on smoothing spectral function. The basic mathematical model for this method will be established in theory. A set of polishing experimental data with rigid conformal tool is used to validate the optimized method. The calculated results can quantitatively indicate error correction capability of TIF for different spatial frequency errors in certain polishing conditions. The comparative analysis with previous method shows that the optimized method is simpler in form and can get the same accuracy results with less calculating time in contrast to previous method.
NASA Technical Reports Server (NTRS)
Bernacki, Bruce E.; Mansuripur, M.
1992-01-01
A commonly used tracking method on pre-grooved magneto-optical (MO) media is the push-pull technique, and the astigmatic method is a popular focus-error detection approach. These two methods are analyzed using DIFFRACT, a general-purpose scalar diffraction modeling program, to observe the effects on the error signals due to focusing lens misalignment, Seidel aberrations, and optical crosstalk (feedthrough) between the focusing and tracking servos. Using the results of the astigmatic/push-pull system as a basis for comparison, a novel focus/track-error detection technique that utilizes a ring toric lens is evaluated as well as the obscuration method (focus error detection only).
Causal inference with measurement error in outcomes: Bias analysis and estimation methods.
Shu, Di; Yi, Grace Y
2017-01-01
Inverse probability weighting estimation has been popularly used to consistently estimate the average treatment effect. Its validity, however, is challenged by the presence of error-prone variables. In this paper, we explore the inverse probability weighting estimation with mismeasured outcome variables. We study the impact of measurement error for both continuous and discrete outcome variables and reveal interesting consequences of the naive analysis which ignores measurement error. When a continuous outcome variable is mismeasured under an additive measurement error model, the naive analysis may still yield a consistent estimator; when the outcome is binary, we derive the asymptotic bias in a closed-form. Furthermore, we develop consistent estimation procedures for practical scenarios where either validation data or replicates are available. With validation data, we propose an efficient method for estimation of average treatment effect; the efficiency gain is substantial relative to usual methods of using validation data. To provide protection against model misspecification, we further propose a doubly robust estimator which is consistent even when either the treatment model or the outcome model is misspecified. Simulation studies are reported to assess the performance of the proposed methods. An application to a smoking cessation dataset is presented.
NASA Astrophysics Data System (ADS)
Zheng, Sifa; Liu, Haitao; Dan, Jiabi; Lian, Xiaomin
2015-05-01
Linear time-invariant assumption for the determination of acoustic source characteristics, the source strength and the source impedance in the frequency domain has been proved reasonable in the design of an exhaust system. Different methods have been proposed to its identification and the multi-load method is widely used for its convenience by varying the load number and impedance. Theoretical error analysis has rarely been referred to and previous results have shown an overdetermined set of open pipes can reduce the identification error. This paper contributes a theoretical error analysis for the load selection. The relationships between the error in the identification of source characteristics and the load selection were analysed. A general linear time-invariant model was built based on the four-load method. To analyse the error of the source impedance, an error estimation function was proposed. The dispersion of the source pressure was obtained by an inverse calculation as an indicator to detect the accuracy of the results. It was found that for a certain load length, the load resistance at the frequency points of one-quarter wavelength of odd multiples results in peaks and in the maximum error for source impedance identification. Therefore, the load impedance of frequency range within the one-quarter wavelength of odd multiples should not be used for source impedance identification. If the selected loads have more similar resistance values (i.e., the same order of magnitude), the identification error of the source impedance could be effectively reduced.
Diffraction analysis of sidelobe characteristics of optical elements with ripple error
NASA Astrophysics Data System (ADS)
Zhao, Lei; Luo, Yupeng; Bai, Jian; Zhou, Xiangdong; Du, Juan; Liu, Qun; Luo, Yujie
2018-03-01
The ripple errors of the lens lead to optical damage in high energy laser system. The analysis of sidelobe on the focal plane, caused by ripple error, provides a reference to evaluate the error and the imaging quality. In this paper, we analyze the diffraction characteristics of sidelobe of optical elements with ripple errors. First, we analyze the characteristics of ripple error and build relationship between ripple error and sidelobe. The sidelobe results from the diffraction of ripple errors. The ripple error tends to be periodic due to fabrication method on the optical surface. The simulated experiments are carried out based on angular spectrum method by characterizing ripple error as rotationally symmetric periodic structures. The influence of two major parameter of ripple including spatial frequency and peak-to-valley value to sidelobe is discussed. The results indicate that spatial frequency and peak-to-valley value both impact sidelobe at the image plane. The peak-tovalley value is the major factor to affect the energy proportion of the sidelobe. The spatial frequency is the major factor to affect the distribution of the sidelobe at the image plane.
NASA Technical Reports Server (NTRS)
Balla, R. Jeffrey; Miller, Corey A.
2008-01-01
This study seeks a numerical algorithm which optimizes frequency precision for the damped sinusoids generated by the nonresonant LITA technique. It compares computed frequencies, frequency errors, and fit errors obtained using five primary signal analysis methods. Using variations on different algorithms within each primary method, results from 73 fits are presented. Best results are obtained using an AutoRegressive method. Compared to previous results using Prony s method, single shot waveform frequencies are reduced approx.0.4% and frequency errors are reduced by a factor of approx.20 at 303K to approx. 0.1%. We explore the advantages of high waveform sample rates and potential for measurements in low density gases.
SEU System Analysis: Not Just the Sum of All Parts
NASA Technical Reports Server (NTRS)
Berg, Melanie D.; Label, Kenneth
2014-01-01
Single event upset (SEU) analysis of complex systems is challenging. Currently, system SEU analysis is performed by component level partitioning and then either: the most dominant SEU cross-sections (SEUs) are used in system error rate calculations; or the partition SEUs are summed to eventually obtain a system error rate. In many cases, system error rates are overestimated because these methods generally overlook system level derating factors. The problem with overestimating is that it can cause overdesign and consequently negatively affect the following: cost, schedule, functionality, and validation/verification. The scope of this presentation is to discuss the risks involved with our current scheme of SEU analysis for complex systems; and to provide alternative methods for improvement.
A Linguistic Analysis of Errors in the Compositions of Arba Minch University Students
ERIC Educational Resources Information Center
Tizazu, Yoseph
2014-01-01
This study reports the dominant linguistic errors that occur in the written productions of Arba Minch University (hereafter AMU) students. A sample of paragraphs was collected for two years from students ranging from freshmen to graduating level. The sampled compositions were then coded, described, and explained using error analysis method. Both…
Deffner, Veronika; Küchenhoff, Helmut; Breitner, Susanne; Schneider, Alexandra; Cyrys, Josef; Peters, Annette
2018-05-01
The ultrafine particle measurements in the Augsburger Umweltstudie, a panel study conducted in Augsburg, Germany, exhibit measurement error from various sources. Measurements of mobile devices show classical possibly individual-specific measurement error; Berkson-type error, which may also vary individually, occurs, if measurements of fixed monitoring stations are used. The combination of fixed site and individual exposure measurements results in a mixture of the two error types. We extended existing bias analysis approaches to linear mixed models with a complex error structure including individual-specific error components, autocorrelated errors, and a mixture of classical and Berkson error. Theoretical considerations and simulation results show, that autocorrelation may severely change the attenuation of the effect estimations. Furthermore, unbalanced designs and the inclusion of confounding variables influence the degree of attenuation. Bias correction with the method of moments using data with mixture measurement error partially yielded better results compared to the usage of incomplete data with classical error. Confidence intervals (CIs) based on the delta method achieved better coverage probabilities than those based on Bootstrap samples. Moreover, we present the application of these new methods to heart rate measurements within the Augsburger Umweltstudie: the corrected effect estimates were slightly higher than their naive equivalents. The substantial measurement error of ultrafine particle measurements has little impact on the results. The developed methodology is generally applicable to longitudinal data with measurement error. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Microscopic saw mark analysis: an empirical approach.
Love, Jennifer C; Derrick, Sharon M; Wiersema, Jason M; Peters, Charles
2015-01-01
Microscopic saw mark analysis is a well published and generally accepted qualitative analytical method. However, little research has focused on identifying and mitigating potential sources of error associated with the method. The presented study proposes the use of classification trees and random forest classifiers as an optimal, statistically sound approach to mitigate the potential for error of variability and outcome error in microscopic saw mark analysis. The statistical model was applied to 58 experimental saw marks created with four types of saws. The saw marks were made in fresh human femurs obtained through anatomical gift and were analyzed using a Keyence digital microscope. The statistical approach weighed the variables based on discriminatory value and produced decision trees with an associated outcome error rate of 8.62-17.82%. © 2014 American Academy of Forensic Sciences.
Error analysis and correction of lever-type stylus profilometer based on Nelder-Mead Simplex method
NASA Astrophysics Data System (ADS)
Hu, Chunbing; Chang, Suping; Li, Bo; Wang, Junwei; Zhang, Zhongyu
2017-10-01
Due to the high measurement accuracy and wide range of applications, lever-type stylus profilometry is commonly used in industrial research areas. However, the error caused by the lever structure has a great influence on the profile measurement, thus this paper analyzes the error of high-precision large-range lever-type stylus profilometry. The errors are corrected by the Nelder-Mead Simplex method, and the results are verified by the spherical surface calibration. It can be seen that this method can effectively reduce the measurement error and improve the accuracy of the stylus profilometry in large-scale measurement.
Passive quantum error correction of linear optics networks through error averaging
NASA Astrophysics Data System (ADS)
Marshman, Ryan J.; Lund, Austin P.; Rohde, Peter P.; Ralph, Timothy C.
2018-02-01
We propose and investigate a method of error detection and noise correction for bosonic linear networks using a method of unitary averaging. The proposed error averaging does not rely on ancillary photons or control and feedforward correction circuits, remaining entirely passive in its operation. We construct a general mathematical framework for this technique and then give a series of proof of principle examples including numerical analysis. Two methods for the construction of averaging are then compared to determine the most effective manner of implementation and probe the related error thresholds. Finally we discuss some of the potential uses of this scheme.
Advancing Usability Evaluation through Human Reliability Analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ronald L. Boring; David I. Gertman
2005-07-01
This paper introduces a novel augmentation to the current heuristic usability evaluation methodology. The SPAR-H human reliability analysis method was developed for categorizing human performance in nuclear power plants. Despite the specialized use of SPAR-H for safety critical scenarios, the method also holds promise for use in commercial off-the-shelf software usability evaluations. The SPAR-H method shares task analysis underpinnings with human-computer interaction, and it can be easily adapted to incorporate usability heuristics as performance shaping factors. By assigning probabilistic modifiers to heuristics, it is possible to arrive at the usability error probability (UEP). This UEP is not a literal probabilitymore » of error but nonetheless provides a quantitative basis to heuristic evaluation. When combined with a consequence matrix for usability errors, this method affords ready prioritization of usability issues.« less
On-Error Training (Book Excerpt).
ERIC Educational Resources Information Center
Fukuda, Ryuji
1985-01-01
This excerpt from "Managerial Engineering: Techniques for Improving Quality and Productivity in the Workplace" describes the development, objectives, and use of On-Error Training (OET), a method which trains workers to learn from their errors. Also described is New Joharry's Window, a performance-error data analysis technique used in…
Automatic Estimation of Verified Floating-Point Round-Off Errors via Static Analysis
NASA Technical Reports Server (NTRS)
Moscato, Mariano; Titolo, Laura; Dutle, Aaron; Munoz, Cesar A.
2017-01-01
This paper introduces a static analysis technique for computing formally verified round-off error bounds of floating-point functional expressions. The technique is based on a denotational semantics that computes a symbolic estimation of floating-point round-o errors along with a proof certificate that ensures its correctness. The symbolic estimation can be evaluated on concrete inputs using rigorous enclosure methods to produce formally verified numerical error bounds. The proposed technique is implemented in the prototype research tool PRECiSA (Program Round-o Error Certifier via Static Analysis) and used in the verification of floating-point programs of interest to NASA.
Comprehensive analysis of a medication dosing error related to CPOE.
Horsky, Jan; Kuperman, Gilad J; Patel, Vimla L
2005-01-01
This case study of a serious medication error demonstrates the necessity of a comprehensive methodology for the analysis of failures in interaction between humans and information systems. The authors used a novel approach to analyze a dosing error related to computer-based ordering of potassium chloride (KCl). The method included a chronological reconstruction of events and their interdependencies from provider order entry usage logs, semistructured interviews with involved clinicians, and interface usability inspection of the ordering system. Information collected from all sources was compared and evaluated to understand how the error evolved and propagated through the system. In this case, the error was the product of faults in interaction among human and system agents that methods limited in scope to their distinct analytical domains would not identify. The authors characterized errors in several converging aspects of the drug ordering process: confusing on-screen laboratory results review, system usability difficulties, user training problems, and suboptimal clinical system safeguards that all contributed to a serious dosing error. The results of the authors' analysis were used to formulate specific recommendations for interface layout and functionality modifications, suggest new user alerts, propose changes to user training, and address error-prone steps of the KCl ordering process to reduce the risk of future medication dosing errors.
Modeling error distributions of growth curve models through Bayesian methods.
Zhang, Zhiyong
2016-06-01
Growth curve models are widely used in social and behavioral sciences. However, typical growth curve models often assume that the errors are normally distributed although non-normal data may be even more common than normal data. In order to avoid possible statistical inference problems in blindly assuming normality, a general Bayesian framework is proposed to flexibly model normal and non-normal data through the explicit specification of the error distributions. A simulation study shows when the distribution of the error is correctly specified, one can avoid the loss in the efficiency of standard error estimates. A real example on the analysis of mathematical ability growth data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 is used to show the application of the proposed methods. Instructions and code on how to conduct growth curve analysis with both normal and non-normal error distributions using the the MCMC procedure of SAS are provided.
Local blur analysis and phase error correction method for fringe projection profilometry systems.
Rao, Li; Da, Feipeng
2018-05-20
We introduce a flexible error correction method for fringe projection profilometry (FPP) systems in the presence of local blur phenomenon. Local blur caused by global light transport such as camera defocus, projector defocus, and subsurface scattering will cause significant systematic errors in FPP systems. Previous methods, which adopt high-frequency patterns to separate the direct and global components, fail when the global light phenomenon occurs locally. In this paper, the influence of local blur on phase quality is thoroughly analyzed, and a concise error correction method is proposed to compensate the phase errors. For defocus phenomenon, this method can be directly applied. With the aid of spatially varying point spread functions and local frontal plane assumption, experiments show that the proposed method can effectively alleviate the system errors and improve the final reconstruction accuracy in various scenes. For a subsurface scattering scenario, if the translucent object is dominated by multiple scattering, the proposed method can also be applied to correct systematic errors once the bidirectional scattering-surface reflectance distribution function of the object material is measured.
Analysis of Statistical Methods and Errors in the Articles Published in the Korean Journal of Pain
Yim, Kyoung Hoon; Han, Kyoung Ah; Park, Soo Young
2010-01-01
Background Statistical analysis is essential in regard to obtaining objective reliability for medical research. However, medical researchers do not have enough statistical knowledge to properly analyze their study data. To help understand and potentially alleviate this problem, we have analyzed the statistical methods and errors of articles published in the Korean Journal of Pain (KJP), with the intention to improve the statistical quality of the journal. Methods All the articles, except case reports and editorials, published from 2004 to 2008 in the KJP were reviewed. The types of applied statistical methods and errors in the articles were evaluated. Results One hundred and thirty-nine original articles were reviewed. Inferential statistics and descriptive statistics were used in 119 papers and 20 papers, respectively. Only 20.9% of the papers were free from statistical errors. The most commonly adopted statistical method was the t-test (21.0%) followed by the chi-square test (15.9%). Errors of omission were encountered 101 times in 70 papers. Among the errors of omission, "no statistics used even though statistical methods were required" was the most common (40.6%). The errors of commission were encountered 165 times in 86 papers, among which "parametric inference for nonparametric data" was the most common (33.9%). Conclusions We found various types of statistical errors in the articles published in the KJP. This suggests that meticulous attention should be given not only in the applying statistical procedures but also in the reviewing process to improve the value of the article. PMID:20552071
A new method for the analysis of fire spread modeling errors
Francis M. Fujioka
2002-01-01
Fire spread models have a long history, and their use will continue to grow as they evolve from a research tool to an operational tool. This paper describes a new method to analyse two-dimensional fire spread modeling errors, particularly to quantify the uncertainties of fire spread predictions. Measures of error are defined from the respective spread distances of...
Analysis and optimization of cyclic methods in orbit computation
NASA Technical Reports Server (NTRS)
Pierce, S.
1973-01-01
The mathematical analysis and computation of the K=3, order 4; K=4, order 6; and K=5, order 7 cyclic methods and the K=5, order 6 Cowell method and some results of optimizing the 3 backpoint cyclic multistep methods for solving ordinary differential equations are presented. Cyclic methods have the advantage over traditional methods of having higher order for a given number of backpoints while at the same time having more free parameters. After considering several error sources the primary source for the cyclic methods has been isolated. The free parameters for three backpoint methods were used to minimize the effects of some of these error sources. They now yield more accuracy with the same computing time as Cowell's method on selected problems. This work is being extended to the five backpoint methods. The analysis and optimization are more difficult here since the matrices are larger and the dimension of the optimizing space is larger. Indications are that the primary error source can be reduced. This will still leave several parameters free to minimize other sources.
Integrated analysis of error detection and recovery
NASA Technical Reports Server (NTRS)
Shin, K. G.; Lee, Y. H.
1985-01-01
An integrated modeling and analysis of error detection and recovery is presented. When fault latency and/or error latency exist, the system may suffer from multiple faults or error propagations which seriously deteriorate the fault-tolerant capability. Several detection models that enable analysis of the effect of detection mechanisms on the subsequent error handling operations and the overall system reliability were developed. Following detection of the faulty unit and reconfiguration of the system, the contaminated processes or tasks have to be recovered. The strategies of error recovery employed depend on the detection mechanisms and the available redundancy. Several recovery methods including the rollback recovery are considered. The recovery overhead is evaluated as an index of the capabilities of the detection and reconfiguration mechanisms.
A Simple Exact Error Rate Analysis for DS-CDMA with Arbitrary Pulse Shape in Flat Nakagami Fading
NASA Astrophysics Data System (ADS)
Rahman, Mohammad Azizur; Sasaki, Shigenobu; Kikuchi, Hisakazu; Harada, Hiroshi; Kato, Shuzo
A simple exact error rate analysis is presented for random binary direct sequence code division multiple access (DS-CDMA) considering a general pulse shape and flat Nakagami fading channel. First of all, a simple model is developed for the multiple access interference (MAI). Based on this, a simple exact expression of the characteristic function (CF) of MAI is developed in a straight forward manner. Finally, an exact expression of error rate is obtained following the CF method of error rate analysis. The exact error rate so obtained can be much easily evaluated as compared to the only reliable approximate error rate expression currently available, which is based on the Improved Gaussian Approximation (IGA).
Use of modeling to identify vulnerabilities to human error in laparoscopy.
Funk, Kenneth H; Bauer, James D; Doolen, Toni L; Telasha, David; Nicolalde, R Javier; Reeber, Miriam; Yodpijit, Nantakrit; Long, Myra
2010-01-01
This article describes an exercise to investigate the utility of modeling and human factors analysis in understanding surgical processes and their vulnerabilities to medical error. A formal method to identify error vulnerabilities was developed and applied to a test case of Veress needle insertion during closed laparoscopy. A team of 2 surgeons, a medical assistant, and 3 engineers used hierarchical task analysis and Integrated DEFinition language 0 (IDEF0) modeling to create rich models of the processes used in initial port creation. Using terminology from a standardized human performance database, detailed task descriptions were written for 4 tasks executed in the process of inserting the Veress needle. Key terms from the descriptions were used to extract from the database generic errors that could occur. Task descriptions with potential errors were translated back into surgical terminology. Referring to the process models and task descriptions, the team used a modified failure modes and effects analysis (FMEA) to consider each potential error for its probability of occurrence, its consequences if it should occur and be undetected, and its probability of detection. The resulting likely and consequential errors were prioritized for intervention. A literature-based validation study confirmed the significance of the top error vulnerabilities identified using the method. Ongoing work includes design and evaluation of procedures to correct the identified vulnerabilities and improvements to the modeling and vulnerability identification methods. Copyright 2010 AAGL. Published by Elsevier Inc. All rights reserved.
Bennett, Derrick A; Landry, Denise; Little, Julian; Minelli, Cosetta
2017-09-19
Several statistical approaches have been proposed to assess and correct for exposure measurement error. We aimed to provide a critical overview of the most common approaches used in nutritional epidemiology. MEDLINE, EMBASE, BIOSIS and CINAHL were searched for reports published in English up to May 2016 in order to ascertain studies that described methods aimed to quantify and/or correct for measurement error for a continuous exposure in nutritional epidemiology using a calibration study. We identified 126 studies, 43 of which described statistical methods and 83 that applied any of these methods to a real dataset. The statistical approaches in the eligible studies were grouped into: a) approaches to quantify the relationship between different dietary assessment instruments and "true intake", which were mostly based on correlation analysis and the method of triads; b) approaches to adjust point and interval estimates of diet-disease associations for measurement error, mostly based on regression calibration analysis and its extensions. Two approaches (multiple imputation and moment reconstruction) were identified that can deal with differential measurement error. For regression calibration, the most common approach to correct for measurement error used in nutritional epidemiology, it is crucial to ensure that its assumptions and requirements are fully met. Analyses that investigate the impact of departures from the classical measurement error model on regression calibration estimates can be helpful to researchers in interpreting their findings. With regard to the possible use of alternative methods when regression calibration is not appropriate, the choice of method should depend on the measurement error model assumed, the availability of suitable calibration study data and the potential for bias due to violation of the classical measurement error model assumptions. On the basis of this review, we provide some practical advice for the use of methods to assess and adjust for measurement error in nutritional epidemiology.
Error correction and diversity analysis of population mixtures determined by NGS
Burroughs, Nigel J.; Evans, David J.; Ryabov, Eugene V.
2014-01-01
The impetus for this work was the need to analyse nucleotide diversity in a viral mix taken from honeybees. The paper has two findings. First, a method for correction of next generation sequencing error in the distribution of nucleotides at a site is developed. Second, a package of methods for assessment of nucleotide diversity is assembled. The error correction method is statistically based and works at the level of the nucleotide distribution rather than the level of individual nucleotides. The method relies on an error model and a sample of known viral genotypes that is used for model calibration. A compendium of existing and new diversity analysis tools is also presented, allowing hypotheses about diversity and mean diversity to be tested and associated confidence intervals to be calculated. The methods are illustrated using honeybee viral samples. Software in both Excel and Matlab and a guide are available at http://www2.warwick.ac.uk/fac/sci/systemsbiology/research/software/, the Warwick University Systems Biology Centre software download site. PMID:25405074
Synchronization Design and Error Analysis of Near-Infrared Cameras in Surgical Navigation.
Cai, Ken; Yang, Rongqian; Chen, Huazhou; Huang, Yizhou; Wen, Xiaoyan; Huang, Wenhua; Ou, Shanxing
2016-01-01
The accuracy of optical tracking systems is important to scientists. With the improvements reported in this regard, such systems have been applied to an increasing number of operations. To enhance the accuracy of these systems further and to reduce the effect of synchronization and visual field errors, this study introduces a field-programmable gate array (FPGA)-based synchronization control method, a method for measuring synchronous errors, and an error distribution map in field of view. Synchronization control maximizes the parallel processing capability of FPGA, and synchronous error measurement can effectively detect the errors caused by synchronization in an optical tracking system. The distribution of positioning errors can be detected in field of view through the aforementioned error distribution map. Therefore, doctors can perform surgeries in areas with few positioning errors, and the accuracy of optical tracking systems is considerably improved. The system is analyzed and validated in this study through experiments that involve the proposed methods, which can eliminate positioning errors attributed to asynchronous cameras and different fields of view.
NASA Astrophysics Data System (ADS)
Genberg, Victor L.; Michels, Gregory J.
2017-08-01
The ultimate design goal of an optical system subjected to dynamic loads is to minimize system level wavefront error (WFE). In random response analysis, system WFE is difficult to predict from finite element results due to the loss of phase information. In the past, the use of ystem WFE was limited by the difficulty of obtaining a linear optics model. In this paper, an automated method for determining system level WFE using a linear optics model is presented. An error estimate is included in the analysis output based on fitting errors of mode shapes. The technique is demonstrated by example with SigFit, a commercially available tool integrating mechanical analysis with optical analysis.
Shen, Chung-Wei; Chen, Yi-Hau
2015-10-01
Missing observations and covariate measurement error commonly arise in longitudinal data. However, existing methods for model selection in marginal regression analysis of longitudinal data fail to address the potential bias resulting from these issues. To tackle this problem, we propose a new model selection criterion, the Generalized Longitudinal Information Criterion, which is based on an approximately unbiased estimator for the expected quadratic error of a considered marginal model accounting for both data missingness and covariate measurement error. The simulation results reveal that the proposed method performs quite well in the presence of missing data and covariate measurement error. On the contrary, the naive procedures without taking care of such complexity in data may perform quite poorly. The proposed method is applied to data from the Taiwan Longitudinal Study on Aging to assess the relationship of depression with health and social status in the elderly, accommodating measurement error in the covariate as well as missing observations. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
On the use of log-transformation vs. nonlinear regression for analyzing biological power laws
Xiao, X.; White, E.P.; Hooten, M.B.; Durham, S.L.
2011-01-01
Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain. ?? 2011 by the Ecological Society of America.
Mathes, Tim; Klaßen, Pauline; Pieper, Dawid
2017-11-28
Our objective was to assess the frequency of data extraction errors and its potential impact on results in systematic reviews. Furthermore, we evaluated the effect of different extraction methods, reviewer characteristics and reviewer training on error rates and results. We performed a systematic review of methodological literature in PubMed, Cochrane methodological registry, and by manual searches (12/2016). Studies were selected by two reviewers independently. Data were extracted in standardized tables by one reviewer and verified by a second. The analysis included six studies; four studies on extraction error frequency, one study comparing different reviewer extraction methods and two studies comparing different reviewer characteristics. We did not find a study on reviewer training. There was a high rate of extraction errors (up to 50%). Errors often had an influence on effect estimates. Different data extraction methods and reviewer characteristics had moderate effect on extraction error rates and effect estimates. The evidence base for established standards of data extraction seems weak despite the high prevalence of extraction errors. More comparative studies are needed to get deeper insights into the influence of different extraction methods.
Krimmel, R.M.
1999-01-01
Net mass balance has been measured since 1958 at South Cascade Glacier using the 'direct method,' e.g. area averages of snow gain and firn and ice loss at stakes. Analysis of cartographic vertical photography has allowed measurement of mass balance using the 'geodetic method' in 1970, 1975, 1977, 1979-80, and 1985-97. Water equivalent change as measured by these nearly independent methods should give similar results. During 1970-97, the direct method shows a cumulative balance of about -15 m, and the geodetic method shows a cumulative balance of about -22 m. The deviation between the two methods is fairly consistent, suggesting no gross errors in either, but rather a cumulative systematic error. It is suspected that the cumulative error is in the direct method because the geodetic method is based on a non-changing reference, the bedrock control, whereas the direct method is measured with reference to only the previous year's summer surface. Possible sources of mass loss that are missing from the direct method are basal melt, internal melt, and ablation on crevasse walls. Possible systematic measurement errors include under-estimation of the density of lost material, sinking stakes, or poorly represented areas.
Identification method of laser gyro error model under changing physical field
NASA Astrophysics Data System (ADS)
Wang, Qingqing; Niu, Zhenzhong
2018-04-01
In this paper, the influence mechanism of temperature, temperature changing rate and temperature gradient on the inertial devices is studied. The two-order model of zero bias and the three-order model of the calibration factor of lster gyro under temperature variation are deduced. The calibration scheme of temperature error is designed, and the experiment is carried out. Two methods of stepwise regression analysis and BP neural network are used to identify the parameters of the temperature error model, and the effectiveness of the two methods is proved by the temperature error compensation.
Solution of elastic-plastic stress analysis problems by the p-version of the finite element method
NASA Technical Reports Server (NTRS)
Szabo, Barna A.; Actis, Ricardo L.; Holzer, Stefan M.
1993-01-01
The solution of small strain elastic-plastic stress analysis problems by the p-version of the finite element method is discussed. The formulation is based on the deformation theory of plasticity and the displacement method. Practical realization of controlling discretization errors for elastic-plastic problems is the main focus. Numerical examples which include comparisons between the deformation and incremental theories of plasticity under tight control of discretization errors are presented.
New Methods for Assessing and Reducing Uncertainty in Microgravity Studies
NASA Astrophysics Data System (ADS)
Giniaux, J. M.; Hooper, A. J.; Bagnardi, M.
2017-12-01
Microgravity surveying, also known as dynamic or 4D gravimetry is a time-dependent geophysical method used to detect mass fluctuations within the shallow crust, by analysing temporal changes in relative gravity measurements. We present here a detailed uncertainty analysis of temporal gravity measurements, considering for the first time all possible error sources, including tilt, error in drift estimations and timing errors. We find that some error sources that are actually ignored, can have a significant impact on the total error budget and it is therefore likely that some gravity signals may have been misinterpreted in previous studies. Our analysis leads to new methods for reducing some of the uncertainties associated with residual gravity estimation. In particular, we propose different approaches for drift estimation and free air correction depending on the survey set up. We also provide formulae to recalculate uncertainties for past studies and lay out a framework for best practice in future studies. We demonstrate our new approach on volcanic case studies, which include Kilauea in Hawaii and Askja in Iceland.
Particle simulation of Coulomb collisions: Comparing the methods of Takizuka and Abe and Nanbu
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang Chiaming; Lin, Tungyou; Caflisch, Russel
2008-04-20
The interactions of charged particles in a plasma are governed by long-range Coulomb collision. We compare two widely used Monte Carlo models for Coulomb collisions. One was developed by Takizuka and Abe in 1977, the other was developed by Nanbu in 1997. We perform deterministic and statistical error analysis with respect to particle number and time step. The two models produce similar stochastic errors, but Nanbu's model gives smaller time step errors. Error comparisons between these two methods are presented.
An analysis of the least-squares problem for the DSN systematic pointing error model
NASA Technical Reports Server (NTRS)
Alvarez, L. S.
1991-01-01
A systematic pointing error model is used to calibrate antennas in the Deep Space Network. The least squares problem is described and analyzed along with the solution methods used to determine the model's parameters. Specifically studied are the rank degeneracy problems resulting from beam pointing error measurement sets that incorporate inadequate sky coverage. A least squares parameter subset selection method is described and its applicability to the systematic error modeling process is demonstrated on Voyager 2 measurement distribution.
Nevo, Daniel; Zucker, David M.; Tamimi, Rulla M.; Wang, Molin
2017-01-01
A common paradigm in dealing with heterogeneity across tumors in cancer analysis is to cluster the tumors into subtypes using marker data on the tumor, and then to analyze each of the clusters separately. A more specific target is to investigate the association between risk factors and specific subtypes and to use the results for personalized preventive treatment. This task is usually carried out in two steps–clustering and risk factor assessment. However, two sources of measurement error arise in these problems. The first is the measurement error in the biomarker values. The second is the misclassification error when assigning observations to clusters. We consider the case with a specified set of relevant markers and propose a unified single-likelihood approach for normally distributed biomarkers. As an alternative, we consider a two-step procedure with the tumor type misclassification error taken into account in the second-step risk factor analysis. We describe our method for binary data and also for survival analysis data using a modified version of the Cox model. We present asymptotic theory for the proposed estimators. Simulation results indicate that our methods significantly lower the bias with a small price being paid in terms of variance. We present an analysis of breast cancer data from the Nurses’ Health Study to demonstrate the utility of our method. PMID:27558651
System review: a method for investigating medical errors in healthcare settings.
Alexander, G L; Stone, T T
2000-01-01
System analysis is a process of evaluating objectives, resources, structure, and design of businesses. System analysis can be used by leaders to collaboratively identify breakthrough opportunities to improve system processes. In healthcare systems, system analysis can be used to review medical errors (system occurrences) that may place patients at risk for injury, disability, and/or death. This study utilizes a case management approach to identify medical errors. Utilizing an interdisciplinary approach, a System Review Team was developed to identify trends in system occurrences, facilitate communication, and enhance the quality of patient care by reducing medical errors.
A modified adjoint-based grid adaptation and error correction method for unstructured grid
NASA Astrophysics Data System (ADS)
Cui, Pengcheng; Li, Bin; Tang, Jing; Chen, Jiangtao; Deng, Youqi
2018-05-01
Grid adaptation is an important strategy to improve the accuracy of output functions (e.g. drag, lift, etc.) in computational fluid dynamics (CFD) analysis and design applications. This paper presents a modified robust grid adaptation and error correction method for reducing simulation errors in integral outputs. The procedure is based on discrete adjoint optimization theory in which the estimated global error of output functions can be directly related to the local residual error. According to this relationship, local residual error contribution can be used as an indicator in a grid adaptation strategy designed to generate refined grids for accurately estimating the output functions. This grid adaptation and error correction method is applied to subsonic and supersonic simulations around three-dimensional configurations. Numerical results demonstrate that the sensitive grids to output functions are detected and refined after grid adaptation, and the accuracy of output functions is obviously improved after error correction. The proposed grid adaptation and error correction method is shown to compare very favorably in terms of output accuracy and computational efficiency relative to the traditional featured-based grid adaptation.
Low-dimensional Representation of Error Covariance
NASA Technical Reports Server (NTRS)
Tippett, Michael K.; Cohn, Stephen E.; Todling, Ricardo; Marchesin, Dan
2000-01-01
Ensemble and reduced-rank approaches to prediction and assimilation rely on low-dimensional approximations of the estimation error covariances. Here stability properties of the forecast/analysis cycle for linear, time-independent systems are used to identify factors that cause the steady-state analysis error covariance to admit a low-dimensional representation. A useful measure of forecast/analysis cycle stability is the bound matrix, a function of the dynamics, observation operator and assimilation method. Upper and lower estimates for the steady-state analysis error covariance matrix eigenvalues are derived from the bound matrix. The estimates generalize to time-dependent systems. If much of the steady-state analysis error variance is due to a few dominant modes, the leading eigenvectors of the bound matrix approximate those of the steady-state analysis error covariance matrix. The analytical results are illustrated in two numerical examples where the Kalman filter is carried to steady state. The first example uses the dynamics of a generalized advection equation exhibiting nonmodal transient growth. Failure to observe growing modes leads to increased steady-state analysis error variances. Leading eigenvectors of the steady-state analysis error covariance matrix are well approximated by leading eigenvectors of the bound matrix. The second example uses the dynamics of a damped baroclinic wave model. The leading eigenvectors of a lowest-order approximation of the bound matrix are shown to approximate well the leading eigenvectors of the steady-state analysis error covariance matrix.
Slow Learner Errors Analysis in Solving Fractions Problems in Inclusive Junior High School Class
NASA Astrophysics Data System (ADS)
Novitasari, N.; Lukito, A.; Ekawati, R.
2018-01-01
A slow learner whose IQ is between 71 and 89 will have difficulties in solving mathematics problems that often lead to errors. The errors could be analyzed to where the errors may occur and its type. This research is qualitative descriptive which aims to describe the locations, types, and causes of slow learner errors in the inclusive junior high school class in solving the fraction problem. The subject of this research is one slow learner of seventh-grade student which was selected through direct observation by the researcher and through discussion with mathematics teacher and special tutor which handles the slow learner students. Data collection methods used in this study are written tasks and semistructured interviews. The collected data was analyzed by Newman’s Error Analysis (NEA). Results show that there are four locations of errors, namely comprehension, transformation, process skills, and encoding errors. There are four types of errors, such as concept, principle, algorithm, and counting errors. The results of this error analysis will help teachers to identify the causes of the errors made by the slow learner.
How to test validity in orthodontic research: a mixed dentition analysis example.
Donatelli, Richard E; Lee, Shin-Jae
2015-02-01
The data used to test the validity of a prediction method should be different from the data used to generate the prediction model. In this study, we explored whether an independent data set is mandatory for testing the validity of a new prediction method and how validity can be tested without independent new data. Several validation methods were compared in an example using the data from a mixed dentition analysis with a regression model. The validation errors of real mixed dentition analysis data and simulation data were analyzed for increasingly large data sets. The validation results of both the real and the simulation studies demonstrated that the leave-1-out cross-validation method had the smallest errors. The largest errors occurred in the traditional simple validation method. The differences between the validation methods diminished as the sample size increased. The leave-1-out cross-validation method seems to be an optimal validation method for improving the prediction accuracy in a data set with limited sample sizes. Copyright © 2015 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.
A novel diagnosis method for a Hall plates-based rotary encoder with a magnetic concentrator.
Meng, Bumin; Wang, Yaonan; Sun, Wei; Yuan, Xiaofang
2014-07-31
In the last few years, rotary encoders based on two-dimensional complementary metal oxide semiconductors (CMOS) Hall plates with a magnetic concentrator have been developed to measure contactless absolute angle. There are various error factors influencing the measuring accuracy, which are difficult to locate after the assembly of encoder. In this paper, a model-based rapid diagnosis method is presented. Based on an analysis of the error mechanism, an error model is built to compare minimum residual angle error and to quantify the error factors. Additionally, a modified particle swarm optimization (PSO) algorithm is used to reduce the calculated amount. The simulation and experimental results show that this diagnosis method is feasible to quantify the causes of the error and to reduce iteration significantly.
NASA Astrophysics Data System (ADS)
Chen, Yuzhen; Xie, Fugui; Liu, Xinjun; Zhou, Yanhua
2014-07-01
Parallel robots with SCARA(selective compliance assembly robot arm) motions are utilized widely in the field of high speed pick-and-place manipulation. Error modeling for these robots generally simplifies the parallelogram structures included by the robots as a link. As the established error model fails to reflect the error feature of the parallelogram structures, the effect of accuracy design and kinematic calibration based on the error model come to be undermined. An error modeling methodology is proposed to establish an error model of parallel robots with parallelogram structures. The error model can embody the geometric errors of all joints, including the joints of parallelogram structures. Thus it can contain more exhaustively the factors that reduce the accuracy of the robot. Based on the error model and some sensitivity indices defined in the sense of statistics, sensitivity analysis is carried out. Accordingly, some atlases are depicted to express each geometric error's influence on the moving platform's pose errors. From these atlases, the geometric errors that have greater impact on the accuracy of the moving platform are identified, and some sensitive areas where the pose errors of the moving platform are extremely sensitive to the geometric errors are also figured out. By taking into account the error factors which are generally neglected in all existing modeling methods, the proposed modeling method can thoroughly disclose the process of error transmission and enhance the efficacy of accuracy design and calibration.
Evaluation of assumptions in soil moisture triple collocation analysis
USDA-ARS?s Scientific Manuscript database
Triple collocation analysis (TCA) enables estimation of error variances for three or more products that retrieve or estimate the same geophysical variable using mutually-independent methods. Several statistical assumptions regarding the statistical nature of errors (e.g., mutual independence and ort...
Interpolation Method Needed for Numerical Uncertainty Analysis of Computational Fluid Dynamics
NASA Technical Reports Server (NTRS)
Groves, Curtis; Ilie, Marcel; Schallhorn, Paul
2014-01-01
Using Computational Fluid Dynamics (CFD) to predict a flow field is an approximation to the exact problem and uncertainties exist. There is a method to approximate the errors in CFD via Richardson's Extrapolation. This method is based off of progressive grid refinement. To estimate the errors in an unstructured grid, the analyst must interpolate between at least three grids. This paper describes a study to find an appropriate interpolation scheme that can be used in Richardson's extrapolation or other uncertainty method to approximate errors. Nomenclature
De Rosario, Helios; Page, Álvaro; Besa, Antonio
2017-09-06
The accurate location of the main axes of rotation (AoR) is a crucial step in many applications of human movement analysis. There are different formal methods to determine the direction and position of the AoR, whose performance varies across studies, depending on the pose and the source of errors. Most methods are based on minimizing squared differences between observed and modelled marker positions or rigid motion parameters, implicitly assuming independent and uncorrelated errors, but the largest error usually results from soft tissue artefacts (STA), which do not have such statistical properties and are not effectively cancelled out by such methods. However, with adequate methods it is possible to assume that STA only account for a small fraction of the observed motion and to obtain explicit formulas through differential analysis that relate STA components to the resulting errors in AoR parameters. In this paper such formulas are derived for three different functional calibration techniques (Geometric Fitting, mean Finite Helical Axis, and SARA), to explain why each technique behaves differently from the others, and to propose strategies to compensate for those errors. These techniques were tested with published data from a sit-to-stand activity, where the true axis was defined using bi-planar fluoroscopy. All the methods were able to estimate the direction of the AoR with an error of less than 5°, whereas there were errors in the location of the axis of 30-40mm. Such location errors could be reduced to less than 17mm by the methods based on equations that use rigid motion parameters (mean Finite Helical Axis, SARA) when the translation component was calculated using the three markers nearest to the axis. Copyright © 2017 Elsevier Ltd. All rights reserved.
Passarge, Michelle; Fix, Michael K; Manser, Peter; Stampanoni, Marco F M; Siebers, Jeffrey V
2017-04-01
To develop a robust and efficient process that detects relevant dose errors (dose errors of ≥5%) in external beam radiation therapy and directly indicates the origin of the error. The process is illustrated in the context of electronic portal imaging device (EPID)-based angle-resolved volumetric-modulated arc therapy (VMAT) quality assurance (QA), particularly as would be implemented in a real-time monitoring program. A Swiss cheese error detection (SCED) method was created as a paradigm for a cine EPID-based during-treatment QA. For VMAT, the method compares a treatment plan-based reference set of EPID images with images acquired over each 2° gantry angle interval. The process utilizes a sequence of independent consecutively executed error detection tests: an aperture check that verifies in-field radiation delivery and ensures no out-of-field radiation; output normalization checks at two different stages; global image alignment check to examine if rotation, scaling, and translation are within tolerances; pixel intensity check containing the standard gamma evaluation (3%, 3 mm) and pixel intensity deviation checks including and excluding high dose gradient regions. Tolerances for each check were determined. To test the SCED method, 12 different types of errors were selected to modify the original plan. A series of angle-resolved predicted EPID images were artificially generated for each test case, resulting in a sequence of precalculated frames for each modified treatment plan. The SCED method was applied multiple times for each test case to assess the ability to detect introduced plan variations. To compare the performance of the SCED process with that of a standard gamma analysis, both error detection methods were applied to the generated test cases with realistic noise variations. Averaged over ten test runs, 95.1% of all plan variations that resulted in relevant patient dose errors were detected within 2° and 100% within 14° (<4% of patient dose delivery). Including cases that led to slightly modified but clinically equivalent plans, 89.1% were detected by the SCED method within 2°. Based on the type of check that detected the error, determination of error sources was achieved. With noise ranging from no random noise to four times the established noise value, the averaged relevant dose error detection rate of the SCED method was between 94.0% and 95.8% and that of gamma between 82.8% and 89.8%. An EPID-frame-based error detection process for VMAT deliveries was successfully designed and tested via simulations. The SCED method was inspected for robustness with realistic noise variations, demonstrating that it has the potential to detect a large majority of relevant dose errors. Compared to a typical (3%, 3 mm) gamma analysis, the SCED method produced a higher detection rate for all introduced dose errors, identified errors in an earlier stage, displayed a higher robustness to noise variations, and indicated the error source. © 2017 American Association of Physicists in Medicine.
NASA Technical Reports Server (NTRS)
Levy, G.; Brown, R. A.
1986-01-01
A simple economical objective analysis scheme is devised and tested on real scatterometer data. It is designed to treat dense data such as those of the Seasat A Satellite Scatterometer (SASS) for individual or multiple passes, and preserves subsynoptic scale features. Errors are evaluated with the aid of sampling ('bootstrap') statistical methods. In addition, sensitivity tests have been performed which establish qualitative confidence in calculated fields of divergence and vorticity. The SASS wind algorithm could be improved; however, the data at this point are limited by instrument errors rather than analysis errors. The analysis error is typically negligible in comparison with the instrument error, but amounts to 30 percent of the instrument error in areas of strong wind shear. The scheme is very economical, and thus suitable for large volumes of dense data such as SASS data.
Skeletal Mechanism Generation of Surrogate Jet Fuels for Aeropropulsion Modeling
NASA Astrophysics Data System (ADS)
Sung, Chih-Jen; Niemeyer, Kyle E.
2010-05-01
A novel implementation for the skeletal reduction of large detailed reaction mechanisms using the directed relation graph with error propagation and sensitivity analysis (DRGEPSA) is developed and presented with skeletal reductions of two important hydrocarbon components, n-heptane and n-decane, relevant to surrogate jet fuel development. DRGEPSA integrates two previously developed methods, directed relation graph-aided sensitivity analysis (DRGASA) and directed relation graph with error propagation (DRGEP), by first applying DRGEP to efficiently remove many unimportant species prior to sensitivity analysis to further remove unimportant species, producing an optimally small skeletal mechanism for a given error limit. It is illustrated that the combination of the DRGEP and DRGASA methods allows the DRGEPSA approach to overcome the weaknesses of each previous method, specifically that DRGEP cannot identify all unimportant species and that DRGASA shields unimportant species from removal.
Linguistic Pattern Analysis of Misspellings of Typically Developing Writers in Grades 1 to 9
Bahr, Ruth Huntley; Silliman, Elaine R.; Berninger, Virginia W.; Dow, Michael
2012-01-01
Purpose A mixed methods approach, evaluating triple word form theory, was used to describe linguistic patterns of misspellings. Method Spelling errors were taken from narrative and expository writing samples provided by 888 typically developing students in grades 1–9. Errors were coded by category (phonological, orthographic, and morphological) and specific linguistic feature affected. Grade level effects were analyzed with trend analysis. Qualitative analyses determined frequent error types and how use of specific linguistic features varied across grades. Results Phonological, orthographic, and morphological errors were noted across all grades, but orthographic errors predominated. Linear trends revealed developmental shifts in error proportions for the orthographic and morphological categories between grades 4–5. Similar error types were noted across age groups but the nature of linguistic feature error changed with age. Conclusions Triple word-form theory was supported. By grade 1, orthographic errors predominated and phonological and morphological error patterns were evident. Morphological errors increased in relative frequency in older students, probably due to a combination of word-formation issues and vocabulary growth. These patterns suggest that normal spelling development reflects non-linear growth and that it takes a long time to develop a robust orthographic lexicon that coordinates phonology, orthography, and morphology and supports word-specific, conventional spelling. PMID:22473834
NASA Astrophysics Data System (ADS)
Yarmohammadi, M.; Javadi, S.; Babolian, E.
2018-04-01
In this study a new spectral iterative method (SIM) based on fractional interpolation is presented for solving nonlinear fractional differential equations (FDEs) involving Caputo derivative. This method is equipped with a pre-algorithm to find the singularity index of solution of the problem. This pre-algorithm gives us a real parameter as the index of the fractional interpolation basis, for which the SIM achieves the highest order of convergence. In comparison with some recent results about the error estimates for fractional approximations, a more accurate convergence rate has been attained. We have also proposed the order of convergence for fractional interpolation error under the L2-norm. Finally, general error analysis of SIM has been considered. The numerical results clearly demonstrate the capability of the proposed method.
Living systematic reviews: 3. Statistical methods for updating meta-analyses.
Simmonds, Mark; Salanti, Georgia; McKenzie, Joanne; Elliott, Julian
2017-11-01
A living systematic review (LSR) should keep the review current as new research evidence emerges. Any meta-analyses included in the review will also need updating as new material is identified. If the aim of the review is solely to present the best current evidence standard meta-analysis may be sufficient, provided reviewers are aware that results may change at later updates. If the review is used in a decision-making context, more caution may be needed. When using standard meta-analysis methods, the chance of incorrectly concluding that any updated meta-analysis is statistically significant when there is no effect (the type I error) increases rapidly as more updates are performed. Inaccurate estimation of any heterogeneity across studies may also lead to inappropriate conclusions. This paper considers four methods to avoid some of these statistical problems when updating meta-analyses: two methods, that is, law of the iterated logarithm and the Shuster method control primarily for inflation of type I error and two other methods, that is, trial sequential analysis and sequential meta-analysis control for type I and II errors (failing to detect a genuine effect) and take account of heterogeneity. This paper compares the methods and considers how they could be applied to LSRs. Copyright © 2017 Elsevier Inc. All rights reserved.
Influence of OPD in wavelength-shifting interferometry
NASA Astrophysics Data System (ADS)
Wang, Hongjun; Tian, Ailing; Liu, Bingcai; Dang, Juanjuan
2009-12-01
Phase-shifting interferometry is a powerful tool for high accuracy optical measurement. It operates by change the optical path length in the reference arm or test arm. This method practices by move optical device. So it has much problem when the optical device is very large and heavy. For solve this problem, the wavelength-shifting interferometry was put forwarded. In wavelength-shifting interferometry, the phase shifting angle was achieved by change the wavelength of optical source. The phase shifting angle was decided by wavelength and OPD (Optical Path Difference) between test and reference wavefront. So the OPD is an important factor to measure results. But in measurement, because the positional error and profile error of under testing optical element is exist, the phase shifting angle is different in different test point when wavelength scanning, it will introduce phase shifting angle error, so it will introduce optical surface measure error. For analysis influence of OPD on optical surface error, the relation between surface error and OPD was researched. By simulation, the relation between phase shifting error and OPD was established. By analysis, the error compensation method was put forward. After error compensation, the measure results can be improved to great extend.
Influence of OPD in wavelength-shifting interferometry
NASA Astrophysics Data System (ADS)
Wang, Hongjun; Tian, Ailing; Liu, Bingcai; Dang, Juanjuan
2010-03-01
Phase-shifting interferometry is a powerful tool for high accuracy optical measurement. It operates by change the optical path length in the reference arm or test arm. This method practices by move optical device. So it has much problem when the optical device is very large and heavy. For solve this problem, the wavelength-shifting interferometry was put forwarded. In wavelength-shifting interferometry, the phase shifting angle was achieved by change the wavelength of optical source. The phase shifting angle was decided by wavelength and OPD (Optical Path Difference) between test and reference wavefront. So the OPD is an important factor to measure results. But in measurement, because the positional error and profile error of under testing optical element is exist, the phase shifting angle is different in different test point when wavelength scanning, it will introduce phase shifting angle error, so it will introduce optical surface measure error. For analysis influence of OPD on optical surface error, the relation between surface error and OPD was researched. By simulation, the relation between phase shifting error and OPD was established. By analysis, the error compensation method was put forward. After error compensation, the measure results can be improved to great extend.
A practical method of estimating standard error of age in the fission track dating method
Johnson, N.M.; McGee, V.E.; Naeser, C.W.
1979-01-01
A first-order approximation formula for the propagation of error in the fission track age equation is given by PA = C[P2s+P2i+P2??-2rPsPi] 1 2, where PA, Ps, Pi and P?? are the percentage error of age, of spontaneous track density, of induced track density, and of neutron dose, respectively, and C is a constant. The correlation, r, between spontaneous are induced track densities is a crucial element in the error analysis, acting generally to improve the standard error of age. In addition, the correlation parameter r is instrumental is specifying the level of neutron dose, a controlled variable, which will minimize the standard error of age. The results from the approximation equation agree closely with the results from an independent statistical model for the propagation of errors in the fission-track dating method. ?? 1979.
Analysis technique for controlling system wavefront error with active/adaptive optics
NASA Astrophysics Data System (ADS)
Genberg, Victor L.; Michels, Gregory J.
2017-08-01
The ultimate goal of an active mirror system is to control system level wavefront error (WFE). In the past, the use of this technique was limited by the difficulty of obtaining a linear optics model. In this paper, an automated method for controlling system level WFE using a linear optics model is presented. An error estimate is included in the analysis output for both surface error disturbance fitting and actuator influence function fitting. To control adaptive optics, the technique has been extended to write system WFE in state space matrix form. The technique is demonstrated by example with SigFit, a commercially available tool integrating mechanical analysis with optical analysis.
Error analysis of motion correction method for laser scanning of moving objects
NASA Astrophysics Data System (ADS)
Goel, S.; Lohani, B.
2014-05-01
The limitation of conventional laser scanning methods is that the objects being scanned should be static. The need of scanning moving objects has resulted in the development of new methods capable of generating correct 3D geometry of moving objects. Limited literature is available showing development of very few methods capable of catering to the problem of object motion during scanning. All the existing methods utilize their own models or sensors. Any studies on error modelling or analysis of any of the motion correction methods are found to be lacking in literature. In this paper, we develop the error budget and present the analysis of one such `motion correction' method. This method assumes availability of position and orientation information of the moving object which in general can be obtained by installing a POS system on board or by use of some tracking devices. It then uses this information along with laser scanner data to apply correction to laser data, thus resulting in correct geometry despite the object being mobile during scanning. The major application of this method lie in the shipping industry to scan ships either moving or parked in the sea and to scan other objects like hot air balloons or aerostats. It is to be noted that the other methods of "motion correction" explained in literature can not be applied to scan the objects mentioned here making the chosen method quite unique. This paper presents some interesting insights in to the functioning of "motion correction" method as well as a detailed account of the behavior and variation of the error due to different sensor components alone and in combination with each other. The analysis can be used to obtain insights in to optimal utilization of available components for achieving the best results.
Guo, Hongbin; Renaut, Rosemary A; Chen, Kewei; Reiman, Eric M
2010-01-01
Graphical analysis methods are widely used in positron emission tomography quantification because of their simplicity and model independence. But they may, particularly for reversible kinetics, lead to bias in the estimated parameters. The source of the bias is commonly attributed to noise in the data. Assuming a two-tissue compartmental model, we investigate the bias that originates from modeling error. This bias is an intrinsic property of the simplified linear models used for limited scan durations, and it is exaggerated by random noise and numerical quadrature error. Conditions are derived under which Logan's graphical method either over- or under-estimates the distribution volume in the noise-free case. The bias caused by modeling error is quantified analytically. The presented analysis shows that the bias of graphical methods is inversely proportional to the dissociation rate. Furthermore, visual examination of the linearity of the Logan plot is not sufficient for guaranteeing that equilibrium has been reached. A new model which retains the elegant properties of graphical analysis methods is presented, along with a numerical algorithm for its solution. We perform simulations with the fibrillar amyloid β radioligand [11C] benzothiazole-aniline using published data from the University of Pittsburgh and Rotterdam groups. The results show that the proposed method significantly reduces the bias due to modeling error. Moreover, the results for data acquired over a 70 minutes scan duration are at least as good as those obtained using existing methods for data acquired over a 90 minutes scan duration. PMID:20493196
Analysis on optical heterodyne frequency error of full-field heterodyne interferometer
NASA Astrophysics Data System (ADS)
Li, Yang; Zhang, Wenxi; Wu, Zhou; Lv, Xiaoyu; Kong, Xinxin; Guo, Xiaoli
2017-06-01
The full-field heterodyne interferometric measurement technology is beginning better applied by employing low frequency heterodyne acousto-optical modulators instead of complex electro-mechanical scanning devices. The optical element surface could be directly acquired by synchronously detecting the received signal phases of each pixel, because standard matrix detector as CCD and CMOS cameras could be used in heterodyne interferometer. Instead of the traditional four-step phase shifting phase calculating, Fourier spectral analysis method is used for phase extracting which brings lower sensitivity to sources of uncertainty and higher measurement accuracy. In this paper, two types of full-field heterodyne interferometer are described whose advantages and disadvantages are also specified. Heterodyne interferometer has to combine two different frequency beams to produce interference, which brings a variety of optical heterodyne frequency errors. Frequency mixing error and beat frequency error are two different kinds of inescapable heterodyne frequency errors. In this paper, the effects of frequency mixing error to surface measurement are derived. The relationship between the phase extraction accuracy and the errors are calculated. :: The tolerance of the extinction ratio of polarization splitting prism and the signal-to-noise ratio of stray light is given. The error of phase extraction by Fourier analysis that caused by beat frequency shifting is derived and calculated. We also propose an improved phase extraction method based on spectrum correction. An amplitude ratio spectrum correction algorithm with using Hanning window is used to correct the heterodyne signal phase extraction. The simulation results show that this method can effectively suppress the degradation of phase extracting caused by beat frequency error and reduce the measurement uncertainty of full-field heterodyne interferometer.
Caprihan, A; Pearlson, G D; Calhoun, V D
2008-08-15
Principal component analysis (PCA) is often used to reduce the dimension of data before applying more sophisticated data analysis methods such as non-linear classification algorithms or independent component analysis. This practice is based on selecting components corresponding to the largest eigenvalues. If the ultimate goal is separation of data in two groups, then these set of components need not have the most discriminatory power. We measured the distance between two such populations using Mahalanobis distance and chose the eigenvectors to maximize it, a modified PCA method, which we call the discriminant PCA (DPCA). DPCA was applied to diffusion tensor-based fractional anisotropy images to distinguish age-matched schizophrenia subjects from healthy controls. The performance of the proposed method was evaluated by the one-leave-out method. We show that for this fractional anisotropy data set, the classification error with 60 components was close to the minimum error and that the Mahalanobis distance was twice as large with DPCA, than with PCA. Finally, by masking the discriminant function with the white matter tracts of the Johns Hopkins University atlas, we identified left superior longitudinal fasciculus as the tract which gave the least classification error. In addition, with six optimally chosen tracts the classification error was zero.
The, Bertram; Flivik, Gunnar; Diercks, Ron L; Verdonschot, Nico
2008-03-01
Wear curves from individual patients often show unexplained irregular wear curves or impossible values (negative wear). We postulated errors of two-dimensional wear measurements are mainly the result of radiographic projection differences. We tested a new method that makes two-dimensional wear measurements less sensitive for radiograph projection differences of cemented THAs. The measurement errors that occur when radiographically projecting a three-dimensional THA were modeled. Based on the model, we developed a method to reduce the errors, thus approximating three-dimensional linear wear values, which are less sensitive for projection differences. An error analysis was performed by virtually simulating 144 wear measurements under varying conditions with and without application of the correction: the mean absolute error was reduced from 1.8 mm (range, 0-4.51 mm) to 0.11 mm (range, 0-0.27 mm). For clinical validation, radiostereometric analysis was performed on 47 patients to determine the true wear at 1, 2, and 5 years. Subsequently, wear was measured on conventional radiographs with and without the correction: the overall occurrence of errors greater than 0.2 mm was reduced from 35% to 15%. Wear measurements are less sensitive to differences in two-dimensional projection of the THA when using the correction method.
Error Analysis and Validation for Insar Height Measurement Induced by Slant Range
NASA Astrophysics Data System (ADS)
Zhang, X.; Li, T.; Fan, W.; Geng, X.
2018-04-01
InSAR technique is an important method for large area DEM extraction. Several factors have significant influence on the accuracy of height measurement. In this research, the effect of slant range measurement for InSAR height measurement was analysis and discussed. Based on the theory of InSAR height measurement, the error propagation model was derived assuming no coupling among different factors, which directly characterise the relationship between slant range error and height measurement error. Then the theoretical-based analysis in combination with TanDEM-X parameters was implemented to quantitatively evaluate the influence of slant range error to height measurement. In addition, the simulation validation of InSAR error model induced by slant range was performed on the basis of SRTM DEM and TanDEM-X parameters. The spatial distribution characteristics and error propagation rule of InSAR height measurement were further discussed and evaluated.
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.
An investigation of error characteristics and coding performance
NASA Technical Reports Server (NTRS)
Ebel, William J.; Ingels, Frank M.
1993-01-01
The first year's effort on NASA Grant NAG5-2006 was an investigation to characterize typical errors resulting from the EOS dorn link. The analysis methods developed for this effort were used on test data from a March 1992 White Sands Terminal Test. The effectiveness of a concatenated coding scheme of a Reed Solomon outer code and a convolutional inner code versus a Reed Solomon only code scheme has been investigated as well as the effectiveness of a Periodic Convolutional Interleaver in dispersing errors of certain types. The work effort consisted of development of software that allows simulation studies with the appropriate coding schemes plus either simulated data with errors or actual data with errors. The software program is entitled Communication Link Error Analysis (CLEAN) and models downlink errors, forward error correcting schemes, and interleavers.
Error Propagation Made Easy--Or at Least Easier
ERIC Educational Resources Information Center
Gardenier, George H.; Gui, Feng; Demas, James N.
2011-01-01
Complex error propagation is reduced to formula and data entry into a Mathcad worksheet or an Excel spreadsheet. The Mathcad routine uses both symbolic calculus analysis and Monte Carlo methods to propagate errors in a formula of up to four variables. Graphical output is used to clarify the contributions to the final error of each of the…
Generation 1.5 Written Error Patterns: A Comparative Study
ERIC Educational Resources Information Center
Doolan, Stephen M.; Miller, Donald
2012-01-01
In an attempt to contribute to existing research on Generation 1.5 students, the current study uses quantitative and qualitative methods to compare error patterns in a corpus of Generation 1.5, L1, and L2 community college student writing. This error analysis provides one important way to determine if error patterns in Generation 1.5 student…
NASA Technical Reports Server (NTRS)
Martos, Borja; Kiszely, Paul; Foster, John V.
2011-01-01
As part of the NASA Aviation Safety Program (AvSP), a novel pitot-static calibration method was developed to allow rapid in-flight calibration for subscale aircraft while flying within confined test areas. This approach uses Global Positioning System (GPS) technology coupled with modern system identification methods that rapidly computes optimal pressure error models over a range of airspeed with defined confidence bounds. This method has been demonstrated in subscale flight tests and has shown small 2- error bounds with significant reduction in test time compared to other methods. The current research was motivated by the desire to further evaluate and develop this method for full-scale aircraft. A goal of this research was to develop an accurate calibration method that enables reductions in test equipment and flight time, thus reducing costs. The approach involved analysis of data acquisition requirements, development of efficient flight patterns, and analysis of pressure error models based on system identification methods. Flight tests were conducted at The University of Tennessee Space Institute (UTSI) utilizing an instrumented Piper Navajo research aircraft. In addition, the UTSI engineering flight simulator was used to investigate test maneuver requirements and handling qualities issues associated with this technique. This paper provides a summary of piloted simulation and flight test results that illustrates the performance and capabilities of the NASA calibration method. Discussion of maneuver requirements and data analysis methods is included as well as recommendations for piloting technique.
NASA Technical Reports Server (NTRS)
Long, S. A. T.
1973-01-01
The triangulation method developed specifically for the Barium Ion Cloud Project is discussed. Expression for the four displacement errors, the three slope errors, and the curvature error in the triangulation solution due to a probable error in the lines-of-sight from the observation stations to points on the cloud are derived. The triangulation method is then used to determine the effect of the following on these different errors in the solution: the number and location of the stations, the observation duration, east-west cloud drift, the number of input data points, and the addition of extra cameras to one of the stations. The pointing displacement errors, and the pointing slope errors are compared. The displacement errors in the solution due to a probable error in the position of a moving station plus the weighting factors for the data from the moving station are also determined.
Cheng, Ching-Min; Hwang, Sheue-Ling
2015-03-01
This paper outlines the human error identification (HEI) techniques that currently exist to assess latent human errors. Many formal error identification techniques have existed for years, but few have been validated to cover latent human error analysis in different domains. This study considers many possible error modes and influential factors, including external error modes, internal error modes, psychological error mechanisms, and performance shaping factors, and integrates several execution procedures and frameworks of HEI techniques. The case study in this research was the operational process of changing chemical cylinders in a factory. In addition, the integrated HEI method was used to assess the operational processes and the system's reliability. It was concluded that the integrated method is a valuable aid to develop much safer operational processes and can be used to predict human error rates on critical tasks in the plant. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.
NASA Astrophysics Data System (ADS)
Owens, P. R.; Libohova, Z.; Seybold, C. A.; Wills, S. A.; Peaslee, S.; Beaudette, D.; Lindbo, D. L.
2017-12-01
The measurement errors and spatial prediction uncertainties of soil properties in the modeling community are usually assessed against measured values when available. However, of equal importance is the assessment of errors and uncertainty impacts on cost benefit analysis and risk assessments. Soil pH was selected as one of the most commonly measured soil properties used for liming recommendations. The objective of this study was to assess the error size from different sources and their implications with respect to management decisions. Error sources include measurement methods, laboratory sources, pedotransfer functions, database transections, spatial aggregations, etc. Several databases of measured and predicted soil pH were used for this study including the United States National Cooperative Soil Survey Characterization Database (NCSS-SCDB), the US Soil Survey Geographic (SSURGO) Database. The distribution of errors among different sources from measurement methods to spatial aggregation showed a wide range of values. The greatest RMSE of 0.79 pH units was from spatial aggregation (SSURGO vs Kriging), while the measurement methods had the lowest RMSE of 0.06 pH units. Assuming the order of data acquisition based on the transaction distance i.e. from measurement method to spatial aggregation the RMSE increased from 0.06 to 0.8 pH units suggesting an "error propagation". This has major implications for practitioners and modeling community. Most soil liming rate recommendations are based on 0.1 pH unit increments, while the desired soil pH level increments are based on 0.4 to 0.5 pH units. Thus, even when the measured and desired target soil pH are the same most guidelines recommend 1 ton ha-1 lime, which translates in 111 ha-1 that the farmer has to factor in the cost-benefit analysis. However, this analysis need to be based on uncertainty predictions (0.5-1.0 pH units) rather than measurement errors (0.1 pH units) which would translate in 555-1,111 investment that need to be assessed against the risk. The modeling community can benefit from such analysis, however, error size and spatial distribution for global and regional predictions need to be assessed against the variability of other drivers and impact on management decisions.
Optimization and Experimentation of Dual-Mass MEMS Gyroscope Quadrature Error Correction Methods
Cao, Huiliang; Li, Hongsheng; Kou, Zhiwei; Shi, Yunbo; Tang, Jun; Ma, Zongmin; Shen, Chong; Liu, Jun
2016-01-01
This paper focuses on an optimal quadrature error correction method for the dual-mass MEMS gyroscope, in order to reduce the long term bias drift. It is known that the coupling stiffness and demodulation error are important elements causing bias drift. The coupling stiffness in dual-mass structures is analyzed. The experiment proves that the left and right masses’ quadrature errors are different, and the quadrature correction system should be arranged independently. The process leading to quadrature error is proposed, and the Charge Injecting Correction (CIC), Quadrature Force Correction (QFC) and Coupling Stiffness Correction (CSC) methods are introduced. The correction objects of these three methods are the quadrature error signal, force and the coupling stiffness, respectively. The three methods are investigated through control theory analysis, model simulation and circuit experiments, and the results support the theoretical analysis. The bias stability results based on CIC, QFC and CSC are 48 °/h, 9.9 °/h and 3.7 °/h, respectively, and this value is 38 °/h before quadrature error correction. The CSC method is proved to be the better method for quadrature correction, and it improves the Angle Random Walking (ARW) value, increasing it from 0.66 °/√h to 0.21 °/√h. The CSC system general test results show that it works well across the full temperature range, and the bias stabilities of the six groups’ output data are 3.8 °/h, 3.6 °/h, 3.4 °/h, 3.1 °/h, 3.0 °/h and 4.2 °/h, respectively, which proves the system has excellent repeatability. PMID:26751455
Optimization and Experimentation of Dual-Mass MEMS Gyroscope Quadrature Error Correction Methods.
Cao, Huiliang; Li, Hongsheng; Kou, Zhiwei; Shi, Yunbo; Tang, Jun; Ma, Zongmin; Shen, Chong; Liu, Jun
2016-01-07
This paper focuses on an optimal quadrature error correction method for the dual-mass MEMS gyroscope, in order to reduce the long term bias drift. It is known that the coupling stiffness and demodulation error are important elements causing bias drift. The coupling stiffness in dual-mass structures is analyzed. The experiment proves that the left and right masses' quadrature errors are different, and the quadrature correction system should be arranged independently. The process leading to quadrature error is proposed, and the Charge Injecting Correction (CIC), Quadrature Force Correction (QFC) and Coupling Stiffness Correction (CSC) methods are introduced. The correction objects of these three methods are the quadrature error signal, force and the coupling stiffness, respectively. The three methods are investigated through control theory analysis, model simulation and circuit experiments, and the results support the theoretical analysis. The bias stability results based on CIC, QFC and CSC are 48 °/h, 9.9 °/h and 3.7 °/h, respectively, and this value is 38 °/h before quadrature error correction. The CSC method is proved to be the better method for quadrature correction, and it improves the Angle Random Walking (ARW) value, increasing it from 0.66 °/√h to 0.21 °/√h. The CSC system general test results show that it works well across the full temperature range, and the bias stabilities of the six groups' output data are 3.8 °/h, 3.6 °/h, 3.4 °/h, 3.1 °/h, 3.0 °/h and 4.2 °/h, respectively, which proves the system has excellent repeatability.
Synthesis and optimization of four bar mechanism with six design parameters
NASA Astrophysics Data System (ADS)
Jaiswal, Ankur; Jawale, H. P.
2018-04-01
Function generation is synthesis of mechanism for specific task, involves complexity for specially synthesis above five precision of coupler points. Thus pertains to large structural error. The methodology for arriving to better precision solution is to use the optimization technique. Work presented herein considers methods of optimization of structural error in closed kinematic chain with single degree of freedom, for generating functions like log(x), ex, tan(x), sin(x) with five precision points. The equation in Freudenstein-Chebyshev method is used to develop five point synthesis of mechanism. The extended formulation is proposed and results are obtained to verify existing results in literature. Optimization of structural error is carried out using least square approach. Comparative structural error analysis is presented on optimized error through least square method and extended Freudenstein-Chebyshev method.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cao, Junjie; Jia, Hongzhi, E-mail: hzjia@usst.edu.cn
2015-11-15
We propose error analysis using a rotating coordinate system with three parameters of linearly polarized light—incidence angle, azimuth angle on the front surface, and angle between the incidence and vibration planes—and demonstrate the method on a rotating birefringent prism system. The transmittance and angles are calculated plane-by-plane using a birefringence ellipsoid model and the final transmitted intensity equation is deduced. The effects of oblique incidence, light interference, beam convergence, and misalignment of the rotation and prism axes are discussed. We simulate the entire error model using MATLAB and conduct experiments based on a built polarimeter. The simulation and experimental resultsmore » are consistent and demonstrate the rationality and validity of this method.« less
Particle Simulation of Coulomb Collisions: Comparing the Methods of Takizuka & Abe and Nanbu
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, C; Lin, T; Caflisch, R
2007-05-22
The interactions of charged particles in a plasma are in a plasma is governed by the long-range Coulomb collision. We compare two widely used Monte Carlo models for Coulomb collisions. One was developed by Takizuka and Abe in 1977, the other was developed by Nanbu in 1997. We perform deterministic and stochastic error analysis with respect to particle number and time step. The two models produce similar stochastic errors, but Nanbu's model gives smaller time step errors. Error comparisons between these two methods are presented.
Suppression of vapor cell temperature error for spin-exchange-relaxation-free magnetometer
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lu, Jixi, E-mail: lujixi@buaa.edu.cn; Qian, Zheng; Fang, Jiancheng
2015-08-15
This paper presents a method to reduce the vapor cell temperature error of the spin-exchange-relaxation-free (SERF) magnetometer. The fluctuation of cell temperature can induce variations of the optical rotation angle, resulting in a scale factor error of the SERF magnetometer. In order to suppress this error, we employ the variation of the probe beam absorption to offset the variation of the optical rotation angle. The theoretical discussion of our method indicates that the scale factor error introduced by the fluctuation of the cell temperature could be suppressed by setting the optical depth close to one. In our experiment, we adjustmore » the probe frequency to obtain various optical depths and then measure the variation of scale factor with respect to the corresponding cell temperature changes. Our experimental results show a good agreement with our theoretical analysis. Under our experimental condition, the error has been reduced significantly compared with those when the probe wavelength is adjusted to maximize the probe signal. The cost of this method is the reduction of the scale factor of the magnetometer. However, according to our analysis, it only has minor effect on the sensitivity under proper operating parameters.« less
Neural Network and Regression Methods Demonstrated in the Design Optimization of a Subsonic Aircraft
NASA Technical Reports Server (NTRS)
Hopkins, Dale A.; Lavelle, Thomas M.; Patnaik, Surya
2003-01-01
The neural network and regression methods of NASA Glenn Research Center s COMETBOARDS design optimization testbed were used to generate approximate analysis and design models for a subsonic aircraft operating at Mach 0.85 cruise speed. The analytical model is defined by nine design variables: wing aspect ratio, engine thrust, wing area, sweep angle, chord-thickness ratio, turbine temperature, pressure ratio, bypass ratio, fan pressure; and eight response parameters: weight, landing velocity, takeoff and landing field lengths, approach thrust, overall efficiency, and compressor pressure and temperature. The variables were adjusted to optimally balance the engines to the airframe. The solution strategy included a sensitivity model and the soft analysis model. Researchers generated the sensitivity model by training the approximators to predict an optimum design. The trained neural network predicted all response variables, within 5-percent error. This was reduced to 1 percent by the regression method. The soft analysis model was developed to replace aircraft analysis as the reanalyzer in design optimization. Soft models have been generated for a neural network method, a regression method, and a hybrid method obtained by combining the approximators. The performance of the models is graphed for aircraft weight versus thrust as well as for wing area and turbine temperature. The regression method followed the analytical solution with little error. The neural network exhibited 5-percent maximum error over all parameters. Performance of the hybrid method was intermediate in comparison to the individual approximators. Error in the response variable is smaller than that shown in the figure because of a distortion scale factor. The overall performance of the approximators was considered to be satisfactory because aircraft analysis with NASA Langley Research Center s FLOPS (Flight Optimization System) code is a synthesis of diverse disciplines: weight estimation, aerodynamic analysis, engine cycle analysis, propulsion data interpolation, mission performance, airfield length for landing and takeoff, noise footprint, and others.
Yang, Yanqiang; Zhang, Chunxi; Lu, Jiazhen
2017-01-16
Strapdown inertial navigation system/celestial navigation system (SINS/CNS) integrated navigation is a fully autonomous and high precision method, which has been widely used to improve the hitting accuracy and quick reaction capability of near-Earth flight vehicles. The installation errors between SINS and star sensors have been one of the main factors that restrict the actual accuracy of SINS/CNS. In this paper, an integration algorithm based on the star vector observations is derived considering the star sensor installation error. Then, the star sensor installation error is accurately estimated based on Kalman Filtering (KF). Meanwhile, a local observability analysis is performed on the rank of observability matrix obtained via linearization observation equation, and the observable conditions are presented and validated. The number of star vectors should be greater than or equal to 2, and the times of posture adjustment also should be greater than or equal to 2. Simulations indicate that the star sensor installation error could be readily observable based on the maneuvering condition; moreover, the attitude errors of SINS are less than 7 arc-seconds. This analysis method and conclusion are useful in the ballistic trajectory design of near-Earth flight vehicles.
Nevo, Daniel; Zucker, David M; Tamimi, Rulla M; Wang, Molin
2016-12-30
A common paradigm in dealing with heterogeneity across tumors in cancer analysis is to cluster the tumors into subtypes using marker data on the tumor, and then to analyze each of the clusters separately. A more specific target is to investigate the association between risk factors and specific subtypes and to use the results for personalized preventive treatment. This task is usually carried out in two steps-clustering and risk factor assessment. However, two sources of measurement error arise in these problems. The first is the measurement error in the biomarker values. The second is the misclassification error when assigning observations to clusters. We consider the case with a specified set of relevant markers and propose a unified single-likelihood approach for normally distributed biomarkers. As an alternative, we consider a two-step procedure with the tumor type misclassification error taken into account in the second-step risk factor analysis. We describe our method for binary data and also for survival analysis data using a modified version of the Cox model. We present asymptotic theory for the proposed estimators. Simulation results indicate that our methods significantly lower the bias with a small price being paid in terms of variance. We present an analysis of breast cancer data from the Nurses' Health Study to demonstrate the utility of our method. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
High-Dimensional Heteroscedastic Regression with an Application to eQTL Data Analysis
Daye, Z. John; Chen, Jinbo; Li, Hongzhe
2011-01-01
Summary We consider the problem of high-dimensional regression under non-constant error variances. Despite being a common phenomenon in biological applications, heteroscedasticity has, so far, been largely ignored in high-dimensional analysis of genomic data sets. We propose a new methodology that allows non-constant error variances for high-dimensional estimation and model selection. Our method incorporates heteroscedasticity by simultaneously modeling both the mean and variance components via a novel doubly regularized approach. Extensive Monte Carlo simulations indicate that our proposed procedure can result in better estimation and variable selection than existing methods when heteroscedasticity arises from the presence of predictors explaining error variances and outliers. Further, we demonstrate the presence of heteroscedasticity in and apply our method to an expression quantitative trait loci (eQTLs) study of 112 yeast segregants. The new procedure can automatically account for heteroscedasticity in identifying the eQTLs that are associated with gene expression variations and lead to smaller prediction errors. These results demonstrate the importance of considering heteroscedasticity in eQTL data analysis. PMID:22547833
Analysis of real-time numerical integration methods applied to dynamic clamp experiments.
Butera, Robert J; McCarthy, Maeve L
2004-12-01
Real-time systems are frequently used as an experimental tool, whereby simulated models interact in real time with neurophysiological experiments. The most demanding of these techniques is known as the dynamic clamp, where simulated ion channel conductances are artificially injected into a neuron via intracellular electrodes for measurement and stimulation. Methodologies for implementing the numerical integration of the gating variables in real time typically employ first-order numerical methods, either Euler or exponential Euler (EE). EE is often used for rapidly integrating ion channel gating variables. We find via simulation studies that for small time steps, both methods are comparable, but at larger time steps, EE performs worse than Euler. We derive error bounds for both methods, and find that the error can be characterized in terms of two ratios: time step over time constant, and voltage measurement error over the slope factor of the steady-state activation curve of the voltage-dependent gating variable. These ratios reliably bound the simulation error and yield results consistent with the simulation analysis. Our bounds quantitatively illustrate how measurement error restricts the accuracy that can be obtained by using smaller step sizes. Finally, we demonstrate that Euler can be computed with identical computational efficiency as EE.
NASA Astrophysics Data System (ADS)
Shinnaka, Shinji
This paper presents a new unified analysis of estimate errors by model-matching extended-back-EMF estimation methods for sensorless drive of permanent-magnet synchronous motors. Analytical solutions about estimate errors, whose validity is confirmed by numerical experiments, are rich in universality and applicability. As an example of universality and applicability, a new trajectory-oriented vector control method is proposed, which can realize directly quasi-optimal strategy minimizing total losses with no additional computational loads by simply orienting one of vector-control coordinates to the associated quasi-optimal trajectory. The coordinate orientation rule, which is analytically derived, is surprisingly simple. Consequently the trajectory-oriented vector control method can be applied to a number of conventional vector control systems using model-matching extended-back-EMF estimation methods.
NASA Technical Reports Server (NTRS)
Litvin, F. L.; Handschuh, R. F.; Zhang, J.
1988-01-01
A method for generation of crowned pinion tooth surfaces using a surface of revolution is developed. The crowned pinion meshes with a regular involute gear and has a prescribed parabolic type of transmission errors when the gears operate in the aligned mode. When the gears are misaligned the transmission error remains parabolic with the maximum level still remaining very small (less than 0.34 arc second for the numerical examples). Tooth Contact Analysis (TCA) is used to simulate the conditions of meshing, determine the transmission error, and the bearing contact.
Human error mitigation initiative (HEMI) : summary report.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stevens, Susan M.; Ramos, M. Victoria; Wenner, Caren A.
2004-11-01
Despite continuing efforts to apply existing hazard analysis methods and comply with requirements, human errors persist across the nuclear weapons complex. Due to a number of factors, current retroactive and proactive methods to understand and minimize human error are highly subjective, inconsistent in numerous dimensions, and are cumbersome to characterize as thorough. An alternative and proposed method begins with leveraging historical data to understand what the systemic issues are and where resources need to be brought to bear proactively to minimize the risk of future occurrences. An illustrative analysis was performed using existing incident databases specific to Pantex weapons operationsmore » indicating systemic issues associated with operating procedures that undergo notably less development rigor relative to other task elements such as tooling and process flow. Future recommended steps to improve the objectivity, consistency, and thoroughness of hazard analysis and mitigation were delineated.« less
[Validation of a method for notifying and monitoring medication errors in pediatrics].
Guerrero-Aznar, M D; Jiménez-Mesa, E; Cotrina-Luque, J; Villalba-Moreno, A; Cumplido-Corbacho, R; Fernández-Fernández, L
2014-12-01
To analyze the impact of a multidisciplinary and decentralized safety committee in the pediatric management unit, and the joint implementation of a computing network application for reporting medication errors, monitoring the follow-up of the errors, and an analysis of the improvements introduced. An observational, descriptive, cross-sectional, pre-post intervention study was performed. An analysis was made of medication errors reported to the central safety committee in the twelve months prior to introduction, and those reported to the decentralized safety committee in the management unit in the nine months after implementation, using the computer application, and the strategies generated by the analysis of reported errors. Number of reported errors/10,000 days of stay, number of reported errors with harm per 10,000 days of stay, types of error, categories based on severity, stage of the process, and groups involved in the notification of medication errors. Reported medication errors increased 4.6 -fold, from 7.6 notifications of medication errors per 10,000 days of stay in the pre-intervention period to 36 in the post-intervention, rate ratio 0.21 (95% CI; 0.11-0.39) (P<.001). The medication errors with harm or requiring monitoring reported per 10,000 days of stay, was virtually unchanged from one period to the other ratio rate 0,77 (95% IC; 0,31-1,91) (P>.05). The notification of potential errors or errors without harm per 10,000 days of stay increased 17.4-fold (rate ratio 0.005., 95% CI; 0.001-0.026, P<.001). The increase in medication errors notified in the post-intervention period is a reflection of an increase in the motivation of health professionals to report errors through this new method. Copyright © 2013 Asociación Española de Pediatría. Published by Elsevier Espana. All rights reserved.
Comparative test on several forms of background error covariance in 3DVar
NASA Astrophysics Data System (ADS)
Shao, Aimei
2013-04-01
The background error covariance matrix (Hereinafter referred to as B matrix) plays an important role in the three-dimensional variational (3DVar) data assimilation method. However, it is difficult to get B matrix accurately because true atmospheric state is unknown. Therefore, some methods were developed to estimate B matrix (e.g. NMC method, innovation analysis method, recursive filters, and ensemble method such as EnKF). Prior to further development and application of these methods, the function of several B matrixes estimated by these methods in 3Dvar is worth studying and evaluating. For this reason, NCEP reanalysis data and forecast data are used to test the effectiveness of the several B matrixes with VAF (Huang, 1999) method. Here the NCEP analysis is treated as the truth and in this case the forecast error is known. The data from 2006 to 2007 is used as the samples to estimate B matrix and the data in 2008 is used to verify the assimilation effects. The 48h and 24h forecast valid at the same time is used to estimate B matrix with NMC method. B matrix can be represented by a correlation part (a non-diagonal matrix) and a variance part (a diagonal matrix of variances). Gaussian filter function as an approximate approach is used to represent the variation of correlation coefficients with distance in numerous 3DVar systems. On the basis of the assumption, the following several forms of B matrixes are designed and test with VAF in the comparative experiments: (1) error variance and the characteristic lengths are fixed and setted to their mean value averaged over the analysis domain; (2) similar to (1), but the mean characteristic lengths reduce to 50 percent for the height and 60 percent for the temperature of the original; (3) similar to (2), but error variance calculated directly by the historical data is space-dependent; (4) error variance and characteristic lengths are all calculated directly by the historical data; (5) B matrix is estimated directly by the historical data; (6) similar to (5), but a localization process is performed; (7) B matrix is estimated by NMC method but error variance is reduced by 1.7 times in order that the value is close to that calculated from the true forecast error samples; (8) similar to (7), but the localization similar to (6) is performed. Experimental results with the different B matrixes show that for the Gaussian-type B matrix the characteristic lengths calculated from the true error samples don't bring a good analysis results. However, the reduced characteristic lengths (about half of the original one) can lead to a good analysis. If the B matrix estimated directly from the historical data is used in 3DVar, the assimilation effect can not reach to the best. The better assimilation results are generated with the application of reduced characteristic length and localization. Even so, it hasn't obvious advantage compared with Gaussian-type B matrix with the optimal characteristic length. It implies that the Gaussian-type B matrix, widely used for operational 3DVar system, can get a good analysis with the appropriate characteristic lengths. The crucial problem is how to determine the appropriate characteristic lengths. (This work is supported by the National Natural Science Foundation of China (41275102, 40875063), and the Fundamental Research Funds for the Central Universities (lzujbky-2010-9) )
Robustness of Type I Error and Power in Set Correlation Analysis of Contingency Tables.
ERIC Educational Resources Information Center
Cohen, Jacob; Nee, John C. M.
1990-01-01
The analysis of contingency tables via set correlation allows the assessment of subhypotheses involving contrast functions of the categories of the nominal scales. The robustness of such methods with regard to Type I error and statistical power was studied via a Monte Carlo experiment. (TJH)
NASA Astrophysics Data System (ADS)
Zheng, Yuejiu; Ouyang, Minggao; Han, Xuebing; Lu, Languang; Li, Jianqiu
2018-02-01
Sate of charge (SOC) estimation is generally acknowledged as one of the most important functions in battery management system for lithium-ion batteries in new energy vehicles. Though every effort is made for various online SOC estimation methods to reliably increase the estimation accuracy as much as possible within the limited on-chip resources, little literature discusses the error sources for those SOC estimation methods. This paper firstly reviews the commonly studied SOC estimation methods from a conventional classification. A novel perspective focusing on the error analysis of the SOC estimation methods is proposed. SOC estimation methods are analyzed from the views of the measured values, models, algorithms and state parameters. Subsequently, the error flow charts are proposed to analyze the error sources from the signal measurement to the models and algorithms for the widely used online SOC estimation methods in new energy vehicles. Finally, with the consideration of the working conditions, choosing more reliable and applicable SOC estimation methods is discussed, and the future development of the promising online SOC estimation methods is suggested.
2013-01-01
Background The production of multiple transcript isoforms from one gene is a major source of transcriptome complexity. RNA-Seq experiments, in which transcripts are converted to cDNA and sequenced, allow the resolution and quantification of alternative transcript isoforms. However, methods to analyze splicing are underdeveloped and errors resulting in incorrect splicing calls occur in every experiment. Results We used RNA-Seq data to develop sequencing and aligner error models. By applying these error models to known input from simulations, we found that errors result from false alignment to minor splice motifs and antisense stands, shifted junction positions, paralog joining, and repeat induced gaps. By using a series of quantitative and qualitative filters, we eliminated diagnosed errors in the simulation, and applied this to RNA-Seq data from Drosophila melanogaster heads. We used high-confidence junction detections to specifically interrogate local splicing differences between transcripts. This method out-performed commonly used RNA-seq methods to identify known alternative splicing events in the Drosophila sex determination pathway. We describe a flexible software package to perform these tasks called Splicing Analysis Kit (Spanki), available at http://www.cbcb.umd.edu/software/spanki. Conclusions Splice-junction centric analysis of RNA-Seq data provides advantages in specificity for detection of alternative splicing. Our software provides tools to better understand error profiles in RNA-Seq data and improve inference from this new technology. The splice-junction centric approach that this software enables will provide more accurate estimates of differentially regulated splicing than current tools. PMID:24209455
Sturgill, David; Malone, John H; Sun, Xia; Smith, Harold E; Rabinow, Leonard; Samson, Marie-Laure; Oliver, Brian
2013-11-09
The production of multiple transcript isoforms from one gene is a major source of transcriptome complexity. RNA-Seq experiments, in which transcripts are converted to cDNA and sequenced, allow the resolution and quantification of alternative transcript isoforms. However, methods to analyze splicing are underdeveloped and errors resulting in incorrect splicing calls occur in every experiment. We used RNA-Seq data to develop sequencing and aligner error models. By applying these error models to known input from simulations, we found that errors result from false alignment to minor splice motifs and antisense stands, shifted junction positions, paralog joining, and repeat induced gaps. By using a series of quantitative and qualitative filters, we eliminated diagnosed errors in the simulation, and applied this to RNA-Seq data from Drosophila melanogaster heads. We used high-confidence junction detections to specifically interrogate local splicing differences between transcripts. This method out-performed commonly used RNA-seq methods to identify known alternative splicing events in the Drosophila sex determination pathway. We describe a flexible software package to perform these tasks called Splicing Analysis Kit (Spanki), available at http://www.cbcb.umd.edu/software/spanki. Splice-junction centric analysis of RNA-Seq data provides advantages in specificity for detection of alternative splicing. Our software provides tools to better understand error profiles in RNA-Seq data and improve inference from this new technology. The splice-junction centric approach that this software enables will provide more accurate estimates of differentially regulated splicing than current tools.
Stekel, Dov J.; Sarti, Donatella; Trevino, Victor; Zhang, Lihong; Salmon, Mike; Buckley, Chris D.; Stevens, Mark; Pallen, Mark J.; Penn, Charles; Falciani, Francesco
2005-01-01
A key step in the analysis of microarray data is the selection of genes that are differentially expressed. Ideally, such experiments should be properly replicated in order to infer both technical and biological variability, and the data should be subjected to rigorous hypothesis tests to identify the differentially expressed genes. However, in microarray experiments involving the analysis of very large numbers of biological samples, replication is not always practical. Therefore, there is a need for a method to select differentially expressed genes in a rational way from insufficiently replicated data. In this paper, we describe a simple method that uses bootstrapping to generate an error model from a replicated pilot study that can be used to identify differentially expressed genes in subsequent large-scale studies on the same platform, but in which there may be no replicated arrays. The method builds a stratified error model that includes array-to-array variability, feature-to-feature variability and the dependence of error on signal intensity. We apply this model to the characterization of the host response in a model of bacterial infection of human intestinal epithelial cells. We demonstrate the effectiveness of error model based microarray experiments and propose this as a general strategy for a microarray-based screening of large collections of biological samples. PMID:15800204
Advancing the research agenda for diagnostic error reduction.
Zwaan, Laura; Schiff, Gordon D; Singh, Hardeep
2013-10-01
Diagnostic errors remain an underemphasised and understudied area of patient safety research. We briefly summarise the methods that have been used to conduct research on epidemiology, contributing factors and interventions related to diagnostic error and outline directions for future research. Research methods that have studied epidemiology of diagnostic error provide some estimate on diagnostic error rates. However, there appears to be a large variability in the reported rates due to the heterogeneity of definitions and study methods used. Thus, future methods should focus on obtaining more precise estimates in different settings of care. This would lay the foundation for measuring error rates over time to evaluate improvements. Research methods have studied contributing factors for diagnostic error in both naturalistic and experimental settings. Both approaches have revealed important and complementary information. Newer conceptual models from outside healthcare are needed to advance the depth and rigour of analysis of systems and cognitive insights of causes of error. While the literature has suggested many potentially fruitful interventions for reducing diagnostic errors, most have not been systematically evaluated and/or widely implemented in practice. Research is needed to study promising intervention areas such as enhanced patient involvement in diagnosis, improving diagnosis through the use of electronic tools and identification and reduction of specific diagnostic process 'pitfalls' (eg, failure to conduct appropriate diagnostic evaluation of a breast lump after a 'normal' mammogram). The last decade of research on diagnostic error has made promising steps and laid a foundation for more rigorous methods to advance the field.
Reference-free error estimation for multiple measurement methods.
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.
SU-E-T-392: Evaluation of Ion Chamber/film and Log File Based QA to Detect Delivery Errors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nelson, C; Mason, B; Kirsner, S
2015-06-15
Purpose: Ion chamber and film (ICAF) is a method used to verify patient dose prior to treatment. More recently, log file based QA has been shown as an alternative for measurement based QA. In this study, we delivered VMAT plans with and without errors to determine if ICAF and/or log file based QA was able to detect the errors. Methods: Using two VMAT patients, the original treatment plan plus 7 additional plans with delivery errors introduced were generated and delivered. The erroneous plans had gantry, collimator, MLC, gantry and collimator, collimator and MLC, MLC and gantry, and gantry, collimator, andmore » MLC errors. The gantry and collimator errors were off by 4{sup 0} for one of the two arcs. The MLC error introduced was one in which the opening aperture didn’t move throughout the delivery of the field. For each delivery, an ICAF measurement was made as well as a dose comparison based upon log files. Passing criteria to evaluate the plans were ion chamber less and 5% and film 90% of pixels pass the 3mm/3% gamma analysis(GA). For log file analysis 90% of voxels pass the 3mm/3% 3D GA and beam parameters match what was in the plan. Results: Two original plans were delivered and passed both ICAF and log file base QA. Both ICAF and log file QA met the dosimetry criteria on 4 of the 12 erroneous cases analyzed (2 cases were not analyzed). For the log file analysis, all 12 erroneous plans alerted a mismatch in delivery versus what was planned. The 8 plans that didn’t meet criteria all had MLC errors. Conclusion: Our study demonstrates that log file based pre-treatment QA was able to detect small errors that may not be detected using an ICAF and both methods of were able to detect larger delivery errors.« less
Data Analysis & Statistical Methods for Command File Errors
NASA Technical Reports Server (NTRS)
Meshkat, Leila; Waggoner, Bruce; Bryant, Larry
2014-01-01
This paper explains current work on modeling for managing the risk of command file errors. It is focused on analyzing actual data from a JPL spaceflight mission to build models for evaluating and predicting error rates as a function of several key variables. We constructed a rich dataset by considering the number of errors, the number of files radiated, including the number commands and blocks in each file, as well as subjective estimates of workload and operational novelty. We have assessed these data using different curve fitting and distribution fitting techniques, such as multiple regression analysis, and maximum likelihood estimation to see how much of the variability in the error rates can be explained with these. We have also used goodness of fit testing strategies and principal component analysis to further assess our data. Finally, we constructed a model of expected error rates based on the what these statistics bore out as critical drivers to the error rate. This model allows project management to evaluate the error rate against a theoretically expected rate as well as anticipate future error rates.
Improved method for implicit Monte Carlo
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brown, F. B.; Martin, W. R.
2001-01-01
The Implicit Monte Carlo (IMC) method has been used for over 30 years to analyze radiative transfer problems, such as those encountered in stellar atmospheres or inertial confinement fusion. Reference [2] provided an exact error analysis of IMC for 0-D problems and demonstrated that IMC can exhibit substantial errors when timesteps are large. These temporal errors are inherent in the method and are in addition to spatial discretization errors and approximations that address nonlinearities (due to variation of physical constants). In Reference [3], IMC and four other methods were analyzed in detail and compared on both theoretical grounds and themore » accuracy of numerical tests. As discussed in, two alternative schemes for solving the radiative transfer equations, the Carter-Forest (C-F) method and the Ahrens-Larsen (A-L) method, do not exhibit the errors found in IMC; for 0-D, both of these methods are exact for all time, while for 3-D, A-L is exact for all time and C-F is exact within a timestep. These methods can yield substantially superior results to IMC.« less
Applying integrals of motion to the numerical solution of differential equations
NASA Technical Reports Server (NTRS)
Vezewski, D. J.
1980-01-01
A method is developed for using the integrals of systems of nonlinear, ordinary, differential equations in a numerical integration process to control the local errors in these integrals and reduce the global errors of the solution. The method is general and can be applied to either scalar or vector integrals. A number of example problems, with accompanying numerical results, are used to verify the analysis and support the conjecture of global error reduction.
Applying integrals of motion to the numerical solution of differential equations
NASA Technical Reports Server (NTRS)
Jezewski, D. J.
1979-01-01
A method is developed for using the integrals of systems of nonlinear, ordinary differential equations in a numerical integration process to control the local errors in these integrals and reduce the global errors of the solution. The method is general and can be applied to either scaler or vector integrals. A number of example problems, with accompanying numerical results, are used to verify the analysis and support the conjecture of global error reduction.
Uncertainty Analysis of Seebeck Coefficient and Electrical Resistivity Characterization
NASA Technical Reports Server (NTRS)
Mackey, Jon; Sehirlioglu, Alp; Dynys, Fred
2014-01-01
In order to provide a complete description of a materials thermoelectric power factor, in addition to the measured nominal value, an uncertainty interval is required. The uncertainty may contain sources of measurement error including systematic bias error and precision error of a statistical nature. The work focuses specifically on the popular ZEM-3 (Ulvac Technologies) measurement system, but the methods apply to any measurement system. The analysis accounts for sources of systematic error including sample preparation tolerance, measurement probe placement, thermocouple cold-finger effect, and measurement parameters; in addition to including uncertainty of a statistical nature. Complete uncertainty analysis of a measurement system allows for more reliable comparison of measurement data between laboratories.
Determining relative error bounds for the CVBEM
Hromadka, T.V.
1985-01-01
The Complex Variable Boundary Element Methods provides a measure of relative error which can be utilized to subsequently reduce the error or provide information for further modeling analysis. By maximizing the relative error norm on each boundary element, a bound on the total relative error for each boundary element can be evaluated. This bound can be utilized to test CVBEM convergence, to analyze the effects of additional boundary nodal points in reducing the modeling error, and to evaluate the sensitivity of resulting modeling error within a boundary element from the error produced in another boundary element as a function of geometric distance. ?? 1985.
Langarika-Rocafort, Argia; Emparanza, José Ignacio; Aramendi, José F; Castellano, Julen; Calleja-González, Julio
2017-01-01
To examine the intra-observer reliability and agreement between five methods of measurement for dorsiflexion during Weight Bearing Dorsiflexion Lunge Test and to assess the degree of agreement between three methods in female athletes. Repeated measurements study design. Volleyball club. Twenty-five volleyball players. Dorsiflexion was evaluated using five methods: heel-wall distance, first toe-wall distance, inclinometer at tibia, inclinometer at Achilles tendon and the dorsiflexion angle obtained by a simple trigonometric function. For the statistical analysis, agreement was studied using the Bland-Altman method, the Standard Error of Measurement and the Minimum Detectable Change. Reliability analysis was performed using the Intraclass Correlation Coefficient. Measurement methods using the inclinometer had more than 6° of measurement error. The angle calculated by trigonometric function had 3.28° error. The reliability of inclinometer based methods had ICC values < 0.90. Distance based methods and trigonometric angle measurement had an ICC values > 0.90. Concerning the agreement between methods, there was from 1.93° to 14.42° bias, and from 4.24° to 7.96° random error. To assess DF angle in WBLT, the angle calculated by a trigonometric function is the most repeatable method. The methods of measurement cannot be used interchangeably. Copyright © 2016 Elsevier Ltd. All rights reserved.
Hartman Testing of X-Ray Telescopes
NASA Technical Reports Server (NTRS)
Saha, Timo T.; Biskasch, Michael; Zhang, William W.
2013-01-01
Hartmann testing of x-ray telescopes is a simple test method to retrieve and analyze alignment errors and low-order circumferential errors of x-ray telescopes and their components. A narrow slit is scanned along the circumference of the telescope in front of the mirror and the centroids of the images are calculated. From the centroid data, alignment errors, radius variation errors, and cone-angle variation errors can be calculated. Mean cone angle, mean radial height (average radius), and the focal length of the telescope can also be estimated if the centroid data is measured at multiple focal plane locations. In this paper we present the basic equations that are used in the analysis process. These equations can be applied to full circumference or segmented x-ray telescopes. We use the Optical Surface Analysis Code (OSAC) to model a segmented x-ray telescope and show that the derived equations and accompanying analysis retrieves the alignment errors and low order circumferential errors accurately.
An analysis of temperature-induced errors for an ultrasound distance measuring system. M. S. Thesis
NASA Technical Reports Server (NTRS)
Wenger, David Paul
1991-01-01
The presentation of research is provided in the following five chapters. Chapter 2 presents the necessary background information and definitions for general work with ultrasound and acoustics. It also discusses the basis for errors in the slant range measurements. Chapter 3 presents a method of problem solution and an analysis of the sensitivity of the equations to slant range measurement errors. It also presents various methods by which the error in the slant range measurements can be reduced to improve overall measurement accuracy. Chapter 4 provides a description of a type of experiment used to test the analytical solution and provides a discussion of its results. Chapter 5 discusses the setup of a prototype collision avoidance system, discusses its accuracy, and demonstrates various methods of improving the accuracy along with the improvements' ramifications. Finally, Chapter 6 provides a summary of the work and a discussion of conclusions drawn from it. Additionally, suggestions for further research are made to improve upon what has been presented here.
Error Ratio Analysis: Alternate Mathematics Assessment for General and Special Educators.
ERIC Educational Resources Information Center
Miller, James H.; Carr, Sonya C.
1997-01-01
Eighty-seven elementary students in grades four, five, and six, were administered a 30-item multiplication instrument to assess performance in computation across grade levels. An interpretation of student performance using error ratio analysis is provided and the use of this method with groups of students for instructional decision making is…
NASA Astrophysics Data System (ADS)
Zhang, Qiong; Peng, Cong; Lu, Yiming; Wang, Hao; Zhu, Kaiguang
2018-04-01
A novel technique is developed to level airborne geophysical data using principal component analysis based on flight line difference. In the paper, flight line difference is introduced to enhance the features of levelling error for airborne electromagnetic (AEM) data and improve the correlation between pseudo tie lines. Thus we conduct levelling to the flight line difference data instead of to the original AEM data directly. Pseudo tie lines are selected distributively cross profile direction, avoiding the anomalous regions. Since the levelling errors of selective pseudo tie lines show high correlations, principal component analysis is applied to extract the local levelling errors by low-order principal components reconstruction. Furthermore, we can obtain the levelling errors of original AEM data through inverse difference after spatial interpolation. This levelling method does not need to fly tie lines and design the levelling fitting function. The effectiveness of this method is demonstrated by the levelling results of survey data, comparing with the results from tie-line levelling and flight-line correlation levelling.
Sensitivity of planetary cruise navigation to earth orientation calibration errors
NASA Technical Reports Server (NTRS)
Estefan, J. A.; Folkner, W. M.
1995-01-01
A detailed analysis was conducted to determine the sensitivity of spacecraft navigation errors to the accuracy and timeliness of Earth orientation calibrations. Analyses based on simulated X-band (8.4-GHz) Doppler and ranging measurements acquired during the interplanetary cruise segment of the Mars Pathfinder heliocentric trajectory were completed for the nominal trajectory design and for an alternative trajectory with a longer transit time. Several error models were developed to characterize the effect of Earth orientation on navigational accuracy based on current and anticipated Deep Space Network calibration strategies. The navigational sensitivity of Mars Pathfinder to calibration errors in Earth orientation was computed for each candidate calibration strategy with the Earth orientation parameters included as estimated parameters in the navigation solution. In these cases, the calibration errors contributed 23 to 58% of the total navigation error budget, depending on the calibration strategy being assessed. Navigation sensitivity calculations were also performed for cases in which Earth orientation calibration errors were not adjusted in the navigation solution. In these cases, Earth orientation calibration errors contributed from 26 to as much as 227% of the total navigation error budget. The final analysis suggests that, not only is the method used to calibrate Earth orientation vitally important for precision navigation of Mars Pathfinder, but perhaps equally important is the method for inclusion of the calibration errors in the navigation solutions.
NASA Astrophysics Data System (ADS)
Heavens, A. F.; Seikel, M.; Nord, B. D.; Aich, M.; Bouffanais, Y.; Bassett, B. A.; Hobson, M. P.
2014-12-01
The Fisher Information Matrix formalism (Fisher 1935) is extended to cases where the data are divided into two parts (X, Y), where the expectation value of Y depends on X according to some theoretical model, and X and Y both have errors with arbitrary covariance. In the simplest case, (X, Y) represent data pairs of abscissa and ordinate, in which case the analysis deals with the case of data pairs with errors in both coordinates, but X can be any measured quantities on which Y depends. The analysis applies for arbitrary covariance, provided all errors are Gaussian, and provided the errors in X are small, both in comparison with the scale over which the expected signal Y changes, and with the width of the prior distribution. This generalizes the Fisher Matrix approach, which normally only considers errors in the `ordinate' Y. In this work, we include errors in X by marginalizing over latent variables, effectively employing a Bayesian hierarchical model, and deriving the Fisher Matrix for this more general case. The methods here also extend to likelihood surfaces which are not Gaussian in the parameter space, and so techniques such as DALI (Derivative Approximation for Likelihoods) can be generalized straightforwardly to include arbitrary Gaussian data error covariances. For simple mock data and theoretical models, we compare to Markov Chain Monte Carlo experiments, illustrating the method with cosmological supernova data. We also include the new method in the FISHER4CAST software.
Carstensen, C.; Feischl, M.; Page, M.; Praetorius, D.
2014-01-01
This paper aims first at a simultaneous axiomatic presentation of the proof of optimal convergence rates for adaptive finite element methods and second at some refinements of particular questions like the avoidance of (discrete) lower bounds, inexact solvers, inhomogeneous boundary data, or the use of equivalent error estimators. Solely four axioms guarantee the optimality in terms of the error estimators. Compared to the state of the art in the temporary literature, the improvements of this article can be summarized as follows: First, a general framework is presented which covers the existing literature on optimality of adaptive schemes. The abstract analysis covers linear as well as nonlinear problems and is independent of the underlying finite element or boundary element method. Second, efficiency of the error estimator is neither needed to prove convergence nor quasi-optimal convergence behavior of the error estimator. In this paper, efficiency exclusively characterizes the approximation classes involved in terms of the best-approximation error and data resolution and so the upper bound on the optimal marking parameters does not depend on the efficiency constant. Third, some general quasi-Galerkin orthogonality is not only sufficient, but also necessary for the R-linear convergence of the error estimator, which is a fundamental ingredient in the current quasi-optimality analysis due to Stevenson 2007. Finally, the general analysis allows for equivalent error estimators and inexact solvers as well as different non-homogeneous and mixed boundary conditions. PMID:25983390
NASA Astrophysics Data System (ADS)
Wang, Ting; Xiang, Jie; Fei, Jianfang; Wang, Yi; Liu, Chunxia; Li, Yuanxiang
2017-12-01
This paper presents an evaluation of the observational impacts on blended sea surface winds from a two-dimensional variational data assimilation (2D-Var) scheme. We begin by briefly introducing the analysis sensitivity with respect to observations in variational data assimilation systems and its relationship with the degrees of freedom for signal (DFS), and then the DFS concept is applied to the 2D-Var sea surface wind blending scheme. Two methods, a priori and a posteriori, are used to estimate the DFS of the zonal ( u) and meridional ( v) components of winds in the 2D-Var blending scheme. The a posteriori method can obtain almost the same results as the a priori method. Because only by-products of the blending scheme are used for the a posteriori method, the computation time is reduced significantly. The magnitude of the DFS is critically related to the observational and background error statistics. Changing the observational and background error variances can affect the DFS value. Because the observation error variances are assumed to be uniform, the observational influence at each observational location is related to the background error variance, and the observations located at the place where there are larger background error variances have larger influences. The average observational influence of u and v with respect to the analysis is about 40%, implying that the background influence with respect to the analysis is about 60%.
Rong, Hao; Tian, Jin
2015-05-01
The study contributes to human reliability analysis (HRA) by proposing a method that focuses more on human error causality within a sociotechnical system, illustrating its rationality and feasibility by using a case of the Minuteman (MM) III missile accident. Due to the complexity and dynamics within a sociotechnical system, previous analyses of accidents involving human and organizational factors clearly demonstrated that the methods using a sequential accident model are inadequate to analyze human error within a sociotechnical system. System-theoretic accident model and processes (STAMP) was used to develop a universal framework of human error causal analysis. To elaborate the causal relationships and demonstrate the dynamics of human error, system dynamics (SD) modeling was conducted based on the framework. A total of 41 contributing factors, categorized into four types of human error, were identified through the STAMP-based analysis. All factors are related to a broad view of sociotechnical systems, and more comprehensive than the causation presented in the accident investigation report issued officially. Recommendations regarding both technical and managerial improvement for a lower risk of the accident are proposed. The interests of an interdisciplinary approach provide complementary support between system safety and human factors. The integrated method based on STAMP and SD model contributes to HRA effectively. The proposed method will be beneficial to HRA, risk assessment, and control of the MM III operating process, as well as other sociotechnical systems. © 2014, Human Factors and Ergonomics Society.
A Unified Approach to Measurement Error and Missing Data: Overview and Applications
ERIC Educational Resources Information Center
Blackwell, Matthew; Honaker, James; King, Gary
2017-01-01
Although social scientists devote considerable effort to mitigating measurement error during data collection, they often ignore the issue during data analysis. And although many statistical methods have been proposed for reducing measurement error-induced biases, few have been widely used because of implausible assumptions, high levels of model…
Cohesive Errors in Writing among ESL Pre-Service Teachers
ERIC Educational Resources Information Center
Kwan, Lisa S. L.; Yunus, Melor Md
2014-01-01
Writing is a complex skill and one of the most difficult to master. A teacher's weak writing skills may negatively influence their students. Therefore, reinforcing teacher education by first determining pre-service teachers' writing weaknesses is imperative. This mixed-methods error analysis study aims to examine the cohesive errors in the writing…
Narayanan, Neethu; Gupta, Suman; Gajbhiye, V T; Manjaiah, K M
2017-04-01
A carboxy methyl cellulose-nano organoclay (nano montmorillonite modified with 35-45 wt % dimethyl dialkyl (C 14 -C 18 ) amine (DMDA)) composite was prepared by solution intercalation method. The prepared composite was characterized by infrared spectroscopy (FTIR), X-Ray diffraction spectroscopy (XRD) and scanning electron microscopy (SEM). The composite was utilized for its pesticide sorption efficiency for atrazine, imidacloprid and thiamethoxam. The sorption data was fitted into Langmuir and Freundlich isotherms using linear and non linear methods. The linear regression method suggested best fitting of sorption data into Type II Langmuir and Freundlich isotherms. In order to avoid the bias resulting from linearization, seven different error parameters were also analyzed by non linear regression method. The non linear error analysis suggested that the sorption data fitted well into Langmuir model rather than in Freundlich model. The maximum sorption capacity, Q 0 (μg/g) was given by imidacloprid (2000) followed by thiamethoxam (1667) and atrazine (1429). The study suggests that the degree of determination of linear regression alone cannot be used for comparing the best fitting of Langmuir and Freundlich models and non-linear error analysis needs to be done to avoid inaccurate results. Copyright © 2017 Elsevier Ltd. All rights reserved.
Bayesian analysis of input uncertainty in hydrological modeling: 2. Application
NASA Astrophysics Data System (ADS)
Kavetski, Dmitri; Kuczera, George; Franks, Stewart W.
2006-03-01
The Bayesian total error analysis (BATEA) methodology directly addresses both input and output errors in hydrological modeling, requiring the modeler to make explicit, rather than implicit, assumptions about the likely extent of data uncertainty. This study considers a BATEA assessment of two North American catchments: (1) French Broad River and (2) Potomac basins. It assesses the performance of the conceptual Variable Infiltration Capacity (VIC) model with and without accounting for input (precipitation) uncertainty. The results show the considerable effects of precipitation errors on the predicted hydrographs (especially the prediction limits) and on the calibrated parameters. In addition, the performance of BATEA in the presence of severe model errors is analyzed. While BATEA allows a very direct treatment of input uncertainty and yields some limited insight into model errors, it requires the specification of valid error models, which are currently poorly understood and require further work. Moreover, it leads to computationally challenging highly dimensional problems. For some types of models, including the VIC implemented using robust numerical methods, the computational cost of BATEA can be reduced using Newton-type methods.
NASA Astrophysics Data System (ADS)
Kim, Shin-Woo; Noh, Nam-Kyu; Lim, Gyu-Ho
2013-04-01
This study presents the introduction of retrospective optimal interpolation (ROI) and its application with Weather Research and Forecasting model (WRF). Song et al. (2009) suggested ROI method which is an optimal interpolation (OI) that gradually assimilates observations over the analysis window for variance-minimum estimate of an atmospheric state at the initial time of the analysis window. The assimilation window of ROI algorithm is gradually increased, similar with that of the quasi-static variational assimilation (QSVA; Pires et al., 1996). Unlike QSVA method, however, ROI method assimilates the data at post analysis time using perturbation method (Verlaan and Heemink, 1997) without adjoint model. Song and Lim (2011) improved this method by incorporating eigen-decomposition and covariance inflation. The computational costs for ROI can be reduced due to the eigen-decomposition of background error covariance which can concentrate ROI analyses on the error variances of governing eigenmodes by transforming the control variables into eigenspace. A total energy norm is used for the normalization of each control variables. In this study, ROI method is applied to WRF model with Observing System Simulation Experiment (OSSE) to validate the algorithm and to investigate the capability. Horizontal wind, pressure, potential temperature, and water vapor mixing ratio are used for control variables and observations. Firstly, 1-profile assimilation experiment is performed. Subsequently, OSSE's are performed using the virtual observing system which consists of synop, ship, and sonde data. The difference between forecast errors with assimilation and without assimilation is obviously increased as time passed, which means the improvement of forecast error with the assimilation by ROI. The characteristics and strength/weakness of ROI method are also investigated by conducting the experiments with 3D-Var (3-dimensional variational) method and 4D-Var (4-dimensional variational) method. In the initial time, ROI produces a larger forecast error than that of 4D-Var. However, the difference between the two experimental results is decreased gradually with time, and the ROI shows apparently better result (i.e., smaller forecast error) than that of 4D-Var after 9-hour forecast.
Soft error evaluation and vulnerability analysis in Xilinx Zynq-7010 system-on chip
NASA Astrophysics Data System (ADS)
Du, Xuecheng; He, Chaohui; Liu, Shuhuan; Zhang, Yao; Li, Yonghong; Xiong, Ceng; Tan, Pengkang
2016-09-01
Radiation-induced soft errors are an increasingly important threat to the reliability of modern electronic systems. In order to evaluate system-on chip's reliability and soft error, the fault tree analysis method was used in this work. The system fault tree was constructed based on Xilinx Zynq-7010 All Programmable SoC. Moreover, the soft error rates of different components in Zynq-7010 SoC were tested by americium-241 alpha radiation source. Furthermore, some parameters that used to evaluate the system's reliability and safety were calculated using Isograph Reliability Workbench 11.0, such as failure rate, unavailability and mean time to failure (MTTF). According to fault tree analysis for system-on chip, the critical blocks and system reliability were evaluated through the qualitative and quantitative analysis.
Yang, Yanqiang; Zhang, Chunxi; Lu, Jiazhen
2017-01-01
Strapdown inertial navigation system/celestial navigation system (SINS/CNS) integrated navigation is a fully autonomous and high precision method, which has been widely used to improve the hitting accuracy and quick reaction capability of near-Earth flight vehicles. The installation errors between SINS and star sensors have been one of the main factors that restrict the actual accuracy of SINS/CNS. In this paper, an integration algorithm based on the star vector observations is derived considering the star sensor installation error. Then, the star sensor installation error is accurately estimated based on Kalman Filtering (KF). Meanwhile, a local observability analysis is performed on the rank of observability matrix obtained via linearization observation equation, and the observable conditions are presented and validated. The number of star vectors should be greater than or equal to 2, and the times of posture adjustment also should be greater than or equal to 2. Simulations indicate that the star sensor installation error could be readily observable based on the maneuvering condition; moreover, the attitude errors of SINS are less than 7 arc-seconds. This analysis method and conclusion are useful in the ballistic trajectory design of near-Earth flight vehicles. PMID:28275211
Eigenvector method for umbrella sampling enables error analysis
Thiede, Erik H.; Van Koten, Brian; Weare, Jonathan; Dinner, Aaron R.
2016-01-01
Umbrella sampling efficiently yields equilibrium averages that depend on exploring rare states of a model by biasing simulations to windows of coordinate values and then combining the resulting data with physical weighting. Here, we introduce a mathematical framework that casts the step of combining the data as an eigenproblem. The advantage to this approach is that it facilitates error analysis. We discuss how the error scales with the number of windows. Then, we derive a central limit theorem for averages that are obtained from umbrella sampling. The central limit theorem suggests an estimator of the error contributions from individual windows, and we develop a simple and computationally inexpensive procedure for implementing it. We demonstrate this estimator for simulations of the alanine dipeptide and show that it emphasizes low free energy pathways between stable states in comparison to existing approaches for assessing error contributions. Our work suggests the possibility of using the estimator and, more generally, the eigenvector method for umbrella sampling to guide adaptation of the simulation parameters to accelerate convergence. PMID:27586912
NASA Astrophysics Data System (ADS)
Weng, Hanli; Li, Youping
2017-04-01
The working principle, process device and test procedure of runner static balancing test method by weighting with three-pivot pressure transducers are introduced in this paper. Based on an actual instance of a V hydraulic turbine runner, the error and sensitivity of the three-pivot pressure transducer static balancing method are analysed. Suggestions about improving the accuracy and the application of the method are also proposed.
Error analysis in inverse scatterometry. I. Modeling.
Al-Assaad, Rayan M; Byrne, Dale M
2007-02-01
Scatterometry is an optical technique that has been studied and tested in recent years in semiconductor fabrication metrology for critical dimensions. Previous work presented an iterative linearized method to retrieve surface-relief profile parameters from reflectance measurements upon diffraction. With the iterative linear solution model in this work, rigorous models are developed to represent the random and deterministic or offset errors in scatterometric measurements. The propagation of different types of error from the measurement data to the profile parameter estimates is then presented. The improvement in solution accuracies is then demonstrated with theoretical and experimental data by adjusting for the offset errors. In a companion paper (in process) an improved optimization method is presented to account for unknown offset errors in the measurements based on the offset error model.
NASA Astrophysics Data System (ADS)
Zhao, Fei; Zhang, Chi; Yang, Guilin; Chen, Chinyin
2016-12-01
This paper presents an online estimation method of cutting error by analyzing of internal sensor readings. The internal sensors of numerical control (NC) machine tool are selected to avoid installation problem. The estimation mathematic model of cutting error was proposed to compute the relative position of cutting point and tool center point (TCP) from internal sensor readings based on cutting theory of gear. In order to verify the effectiveness of the proposed model, it was simulated and experimented in gear generating grinding process. The cutting error of gear was estimated and the factors which induce cutting error were analyzed. The simulation and experiments verify that the proposed approach is an efficient way to estimate the cutting error of work-piece during machining process.
Farooqui, Javed Hussain; Sharma, Mansi; Koul, Archana; Dutta, Ranjan; Shroff, Noshir Minoo
2017-01-01
The aim of this study is to compare two different methods of analysis of preoperative reference marking for toric intraocular lens (IOL) after marking with an electronic marker. Cataract and IOL Implantation Service, Shroff Eye Centre, New Delhi, India. Fifty-two eyes of thirty patients planned for toric IOL implantation were included in the study. All patients had preoperative marking performed with an electronic preoperative two-step toric IOL reference marker (ASICO AE-2929). Reference marks were placed at 3-and 9-o'clock positions. Marks were analyzed with two systems. First, slit-lamp photographs taken and analyzed using Adobe Photoshop (version 7.0). Second, Tracey iTrace Visual Function Analyzer (version 5.1.1) was used for capturing corneal topograph examination and position of marks noted. Amount of alignment error was calculated. Mean absolute rotation error was 2.38 ± 1.78° by Photoshop and 2.87 ± 2.03° by iTrace which was not statistically significant ( P = 0.215). Nearly 72.7% of eyes by Photoshop and 61.4% by iTrace had rotation error ≤3° ( P = 0.359); and 90.9% of eyes by Photoshop and 81.8% by iTrace had rotation error ≤5° ( P = 0.344). No significant difference in absolute amount of rotation between eyes when analyzed by either method. Difference in reference mark positions when analyzed by two systems suggests the presence of varying cyclotorsion at different points of time. Both analysis methods showed an approximately 3° of alignment error, which could contribute to 10% loss of astigmatic correction of toric IOL. This can be further compounded by intra-operative marking errors and final placement of IOL in the bag.
ANSYS simulation of the capacitance coupling of quartz tuning fork gyroscope
NASA Astrophysics Data System (ADS)
Zhang, Qing; Feng, Lihui; Zhao, Ke; Cui, Fang; Sun, Yu-nan
2013-12-01
Coupling error is one of the main error sources of the quartz tuning fork gyroscope. The mechanism of capacitance coupling error is analyzed in this article. Finite Element Method (FEM) is used to simulate the structure of the quartz tuning fork by ANSYS software. The voltage output induced by the capacitance coupling is simulated with the harmonic analysis and characteristics of electrical and mechanical parameters influenced by the capacitance coupling between drive electrodes and sense electrodes are discussed with the transient analysis.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kaczmarski, Krzysztof; Guiochon, Georges A
The adsorption isotherms of selected compounds are our main source of information on the mechanisms of adsorption processes. Thus, the selection of the methods used to determine adsorption isotherm data and to evaluate the errors made is critical. Three chromatographic methods were evaluated, frontal analysis (FA), frontal analysis by characteristic point (FACP), and the pulse or perturbation method (PM), and their accuracies were compared. Using the equilibrium-dispersive (ED) model of chromatography, breakthrough curves of single components were generated corresponding to three different adsorption isotherm models: the Langmuir, the bi-Langmuir, and the Moreau isotherms. For each breakthrough curve, the best conventionalmore » procedures of each method (FA, FACP, PM) were used to calculate the corresponding data point, using typical values of the parameters of each isotherm model, for four different values of the column efficiency (N = 500, 1000, 2000, and 10,000). Then, the data points were fitted to each isotherm model and the corresponding isotherm parameters were compared to those of the initial isotherm model. When isotherm data are derived with a chromatographic method, they may suffer from two types of errors: (1) the errors made in deriving the experimental data points from the chromatographic records; (2) the errors made in selecting an incorrect isotherm model and fitting to it the experimental data. Both errors decrease significantly with increasing column efficiency with FA and FACP, but not with PM.« less
Valeri, Linda; Lin, Xihong; VanderWeele, Tyler J.
2014-01-01
Mediation analysis is a popular approach to examine the extent to which the effect of an exposure on an outcome is through an intermediate variable (mediator) and the extent to which the effect is direct. When the mediator is mis-measured the validity of mediation analysis can be severely undermined. In this paper we first study the bias of classical, non-differential measurement error on a continuous mediator in the estimation of direct and indirect causal effects in generalized linear models when the outcome is either continuous or discrete and exposure-mediator interaction may be present. Our theoretical results as well as a numerical study demonstrate that in the presence of non-linearities the bias of naive estimators for direct and indirect effects that ignore measurement error can take unintuitive directions. We then develop methods to correct for measurement error. Three correction approaches using method of moments, regression calibration and SIMEX are compared. We apply the proposed method to the Massachusetts General Hospital lung cancer study to evaluate the effect of genetic variants mediated through smoking on lung cancer risk. PMID:25220625
Encoder fault analysis system based on Moire fringe error signal
NASA Astrophysics Data System (ADS)
Gao, Xu; Chen, Wei; Wan, Qiu-hua; Lu, Xin-ran; Xie, Chun-yu
2018-02-01
Aiming at the problem of any fault and wrong code in the practical application of photoelectric shaft encoder, a fast and accurate encoder fault analysis system is researched from the aspect of Moire fringe photoelectric signal processing. DSP28335 is selected as the core processor and high speed serial A/D converter acquisition card is used. And temperature measuring circuit using AD7420 is designed. Discrete data of Moire fringe error signal is collected at different temperatures and it is sent to the host computer through wireless transmission. The error signal quality index and fault type is displayed on the host computer based on the error signal identification method. The error signal quality can be used to diagnosis the state of error code through the human-machine interface.
[Determination of the error of aerosol extinction coefficient measured by DOAS].
Si, Fu-qi; Liu, Jian-guo; Xie, Pin-hua; Zhang, Yu-jun; Wang, Mian; Liu, Wen-qing; Hiroaki, Kuze; Liu, Cheng; Nobuo, Takeuchi
2006-10-01
The method of defining the error of aerosol extinction coefficient measured by differential optical absorption spectroscopy (DOAS) is described. Some factors which could bring errors to result, such as variation of source, integral time, atmospheric turbulence, calibration of system parameter, displacement of system, and back scattering of particles, are analyzed. The error of aerosol extinction coefficient, 0.03 km(-1), is determined by theoretical analysis and practical measurement.
Experimental Investigation of Jet Impingement Heat Transfer Using Thermochromic Liquid Crystals
NASA Technical Reports Server (NTRS)
Dempsey, Brian Paul
1997-01-01
Jet impingement cooling of a hypersonic airfoil leading edge is experimentally investigated using thermochromic liquid crystals (TLCS) to measure surface temperature. The experiment uses computer data acquisition with digital imaging of the TLCs to determine heat transfer coefficients during a transient experiment. The data reduction relies on analysis of a coupled transient conduction - convection heat transfer problem that characterizes the experiment. The recovery temperature of the jet is accounted for by running two experiments with different heating rates, thereby generating a second equation that is used to solve for the recovery temperature. The resulting solution requires a complicated numerical iteration that is handled by a computer. Because the computational data reduction method is complex, special attention is paid to error assessment. The error analysis considers random and systematic errors generated by the instrumentation along with errors generated by the approximate nature of the numerical methods. Results of the error analysis show that the experimentally determined heat transfer coefficients are accurate to within 15%. The error analysis also shows that the recovery temperature data may be in error by more than 50%. The results show that the recovery temperature data is only reliable when the recovery temperature of the jet is greater than 5 C, i.e. the jet velocity is in excess of 100 m/s. Parameters that were investigated include nozzle width, distance from the nozzle exit to the airfoil surface, and jet velocity. Heat transfer data is presented in graphical and tabular forms. An engineering analysis of hypersonic airfoil leading edge cooling is performed using the results from these experiments. Several suggestions for the improvement of the experimental technique are discussed.
Waskitho, Dri; Lukitaningsih, Endang; Sudjadi; Rohman, Abdul
2016-01-01
Analysis of lard extracted from lipstick formulation containing castor oil has been performed using FTIR spectroscopic method combined with multivariate calibration. Three different extraction methods were compared, namely saponification method followed by liquid/liquid extraction with hexane/dichlorometane/ethanol/water, saponification method followed by liquid/liquid extraction with dichloromethane/ethanol/water, and Bligh & Dyer method using chloroform/methanol/water as extracting solvent. Qualitative and quantitative analysis of lard were performed using principle component (PCA) and partial least square (PLS) analysis, respectively. The results showed that, in all samples prepared by the three extraction methods, PCA was capable of identifying lard at wavelength region of 1200-800 cm -1 with the best result was obtained by Bligh & Dyer method. Furthermore, PLS analysis at the same wavelength region used for qualification showed that Bligh and Dyer was the most suitable extraction method with the highest determination coefficient (R 2 ) and the lowest root mean square error of calibration (RMSEC) as well as root mean square error of prediction (RMSEP) values.
Evaluation of Acoustic Doppler Current Profiler measurements of river discharge
Morlock, S.E.
1996-01-01
The standard deviations of the ADCP measurements ranged from approximately 1 to 6 percent and were generally higher than the measurement errors predicted by error-propagation analysis of ADCP instrument performance. These error-prediction methods assume that the largest component of ADCP discharge measurement error is instrument related. The larger standard deviations indicate that substantial portions of measurement error may be attributable to sources unrelated to ADCP electronics or signal processing and are functions of the field environment.
West, Jamie; Atherton, Jennifer; Costelloe, Seán J; Pourmahram, Ghazaleh; Stretton, Adam; Cornes, Michael
2017-01-01
Preanalytical errors have previously been shown to contribute a significant proportion of errors in laboratory processes and contribute to a number of patient safety risks. Accreditation against ISO 15189:2012 requires that laboratory Quality Management Systems consider the impact of preanalytical processes in areas such as the identification and control of non-conformances, continual improvement, internal audit and quality indicators. Previous studies have shown that there is a wide variation in the definition, repertoire and collection methods for preanalytical quality indicators. The International Federation of Clinical Chemistry Working Group on Laboratory Errors and Patient Safety has defined a number of quality indicators for the preanalytical stage, and the adoption of harmonized definitions will support interlaboratory comparisons and continual improvement. There are a variety of data collection methods, including audit, manual recording processes, incident reporting mechanisms and laboratory information systems. Quality management processes such as benchmarking, statistical process control, Pareto analysis and failure mode and effect analysis can be used to review data and should be incorporated into clinical governance mechanisms. In this paper, The Association for Clinical Biochemistry and Laboratory Medicine PreAnalytical Specialist Interest Group review the various data collection methods available. Our recommendation is the use of the laboratory information management systems as a recording mechanism for preanalytical errors as this provides the easiest and most standardized mechanism of data capture.
Two MIS Analysis Methods: An Experimental Comparison.
ERIC Educational Resources Information Center
Wang, Shouhong
1996-01-01
In China, 24 undergraduate business students applied data flow diagrams (DFD) to a mini-case, and 20 used object-oriented analysis (OOA). DFD seemed easier to learn, but after training, those using the OOA method for systems analysis made fewer errors. (SK)
Large scale analysis of the mutational landscape in HT-SELEX improves aptamer discovery
Hoinka, Jan; Berezhnoy, Alexey; Dao, Phuong; Sauna, Zuben E.; Gilboa, Eli; Przytycka, Teresa M.
2015-01-01
High-Throughput (HT) SELEX combines SELEX (Systematic Evolution of Ligands by EXponential Enrichment), a method for aptamer discovery, with massively parallel sequencing technologies. This emerging technology provides data for a global analysis of the selection process and for simultaneous discovery of a large number of candidates but currently lacks dedicated computational approaches for their analysis. To close this gap, we developed novel in-silico methods to analyze HT-SELEX data and utilized them to study the emergence of polymerase errors during HT-SELEX. Rather than considering these errors as a nuisance, we demonstrated their utility for guiding aptamer discovery. Our approach builds on two main advancements in aptamer analysis: AptaMut—a novel technique allowing for the identification of polymerase errors conferring an improved binding affinity relative to the ‘parent’ sequence and AptaCluster—an aptamer clustering algorithm which is to our best knowledge, the only currently available tool capable of efficiently clustering entire aptamer pools. We applied these methods to an HT-SELEX experiment developing aptamers against Interleukin 10 receptor alpha chain (IL-10RA) and experimentally confirmed our predictions thus validating our computational methods. PMID:25870409
NASA Astrophysics Data System (ADS)
Shinnaka, Shinji; Sano, Kousuke
This paper presents a new unified analysis of estimate errors by model-matching phase-estimation methods such as rotor-flux state-observers, back EMF state-observers, and back EMF disturbance-observers, for sensorless drive of permanent-magnet synchronous motors. Analytical solutions about estimate errors, whose validity is confirmed by numerical experiments, are rich in universality and applicability. As an example of universality and applicability, a new trajectory-oriented vector control method is proposed, which can realize directly quasi-optimal strategy minimizing total losses with no additional computational loads by simply orienting one of vector-control coordinates to the associated quasi-optimal trajectory. The coordinate orientation rule, which is analytically derived, is surprisingly simple. Consequently the trajectory-oriented vector control method can be applied to a number of conventional vector control systems using one of the model-matching phase-estimation methods.
Analysis and compensation of synchronous measurement error for multi-channel laser interferometer
NASA Astrophysics Data System (ADS)
Du, Shengwu; Hu, Jinchun; Zhu, Yu; Hu, Chuxiong
2017-05-01
Dual-frequency laser interferometer has been widely used in precision motion system as a displacement sensor, to achieve nanoscale positioning or synchronization accuracy. In a multi-channel laser interferometer synchronous measurement system, signal delays are different in the different channels, which will cause asynchronous measurement, and then lead to measurement error, synchronous measurement error (SME). Based on signal delay analysis of the measurement system, this paper presents a multi-channel SME framework for synchronous measurement, and establishes the model between SME and motion velocity. Further, a real-time compensation method for SME is proposed. This method has been verified in a self-developed laser interferometer signal processing board (SPB). The experiment result showed that, using this compensation method, at a motion velocity 0.89 m s-1, the max SME between two measuring channels in the SPB is 1.1 nm. This method is more easily implemented and applied to engineering than the method of directly testing smaller signal delay.
Wang, Jinfeng; Zhao, Meng; Zhang, Min; Liu, Yang; Li, Hong
2014-01-01
We discuss and analyze an H 1-Galerkin mixed finite element (H 1-GMFE) method to look for the numerical solution of time fractional telegraph equation. We introduce an auxiliary variable to reduce the original equation into lower-order coupled equations and then formulate an H 1-GMFE scheme with two important variables. We discretize the Caputo time fractional derivatives using the finite difference methods and approximate the spatial direction by applying the H 1-GMFE method. Based on the discussion on the theoretical error analysis in L 2-norm for the scalar unknown and its gradient in one dimensional case, we obtain the optimal order of convergence in space-time direction. Further, we also derive the optimal error results for the scalar unknown in H 1-norm. Moreover, we derive and analyze the stability of H 1-GMFE scheme and give the results of a priori error estimates in two- or three-dimensional cases. In order to verify our theoretical analysis, we give some results of numerical calculation by using the Matlab procedure. PMID:25184148
Zhang, Jiayu; Li, Jie; Zhang, Xi; Che, Xiaorui; Huang, Yugang; Feng, Kaiqiang
2018-05-04
The Semi-Strapdown Inertial Navigation System (SSINS) provides a new solution to attitude measurement of a high-speed rotating missile. However, micro-electro-mechanical-systems (MEMS) inertial measurement unit (MIMU) outputs are corrupted by significant sensor errors. In order to improve the navigation precision, a rotation modulation technology method called Rotation Semi-Strapdown Inertial Navigation System (RSSINS) is introduced into SINS. In fact, the stability of the modulation angular rate is difficult to achieve in a high-speed rotation environment. The changing rotary angular rate has an impact on the inertial sensor error self-compensation. In this paper, the influence of modulation angular rate error, including acceleration-deceleration process, and instability of the angular rate on the navigation accuracy of RSSINS is deduced and the error characteristics of the reciprocating rotation scheme are analyzed. A new compensation method is proposed to remove or reduce sensor errors so as to make it possible to maintain high precision autonomous navigation performance by MIMU when there is no external aid. Experiments have been carried out to validate the performance of the method. In addition, the proposed method is applicable for modulation angular rate error compensation under various dynamic conditions.
Lock-in amplifier error prediction and correction in frequency sweep measurements.
Sonnaillon, Maximiliano Osvaldo; Bonetto, Fabian Jose
2007-01-01
This article proposes an analytical algorithm for predicting errors in lock-in amplifiers (LIAs) working with time-varying reference frequency. Furthermore, a simple method for correcting such errors is presented. The reference frequency can be swept in order to measure the frequency response of a system within a given spectrum. The continuous variation of the reference frequency produces a measurement error that depends on three factors: the sweep speed, the LIA low-pass filters, and the frequency response of the measured system. The proposed error prediction algorithm is based on the final value theorem of the Laplace transform. The correction method uses a double-sweep measurement. A mathematical analysis is presented and validated with computational simulations and experimental measurements.
Evaluation of random errors in Williams’ series coefficients obtained with digital image correlation
NASA Astrophysics Data System (ADS)
Lychak, Oleh V.; Holyns'kiy, Ivan S.
2016-03-01
The use of the Williams’ series parameters for fracture analysis requires valid information about their error values. The aim of this investigation is the development of the method for estimation of the standard deviation of random errors of the Williams’ series parameters, obtained from the measured components of the stress field. Also, the criteria for choosing the optimal number of terms in the truncated Williams’ series for derivation of their parameters with minimal errors is proposed. The method was used for the evaluation of the Williams’ parameters, obtained from the data, and measured by the digital image correlation technique for testing a three-point bending specimen.
A Study on Mutil-Scale Background Error Covariances in 3D-Var Data Assimilation
NASA Astrophysics Data System (ADS)
Zhang, Xubin; Tan, Zhe-Min
2017-04-01
The construction of background error covariances is a key component of three-dimensional variational data assimilation. There are different scale background errors and interactions among them in the numerical weather Prediction. However, the influence of these errors and their interactions cannot be represented in the background error covariances statistics when estimated by the leading methods. So, it is necessary to construct background error covariances influenced by multi-scale interactions among errors. With the NMC method, this article firstly estimates the background error covariances at given model-resolution scales. And then the information of errors whose scales are larger and smaller than the given ones is introduced respectively, using different nesting techniques, to estimate the corresponding covariances. The comparisons of three background error covariances statistics influenced by information of errors at different scales reveal that, the background error variances enhance particularly at large scales and higher levels when introducing the information of larger-scale errors by the lateral boundary condition provided by a lower-resolution model. On the other hand, the variances reduce at medium scales at the higher levels, while those show slight improvement at lower levels in the nested domain, especially at medium and small scales, when introducing the information of smaller-scale errors by nesting a higher-resolution model. In addition, the introduction of information of larger- (smaller-) scale errors leads to larger (smaller) horizontal and vertical correlation scales of background errors. Considering the multivariate correlations, the Ekman coupling increases (decreases) with the information of larger- (smaller-) scale errors included, whereas the geostrophic coupling in free atmosphere weakens in both situations. The three covariances obtained in above work are used in a data assimilation and model forecast system respectively, and then the analysis-forecast cycles for a period of 1 month are conducted. Through the comparison of both analyses and forecasts from this system, it is found that the trends for variation in analysis increments with information of different scale errors introduced are consistent with those for variation in variances and correlations of background errors. In particular, introduction of smaller-scale errors leads to larger amplitude of analysis increments for winds at medium scales at the height of both high- and low- level jet. And analysis increments for both temperature and humidity are greater at the corresponding scales at middle and upper levels under this circumstance. These analysis increments improve the intensity of jet-convection system which includes jets at different levels and coupling between them associated with latent heat release, and these changes in analyses contribute to the better forecasts for winds and temperature in the corresponding areas. When smaller-scale errors are included, analysis increments for humidity enhance significantly at large scales at lower levels to moisten southern analyses. This humidification devotes to correcting dry bias there and eventually improves forecast skill of humidity. Moreover, inclusion of larger- (smaller-) scale errors is beneficial for forecast quality of heavy (light) precipitation at large (small) scales due to the amplification (diminution) of intensity and area in precipitation forecasts but tends to overestimate (underestimate) light (heavy) precipitation .
Methods for Addressing Technology-induced Errors: The Current State.
Borycki, E; Dexheimer, J W; Hullin Lucay Cossio, C; Gong, Y; Jensen, S; Kaipio, J; Kennebeck, S; Kirkendall, E; Kushniruk, A W; Kuziemsky, C; Marcilly, R; Röhrig, R; Saranto, K; Senathirajah, Y; Weber, J; Takeda, H
2016-11-10
The objectives of this paper are to review and discuss the methods that are being used internationally to report on, mitigate, and eliminate technology-induced errors. The IMIA Working Group for Health Informatics for Patient Safety worked together to review and synthesize some of the main methods and approaches associated with technology- induced error reporting, reduction, and mitigation. The work involved a review of the evidence-based literature as well as guideline publications specific to health informatics. The paper presents a rich overview of current approaches, issues, and methods associated with: (1) safe HIT design, (2) safe HIT implementation, (3) reporting on technology-induced errors, (4) technology-induced error analysis, and (5) health information technology (HIT) risk management. The work is based on research from around the world. Internationally, researchers have been developing methods that can be used to identify, report on, mitigate, and eliminate technology-induced errors. Although there remain issues and challenges associated with the methodologies, they have been shown to improve the quality and safety of HIT. Since the first publications documenting technology-induced errors in healthcare in 2005, we have seen in a short 10 years researchers develop ways of identifying and addressing these types of errors. We have also seen organizations begin to use these approaches. Knowledge has been translated into practice in a short ten years whereas the norm for other research areas is of 20 years.
An approach to the analysis of performance of quasi-optimum digital phase-locked loops.
NASA Technical Reports Server (NTRS)
Polk, D. R.; Gupta, S. C.
1973-01-01
An approach to the analysis of performance of quasi-optimum digital phase-locked loops (DPLL's) is presented. An expression for the characteristic function of the prior error in the state estimate is derived, and from this expression an infinite dimensional equation for the prior error variance is obtained. The prior error-variance equation is a function of the communication system model and the DPLL gain and is independent of the method used to derive the DPLL gain. Two approximations are discussed for reducing the prior error-variance equation to finite dimension. The effectiveness of one approximation in analyzing DPLL performance is studied.
ADEPT, a dynamic next generation sequencing data error-detection program with trimming
DOE Office of Scientific and Technical Information (OSTI.GOV)
Feng, Shihai; Lo, Chien-Chi; Li, Po-E
Illumina is the most widely used next generation sequencing technology and produces millions of short reads that contain errors. These sequencing errors constitute a major problem in applications such as de novo genome assembly, metagenomics analysis and single nucleotide polymorphism discovery. In this study, we present ADEPT, a dynamic error detection method, based on the quality scores of each nucleotide and its neighboring nucleotides, together with their positions within the read and compares this to the position-specific quality score distribution of all bases within the sequencing run. This method greatly improves upon other available methods in terms of the truemore » positive rate of error discovery without affecting the false positive rate, particularly within the middle of reads. We conclude that ADEPT is the only tool to date that dynamically assesses errors within reads by comparing position-specific and neighboring base quality scores with the distribution of quality scores for the dataset being analyzed. The result is a method that is less prone to position-dependent under-prediction, which is one of the most prominent issues in error prediction. The outcome is that ADEPT improves upon prior efforts in identifying true errors, primarily within the middle of reads, while reducing the false positive rate.« less
ADEPT, a dynamic next generation sequencing data error-detection program with trimming
Feng, Shihai; Lo, Chien-Chi; Li, Po-E; ...
2016-02-29
Illumina is the most widely used next generation sequencing technology and produces millions of short reads that contain errors. These sequencing errors constitute a major problem in applications such as de novo genome assembly, metagenomics analysis and single nucleotide polymorphism discovery. In this study, we present ADEPT, a dynamic error detection method, based on the quality scores of each nucleotide and its neighboring nucleotides, together with their positions within the read and compares this to the position-specific quality score distribution of all bases within the sequencing run. This method greatly improves upon other available methods in terms of the truemore » positive rate of error discovery without affecting the false positive rate, particularly within the middle of reads. We conclude that ADEPT is the only tool to date that dynamically assesses errors within reads by comparing position-specific and neighboring base quality scores with the distribution of quality scores for the dataset being analyzed. The result is a method that is less prone to position-dependent under-prediction, which is one of the most prominent issues in error prediction. The outcome is that ADEPT improves upon prior efforts in identifying true errors, primarily within the middle of reads, while reducing the false positive rate.« less
NASA Astrophysics Data System (ADS)
Liu, Zhixiang; Xing, Tingwen; Jiang, Yadong; Lv, Baobin
2018-02-01
A two-dimensional (2-D) shearing interferometer based on an amplitude chessboard grating was designed to measure the wavefront aberration of a high numerical-aperture (NA) objective. Chessboard gratings offer better diffraction efficiencies and fewer disturbing diffraction orders than traditional cross gratings. The wavefront aberration of the tested objective was retrieved from the shearing interferogram using the Fourier transform and differential Zernike polynomial-fitting methods. Grating manufacturing errors, including the duty-cycle and pattern-deviation errors, were analyzed with the Fourier transform method. Then, according to the relation between the spherical pupil and planar detector coordinates, the influence of the distortion of the pupil coordinates was simulated. Finally, the systematic error attributable to grating alignment errors was deduced through the geometrical ray-tracing method. Experimental results indicate that the measuring repeatability (3σ) of the wavefront aberration of an objective with NA 0.4 was 3.4 mλ. The systematic-error results were consistent with previous analyses. Thus, the correct wavefront aberration can be obtained after calibration.
Evaluation of algorithms for geological thermal-inertia mapping
NASA Technical Reports Server (NTRS)
Miller, S. H.; Watson, K.
1977-01-01
The errors incurred in producing a thermal inertia map are of three general types: measurement, analysis, and model simplification. To emphasize the geophysical relevance of these errors, they were expressed in terms of uncertainty in thermal inertia and compared with the thermal inertia values of geologic materials. Thus the applications and practical limitations of the technique were illustrated. All errors were calculated using the parameter values appropriate to a site at the Raft River, Id. Although these error values serve to illustrate the magnitudes that can be expected from the three general types of errors, extrapolation to other sites should be done using parameter values particular to the area. Three surface temperature algorithms were evaluated: linear Fourier series, finite difference, and Laplace transform. In terms of resulting errors in thermal inertia, the Laplace transform method is the most accurate (260 TIU), the forward finite difference method is intermediate (300 TIU), and the linear Fourier series method the least accurate (460 TIU).
Carrier recovery methods for a dual-mode modem: A design approach
NASA Technical Reports Server (NTRS)
Richards, C. W.; Wilson, S. G.
1984-01-01
A dual mode model with selectable QPSK or 16-QASK modulation schemes is discussed. The theoretical reasoning as well as the practical trade-offs made during the development of a modem are presented, with attention given to the carrier recovery method used for coherent demodulation. Particular attention is given to carrier recovery methods that can provide little degradation due to phase error for both QPSK and 16-QASK, while being insensitive to the amplitude characteristic of a 16-QASK modulation scheme. A computer analysis of the degradation is symbol error rate (SER) for QPSK and 16-QASK due to phase error is prresented. Results find that an energy increase of roughly 4 dB is needed to maintain a SER of 1X10(-5) for QPSK with 20 deg of phase error and 16-QASK with 7 deg phase error.
NASA Astrophysics Data System (ADS)
Bezan, Scott; Shirani, Shahram
2006-12-01
To reliably transmit video over error-prone channels, the data should be both source and channel coded. When multiple channels are available for transmission, the problem extends to that of partitioning the data across these channels. The condition of transmission channels, however, varies with time. Therefore, the error protection added to the data at one instant of time may not be optimal at the next. In this paper, we propose a method for adaptively adding error correction code in a rate-distortion (RD) optimized manner using rate-compatible punctured convolutional codes to an MJPEG2000 constant rate-coded frame of video. We perform an analysis on the rate-distortion tradeoff of each of the coding units (tiles and packets) in each frame and adapt the error correction code assigned to the unit taking into account the bandwidth and error characteristics of the channels. This method is applied to both single and multiple time-varying channel environments. We compare our method with a basic protection method in which data is either not transmitted, transmitted with no protection, or transmitted with a fixed amount of protection. Simulation results show promising performance for our proposed method.
Spindle Thermal Error Optimization Modeling of a Five-axis Machine Tool
NASA Astrophysics Data System (ADS)
Guo, Qianjian; Fan, Shuo; Xu, Rufeng; Cheng, Xiang; Zhao, Guoyong; Yang, Jianguo
2017-05-01
Aiming at the problem of low machining accuracy and uncontrollable thermal errors of NC machine tools, spindle thermal error measurement, modeling and compensation of a two turntable five-axis machine tool are researched. Measurement experiment of heat sources and thermal errors are carried out, and GRA(grey relational analysis) method is introduced into the selection of temperature variables used for thermal error modeling. In order to analyze the influence of different heat sources on spindle thermal errors, an ANN (artificial neural network) model is presented, and ABC(artificial bee colony) algorithm is introduced to train the link weights of ANN, a new ABC-NN(Artificial bee colony-based neural network) modeling method is proposed and used in the prediction of spindle thermal errors. In order to test the prediction performance of ABC-NN model, an experiment system is developed, the prediction results of LSR (least squares regression), ANN and ABC-NN are compared with the measurement results of spindle thermal errors. Experiment results show that the prediction accuracy of ABC-NN model is higher than LSR and ANN, and the residual error is smaller than 3 μm, the new modeling method is feasible. The proposed research provides instruction to compensate thermal errors and improve machining accuracy of NC machine tools.
Analysis of phase error effects in multishot diffusion-prepared turbo spin echo imaging
Cervantes, Barbara; Kooijman, Hendrik; Karampinos, Dimitrios C.
2017-01-01
Background To characterize the effect of phase errors on the magnitude and the phase of the diffusion-weighted (DW) signal acquired with diffusion-prepared turbo spin echo (dprep-TSE) sequences. Methods Motion and eddy currents were identified as the main sources of phase errors. An analytical expression for the effect of phase errors on the acquired signal was derived and verified using Bloch simulations, phantom, and in vivo experiments. Results Simulations and experiments showed that phase errors during the diffusion preparation cause both magnitude and phase modulation on the acquired data. When motion-induced phase error (MiPe) is accounted for (e.g., with motion-compensated diffusion encoding), the signal magnitude modulation due to the leftover eddy-current-induced phase error cannot be eliminated by the conventional phase cycling and sum-of-squares (SOS) method. By employing magnitude stabilizers, the phase-error-induced magnitude modulation, regardless of its cause, was removed but the phase modulation remained. The in vivo comparison between pulsed gradient and flow-compensated diffusion preparations showed that MiPe needed to be addressed in multi-shot dprep-TSE acquisitions employing magnitude stabilizers. Conclusions A comprehensive analysis of phase errors in dprep-TSE sequences showed that magnitude stabilizers are mandatory in removing the phase error induced magnitude modulation. Additionally, when multi-shot dprep-TSE is employed the inconsistent signal phase modulation across shots has to be resolved before shot-combination is performed. PMID:28516049
Methods for Addressing Technology-Induced Errors: The Current State
Dexheimer, J. W.; Hullin Lucay Cossio, C.; Gong, Y.; Jensen, S.; Kaipio, J.; Kennebeck, S.; Kirkendall, E.; Kushniruk, A. W.; Kuziemsky, C.; Marcilly, R.; Röhrig, R.; Saranto, K.; Senathirajah, Y.; Weber, J.; Takeda, H.
2016-01-01
Summary Objectives The objectives of this paper are to review and discuss the methods that are being used internationally to report on, mitigate, and eliminate technology-induced errors. Methods The IMIA Working Group for Health Informatics for Patient Safety worked together to review and synthesize some of the main methods and approaches associated with technology-induced error reporting, reduction, and mitigation. The work involved a review of the evidence-based literature as well as guideline publications specific to health informatics. Results The paper presents a rich overview of current approaches, issues, and methods associated with: (1) safe HIT design, (2) safe HIT implementation, (3) reporting on technology-induced errors, (4) technology-induced error analysis, and (5) health information technology (HIT) risk management. The work is based on research from around the world. Conclusions Internationally, researchers have been developing methods that can be used to identify, report on, mitigate, and eliminate technology-induced errors. Although there remain issues and challenges associated with the methodologies, they have been shown to improve the quality and safety of HIT. Since the first publications documenting technology-induced errors in healthcare in 2005, we have seen in a short 10 years researchers develop ways of identifying and addressing these types of errors. We have also seen organizations begin to use these approaches. Knowledge has been translated into practice in a short ten years whereas the norm for other research areas is of 20 years. PMID:27830228
Kreilinger, Alex; Hiebel, Hannah; Müller-Putz, Gernot R
2016-03-01
This work aimed to find and evaluate a new method for detecting errors in continuous brain-computer interface (BCI) applications. Instead of classifying errors on a single-trial basis, the new method was based on multiple events (MEs) analysis to increase the accuracy of error detection. In a BCI-driven car game, based on motor imagery (MI), discrete events were triggered whenever subjects collided with coins and/or barriers. Coins counted as correct events, whereas barriers were errors. This new method, termed ME method, combined and averaged the classification results of single events (SEs) and determined the correctness of MI trials, which consisted of event sequences instead of SEs. The benefit of this method was evaluated in an offline simulation. In an online experiment, the new method was used to detect erroneous MI trials. Such MI trials were discarded and could be repeated by the users. We found that, even with low SE error potential (ErrP) detection rates, feasible accuracies can be achieved when combining MEs to distinguish erroneous from correct MI trials. Online, all subjects reached higher scores with error detection than without, at the cost of longer times needed for completing the game. Findings suggest that ErrP detection may become a reliable tool for monitoring continuous states in BCI applications when combining MEs. This paper demonstrates a novel technique for detecting errors in online continuous BCI applications, which yields promising results even with low single-trial detection rates.
Turbulence excited frequency domain damping measurement and truncation effects
NASA Technical Reports Server (NTRS)
Soovere, J.
1976-01-01
Existing frequency domain modal frequency and damping analysis methods are discussed. The effects of truncation in the Laplace and Fourier transform data analysis methods are described. Methods for eliminating truncation errors from measured damping are presented. Implications of truncation effects in fast Fourier transform analysis are discussed. Limited comparison with test data is presented.
Farooqui, Javed Hussain; Sharma, Mansi; Koul, Archana; Dutta, Ranjan; Shroff, Noshir Minoo
2017-01-01
PURPOSE: The aim of this study is to compare two different methods of analysis of preoperative reference marking for toric intraocular lens (IOL) after marking with an electronic marker. SETTING/VENUE: Cataract and IOL Implantation Service, Shroff Eye Centre, New Delhi, India. PATIENTS AND METHODS: Fifty-two eyes of thirty patients planned for toric IOL implantation were included in the study. All patients had preoperative marking performed with an electronic preoperative two-step toric IOL reference marker (ASICO AE-2929). Reference marks were placed at 3-and 9-o'clock positions. Marks were analyzed with two systems. First, slit-lamp photographs taken and analyzed using Adobe Photoshop (version 7.0). Second, Tracey iTrace Visual Function Analyzer (version 5.1.1) was used for capturing corneal topograph examination and position of marks noted. Amount of alignment error was calculated. RESULTS: Mean absolute rotation error was 2.38 ± 1.78° by Photoshop and 2.87 ± 2.03° by iTrace which was not statistically significant (P = 0.215). Nearly 72.7% of eyes by Photoshop and 61.4% by iTrace had rotation error ≤3° (P = 0.359); and 90.9% of eyes by Photoshop and 81.8% by iTrace had rotation error ≤5° (P = 0.344). No significant difference in absolute amount of rotation between eyes when analyzed by either method. CONCLUSIONS: Difference in reference mark positions when analyzed by two systems suggests the presence of varying cyclotorsion at different points of time. Both analysis methods showed an approximately 3° of alignment error, which could contribute to 10% loss of astigmatic correction of toric IOL. This can be further compounded by intra-operative marking errors and final placement of IOL in the bag. PMID:28757694
Comparative Analysis of Methods of Evaluating the Lower Ionosphere Parameters by Tweek Atmospherics
NASA Astrophysics Data System (ADS)
Krivonos, A. P.; Shvets, A. V.
2016-12-01
Purpose: A comparative analysis of the phase and frequency methods for determining the Earth-ionosphere effective waveguide heights for the basic and higher types of normal waves (modes) and distance to the source of radiation - lightning - has been made by analyzing pulse signals in the ELF-VLF range - tweek-atmospherics (tweeks). Design/methodology/approach: To test the methods in computer simulations, the tweeks waveforms were synthesized for the Earth-ionosphere waveguide model with the exponential conductivity profile of the lower ionosphere. The calculations were made for a 20-40 dB signal/noise ratio. Findings: The error of the frequency method of determining the effective height of the waveguide for different waveguide modes was less than 0.5 %. The error of the phase method for determining the effective height of the waveguide was less than 0.8 %. Errors in determining the distance to the lightning was less than 1 % for the phase method, and less than 5 % for the frequency method for the source ranges 1000-3000 km. Conclusions: The analysis results have showed the accuracy of the frequency and phase methods being practically the same within distances of 1000-3000 km. For distances less than 1000 km, the phase method shows a more accurate evaluation of the range, so the combination of the two methods can be used to improve estimating the tweek’s propagation path parameters.
A numerical study of some potential sources of error in side-by-side seismometer evaluations
Holcomb, L. Gary
1990-01-01
This report presents the results of a series of computer simulations of potential errors in test data, which might be obtained when conducting side-by-side comparisons of seismometers. These results can be used as guides in estimating potential sources and magnitudes of errors one might expect when analyzing real test data. First, the derivation of a direct method for calculating the noise levels of two sensors in a side-by-side evaluation is repeated and extended slightly herein. This bulk of this derivation was presented previously (see Holcomb 1989); it is repeated here for easy reference.This method is applied to the analysis of a simulated test of two sensors in a side-by-side test in which the outputs of both sensors consist of white noise spectra with known signal-tonoise ratios (SNR's). This report extends this analysis to high SNR's to determine the limitations of the direct method for calculating the noise levels at signal-to-noise levels which are much higher than presented previously (see Holcomb 1989). Next, the method is used to analyze a simulated test of two sensors in a side-by-side test in which the outputs of both sensors consist of bandshaped noise spectra with known signal-tonoise ratios. This is a much more realistic representation of real world data because the earth's background spectrum is certainly not flat.Finally, the results of the analysis of simulated white and bandshaped side-by-side test data are used to assist in interpreting the analysis of the effects of simulated azimuthal misalignment in side-by-side sensor evaluations. A thorough understanding of azimuthal misalignment errors is important because of the physical impossibility of perfectly aligning two sensors in a real world situation. The analysis herein indicates that alignment errors place lower limits on the levels of system noise which can be resolved in a side-by-side measurement It also indicates that alignment errors are the source of the fact that real data noise spectra tend to follow the earth's background spectra in shape.
Evaluation and error apportionment of an ensemble of ...
Through the comparison of several regional-scale chemistry transport modelling systems that simulate meteorology and air quality over the European and American continents, this study aims at i) apportioning the error to the responsible processes using time-scale analysis, ii) helping to detect causes of models error, and iii) identifying the processes and scales most urgently requiring dedicated investigations. The analysis is conducted within the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII) and tackles model performance gauging through measurement-to-model comparison, error decomposition and time series analysis of the models biases for several fields (ozone, CO, SO2, NO, NO2, PM10, PM2.5, wind speed, and temperature). The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overall sense of model strengths and deficiencies, while apportioning the error to its constituent parts (bias, variance and covariance) can help to assess the nature and quality of the error. Each of the error components is analysed independently and apportioned to specific processes based on the corresponding timescale (long scale, synoptic, diurnal, and intra-day) using the error apportionment technique devised in the former phases of AQMEII.The application of the error apportionment method to the AQMEII Phase 3 simulations provides several key insights. In addition to reaffirming the strong impact
Identifying model error in metabolic flux analysis - a generalized least squares approach.
Sokolenko, Stanislav; Quattrociocchi, Marco; Aucoin, Marc G
2016-09-13
The estimation of intracellular flux through traditional metabolic flux analysis (MFA) using an overdetermined system of equations is a well established practice in metabolic engineering. Despite the continued evolution of the methodology since its introduction, there has been little focus on validation and identification of poor model fit outside of identifying "gross measurement error". The growing complexity of metabolic models, which are increasingly generated from genome-level data, has necessitated robust validation that can directly assess model fit. In this work, MFA calculation is framed as a generalized least squares (GLS) problem, highlighting the applicability of the common t-test for model validation. To differentiate between measurement and model error, we simulate ideal flux profiles directly from the model, perturb them with estimated measurement error, and compare their validation to real data. Application of this strategy to an established Chinese Hamster Ovary (CHO) cell model shows how fluxes validated by traditional means may be largely non-significant due to a lack of model fit. With further simulation, we explore how t-test significance relates to calculation error and show that fluxes found to be non-significant have 2-4 fold larger error (if measurement uncertainty is in the 5-10 % range). The proposed validation method goes beyond traditional detection of "gross measurement error" to identify lack of fit between model and data. Although the focus of this work is on t-test validation and traditional MFA, the presented framework is readily applicable to other regression analysis methods and MFA formulations.
Flexible methods for segmentation evaluation: results from CT-based luggage screening.
Karimi, Seemeen; Jiang, Xiaoqian; Cosman, Pamela; Martz, Harry
2014-01-01
Imaging systems used in aviation security include segmentation algorithms in an automatic threat recognition pipeline. The segmentation algorithms evolve in response to emerging threats and changing performance requirements. Analysis of segmentation algorithms' behavior, including the nature of errors and feature recovery, facilitates their development. However, evaluation methods from the literature provide limited characterization of the segmentation algorithms. To develop segmentation evaluation methods that measure systematic errors such as oversegmentation and undersegmentation, outliers, and overall errors. The methods must measure feature recovery and allow us to prioritize segments. We developed two complementary evaluation methods using statistical techniques and information theory. We also created a semi-automatic method to define ground truth from 3D images. We applied our methods to evaluate five segmentation algorithms developed for CT luggage screening. We validated our methods with synthetic problems and an observer evaluation. Both methods selected the same best segmentation algorithm. Human evaluation confirmed the findings. The measurement of systematic errors and prioritization helped in understanding the behavior of each segmentation algorithm. Our evaluation methods allow us to measure and explain the accuracy of segmentation algorithms.
A method to map errors in the deformable registration of 4DCT images1
Vaman, Constantin; Staub, David; Williamson, Jeffrey; Murphy, Martin J.
2010-01-01
Purpose: To present a new approach to the problem of estimating errors in deformable image registration (DIR) applied to sequential phases of a 4DCT data set. Methods: A set of displacement vector fields (DVFs) are made by registering a sequence of 4DCT phases. The DVFs are assumed to display anatomical movement, with the addition of errors due to the imaging and registration processes. The positions of physical landmarks in each CT phase are measured as ground truth for the physical movement in the DVF. Principal component analysis of the DVFs and the landmarks is used to identify and separate the eigenmodes of physical movement from the error eigenmodes. By subtracting the physical modes from the principal components of the DVFs, the registration errors are exposed and reconstructed as DIR error maps. The method is demonstrated via a simple numerical model of 4DCT DVFs that combines breathing movement with simulated maps of spatially correlated DIR errors. Results: The principal components of the simulated DVFs were observed to share the basic properties of principal components for actual 4DCT data. The simulated error maps were accurately recovered by the estimation method. Conclusions: Deformable image registration errors can have complex spatial distributions. Consequently, point-by-point landmark validation can give unrepresentative results that do not accurately reflect the registration uncertainties away from the landmarks. The authors are developing a method for mapping the complete spatial distribution of DIR errors using only a small number of ground truth validation landmarks. PMID:21158288
DOE Office of Scientific and Technical Information (OSTI.GOV)
Estep, Donald
2015-11-30
This project addressed the challenge of predictive computational analysis of strongly coupled, highly nonlinear multiphysics systems characterized by multiple physical phenomena that span a large range of length- and time-scales. Specifically, the project was focused on computational estimation of numerical error and sensitivity analysis of computational solutions with respect to variations in parameters and data. In addition, the project investigated the use of accurate computational estimates to guide efficient adaptive discretization. The project developed, analyzed and evaluated new variational adjoint-based techniques for integration, model, and data error estimation/control and sensitivity analysis, in evolutionary multiphysics multiscale simulations.
Analysis of Covariance: Is It the Appropriate Model to Study Change?
ERIC Educational Resources Information Center
Marston, Paul T., Borich, Gary D.
The four main approaches to measuring treatment effects in schools; raw gain, residual gain, covariance, and true scores; were compared. A simulation study showed true score analysis produced a large number of Type-I errors. When corrected for this error, this method showed the least power of the four. This outcome was clearly the result of the…
NASA Technical Reports Server (NTRS)
Rodriguez, G.
1981-01-01
A function space approach to smoothing is used to obtain a set of model error estimates inherent in a reduced-order model. By establishing knowledge of inevitable deficiencies in the truncated model, the error estimates provide a foundation for updating the model and thereby improving system performance. The function space smoothing solution leads to a specification of a method for computation of the model error estimates and development of model error analysis techniques for comparison between actual and estimated errors. The paper summarizes the model error estimation approach as well as an application arising in the area of modeling for spacecraft attitude control.
Model error estimation for distributed systems described by elliptic equations
NASA Technical Reports Server (NTRS)
Rodriguez, G.
1983-01-01
A function space approach is used to develop a theory for estimation of the errors inherent in an elliptic partial differential equation model for a distributed parameter system. By establishing knowledge of the inevitable deficiencies in the model, the error estimates provide a foundation for updating the model. The function space solution leads to a specification of a method for computation of the model error estimates and development of model error analysis techniques for comparison between actual and estimated errors. The paper summarizes the model error estimation approach as well as an application arising in the area of modeling for static shape determination of large flexible systems.
Blood specimen labelling errors: Implications for nephrology nursing practice.
Duteau, Jennifer
2014-01-01
Patient safety is the foundation of high-quality health care, as recognized both nationally and worldwide. Patient blood specimen identification is critical in ensuring the delivery of safe and appropriate care. The practice of nephrology nursing involves frequent patient blood specimen withdrawals to treat and monitor kidney disease. A critical review of the literature reveals that incorrect patient identification is one of the major causes of blood specimen labelling errors. Misidentified samples create a serious risk to patient safety leading to multiple specimen withdrawals, delay in diagnosis, misdiagnosis, incorrect treatment, transfusion reactions, increased length of stay and other negative patient outcomes. Barcode technology has been identified as a preferred method for positive patient identification leading to a definitive decrease in blood specimen labelling errors by as much as 83% (Askeland, et al., 2008). The use of a root cause analysis followed by an action plan is one approach to decreasing the occurrence of blood specimen labelling errors. This article will present a review of the evidence-based literature surrounding blood specimen labelling errors, followed by author recommendations for completing a root cause analysis and action plan. A failure modes and effects analysis (FMEA) will be presented as one method to determine root cause, followed by the Ottawa Model of Research Use (OMRU) as a framework for implementation of strategies to reduce blood specimen labelling errors.
Slotnick, Scott D
2017-07-01
Analysis of functional magnetic resonance imaging (fMRI) data typically involves over one hundred thousand independent statistical tests; therefore, it is necessary to correct for multiple comparisons to control familywise error. In a recent paper, Eklund, Nichols, and Knutsson used resting-state fMRI data to evaluate commonly employed methods to correct for multiple comparisons and reported unacceptable rates of familywise error. Eklund et al.'s analysis was based on the assumption that resting-state fMRI data reflect null data; however, their 'null data' actually reflected default network activity that inflated familywise error. As such, Eklund et al.'s results provide no basis to question the validity of the thousands of published fMRI studies that have corrected for multiple comparisons or the commonly employed methods to correct for multiple comparisons.
Wang, Wansheng; Chen, Long; Zhou, Jie
2015-01-01
A postprocessing technique for mixed finite element methods for the Cahn-Hilliard equation is developed and analyzed. Once the mixed finite element approximations have been computed at a fixed time on the coarser mesh, the approximations are postprocessed by solving two decoupled Poisson equations in an enriched finite element space (either on a finer grid or a higher-order space) for which many fast Poisson solvers can be applied. The nonlinear iteration is only applied to a much smaller size problem and the computational cost using Newton and direct solvers is negligible compared with the cost of the linear problem. The analysis presented here shows that this technique remains the optimal rate of convergence for both the concentration and the chemical potential approximations. The corresponding error estimate obtained in our paper, especially the negative norm error estimates, are non-trivial and different with the existing results in the literatures. PMID:27110063
1951-05-01
prccedur&:s to be of hipn accuracy. Ambij;uity of subject responizes due to overlap of entries on tU,, record sheets vas negligible. Handwriting ...experimental variables on reading errors us carried out by analysis of variance methods. For this purpose it was convenient to consider different classes...on any scale - an error ofY one numbered division. For this reason, the result. of the analysis of variance of the /10’s errors by dial types may
[Design and accuracy analysis of upper slicing system of MSCT].
Jiang, Rongjian
2013-05-01
The upper slicing system is the main components of the optical system in MSCT. This paper focuses on the design of upper slicing system and its accuracy analysis to improve the accuracy of imaging. The error of slice thickness and ray center by bearings, screw and control system were analyzed and tested. In fact, the accumulated error measured is less than 1 microm, absolute error measured is less than 10 microm. Improving the accuracy of the upper slicing system contributes to the appropriate treatment methods and success rate of treatment.
Accuracy of Time Integration Approaches for Stiff Magnetohydrodynamics Problems
NASA Astrophysics Data System (ADS)
Knoll, D. A.; Chacon, L.
2003-10-01
The simulation of complex physical processes with multiple time scales presents a continuing challenge to the computational plasma physisist due to the co-existence of fast and slow time scales. Within computational plasma physics, practitioners have developed and used linearized methods, semi-implicit methods, and time splitting in an attempt to tackle such problems. All of these methods are understood to generate numerical error. We are currently developing algorithms which remove such error for MHD problems [1,2]. These methods do not rely on linearization or time splitting. We are also attempting to analyze the errors introduced by existing ``implicit'' methods using modified equation analysis (MEA) [3]. In this presentation we will briefly cover the major findings in [3]. We will then extend this work further into MHD. This analysis will be augmented with numerical experiments with the hope of gaining insight, particularly into how these errors accumulate over many time steps. [1] L. Chacon,. D.A. Knoll, J.M. Finn, J. Comput. Phys., vol. 178, pp. 15-36 (2002) [2] L. Chacon and D.A. Knoll, J. Comput. Phys., vol. 188, pp. 573-592 (2003) [3] D.A. Knoll , L. Chacon, L.G. Margolin, V.A. Mousseau, J. Comput. Phys., vol. 185, pp. 583-611 (2003)
Minimizing treatment planning errors in proton therapy using failure mode and effects analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zheng, Yuanshui, E-mail: yuanshui.zheng@okc.procure.com; Johnson, Randall; Larson, Gary
Purpose: Failure mode and effects analysis (FMEA) is a widely used tool to evaluate safety or reliability in conventional photon radiation therapy. However, reports about FMEA application in proton therapy are scarce. The purpose of this study is to apply FMEA in safety improvement of proton treatment planning at their center. Methods: The authors performed an FMEA analysis of their proton therapy treatment planning process using uniform scanning proton beams. The authors identified possible failure modes in various planning processes, including image fusion, contouring, beam arrangement, dose calculation, plan export, documents, billing, and so on. For each error, the authorsmore » estimated the frequency of occurrence, the likelihood of being undetected, and the severity of the error if it went undetected and calculated the risk priority number (RPN). The FMEA results were used to design their quality management program. In addition, the authors created a database to track the identified dosimetric errors. Periodically, the authors reevaluated the risk of errors by reviewing the internal error database and improved their quality assurance program as needed. Results: In total, the authors identified over 36 possible treatment planning related failure modes and estimated the associated occurrence, detectability, and severity to calculate the overall risk priority number. Based on the FMEA, the authors implemented various safety improvement procedures into their practice, such as education, peer review, and automatic check tools. The ongoing error tracking database provided realistic data on the frequency of occurrence with which to reevaluate the RPNs for various failure modes. Conclusions: The FMEA technique provides a systematic method for identifying and evaluating potential errors in proton treatment planning before they result in an error in patient dose delivery. The application of FMEA framework and the implementation of an ongoing error tracking system at their clinic have proven to be useful in error reduction in proton treatment planning, thus improving the effectiveness and safety of proton therapy.« less
Errors in finite-difference computations on curvilinear coordinate systems
NASA Technical Reports Server (NTRS)
Mastin, C. W.; Thompson, J. F.
1980-01-01
Curvilinear coordinate systems were used extensively to solve partial differential equations on arbitrary regions. An analysis of truncation error in the computation of derivatives revealed why numerical results may be erroneous. A more accurate method of computing derivatives is presented.
NASA Astrophysics Data System (ADS)
Yang, Shuang-Long; Liang, Li-Ping; Liu, Hou-De; Xu, Ke-Jun
2018-03-01
Aiming at reducing the estimation error of the sensor frequency response function (FRF) estimated by the commonly used window-based spectral estimation method, the error models of interpolation and transient errors are derived in the form of non-parameter models. Accordingly, window effects on the errors are analyzed and reveal that the commonly used hanning window leads to smaller interpolation error which can also be significantly eliminated by the cubic spline interpolation method when estimating the FRF from the step response data, and window with smaller front-end value can restrain more transient error. Thus, a new dual-cosine window with its non-zero discrete Fourier transform bins at -3, -1, 0, 1, and 3 is constructed for FRF estimation. Compared with the hanning window, the new dual-cosine window has the equivalent interpolation error suppression capability and better transient error suppression capability when estimating the FRF from the step response; specifically, it reduces the asymptotic property of the transient error from O(N-2) of the hanning window method to O(N-4) while only increases the uncertainty slightly (about 0.4 dB). Then, one direction of a wind tunnel strain gauge balance which is a high order, small damping, and non-minimum phase system is employed as the example for verifying the new dual-cosine window-based spectral estimation method. The model simulation result shows that the new dual-cosine window method is better than the hanning window method for FRF estimation, and compared with the Gans method and LPM method, it has the advantages of simple computation, less time consumption, and short data requirement; the actual data calculation result of the balance FRF is consistent to the simulation result. Thus, the new dual-cosine window is effective and practical for FRF estimation.
NASA Astrophysics Data System (ADS)
Shinoda, Masahisa; Nakatani, Hidehiko
2015-04-01
We theoretically calculate the behavior of the focusing error signal in the land-groove-type optical disk when the objective lens traverses on out of the radius of the optical disk. The differential astigmatic method is employed instead of the conventional astigmatic method for generating the focusing error signals. The signal behaviors are compared and analyzed in terms of the gain difference of the slope sensitivity of the focusing error signals from the land and the groove. In our calculation, the format of digital versatile disc-random access memory (DVD-RAM) is adopted as the land-groove-type optical disk model, and advantageous conditions for suppressing the gain difference are investigated. The calculation method and results described in this paper will be reflected in the next generation land-groove-type optical disks.
Cohen, Trevor; Blatter, Brett; Almeida, Carlos; Patel, Vimla L.
2007-01-01
Objective Contemporary error research suggests that the quest to eradicate error is misguided. Error commission, detection, and recovery are an integral part of cognitive work, even at the expert level. In collaborative workspaces, the perception of potential error is directly observable: workers discuss and respond to perceived violations of accepted practice norms. As perceived violations are captured and corrected preemptively, they do not fit Reason’s widely accepted definition of error as “failure to achieve an intended outcome.” However, perceived violations suggest the aversion of potential error, and consequently have implications for error prevention. This research aims to identify and describe perceived violations of the boundaries of accepted procedure in a psychiatric emergency department (PED), and how they are resolved in practice. Design Clinical discourse from fourteen PED patient rounds was audio-recorded. Excerpts from recordings suggesting perceived violations or incidents of miscommunication were extracted and analyzed using qualitative coding methods. The results are interpreted in relation to prior research on vulnerabilities to error in the PED. Results Thirty incidents of perceived violations or miscommunication are identified and analyzed. Of these, only one medication error was formally reported. Other incidents would not have been detected by a retrospective analysis. Conclusions The analysis of perceived violations expands the data available for error analysis beyond occasional reported adverse events. These data are prospective: responses are captured in real time. This analysis supports a set of recommendations to improve the quality of care in the PED and other critical care contexts. PMID:17329728
Geolocation and Pointing Accuracy Analysis for the WindSat Sensor
NASA Technical Reports Server (NTRS)
Meissner, Thomas; Wentz, Frank J.; Purdy, William E.; Gaiser, Peter W.; Poe, Gene; Uliana, Enzo A.
2006-01-01
Geolocation and pointing accuracy analyses of the WindSat flight data are presented. The two topics were intertwined in the flight data analysis and will be addressed together. WindSat has no unusual geolocation requirements relative to other sensors, but its beam pointing knowledge accuracy is especially critical to support accurate polarimetric radiometry. Pointing accuracy was improved and verified using geolocation analysis in conjunction with scan bias analysis. nvo methods were needed to properly identify and differentiate between data time tagging and pointing knowledge errors. Matchups comparing coastlines indicated in imagery data with their known geographic locations were used to identify geolocation errors. These coastline matchups showed possible pointing errors with ambiguities as to the true source of the errors. Scan bias analysis of U, the third Stokes parameter, and of vertical and horizontal polarizations provided measurement of pointing offsets resolving ambiguities in the coastline matchup analysis. Several geolocation and pointing bias sources were incfementally eliminated resulting in pointing knowledge and geolocation accuracy that met all design requirements.
Triangular covariance factorizations for. Ph.D. Thesis. - Calif. Univ.
NASA Technical Reports Server (NTRS)
Thornton, C. L.
1976-01-01
An improved computational form of the discrete Kalman filter is derived using an upper triangular factorization of the error covariance matrix. The covariance P is factored such that P = UDUT where U is unit upper triangular and D is diagonal. Recursions are developed for propagating the U-D covariance factors together with the corresponding state estimate. The resulting algorithm, referred to as the U-D filter, combines the superior numerical precision of square root filtering techniques with an efficiency comparable to that of Kalman's original formula. Moreover, this method is easily implemented and involves no more computer storage than the Kalman algorithm. These characteristics make the U-D method an attractive realtime filtering technique. A new covariance error analysis technique is obtained from an extension of the U-D filter equations. This evaluation method is flexible and efficient and may provide significantly improved numerical results. Cost comparisons show that for a large class of problems the U-D evaluation algorithm is noticeably less expensive than conventional error analysis methods.
Assessment of the relative merits of a few methods to detect evolutionary trends.
Laurin, Michel
2010-12-01
Some of the most basic questions about the history of life concern evolutionary trends. These include determining whether or not metazoans have become more complex over time, whether or not body size tends to increase over time (the Cope-Depéret rule), or whether or not brain size has increased over time in various taxa, such as mammals and birds. Despite the proliferation of studies on such topics, assessment of the reliability of results in this field is hampered by the variability of techniques used and the lack of statistical validation of these methods. To solve this problem, simulations are performed using a variety of evolutionary models (gradual Brownian motion, speciational Brownian motion, and Ornstein-Uhlenbeck), with or without a drift of variable amplitude, with variable variance of tips, and with bounds placed close or far from the starting values and final means of simulated characters. These are used to assess the relative merits (power, Type I error rate, bias, and mean absolute value of error on slope estimate) of several statistical methods that have recently been used to assess the presence of evolutionary trends in comparative data. Results show widely divergent performance of the methods. The simple, nonphylogenetic regression (SR) and variance partitioning using phylogenetic eigenvector regression (PVR) with a broken stick selection procedure have greatly inflated Type I error rate (0.123-0.180 at a 0.05 threshold), which invalidates their use in this context. However, they have the greatest power. Most variants of Felsenstein's independent contrasts (FIC; five of which are presented) have adequate Type I error rate, although two have a slightly inflated Type I error rate with at least one of the two reference trees (0.064-0.090 error rate at a 0.05 threshold). The power of all contrast-based methods is always much lower than that of SR and PVR, except under Brownian motion with a strong trend and distant bounds. Mean absolute value of error on slope of all FIC methods is slightly higher than that of phylogenetic generalized least squares (PGLS), SR, and PVR. PGLS performs well, with low Type I error rate, low error on regression coefficient, and power comparable with some FIC methods. Four variants of skewness analysis are examined, and a new method to assess significance of results is presented. However, all have consistently low power, except in rare combinations of trees, trend strength, and distance between final means and bounds. Globally, the results clearly show that FIC-based methods and PGLS are globally better than nonphylogenetic methods and variance partitioning with PVR. FIC methods and PGLS are sensitive to the model of evolution (and, hence, to branch length errors). Our results suggest that regressing raw character contrasts against raw geological age contrasts yields a good combination of power and Type I error rate. New software to facilitate batch analysis is presented.
NASA Astrophysics Data System (ADS)
Wang, Dong; Ding, Hao; Singh, Vijay P.; Shang, Xiaosan; Liu, Dengfeng; Wang, Yuankun; Zeng, Xiankui; Wu, Jichun; Wang, Lachun; Zou, Xinqing
2015-05-01
For scientific and sustainable management of water resources, hydrologic and meteorologic data series need to be often extended. This paper proposes a hybrid approach, named WA-CM (wavelet analysis-cloud model), for data series extension. Wavelet analysis has time-frequency localization features, known as "mathematics microscope," that can decompose and reconstruct hydrologic and meteorologic series by wavelet transform. The cloud model is a mathematical representation of fuzziness and randomness and has strong robustness for uncertain data. The WA-CM approach first employs the wavelet transform to decompose the measured nonstationary series and then uses the cloud model to develop an extension model for each decomposition layer series. The final extension is obtained by summing the results of extension of each layer. Two kinds of meteorologic and hydrologic data sets with different characteristics and different influence of human activity from six (three pairs) representative stations are used to illustrate the WA-CM approach. The approach is also compared with four other methods, which are conventional correlation extension method, Kendall-Theil robust line method, artificial neural network method (back propagation, multilayer perceptron, and radial basis function), and single cloud model method. To evaluate the model performance completely and thoroughly, five measures are used, which are relative error, mean relative error, standard deviation of relative error, root mean square error, and Thiel inequality coefficient. Results show that the WA-CM approach is effective, feasible, and accurate and is found to be better than other four methods compared. The theory employed and the approach developed here can be applied to extension of data in other areas as well.
Danielson, Patrick; Yang, Limin; Jin, Suming; Homer, Collin G.; Napton, Darrell
2016-01-01
We developed a method that analyzes the quality of the cultivated cropland class mapped in the USA National Land Cover Database (NLCD) 2006. The method integrates multiple geospatial datasets and a Multi Index Integrated Change Analysis (MIICA) change detection method that captures spectral changes to identify the spatial distribution and magnitude of potential commission and omission errors for the cultivated cropland class in NLCD 2006. The majority of the commission and omission errors in NLCD 2006 are in areas where cultivated cropland is not the most dominant land cover type. The errors are primarily attributed to the less accurate training dataset derived from the National Agricultural Statistics Service Cropland Data Layer dataset. In contrast, error rates are low in areas where cultivated cropland is the dominant land cover. Agreement between model-identified commission errors and independently interpreted reference data was high (79%). Agreement was low (40%) for omission error comparison. The majority of the commission errors in the NLCD 2006 cultivated crops were confused with low-intensity developed classes, while the majority of omission errors were from herbaceous and shrub classes. Some errors were caused by inaccurate land cover change from misclassification in NLCD 2001 and the subsequent land cover post-classification process.
Xiao, Yongling; Abrahamowicz, Michal
2010-03-30
We propose two bootstrap-based methods to correct the standard errors (SEs) from Cox's model for within-cluster correlation of right-censored event times. The cluster-bootstrap method resamples, with replacement, only the clusters, whereas the two-step bootstrap method resamples (i) the clusters, and (ii) individuals within each selected cluster, with replacement. In simulations, we evaluate both methods and compare them with the existing robust variance estimator and the shared gamma frailty model, which are available in statistical software packages. We simulate clustered event time data, with latent cluster-level random effects, which are ignored in the conventional Cox's model. For cluster-level covariates, both proposed bootstrap methods yield accurate SEs, and type I error rates, and acceptable coverage rates, regardless of the true random effects distribution, and avoid serious variance under-estimation by conventional Cox-based standard errors. However, the two-step bootstrap method over-estimates the variance for individual-level covariates. We also apply the proposed bootstrap methods to obtain confidence bands around flexible estimates of time-dependent effects in a real-life analysis of cluster event times.
Mass Spectral Library Quality Assurance by Inter-Library Comparison
NASA Astrophysics Data System (ADS)
Wallace, William E.; Ji, Weihua; Tchekhovskoi, Dmitrii V.; Phinney, Karen W.; Stein, Stephen E.
2017-04-01
A method to discover and correct errors in mass spectral libraries is described. Comparing across a set of highly curated reference libraries compounds that have the same chemical structure quickly identifies entries that are outliers. In cases where three or more entries for the same compound are compared, the outlier as determined by visual inspection was almost always found to contain the error. These errors were either in the spectrum itself or in the chemical descriptors that accompanied it. The method is demonstrated on finding errors in compounds of forensic interest in the NIST/EPA/NIH Mass Spectral Library. The target list of compounds checked was the Scientific Working Group for the Analysis of Seized Drugs (SWGDRUG) mass spectral library. Some examples of errors found are described. A checklist of errors that curators should look for when performing inter-library comparisons is provided.
Mass Spectral Library Quality Assurance by Inter-Library Comparison
Wallace, W.E.; Ji, W.; Tchekhovskoi, D.V.; Phinney, K.W.; Stein, S.E.
2017-01-01
A method to discover and correct errors in mass spectral libraries is described. Comparing across a set of highly curated reference libraries compounds that have the same chemical structure quickly identifies entries that are outliers. In cases where three or more entries for the same compound are compared the outlier as determined by visual inspection was almost always found to contain the error. These errors were either in the spectrum itself or in the chemical descriptors that accompanied it. The method is demonstrated on finding errors in compounds of forensic interest in the NIST/EPA/NIH Mass Spectral Library. The target list of compounds checked was the Scientific Working Group for the Analysis of Seized Drugs (SWGDRUG) mass spectral library. Some examples of errors found are described. A checklist of errors that curators should look for when performing inter-library comparisons is provided. PMID:28127680
A Third Moment Adjusted Test Statistic for Small Sample Factor Analysis.
Lin, Johnny; Bentler, Peter M
2012-01-01
Goodness of fit testing in factor analysis is based on the assumption that the test statistic is asymptotically chi-square; but this property may not hold in small samples even when the factors and errors are normally distributed in the population. Robust methods such as Browne's asymptotically distribution-free method and Satorra Bentler's mean scaling statistic were developed under the presumption of non-normality in the factors and errors. This paper finds new application to the case where factors and errors are normally distributed in the population but the skewness of the obtained test statistic is still high due to sampling error in the observed indicators. An extension of Satorra Bentler's statistic is proposed that not only scales the mean but also adjusts the degrees of freedom based on the skewness of the obtained test statistic in order to improve its robustness under small samples. A simple simulation study shows that this third moment adjusted statistic asymptotically performs on par with previously proposed methods, and at a very small sample size offers superior Type I error rates under a properly specified model. Data from Mardia, Kent and Bibby's study of students tested for their ability in five content areas that were either open or closed book were used to illustrate the real-world performance of this statistic.
Blue, Elizabeth Marchani; Sun, Lei; Tintle, Nathan L.; Wijsman, Ellen M.
2014-01-01
When analyzing family data, we dream of perfectly informative data, even whole genome sequences (WGS) for all family members. Reality intervenes, and we find next-generation sequence (NGS) data have error, and are often too expensive or impossible to collect on everyone. Genetic Analysis Workshop 18 groups “Quality Control” and “Dropping WGS through families using GWAS framework” focused on finding, correcting, and using errors within the available sequence and family data, developing methods to infer and analyze missing sequence data among relatives, and testing for linkage and association with simulated blood pressure. We found that single nucleotide polymorphisms, NGS, and imputed data are generally concordant, but that errors are particularly likely at rare variants, homozygous genotypes, within regions with repeated sequences or structural variants, and within sequence data imputed from unrelateds. Admixture complicated identification of cryptic relatedness, but information from Mendelian transmission improved error detection and provided an estimate of the de novo mutation rate. Both genotype and pedigree errors had an adverse effect on subsequent analyses. Computationally fast rules-based imputation was accurate, but could not cover as many loci or subjects as more computationally demanding probability-based methods. Incorporating population-level data into pedigree-based imputation methods improved results. Observed data outperformed imputed data in association testing, but imputed data were also useful. We discuss the strengths and weaknesses of existing methods, and suggest possible future directions. Topics include improving communication between those performing data collection and analysis, establishing thresholds for and improving imputation quality, and incorporating error into imputation and analytical models. PMID:25112184
Why Does a Method That Fails Continue To Be Used: The Answer
Templeton, Alan R.
2009-01-01
It has been claimed that hundreds of researchers use nested clade phylogeographic analysis (NCPA) based on what the method promises rather than requiring objective validation of the method. The supposed failure of NCPA is based upon the argument that validating it by using positive controls ignored type I error, and that computer simulations have shown a high type I error. The first argument is factually incorrect: the previously published validation analysis fully accounted for both type I and type II errors. The simulations that indicate a 75% type I error rate have serious flaws and only evaluate outdated versions of NCPA. These outdated type I error rates fall precipitously when the 2003 version of single locus NCPA is used or when the 2002 multi-locus version of NCPA is used. It is shown that the treewise type I errors in single-locus NCPA can be corrected to the desired nominal level by a simple statistical procedure, and that multilocus NCPA reconstructs a simulated scenario used to discredit NCPA with 100% accuracy. Hence, NCPA is a not a failed method at all, but rather has been validated both by actual data and by simulated data in a manner that satisfies the published criteria given by its critics. The critics have come to different conclusions because they have focused on the pre-2002 versions of NCPA and have failed to take into account the extensive developments in NCPA since 2002. Hence, researchers can choose to use NCPA based upon objective critical validation that shows that NCPA delivers what it promises. PMID:19335340
Students’ Errors in Geometry Viewed from Spatial Intelligence
NASA Astrophysics Data System (ADS)
Riastuti, N.; Mardiyana, M.; Pramudya, I.
2017-09-01
Geometry is one of the difficult materials because students must have ability to visualize, describe images, draw shapes, and know the kind of shapes. This study aim is to describe student error based on Newmans’ Error Analysis in solving geometry problems viewed from spatial intelligence. This research uses descriptive qualitative method by using purposive sampling technique. The datas in this research are the result of geometri material test and interview by the 8th graders of Junior High School in Indonesia. The results of this study show that in each category of spatial intelligence has a different type of error in solving the problem on the material geometry. Errors are mostly made by students with low spatial intelligence because they have deficiencies in visual abilities. Analysis of student error viewed from spatial intelligence is expected to help students do reflection in solving the problem of geometry.
Ristić-Djurović, Jasna L; Ćirković, Saša; Mladenović, Pavle; Romčević, Nebojša; Trbovich, Alexander M
2018-04-01
A rough estimate indicated that use of samples of size not larger than ten is not uncommon in biomedical research and that many of such studies are limited to strong effects due to sample sizes smaller than six. For data collected from biomedical experiments it is also often unknown if mathematical requirements incorporated in the sample comparison methods are satisfied. Computer simulated experiments were used to examine performance of methods for qualitative sample comparison and its dependence on the effectiveness of exposure, effect intensity, distribution of studied parameter values in the population, and sample size. The Type I and Type II errors, their average, as well as the maximal errors were considered. The sample size 9 and the t-test method with p = 5% ensured error smaller than 5% even for weak effects. For sample sizes 6-8 the same method enabled detection of weak effects with errors smaller than 20%. If the sample sizes were 3-5, weak effects could not be detected with an acceptable error; however, the smallest maximal error in the most general case that includes weak effects is granted by the standard error of the mean method. The increase of sample size from 5 to 9 led to seven times more accurate detection of weak effects. Strong effects were detected regardless of the sample size and method used. The minimal recommended sample size for biomedical experiments is 9. Use of smaller sizes and the method of their comparison should be justified by the objective of the experiment. Copyright © 2018 Elsevier B.V. All rights reserved.
Survey and Method for Determination of Trajectory Predictor Requirements
NASA Technical Reports Server (NTRS)
Rentas, Tamika L.; Green, Steven M.; Cate, Karen Tung
2009-01-01
A survey of air-traffic-management researchers, representing a broad range of automation applications, was conducted to document trajectory-predictor requirements for future decision-support systems. Results indicated that the researchers were unable to articulate a basic set of trajectory-prediction requirements for their automation concepts. Survey responses showed the need to establish a process to help developers determine the trajectory-predictor-performance requirements for their concepts. Two methods for determining trajectory-predictor requirements are introduced. A fast-time simulation method is discussed that captures the sensitivity of a concept to the performance of its trajectory-prediction capability. A characterization method is proposed to provide quicker, yet less precise results, based on analysis and simulation to characterize the trajectory-prediction errors associated with key modeling options for a specific concept. Concept developers can then identify the relative sizes of errors associated with key modeling options, and qualitatively determine which options lead to significant errors. The characterization method is demonstrated for a case study involving future airport surface traffic management automation. Of the top four sources of error, results indicated that the error associated with accelerations to and from turn speeds was unacceptable, the error associated with the turn path model was acceptable, and the error associated with taxi-speed estimation was of concern and needed a higher fidelity concept simulation to obtain a more precise result
Counting OCR errors in typeset text
NASA Astrophysics Data System (ADS)
Sandberg, Jonathan S.
1995-03-01
Frequently object recognition accuracy is a key component in the performance analysis of pattern matching systems. In the past three years, the results of numerous excellent and rigorous studies of OCR system typeset-character accuracy (henceforth OCR accuracy) have been published, encouraging performance comparisons between a variety of OCR products and technologies. These published figures are important; OCR vendor advertisements in the popular trade magazines lead readers to believe that published OCR accuracy figures effect market share in the lucrative OCR market. Curiously, a detailed review of many of these OCR error occurrence counting results reveals that they are not reproducible as published and they are not strictly comparable due to larger variances in the counts than would be expected by the sampling variance. Naturally, since OCR accuracy is based on a ratio of the number of OCR errors over the size of the text searched for errors, imprecise OCR error accounting leads to similar imprecision in OCR accuracy. Some published papers use informal, non-automatic, or intuitively correct OCR error accounting. Still other published results present OCR error accounting methods based on string matching algorithms such as dynamic programming using Levenshtein (edit) distance but omit critical implementation details (such as the existence of suspect markers in the OCR generated output or the weights used in the dynamic programming minimization procedure). The problem with not specifically revealing the accounting method is that the number of errors found by different methods are significantly different. This paper identifies the basic accounting methods used to measure OCR errors in typeset text and offers an evaluation and comparison of the various accounting methods.
Zhang, Jiayu; Li, Jie; Zhang, Xi; Che, Xiaorui; Huang, Yugang; Feng, Kaiqiang
2018-01-01
The Semi-Strapdown Inertial Navigation System (SSINS) provides a new solution to attitude measurement of a high-speed rotating missile. However, micro-electro-mechanical-systems (MEMS) inertial measurement unit (MIMU) outputs are corrupted by significant sensor errors. In order to improve the navigation precision, a rotation modulation technology method called Rotation Semi-Strapdown Inertial Navigation System (RSSINS) is introduced into SINS. In fact, the stability of the modulation angular rate is difficult to achieve in a high-speed rotation environment. The changing rotary angular rate has an impact on the inertial sensor error self-compensation. In this paper, the influence of modulation angular rate error, including acceleration-deceleration process, and instability of the angular rate on the navigation accuracy of RSSINS is deduced and the error characteristics of the reciprocating rotation scheme are analyzed. A new compensation method is proposed to remove or reduce sensor errors so as to make it possible to maintain high precision autonomous navigation performance by MIMU when there is no external aid. Experiments have been carried out to validate the performance of the method. In addition, the proposed method is applicable for modulation angular rate error compensation under various dynamic conditions. PMID:29734707
Linguistic pattern analysis of misspellings of typically developing writers in grades 1-9.
Bahr, Ruth Huntley; Sillian, Elaine R; Berninger, Virginia W; Dow, Michael
2012-12-01
A mixed-methods approach, evaluating triple word-form theory, was used to describe linguistic patterns of misspellings. Spelling errors were taken from narrative and expository writing samples provided by 888 typically developing students in Grades 1-9. Errors were coded by category (phonological, orthographic, and morphological) and specific linguistic feature affected. Grade-level effects were analyzed with trend analysis. Qualitative analyses determined frequent error types and how use of specific linguistic features varied across grades. Phonological, orthographic, and morphological errors were noted across all grades, but orthographic errors predominated. Linear trends revealed developmental shifts in error proportions for the orthographic and morphological categories between Grades 4 and 5. Similar error types were noted across age groups, but the nature of linguistic feature error changed with age. Triple word-form theory was supported. By Grade 1, orthographic errors predominated, and phonological and morphological error patterns were evident. Morphological errors increased in relative frequency in older students, probably due to a combination of word-formation issues and vocabulary growth. These patterns suggest that normal spelling development reflects nonlinear growth and that it takes a long time to develop a robust orthographic lexicon that coordinates phonology, orthography, and morphology and supports word-specific, conventional spelling.
Wavefront error budget and optical manufacturing tolerance analysis for 1.8m telescope system
NASA Astrophysics Data System (ADS)
Wei, Kai; Zhang, Xuejun; Xian, Hao; Rao, Changhui; Zhang, Yudong
2010-05-01
We present the wavefront error budget and optical manufacturing tolerance analysis for 1.8m telescope. The error budget accounts for aberrations induced by optical design residual, manufacturing error, mounting effects, and misalignments. The initial error budget has been generated from the top-down. There will also be an ongoing effort to track the errors from the bottom-up. This will aid in identifying critical areas of concern. The resolution of conflicts will involve a continual process of review and comparison of the top-down and bottom-up approaches, modifying both as needed to meet the top level requirements in the end. As we all know, the adaptive optical system will correct for some of the telescope system imperfections but it cannot be assumed that all errors will be corrected. Therefore, two kinds of error budgets will be presented, one is non-AO top-down error budget and the other is with-AO system error budget. The main advantage of the method is that at the same time it describes the final performance of the telescope, and gives to the optical manufacturer the maximum freedom to define and possibly modify its own manufacturing error budget.
NASA Technical Reports Server (NTRS)
Gordon, Steven C.
1993-01-01
Spacecraft in orbit near libration point L1 in the Sun-Earth system are excellent platforms for research concerning solar effects on the terrestrial environment. One spacecraft mission launched in 1978 used an L1 orbit for nearly 4 years, and future L1 orbital missions are also being planned. Orbit determination and station-keeping are, however, required for these orbits. In particular, orbit determination error analysis may be used to compute the state uncertainty after a predetermined tracking period; the predicted state uncertainty levels then will impact the control costs computed in station-keeping simulations. Error sources, such as solar radiation pressure and planetary mass uncertainties, are also incorporated. For future missions, there may be some flexibility in the type and size of the spacecraft's nominal trajectory, but different orbits may produce varying error analysis and station-keeping results. The nominal path, for instance, can be (nearly) periodic or distinctly quasi-periodic. A periodic 'halo' orbit may be constructed to be significantly larger than a quasi-periodic 'Lissajous' path; both may meet mission requirements, but perhaps the required control costs for these orbits are probably different. Also for this spacecraft tracking and control simulation problem, experimental design methods can be used to determine the most significant uncertainties. That is, these methods can determine the error sources in the tracking and control problem that most impact the control cost (output); it also produces an equation that gives the approximate functional relationship between the error inputs and the output.
CME Velocity and Acceleration Error Estimates Using the Bootstrap Method
NASA Technical Reports Server (NTRS)
Michalek, Grzegorz; Gopalswamy, Nat; Yashiro, Seiji
2017-01-01
The bootstrap method is used to determine errors of basic attributes of coronal mass ejections (CMEs) visually identified in images obtained by the Solar and Heliospheric Observatory (SOHO) mission's Large Angle and Spectrometric Coronagraph (LASCO) instruments. The basic parameters of CMEs are stored, among others, in a database known as the SOHO/LASCO CME catalog and are widely employed for many research studies. The basic attributes of CMEs (e.g. velocity and acceleration) are obtained from manually generated height-time plots. The subjective nature of manual measurements introduces random errors that are difficult to quantify. In many studies the impact of such measurement errors is overlooked. In this study we present a new possibility to estimate measurements errors in the basic attributes of CMEs. This approach is a computer-intensive method because it requires repeating the original data analysis procedure several times using replicate datasets. This is also commonly called the bootstrap method in the literature. We show that the bootstrap approach can be used to estimate the errors of the basic attributes of CMEs having moderately large numbers of height-time measurements. The velocity errors are in the vast majority small and depend mostly on the number of height-time points measured for a particular event. In the case of acceleration, the errors are significant, and for more than half of all CMEs, they are larger than the acceleration itself.
Balancing aggregation and smoothing errors in inverse models
Turner, A. J.; Jacob, D. J.
2015-06-30
Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function ofmore » state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.« less
Balancing aggregation and smoothing errors in inverse models
NASA Astrophysics Data System (ADS)
Turner, A. J.; Jacob, D. J.
2015-01-01
Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function of state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.
Balancing aggregation and smoothing errors in inverse models
NASA Astrophysics Data System (ADS)
Turner, A. J.; Jacob, D. J.
2015-06-01
Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function of state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.
Huang, Junhui; Xue, Qi; Wang, Zhao; Gao, Jianmin
2016-09-03
While color-coding methods have improved the measuring efficiency of a structured light three-dimensional (3D) measurement system, they decreased the measuring accuracy significantly due to lateral chromatic aberration (LCA). In this study, the LCA in a structured light measurement system is analyzed, and a method is proposed to compensate the error caused by the LCA. Firstly, based on the projective transformation, a 3D error map of LCA is constructed in the projector images by using a flat board and comparing the image coordinates of red, green and blue circles with the coordinates of white circles at preselected sample points within the measurement volume. The 3D map consists of the errors, which are the equivalent errors caused by LCA of the camera and projector. Then in measurements, error values of LCA are calculated and compensated to correct the projector image coordinates through the 3D error map and a tri-linear interpolation method. Eventually, 3D coordinates with higher accuracy are re-calculated according to the compensated image coordinates. The effectiveness of the proposed method is verified in the following experiments.
Huang, Junhui; Xue, Qi; Wang, Zhao; Gao, Jianmin
2016-01-01
While color-coding methods have improved the measuring efficiency of a structured light three-dimensional (3D) measurement system, they decreased the measuring accuracy significantly due to lateral chromatic aberration (LCA). In this study, the LCA in a structured light measurement system is analyzed, and a method is proposed to compensate the error caused by the LCA. Firstly, based on the projective transformation, a 3D error map of LCA is constructed in the projector images by using a flat board and comparing the image coordinates of red, green and blue circles with the coordinates of white circles at preselected sample points within the measurement volume. The 3D map consists of the errors, which are the equivalent errors caused by LCA of the camera and projector. Then in measurements, error values of LCA are calculated and compensated to correct the projector image coordinates through the 3D error map and a tri-linear interpolation method. Eventually, 3D coordinates with higher accuracy are re-calculated according to the compensated image coordinates. The effectiveness of the proposed method is verified in the following experiments. PMID:27598174
Star centroiding error compensation for intensified star sensors.
Jiang, Jie; Xiong, Kun; Yu, Wenbo; Yan, Jinyun; Zhang, Guangjun
2016-12-26
A star sensor provides high-precision attitude information by capturing a stellar image; however, the traditional star sensor has poor dynamic performance, which is attributed to its low sensitivity. Regarding the intensified star sensor, the image intensifier is utilized to improve the sensitivity, thereby further improving the dynamic performance of the star sensor. However, the introduction of image intensifier results in star centroiding accuracy decrease, further influencing the attitude measurement precision of the star sensor. A star centroiding error compensation method for intensified star sensors is proposed in this paper to reduce the influences. First, the imaging model of the intensified detector, which includes the deformation parameter of the optical fiber panel, is established based on the orthographic projection through the analysis of errors introduced by the image intensifier. Thereafter, the position errors at the target points based on the model are obtained by using the Levenberg-Marquardt (LM) optimization method. Last, the nearest trigonometric interpolation method is presented to compensate for the arbitrary centroiding error of the image plane. Laboratory calibration result and night sky experiment result show that the compensation method effectively eliminates the error introduced by the image intensifier, thus remarkably improving the precision of the intensified star sensors.
Nonlinear analysis and dynamic compensation of stylus scanning measurement with wide range
NASA Astrophysics Data System (ADS)
Hui, Heiyang; Liu, Xiaojun; Lu, Wenlong
2011-12-01
Surface topography is an important geometrical feature of a workpiece that influences its quality and functions such as friction, wearing, lubrication and sealing. Precision measurement of surface topography is fundamental for product quality characterizing and assurance. Stylus scanning technique is a widely used method for surface topography measurement, and it is also regarded as the international standard method for 2-D surface characterizing. Usually surface topography, including primary profile, waviness and roughness, can be measured precisely and efficiently by this method. However, by stylus scanning method to measure curved surface topography, the nonlinear error is unavoidable because of the difference of horizontal position of the actual measured point from given sampling point and the nonlinear transformation process from vertical displacement of the stylus tip to angle displacement of the stylus arm, and the error increases with the increasing of measuring range. In this paper, a wide range stylus scanning measurement system based on cylindrical grating interference principle is constructed, the originations of the nonlinear error are analyzed, the error model is established and a solution to decrease the nonlinear error is proposed, through which the error of the collected data is dynamically compensated.
Method for computing self-consistent solution in a gun code
Nelson, Eric M
2014-09-23
Complex gun code computations can be made to converge more quickly based on a selection of one or more relaxation parameters. An eigenvalue analysis is applied to error residuals to identify two error eigenvalues that are associated with respective error residuals. Relaxation values can be selected based on these eigenvalues so that error residuals associated with each can be alternately reduced in successive iterations. In some examples, relaxation values that would be unstable if used alone can be used.
Yang, Jie; Liu, Qingquan; Dai, Wei
2017-02-01
To improve the air temperature observation accuracy, a low measurement error temperature sensor is proposed. A computational fluid dynamics (CFD) method is implemented to obtain temperature errors under various environmental conditions. Then, a temperature error correction equation is obtained by fitting the CFD results using a genetic algorithm method. The low measurement error temperature sensor, a naturally ventilated radiation shield, a thermometer screen, and an aspirated temperature measurement platform are characterized in the same environment to conduct the intercomparison. The aspirated platform served as an air temperature reference. The mean temperature errors of the naturally ventilated radiation shield and the thermometer screen are 0.74 °C and 0.37 °C, respectively. In contrast, the mean temperature error of the low measurement error temperature sensor is 0.11 °C. The mean absolute error and the root mean square error between the corrected results and the measured results are 0.008 °C and 0.01 °C, respectively. The correction equation allows the temperature error of the low measurement error temperature sensor to be reduced by approximately 93.8%. The low measurement error temperature sensor proposed in this research may be helpful to provide a relatively accurate air temperature result.
Sun, You-Wen; Liu, Wen-Qing; Wang, Shi-Mei; Huang, Shu-Hua; Yu, Xiao-Man
2011-10-01
A method of interference correction for nondispersive infrared multi-component gas analysis was described. According to the successive integral gas absorption models and methods, the influence of temperature and air pressure on the integral line strengths and linetype was considered, and based on Lorentz detuning linetypes, the absorption cross sections and response coefficients of H2O, CO2, CO, and NO on each filter channel were obtained. The four dimension linear regression equations for interference correction were established by response coefficients, the absorption cross interference was corrected by solving the multi-dimensional linear regression equations, and after interference correction, the pure absorbance signal on each filter channel was only controlled by the corresponding target gas concentration. When the sample cell was filled with gas mixture with a certain concentration proportion of CO, NO and CO2, the pure absorbance after interference correction was used for concentration inversion, the inversion concentration error for CO2 is 2.0%, the inversion concentration error for CO is 1.6%, and the inversion concentration error for NO is 1.7%. Both the theory and experiment prove that the interference correction method proposed for NDIR multi-component gas analysis is feasible.
Steward, Christine D.; Stocker, Sheila A.; Swenson, Jana M.; O’Hara, Caroline M.; Edwards, Jonathan R.; Gaynes, Robert P.; McGowan, John E.; Tenover, Fred C.
1999-01-01
Fluoroquinolone resistance appears to be increasing in many species of bacteria, particularly in those causing nosocomial infections. However, the accuracy of some antimicrobial susceptibility testing methods for detecting fluoroquinolone resistance remains uncertain. Therefore, we compared the accuracy of the results of agar dilution, disk diffusion, MicroScan Walk Away Neg Combo 15 conventional panels, and Vitek GNS-F7 cards to the accuracy of the results of the broth microdilution reference method for detection of ciprofloxacin and ofloxacin resistance in 195 clinical isolates of the family Enterobacteriaceae collected from six U.S. hospitals for a national surveillance project (Project ICARE [Intensive Care Antimicrobial Resistance Epidemiology]). For ciprofloxacin, very major error rates were 0% (disk diffusion and MicroScan), 0.9% (agar dilution), and 2.7% (Vitek), while major error rates ranged from 0% (agar dilution) to 3.7% (MicroScan and Vitek). Minor error rates ranged from 12.3% (agar dilution) to 20.5% (MicroScan). For ofloxacin, no very major errors were observed, and major errors were noted only with MicroScan (3.7% major error rate). Minor error rates ranged from 8.2% (agar dilution) to 18.5% (Vitek). Minor errors for all methods were substantially reduced when results with MICs within ±1 dilution of the broth microdilution reference MIC were excluded from analysis. However, the high number of minor errors by all test systems remains a concern. PMID:9986809
Quotation accuracy in medical journal articles-a systematic review and meta-analysis.
Jergas, Hannah; Baethge, Christopher
2015-01-01
Background. Quotations and references are an indispensable element of scientific communication. They should support what authors claim or provide important background information for readers. Studies indicate, however, that quotations not serving their purpose-quotation errors-may be prevalent. Methods. We carried out a systematic review, meta-analysis and meta-regression of quotation errors, taking account of differences between studies in error ascertainment. Results. Out of 559 studies screened we included 28 in the main analysis, and estimated major, minor and total quotation error rates of 11,9%, 95% CI [8.4, 16.6] 11.5% [8.3, 15.7], and 25.4% [19.5, 32.4]. While heterogeneity was substantial, even the lowest estimate of total quotation errors was considerable (6.7%). Indirect references accounted for less than one sixth of all quotation problems. The findings remained robust in a number of sensitivity and subgroup analyses (including risk of bias analysis) and in meta-regression. There was no indication of publication bias. Conclusions. Readers of medical journal articles should be aware of the fact that quotation errors are common. Measures against quotation errors include spot checks by editors and reviewers, correct placement of citations in the text, and declarations by authors that they have checked cited material. Future research should elucidate if and to what degree quotation errors are detrimental to scientific progress.
Hip joint center localisation: A biomechanical application to hip arthroplasty population
Bouffard, Vicky; Begon, Mickael; Champagne, Annick; Farhadnia, Payam; Vendittoli, Pascal-André; Lavigne, Martin; Prince, François
2012-01-01
AIM: To determine hip joint center (HJC) location on hip arthroplasty population comparing predictive and functional approaches with radiographic measurements. METHODS: The distance between the HJC and the mid-pelvis was calculated and compared between the three approaches. The localisation error between the predictive and functional approach was compared using the radiographic measurements as the reference. The operated leg was compared to the non-operated leg. RESULTS: A significant difference was found for the distance between the HJC and the mid-pelvis when comparing the predictive and functional method. The functional method leads to fewer errors. A statistical difference was found for the localization error between the predictive and functional method. The functional method is twice more precise. CONCLUSION: Although being more individualized, the functional method improves HJC localization and should be used in three-dimensional gait analysis. PMID:22919569
Flexible methods for segmentation evaluation: Results from CT-based luggage screening
Karimi, Seemeen; Jiang, Xiaoqian; Cosman, Pamela; Martz, Harry
2017-01-01
BACKGROUND Imaging systems used in aviation security include segmentation algorithms in an automatic threat recognition pipeline. The segmentation algorithms evolve in response to emerging threats and changing performance requirements. Analysis of segmentation algorithms’ behavior, including the nature of errors and feature recovery, facilitates their development. However, evaluation methods from the literature provide limited characterization of the segmentation algorithms. OBJECTIVE To develop segmentation evaluation methods that measure systematic errors such as oversegmentation and undersegmentation, outliers, and overall errors. The methods must measure feature recovery and allow us to prioritize segments. METHODS We developed two complementary evaluation methods using statistical techniques and information theory. We also created a semi-automatic method to define ground truth from 3D images. We applied our methods to evaluate five segmentation algorithms developed for CT luggage screening. We validated our methods with synthetic problems and an observer evaluation. RESULTS Both methods selected the same best segmentation algorithm. Human evaluation confirmed the findings. The measurement of systematic errors and prioritization helped in understanding the behavior of each segmentation algorithm. CONCLUSIONS Our evaluation methods allow us to measure and explain the accuracy of segmentation algorithms. PMID:24699346
NASA Astrophysics Data System (ADS)
Semenov, Z. V.; Labusov, V. A.
2017-11-01
Results of studying the errors of indirect monitoring by means of computer simulations are reported. The monitoring method is based on measuring spectra of reflection from additional monitoring substrates in a wide spectral range. Special software (Deposition Control Simulator) is developed, which allows one to estimate the influence of the monitoring system parameters (noise of the photodetector array, operating spectral range of the spectrometer and errors of its calibration in terms of wavelengths, drift of the radiation source intensity, and errors in the refractive index of deposited materials) on the random and systematic errors of deposited layer thickness measurements. The direct and inverse problems of multilayer coatings are solved using the OptiReOpt library. Curves of the random and systematic errors of measurements of the deposited layer thickness as functions of the layer thickness are presented for various values of the system parameters. Recommendations are given on using the indirect monitoring method for the purpose of reducing the layer thickness measurement error.
Impact and quantification of the sources of error in DNA pooling designs.
Jawaid, A; Sham, P
2009-01-01
The analysis of genome wide variation offers the possibility of unravelling the genes involved in the pathogenesis of disease. Genome wide association studies are also particularly useful for identifying and validating targets for therapeutic intervention as well as for detecting markers for drug efficacy and side effects. The cost of such large-scale genetic association studies may be reduced substantially by the analysis of pooled DNA from multiple individuals. However, experimental errors inherent in pooling studies lead to a potential increase in the false positive rate and a loss in power compared to individual genotyping. Here we quantify various sources of experimental error using empirical data from typical pooling experiments and corresponding individual genotyping counts using two statistical methods. We provide analytical formulas for calculating these different errors in the absence of complete information, such as replicate pool formation, and for adjusting for the errors in the statistical analysis. We demonstrate that DNA pooling has the potential of estimating allele frequencies accurately, and adjusting the pooled allele frequency estimates for differential allelic amplification considerably improves accuracy. Estimates of the components of error show that differential allelic amplification is the most important contributor to the error variance in absolute allele frequency estimation, followed by allele frequency measurement and pool formation errors. Our results emphasise the importance of minimising experimental errors and obtaining correct error estimates in genetic association studies.
Zhao, Qilong; Strykowski, Gabriel; Li, Jiancheng; Pan, Xiong; Xu, Xinyu
2017-05-25
Gravity data gaps in mountainous areas are nowadays often filled in with the data from airborne gravity surveys. Because of the errors caused by the airborne gravimeter sensors, and because of rough flight conditions, such errors cannot be completely eliminated. The precision of the gravity disturbances generated by the airborne gravimetry is around 3-5 mgal. A major obstacle in using airborne gravimetry are the errors caused by the downward continuation. In order to improve the results the external high-accuracy gravity information e.g., from the surface data can be used for high frequency correction, while satellite information can be applying for low frequency correction. Surface data may be used to reduce the systematic errors, while regularization methods can reduce the random errors in downward continuation. Airborne gravity surveys are sometimes conducted in mountainous areas and the most extreme area of the world for this type of survey is the Tibetan Plateau. Since there are no high-accuracy surface gravity data available for this area, the above error minimization method involving the external gravity data cannot be used. We propose a semi-parametric downward continuation method in combination with regularization to suppress the systematic error effect and the random error effect in the Tibetan Plateau; i.e., without the use of the external high-accuracy gravity data. We use a Louisiana airborne gravity dataset from the USA National Oceanic and Atmospheric Administration (NOAA) to demonstrate that the new method works effectively. Furthermore, and for the Tibetan Plateau we show that the numerical experiment is also successfully conducted using the synthetic Earth Gravitational Model 2008 (EGM08)-derived gravity data contaminated with the synthetic errors. The estimated systematic errors generated by the method are close to the simulated values. In addition, we study the relationship between the downward continuation altitudes and the error effect. The analysis results show that the proposed semi-parametric method combined with regularization is efficient to address such modelling problems.
Zhao, Qilong; Strykowski, Gabriel; Li, Jiancheng; Pan, Xiong; Xu, Xinyu
2017-01-01
Gravity data gaps in mountainous areas are nowadays often filled in with the data from airborne gravity surveys. Because of the errors caused by the airborne gravimeter sensors, and because of rough flight conditions, such errors cannot be completely eliminated. The precision of the gravity disturbances generated by the airborne gravimetry is around 3–5 mgal. A major obstacle in using airborne gravimetry are the errors caused by the downward continuation. In order to improve the results the external high-accuracy gravity information e.g., from the surface data can be used for high frequency correction, while satellite information can be applying for low frequency correction. Surface data may be used to reduce the systematic errors, while regularization methods can reduce the random errors in downward continuation. Airborne gravity surveys are sometimes conducted in mountainous areas and the most extreme area of the world for this type of survey is the Tibetan Plateau. Since there are no high-accuracy surface gravity data available for this area, the above error minimization method involving the external gravity data cannot be used. We propose a semi-parametric downward continuation method in combination with regularization to suppress the systematic error effect and the random error effect in the Tibetan Plateau; i.e., without the use of the external high-accuracy gravity data. We use a Louisiana airborne gravity dataset from the USA National Oceanic and Atmospheric Administration (NOAA) to demonstrate that the new method works effectively. Furthermore, and for the Tibetan Plateau we show that the numerical experiment is also successfully conducted using the synthetic Earth Gravitational Model 2008 (EGM08)-derived gravity data contaminated with the synthetic errors. The estimated systematic errors generated by the method are close to the simulated values. In addition, we study the relationship between the downward continuation altitudes and the error effect. The analysis results show that the proposed semi-parametric method combined with regularization is efficient to address such modelling problems. PMID:28587086
NASA Astrophysics Data System (ADS)
Zhao, Q.
2017-12-01
Gravity data gaps in mountainous areas are nowadays often filled in with the data from airborne gravity surveys. Because of the errors caused by the airborne gravimeter sensors, and because of rough flight conditions, such errors cannot be completely eliminated. The precision of the gravity disturbances generated by the airborne gravimetry is around 3-5 mgal. A major obstacle in using airborne gravimetry are the errors caused by the downward continuation. In order to improve the results the external high-accuracy gravity information e.g., from the surface data can be used for high frequency correction, while satellite information can be applying for low frequency correction. Surface data may be used to reduce the systematic errors, while regularization methods can reduce the random errors in downward continuation. Airborne gravity surveys are sometimes conducted in mountainous areas and the most extreme area of the world for this type of survey is the Tibetan Plateau. Since there are no high-accuracy surface gravity data available for this area, the above error minimization method involving the external gravity data cannot be used. We propose a semi-parametric downward continuation method in combination with regularization to suppress the systematic error effect and the random error effect in the Tibetan Plateau; i.e., without the use of the external high-accuracy gravity data. We use a Louisiana airborne gravity dataset from the USA National Oceanic and Atmospheric Administration (NOAA) to demonstrate that the new method works effectively. Furthermore, and for the Tibetan Plateau we show that the numerical experiment is also successfully conducted using the synthetic Earth Gravitational Model 2008 (EGM08)-derived gravity data contaminated with the synthetic errors. The estimated systematic errors generated by the method are close to the simulated values. In addition, we study the relationship between the downward continuation altitudes and the error effect. The analysis results show that the proposed semi-parametric method combined with regularization is efficient to address such modelling problems.
A day in the life of a volunteer incident commander: errors, pressures and mitigating strategies.
Bearman, Christopher; Bremner, Peter A
2013-05-01
To meet an identified gap in the literature this paper investigates the tasks that a volunteer incident commander needs to carry out during an incident, the errors that can be made and the way that errors are managed. In addition, pressure from goal seduction and situation aversion were also examined. Volunteer incident commanders participated in a two-part interview consisting of a critical decision method interview and discussions about a hierarchical task analysis constructed by the authors. A SHERPA analysis was conducted to further identify potential errors. The results identified the key tasks, errors with extreme risk, pressures from strong situations and mitigating strategies for errors and pressures. The errors and pressures provide a basic set of issues that need to be managed by both volunteer incident commanders and fire agencies. The mitigating strategies identified here suggest some ways that this can be done. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.
Accuracy analysis for triangulation and tracking based on time-multiplexed structured light.
Wagner, Benjamin; Stüber, Patrick; Wissel, Tobias; Bruder, Ralf; Schweikard, Achim; Ernst, Floris
2014-08-01
The authors' research group is currently developing a new optical head tracking system for intracranial radiosurgery. This tracking system utilizes infrared laser light to measure features of the soft tissue on the patient's forehead. These features are intended to offer highly accurate registration with respect to the rigid skull structure by means of compensating for the soft tissue. In this context, the system also has to be able to quickly generate accurate reconstructions of the skin surface. For this purpose, the authors have developed a laser scanning device which uses time-multiplexed structured light to triangulate surface points. The accuracy of the authors' laser scanning device is analyzed and compared for different triangulation methods. These methods are given by the Linear-Eigen method and a nonlinear least squares method. Since Microsoft's Kinect camera represents an alternative for fast surface reconstruction, the authors' results are also compared to the triangulation accuracy of the Kinect device. Moreover, the authors' laser scanning device was used for tracking of a rigid object to determine how this process is influenced by the remaining triangulation errors. For this experiment, the scanning device was mounted to the end-effector of a robot to be able to calculate a ground truth for the tracking. The analysis of the triangulation accuracy of the authors' laser scanning device revealed a root mean square (RMS) error of 0.16 mm. In comparison, the analysis of the triangulation accuracy of the Kinect device revealed a RMS error of 0.89 mm. It turned out that the remaining triangulation errors only cause small inaccuracies for the tracking of a rigid object. Here, the tracking accuracy was given by a RMS translational error of 0.33 mm and a RMS rotational error of 0.12°. This paper shows that time-multiplexed structured light can be used to generate highly accurate reconstructions of surfaces. Furthermore, the reconstructed point sets can be used for high-accuracy tracking of objects, meeting the strict requirements of intracranial radiosurgery.
NASA Technical Reports Server (NTRS)
Jekeli, C.
1979-01-01
Through the method of truncation functions, the oceanic geoid undulation is divided into two constituents: an inner zone contribution expressed as an integral of surface gravity disturbances over a spherical cap; and an outer zone contribution derived from a finite set of potential harmonic coefficients. Global, average error estimates are formulated for undulation differences, thereby providing accuracies for a relative geoid. The error analysis focuses on the outer zone contribution for which the potential coefficient errors are modeled. The method of computing undulations based on gravity disturbance data for the inner zone is compared to the similar, conventional method which presupposes gravity anomaly data within this zone.
Research on effects of phase error in phase-shifting interferometer
NASA Astrophysics Data System (ADS)
Wang, Hongjun; Wang, Zhao; Zhao, Hong; Tian, Ailing; Liu, Bingcai
2007-12-01
Referring to phase-shifting interferometry technology, the phase shifting error from the phase shifter is the main factor that directly affects the measurement accuracy of the phase shifting interferometer. In this paper, the resources and sorts of phase shifting error were introduction, and some methods to eliminate errors were mentioned. Based on the theory of phase shifting interferometry, the effects of phase shifting error were analyzed in detail. The Liquid Crystal Display (LCD) as a new shifter has advantage as that the phase shifting can be controlled digitally without any mechanical moving and rotating element. By changing coded image displayed on LCD, the phase shifting in measuring system was induced. LCD's phase modulation characteristic was analyzed in theory and tested. Based on Fourier transform, the effect model of phase error coming from LCD was established in four-step phase shifting interferometry. And the error range was obtained. In order to reduce error, a new error compensation algorithm was put forward. With this method, the error can be obtained by process interferogram. The interferogram can be compensated, and the measurement results can be obtained by four-step phase shifting interferogram. Theoretical analysis and simulation results demonstrate the feasibility of this approach to improve measurement accuracy.
NASA Technical Reports Server (NTRS)
Troy, B. E., Jr.; Maier, E. J.
1975-01-01
The effects of the grid transparency and finite collector size on the values of thermal ion density and temperature determined by the standard RPA (retarding potential analyzer) analysis method are investigated. The current-voltage curves calculated for varying RPA parameters and a given ion mass, temperature, and density are analyzed by the standard RPA method. It is found that only small errors in temperature and density are introduced for an RPA with typical dimensions, and that even when the density error is substantial for nontypical dimensions, the temperature error remains minimum.
Tan, Bing; Huang, Min; Zhu, Qibing; Guo, Ya; Qin, Jianwei
2017-09-01
The laser induced breakdown spectroscopy (LIBS) technique is an effective method to detect material composition by obtaining the plasma emission spectrum. The overlapping peaks in the spectrum are a fundamental problem in the qualitative and quantitative analysis of LIBS. Based on a curve fitting method, this paper studies an error compensation method to achieve the decomposition and correction of overlapping peaks. The vital step is that the fitting residual is fed back to the overlapping peaks and performs multiple curve fitting processes to obtain a lower residual result. For the quantitative experiments of Cu, the Cu-Fe overlapping peaks in the range of 321-327 nm obtained from the LIBS spectrum of five different concentrations of CuSO 4 ·5H 2 O solution were decomposed and corrected using curve fitting and error compensation methods. Compared with the curve fitting method, the error compensation reduced the fitting residual about 18.12-32.64% and improved the correlation about 0.86-1.82%. Then, the calibration curve between the intensity and concentration of the Cu was established. It can be seen that the error compensation method exhibits a higher linear correlation between the intensity and concentration of Cu, which can be applied to the decomposition and correction of overlapping peaks in the LIBS spectrum.
Error analysis of finite difference schemes applied to hyperbolic initial boundary value problems
NASA Technical Reports Server (NTRS)
Skollermo, G.
1979-01-01
Finite difference methods for the numerical solution of mixed initial boundary value problems for hyperbolic equations are studied. The reported investigation has the objective to develop a technique for the total error analysis of a finite difference scheme, taking into account initial approximations, boundary conditions, and interior approximation. Attention is given to the Cauchy problem and the initial approximation, the homogeneous problem in an infinite strip with inhomogeneous boundary data, the reflection of errors in the boundaries, and two different boundary approximations for the leapfrog scheme with a fourth order accurate difference operator in space.
A comparison of locally adaptive multigrid methods: LDC, FAC and FIC
NASA Technical Reports Server (NTRS)
Khadra, Khodor; Angot, Philippe; Caltagirone, Jean-Paul
1993-01-01
This study is devoted to a comparative analysis of three 'Adaptive ZOOM' (ZOom Overlapping Multi-level) methods based on similar concepts of hierarchical multigrid local refinement: LDC (Local Defect Correction), FAC (Fast Adaptive Composite), and FIC (Flux Interface Correction)--which we proposed recently. These methods are tested on two examples of a bidimensional elliptic problem. We compare, for V-cycle procedures, the asymptotic evolution of the global error evaluated by discrete norms, the corresponding local errors, and the convergence rates of these algorithms.
NASA Technical Reports Server (NTRS)
Snow, Frank; Harman, Richard; Garrick, Joseph
1988-01-01
The Gamma Ray Observatory (GRO) spacecraft needs a highly accurate attitude knowledge to achieve its mission objectives. Utilizing the fixed-head star trackers (FHSTs) for observations and gyroscopes for attitude propagation, the discrete Kalman Filter processes the attitude data to obtain an onboard accuracy of 86 arc seconds (3 sigma). A combination of linear analysis and simulations using the GRO Software Simulator (GROSS) are employed to investigate the Kalman filter for stability and the effects of corrupted observations (misalignment, noise), incomplete dynamic modeling, and nonlinear errors on Kalman filter. In the simulations, on-board attitude is compared with true attitude, the sensitivity of attitude error to model errors is graphed, and a statistical analysis is performed on the residuals of the Kalman Filter. In this paper, the modeling and sensor errors that degrade the Kalman filter solution beyond mission requirements are studied, and methods are offered to identify the source of these errors.
Comparative study of signalling methods for high-speed backplane transceiver
NASA Astrophysics Data System (ADS)
Wu, Kejun
2017-11-01
A combined analysis of transient simulation and statistical method is proposed for comparative study of signalling methods applied to high-speed backplane transceivers. This method enables fast and accurate signal-to-noise ratio and symbol error rate estimation of a serial link based on a four-dimension design space, including channel characteristics, noise scenarios, equalisation schemes, and signalling methods. The proposed combined analysis method chooses an efficient sampling size for performance evaluation. A comparative study of non-return-to-zero (NRZ), PAM-4, and four-phase shifted sinusoid symbol (PSS-4) using parameterised behaviour-level simulation shows PAM-4 and PSS-4 has substantial advantages over conventional NRZ in most of the cases. A comparison between PAM-4 and PSS-4 shows PAM-4 gets significant bit error rate degradation when noise level is enhanced.
Adaptive Harmonic Balance Method for Unsteady, Nonlinear, One-Dimensional Periodic Flows
2002-09-01
Design and Implemen- tation. May 1999. REF-2 23. Toro , Eleuterio F . Fiemann Solvers and Numerical Methods for Fluid Dynamics, chapter 15. New York...prominent for high-frequency unsteady-flows. Experimental Analysis of Splitting-induced Error To assess the actual effect of splitting error on a...VITA-1 vi List of Figures Figure Page 1.1. Experimental Pressure Data on Inlet Guide Vane Upstream of Transonic Rotating
Reanalysis, compatibility and correlation in analysis of modified antenna structures
NASA Technical Reports Server (NTRS)
Levy, R.
1989-01-01
A simple computational procedure is synthesized to process changes in the microwave-antenna pathlength-error measure when there are changes in the antenna structure model. The procedure employs structural modification reanalysis methods combined with new extensions of correlation analysis to provide the revised rms pathlength error. Mainframe finite-element-method processing of the structure model is required only for the initial unmodified structure, and elementary postprocessor computations develop and deal with the effects of the changes. Several illustrative computational examples are included. The procedure adapts readily to processing spectra of changes for parameter studies or sensitivity analyses.
Fusion of magnetometer and gradiometer sensors of MEG in the presence of multiplicative error.
Mohseni, Hamid R; Woolrich, Mark W; Kringelbach, Morten L; Luckhoo, Henry; Smith, Penny Probert; Aziz, Tipu Z
2012-07-01
Novel neuroimaging techniques have provided unprecedented information on the structure and function of the living human brain. Multimodal fusion of data from different sensors promises to radically improve this understanding, yet optimal methods have not been developed. Here, we demonstrate a novel method for combining multichannel signals. We show how this method can be used to fuse signals from the magnetometer and gradiometer sensors used in magnetoencephalography (MEG), and through extensive experiments using simulation, head phantom and real MEG data, show that it is both robust and accurate. This new approach works by assuming that the lead fields have multiplicative error. The criterion to estimate the error is given within a spatial filter framework such that the estimated power is minimized in the worst case scenario. The method is compared to, and found better than, existing approaches. The closed-form solution and the conditions under which the multiplicative error can be optimally estimated are provided. This novel approach can also be employed for multimodal fusion of other multichannel signals such as MEG and EEG. Although the multiplicative error is estimated based on beamforming, other methods for source analysis can equally be used after the lead-field modification.
A method to estimate the effect of deformable image registration uncertainties on daily dose mapping
Murphy, Martin J.; Salguero, Francisco J.; Siebers, Jeffrey V.; Staub, David; Vaman, Constantin
2012-01-01
Purpose: To develop a statistical sampling procedure for spatially-correlated uncertainties in deformable image registration and then use it to demonstrate their effect on daily dose mapping. Methods: Sequential daily CT studies are acquired to map anatomical variations prior to fractionated external beam radiotherapy. The CTs are deformably registered to the planning CT to obtain displacement vector fields (DVFs). The DVFs are used to accumulate the dose delivered each day onto the planning CT. Each DVF has spatially-correlated uncertainties associated with it. Principal components analysis (PCA) is applied to measured DVF error maps to produce decorrelated principal component modes of the errors. The modes are sampled independently and reconstructed to produce synthetic registration error maps. The synthetic error maps are convolved with dose mapped via deformable registration to model the resulting uncertainty in the dose mapping. The results are compared to the dose mapping uncertainty that would result from uncorrelated DVF errors that vary randomly from voxel to voxel. Results: The error sampling method is shown to produce synthetic DVF error maps that are statistically indistinguishable from the observed error maps. Spatially-correlated DVF uncertainties modeled by our procedure produce patterns of dose mapping error that are different from that due to randomly distributed uncertainties. Conclusions: Deformable image registration uncertainties have complex spatial distributions. The authors have developed and tested a method to decorrelate the spatial uncertainties and make statistical samples of highly correlated error maps. The sample error maps can be used to investigate the effect of DVF uncertainties on daily dose mapping via deformable image registration. An initial demonstration of this methodology shows that dose mapping uncertainties can be sensitive to spatial patterns in the DVF uncertainties. PMID:22320766
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.
Alignment control study for the solar optical telescope
NASA Technical Reports Server (NTRS)
1976-01-01
Analysis of the alignment and focus errors than can be tolerated, methods of sensing such errors, and mechanisms to make the necessary corrections were addressed. Alternate approaches and their relative merits were considered. The results of this study indicate that adequate alignment control can be achieved.
ERIC Educational Resources Information Center
Katch, Frank I.; Katch, Victor L.
1980-01-01
Sources of error in body composition assessment by laboratory and field methods can be found in hydrostatic weighing, residual air volume, skinfolds, and circumferences. Statistical analysis can and should be used in the measurement of body composition. (CJ)
The Delicate Analysis of Short-Term Load Forecasting
NASA Astrophysics Data System (ADS)
Song, Changwei; Zheng, Yuan
2017-05-01
This paper proposes a new method for short-term load forecasting based on the similar day method, correlation coefficient and Fast Fourier Transform (FFT) to achieve the precision analysis of load variation from three aspects (typical day, correlation coefficient, spectral analysis) and three dimensions (time dimension, industry dimensions, the main factors influencing the load characteristic such as national policies, regional economic, holidays, electricity and so on). First, the branch algorithm one-class-SVM is adopted to selection the typical day. Second, correlation coefficient method is used to obtain the direction and strength of the linear relationship between two random variables, which can reflect the influence caused by the customer macro policy and the scale of production to the electricity price. Third, Fourier transform residual error correction model is proposed to reflect the nature of load extracting from the residual error. Finally, simulation result indicates the validity and engineering practicability of the proposed method.
NASA Astrophysics Data System (ADS)
Xia, Xintao; Wang, Zhongyu
2008-10-01
For some methods of stability analysis of a system using statistics, it is difficult to resolve the problems of unknown probability distribution and small sample. Therefore, a novel method is proposed in this paper to resolve these problems. This method is independent of probability distribution, and is useful for small sample systems. After rearrangement of the original data series, the order difference and two polynomial membership functions are introduced to estimate the true value, the lower bound and the supper bound of the system using fuzzy-set theory. Then empirical distribution function is investigated to ensure confidence level above 95%, and the degree of similarity is presented to evaluate stability of the system. Cases of computer simulation investigate stable systems with various probability distribution, unstable systems with linear systematic errors and periodic systematic errors and some mixed systems. The method of analysis for systematic stability is approved.
Periodic trim solutions with hp-version finite elements in time
NASA Technical Reports Server (NTRS)
Peters, David A.; Hou, Lin-Jun
1990-01-01
Finite elements in time as an alternative strategy for rotorcraft trim problems are studied. The research treats linear flap and linearized flap-lag response both for quasi-trim and trim cases. The connection between Fourier series analysis and hp-finite elements for periodic a problem is also examined. It is proved that Fourier series is a special case of space-time finite elements in which one element is used with a strong displacement formulation. Comparisons are made with respect to accuracy among Fourier analysis, displacement methods, and mixed methods over a variety parameters. The hp trade-off is studied for the periodic trim problem to provide an optimum step size and order of polynomial for a given error criteria. It is found that finite elements in time can outperform Fourier analysis for periodic problems, and for some given error criteria. The mixed method provides better results than does the displacement method.
NASA Astrophysics Data System (ADS)
Bhushan, A.; Sharker, M. H.; Karimi, H. A.
2015-07-01
In this paper, we address outliers in spatiotemporal data streams obtained from sensors placed across geographically distributed locations. Outliers may appear in such sensor data due to various reasons such as instrumental error and environmental change. Real-time detection of these outliers is essential to prevent propagation of errors in subsequent analyses and results. Incremental Principal Component Analysis (IPCA) is one possible approach for detecting outliers in such type of spatiotemporal data streams. IPCA has been widely used in many real-time applications such as credit card fraud detection, pattern recognition, and image analysis. However, the suitability of applying IPCA for outlier detection in spatiotemporal data streams is unknown and needs to be investigated. To fill this research gap, this paper contributes by presenting two new IPCA-based outlier detection methods and performing a comparative analysis with the existing IPCA-based outlier detection methods to assess their suitability for spatiotemporal sensor data streams.
Investigating Convergence Patterns for Numerical Methods Using Data Analysis
ERIC Educational Resources Information Center
Gordon, Sheldon P.
2013-01-01
The article investigates the patterns that arise in the convergence of numerical methods, particularly those in the errors involved in successive iterations, using data analysis and curve fitting methods. In particular, the results obtained are used to convey a deeper level of understanding of the concepts of linear, quadratic, and cubic…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lon N. Haney; David I. Gertman
2003-04-01
Beginning in the 1980s a primary focus of human reliability analysis was estimation of human error probabilities. However, detailed qualitative modeling with comprehensive representation of contextual variables often was lacking. This was likely due to the lack of comprehensive error and performance shaping factor taxonomies, and the limited data available on observed error rates and their relationship to specific contextual variables. In the mid 90s Boeing, America West Airlines, NASA Ames Research Center and INEEL partnered in a NASA sponsored Advanced Concepts grant to: assess the state of the art in human error analysis, identify future needs for human errormore » analysis, and develop an approach addressing these needs. Identified needs included the need for a method to identify and prioritize task and contextual characteristics affecting human reliability. Other needs identified included developing comprehensive taxonomies to support detailed qualitative modeling and to structure meaningful data collection efforts across domains. A result was the development of the FRamework Assessing Notorious Contributing Influences for Error (FRANCIE) with a taxonomy for airline maintenance tasks. The assignment of performance shaping factors to generic errors by experts proved to be valuable to qualitative modeling. Performance shaping factors and error types from such detailed approaches can be used to structure error reporting schemes. In a recent NASA Advanced Human Support Technology grant FRANCIE was refined, and two new taxonomies for use on space missions were developed. The development, sharing, and use of error taxonomies, and the refinement of approaches for increased fidelity of qualitative modeling is offered as a means to help direct useful data collection strategies.« less
Nicolás, Paula; Lassalle, Verónica L; Ferreira, María L
2017-02-01
The aim of this manuscript was to study the application of a new method of protein quantification in Candida antarctica lipase B commercial solutions. Error sources associated to the traditional Bradford technique were demonstrated. Eight biocatalysts based on C. antarctica lipase B (CALB) immobilized onto magnetite nanoparticles were used. Magnetite nanoparticles were coated with chitosan (CHIT) and modified with glutaraldehyde (GLUT) and aminopropyltriethoxysilane (APTS). Later, CALB was adsorbed on the modified support. The proposed novel protein quantification method included the determination of sulfur (from protein in CALB solution) by means of Atomic Emission by Inductive Coupling Plasma (AE-ICP). Four different protocols were applied combining AE-ICP and classical Bradford assays, besides Carbon, Hydrogen and Nitrogen (CHN) analysis. The calculated error in protein content using the "classic" Bradford method with bovine serum albumin as standard ranged from 400 to 1200% when protein in CALB solution was quantified. These errors were calculated considering as "true protein content values" the results of the amount of immobilized protein obtained with the improved method. The optimum quantification procedure involved the combination of Bradford method, ICP and CHN analysis. Copyright © 2016 Elsevier Inc. All rights reserved.
Using comparative genome analysis to identify problems in annotated microbial genomes.
Poptsova, Maria S; Gogarten, J Peter
2010-07-01
Genome annotation is a tedious task that is mostly done by automated methods; however, the accuracy of these approaches has been questioned since the beginning of the sequencing era. Genome annotation is a multilevel process, and errors can emerge at different stages: during sequencing, as a result of gene-calling procedures, and in the process of assigning gene functions. Missed or wrongly annotated genes differentially impact different types of analyses. Here we discuss and demonstrate how the methods of comparative genome analysis can refine annotations by locating missing orthologues. We also discuss possible reasons for errors and show that the second-generation annotation systems, which combine multiple gene-calling programs with similarity-based methods, perform much better than the first annotation tools. Since old errors may propagate to the newly sequenced genomes, we emphasize that the problem of continuously updating popular public databases is an urgent and unresolved one. Due to the progress in genome-sequencing technologies, automated annotation techniques will remain the main approach in the future. Researchers need to be aware of the existing errors in the annotation of even well-studied genomes, such as Escherichia coli, and consider additional quality control for their results.
NASA Technical Reports Server (NTRS)
Richards, W. Lance
1996-01-01
Significant strain-gage errors may exist in measurements acquired in transient-temperature environments if conventional correction methods are applied. As heating or cooling rates increase, temperature gradients between the strain-gage sensor and substrate surface increase proportionally. These temperature gradients introduce strain-measurement errors that are currently neglected in both conventional strain-correction theory and practice. Therefore, the conventional correction theory has been modified to account for these errors. A new experimental method has been developed to correct strain-gage measurements acquired in environments experiencing significant temperature transients. The new correction technique has been demonstrated through a series of tests in which strain measurements were acquired for temperature-rise rates ranging from 1 to greater than 100 degrees F/sec. Strain-gage data from these tests have been corrected with both the new and conventional methods and then compared with an analysis. Results show that, for temperature-rise rates greater than 10 degrees F/sec, the strain measurements corrected with the conventional technique produced strain errors that deviated from analysis by as much as 45 percent, whereas results corrected with the new technique were in good agreement with analytical results.
Feischl, Michael; Gantner, Gregor; Praetorius, Dirk
2015-01-01
We consider the Galerkin boundary element method (BEM) for weakly-singular integral equations of the first-kind in 2D. We analyze some residual-type a posteriori error estimator which provides a lower as well as an upper bound for the unknown Galerkin BEM error. The required assumptions are weak and allow for piecewise smooth parametrizations of the boundary, local mesh-refinement, and related standard piecewise polynomials as well as NURBS. In particular, our analysis gives a first contribution to adaptive BEM in the frame of isogeometric analysis (IGABEM), for which we formulate an adaptive algorithm which steers the local mesh-refinement and the multiplicity of the knots. Numerical experiments underline the theoretical findings and show that the proposed adaptive strategy leads to optimal convergence. PMID:26085698
Vajda, E G; Skedros, J G; Bloebaum, R D
1998-10-01
Backscattered electron (BSE) imaging has proven to be a useful method for analyzing the mineral distribution in microscopic regions of bone. However, an accepted method of standardization has not been developed, limiting the utility of BSE imaging for truly quantitative analysis. Previous work has suggested that BSE images can be standardized by energy-dispersive x-ray spectrometry (EDX). Unfortunately, EDX-standardized BSE images tend to underestimate the mineral content of bone when compared with traditional ash measurements. The goal of this study is to investigate the nature of the deficit between EDX-standardized BSE images and ash measurements. A series of analytical standards, ashed bone specimens, and unembedded bone specimens were investigated to determine the source of the deficit previously reported. The primary source of error was found to be inaccurate ZAF corrections to account for the organic phase of the bone matrix. Conductive coatings, methylmethacrylate embedding media, and minor elemental constituents in bone mineral introduced negligible errors. It is suggested that the errors would remain constant and an empirical correction could be used to account for the deficit. However, extensive preliminary testing of the analysis equipment is essential.
AQMEII3 evaluation of regional NA/EU simulations and ...
Through the comparison of several regional-scale chemistry transport modelling systems that simulate meteorology and air quality over the European and American continents, this study aims at i) apportioning the error to the responsible processes using time-scale analysis, ii) helping to detect causes of models error, and iii) identifying the processes and scales most urgently requiring dedicated investigations. The analysis is conducted within the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII) and tackles model performance gauging through measurement-to-model comparison, error decomposition and time series analysis of the models biases for several fields (ozone, CO, SO2, NO, NO2, PM10, PM2.5, wind speed, and temperature). The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overall sense of model strengths and deficiencies, while apportioning the error to its constituent parts (bias, variance and covariance) can help to assess the nature and quality of the error. Each of the error components is analysed independently and apportioned to specific processes based on the corresponding timescale (long scale, synoptic, diurnal, and intra-day) using the error apportionment technique devised in the former phases of AQMEII. The application of the error apportionment method to the AQMEII Phase 3 simulations provides several key insights. In addition to reaffirming the strong impac
Cao, Youfang; Terebus, Anna; Liang, Jie
2016-01-01
The discrete chemical master equation (dCME) provides a general framework for studying stochasticity in mesoscopic reaction networks. Since its direct solution rapidly becomes intractable due to the increasing size of the state space, truncation of the state space is necessary for solving most dCMEs. It is therefore important to assess the consequences of state space truncations so errors can be quantified and minimized. Here we describe a novel method for state space truncation. By partitioning a reaction network into multiple molecular equivalence groups (MEG), we truncate the state space by limiting the total molecular copy numbers in each MEG. We further describe a theoretical framework for analysis of the truncation error in the steady state probability landscape using reflecting boundaries. By aggregating the state space based on the usage of a MEG and constructing an aggregated Markov process, we show that the truncation error of a MEG can be asymptotically bounded by the probability of states on the reflecting boundary of the MEG. Furthermore, truncating states of an arbitrary MEG will not undermine the estimated error of truncating any other MEGs. We then provide an overall error estimate for networks with multiple MEGs. To rapidly determine the appropriate size of an arbitrary MEG, we also introduce an a priori method to estimate the upper bound of its truncation error. This a priori estimate can be rapidly computed from reaction rates of the network, without the need of costly trial solutions of the dCME. As examples, we show results of applying our methods to the four stochastic networks of 1) the birth and death model, 2) the single gene expression model, 3) the genetic toggle switch model, and 4) the phage lambda bistable epigenetic switch model. We demonstrate how truncation errors and steady state probability landscapes can be computed using different sizes of the MEG(s) and how the results validate out theories. Overall, the novel state space truncation and error analysis methods developed here can be used to ensure accurate direct solutions to the dCME for a large number of stochastic networks. PMID:27105653
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cao, Youfang; Terebus, Anna; Liang, Jie
The discrete chemical master equation (dCME) provides a general framework for studying stochasticity in mesoscopic reaction networks. Since its direct solution rapidly becomes intractable due to the increasing size of the state space, truncation of the state space is necessary for solving most dCMEs. It is therefore important to assess the consequences of state space truncations so errors can be quantified and minimized. Here we describe a novel method for state space truncation. By partitioning a reaction network into multiple molecular equivalence groups (MEGs), we truncate the state space by limiting the total molecular copy numbers in each MEG. Wemore » further describe a theoretical framework for analysis of the truncation error in the steady-state probability landscape using reflecting boundaries. By aggregating the state space based on the usage of a MEG and constructing an aggregated Markov process, we show that the truncation error of a MEG can be asymptotically bounded by the probability of states on the reflecting boundary of the MEG. Furthermore, truncating states of an arbitrary MEG will not undermine the estimated error of truncating any other MEGs. We then provide an overall error estimate for networks with multiple MEGs. To rapidly determine the appropriate size of an arbitrary MEG, we also introduce an a priori method to estimate the upper bound of its truncation error. This a priori estimate can be rapidly computed from reaction rates of the network, without the need of costly trial solutions of the dCME. As examples, we show results of applying our methods to the four stochastic networks of (1) the birth and death model, (2) the single gene expression model, (3) the genetic toggle switch model, and (4) the phage lambda bistable epigenetic switch model. We demonstrate how truncation errors and steady-state probability landscapes can be computed using different sizes of the MEG(s) and how the results validate our theories. Overall, the novel state space truncation and error analysis methods developed here can be used to ensure accurate direct solutions to the dCME for a large number of stochastic networks.« less
Cao, Youfang; Terebus, Anna; Liang, Jie
2016-04-22
The discrete chemical master equation (dCME) provides a general framework for studying stochasticity in mesoscopic reaction networks. Since its direct solution rapidly becomes intractable due to the increasing size of the state space, truncation of the state space is necessary for solving most dCMEs. It is therefore important to assess the consequences of state space truncations so errors can be quantified and minimized. Here we describe a novel method for state space truncation. By partitioning a reaction network into multiple molecular equivalence groups (MEGs), we truncate the state space by limiting the total molecular copy numbers in each MEG. Wemore » further describe a theoretical framework for analysis of the truncation error in the steady-state probability landscape using reflecting boundaries. By aggregating the state space based on the usage of a MEG and constructing an aggregated Markov process, we show that the truncation error of a MEG can be asymptotically bounded by the probability of states on the reflecting boundary of the MEG. Furthermore, truncating states of an arbitrary MEG will not undermine the estimated error of truncating any other MEGs. We then provide an overall error estimate for networks with multiple MEGs. To rapidly determine the appropriate size of an arbitrary MEG, we also introduce an a priori method to estimate the upper bound of its truncation error. This a priori estimate can be rapidly computed from reaction rates of the network, without the need of costly trial solutions of the dCME. As examples, we show results of applying our methods to the four stochastic networks of (1) the birth and death model, (2) the single gene expression model, (3) the genetic toggle switch model, and (4) the phage lambda bistable epigenetic switch model. We demonstrate how truncation errors and steady-state probability landscapes can be computed using different sizes of the MEG(s) and how the results validate our theories. Overall, the novel state space truncation and error analysis methods developed here can be used to ensure accurate direct solutions to the dCME for a large number of stochastic networks.« less
TLE uncertainty estimation using robust weighted differencing
NASA Astrophysics Data System (ADS)
Geul, Jacco; Mooij, Erwin; Noomen, Ron
2017-05-01
Accurate knowledge of satellite orbit errors is essential for many types of analyses. Unfortunately, for two-line elements (TLEs) this is not available. This paper presents a weighted differencing method using robust least-squares regression for estimating many important error characteristics. The method is applied to both classic and enhanced TLEs, compared to previous implementations, and validated using Global Positioning System (GPS) solutions for the GOCE satellite in Low-Earth Orbit (LEO), prior to its re-entry. The method is found to be more accurate than previous TLE differencing efforts in estimating initial uncertainty, as well as error growth. The method also proves more reliable and requires no data filtering (such as outlier removal). Sensitivity analysis shows a strong relationship between argument of latitude and covariance (standard deviations and correlations), which the method is able to approximate. Overall, the method proves accurate, computationally fast, and robust, and is applicable to any object in the satellite catalogue (SATCAT).
Pazó, Jose A.; Granada, Enrique; Saavedra, Ángeles; Eguía, Pablo; Collazo, Joaquín
2010-01-01
The objective of this study was to develop a methodology for the determination of the maximum sampling error and confidence intervals of thermal properties obtained from thermogravimetric analysis (TG), including moisture, volatile matter, fixed carbon and ash content. The sampling procedure of the TG analysis was of particular interest and was conducted with care. The results of the present study were compared to those of a prompt analysis, and a correlation between the mean values and maximum sampling errors of the methods were not observed. In general, low and acceptable levels of uncertainty and error were obtained, demonstrating that the properties evaluated by TG analysis were representative of the overall fuel composition. The accurate determination of the thermal properties of biomass with precise confidence intervals is of particular interest in energetic biomass applications. PMID:20717532
Juhlin, Kristina; Norén, G. Niklas
2017-01-01
Abstract Purpose To develop a method for data‐driven exploration in pharmacovigilance and illustrate its use by identifying the key features of individual case safety reports related to medication errors. Methods We propose vigiPoint, a method that contrasts the relative frequency of covariate values in a data subset of interest to those within one or more comparators, utilizing odds ratios with adaptive statistical shrinkage. Nested analyses identify higher order patterns, and permutation analysis is employed to protect against chance findings. For illustration, a total of 164 000 adverse event reports related to medication errors were characterized and contrasted to the other 7 833 000 reports in VigiBase, the WHO global database of individual case safety reports, as of May 2013. The initial scope included 2000 features, such as patient age groups, reporter qualifications, and countries of origin. Results vigiPoint highlighted 109 key features of medication error reports. The most prominent were that the vast majority of medication error reports were from the United States (89% compared with 49% for other reports in VigiBase); that the majority of reports were sent by consumers (53% vs 17% for other reports); that pharmacists (12% vs 5.3%) and lawyers (2.9% vs 1.5%) were overrepresented; and that there were more medication error reports than expected for patients aged 2‐11 years (10% vs 5.7%), particularly in Germany (16%). Conclusions vigiPoint effectively identified key features of medication error reports in VigiBase. More generally, it reduces lead times for analysis and ensures reproducibility and transparency. An important next step is to evaluate its use in other data. PMID:28815800
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
NASA Technical Reports Server (NTRS)
Miller, J. M.
1980-01-01
ATMOS is a Fourier transform spectrometer to measure atmospheric trace molecules over a spectral range of 2-16 microns. Assessment of the system performance of ATMOS includes evaluations of optical system errors induced by thermal and structural effects. In order to assess the optical system errors induced from thermal and structural effects, error budgets are assembled during system engineering tasks and line of sight and wavefront deformations predictions (using operational thermal and vibration environments and computer models) are subsequently compared to the error budgets. This paper discusses the thermal/structural error budgets, modelling and analysis methods used to predict thermal/structural induced errors and the comparisons that show that predictions are within the error budgets.
Developing a model for the adequate description of electronic communication in hospitals.
Saboor, Samrend; Ammenwerth, Elske
2011-01-01
Adequate information and communication systems (ICT) can help to improve the communication in hospitals. Changes to the ICT-infrastructure of hospitals must be planed carefully. In order to support a comprehensive planning, we presented a classification of 81 common errors of the electronic communication on the MIE 2008 congress. Our objective now was to develop a data model that defines specific requirements for an adequate description of electronic communication processes We first applied the method of explicating qualitative content analysis on the error categorization in order to determine the essential process details. After this, we applied the method of subsuming qualitative content analysis on the results of the first step. A data model for the adequate description of electronic communication. This model comprises 61 entities and 91 relationships. The data model comprises and organizes all details that are necessary for the detection of the respective errors. It can be for either used to extend the capabilities of existing modeling methods or as a basis for the development of a new approach.
Rong, Hao; Tian, Jin; Zhao, Tingdi
2016-01-01
In traditional approaches of human reliability assessment (HRA), the definition of the error producing conditions (EPCs) and the supporting guidance are such that some of the conditions (especially organizational or managerial conditions) can hardly be included, and thus the analysis is burdened with incomprehensiveness without reflecting the temporal trend of human reliability. A method based on system dynamics (SD), which highlights interrelationships among technical and organizational aspects that may contribute to human errors, is presented to facilitate quantitatively estimating the human error probability (HEP) and its related variables changing over time in a long period. Taking the Minuteman III missile accident in 2008 as a case, the proposed HRA method is applied to assess HEP during missile operations over 50 years by analyzing the interactions among the variables involved in human-related risks; also the critical factors are determined in terms of impact that the variables have on risks in different time periods. It is indicated that both technical and organizational aspects should be focused on to minimize human errors in a long run. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.
How do Community Pharmacies Recover from E-prescription Errors?
Odukoya, Olufunmilola K.; Stone, Jamie A.; Chui, Michelle A.
2014-01-01
Background The use of e-prescribing is increasing annually, with over 788 million e-prescriptions received in US pharmacies in 2012. Approximately 9% of e-prescriptions have medication errors. Objective To describe the process used by community pharmacy staff to detect, explain, and correct e-prescription errors. Methods The error recovery conceptual framework was employed for data collection and analysis. 13 pharmacists and 14 technicians from five community pharmacies in Wisconsin participated in the study. A combination of data collection methods were utilized, including direct observations, interviews, and focus groups. The transcription and content analysis of recordings were guided by the three-step error recovery model. Results Most of the e-prescription errors were detected during the entering of information into the pharmacy system. These errors were detected by both pharmacists and technicians using a variety of strategies which included: (1) performing double checks of e-prescription information; (2) printing the e-prescription to paper and confirming the information on the computer screen with information from the paper printout; and (3) using colored pens to highlight important information. Strategies used for explaining errors included: (1) careful review of patient’ medication history; (2) pharmacist consultation with patients; (3) consultation with another pharmacy team member; and (4) use of online resources. In order to correct e-prescription errors, participants made educated guesses of the prescriber’s intent or contacted the prescriber via telephone or fax. When e-prescription errors were encountered in the community pharmacies, the primary goal of participants was to get the order right for patients by verifying the prescriber’s intent. Conclusion Pharmacists and technicians play an important role in preventing e-prescription errors through the detection of errors and the verification of prescribers’ intent. Future studies are needed to examine factors that facilitate or hinder recovery from e-prescription errors. PMID:24373898
Covariance analysis for evaluating head trackers
NASA Astrophysics Data System (ADS)
Kang, Donghoon
2017-10-01
Existing methods for evaluating the performance of head trackers usually rely on publicly available face databases, which contain facial images and the ground truths of their corresponding head orientations. However, most of the existing publicly available face databases are constructed by assuming that a frontal head orientation can be determined by compelling the person under examination to look straight ahead at the camera on the first video frame. Since nobody can accurately direct one's head toward the camera, this assumption may be unrealistic. Rather than obtaining estimation errors, we present a method for computing the covariance of estimation error rotations to evaluate the reliability of head trackers. As an uncertainty measure of estimators, the Schatten 2-norm of a square root of error covariance (or the algebraic average of relative error angles) can be used. The merit of the proposed method is that it does not disturb the person under examination by asking him to direct his head toward certain directions. Experimental results using real data validate the usefulness of our method.
Gajewski, Byron J.; Lee, Robert; Dunton, Nancy
2012-01-01
Data Envelopment Analysis (DEA) is the most commonly used approach for evaluating healthcare efficiency (Hollingsworth, 2008), but a long-standing concern is that DEA assumes that data are measured without error. This is quite unlikely, and DEA and other efficiency analysis techniques may yield biased efficiency estimates if it is not realized (Gajewski, Lee, Bott, Piamjariyakul and Taunton, 2009; Ruggiero, 2004). We propose to address measurement error systematically using a Bayesian method (Bayesian DEA). We will apply Bayesian DEA to data from the National Database of Nursing Quality Indicators® (NDNQI®) to estimate nursing units’ efficiency. Several external reliability studies inform the posterior distribution of the measurement error on the DEA variables. We will discuss the case of generalizing the approach to situations where an external reliability study is not feasible. PMID:23328796
Some Surprising Errors in Numerical Differentiation
ERIC Educational Resources Information Center
Gordon, Sheldon P.
2012-01-01
Data analysis methods, both numerical and visual, are used to discover a variety of surprising patterns in the errors associated with successive approximations to the derivatives of sinusoidal and exponential functions based on the Newton difference-quotient. L'Hopital's rule and Taylor polynomial approximations are then used to explain why these…
Modeling Morphogenesis with Reaction-Diffusion Equations Using Galerkin Spectral Methods
2002-05-06
reaction- diffusion equation is a difficult problem in analysis that will not be addressed here. Errors will also arise from numerically approx solutions to...the ODEs. When comparing the approximate solution to actual reaction- diffusion systems found in nature, we must also take into account errors that...
Wang, Shijun; Yao, Jianhua; Liu, Jiamin; Petrick, Nicholas; Van Uitert, Robert L.; Periaswamy, Senthil; Summers, Ronald M.
2009-01-01
Purpose: In computed tomographic colonography (CTC), a patient will be scanned twice—Once supine and once prone—to improve the sensitivity for polyp detection. To assist radiologists in CTC reading, in this paper we propose an automated method for colon registration from supine and prone CTC scans. Methods: We propose a new colon centerline registration method for prone and supine CTC scans using correlation optimized warping (COW) and canonical correlation analysis (CCA) based on the anatomical structure of the colon. Four anatomical salient points on the colon are first automatically distinguished. Then correlation optimized warping is applied to the segments defined by the anatomical landmarks to improve the global registration based on local correlation of segments. The COW method was modified by embedding canonical correlation analysis to allow multiple features along the colon centerline to be used in our implementation. Results: We tested the COW algorithm on a CTC data set of 39 patients with 39 polyps (19 training and 20 test cases) to verify the effectiveness of the proposed COW registration method. Experimental results on the test set show that the COW method significantly reduces the average estimation error in a polyp location between supine and prone scans by 67.6%, from 46.27±52.97 to 14.98 mm±11.41 mm, compared to the normalized distance along the colon centerline algorithm (p<0.01). Conclusions: The proposed COW algorithm is more accurate for the colon centerline registration compared to the normalized distance along the colon centerline method and the dynamic time warping method. Comparison results showed that the feature combination of z-coordinate and curvature achieved lowest registration error compared to the other feature combinations used by COW. The proposed method is tolerant to centerline errors because anatomical landmarks help prevent the propagation of errors across the entire colon centerline. PMID:20095272
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang Shijun; Yao Jianhua; Liu Jiamin
Purpose: In computed tomographic colonography (CTC), a patient will be scanned twice--Once supine and once prone--to improve the sensitivity for polyp detection. To assist radiologists in CTC reading, in this paper we propose an automated method for colon registration from supine and prone CTC scans. Methods: We propose a new colon centerline registration method for prone and supine CTC scans using correlation optimized warping (COW) and canonical correlation analysis (CCA) based on the anatomical structure of the colon. Four anatomical salient points on the colon are first automatically distinguished. Then correlation optimized warping is applied to the segments defined bymore » the anatomical landmarks to improve the global registration based on local correlation of segments. The COW method was modified by embedding canonical correlation analysis to allow multiple features along the colon centerline to be used in our implementation. Results: We tested the COW algorithm on a CTC data set of 39 patients with 39 polyps (19 training and 20 test cases) to verify the effectiveness of the proposed COW registration method. Experimental results on the test set show that the COW method significantly reduces the average estimation error in a polyp location between supine and prone scans by 67.6%, from 46.27{+-}52.97 to 14.98 mm{+-}11.41 mm, compared to the normalized distance along the colon centerline algorithm (p<0.01). Conclusions: The proposed COW algorithm is more accurate for the colon centerline registration compared to the normalized distance along the colon centerline method and the dynamic time warping method. Comparison results showed that the feature combination of z-coordinate and curvature achieved lowest registration error compared to the other feature combinations used by COW. The proposed method is tolerant to centerline errors because anatomical landmarks help prevent the propagation of errors across the entire colon centerline.« less
A Third Moment Adjusted Test Statistic for Small Sample Factor Analysis
Lin, Johnny; Bentler, Peter M.
2012-01-01
Goodness of fit testing in factor analysis is based on the assumption that the test statistic is asymptotically chi-square; but this property may not hold in small samples even when the factors and errors are normally distributed in the population. Robust methods such as Browne’s asymptotically distribution-free method and Satorra Bentler’s mean scaling statistic were developed under the presumption of non-normality in the factors and errors. This paper finds new application to the case where factors and errors are normally distributed in the population but the skewness of the obtained test statistic is still high due to sampling error in the observed indicators. An extension of Satorra Bentler’s statistic is proposed that not only scales the mean but also adjusts the degrees of freedom based on the skewness of the obtained test statistic in order to improve its robustness under small samples. A simple simulation study shows that this third moment adjusted statistic asymptotically performs on par with previously proposed methods, and at a very small sample size offers superior Type I error rates under a properly specified model. Data from Mardia, Kent and Bibby’s study of students tested for their ability in five content areas that were either open or closed book were used to illustrate the real-world performance of this statistic. PMID:23144511
Fully Convolutional Networks for Ground Classification from LIDAR Point Clouds
NASA Astrophysics Data System (ADS)
Rizaldy, A.; Persello, C.; Gevaert, C. M.; Oude Elberink, S. J.
2018-05-01
Deep Learning has been massively used for image classification in recent years. The use of deep learning for ground classification from LIDAR point clouds has also been recently studied. However, point clouds need to be converted into an image in order to use Convolutional Neural Networks (CNNs). In state-of-the-art techniques, this conversion is slow because each point is converted into a separate image. This approach leads to highly redundant computation during conversion and classification. The goal of this study is to design a more efficient data conversion and ground classification. This goal is achieved by first converting the whole point cloud into a single image. The classification is then performed by a Fully Convolutional Network (FCN), a modified version of CNN designed for pixel-wise image classification. The proposed method is significantly faster than state-of-the-art techniques. On the ISPRS Filter Test dataset, it is 78 times faster for conversion and 16 times faster for classification. Our experimental analysis on the same dataset shows that the proposed method results in 5.22 % of total error, 4.10 % of type I error, and 15.07 % of type II error. Compared to the previous CNN-based technique and LAStools software, the proposed method reduces the total error and type I error (while type II error is slightly higher). The method was also tested on a very high point density LIDAR point clouds resulting in 4.02 % of total error, 2.15 % of type I error and 6.14 % of type II error.
Optimal analytic method for the nonlinear Hasegawa-Mima equation
NASA Astrophysics Data System (ADS)
Baxter, Mathew; Van Gorder, Robert A.; Vajravelu, Kuppalapalle
2014-05-01
The Hasegawa-Mima equation is a nonlinear partial differential equation that describes the electric potential due to a drift wave in a plasma. In the present paper, we apply the method of homotopy analysis to a slightly more general Hasegawa-Mima equation, which accounts for hyper-viscous damping or viscous dissipation. First, we outline the method for the general initial/boundary value problem over a compact rectangular spatial domain. We use a two-stage method, where both the convergence control parameter and the auxiliary linear operator are optimally selected to minimize the residual error due to the approximation. To do the latter, we consider a family of operators parameterized by a constant which gives the decay rate of the solutions. After outlining the general method, we consider a number of concrete examples in order to demonstrate the utility of this approach. The results enable us to study properties of the initial/boundary value problem for the generalized Hasegawa-Mima equation. In several cases considered, we are able to obtain solutions with extremely small residual errors after relatively few iterations are computed (residual errors on the order of 10-15 are found in multiple cases after only three iterations). The results demonstrate that selecting a parameterized auxiliary linear operator can be extremely useful for minimizing residual errors when used concurrently with the optimal homotopy analysis method, suggesting that this approach can prove useful for a number of nonlinear partial differential equations arising in physics and nonlinear mechanics.
NASA Astrophysics Data System (ADS)
Bousserez, Nicolas; Henze, Daven; Bowman, Kevin; Liu, Junjie; Jones, Dylan; Keller, Martin; Deng, Feng
2013-04-01
This work presents improved analysis error estimates for 4D-Var systems. From operational NWP models to top-down constraints on trace gas emissions, many of today's data assimilation and inversion systems in atmospheric science rely on variational approaches. This success is due to both the mathematical clarity of these formulations and the availability of computationally efficient minimization algorithms. However, unlike Kalman Filter-based algorithms, these methods do not provide an estimate of the analysis or forecast error covariance matrices, these error statistics being propagated only implicitly by the system. From both a practical (cycling assimilation) and scientific perspective, assessing uncertainties in the solution of the variational problem is critical. For large-scale linear systems, deterministic or randomization approaches can be considered based on the equivalence between the inverse Hessian of the cost function and the covariance matrix of analysis error. For perfectly quadratic systems, like incremental 4D-Var, Lanczos/Conjugate-Gradient algorithms have proven to be most efficient in generating low-rank approximations of the Hessian matrix during the minimization. For weakly non-linear systems though, the Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS), a quasi-Newton descent algorithm, is usually considered the best method for the minimization. Suitable for large-scale optimization, this method allows one to generate an approximation to the inverse Hessian using the latest m vector/gradient pairs generated during the minimization, m depending upon the available core memory. At each iteration, an initial low-rank approximation to the inverse Hessian has to be provided, which is called preconditioning. The ability of the preconditioner to retain useful information from previous iterations largely determines the efficiency of the algorithm. Here we assess the performance of different preconditioners to estimate the inverse Hessian of a large-scale 4D-Var system. The impact of using the diagonal preconditioners proposed by Gilbert and Le Maréchal (1989) instead of the usual Oren-Spedicato scalar will be first presented. We will also introduce new hybrid methods that combine randomization estimates of the analysis error variance with L-BFGS diagonal updates to improve the inverse Hessian approximation. Results from these new algorithms will be evaluated against standard large ensemble Monte-Carlo simulations. The methods explored here are applied to the problem of inferring global atmospheric CO2 fluxes using remote sensing observations, and are intended to be integrated with the future NASA Carbon Monitoring System.
NASA Astrophysics Data System (ADS)
Mena, Marcelo Andres
During 2004 and 2006 the University of Iowa provided air quality forecast support for flight planning of the ICARTT and MILAGRO field campaigns. A method for improvement of model performance in comparison to observations is showed. The method allows identifying sources of model error from boundary conditions and emissions inventories. Simultaneous analysis of horizontal interpolation of model error and error covariance showed that error in ozone modeling is highly correlated to the error of its precursors, and that there is geographical correlation also. During ICARTT ozone modeling error was improved by updating from the National Emissions Inventory from 1999 and 2001, and furthermore by updating large point source emissions from continuous monitoring data. Further improvements were achieved by reducing area emissions of NOx y 60% for states in the Southeast United States. Ozone error was highly correlated to NOy error during this campaign. Also ozone production in the United States was most sensitive to NOx emissions. During MILAGRO model performance in terms of correlation coefficients was higher, but model error in ozone modeling was high due overestimation of NOx and VOC emissions in Mexico City during forecasting. Large model improvements were shown by decreasing NOx emissions in Mexico City by 50% and VOC by 60%. Recurring ozone error is spatially correlated to CO and NOy error. Sensitivity studies show that Mexico City aerosol can reduce regional photolysis rates by 40% and ozone formation by 5-10%. Mexico City emissions can enhance NOy and O3 concentrations over the Gulf of Mexico in up to 10-20%. Mexico City emissions can convert regional ozone production regimes from VOC to NOx limited. A method of interpolation of observations along flight tracks is shown, which can be used to infer on the direction of outflow plumes. The use of ratios such as O3/NOy and NOx/NOy can be used to provide information on chemical characteristics of the plume, such as age, and ozone production regime. Interpolated MTBE observations can be used as a tracer of urban mobile source emissions. Finally procedures for estimating and gridding emissions inventories in Brazil and Mexico are presented.
Uncovering the requirements of cognitive work.
Roth, Emilie M
2008-06-01
In this article, the author provides an overview of cognitive analysis methods and how they can be used to inform system analysis and design. Human factors has seen a shift toward modeling and support of cognitively intensive work (e.g., military command and control, medical planning and decision making, supervisory control of automated systems). Cognitive task analysis and cognitive work analysis methods extend traditional task analysis techniques to uncover the knowledge and thought processes that underlie performance in cognitively complex settings. The author reviews the multidisciplinary roots of cognitive analysis and the variety of cognitive task analysis and cognitive work analysis methods that have emerged. Cognitive analysis methods have been used successfully to guide system design, as well as development of function allocation, team structure, and training, so as to enhance performance and reduce the potential for error. A comprehensive characterization of cognitive work requires two mutually informing analyses: (a) examination of domain characteristics and constraints that define cognitive requirements and challenges and (b) examination of practitioner knowledge and strategies that underlie both expert and error-vulnerable performance. A variety of specific methods can be adapted to achieve these aims within the pragmatic constraints of particular projects. Cognitive analysis methods can be used effectively to anticipate cognitive performance problems and specify ways to improve individual and team cognitive performance (be it through new forms of training, user interfaces, or decision aids).
Quotation accuracy in medical journal articles—a systematic review and meta-analysis
Jergas, Hannah
2015-01-01
Background. Quotations and references are an indispensable element of scientific communication. They should support what authors claim or provide important background information for readers. Studies indicate, however, that quotations not serving their purpose—quotation errors—may be prevalent. Methods. We carried out a systematic review, meta-analysis and meta-regression of quotation errors, taking account of differences between studies in error ascertainment. Results. Out of 559 studies screened we included 28 in the main analysis, and estimated major, minor and total quotation error rates of 11,9%, 95% CI [8.4, 16.6] 11.5% [8.3, 15.7], and 25.4% [19.5, 32.4]. While heterogeneity was substantial, even the lowest estimate of total quotation errors was considerable (6.7%). Indirect references accounted for less than one sixth of all quotation problems. The findings remained robust in a number of sensitivity and subgroup analyses (including risk of bias analysis) and in meta-regression. There was no indication of publication bias. Conclusions. Readers of medical journal articles should be aware of the fact that quotation errors are common. Measures against quotation errors include spot checks by editors and reviewers, correct placement of citations in the text, and declarations by authors that they have checked cited material. Future research should elucidate if and to what degree quotation errors are detrimental to scientific progress. PMID:26528420
NASA Astrophysics Data System (ADS)
Ignac-Nowicka, Jolanta
2018-03-01
The paper analyzes the conditions of safe use of industrial gas systems and factors influencing gas hazards. Typical gas installation and its basic features have been characterized. The results of gas threat analysis in an industrial enterprise using FTA error tree method and ETA event tree method are presented. Compares selected methods of identifying hazards gas industry with respect to the scope of their use. The paper presents an analysis of two exemplary hazards: an industrial gas catastrophe (FTA) and an explosive gas explosion (ETA). In both cases, technical risks and human errors (human factor) were taken into account. The cause-effect relationships of hazards and their causes are presented in the form of diagrams in the drawings.
Standardising analysis of carbon monoxide rebreathing for application in anti-doping.
Alexander, Anthony C; Garvican, Laura A; Burge, Caroline M; Clark, Sally A; Plowman, James S; Gore, Christopher J
2011-03-01
Determination of total haemoglobin mass (Hbmass) via carbon monoxide (CO) depends critically on repeatable measurement of percent carboxyhaemoglobin (%HbCO) in blood with a hemoximeter. The main aim of this study was to determine, for an OSM3 hemoximeter, the number of replicate measures as well as the theoretical change in percent carboxyhaemoglobin required to yield a random error of analysis (Analyser Error) of ≤1%. Before and after inhalation of CO, nine participants provided a total of 576 blood samples that were each analysed five times for percent carboxyhaemoglobin on one of three OSM3 hemoximeters; with approximately one-third of blood samples analysed on each OSM3. The Analyser Error was calculated for the first two (duplicate), first three (triplicate) and first four (quadruplicate) measures on each OSM3, as well as for all five measures (quintuplicates). Two methods of CO-rebreathing, a 2-min and 10-min procedure, were evaluated for Analyser Error. For duplicate analyses of blood, the Analyser Error for the 2-min method was 3.7, 4.0 and 5.0% for the three OSM3s when the percent carboxyhaemoglobin increased by two above resting values. With quintuplicate analyses of blood, the corresponding errors reduced to .8, .9 and 1.0% for the 2-min method when the percent carboxyhaemoglobin increased by 5.5 above resting values. In summary, to minimise the Analyser Error to ∼≤1% on an OSM3 hemoximeter, researchers should make ≥5 replicates of percent carboxyhaemoglobin and the volume of CO administered should be sufficient increase percent carboxyhaemoglobin by ≥5.5 above baseline levels. Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.
Does a better model yield a better argument? An info-gap analysis
NASA Astrophysics Data System (ADS)
Ben-Haim, Yakov
2017-04-01
Theories, models and computations underlie reasoned argumentation in many areas. The possibility of error in these arguments, though of low probability, may be highly significant when the argument is used in predicting the probability of rare high-consequence events. This implies that the choice of a theory, model or computational method for predicting rare high-consequence events must account for the probability of error in these components. However, error may result from lack of knowledge or surprises of various sorts, and predicting the probability of error is highly uncertain. We show that the putatively best, most innovative and sophisticated argument may not actually have the lowest probability of error. Innovative arguments may entail greater uncertainty than more standard but less sophisticated methods, creating an innovation dilemma in formulating the argument. We employ info-gap decision theory to characterize and support the resolution of this problem and present several examples.
Measurement Error and Environmental Epidemiology: A Policy Perspective
Edwards, Jessie K.; Keil, Alexander P.
2017-01-01
Purpose of review Measurement error threatens public health by producing bias in estimates of the population impact of environmental exposures. Quantitative methods to account for measurement bias can improve public health decision making. Recent findings We summarize traditional and emerging methods to improve inference under a standard perspective, in which the investigator estimates an exposure response function, and a policy perspective, in which the investigator directly estimates population impact of a proposed intervention. Summary Under a policy perspective, the analysis must be sensitive to errors in measurement of factors that modify the effect of exposure on outcome, must consider whether policies operate on the true or measured exposures, and may increasingly need to account for potentially dependent measurement error of two or more exposures affected by the same policy or intervention. Incorporating approaches to account for measurement error into such a policy perspective will increase the impact of environmental epidemiology. PMID:28138941
Adaptive optics system performance approximations for atmospheric turbulence correction
NASA Astrophysics Data System (ADS)
Tyson, Robert K.
1990-10-01
Analysis of adaptive optics system behavior often can be reduced to a few approximations and scaling laws. For atmospheric turbulence correction, the deformable mirror (DM) fitting error is most often used to determine a priori the interactuator spacing and the total number of correction zones required. This paper examines the mirror fitting error in terms of its most commonly used exponential form. The explicit constant in the error term is dependent on deformable mirror influence function shape and actuator geometry. The method of least squares fitting of discrete influence functions to the turbulent wavefront is compared to the linear spatial filtering approximation of system performance. It is found that the spatial filtering method overstimates the correctability of the adaptive optics system by a small amount. By evaluating fitting error for a number of DM configurations, actuator geometries, and influence functions, fitting error constants verify some earlier investigations.
Strain gage measurement errors in the transient heating of structural components
NASA Technical Reports Server (NTRS)
Richards, W. Lance
1993-01-01
Significant strain-gage errors may exist in measurements acquired in transient thermal environments if conventional correction methods are applied. Conventional correction theory was modified and a new experimental method was developed to correct indicated strain data for errors created in radiant heating environments ranging from 0.6 C/sec (1 F/sec) to over 56 C/sec (100 F/sec). In some cases the new and conventional methods differed by as much as 30 percent. Experimental and analytical results were compared to demonstrate the new technique. For heating conditions greater than 6 C/sec (10 F/sec), the indicated strain data corrected with the developed technique compared much better to analysis than the same data corrected with the conventional technique.
Pacheco, Shaun; Brand, Jonathan F.; Zaverton, Melissa; Milster, Tom; Liang, Rongguang
2015-01-01
A method to design one-dimensional beam-spitting phase gratings with low sensitivity to fabrication errors is described. The method optimizes the phase function of a grating by minimizing the integrated variance of the energy of each output beam over a range of fabrication errors. Numerical results for three 1x9 beam splitting phase gratings are given. Two optimized gratings with low sensitivity to fabrication errors were compared with a grating designed for optimal efficiency. These three gratings were fabricated using gray-scale photolithography. The standard deviation of the 9 outgoing beam energies in the optimized gratings were 2.3 and 3.4 times lower than the optimal efficiency grating. PMID:25969268
Vašek, Jakub; Viehmannová, Iva; Ocelák, Martin; Cachique Huansi, Danter; Vejl, Pavel
2017-01-01
An analysis of the population structure and genetic diversity for any organism often depends on one or more molecular marker techniques. Nonetheless, these techniques are not absolutely reliable because of various sources of errors arising during the genotyping process. Thus, a complex analysis of genotyping error was carried out with the AFLP method in 169 samples of the oil seed plant Plukenetia volubilis L. from small isolated subpopulations in the Peruvian Amazon. Samples were collected in nine localities from the region of San Martin. Analysis was done in eight datasets with a genotyping error from 0 to 5%. Using eleven primer combinations, 102 to 275 markers were obtained according to the dataset. It was found that it is only possible to obtain the most reliable and robust results through a multiple-level filtering process. Genotyping error and software set up influence both the estimation of population structure and genetic diversity, where in our case population number (K) varied between 2–9 depending on the dataset and statistical method used. Surprisingly, discrepancies in K number were caused more by statistical approaches than by genotyping errors themselves. However, for estimation of genetic diversity, the degree of genotyping error was critical because descriptive parameters (He, FST, PLP 5%) varied substantially (by at least 25%). Due to low gene flow, P. volubilis mostly consists of small isolated subpopulations (ΦPT = 0.252–0.323) with some degree of admixture given by socio-economic connectivity among the sites; a direct link between the genetic and geographic distances was not confirmed. The study illustrates the successful application of AFLP to infer genetic structure in non-model plants. PMID:28910307
Error Analysis and Performance Data from an Automated Azimuth Measuring System,
1981-02-17
microprocessors, tape drives, input and i NM. A detailed error analysis of the output hardware, a dual-axis tiltmeter ystem and methods to improve...performance mounted on the azimuth gimbal of each ALS, and accuracy are presented. Discussion and six tiltmeters arranged on an optical includes selected...velocity air flowing through tubes along the optical paths to each target. 1 . Introduction Temperature sensors are located in each To accurately and
ERIC Educational Resources Information Center
Huitema, Bradley E.; McKean, Joseph W.
2007-01-01
Regression models used in the analysis of interrupted time-series designs assume statistically independent errors. Four methods of evaluating this assumption are the Durbin-Watson (D-W), Huitema-McKean (H-M), Box-Pierce (B-P), and Ljung-Box (L-B) tests. These tests were compared with respect to Type I error and power under a wide variety of error…
Simulating and Detecting Radiation-Induced Errors for Onboard Machine Learning
NASA Technical Reports Server (NTRS)
Wagstaff, Kiri L.; Bornstein, Benjamin; Granat, Robert; Tang, Benyang; Turmon, Michael
2009-01-01
Spacecraft processors and memory are subjected to high radiation doses and therefore employ radiation-hardened components. However, these components are orders of magnitude more expensive than typical desktop components, and they lag years behind in terms of speed and size. We have integrated algorithm-based fault tolerance (ABFT) methods into onboard data analysis algorithms to detect radiation-induced errors, which ultimately may permit the use of spacecraft memory that need not be fully hardened, reducing cost and increasing capability at the same time. We have also developed a lightweight software radiation simulator, BITFLIPS, that permits evaluation of error detection strategies in a controlled fashion, including the specification of the radiation rate and selective exposure of individual data structures. Using BITFLIPS, we evaluated our error detection methods when using a support vector machine to analyze data collected by the Mars Odyssey spacecraft. We found ABFT error detection for matrix multiplication is very successful, while error detection for Gaussian kernel computation still has room for improvement.
Instrumental variables vs. grouping approach for reducing bias due to measurement error.
Batistatou, Evridiki; McNamee, Roseanne
2008-01-01
Attenuation of the exposure-response relationship due to exposure measurement error is often encountered in epidemiology. Given that error cannot be totally eliminated, bias correction methods of analysis are needed. Many methods require more than one exposure measurement per person to be made, but the `group mean OLS method,' in which subjects are grouped into several a priori defined groups followed by ordinary least squares (OLS) regression on the group means, can be applied with one measurement. An alternative approach is to use an instrumental variable (IV) method in which both the single error-prone measure and an IV are used in IV analysis. In this paper we show that the `group mean OLS' estimator is equal to an IV estimator with the group mean used as IV, but that the variance estimators for the two methods are different. We derive a simple expression for the bias in the common estimator which is a simple function of group size, reliability and contrast of exposure between groups, and show that the bias can be very small when group size is large. We compare this method with a new proposal (group mean ranking method), also applicable with a single exposure measurement, in which the IV is the rank of the group means. When there are two independent exposure measurements per subject, we propose a new IV method (EVROS IV) and compare it with Carroll and Stefanski's (CS IV) proposal in which the second measure is used as an IV; the new IV estimator combines aspects of the `group mean' and `CS' strategies. All methods are evaluated in terms of bias, precision and root mean square error via simulations and a dataset from occupational epidemiology. The `group mean ranking method' does not offer much improvement over the `group mean method.' Compared with the `CS' method, the `EVROS' method is less affected by low reliability of exposure. We conclude that the group IV methods we propose may provide a useful way to handle mismeasured exposures in epidemiology with or without replicate measurements. Our finding may also have implications for the use of aggregate variables in epidemiology to control for unmeasured confounding.
Lystrom, David J.
1972-01-01
Various methods of verifying real-time streamflow data are outlined in part II. Relatively large errors (those greater than 20-30 percent) can be detected readily by use of well-designed verification programs for a digital computer, and smaller errors can be detected only by discharge measurements and field observations. The capability to substitute a simulated discharge value for missing or erroneous data is incorporated in some of the verification routines described. The routines represent concepts ranging from basic statistical comparisons to complex watershed modeling and provide a selection from which real-time data users can choose a suitable level of verification.
Meijer, Erik; Rohwedder, Susann; Wansbeek, Tom
2012-01-01
Survey data on earnings tend to contain measurement error. Administrative data are superior in principle, but they are worthless in case of a mismatch. We develop methods for prediction in mixture factor analysis models that combine both data sources to arrive at a single earnings figure. We apply the methods to a Swedish data set. Our results show that register earnings data perform poorly if there is a (small) probability of a mismatch. Survey earnings data are more reliable, despite their measurement error. Predictors that combine both and take conditional class probabilities into account outperform all other predictors.
Population viability analysis with species occurrence data from museum collections.
Skarpaas, Olav; Stabbetorp, Odd E
2011-06-01
The most comprehensive data on many species come from scientific collections. Thus, we developed a method of population viability analysis (PVA) in which this type of occurrence data can be used. In contrast to classical PVA, our approach accounts for the inherent observation error in occurrence data and allows the estimation of the population parameters needed for viability analysis. We tested the sensitivity of the approach to spatial resolution of the data, length of the time series, sampling effort, and detection probability with simulated data and conducted PVAs for common, rare, and threatened species. We compared the results of these PVAs with results of standard method PVAs in which observation error is ignored. Our method provided realistic estimates of population growth terms and quasi-extinction risk in cases in which the standard method without observation error could not. For low values of any of the sampling variables we tested, precision decreased, and in some cases biased estimates resulted. The results of our PVAs with the example species were consistent with information in the literature on these species. Our approach may facilitate PVA for a wide range of species of conservation concern for which demographic data are lacking but occurrence data are readily available. ©2011 Society for Conservation Biology.
Using Robust Standard Errors to Combine Multiple Regression Estimates with Meta-Analysis
ERIC Educational Resources Information Center
Williams, Ryan T.
2012-01-01
Combining multiple regression estimates with meta-analysis has continued to be a difficult task. A variety of methods have been proposed and used to combine multiple regression slope estimates with meta-analysis, however, most of these methods have serious methodological and practical limitations. The purpose of this study was to explore the use…
Improved methods for the measurement and analysis of stellar magnetic fields
NASA Technical Reports Server (NTRS)
Saar, Steven H.
1988-01-01
The paper presents several improved methods for the measurement of magnetic fields on cool stars which take into account simple radiative transfer effects and the exact Zeeman patterns. Using these methods, high-resolution, low-noise data can be fitted with theoretical line profiles to determine the mean magnetic field strength in stellar active regions and a model-dependent fraction of the stellar surface (filling factor) covered by these regions. Random errors in the derived field strength and filling factor are parameterized in terms of signal-to-noise ratio, wavelength, spectral resolution, stellar rotation rate, and the magnetic parameters themselves. Weak line blends, if left uncorrected, can have significant systematic effects on the derived magnetic parameters, and thus several methods are developed to compensate partially for them. The magnetic parameters determined by previous methods likely have systematic errors because of such line blends and because of line saturation effects. Other sources of systematic error are explored in detail. These sources of error currently make it difficult to determine the magnetic parameters of individual stars to better than about + or - 20 percent.
A correlated meta-analysis strategy for data mining "OMIC" scans.
Province, Michael A; Borecki, Ingrid B
2013-01-01
Meta-analysis is becoming an increasingly popular and powerful tool to integrate findings across studies and OMIC dimensions. But there is the danger that hidden dependencies between putatively "independent" studies can cause inflation of type I error, due to reinforcement of the evidence from false-positive findings. We present here a simple method for conducting meta-analyses that automatically estimates the degree of any such non-independence between OMIC scans and corrects the inference for it, retaining the proper type I error structure. The method does not require the original data from the source studies, but operates only on summary analysis results from these in OMIC scans. The method is applicable in a wide variety of situations including combining GWAS and or sequencing scan results across studies with dependencies due to overlapping subjects, as well as to scans of correlated traits, in a meta-analysis scan for pleiotropic genetic effects. The method correctly detects which scans are actually independent in which case it yields the traditional meta-analysis, so it may safely be used in all cases, when there is even a suspicion of correlation amongst scans.
NASA Technical Reports Server (NTRS)
Didlake, Anthony C., Jr.; Heymsfield, Gerald M.; Tian, Lin; Guimond, Stephen R.
2015-01-01
The coplane analysis technique for mapping the three-dimensional wind field of precipitating systems is applied to the NASA High Altitude Wind and Rain Airborne Profiler (HIWRAP). HIWRAP is a dual-frequency Doppler radar system with two downward pointing and conically scanning beams. The coplane technique interpolates radar measurements to a natural coordinate frame, directly solves for two wind components, and integrates the mass continuity equation to retrieve the unobserved third wind component. This technique is tested using a model simulation of a hurricane and compared to a global optimization retrieval. The coplane method produced lower errors for the cross-track and vertical wind components, while the global optimization method produced lower errors for the along-track wind component. Cross-track and vertical wind errors were dependent upon the accuracy of the estimated boundary condition winds near the surface and at nadir, which were derived by making certain assumptions about the vertical velocity field. The coplane technique was then applied successfully to HIWRAP observations of Hurricane Ingrid (2013). Unlike the global optimization method, the coplane analysis allows for a transparent connection between the radar observations and specific analysis results. With this ability, small-scale features can be analyzed more adequately and erroneous radar measurements can be identified more easily.
Woolf, Steven H.; Kuzel, Anton J.; Dovey, Susan M.; Phillips, Robert L.
2004-01-01
BACKGROUND Notions about the most common errors in medicine currently rest on conjecture and weak epidemiologic evidence. We sought to determine whether cascade analysis is of value in clarifying the epidemiology and causes of errors and whether physician reports are sensitive to the impact of errors on patients. METHODS Eighteen US family physicians participating in a 6-country international study filed 75 anonymous error reports. The narratives were examined to identify the chain of events and the predominant proximal errors. We tabulated the consequences to patients, both reported by physicians and inferred by investigators. RESULTS A chain of errors was documented in 77% of incidents. Although 83% of the errors that ultimately occurred were mistakes in treatment or diagnosis, 2 of 3 were set in motion by errors in communication. Fully 80% of the errors that initiated cascades involved informational or personal miscommunication. Examples of informational miscommunication included communication breakdowns among colleagues and with patients (44%), misinformation in the medical record (21%), mishandling of patients’ requests and messages (18%), inaccessible medical records (12%), and inadequate reminder systems (5%). When asked whether the patient was harmed, physicians answered affirmatively in 43% of cases in which their narratives described harms. Psychological and emotional effects accounted for 17% of physician-reported consequences but 69% of investigator-inferred consequences. CONCLUSIONS Cascade analysis of physicians’ error reports is helpful in understanding the precipitant chain of events, but physicians provide incomplete information about how patients are affected. Miscommunication appears to play an important role in propagating diagnostic and treatment mistakes. PMID:15335130
[Gaussian process regression and its application in near-infrared spectroscopy analysis].
Feng, Ai-Ming; Fang, Li-Min; Lin, Min
2011-06-01
Gaussian process (GP) is applied in the present paper as a chemometric method to explore the complicated relationship between the near infrared (NIR) spectra and ingredients. After the outliers were detected by Monte Carlo cross validation (MCCV) method and removed from dataset, different preprocessing methods, such as multiplicative scatter correction (MSC), smoothing and derivate, were tried for the best performance of the models. Furthermore, uninformative variable elimination (UVE) was introduced as a variable selection technique and the characteristic wavelengths obtained were further employed as input for modeling. A public dataset with 80 NIR spectra of corn was introduced as an example for evaluating the new algorithm. The optimal models for oil, starch and protein were obtained by the GP regression method. The performance of the final models were evaluated according to the root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP) and correlation coefficient (r). The models give good calibration ability with r values above 0.99 and the prediction ability is also satisfactory with r values higher than 0.96. The overall results demonstrate that GP algorithm is an effective chemometric method and is promising for the NIR analysis.
Statistical approaches to account for false-positive errors in environmental DNA samples.
Lahoz-Monfort, José J; Guillera-Arroita, Gurutzeta; Tingley, Reid
2016-05-01
Environmental DNA (eDNA) sampling is prone to both false-positive and false-negative errors. We review statistical methods to account for such errors in the analysis of eDNA data and use simulations to compare the performance of different modelling approaches. Our simulations illustrate that even low false-positive rates can produce biased estimates of occupancy and detectability. We further show that removing or classifying single PCR detections in an ad hoc manner under the suspicion that such records represent false positives, as sometimes advocated in the eDNA literature, also results in biased estimation of occupancy, detectability and false-positive rates. We advocate alternative approaches to account for false-positive errors that rely on prior information, or the collection of ancillary detection data at a subset of sites using a sampling method that is not prone to false-positive errors. We illustrate the advantages of these approaches over ad hoc classifications of detections and provide practical advice and code for fitting these models in maximum likelihood and Bayesian frameworks. Given the severe bias induced by false-negative and false-positive errors, the methods presented here should be more routinely adopted in eDNA studies. © 2015 John Wiley & Sons Ltd.
Local and global evaluation for remote sensing image segmentation
NASA Astrophysics Data System (ADS)
Su, Tengfei; Zhang, Shengwei
2017-08-01
In object-based image analysis, how to produce accurate segmentation is usually a very important issue that needs to be solved before image classification or target recognition. The study for segmentation evaluation method is key to solving this issue. Almost all of the existent evaluation strategies only focus on the global performance assessment. However, these methods are ineffective for the situation that two segmentation results with very similar overall performance have very different local error distributions. To overcome this problem, this paper presents an approach that can both locally and globally quantify segmentation incorrectness. In doing so, region-overlapping metrics are utilized to quantify each reference geo-object's over and under-segmentation error. These quantified error values are used to produce segmentation error maps which have effective illustrative power to delineate local segmentation error patterns. The error values for all of the reference geo-objects are aggregated through using area-weighted summation, so that global indicators can be derived. An experiment using two scenes of very different high resolution images showed that the global evaluation part of the proposed approach was almost as effective as other two global evaluation methods, and the local part was a useful complement to comparing different segmentation results.
Comparison of structural and least-squares lines for estimating geologic relations
Williams, G.P.; Troutman, B.M.
1990-01-01
Two different goals in fitting straight lines to data are to estimate a "true" linear relation (physical law) and to predict values of the dependent variable with the smallest possible error. Regarding the first goal, a Monte Carlo study indicated that the structural-analysis (SA) method of fitting straight lines to data is superior to the ordinary least-squares (OLS) method for estimating "true" straight-line relations. Number of data points, slope and intercept of the true relation, and variances of the errors associated with the independent (X) and dependent (Y) variables influence the degree of agreement. For example, differences between the two line-fitting methods decrease as error in X becomes small relative to error in Y. Regarding the second goal-predicting the dependent variable-OLS is better than SA. Again, the difference diminishes as X takes on less error relative to Y. With respect to estimation of slope and intercept and prediction of Y, agreement between Monte Carlo results and large-sample theory was very good for sample sizes of 100, and fair to good for sample sizes of 20. The procedures and error measures are illustrated with two geologic examples. ?? 1990 International Association for Mathematical Geology.
Method to mosaic gratings that relies on analysis of far-field intensity patterns in two wavelengths
NASA Astrophysics Data System (ADS)
Hu, Yao; Zeng, Lijiang; Li, Lifeng
2007-01-01
We propose an experimental method to coherently mosaic two planar diffraction gratings. The method uses a Twyman-Green interferometer to guarantee the planar parallelism of the two sub-aperture gratings, and obtains the in-plane rotational error and the two translational errors from analysis of the far-field diffraction intensity patterns in two alignment wavelengths. We adjust the relative attitude and position of the two sub-aperture gratings to produce Airy disk diffraction patterns in both wavelengths. In our experiment, the repeatability of in-plane rotation adjustment was 2.35 μrad and that of longitudinal adjustment was 0.11 μm. The accuracy of lateral adjustment was about 2.9% of the grating period.
Image-based red cell counting for wild animals blood.
Mauricio, Claudio R M; Schneider, Fabio K; Dos Santos, Leonilda Correia
2010-01-01
An image-based red blood cell (RBC) automatic counting system is presented for wild animals blood analysis. Images with 2048×1536-pixel resolution acquired on an optical microscope using Neubauer chambers are used to evaluate RBC counting for three animal species (Leopardus pardalis, Cebus apella and Nasua nasua) and the error found using the proposed method is similar to that obtained for inter observer visual counting method, i.e., around 10%. Smaller errors (e.g., 3%) can be obtained in regions with less grid artifacts. These promising results allow the use of the proposed method either as a complete automatic counting tool in laboratories for wild animal's blood analysis or as a first counting stage in a semi-automatic counting tool.
Text Classification for Assisting Moderators in Online Health Communities
Huh, Jina; Yetisgen-Yildiz, Meliha; Pratt, Wanda
2013-01-01
Objectives Patients increasingly visit online health communities to get help on managing health. The large scale of these online communities makes it impossible for the moderators to engage in all conversations; yet, some conversations need their expertise. Our work explores low-cost text classification methods to this new domain of determining whether a thread in an online health forum needs moderators’ help. Methods We employed a binary classifier on WebMD’s online diabetes community data. To train the classifier, we considered three feature types: (1) word unigram, (2) sentiment analysis features, and (3) thread length. We applied feature selection methods based on χ2 statistics and under sampling to account for unbalanced data. We then performed a qualitative error analysis to investigate the appropriateness of the gold standard. Results Using sentiment analysis features, feature selection methods, and balanced training data increased the AUC value up to 0.75 and the F1-score up to 0.54 compared to the baseline of using word unigrams with no feature selection methods on unbalanced data (0.65 AUC and 0.40 F1-score). The error analysis uncovered additional reasons for why moderators respond to patients’ posts. Discussion We showed how feature selection methods and balanced training data can improve the overall classification performance. We present implications of weighing precision versus recall for assisting moderators of online health communities. Our error analysis uncovered social, legal, and ethical issues around addressing community members’ needs. We also note challenges in producing a gold standard, and discuss potential solutions for addressing these challenges. Conclusion Social media environments provide popular venues in which patients gain health-related information. Our work contributes to understanding scalable solutions for providing moderators’ expertise in these large-scale, social media environments. PMID:24025513
2014-01-01
Background The DerSimonian and Laird approach (DL) is widely used for random effects meta-analysis, but this often results in inappropriate type I error rates. The method described by Hartung, Knapp, Sidik and Jonkman (HKSJ) is known to perform better when trials of similar size are combined. However evidence in realistic situations, where one trial might be much larger than the other trials, is lacking. We aimed to evaluate the relative performance of the DL and HKSJ methods when studies of different sizes are combined and to develop a simple method to convert DL results to HKSJ results. Methods We evaluated the performance of the HKSJ versus DL approach in simulated meta-analyses of 2–20 trials with varying sample sizes and between-study heterogeneity, and allowing trials to have various sizes, e.g. 25% of the trials being 10-times larger than the smaller trials. We also compared the number of “positive” (statistically significant at p < 0.05) findings using empirical data of recent meta-analyses with > = 3 studies of interventions from the Cochrane Database of Systematic Reviews. Results The simulations showed that the HKSJ method consistently resulted in more adequate error rates than the DL method. When the significance level was 5%, the HKSJ error rates at most doubled, whereas for DL they could be over 30%. DL, and, far less so, HKSJ had more inflated error rates when the combined studies had unequal sizes and between-study heterogeneity. The empirical data from 689 meta-analyses showed that 25.1% of the significant findings for the DL method were non-significant with the HKSJ method. DL results can be easily converted into HKSJ results. Conclusions Our simulations showed that the HKSJ method consistently results in more adequate error rates than the DL method, especially when the number of studies is small, and can easily be applied routinely in meta-analyses. Even with the HKSJ method, extra caution is needed when there are = <5 studies of very unequal sizes. PMID:24548571
Evaluation of B1 inhomogeneity effect on DCE-MRI data analysis of brain tumor patients at 3T.
Sengupta, Anirban; Gupta, Rakesh Kumar; Singh, Anup
2017-12-02
Dynamic-contrast-enhanced (DCE) MRI data acquired using gradient echo based sequences is affected by errors in flip angle (FA) due to transmit B 1 inhomogeneity (B 1 inh). The purpose of the study was to evaluate the effect of B 1 inh on quantitative analysis of DCE-MRI data of human brain tumor patients and to evaluate the clinical significance of B 1 inh correction of perfusion parameters (PPs) on tumor grading. An MRI study was conducted on 35 glioma patients at 3T. The patients had histologically confirmed glioma with 23 high-grade (HG) and 12 low-grade (LG). Data for B 1 -mapping, T 1 -mapping and DCE-MRI were acquired. Relative B 1 maps (B 1rel ) were generated using the saturated-double-angle method. T 1 -maps were computed using the variable flip-angle method. Post-processing was performed for conversion of signal-intensity time (S(t)) curve to concentration-time (C(t)) curve followed by tracer kinetic analysis (K trans , Ve, Vp, Kep) and first pass analysis (CBV, CBF) using the general tracer-kinetic model. DCE-MRI data was analyzed without and with B 1 inh correction and errors in PPs were computed. Receiver-operating-characteristic (ROC) analysis was performed on HG and LG patients. Simulations were carried out to understand the effect of B 1 inhomogeneity on DCE-MRI data analysis in a systematic way. S(t) curves mimicking those in tumor tissue, were generated and FA errors were introduced followed by error analysis of PPs. Dependence of FA-based errors on the concentration of contrast agent and on the duration of DCE-MRI data was also studied. Simulations were also done to obtain K trans of glioma patients at different B 1rel values and see whether grading is affected or not. Current study shows that B 1rel value higher than nominal results in an overestimation of C(t) curves as well as derived PPs and vice versa. Moreover, at same B 1rel values, errors were large for larger values of C(t). Simulation results showed that grade of patients can change because of B 1 inh. B 1 inh in the human brain at 3T-MRI can introduce substantial errors in PPs derived from DCE-MRI data that might affect the accuracy of tumor grading, particularly for border zone cases. These errors can be mitigated using B 1 inh correction during DCE-MRI data analysis.
Choi, Seung Hoan; Labadorf, Adam T; Myers, Richard H; Lunetta, Kathryn L; Dupuis, Josée; DeStefano, Anita L
2017-02-06
Next generation sequencing provides a count of RNA molecules in the form of short reads, yielding discrete, often highly non-normally distributed gene expression measurements. Although Negative Binomial (NB) regression has been generally accepted in the analysis of RNA sequencing (RNA-Seq) data, its appropriateness has not been exhaustively evaluated. We explore logistic regression as an alternative method for RNA-Seq studies designed to compare cases and controls, where disease status is modeled as a function of RNA-Seq reads using simulated and Huntington disease data. We evaluate the effect of adjusting for covariates that have an unknown relationship with gene expression. Finally, we incorporate the data adaptive method in order to compare false positive rates. When the sample size is small or the expression levels of a gene are highly dispersed, the NB regression shows inflated Type-I error rates but the Classical logistic and Bayes logistic (BL) regressions are conservative. Firth's logistic (FL) regression performs well or is slightly conservative. Large sample size and low dispersion generally make Type-I error rates of all methods close to nominal alpha levels of 0.05 and 0.01. However, Type-I error rates are controlled after applying the data adaptive method. The NB, BL, and FL regressions gain increased power with large sample size, large log2 fold-change, and low dispersion. The FL regression has comparable power to NB regression. We conclude that implementing the data adaptive method appropriately controls Type-I error rates in RNA-Seq analysis. Firth's logistic regression provides a concise statistical inference process and reduces spurious associations from inaccurately estimated dispersion parameters in the negative binomial framework.
Results of a nuclear power plant application of A New Technique for Human Error Analysis (ATHEANA)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Whitehead, D.W.; Forester, J.A.; Bley, D.C.
1998-03-01
A new method to analyze human errors has been demonstrated at a pressurized water reactor (PWR) nuclear power plant. This was the first application of the new method referred to as A Technique for Human Error Analysis (ATHEANA). The main goals of the demonstration were to test the ATHEANA process as described in the frame-of-reference manual and the implementation guideline, test a training package developed for the method, test the hypothesis that plant operators and trainers have significant insight into the error-forcing-contexts (EFCs) that can make unsafe actions (UAs) more likely, and to identify ways to improve the method andmore » its documentation. A set of criteria to evaluate the success of the ATHEANA method as used in the demonstration was identified. A human reliability analysis (HRA) team was formed that consisted of an expert in probabilistic risk assessment (PRA) with some background in HRA (not ATHEANA) and four personnel from the nuclear power plant. Personnel from the plant included two individuals from their PRA staff and two individuals from their training staff. Both individuals from training are currently licensed operators and one of them was a senior reactor operator on shift until a few months before the demonstration. The demonstration was conducted over a 5-month period and was observed by members of the Nuclear Regulatory Commission`s ATHEANA development team, who also served as consultants to the HRA team when necessary. Example results of the demonstration to date, including identified human failure events (HFEs), UAs, and EFCs are discussed. Also addressed is how simulator exercises are used in the ATHEANA demonstration project.« less
A New Design of the Test Rig to Measure the Transmission Error of Automobile Gearbox
NASA Astrophysics Data System (ADS)
Hou, Yixuan; Zhou, Xiaoqin; He, Xiuzhi; Liu, Zufei; Liu, Qiang
2017-12-01
Noise and vibration affect the performance of automobile gearbox. And transmission error has been regarded as an important excitation source in gear system. Most of current research is focused on the measurement and analysis of single gear drive, and few investigations on the transmission error measurement in complete gearbox were conducted. In order to measure transmission error in a complete automobile gearbox, a kind of electrically closed test rig is developed. Based on the principle of modular design, the test rig can be used to test different types of gearbox by adding necessary modules. The test rig for front engine, rear-wheel-drive gearbox is constructed. And static and modal analysis methods are taken to verify the performance of a key component.
Linear error analysis of slope-area discharge determinations
Kirby, W.H.
1987-01-01
The slope-area method can be used to calculate peak flood discharges when current-meter measurements are not possible. This calculation depends on several quantities, such as water-surface fall, that are subject to large measurement errors. Other critical quantities, such as Manning's n, are not even amenable to direct measurement but can only be estimated. Finally, scour and fill may cause gross discrepancies between the observed condition of the channel and the hydraulic conditions during the flood peak. The effects of these potential errors on the accuracy of the computed discharge have been estimated by statistical error analysis using a Taylor-series approximation of the discharge formula and the well-known formula for the variance of a sum of correlated random variates. The resultant error variance of the computed discharge is a weighted sum of covariances of the various observational errors. The weights depend on the hydraulic and geometric configuration of the channel. The mathematical analysis confirms the rule of thumb that relative errors in computed discharge increase rapidly when velocity heads exceed the water-surface fall, when the flow field is expanding and when lateral velocity variation (alpha) is large. It also confirms the extreme importance of accurately assessing the presence of scour or fill. ?? 1987.
Shi, Yun; Xu, Peiliang; Peng, Junhuan; Shi, Chuang; Liu, Jingnan
2014-01-01
Modern observation technology has verified that measurement errors can be proportional to the true values of measurements such as GPS, VLBI baselines and LiDAR. Observational models of this type are called multiplicative error models. This paper is to extend the work of Xu and Shimada published in 2000 on multiplicative error models to analytical error analysis of quantities of practical interest and estimates of the variance of unit weight. We analytically derive the variance-covariance matrices of the three least squares (LS) adjustments, the adjusted measurements and the corrections of measurements in multiplicative error models. For quality evaluation, we construct five estimators for the variance of unit weight in association of the three LS adjustment methods. Although LiDAR measurements are contaminated with multiplicative random errors, LiDAR-based digital elevation models (DEM) have been constructed as if they were of additive random errors. We will simulate a model landslide, which is assumed to be surveyed with LiDAR, and investigate the effect of LiDAR-type multiplicative error measurements on DEM construction and its effect on the estimate of landslide mass volume from the constructed DEM. PMID:24434880
DOE Office of Scientific and Technical Information (OSTI.GOV)
Vazquez Quino, L; Huerta Hernandez, C; Morrow, A
2016-06-15
Purpose: To evaluate the use of MobiusFX as a pre-treatment verification IMRT QA tool and compare it with a commercial 4D detector array for VMAT plan QA. Methods: 15 VMAT plan QA of different treatment sites were delivered and measured by traditional means with the 4D detector array ArcCheck (Sun Nuclear corporation) and at the same time measurement in linac treatment logs (Varian Dynalogs files) were analyzed from the same delivery with MobiusFX software (Mobius Medical Systems). VMAT plan QAs created in Eclipse treatment planning system (Varian) in a TrueBeam linac machine (Varian) were delivered and analyzed with the gammamore » analysis routine from SNPA software (Sun Nuclear corporation). Results: Comparable results in terms of the gamma analysis with 99.06% average gamma passing with 3%,3mm passing rate is observed in the comparison among MobiusFX, ArcCheck measurements, and the Treatment Planning System dose calculated. When going to a stricter criterion (1%,1mm) larger discrepancies are observed in different regions of the measurements with an average gamma of 66.24% between MobiusFX and ArcCheck. Conclusion: This work indicates the potential for using MobiusFX as a routine pre-treatment patient specific IMRT method for quality assurance purposes and its advantages as a phantom-less method which reduce the time for IMRT QA measurement. MobiusFX is capable of produce similar results of those by traditional methods used for patient specific pre-treatment verification VMAT QA. Even the gamma results comparing to the TPS are similar the analysis of both methods show that the errors being identified by each method are found in different regions. Traditional methods like ArcCheck are sensitive to setup errors and dose difference errors coming from the linac output. On the other hand linac log files analysis record different errors in the VMAT QA associated with the MLCs and gantry motion that by traditional methods cannot be detected.« less
Markerless attenuation correction for carotid MRI surface receiver coils in combined PET/MR imaging
NASA Astrophysics Data System (ADS)
Eldib, Mootaz; Bini, Jason; Robson, Philip M.; Calcagno, Claudia; Faul, David D.; Tsoumpas, Charalampos; Fayad, Zahi A.
2015-06-01
The purpose of the study was to evaluate the effect of attenuation of MR coils on quantitative carotid PET/MR exams. Additionally, an automated attenuation correction method for flexible carotid MR coils was developed and evaluated. The attenuation of the carotid coil was measured by imaging a uniform water phantom injected with 37 MBq of 18F-FDG in a combined PET/MR scanner for 24 min with and without the coil. In the same session, an ultra-short echo time (UTE) image of the coil on top of the phantom was acquired. Using a combination of rigid and non-rigid registration, a CT-based attenuation map was registered to the UTE image of the coil for attenuation and scatter correction. After phantom validation, the effect of the carotid coil attenuation and the attenuation correction method were evaluated in five subjects. Phantom studies indicated that the overall loss of PET counts due to the coil was 6.3% with local region-of-interest (ROI) errors reaching up to 18.8%. Our registration method to correct for attenuation from the coil decreased the global error and local error (ROI) to 0.8% and 3.8%, respectively. The proposed registration method accurately captured the location and shape of the coil with a maximum spatial error of 2.6 mm. Quantitative analysis in human studies correlated with the phantom findings, but was dependent on the size of the ROI used in the analysis. MR coils result in significant error in PET quantification and thus attenuation correction is needed. The proposed strategy provides an operator-free method for attenuation and scatter correction for a flexible MRI carotid surface coil for routine clinical use.
NASA Astrophysics Data System (ADS)
Carpenter, Matthew H.; Jernigan, J. G.
2007-05-01
We present examples of an analysis progression consisting of a synthesis of the Photon Clean Method (Carpenter, Jernigan, Brown, Beiersdorfer 2007) and bootstrap methods to quantify errors and variations in many-parameter models. The Photon Clean Method (PCM) works well for model spaces with large numbers of parameters proportional to the number of photons, therefore a Monte Carlo paradigm is a natural numerical approach. Consequently, PCM, an "inverse Monte-Carlo" method, requires a new approach for quantifying errors as compared to common analysis methods for fitting models of low dimensionality. This presentation will explore the methodology and presentation of analysis results derived from a variety of public data sets, including observations with XMM-Newton, Chandra, and other NASA missions. Special attention is given to the visualization of both data and models including dynamic interactive presentations. This work was performed under the auspices of the Department of Energy under contract No. W-7405-Eng-48. We thank Peter Beiersdorfer and Greg Brown for their support of this technical portion of a larger program related to science with the LLNL EBIT program.
Global Warming Estimation from MSU
NASA Technical Reports Server (NTRS)
Prabhakara, C.; Iacovazzi, Robert; Yoo, Jung-Moon
1998-01-01
Microwave Sounding Unit (MSU) radiometer observations in Ch 2 (53.74 GHz) from sequential, sun-synchronous, polar-orbiting NOAA satellites contain small systematic errors. Some of these errors are time-dependent and some are time-independent. Small errors in Ch 2 data of successive satellites arise from calibration differences. Also, successive NOAA satellites tend to have different Local Equatorial Crossing Times (LECT), which introduce differences in Ch 2 data due to the diurnal cycle. These two sources of systematic error are largely time independent. However, because of atmospheric drag, there can be a drift in the LECT of a given satellite, which introduces time-dependent systematic errors. One of these errors is due to the progressive chance in the diurnal cycle and the other is due to associated chances in instrument heating by the sun. In order to infer global temperature trend from the these MSU data, we have eliminated explicitly the time-independent systematic errors. Both of the time-dependent errors cannot be assessed from each satellite. For this reason, their cumulative effect on the global temperature trend is evaluated implicitly. Christy et al. (1998) (CSL). based on their method of analysis of the MSU Ch 2 data, infer a global temperature cooling trend (-0.046 K per decade) from 1979 to 1997, although their near nadir measurements yield near zero trend (0.003 K/decade). Utilising an independent method of analysis, we infer global temperature warmed by 0.12 +/- 0.06 C per decade from the observations of the MSU Ch 2 during the period 1980 to 1997.
A video method to study Drosophila sleep.
Zimmerman, John E; Raizen, David M; Maycock, Matthew H; Maislin, Greg; Pack, Allan I
2008-11-01
To use video to determine the accuracy of the infrared beam-splitting method for measuring sleep in Drosophila and to determine the effect of time of day, sex, genotype, and age on sleep measurements. A digital image analysis method based on frame subtraction principle was developed to distinguish a quiescent from a moving fly. Data obtained using this method were compared with data obtained using the Drosophila Activity Monitoring System (DAMS). The location of the fly was identified based on its centroid location in the subtracted images. The error associated with the identification of total sleep using DAMS ranged from 7% to 95% and depended on genotype, sex, age, and time of day. The degree of the total sleep error was dependent on genotype during the daytime (P < 0.001) and was dependent on age during both the daytime and the nighttime (P < 0.001 for both). The DAMS method overestimated sleep bout duration during both the day and night, and the degree of these errors was genotype dependent (P < 0.001). Brief movements that occur during sleep bouts can be accurately identified using video. Both video and DAMS detected a homeostatic response to sleep deprivation. Video digital analysis is more accurate than DAMS in fly sleep measurements. In particular, conclusions drawn from DAMS measurements regarding daytime sleep and sleep architecture should be made with caution. Video analysis also permits the assessment of fly position and brief movements during sleep.
Bootstrap Methods: A Very Leisurely Look.
ERIC Educational Resources Information Center
Hinkle, Dennis E.; Winstead, Wayland H.
The Bootstrap method, a computer-intensive statistical method of estimation, is illustrated using a simple and efficient Statistical Analysis System (SAS) routine. The utility of the method for generating unknown parameters, including standard errors for simple statistics, regression coefficients, discriminant function coefficients, and factor…
NASA Astrophysics Data System (ADS)
Jia, Mei-Hui; Wang, Cheng-Lin; Ren, Bin
2017-07-01
Stress, strain and vibration characteristics of rotor parts should be changed significantly under high acceleration, manufacturing error is one of the most important reason. However, current research on this problem has not been carried out. A rotor with an acceleration of 150,000 g is considered as the objective, the effects of manufacturing errors on rotor mechanical properties and dynamic characteristics are executed by the selection of the key affecting factors. Through the force balance equation of the rotor infinitesimal unit establishment, a theoretical model of stress calculation based on slice method is proposed and established, a formula for the rotor stress at any point derives. A finite element model (FEM) of rotor with holes is established with manufacturing errors. The changes of the stresses and strains of a rotor in parallelism and symmetry errors are analyzed, which verify the validity of the theoretical model. The pre-stressing modal analysis is performed based on the aforementioned static analysis. The key dynamic characteristics are analyzed. The results demonstrated that, as the parallelism and symmetry errors increase, the equivalent stresses and strains of the rotor slowly increase linearly, the highest growth rate does not exceed 4%, the maximum change rate of natural frequency is 0.1%. The rotor vibration mode is not significantly affected. The FEM construction method of the rotor with manufacturing errors can be utilized for the quantitative research on rotor characteristics, which will assist in the active control of rotor component reliability under high acceleration.
Gamma model and its analysis for phase measuring profilometry.
Liu, Kai; Wang, Yongchang; Lau, Daniel L; Hao, Qi; Hassebrook, Laurence G
2010-03-01
Phase measuring profilometry is a method of structured light illumination whose three-dimensional reconstructions are susceptible to error from nonunitary gamma in the associated optical devices. While the effects of this distortion diminish with an increasing number of employed phase-shifted patterns, gamma distortion may be unavoidable in real-time systems where the number of projected patterns is limited by the presence of target motion. A mathematical model is developed for predicting the effects of nonunitary gamma on phase measuring profilometry, while also introducing an accurate gamma calibration method and two strategies for minimizing gamma's effect on phase determination. These phase correction strategies include phase corrections with and without gamma calibration. With the reduction in noise, for three-step phase measuring profilometry, analysis of the root mean squared error of the corrected phase will show a 60x reduction in phase error when the proposed gamma calibration is performed versus 33x reduction without calibration.
Methods for increasing cooperation rates for surveys of family forest owners
Brett J. Butler; Jaketon H. Hewes; Mary L. Tyrrell; Sarah M. Butler
2016-01-01
To maximize the representativeness of results from surveys, coverage, sampling, nonresponse, measurement, and analysis errors must be minimized. Although not a cure-all, one approach for mitigating nonresponse errors is to maximize cooperation rates. In this study, personalizing mailings, token financial incentives, and the use of real stamps were tested for their...
Ruuska, Salla; Hämäläinen, Wilhelmiina; Kajava, Sari; Mughal, Mikaela; Matilainen, Pekka; Mononen, Jaakko
2018-03-01
The aim of the present study was to evaluate empirically confusion matrices in device validation. We compared the confusion matrix method to linear regression and error indices in the validation of a device measuring feeding behaviour of dairy cattle. In addition, we studied how to extract additional information on classification errors with confusion probabilities. The data consisted of 12 h behaviour measurements from five dairy cows; feeding and other behaviour were detected simultaneously with a device and from video recordings. The resulting 216 000 pairs of classifications were used to construct confusion matrices and calculate performance measures. In addition, hourly durations of each behaviour were calculated and the accuracy of measurements was evaluated with linear regression and error indices. All three validation methods agreed when the behaviour was detected very accurately or inaccurately. Otherwise, in the intermediate cases, the confusion matrix method and error indices produced relatively concordant results, but the linear regression method often disagreed with them. Our study supports the use of confusion matrix analysis in validation since it is robust to any data distribution and type of relationship, it makes a stringent evaluation of validity, and it offers extra information on the type and sources of errors. Copyright © 2018 Elsevier B.V. All rights reserved.
Nkenke, Emeka; Lehner, Bernhard; Kramer, Manuel; Haeusler, Gerd; Benz, Stefanie; Schuster, Maria; Neukam, Friedrich W; Vairaktaris, Eleftherios G; Wurm, Jochen
2006-03-01
To assess measurement errors of a novel technique for the three-dimensional determination of the degree of facial symmetry in patients suffering from unilateral cleft lip and palate malformations. Technical report, reliability study. Cleft Lip and Palate Center of the University of Erlangen-Nuremberg, Erlangen, Germany. The three-dimensional facial surface data of five 10-year-old unilateral cleft lip and palate patients were subjected to the analysis. Distances, angles, surface areas, and volumes were assessed twice. Calculations were made for method error, intraclass correlation coefficient, and repeatability of the measurements of distances, angles, surface areas, and volumes. The method errors were less than 1 mm for distances and less than 1.5 degrees for angles. The intraclass correlation coefficients showed values greater than .90 for all parameters. The repeatability values were comparable for cleft and noncleft sides. The small method errors, high intraclass correlation coefficients, and comparable repeatability values for cleft and noncleft sides reveal that the new technique is appropriate for clinical use.
The inference of atmospheric ozone using satellite horizon measurements in the 1042 per cm band.
NASA Technical Reports Server (NTRS)
Russell, J. M., III; Drayson, S. R.
1972-01-01
Description of a method for inferring atmospheric ozone information using infrared horizon radiance measurements in the 1042 per cm band. An analysis based on this method proves the feasibility of the horizon experiment for determining ozone information and shows that the ozone partial pressure can be determined in the altitude range from 50 down to 25 km. A comprehensive error study is conducted which considers effects of individual errors as well as the effect of all error sources acting simultaneously. The results show that in the absence of a temperature profile bias error, it should be possible to determine the ozone partial pressure to within an rms value of 15 to 20%. It may be possible to reduce this rms error to 5% by smoothing the solution profile. These results would be seriously degraded by an atmospheric temperature bias error of only 3 K; thus, great care should be taken to minimize this source of error in an experiment. It is probable, in view of recent technological developments, that these errors will be much smaller in future flight experiments and the altitude range will widen to include from about 60 km down to the tropopause region.
Head repositioning accuracy to neutral: a comparative study of error calculation.
Hill, Robert; Jensen, Pål; Baardsen, Tor; Kulvik, Kristian; Jull, Gwendolen; Treleaven, Julia
2009-02-01
Deficits in cervical proprioception have been identified in subjects with neck pain through the measure of head repositioning accuracy (HRA). Nevertheless there appears to be no general consensus regarding the construct of measurement of error used for calculating HRA. This study investigated four different mathematical methods of measurement of error to determine if there were any differences in their ability to discriminate between a control group and subjects with a whiplash associated disorder. The four methods for measuring cervical joint position error were calculated using a previous data set consisting of 50 subjects with whiplash complaining of dizziness (WAD D), 50 subjects with whiplash not complaining of dizziness (WAD ND) and 50 control subjects. The results indicated that no one measure of HRA uniquely detected or defined the differences between the whiplash and control groups. Constant error (CE) was significantly different between the whiplash and control groups from extension (p<0.05). Absolute errors (AEs) and root mean square errors (RMSEs) demonstrated differences between the two WAD groups in rotation trials (p<0.05). No differences were seen with variable error (VE). The results suggest that a combination of AE (or RMSE) and CE are probably the most suitable measures for analysis of HRA.
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.
NASA Astrophysics Data System (ADS)
Berger, Lukas; Kleinheinz, Konstantin; Attili, Antonio; Bisetti, Fabrizio; Pitsch, Heinz; Mueller, Michael E.
2018-05-01
Modelling unclosed terms in partial differential equations typically involves two steps: First, a set of known quantities needs to be specified as input parameters for a model, and second, a specific functional form needs to be defined to model the unclosed terms by the input parameters. Both steps involve a certain modelling error, with the former known as the irreducible error and the latter referred to as the functional error. Typically, only the total modelling error, which is the sum of functional and irreducible error, is assessed, but the concept of the optimal estimator enables the separate analysis of the total and the irreducible errors, yielding a systematic modelling error decomposition. In this work, attention is paid to the techniques themselves required for the practical computation of irreducible errors. Typically, histograms are used for optimal estimator analyses, but this technique is found to add a non-negligible spurious contribution to the irreducible error if models with multiple input parameters are assessed. Thus, the error decomposition of an optimal estimator analysis becomes inaccurate, and misleading conclusions concerning modelling errors may be drawn. In this work, numerically accurate techniques for optimal estimator analyses are identified and a suitable evaluation of irreducible errors is presented. Four different computational techniques are considered: a histogram technique, artificial neural networks, multivariate adaptive regression splines, and an additive model based on a kernel method. For multiple input parameter models, only artificial neural networks and multivariate adaptive regression splines are found to yield satisfactorily accurate results. Beyond a certain number of input parameters, the assessment of models in an optimal estimator analysis even becomes practically infeasible if histograms are used. The optimal estimator analysis in this paper is applied to modelling the filtered soot intermittency in large eddy simulations using a dataset of a direct numerical simulation of a non-premixed sooting turbulent flame.
[The history of correction of refractive errors: spectacles].
Wojtyczkak, E
2000-01-01
An historical analysis of discoveries related to the treatment of defects of vision is described. Opinions on visual processes, optics and methods of treating myopia, hypermetropia and astigmatism from ancient times through the Middle Ages, the renaissance and the following centuries are presented in particular. The beginning of the usage of glasses is discussed. Examples of the techniques which have been used to improve the subjective and objective methods of measuring refractive errors are also presented.
NASA Astrophysics Data System (ADS)
Vasilevsky, A. M.; Konoplev, G. A.; Stepanova, O. S.; Toropov, D. K.; Zagorsky, A. L.
2016-04-01
A novel direct spectrophotometric method for quantitative determination of Oxiphore® drug substance (synthetic polyhydroquinone complex) in food supplements is developed. Absorption spectra of Oxiphore® water solutions in the ultraviolet region are presented. Samples preparation procedures and mathematical methods of spectra post-analytical procession are discussed. Basic characteristics of the automatic CCD-based UV spectrophotometer and special software implementing the developed method are described. The results of the trials of the developed method and software are analyzed: the error of determination for Oxiphore® concentration in water solutions of the isolated substance and singlecomponent food supplements did not exceed 15% (average error was 7…10%).
IMRT QA: Selecting gamma criteria based on error detection sensitivity.
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.
Rejman, Marek
2013-01-01
The aim of this study was to analyze the error structure in propulsive movements with regard to its influence on monofin swimming speed. The random cycles performed by six swimmers were filmed during a progressive test (900m). An objective method to estimate errors committed in the area of angular displacement of the feet and monofin segments was employed. The parameters were compared with a previously described model. Mutual dependences between the level of errors, stroke frequency, stroke length and amplitude in relation to swimming velocity were analyzed. The results showed that proper foot movements and the avoidance of errors, arising at the distal part of the fin, ensure the progression of swimming speed. The individual stroke parameters distribution which consists of optimally increasing stroke frequency to the maximal possible level that enables the stabilization of stroke length leads to the minimization of errors. Identification of key elements in the stroke structure based on the analysis of errors committed should aid in improving monofin swimming technique. Key points The monofin swimming technique was evaluated through the prism of objectively defined errors committed by the swimmers. The dependences between the level of errors, stroke rate, stroke length and amplitude in relation to swimming velocity were analyzed. Optimally increasing stroke rate to the maximal possible level that enables the stabilization of stroke length leads to the minimization of errors. Propriety foot movement and the avoidance of errors arising at the distal part of fin, provide for the progression of swimming speed. The key elements improving monofin swimming technique, based on the analysis of errors committed, were designated. PMID:24149742
Covariance Analysis Tool (G-CAT) for Computing Ascent, Descent, and Landing Errors
NASA Technical Reports Server (NTRS)
Boussalis, Dhemetrios; Bayard, David S.
2013-01-01
G-CAT is a covariance analysis tool that enables fast and accurate computation of error ellipses for descent, landing, ascent, and rendezvous scenarios, and quantifies knowledge error contributions needed for error budgeting purposes. Because GCAT supports hardware/system trade studies in spacecraft and mission design, it is useful in both early and late mission/ proposal phases where Monte Carlo simulation capability is not mature, Monte Carlo simulation takes too long to run, and/or there is a need to perform multiple parametric system design trades that would require an unwieldy number of Monte Carlo runs. G-CAT is formulated as a variable-order square-root linearized Kalman filter (LKF), typically using over 120 filter states. An important property of G-CAT is that it is based on a 6-DOF (degrees of freedom) formulation that completely captures the combined effects of both attitude and translation errors on the propagated trajectories. This ensures its accuracy for guidance, navigation, and control (GN&C) analysis. G-CAT provides the desired fast turnaround analysis needed for error budgeting in support of mission concept formulations, design trade studies, and proposal development efforts. The main usefulness of a covariance analysis tool such as G-CAT is its ability to calculate the performance envelope directly from a single run. This is in sharp contrast to running thousands of simulations to obtain similar information using Monte Carlo methods. It does this by propagating the "statistics" of the overall design, rather than simulating individual trajectories. G-CAT supports applications to lunar, planetary, and small body missions. It characterizes onboard knowledge propagation errors associated with inertial measurement unit (IMU) errors (gyro and accelerometer), gravity errors/dispersions (spherical harmonics, masscons), and radar errors (multiple altimeter beams, multiple Doppler velocimeter beams). G-CAT is a standalone MATLAB- based tool intended to run on any engineer's desktop computer.
Learning mechanisms to limit medication administration errors.
Drach-Zahavy, Anat; Pud, Dorit
2010-04-01
This paper is a report of a study conducted to identify and test the effectiveness of learning mechanisms applied by the nursing staff of hospital wards as a means of limiting medication administration errors. Since the influential report ;To Err Is Human', research has emphasized the role of team learning in reducing medication administration errors. Nevertheless, little is known about the mechanisms underlying team learning. Thirty-two hospital wards were randomly recruited. Data were collected during 2006 in Israel by a multi-method (observations, interviews and administrative data), multi-source (head nurses, bedside nurses) approach. Medication administration error was defined as any deviation from procedures, policies and/or best practices for medication administration, and was identified using semi-structured observations of nurses administering medication. Organizational learning was measured using semi-structured interviews with head nurses, and the previous year's reported medication administration errors were assessed using administrative data. The interview data revealed four learning mechanism patterns employed in an attempt to learn from medication administration errors: integrated, non-integrated, supervisory and patchy learning. Regression analysis results demonstrated that whereas the integrated pattern of learning mechanisms was associated with decreased errors, the non-integrated pattern was associated with increased errors. Supervisory and patchy learning mechanisms were not associated with errors. Superior learning mechanisms are those that represent the whole cycle of team learning, are enacted by nurses who administer medications to patients, and emphasize a system approach to data analysis instead of analysis of individual cases.
Koprowski, Robert
2014-07-04
Dedicated, automatic algorithms for image analysis and processing are becoming more and more common in medical diagnosis. When creating dedicated algorithms, many factors must be taken into consideration. They are associated with selecting the appropriate algorithm parameters and taking into account the impact of data acquisition on the results obtained. An important feature of algorithms is the possibility of their use in other medical units by other operators. This problem, namely operator's (acquisition) impact on the results obtained from image analysis and processing, has been shown on a few examples. The analysed images were obtained from a variety of medical devices such as thermal imaging, tomography devices and those working in visible light. The objects of imaging were cellular elements, the anterior segment and fundus of the eye, postural defects and others. In total, almost 200'000 images coming from 8 different medical units were analysed. All image analysis algorithms were implemented in C and Matlab. For various algorithms and methods of medical imaging, the impact of image acquisition on the results obtained is different. There are different levels of algorithm sensitivity to changes in the parameters, for example: (1) for microscope settings and the brightness assessment of cellular elements there is a difference of 8%; (2) for the thyroid ultrasound images there is a difference in marking the thyroid lobe area which results in a brightness assessment difference of 2%. The method of image acquisition in image analysis and processing also affects: (3) the accuracy of determining the temperature in the characteristic areas on the patient's back for the thermal method - error of 31%; (4) the accuracy of finding characteristic points in photogrammetric images when evaluating postural defects - error of 11%; (5) the accuracy of performing ablative and non-ablative treatments in cosmetology - error of 18% for the nose, 10% for the cheeks, and 7% for the forehead. Similarly, when: (7) measuring the anterior eye chamber - there is an error of 20%; (8) measuring the tooth enamel thickness - error of 15%; (9) evaluating the mechanical properties of the cornea during pressure measurement - error of 47%. The paper presents vital, selected issues occurring when assessing the accuracy of designed automatic algorithms for image analysis and processing in bioengineering. The impact of acquisition of images on the problems arising in their analysis has been shown on selected examples. It has also been indicated to which elements of image analysis and processing special attention should be paid in their design.
Accuracy analysis and design of A3 parallel spindle head
NASA Astrophysics Data System (ADS)
Ni, Yanbing; Zhang, Biao; Sun, Yupeng; Zhang, Yuan
2016-03-01
As functional components of machine tools, parallel mechanisms are widely used in high efficiency machining of aviation components, and accuracy is one of the critical technical indexes. Lots of researchers have focused on the accuracy problem of parallel mechanisms, but in terms of controlling the errors and improving the accuracy in the stage of design and manufacturing, further efforts are required. Aiming at the accuracy design of a 3-DOF parallel spindle head(A3 head), its error model, sensitivity analysis and tolerance allocation are investigated. Based on the inverse kinematic analysis, the error model of A3 head is established by using the first-order perturbation theory and vector chain method. According to the mapping property of motion and constraint Jacobian matrix, the compensatable and uncompensatable error sources which affect the accuracy in the end-effector are separated. Furthermore, sensitivity analysis is performed on the uncompensatable error sources. The sensitivity probabilistic model is established and the global sensitivity index is proposed to analyze the influence of the uncompensatable error sources on the accuracy in the end-effector of the mechanism. The results show that orientation error sources have bigger effect on the accuracy in the end-effector. Based upon the sensitivity analysis results, the tolerance design is converted into the issue of nonlinearly constrained optimization with the manufacturing cost minimum being the optimization objective. By utilizing the genetic algorithm, the allocation of the tolerances on each component is finally determined. According to the tolerance allocation results, the tolerance ranges of ten kinds of geometric error sources are obtained. These research achievements can provide fundamental guidelines for component manufacturing and assembly of this kind of parallel mechanisms.
Analysis and Calibration of Sources of Electronic Error in PSD Sensor Response.
Rodríguez-Navarro, David; Lázaro-Galilea, José Luis; Bravo-Muñoz, Ignacio; Gardel-Vicente, Alfredo; Tsirigotis, Georgios
2016-04-29
In order to obtain very precise measurements of the position of agents located at a considerable distance using a sensor system based on position sensitive detectors (PSD), it is necessary to analyze and mitigate the factors that generate substantial errors in the system's response. These sources of error can be divided into electronic and geometric factors. The former stem from the nature and construction of the PSD as well as the performance, tolerances and electronic response of the system, while the latter are related to the sensor's optical system. Here, we focus solely on the electrical effects, since the study, analysis and correction of these are a prerequisite for subsequently addressing geometric errors. A simple calibration method is proposed, which considers PSD response, component tolerances, temperature variations, signal frequency used, signal to noise ratio (SNR), suboptimal operational amplifier parameters, and analog to digital converter (ADC) quantitation SNRQ, etc. Following an analysis of these effects and calibration of the sensor, it was possible to correct the errors, thus rendering the effects negligible, as reported in the results section.
Analysis and Calibration of Sources of Electronic Error in PSD Sensor Response
Rodríguez-Navarro, David; Lázaro-Galilea, José Luis; Bravo-Muñoz, Ignacio; Gardel-Vicente, Alfredo; Tsirigotis, Georgios
2016-01-01
In order to obtain very precise measurements of the position of agents located at a considerable distance using a sensor system based on position sensitive detectors (PSD), it is necessary to analyze and mitigate the factors that generate substantial errors in the system’s response. These sources of error can be divided into electronic and geometric factors. The former stem from the nature and construction of the PSD as well as the performance, tolerances and electronic response of the system, while the latter are related to the sensor’s optical system. Here, we focus solely on the electrical effects, since the study, analysis and correction of these are a prerequisite for subsequently addressing geometric errors. A simple calibration method is proposed, which considers PSD response, component tolerances, temperature variations, signal frequency used, signal to noise ratio (SNR), suboptimal operational amplifier parameters, and analog to digital converter (ADC) quantitation SNRQ, etc. Following an analysis of these effects and calibration of the sensor, it was possible to correct the errors, thus rendering the effects negligible, as reported in the results section. PMID:27136562
Oddou-Muratorio, S; Houot, M-L; Demesure-Musch, B; Austerlitz, F
2003-12-01
The joint development of polymorphic molecular markers and paternity analysis methods provides new approaches to investigate ongoing patterns of pollen flow in natural plant populations. However, paternity studies are hindered by false paternity assignment and the nondetection of true fathers. To gauge the risk of these two types of errors, we performed a simulation study to investigate the impact on paternity analysis of: (i) the assumed values for the size of the breeding male population (NBMP), and (ii) the rate of scoring error in genotype assessment. Our simulations were based on microsatellite data obtained from a natural population of the entomophilous wild service tree, Sorbus torminalis (L.) Crantz. We show that an accurate estimate of NBMP is required to minimize both types of errors, and we assess the reliability of a technique used to estimate NBMP based on parent-offspring genetic data. We then show that scoring errors in genotype assessment only slightly affect the assessment of paternity relationships, and conclude that it is generally better to neglect the scoring error rate in paternity analyses within a nonisolated population.
Analysis of operator splitting errors for near-limit flame simulations
NASA Astrophysics Data System (ADS)
Lu, Zhen; Zhou, Hua; Li, Shan; Ren, Zhuyin; Lu, Tianfeng; Law, Chung K.
2017-04-01
High-fidelity simulations of ignition, extinction and oscillatory combustion processes are of practical interest in a broad range of combustion applications. Splitting schemes, widely employed in reactive flow simulations, could fail for stiff reaction-diffusion systems exhibiting near-limit flame phenomena. The present work first employs a model perfectly stirred reactor (PSR) problem with an Arrhenius reaction term and a linear mixing term to study the effects of splitting errors on the near-limit combustion phenomena. Analysis shows that the errors induced by decoupling of the fractional steps may result in unphysical extinction or ignition. The analysis is then extended to the prediction of ignition, extinction and oscillatory combustion in unsteady PSRs of various fuel/air mixtures with a 9-species detailed mechanism for hydrogen oxidation and an 88-species skeletal mechanism for n-heptane oxidation, together with a Jacobian-based analysis for the time scales. The tested schemes include the Strang splitting, the balanced splitting, and a newly developed semi-implicit midpoint method. Results show that the semi-implicit midpoint method can accurately reproduce the dynamics of the near-limit flame phenomena and it is second-order accurate over a wide range of time step size. For the extinction and ignition processes, both the balanced splitting and midpoint method can yield accurate predictions, whereas the Strang splitting can lead to significant shifts on the ignition/extinction processes or even unphysical results. With an enriched H radical source in the inflow stream, a delay of the ignition process and the deviation on the equilibrium temperature are observed for the Strang splitting. On the contrary, the midpoint method that solves reaction and diffusion together matches the fully implicit accurate solution. The balanced splitting predicts the temperature rise correctly but with an over-predicted peak. For the sustainable and decaying oscillatory combustion from cool flames, both the Strang splitting and the midpoint method can successfully capture the dynamic behavior, whereas the balanced splitting scheme results in significant errors.
Analysis of operator splitting errors for near-limit flame simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lu, Zhen; Zhou, Hua; Li, Shan
High-fidelity simulations of ignition, extinction and oscillatory combustion processes are of practical interest in a broad range of combustion applications. Splitting schemes, widely employed in reactive flow simulations, could fail for stiff reaction–diffusion systems exhibiting near-limit flame phenomena. The present work first employs a model perfectly stirred reactor (PSR) problem with an Arrhenius reaction term and a linear mixing term to study the effects of splitting errors on the near-limit combustion phenomena. Analysis shows that the errors induced by decoupling of the fractional steps may result in unphysical extinction or ignition. The analysis is then extended to the prediction ofmore » ignition, extinction and oscillatory combustion in unsteady PSRs of various fuel/air mixtures with a 9-species detailed mechanism for hydrogen oxidation and an 88-species skeletal mechanism for n-heptane oxidation, together with a Jacobian-based analysis for the time scales. The tested schemes include the Strang splitting, the balanced splitting, and a newly developed semi-implicit midpoint method. Results show that the semi-implicit midpoint method can accurately reproduce the dynamics of the near-limit flame phenomena and it is second-order accurate over a wide range of time step size. For the extinction and ignition processes, both the balanced splitting and midpoint method can yield accurate predictions, whereas the Strang splitting can lead to significant shifts on the ignition/extinction processes or even unphysical results. With an enriched H radical source in the inflow stream, a delay of the ignition process and the deviation on the equilibrium temperature are observed for the Strang splitting. On the contrary, the midpoint method that solves reaction and diffusion together matches the fully implicit accurate solution. The balanced splitting predicts the temperature rise correctly but with an over-predicted peak. For the sustainable and decaying oscillatory combustion from cool flames, both the Strang splitting and the midpoint method can successfully capture the dynamic behavior, whereas the balanced splitting scheme results in significant errors.« less
Lu, Xinjiang; Liu, Wenbo; Zhou, Chuang; Huang, Minghui
2017-06-13
The least-squares support vector machine (LS-SVM) is a popular data-driven modeling method and has been successfully applied to a wide range of applications. However, it has some disadvantages, including being ineffective at handling non-Gaussian noise as well as being sensitive to outliers. In this paper, a robust LS-SVM method is proposed and is shown to have more reliable performance when modeling a nonlinear system under conditions where Gaussian or non-Gaussian noise is present. The construction of a new objective function allows for a reduction of the mean of the modeling error as well as the minimization of its variance, and it does not constrain the mean of the modeling error to zero. This differs from the traditional LS-SVM, which uses a worst-case scenario approach in order to minimize the modeling error and constrains the mean of the modeling error to zero. In doing so, the proposed method takes the modeling error distribution information into consideration and is thus less conservative and more robust in regards to random noise. A solving method is then developed in order to determine the optimal parameters for the proposed robust LS-SVM. An additional analysis indicates that the proposed LS-SVM gives a smaller weight to a large-error training sample and a larger weight to a small-error training sample, and is thus more robust than the traditional LS-SVM. The effectiveness of the proposed robust LS-SVM is demonstrated using both artificial and real life cases.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tateoka, K; Graduate School of Medicine, Sapporo Medical University, Sapporo, JP; Fujimomo, K
2014-06-01
Purpose: The aim of the study is to evaluate the use of Varian DynaLog files to verify VMAT plans delivery and modulation complexity score (MCS) of VMAT. Methods: Delivery accuracy of machine performance was quantified by multileaf collimator (MLC) position errors, gantry angle errors and fluence delivery accuracy for volumetric modulated arc therapy (VMAT). The relationship between machine performance and plan complexity were also investigated using the modulation complexity score (MCS). Plan and Actual MLC positions, gantry angles and delivered fraction of monitor units were extracted from Varian DynaLog files. These factors were taken from the record and verify systemmore » of MLC control file. Planned and delivered beam data were compared to determine leaf position errors and gantry angle errors. Analysis was also performed on planned and actual fluence maps reconstructed from those of the DynaLog files. This analysis was performed for all treatment fractions of 5 prostate VMAT plans. The analysis of DynaLog files have been carried out by in-house programming in Visual C++. Results: The root mean square of leaf position and gantry angle errors were about 0.12 and 0.15, respectively. The Gamma of planned and actual fluence maps at 3%/3 mm criterion was about 99.21. The gamma of the leaf position errors were not directly related to plan complexity as determined by the MCS. Therefore, the gamma of the gantry angle errors were directly related to plan complexity as determined by the MCS. Conclusion: This study shows Varian dynalog files for VMAT plan can be diagnosed delivery errors not possible with phantom based quality assurance. Furthermore, the MCS of VMAT plan can evaluate delivery accuracy for patients receiving of VMAT. Machine performance was found to be directly related to plan complexity but this is not the dominant determinant of delivery accuracy.« less
Evaluation of errors in quantitative determination of asbestos in rock
NASA Astrophysics Data System (ADS)
Baietto, Oliviero; Marini, Paola; Vitaliti, Martina
2016-04-01
The quantitative determination of the content of asbestos in rock matrices is a complex operation which is susceptible to important errors. The principal methodologies for the analysis are Scanning Electron Microscopy (SEM) and Phase Contrast Optical Microscopy (PCOM). Despite the PCOM resolution is inferior to that of SEM, PCOM analysis has several advantages, including more representativity of the analyzed sample, more effective recognition of chrysotile and a lower cost. The DIATI LAA internal methodology for the analysis in PCOM is based on a mild grinding of a rock sample, its subdivision in 5-6 grain size classes smaller than 2 mm and a subsequent microscopic analysis of a portion of each class. The PCOM is based on the optical properties of asbestos and of the liquids with note refractive index in which the particles in analysis are immersed. The error evaluation in the analysis of rock samples, contrary to the analysis of airborne filters, cannot be based on a statistical distribution. In fact for airborne filters a binomial distribution (Poisson), which theoretically defines the variation in the count of fibers resulting from the observation of analysis fields, chosen randomly on the filter, can be applied. The analysis in rock matrices instead cannot lean on any statistical distribution because the most important object of the analysis is the size of the of asbestiform fibers and bundles of fibers observed and the resulting relationship between the weights of the fibrous component compared to the one granular. The error evaluation generally provided by public and private institutions varies between 50 and 150 percent, but there are not, however, specific studies that discuss the origin of the error or that link it to the asbestos content. Our work aims to provide a reliable estimation of the error in relation to the applied methodologies and to the total content of asbestos, especially for the values close to the legal limits. The error assessments must be made through the repetition of the same analysis on the same sample to try to estimate the error on the representativeness of the sample and the error related to the sensitivity of the operator, in order to provide a sufficiently reliable uncertainty of the method. We used about 30 natural rock samples with different asbestos content, performing 3 analysis on each sample to obtain a trend sufficiently representative of the percentage. Furthermore we made on one chosen sample 10 repetition of the analysis to try to define more specifically the error of the methodology.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Butler, J.J. Jr.; Hyder, Z.
The Nguyen and Pinder method is one of four techniques commonly used for analysis of response data from slug tests. Limited field research has raised questions about the reliability of the parameter estimates obtained with this method. A theoretical evaluation of this technique reveals that errors were made in the derivation of the analytical solution upon which the technique is based. Simulation and field examples show that the errors result in parameter estimates that can differ from actual values by orders of magnitude. These findings indicate that the Nguyen and Pinder method should no longer be a tool in themore » repertoire of the field hydrogeologist. If data from a slug test performed in a partially penetrating well in a confined aquifer need to be analyzed, recent work has shown that the Hvorslev method is the best alternative among the commonly used techniques.« less
Patient safety education at Japanese medical schools: results of a nationwide survey.
Maeda, Shoichi; Kamishiraki, Etsuko; Starkey, Jay
2012-05-10
Patient safety education, including error prevention strategies and management of adverse events, has become a topic of worldwide concern. The importance of the patient safety is also recognized in Japan following two serious medical accidents in 1999. Furthermore, educational curriculum guideline revisions in 2008 by relevant the Ministry of Education includes patient safety as part of the core medical curriculum. However, little is known about the patient safety education in Japanese medical schools partly because a comprehensive study has not yet been conducted in this field. Therefore, we have conducted a nationwide survey in order to clarify the current status of patient safety education at medical schools in Japan. Response rate was 60.0% (n = 48/80). Ninety-eight-percent of respondents (n = 47/48) reported integration of patient safety education into their curricula. Thirty-nine percent reported devoting less than five hours to the topic. All schools that teach patient safety reported use of lecture based teaching methods while few used alternative methods, such as role-playing or in-hospital training. Topics related to medical error theory and legal ramifications of error are widely taught while practical topics related to error analysis such as root cause analysis are less often covered. Based on responses to our survey, most Japanese medical schools have incorporated the topic of patient safety into their curricula. However, the number of hours devoted to the patient safety education is far from the sufficient level with forty percent of medical schools that devote five hours or less to it. In addition, most medical schools employ only the lecture based learning, lacking diversity in teaching methods. Although most medical schools cover basic error theory, error analysis is taught at fewer schools. We still need to make improvements to our medical safety curricula. We believe that this study has the implications for the rest of the world as a model of what is possible and a sounding board for what topics might be important.
Error analysis on squareness of multi-sensor integrated CMM for the multistep registration method
NASA Astrophysics Data System (ADS)
Zhao, Yan; Wang, Yiwen; Ye, Xiuling; Wang, Zhong; Fu, Luhua
2018-01-01
The multistep registration(MSR) method in [1] is to register two different classes of sensors deployed on z-arm of CMM(coordinate measuring machine): a video camera and a tactile probe sensor. In general, it is difficult to obtain a very precise registration result with a single common standard, instead, this method is achieved by measuring two different standards with a constant distance between them two which are fixed on a steel plate. Although many factors have been considered such as the measuring ability of sensors, the uncertainty of the machine and the number of data pairs, there is no exact analysis on the squareness between the x-axis and the y-axis on the xy plane. For this sake, error analysis on the squareness of multi-sensor integrated CMM for the multistep registration method will be made to examine the validation of the MSR method. Synthetic experiments on the squareness on the xy plane for the simplified MSR with an inclination rotation are simulated, which will lead to a regular result. Experiments have been carried out with the multi-standard device designed also in [1], meanwhile, inspections with the help of a laser interferometer on the xy plane have been carried out. The final results are conformed to the simulations, and the squareness errors of the MSR method are also similar to the results of interferometer. In other word, the MSR can also adopted/utilized to verify the squareness of a CMM.
Multi-reader ROC studies with split-plot designs: a comparison of statistical methods.
Obuchowski, Nancy A; Gallas, Brandon D; Hillis, Stephen L
2012-12-01
Multireader imaging trials often use a factorial design, in which study patients undergo testing with all imaging modalities and readers interpret the results of all tests for all patients. A drawback of this design is the large number of interpretations required of each reader. Split-plot designs have been proposed as an alternative, in which one or a subset of readers interprets all images of a sample of patients, while other readers interpret the images of other samples of patients. In this paper, the authors compare three methods of analysis for the split-plot design. Three statistical methods are presented: the Obuchowski-Rockette method modified for the split-plot design, a newly proposed marginal-mean analysis-of-variance approach, and an extension of the three-sample U-statistic method. A simulation study using the Roe-Metz model was performed to compare the type I error rate, power, and confidence interval coverage of the three test statistics. The type I error rates for all three methods are close to the nominal level but tend to be slightly conservative. The statistical power is nearly identical for the three methods. The coverage of 95% confidence intervals falls close to the nominal coverage for small and large sample sizes. The split-plot multireader, multicase study design can be statistically efficient compared to the factorial design, reducing the number of interpretations required per reader. Three methods of analysis, shown to have nominal type I error rates, similar power, and nominal confidence interval coverage, are available for this study design. Copyright © 2012 AUR. All rights reserved.
Mobility and Position Error Analysis of a Complex Planar Mechanism with Redundant Constraints
NASA Astrophysics Data System (ADS)
Sun, Qipeng; Li, Gangyan
2018-03-01
Nowadays mechanisms with redundant constraints have been created and attracted much attention for their merits. The mechanism of the redundant constraints in a mechanical system is analyzed in this paper. A analysis method of Planar Linkage with a repetitive structure is proposed to get the number and type of constraints. According to the difference of applications and constraint characteristics, the redundant constraints are divided into the theoretical planar redundant constraints and the space-planar redundant constraints. And the calculation formula for the number of redundant constraints and type of judging method are carried out. And a complex mechanism with redundant constraints is analyzed of the influence about redundant constraints on mechanical performance. With the combination of theoretical derivation and simulation research, a mechanism analysis method is put forward about the position error of complex mechanism with redundant constraints. It points out the direction on how to eliminate or reduce the influence of redundant constraints.
Intra-rater reliability of hallux flexor strength measures using the Nintendo Wii Balance Board.
Quek, June; Treleaven, Julia; Brauer, Sandra G; O'Leary, Shaun; Clark, Ross A
2015-01-01
The purpose of this study was to investigate the intra-rater reliability of a new method in combination with the Nintendo Wii Balance Board (NWBB) to measure the strength of hallux flexor muscle. Thirty healthy individuals (age: 34.9 ± 12.9 years, height: 170.4 ± 10.5 cm, weight: 69.3 ± 15.3 kg, female = 15) participated. Repeated testing was completed within 7 days. Participants performed strength testing in sitting using a wooden platform in combination with the NWBB. This new method was set up to selectively recruit an intrinsic muscle of the foot, specifically the flexor hallucis brevis muscle. Statistical analysis was performed using intra-class coefficients and ordinary least product analysis. To estimate measurement error, standard error of measurement (SEM), minimal detectable change (MDC) and percentage error were calculated. Results indicate excellent intra-rater reliability (ICC = 0.982, CI = 0.96-0.99) with an absence of systematic bias. SEM, MDC and percentage error value were 0.5, 1.4 and 12 % respectively. This study demonstrates that a new method in combination with the NWBB application is reliable to measure hallux flexor strength and has potential to be used for future research and clinical application.
Kirkendall, D T; Grogan, J W; Bowers, R G
1991-01-01
Body composition and appropriate playing weight are frequently requested by coaches. Numerous methods for estimating these figures are available, and each has its own limitation, be it technical or biological. A comparison of three common methods was made-underwater weighting (H2O, the criterion), skinfold thicknesses (SF), and commercial bioelectrical impedance analysis (BIA). Subjects were 29 professional football players measured by each of the three methods after an overnight fast. Data was collected 10 weeks preceding the players' formal training camp. There was no difference for percentage of weight as fat between SF (15.8%) and H2O (14.2%). Bioelectrical impedance analysis significantly (p < .05) overestimated percent fat (19.2%) compared to H20. Error rates when regressing SF on H2O were favorable, whether expressed for the whole sample (3.04%) or by race (1.78% or 3.56% for whites and blacks, respectively). Regression of BIA on H2O showed an elevated, overall error rate (14.12%) and elevated error rates for whites (11.57%) and blacks (13.81%). Of the two estimates of body composition on a racially mixed sample of males, SF provided the best estimate with the least amount of error. J Orthop Sports Phys Ther 1991;13(5):235-239.
Dehghan, Ashraf; Abumasoudi, Rouhollah Sheikh; Ehsanpour, Soheila
2016-01-01
Infertility and errors in the process of its treatment have a negative impact on infertile couples. The present study was aimed to identify and assess the common errors in the reception process by applying the approach of "failure modes and effects analysis" (FMEA). In this descriptive cross-sectional study, the admission process of fertility and infertility center of Isfahan was selected for evaluation of its errors based on the team members' decision. At first, the admission process was charted through observations and interviewing employees, holding multiple panels, and using FMEA worksheet, which has been used in many researches all over the world and also in Iran. Its validity was evaluated through content and face validity, and its reliability was evaluated through reviewing and confirmation of the obtained information by the FMEA team, and eventually possible errors, causes, and three indicators of severity of effect, probability of occurrence, and probability of detection were determined and corrective actions were proposed. Data analysis was determined by the number of risk priority (RPN) which is calculated by multiplying the severity of effect, probability of occurrence, and probability of detection. Twenty-five errors with RPN ≥ 125 was detected through the admission process, in which six cases of error had high priority in terms of severity and occurrence probability and were identified as high-risk errors. The team-oriented method of FMEA could be useful for assessment of errors and also to reduce the occurrence probability of errors.
Fast online generalized multiscale finite element method using constraint energy minimization
NASA Astrophysics Data System (ADS)
Chung, Eric T.; Efendiev, Yalchin; Leung, Wing Tat
2018-02-01
Local multiscale methods often construct multiscale basis functions in the offline stage without taking into account input parameters, such as source terms, boundary conditions, and so on. These basis functions are then used in the online stage with a specific input parameter to solve the global problem at a reduced computational cost. Recently, online approaches have been introduced, where multiscale basis functions are adaptively constructed in some regions to reduce the error significantly. In multiscale methods, it is desired to have only 1-2 iterations to reduce the error to a desired threshold. Using Generalized Multiscale Finite Element Framework [10], it was shown that by choosing sufficient number of offline basis functions, the error reduction can be made independent of physical parameters, such as scales and contrast. In this paper, our goal is to improve this. Using our recently proposed approach [4] and special online basis construction in oversampled regions, we show that the error reduction can be made sufficiently large by appropriately selecting oversampling regions. Our numerical results show that one can achieve a three order of magnitude error reduction, which is better than our previous methods. We also develop an adaptive algorithm and enrich in selected regions with large residuals. In our adaptive method, we show that the convergence rate can be determined by a user-defined parameter and we confirm this by numerical simulations. The analysis of the method is presented.
Roland, Michelle; Hull, M L; Howell, S M
2011-05-01
In a previous paper, we reported the virtual axis finder, which is a new method for finding the rotational axes of the knee. The virtual axis finder was validated through simulations that were subject to limitations. Hence, the objective of the present study was to perform a mechanical validation with two measurement modalities: 3D video-based motion analysis and marker-based roentgen stereophotogrammetric analysis (RSA). A two rotational axis mechanism was developed, which simulated internal-external (or longitudinal) and flexion-extension (FE) rotations. The actual axes of rotation were known with respect to motion analysis and RSA markers within ± 0.0006 deg and ± 0.036 mm and ± 0.0001 deg and ± 0.016 mm, respectively. The orientation and position root mean squared errors for identifying the longitudinal rotation (LR) and FE axes with video-based motion analysis (0.26 deg, 0.28 m, 0.36 deg, and 0.25 mm, respectively) were smaller than with RSA (1.04 deg, 0.84 mm, 0.82 deg, and 0.32 mm, respectively). The random error or precision in the orientation and position was significantly better (p=0.01 and p=0.02, respectively) in identifying the LR axis with video-based motion analysis (0.23 deg and 0.24 mm) than with RSA (0.95 deg and 0.76 mm). There was no significant difference in the bias errors between measurement modalities. In comparing the mechanical validations to virtual validations, the virtual validations produced comparable errors to those of the mechanical validation. The only significant difference between the errors of the mechanical and virtual validations was the precision in the position of the LR axis while simulating video-based motion analysis (0.24 mm and 0.78 mm, p=0.019). These results indicate that video-based motion analysis with the equipment used in this study is the superior measurement modality for use with the virtual axis finder but both measurement modalities produce satisfactory results. The lack of significant differences between validation techniques suggests that the virtual sensitivity analysis previously performed was appropriately modeled. Thus, the virtual axis finder can be applied with a thorough understanding of its errors in a variety of test conditions.
Measuring quality in anatomic pathology.
Raab, Stephen S; Grzybicki, Dana Marie
2008-06-01
This article focuses mainly on diagnostic accuracy in measuring quality in anatomic pathology, noting that measuring any quality metric is complex and demanding. The authors discuss standardization and its variability within and across areas of care delivery and efforts involving defining and measuring error to achieve pathology quality and patient safety. They propose that data linking error to patient outcome are critical for developing quality improvement initiatives targeting errors that cause patient harm in addition to using methods of root cause analysis, beyond those traditionally used in cytologic-histologic correlation, to assist in the development of error reduction and quality improvement plans.
Peleato, Nicolás M; Andrews, Robert C
2015-01-01
This work investigated the application of several fluorescence excitation-emission matrix analysis methods as natural organic matter (NOM) indicators for use in predicting the formation of trihalomethanes (THMs) and haloacetic acids (HAAs). Waters from four different sources (two rivers and two lakes) were subjected to jar testing followed by 24hr disinfection by-product formation tests using chlorine. NOM was quantified using three common measures: dissolved organic carbon, ultraviolet absorbance at 254 nm, and specific ultraviolet absorbance as well as by principal component analysis, peak picking, and parallel factor analysis of fluorescence spectra. Based on multi-linear modeling of THMs and HAAs, principle component (PC) scores resulted in the lowest mean squared prediction error of cross-folded test sets (THMs: 43.7 (μg/L)(2), HAAs: 233.3 (μg/L)(2)). Inclusion of principle components representative of protein-like material significantly decreased prediction error for both THMs and HAAs. Parallel factor analysis did not identify a protein-like component and resulted in prediction errors similar to traditional NOM surrogates as well as fluorescence peak picking. These results support the value of fluorescence excitation-emission matrix-principal component analysis as a suitable NOM indicator in predicting the formation of THMs and HAAs for the water sources studied. Copyright © 2014. Published by Elsevier B.V.
Repeat-aware modeling and correction of short read errors.
Yang, Xiao; Aluru, Srinivas; Dorman, Karin S
2011-02-15
High-throughput short read sequencing is revolutionizing genomics and systems biology research by enabling cost-effective deep coverage sequencing of genomes and transcriptomes. Error detection and correction are crucial to many short read sequencing applications including de novo genome sequencing, genome resequencing, and digital gene expression analysis. Short read error detection is typically carried out by counting the observed frequencies of kmers in reads and validating those with frequencies exceeding a threshold. In case of genomes with high repeat content, an erroneous kmer may be frequently observed if it has few nucleotide differences with valid kmers with multiple occurrences in the genome. Error detection and correction were mostly applied to genomes with low repeat content and this remains a challenging problem for genomes with high repeat content. We develop a statistical model and a computational method for error detection and correction in the presence of genomic repeats. We propose a method to infer genomic frequencies of kmers from their observed frequencies by analyzing the misread relationships among observed kmers. We also propose a method to estimate the threshold useful for validating kmers whose estimated genomic frequency exceeds the threshold. We demonstrate that superior error detection is achieved using these methods. Furthermore, we break away from the common assumption of uniformly distributed errors within a read, and provide a framework to model position-dependent error occurrence frequencies common to many short read platforms. Lastly, we achieve better error correction in genomes with high repeat content. The software is implemented in C++ and is freely available under GNU GPL3 license and Boost Software V1.0 license at "http://aluru-sun.ece.iastate.edu/doku.php?id = redeem". We introduce a statistical framework to model sequencing errors in next-generation reads, which led to promising results in detecting and correcting errors for genomes with high repeat content.
Exponential error reduction in pretransfusion testing with automation.
South, Susan F; Casina, Tony S; Li, Lily
2012-08-01
Protecting the safety of blood transfusion is the top priority of transfusion service laboratories. Pretransfusion testing is a critical element of the entire transfusion process to enhance vein-to-vein safety. Human error associated with manual pretransfusion testing is a cause of transfusion-related mortality and morbidity and most human errors can be eliminated by automated systems. However, the uptake of automation in transfusion services has been slow and many transfusion service laboratories around the world still use manual blood group and antibody screen (G&S) methods. The goal of this study was to compare error potentials of commonly used manual (e.g., tiles and tubes) versus automated (e.g., ID-GelStation and AutoVue Innova) G&S methods. Routine G&S processes in seven transfusion service laboratories (four with manual and three with automated G&S methods) were analyzed using failure modes and effects analysis to evaluate the corresponding error potentials of each method. Manual methods contained a higher number of process steps ranging from 22 to 39, while automated G&S methods only contained six to eight steps. Corresponding to the number of the process steps that required human interactions, the risk priority number (RPN) of the manual methods ranged from 5304 to 10,976. In contrast, the RPN of the automated methods was between 129 and 436 and also demonstrated a 90% to 98% reduction of the defect opportunities in routine G&S testing. This study provided quantitative evidence on how automation could transform pretransfusion testing processes by dramatically reducing error potentials and thus would improve the safety of blood transfusion. © 2012 American Association of Blood Banks.
Image processing and analysis using neural networks for optometry area
NASA Astrophysics Data System (ADS)
Netto, Antonio V.; Ferreira de Oliveira, Maria C.
2002-11-01
In this work we describe the framework of a functional system for processing and analyzing images of the human eye acquired by the Hartmann-Shack technique (HS), in order to extract information to formulate a diagnosis of eye refractive errors (astigmatism, hypermetropia and myopia). The analysis is to be carried out using an Artificial Intelligence system based on Neural Nets, Fuzzy Logic and Classifier Combination. The major goal is to establish the basis of a new technology to effectively measure ocular refractive errors that is based on methods alternative those adopted in current patented systems. Moreover, analysis of images acquired with the Hartmann-Shack technique may enable the extraction of additional information on the health of an eye under exam from the same image used to detect refraction errors.
De-biasing the dynamic mode decomposition for applied Koopman spectral analysis of noisy datasets
NASA Astrophysics Data System (ADS)
Hemati, Maziar S.; Rowley, Clarence W.; Deem, Eric A.; Cattafesta, Louis N.
2017-08-01
The dynamic mode decomposition (DMD)—a popular method for performing data-driven Koopman spectral analysis—has gained increased popularity for extracting dynamically meaningful spatiotemporal descriptions of fluid flows from snapshot measurements. Often times, DMD descriptions can be used for predictive purposes as well, which enables informed decision-making based on DMD model forecasts. Despite its widespread use and utility, DMD can fail to yield accurate dynamical descriptions when the measured snapshot data are imprecise due to, e.g., sensor noise. Here, we express DMD as a two-stage algorithm in order to isolate a source of systematic error. We show that DMD's first stage, a subspace projection step, systematically introduces bias errors by processing snapshots asymmetrically. To remove this systematic error, we propose utilizing an augmented snapshot matrix in a subspace projection step, as in problems of total least-squares, in order to account for the error present in all snapshots. The resulting unbiased and noise-aware total DMD (TDMD) formulation reduces to standard DMD in the absence of snapshot errors, while the two-stage perspective generalizes the de-biasing framework to other related methods as well. TDMD's performance is demonstrated in numerical and experimental fluids examples. In particular, in the analysis of time-resolved particle image velocimetry data for a separated flow, TDMD outperforms standard DMD by providing dynamical interpretations that are consistent with alternative analysis techniques. Further, TDMD extracts modes that reveal detailed spatial structures missed by standard DMD.
NASA Technical Reports Server (NTRS)
Keppenne, Christian L.; Rienecker, Michele M.; Kovach, Robin M.; Vernieres, Guillaume; Koster, Randal D. (Editor)
2014-01-01
An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory. SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.
NASA Technical Reports Server (NTRS)
Keppenne, Christian L.; Rienecker, Michele; Kovach, Robin M.; Vernieres, Guillaume
2014-01-01
An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory.SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.
NASA Astrophysics Data System (ADS)
Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping
2016-05-01
An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (τ), effective radius (reff), and cloud top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary data sets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.
Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping
2016-05-27
An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness ( τ ), effective radius ( r eff ), and cloud-top height ( h ). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.
Makeyev, Oleksandr; Joe, Cody; Lee, Colin; Besio, Walter G
2017-07-01
Concentric ring electrodes have shown promise in non-invasive electrophysiological measurement demonstrating their superiority to conventional disc electrodes, in particular, in accuracy of Laplacian estimation. Recently, we have proposed novel variable inter-ring distances concentric ring electrodes. Analytic and finite element method modeling results for linearly increasing distances electrode configurations suggested they may decrease the truncation error resulting in more accurate Laplacian estimates compared to currently used constant inter-ring distances configurations. This study assesses statistical significance of Laplacian estimation accuracy improvement due to novel variable inter-ring distances concentric ring electrodes. Full factorial design of analysis of variance was used with one categorical and two numerical factors: the inter-ring distances, the electrode diameter, and the number of concentric rings in the electrode. The response variables were the Relative Error and the Maximum Error of Laplacian estimation computed using a finite element method model for each of the combinations of levels of three factors. Effects of the main factors and their interactions on Relative Error and Maximum Error were assessed and the obtained results suggest that all three factors have statistically significant effects in the model confirming the potential of using inter-ring distances as a means of improving accuracy of Laplacian estimation.
NASA Astrophysics Data System (ADS)
Zong, Yali; Hu, Naigang; Duan, Baoyan; Yang, Guigeng; Cao, Hongjun; Xu, Wanye
2016-03-01
Inevitable manufacturing errors and inconsistency between assumed and actual boundary conditions can affect the shape precision and cable tensions of a cable-network antenna, and even result in failure of the structure in service. In this paper, an analytical sensitivity analysis method of the shape precision and cable tensions with respect to the parameters carrying uncertainty was studied. Based on the sensitivity analysis, an optimal design procedure was proposed to alleviate the effects of the parameters that carry uncertainty. The validity of the calculated sensitivities is examined by those computed by a finite difference method. Comparison with a traditional design method shows that the presented design procedure can remarkably reduce the influence of the uncertainties on the antenna performance. Moreover, the results suggest that especially slender front net cables, thick tension ties, relatively slender boundary cables and high tension level can improve the ability of cable-network antenna structures to resist the effects of the uncertainties on the antenna performance.
Kurrant, Douglas; Fear, Elise; Baran, Anastasia; LoVetri, Joe
2017-12-01
The authors have developed a method to combine a patient-specific map of tissue structure and average dielectric properties with microwave tomography. The patient-specific map is acquired with radar-based techniques and serves as prior information for microwave tomography. The impact that the degree of structural detail included in this prior information has on image quality was reported in a previous investigation. The aim of the present study is to extend this previous work by identifying and quantifying the impact that errors in the prior information have on image quality, including the reconstruction of internal structures and lesions embedded in fibroglandular tissue. This study also extends the work of others reported in literature by emulating a clinical setting with a set of experiments that incorporate heterogeneity into both the breast interior and glandular region, as well as prior information related to both fat and glandular structures. Patient-specific structural information is acquired using radar-based methods that form a regional map of the breast. Errors are introduced to create a discrepancy in the geometry and electrical properties between the regional map and the model used to generate the data. This permits the impact that errors in the prior information have on image quality to be evaluated. Image quality is quantitatively assessed by measuring the ability of the algorithm to reconstruct both internal structures and lesions embedded in fibroglandular tissue. The study is conducted using both 2D and 3D numerical breast models constructed from MRI scans. The reconstruction results demonstrate robustness of the method relative to errors in the dielectric properties of the background regional map, and to misalignment errors. These errors do not significantly influence the reconstruction accuracy of the underlying structures, or the ability of the algorithm to reconstruct malignant tissue. Although misalignment errors do not significantly impact the quality of the reconstructed fat and glandular structures for the 3D scenarios, the dielectric properties are reconstructed less accurately within the glandular structure for these cases relative to the 2D cases. However, general agreement between the 2D and 3D results was found. A key contribution of this paper is the detailed analysis of the impact of prior information errors on the reconstruction accuracy and ability to detect tumors. The results support the utility of acquiring patient-specific information with radar-based techniques and incorporating this information into MWT. The method is robust to errors in the dielectric properties of the background regional map, and to misalignment errors. Completion of this analysis is an important step toward developing the method into a practical diagnostic tool. © 2017 American Association of Physicists in Medicine.
Array coding for large data memories
NASA Technical Reports Server (NTRS)
Tranter, W. H.
1982-01-01
It is pointed out that an array code is a convenient method for storing large quantities of data. In a typical application, the array consists of N data words having M symbols in each word. The probability of undetected error is considered, taking into account three symbol error probabilities which are of interest, and a formula for determining the probability of undetected error. Attention is given to the possibility of reading data into the array using a digital communication system with symbol error probability p. Two different schemes are found to be of interest. The conducted analysis of array coding shows that the probability of undetected error is very small even for relatively large arrays.
National suicide rates a century after Durkheim: do we know enough to estimate error?
Claassen, Cynthia A; Yip, Paul S; Corcoran, Paul; Bossarte, Robert M; Lawrence, Bruce A; Currier, Glenn W
2010-06-01
Durkheim's nineteenth-century analysis of national suicide rates dismissed prior concerns about mortality data fidelity. Over the intervening century, however, evidence documenting various types of error in suicide data has only mounted, and surprising levels of such error continue to be routinely uncovered. Yet the annual suicide rate remains the most widely used population-level suicide metric today. After reviewing the unique sources of bias incurred during stages of suicide data collection and concatenation, we propose a model designed to uniformly estimate error in future studies. A standardized method of error estimation uniformly applied to mortality data could produce data capable of promoting high quality analyses of cross-national research questions.
Precision analysis of autonomous orbit determination using star sensor for Beidou MEO satellite
NASA Astrophysics Data System (ADS)
Shang, Lin; Chang, Jiachao; Zhang, Jun; Li, Guotong
2018-04-01
This paper focuses on the autonomous orbit determination accuracy of Beidou MEO satellite using the onboard observations of the star sensors and infrared horizon sensor. A polynomial fitting method is proposed to calibrate the periodic error in the observation of the infrared horizon sensor, which will greatly influence the accuracy of autonomous orbit determination. Test results show that the periodic error can be eliminated using the polynomial fitting method. The User Range Error (URE) of Beidou MEO satellite is less than 2 km using the observations of the star sensors and infrared horizon sensor for autonomous orbit determination. The error of the Right Ascension of Ascending Node (RAAN) is less than 60 μrad and the observations of star sensors can be used as a spatial basis for Beidou MEO navigation constellation.
Rocketdyne automated dynamics data analysis and management system
NASA Technical Reports Server (NTRS)
Tarn, Robert B.
1988-01-01
An automated dynamics data analysis and management systems implemented on a DEC VAX minicomputer cluster is described. Multichannel acquisition, Fast Fourier Transformation analysis, and an online database have significantly improved the analysis of wideband transducer responses from Space Shuttle Main Engine testing. Leakage error correction to recover sinusoid amplitudes and correct for frequency slewing is described. The phase errors caused by FM recorder/playback head misalignment are automatically measured and used to correct the data. Data compression methods are described and compared. The system hardware is described. Applications using the data base are introduced, including software for power spectral density, instantaneous time history, amplitude histogram, fatigue analysis, and rotordynamics expert system analysis.
On the Discriminant Analysis in the 2-Populations Case
NASA Astrophysics Data System (ADS)
Rublík, František
2008-01-01
The empirical Bayes Gaussian rule, which in the normal case yields good values of the probability of total error, may yield high values of the maximum probability error. From this point of view the presented modified version of the classification rule of Broffitt, Randles and Hogg appears to be superior. The modification included in this paper is termed as a WR method, and the choice of its weights is discussed. The mentioned methods are also compared with the K nearest neighbours classification rule.
Uncertainties in predicting solar panel power output
NASA Technical Reports Server (NTRS)
Anspaugh, B.
1974-01-01
The problem of calculating solar panel power output at launch and during a space mission is considered. The major sources of uncertainty and error in predicting the post launch electrical performance of the panel are considered. A general discussion of error analysis is given. Examples of uncertainty calculations are included. A general method of calculating the effect on the panel of various degrading environments is presented, with references supplied for specific methods. A technique for sizing a solar panel for a required mission power profile is developed.
NASA Astrophysics Data System (ADS)
yu, Zhang; hui, Li; guibo, Bao; wuyu, Zhang; ningshan, Jiang; xiaoyun, Yang
2018-05-01
The collapsibility test in field may have huge error with computed results[1-4]. The writer gave a compare between single-line and double-line method and then compared with the field’s result. The writer’s purpose is to reduce the error of measured value to computed value and propose a way to decrease the error through consider the matric suction’s influence to unsaturated soil in using finite element analysis, field test was completed to verify the reasonability of this method and get some regulate of development of collapse deformation and supply some calculation basis of engineering design and forecast in emergency situation.
Human factors process failure modes and effects analysis (HF PFMEA) software tool
NASA Technical Reports Server (NTRS)
Chandler, Faith T. (Inventor); Relvini, Kristine M. (Inventor); Shedd, Nathaneal P. (Inventor); Valentino, William D. (Inventor); Philippart, Monica F. (Inventor); Bessette, Colette I. (Inventor)
2011-01-01
Methods, computer-readable media, and systems for automatically performing Human Factors Process Failure Modes and Effects Analysis for a process are provided. At least one task involved in a process is identified, where the task includes at least one human activity. The human activity is described using at least one verb. A human error potentially resulting from the human activity is automatically identified, the human error is related to the verb used in describing the task. A likelihood of occurrence, detection, and correction of the human error is identified. The severity of the effect of the human error is identified. The likelihood of occurrence, and the severity of the risk of potential harm is identified. The risk of potential harm is compared with a risk threshold to identify the appropriateness of corrective measures.
Webster, Joshua D; Michalowski, Aleksandra M; Dwyer, Jennifer E; Corps, Kara N; Wei, Bih-Rong; Juopperi, Tarja; Hoover, Shelley B; Simpson, R Mark
2012-01-01
The extent to which histopathology pattern recognition image analysis (PRIA) agrees with microscopic assessment has not been established. Thus, a commercial PRIA platform was evaluated in two applications using whole-slide images. Substantial agreement, lacking significant constant or proportional errors, between PRIA and manual morphometric image segmentation was obtained for pulmonary metastatic cancer areas (Passing/Bablok regression). Bland-Altman analysis indicated heteroscedastic measurements and tendency toward increasing variance with increasing tumor burden, but no significant trend in mean bias. The average between-methods percent tumor content difference was -0.64. Analysis of between-methods measurement differences relative to the percent tumor magnitude revealed that method disagreement had an impact primarily in the smallest measurements (tumor burden <3%). Regression-based 95% limits of agreement indicated substantial agreement for method interchangeability. Repeated measures revealed concordance correlation of >0.988, indicating high reproducibility for both methods, yet PRIA reproducibility was superior (C.V.: PRIA = 7.4, manual = 17.1). Evaluation of PRIA on morphologically complex teratomas led to diagnostic agreement with pathologist assessments of pluripotency on subsets of teratomas. Accommodation of the diversity of teratoma histologic features frequently resulted in detrimental trade-offs, increasing PRIA error elsewhere in images. PRIA error was nonrandom and influenced by variations in histomorphology. File-size limitations encountered while training algorithms and consequences of spectral image processing dominance contributed to diagnostic inaccuracies experienced for some teratomas. PRIA appeared better suited for tissues with limited phenotypic diversity. Technical improvements may enhance diagnostic agreement, and consistent pathologist input will benefit further development and application of PRIA.
NASA Astrophysics Data System (ADS)
Shinoda, Masahisa; Nakatani, Hidehiko; Nakai, Kenya; Ohmaki, Masayuki
2015-09-01
We theoretically calculate behaviors of focusing error signals generated by an astigmatic method in a land-groove-type optical disk. The focusing error signal from the land does not coincide with that from the groove. This behavior is enhanced when a focused spot of an optical pickup moves beyond the radius of the optical disk. A gain difference between the slope sensitivities of focusing error signals from the land and the groove is an important factor with respect to stable focusing servo control. In our calculation, the format of digital versatile disc-random access memory (DVD-RAM) is adopted as the land-groove-type optical disk model, and the dependences of the gain difference on various factors are investigated. The gain difference strongly depends on the optical intensity distribution of the laser beam in the optical pickup. The calculation method and results in this paper will be reflected in newly developed land-groove-type optical disks.
NASA Technical Reports Server (NTRS)
Diak, George R.; Stewart, Tod R.
1989-01-01
A method is presented for evaluating the fluxes of sensible and latent heating at the land surface, using satellite-measured surface temperature changes in a composite surface layer-mixed layer representation of the planetary boundary layer. The basic prognostic model is tested by comparison with synoptic station information at sites where surface evaporation climatology is well known. The remote sensing version of the model, using satellite-measured surface temperature changes, is then used to quantify the sharp spatial gradient in surface heating/evaporation across the central United States. An error analysis indicates that perhaps five levels of evaporation are recognizable by these methods and that the chief cause of error is the interaction of errors in the measurement of surface temperature change with errors in the assigment of surface roughness character. Finally, two new potential methods for remote sensing of the land-surface energy balance are suggested which will relay on space-borne instrumentation planned for the 1990s.
Guelpa, Anina; Bevilacqua, Marta; Marini, Federico; O'Kennedy, Kim; Geladi, Paul; Manley, Marena
2015-04-15
It has been established in this study that the Rapid Visco Analyser (RVA) can describe maize hardness, irrespective of the RVA profile, when used in association with appropriate multivariate data analysis techniques. Therefore, the RVA can complement or replace current and/or conventional methods as a hardness descriptor. Hardness modelling based on RVA viscograms was carried out using seven conventional hardness methods (hectoliter mass (HLM), hundred kernel mass (HKM), particle size index (PSI), percentage vitreous endosperm (%VE), protein content, percentage chop (%chop) and near infrared (NIR) spectroscopy) as references and three different RVA profiles (hard, soft and standard) as predictors. An approach using locally weighted partial least squares (LW-PLS) was followed to build the regression models. The resulted prediction errors (root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP)) for the quantification of hardness values were always lower or in the same order of the laboratory error of the reference method. Copyright © 2014 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Utegulov, B. B.
2018-02-01
In the work the study of the developed method was carried out for reliability by analyzing the error in indirect determination of the insulation parameters in an asymmetric network with an isolated neutral voltage above 1000 V. The conducted studies of the random relative mean square errors show that the accuracy of indirect measurements in the developed method can be effectively regulated not only by selecting a capacitive additional conductivity, which are connected between phases of the electrical network and the ground, but also by the selection of measuring instruments according to the accuracy class. When choosing meters with accuracy class of 0.5 with the correct selection of capacitive additional conductivity that are connected between the phases of the electrical network and the ground, the errors in measuring the insulation parameters will not exceed 10%.
Error in geometric morphometric data collection: Combining data from multiple sources.
Robinson, Chris; Terhune, Claire E
2017-09-01
This study compares two- and three-dimensional morphometric data to determine the extent to which intra- and interobserver and intermethod error influence the outcomes of statistical analyses. Data were collected five times for each method and observer on 14 anthropoid crania using calipers, a MicroScribe, and 3D models created from NextEngine and microCT scans. ANOVA models were used to examine variance in the linear data at the level of genus, species, specimen, observer, method, and trial. Three-dimensional data were analyzed using geometric morphometric methods; principal components analysis was employed to examine how trials of all specimens were distributed in morphospace and Procrustes distances among trials were calculated and used to generate UPGMA trees to explore whether all trials of the same individual grouped together regardless of observer or method. Most variance in the linear data was at the genus level, with greater variance at the observer than method levels. In the 3D data, interobserver and intermethod error were similar to intraspecific distances among Callicebus cupreus individuals, with interobserver error being higher than intermethod error. Generally, taxa separate well in morphospace, with different trials of the same specimen typically grouping together. However, trials of individuals in the same species overlapped substantially with one another. Researchers should be cautious when compiling data from multiple methods and/or observers, especially if analyses are focused on intraspecific variation or closely related species, as in these cases, patterns among individuals may be obscured by interobserver and intermethod error. Conducting interobserver and intermethod reliability assessments prior to the collection of data is recommended. © 2017 Wiley Periodicals, Inc.
Pan, Hong-Wei; Li, Wei; Li, Rong-Guo; Li, Yong; Zhang, Yi; Sun, En-Hua
2018-01-01
Rapid identification and determination of the antibiotic susceptibility profiles of the infectious agents in patients with bloodstream infections are critical steps in choosing an effective targeted antibiotic for treatment. However, there has been minimal effort focused on developing combined methods for the simultaneous direct identification and antibiotic susceptibility determination of bacteria in positive blood cultures. In this study, we constructed a lysis-centrifugation-wash procedure to prepare a bacterial pellet from positive blood cultures, which can be used directly for identification by matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) and antibiotic susceptibility testing by the Vitek 2 system. The method was evaluated using a total of 129 clinical bacteria-positive blood cultures. The whole sample preparation process could be completed in <15 min. The correct rate of direct MALDI-TOF MS identification was 96.49% for gram-negative bacteria and 97.22% for gram-positive bacteria. Vitek 2 antimicrobial susceptibility testing of gram-negative bacteria showed an agreement rate of antimicrobial categories of 96.89% with a minor error, major error, and very major error rate of 2.63, 0.24, and 0.24%, respectively. Category agreement of antimicrobials against gram-positive bacteria was 92.81%, with a minor error, major error, and very major error rate of 4.51, 1.22, and 1.46%, respectively. These results indicated that our direct antibiotic susceptibility analysis method worked well compared to the conventional culture-dependent laboratory method. Overall, this fast, easy, and accurate method can facilitate the direct identification and antibiotic susceptibility testing of bacteria in positive blood cultures.
NASA Astrophysics Data System (ADS)
Yehia, Ali M.; Mohamed, Heba M.
2016-01-01
Three advanced chemmometric-assisted spectrophotometric methods namely; Concentration Residuals Augmented Classical Least Squares (CRACLS), Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) and Principal Component Analysis-Artificial Neural Networks (PCA-ANN) were developed, validated and benchmarked to PLS calibration; to resolve the severely overlapped spectra and simultaneously determine; Paracetamol (PAR), Guaifenesin (GUA) and Phenylephrine (PHE) in their ternary mixture and in presence of p-aminophenol (AP) the main degradation product and synthesis impurity of Paracetamol. The analytical performance of the proposed methods was described by percentage recoveries, root mean square error of calibration and standard error of prediction. The four multivariate calibration methods could be directly used without any preliminary separation step and successfully applied for pharmaceutical formulation analysis, showing no excipients' interference.
Noise removing in encrypted color images by statistical analysis
NASA Astrophysics Data System (ADS)
Islam, N.; Puech, W.
2012-03-01
Cryptographic techniques are used to secure confidential data from unauthorized access but these techniques are very sensitive to noise. A single bit change in encrypted data can have catastrophic impact over the decrypted data. This paper addresses the problem of removing bit error in visual data which are encrypted using AES algorithm in the CBC mode. In order to remove the noise, a method is proposed which is based on the statistical analysis of each block during the decryption. The proposed method exploits local statistics of the visual data and confusion/diffusion properties of the encryption algorithm to remove the errors. Experimental results show that the proposed method can be used at the receiving end for the possible solution for noise removing in visual data in encrypted domain.
Optoelectronic scanning system upgrade by energy center localization methods
NASA Astrophysics Data System (ADS)
Flores-Fuentes, W.; Sergiyenko, O.; Rodriguez-Quiñonez, J. C.; Rivas-López, M.; Hernández-Balbuena, D.; Básaca-Preciado, L. C.; Lindner, L.; González-Navarro, F. F.
2016-11-01
A problem of upgrading an optoelectronic scanning system with digital post-processing of the signal based on adequate methods of energy center localization is considered. An improved dynamic triangulation analysis technique is proposed by an example of industrial infrastructure damage detection. A modification of our previously published method aimed at searching for the energy center of an optoelectronic signal is described. Application of the artificial intelligence algorithm of compensation for the error of determining the angular coordinate in calculating the spatial coordinate through dynamic triangulation is demonstrated. Five energy center localization methods are developed and tested to select the best method. After implementation of these methods, digital compensation for the measurement error, and statistical data analysis, a non-parametric behavior of the data is identified. The Wilcoxon signed rank test is applied to improve the result further. For optical scanning systems, it is necessary to detect a light emitter mounted on the infrastructure being investigated to calculate its spatial coordinate by the energy center localization method.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wahl, D.E.; Jakowatz, C.V. Jr.; Ghiglia, D.C.
1991-01-01
Autofocus methods in SAR and self-survey techniques in SONAR have a common mathematical basis in that they both involve estimation and correction of phase errors introduced by sensor position uncertainties. Time delay estimation and correlation methods have been shown to be effective in solving the self-survey problem for towed SONAR arrays. Since it can be shown that platform motion errors introduce similar time-delay estimation problems in SAR imaging, the question arises as to whether such techniques could be effectively employed for autofocus of SAR imagery. With a simple mathematical model for motion errors in SAR, we will show why suchmore » correlation/time-delay techniques are not nearly as effective as established SAR autofocus algorithms such as phase gradient autofocus or sub-aperture based methods. This analysis forms an important bridge between signal processing methodologies for SAR and SONAR. 5 refs., 4 figs.« less
An analysis of estimation of pulmonary blood flow by the single-breath method
NASA Technical Reports Server (NTRS)
Srinivasan, R.
1986-01-01
The single-breath method represents a simple noninvasive technique for the assessment of capillary blood flow across the lung. However, this method has not gained widespread acceptance, because its accuracy is still being questioned. A rigorous procedure is described for estimating pulmonary blood flow (PBF) using data obtained with the aid of the single-breath method. Attention is given to the minimization of data-processing errors in the presence of measurement errors and to questions regarding a correction for possible loss of CO2 in the lung tissue. It is pointed out that the estimations are based on the exact solution of the underlying differential equations which describe the dynamics of gas exchange in the lung. The reported study demonstrates the feasibility of obtaining highly reliable estimates of PBF from expiratory data in the presence of random measurement errors.
Generated spiral bevel gears: Optimal machine-tool settings and tooth contact analysis
NASA Technical Reports Server (NTRS)
Litvin, F. L.; Tsung, W. J.; Coy, J. J.; Heine, C.
1985-01-01
Geometry and kinematic errors were studied for Gleason generated spiral bevel gears. A new method was devised for choosing optimal machine settings. These settings provide zero kinematic errors and an improved bearing contact. The kinematic errors are a major source of noise and vibration in spiral bevel gears. The improved bearing contact gives improved conditions for lubrication. A computer program for tooth contact analysis was developed, and thereby the new generation process was confirmed. The new process is governed by the requirement that during the generation process there is directional constancy of the common normal of the contacting surfaces for generator and generated surfaces of pinion and gear.
Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W; Müller, Klaus-Robert; Lemm, Steven
2013-01-01
Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation.
Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W.; Müller, Klaus-Robert; Lemm, Steven
2013-01-01
Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation. PMID:23844016
Multiscale Modeling and Uncertainty Quantification for Nuclear Fuel Performance
DOE Office of Scientific and Technical Information (OSTI.GOV)
Estep, Donald; El-Azab, Anter; Pernice, Michael
2017-03-23
In this project, we will address the challenges associated with constructing high fidelity multiscale models of nuclear fuel performance. We (*) propose a novel approach for coupling mesoscale and macroscale models, (*) devise efficient numerical methods for simulating the coupled system, and (*) devise and analyze effective numerical approaches for error and uncertainty quantification for the coupled multiscale system. As an integral part of the project, we will carry out analysis of the effects of upscaling and downscaling, investigate efficient methods for stochastic sensitivity analysis of the individual macroscale and mesoscale models, and carry out a posteriori error analysis formore » computed results. We will pursue development and implementation of solutions in software used at Idaho National Laboratories on models of interest to the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program.« less
Nuclear norm-based 2-DPCA for extracting features from images.
Zhang, Fanlong; Yang, Jian; Qian, Jianjun; Xu, Yong
2015-10-01
The 2-D principal component analysis (2-DPCA) is a widely used method for image feature extraction. However, it can be equivalently implemented via image-row-based principal component analysis. This paper presents a structured 2-D method called nuclear norm-based 2-DPCA (N-2-DPCA), which uses a nuclear norm-based reconstruction error criterion. The nuclear norm is a matrix norm, which can provide a structured 2-D characterization for the reconstruction error image. The reconstruction error criterion is minimized by converting the nuclear norm-based optimization problem into a series of F-norm-based optimization problems. In addition, N-2-DPCA is extended to a bilateral projection-based N-2-DPCA (N-B2-DPCA). The virtue of N-B2-DPCA over N-2-DPCA is that an image can be represented with fewer coefficients. N-2-DPCA and N-B2-DPCA are applied to face recognition and reconstruction and evaluated using the Extended Yale B, CMU PIE, FRGC, and AR databases. Experimental results demonstrate the effectiveness of the proposed methods.
A method for automatic feature points extraction of human vertebrae three-dimensional model
NASA Astrophysics Data System (ADS)
Wu, Zhen; Wu, Junsheng
2017-05-01
A method for automatic extraction of the feature points of the human vertebrae three-dimensional model is presented. Firstly, the statistical model of vertebrae feature points is established based on the results of manual vertebrae feature points extraction. Then anatomical axial analysis of the vertebrae model is performed according to the physiological and morphological characteristics of the vertebrae. Using the axial information obtained from the analysis, a projection relationship between the statistical model and the vertebrae model to be extracted is established. According to the projection relationship, the statistical model is matched with the vertebrae model to get the estimated position of the feature point. Finally, by analyzing the curvature in the spherical neighborhood with the estimated position of feature points, the final position of the feature points is obtained. According to the benchmark result on multiple test models, the mean relative errors of feature point positions are less than 5.98%. At more than half of the positions, the error rate is less than 3% and the minimum mean relative error is 0.19%, which verifies the effectiveness of the method.
Tabelow, Karsten; König, Reinhard; Polzehl, Jörg
2016-01-01
Estimation of learning curves is ubiquitously based on proportions of correct responses within moving trial windows. Thereby, it is tacitly assumed that learning performance is constant within the moving windows, which, however, is often not the case. In the present study we demonstrate that violations of this assumption lead to systematic errors in the analysis of learning curves, and we explored the dependency of these errors on window size, different statistical models, and learning phase. To reduce these errors in the analysis of single-subject data as well as on the population level, we propose adequate statistical methods for the estimation of learning curves and the construction of confidence intervals, trial by trial. Applied to data from an avoidance learning experiment with rodents, these methods revealed performance changes occurring at multiple time scales within and across training sessions which were otherwise obscured in the conventional analysis. Our work shows that the proper assessment of the behavioral dynamics of learning at high temporal resolution can shed new light on specific learning processes, and, thus, allows to refine existing learning concepts. It further disambiguates the interpretation of neurophysiological signal changes recorded during training in relation to learning. PMID:27303809
NASA Astrophysics Data System (ADS)
Grigorie, Teodor Lucian; Corcau, Ileana Jenica; Tudosie, Alexandru Nicolae
2017-06-01
The paper presents a way to obtain an intelligent miniaturized three-axial accelerometric sensor, based on the on-line estimation and compensation of the sensor errors generated by the environmental temperature variation. Taking into account that this error's value is a strongly nonlinear complex function of the values of environmental temperature and of the acceleration exciting the sensor, its correction may not be done off-line and it requires the presence of an additional temperature sensor. The proposed identification methodology for the error model is based on the least square method which process off-line the numerical values obtained from the accelerometer experimental testing for different values of acceleration applied to its axes of sensitivity and for different values of operating temperature. A final analysis of the error level after the compensation highlights the best variant for the matrix in the error model. In the sections of the paper are shown the results of the experimental testing of the accelerometer on all the three sensitivity axes, the identification of the error models on each axis by using the least square method, and the validation of the obtained models with experimental values. For all of the three detection channels was obtained a reduction by almost two orders of magnitude of the acceleration absolute maximum error due to environmental temperature variation.
Moore, Michael D; Shi, Zhenqi; Wildfong, Peter L D
2010-12-01
To develop a method for drawing statistical inferences from differences between multiple experimental pair distribution function (PDF) transforms of powder X-ray diffraction (PXRD) data. The appropriate treatment of initial PXRD error estimates using traditional error propagation algorithms was tested using Monte Carlo simulations on amorphous ketoconazole. An amorphous felodipine:polyvinyl pyrrolidone:vinyl acetate (PVPva) physical mixture was prepared to define an error threshold. Co-solidified products of felodipine:PVPva and terfenadine:PVPva were prepared using a melt-quench method and subsequently analyzed using PXRD and PDF. Differential scanning calorimetry (DSC) was used as an additional characterization method. The appropriate manipulation of initial PXRD error estimates through the PDF transform were confirmed using the Monte Carlo simulations for amorphous ketoconazole. The felodipine:PVPva physical mixture PDF analysis determined ±3σ to be an appropriate error threshold. Using the PDF and error propagation principles, the felodipine:PVPva co-solidified product was determined to be completely miscible, and the terfenadine:PVPva co-solidified product, although having appearances of an amorphous molecular solid dispersion by DSC, was determined to be phase-separated. Statistically based inferences were successfully drawn from PDF transforms of PXRD patterns obtained from composite systems. The principles applied herein may be universally adapted to many different systems and provide a fundamentally sound basis for drawing structural conclusions from PDF studies.
Mesh refinement in finite element analysis by minimization of the stiffness matrix trace
NASA Technical Reports Server (NTRS)
Kittur, Madan G.; Huston, Ronald L.
1989-01-01
Most finite element packages provide means to generate meshes automatically. However, the user is usually confronted with the problem of not knowing whether the mesh generated is appropriate for the problem at hand. Since the accuracy of the finite element results is mesh dependent, mesh selection forms a very important step in the analysis. Indeed, in accurate analyses, meshes need to be refined or rezoned until the solution converges to a value so that the error is below a predetermined tolerance. A-posteriori methods use error indicators, developed by using the theory of interpolation and approximation theory, for mesh refinements. Some use other criterions, such as strain energy density variation and stress contours for example, to obtain near optimal meshes. Although these methods are adaptive, they are expensive. Alternatively, a priori methods, until now available, use geometrical parameters, for example, element aspect ratio. Therefore, they are not adaptive by nature. An adaptive a-priori method is developed. The criterion is that the minimization of the trace of the stiffness matrix with respect to the nodal coordinates, leads to a minimization of the potential energy, and as a consequence provide a good starting mesh. In a few examples the method is shown to provide the optimal mesh. The method is also shown to be relatively simple and amenable to development of computer algorithms. When the procedure is used in conjunction with a-posteriori methods of grid refinement, it is shown that fewer refinement iterations and fewer degrees of freedom are required for convergence as opposed to when the procedure is not used. The mesh obtained is shown to have uniform distribution of stiffness among the nodes and elements which, as a consequence, leads to uniform error distribution. Thus the mesh obtained meets the optimality criterion of uniform error distribution.
Smoothing of the bivariate LOD score for non-normal quantitative traits.
Buil, Alfonso; Dyer, Thomas D; Almasy, Laura; Blangero, John
2005-12-30
Variance component analysis provides an efficient method for performing linkage analysis for quantitative traits. However, type I error of variance components-based likelihood ratio testing may be affected when phenotypic data are non-normally distributed (especially with high values of kurtosis). This results in inflated LOD scores when the normality assumption does not hold. Even though different solutions have been proposed to deal with this problem with univariate phenotypes, little work has been done in the multivariate case. We present an empirical approach to adjust the inflated LOD scores obtained from a bivariate phenotype that violates the assumption of normality. Using the Collaborative Study on the Genetics of Alcoholism data available for the Genetic Analysis Workshop 14, we show how bivariate linkage analysis with leptokurtotic traits gives an inflated type I error. We perform a novel correction that achieves acceptable levels of type I error.
Location precision analysis of stereo thermal anti-sniper detection system
NASA Astrophysics Data System (ADS)
He, Yuqing; Lu, Ya; Zhang, Xiaoyan; Jin, Weiqi
2012-06-01
Anti-sniper detection devices are the urgent requirement in modern warfare. The precision of the anti-sniper detection system is especially important. This paper discusses the location precision analysis of the anti-sniper detection system based on the dual-thermal imaging system. It mainly discusses the following two aspects which produce the error: the digital quantitative effects of the camera; effect of estimating the coordinate of bullet trajectory according to the infrared images in the process of image matching. The formula of the error analysis is deduced according to the method of stereovision model and digital quantitative effects of the camera. From this, we can get the relationship of the detecting accuracy corresponding to the system's parameters. The analysis in this paper provides the theory basis for the error compensation algorithms which are put forward to improve the accuracy of 3D reconstruction of the bullet trajectory in the anti-sniper detection devices.
Angular rate optimal design for the rotary strapdown inertial navigation system.
Yu, Fei; Sun, Qian
2014-04-22
Due to the characteristics of high precision for a long duration, the rotary strapdown inertial navigation system (RSINS) has been widely used in submarines and surface ships. Nowadays, the core technology, the rotating scheme, has been studied by numerous researchers. It is well known that as one of the key technologies, the rotating angular rate seriously influences the effectiveness of the error modulating. In order to design the optimal rotating angular rate of the RSINS, the relationship between the rotating angular rate and the velocity error of the RSINS was analyzed in detail based on the Laplace transform and the inverse Laplace transform in this paper. The analysis results showed that the velocity error of the RSINS depends on not only the sensor error, but also the rotating angular rate. In order to minimize the velocity error, the rotating angular rate of the RSINS should match the sensor error. One optimal design method for the rotating rate of the RSINS was also proposed in this paper. Simulation and experimental results verified the validity and superiority of this optimal design method for the rotating rate of the RSINS.
Maikusa, Norihide; Yamashita, Fumio; Tanaka, Kenichiro; Abe, Osamu; Kawaguchi, Atsushi; Kabasawa, Hiroyuki; Chiba, Shoma; Kasahara, Akihiro; Kobayashi, Nobuhisa; Yuasa, Tetsuya; Sato, Noriko; Matsuda, Hiroshi; Iwatsubo, Takeshi
2013-06-01
Serial magnetic resonance imaging (MRI) images acquired from multisite and multivendor MRI scanners are widely used in measuring longitudinal structural changes in the brain. Precise and accurate measurements are important in understanding the natural progression of neurodegenerative disorders such as Alzheimer's disease. However, geometric distortions in MRI images decrease the accuracy and precision of volumetric or morphometric measurements. To solve this problem, the authors suggest a commercially available phantom-based distortion correction method that accommodates the variation in geometric distortion within MRI images obtained with multivendor MRI scanners. The authors' method is based on image warping using a polynomial function. The method detects fiducial points within a phantom image using phantom analysis software developed by the Mayo Clinic and calculates warping functions for distortion correction. To quantify the effectiveness of the authors' method, the authors corrected phantom images obtained from multivendor MRI scanners and calculated the root-mean-square (RMS) of fiducial errors and the circularity ratio as evaluation values. The authors also compared the performance of the authors' method with that of a distortion correction method based on a spherical harmonics description of the generic gradient design parameters. Moreover, the authors evaluated whether this correction improves the test-retest reproducibility of voxel-based morphometry in human studies. A Wilcoxon signed-rank test with uncorrected and corrected images was performed. The root-mean-square errors and circularity ratios for all slices significantly improved (p < 0.0001) after the authors' distortion correction. Additionally, the authors' method was significantly better than a distortion correction method based on a description of spherical harmonics in improving the distortion of root-mean-square errors (p < 0.001 and 0.0337, respectively). Moreover, the authors' method reduced the RMS error arising from gradient nonlinearity more than gradwarp methods. In human studies, the coefficient of variation of voxel-based morphometry analysis of the whole brain improved significantly from 3.46% to 2.70% after distortion correction of the whole gray matter using the authors' method (Wilcoxon signed-rank test, p < 0.05). The authors proposed a phantom-based distortion correction method to improve reproducibility in longitudinal structural brain analysis using multivendor MRI. The authors evaluated the authors' method for phantom images in terms of two geometrical values and for human images in terms of test-retest reproducibility. The results showed that distortion was corrected significantly using the authors' method. In human studies, the reproducibility of voxel-based morphometry analysis for the whole gray matter significantly improved after distortion correction using the authors' method.
Statistical image quantification toward optimal scan fusion and change quantification
NASA Astrophysics Data System (ADS)
Potesil, Vaclav; Zhou, Xiang Sean
2007-03-01
Recent advance of imaging technology has brought new challenges and opportunities for automatic and quantitative analysis of medical images. With broader accessibility of more imaging modalities for more patients, fusion of modalities/scans from one time point and longitudinal analysis of changes across time points have become the two most critical differentiators to support more informed, more reliable and more reproducible diagnosis and therapy decisions. Unfortunately, scan fusion and longitudinal analysis are both inherently plagued with increased levels of statistical errors. A lack of comprehensive analysis by imaging scientists and a lack of full awareness by physicians pose potential risks in clinical practice. In this paper, we discuss several key error factors affecting imaging quantification, studying their interactions, and introducing a simulation strategy to establish general error bounds for change quantification across time. We quantitatively show that image resolution, voxel anisotropy, lesion size, eccentricity, and orientation are all contributing factors to quantification error; and there is an intricate relationship between voxel anisotropy and lesion shape in affecting quantification error. Specifically, when two or more scans are to be fused at feature level, optimal linear fusion analysis reveals that scans with voxel anisotropy aligned with lesion elongation should receive a higher weight than other scans. As a result of such optimal linear fusion, we will achieve a lower variance than naïve averaging. Simulated experiments are used to validate theoretical predictions. Future work based on the proposed simulation methods may lead to general guidelines and error lower bounds for quantitative image analysis and change detection.
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.
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.
Online beam energy measurement of Beijing electron positron collider II linear accelerator
NASA Astrophysics Data System (ADS)
Wang, S.; Iqbal, M.; Liu, R.; Chi, Y.
2016-02-01
This paper describes online beam energy measurement of Beijing Electron Positron Collider upgraded version II linear accelerator (linac) adequately. It presents the calculation formula, gives the error analysis in detail, discusses the realization in practice, and makes some verification. The method mentioned here measures the beam energy by acquiring the horizontal beam position with three beam position monitors (BPMs), which eliminates the effect of orbit fluctuation, and is much better than the one using the single BPM. The error analysis indicates that this online measurement has further potential usage such as a part of beam energy feedback system. The reliability of this method is also discussed and demonstrated in this paper.
Online beam energy measurement of Beijing electron positron collider II linear accelerator.
Wang, S; Iqbal, M; Liu, R; Chi, Y
2016-02-01
This paper describes online beam energy measurement of Beijing Electron Positron Collider upgraded version II linear accelerator (linac) adequately. It presents the calculation formula, gives the error analysis in detail, discusses the realization in practice, and makes some verification. The method mentioned here measures the beam energy by acquiring the horizontal beam position with three beam position monitors (BPMs), which eliminates the effect of orbit fluctuation, and is much better than the one using the single BPM. The error analysis indicates that this online measurement has further potential usage such as a part of beam energy feedback system. The reliability of this method is also discussed and demonstrated in this paper.
Errors in MR-based attenuation correction for brain imaging with PET/MR scanners
NASA Astrophysics Data System (ADS)
Rota Kops, Elena; Herzog, Hans
2013-02-01
AimAttenuation correction of PET data acquired by hybrid MR/PET scanners remains a challenge, even if several methods for brain and whole-body measurements have been developed recently. A template-based attenuation correction for brain imaging proposed by our group is easy to handle and delivers reliable attenuation maps in a short time. However, some potential error sources are analyzed in this study. We investigated the choice of template reference head among all the available data (error A), and possible skull anomalies of the specific patient, such as discontinuities due to surgery (error B). Materials and methodsAn anatomical MR measurement and a 2-bed-position transmission scan covering the whole head and neck region were performed in eight normal subjects (4 females, 4 males). Error A: Taking alternatively one of the eight heads as reference, eight different templates were created by nonlinearly registering the images to the reference and calculating the average. Eight patients (4 females, 4 males; 4 with brain lesions, 4 w/o brain lesions) were measured in the Siemens BrainPET/MR scanner. The eight templates were used to generate the patients' attenuation maps required for reconstruction. ROI and VOI atlas-based comparisons were performed employing all the reconstructed images. Error B: CT-based attenuation maps of two volunteers were manipulated by manually inserting several skull lesions and filling a nasal cavity. The corresponding attenuation coefficients were substituted with the water's coefficient (0.096/cm). ResultsError A: The mean SUVs over the eight templates pairs for all eight patients and all VOIs did not differ significantly one from each other. Standard deviations up to 1.24% were found. Error B: After reconstruction of the volunteers' BrainPET data with the CT-based attenuation maps without and with skull anomalies, a VOI-atlas analysis was performed revealing very little influence of the skull lesions (less than 3%), while the filled nasal cavity yielded an overestimation in cerebellum up to 5%. ConclusionsThe present error analysis confirms that our template-based attenuation method provides reliable attenuation corrections of PET brain imaging measured in PET/MR scanners.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Arnold, Anthony, E-mail: anthony.arnold@sesiahs.health.nsw.gov.a; Delaney, Geoff P.; Cassapi, Lynette
Purpose: Radiotherapy is a common treatment for cancer patients. Although incidence of error is low, errors can be severe or affect significant numbers of patients. In addition, errors will often not manifest until long periods after treatment. This study describes the development of an incident reporting tool that allows categorical analysis and time trend reporting, covering first 3 years of use. Methods and Materials: A radiotherapy-specific incident analysis system was established. Staff members were encouraged to report actual errors and near-miss events detected at prescription, simulation, planning, or treatment phases of radiotherapy delivery. Trend reporting was reviewed monthly. Results: Reportsmore » were analyzed for the first 3 years of operation (May 2004-2007). A total of 688 reports was received during the study period. The actual error rate was 0.2% per treatment episode. During the study period, the actual error rates reduced significantly from 1% per year to 0.3% per year (p < 0.001), as did the total event report rates (p < 0.0001). There were 3.5 times as many near misses reported compared with actual errors. Conclusions: This system has allowed real-time analysis of events within a radiation oncology department to a reduced error rate through focus on learning and prevention from the near-miss reports. Plans are underway to develop this reporting tool for Australia and New Zealand.« less
Sure, Rebecca; Brandenburg, Jan Gerit
2015-01-01
Abstract In quantum chemical computations the combination of Hartree–Fock or a density functional theory (DFT) approximation with relatively small atomic orbital basis sets of double‐zeta quality is still widely used, for example, in the popular B3LYP/6‐31G* approach. In this Review, we critically analyze the two main sources of error in such computations, that is, the basis set superposition error on the one hand and the missing London dispersion interactions on the other. We review various strategies to correct those errors and present exemplary calculations on mainly noncovalently bound systems of widely varying size. Energies and geometries of small dimers, large supramolecular complexes, and molecular crystals are covered. We conclude that it is not justified to rely on fortunate error compensation, as the main inconsistencies can be cured by modern correction schemes which clearly outperform the plain mean‐field methods. PMID:27308221
Evaluation of centroiding algorithm error for Nano-JASMINE
NASA Astrophysics Data System (ADS)
Hara, Takuji; Gouda, Naoteru; Yano, Taihei; Yamada, Yoshiyuki
2014-08-01
The Nano-JASMINE mission has been designed to perform absolute astrometric measurements with unprecedented accuracy; the end-of-mission parallax standard error is required to be of the order of 3 milli arc seconds for stars brighter than 7.5 mag in the zw-band(0.6μm-1.0μm) .These requirements set a stringent constraint on the accuracy of the estimation of the location of the stellar image on the CCD for each observation. However each stellar images have individual shape depend on the spectral energy distribution of the star, the CCD properties, and the optics and its associated wave front errors. So it is necessity that the centroiding algorithm performs a high accuracy in any observables. Referring to the study of Gaia, we use LSF fitting method for centroiding algorithm, and investigate systematic error of the algorithm for Nano-JASMINE. Furthermore, we found to improve the algorithm by restricting sample LSF when we use a Principle Component Analysis. We show that centroiding algorithm error decrease after adapted the method.
Dictionary learning-based spatiotemporal regularization for 3D dense speckle tracking
NASA Astrophysics Data System (ADS)
Lu, Allen; Zontak, Maria; Parajuli, Nripesh; Stendahl, John C.; Boutagy, Nabil; Eberle, Melissa; O'Donnell, Matthew; Sinusas, Albert J.; Duncan, James S.
2017-03-01
Speckle tracking is a common method for non-rigid tissue motion analysis in 3D echocardiography, where unique texture patterns are tracked through the cardiac cycle. However, poor tracking often occurs due to inherent ultrasound issues, such as image artifacts and speckle decorrelation; thus regularization is required. Various methods, such as optical flow, elastic registration, and block matching techniques have been proposed to track speckle motion. Such methods typically apply spatial and temporal regularization in a separate manner. In this paper, we propose a joint spatiotemporal regularization method based on an adaptive dictionary representation of the dense 3D+time Lagrangian motion field. Sparse dictionaries have good signal adaptive and noise-reduction properties; however, they are prone to quantization errors. Our method takes advantage of the desirable noise suppression, while avoiding the undesirable quantization error. The idea is to enforce regularization only on the poorly tracked trajectories. Specifically, our method 1.) builds data-driven 4-dimensional dictionary of Lagrangian displacements using sparse learning, 2.) automatically identifies poorly tracked trajectories (outliers) based on sparse reconstruction errors, and 3.) performs sparse reconstruction of the outliers only. Our approach can be applied on dense Lagrangian motion fields calculated by any method. We demonstrate the effectiveness of our approach on a baseline block matching speckle tracking and evaluate performance of the proposed algorithm using tracking and strain accuracy analysis.
Error Estimates for Approximate Solutions of the Riccati Equation with Real or Complex Potentials
NASA Astrophysics Data System (ADS)
Finster, Felix; Smoller, Joel
2010-09-01
A method is presented for obtaining rigorous error estimates for approximate solutions of the Riccati equation, with real or complex potentials. Our main tool is to derive invariant region estimates for complex solutions of the Riccati equation. We explain the general strategy for applying these estimates and illustrate the method in typical examples, where the approximate solutions are obtained by gluing together WKB and Airy solutions of corresponding one-dimensional Schrödinger equations. Our method is motivated by, and has applications to, the analysis of linear wave equations in the geometry of a rotating black hole.
Analysis of S-box in Image Encryption Using Root Mean Square Error Method
NASA Astrophysics Data System (ADS)
Hussain, Iqtadar; Shah, Tariq; Gondal, Muhammad Asif; Mahmood, Hasan
2012-07-01
The use of substitution boxes (S-boxes) in encryption applications has proven to be an effective nonlinear component in creating confusion and randomness. The S-box is evolving and many variants appear in literature, which include advanced encryption standard (AES) S-box, affine power affine (APA) S-box, Skipjack S-box, Gray S-box, Lui J S-box, residue prime number S-box, Xyi S-box, and S8 S-box. These S-boxes have algebraic and statistical properties which distinguish them from each other in terms of encryption strength. In some circumstances, the parameters from algebraic and statistical analysis yield results which do not provide clear evidence in distinguishing an S-box for an application to a particular set of data. In image encryption applications, the use of S-boxes needs special care because the visual analysis and perception of a viewer can sometimes identify artifacts embedded in the image. In addition to existing algebraic and statistical analysis already used for image encryption applications, we propose an application of root mean square error technique, which further elaborates the results and enables the analyst to vividly distinguish between the performances of various S-boxes. While the use of the root mean square error analysis in statistics has proven to be effective in determining the difference in original data and the processed data, its use in image encryption has shown promising results in estimating the strength of the encryption method. In this paper, we show the application of the root mean square error analysis to S-box image encryption. The parameters from this analysis are used in determining the strength of S-boxes
A two-factor error model for quantitative steganalysis
NASA Astrophysics Data System (ADS)
Böhme, Rainer; Ker, Andrew D.
2006-02-01
Quantitative steganalysis refers to the exercise not only of detecting the presence of hidden stego messages in carrier objects, but also of estimating the secret message length. This problem is well studied, with many detectors proposed but only a sparse analysis of errors in the estimators. A deep understanding of the error model, however, is a fundamental requirement for the assessment and comparison of different detection methods. This paper presents a rationale for a two-factor model for sources of error in quantitative steganalysis, and shows evidence from a dedicated large-scale nested experimental set-up with a total of more than 200 million attacks. Apart from general findings about the distribution functions found in both classes of errors, their respective weight is determined, and implications for statistical hypothesis tests in benchmarking scenarios or regression analyses are demonstrated. The results are based on a rigorous comparison of five different detection methods under many different external conditions, such as size of the carrier, previous JPEG compression, and colour channel selection. We include analyses demonstrating the effects of local variance and cover saturation on the different sources of error, as well as presenting the case for a relative bias model for between-image error.
An improved error assessment for the GEM-T1 gravitational model
NASA Technical Reports Server (NTRS)
Lerch, F. J.; Marsh, J. G.; Klosko, S. M.; Pavlis, E. C.; Patel, G. B.; Chinn, D. S.; Wagner, C. A.
1988-01-01
Several tests were designed to determine the correct error variances for the Goddard Earth Model (GEM)-T1 gravitational solution which was derived exclusively from satellite tracking data. The basic method employs both wholly independent and dependent subset data solutions and produces a full field coefficient estimate of the model uncertainties. The GEM-T1 errors were further analyzed using a method based upon eigenvalue-eigenvector analysis which calibrates the entire covariance matrix. Dependent satellite and independent altimetric and surface gravity data sets, as well as independent satellite deep resonance information, confirm essentially the same error assessment. These calibrations (utilizing each of the major data subsets within the solution) yield very stable calibration factors which vary by approximately 10 percent over the range of tests employed. Measurements of gravity anomalies obtained from altimetry were also used directly as observations to show that GEM-T1 is calibrated. The mathematical representation of the covariance error in the presence of unmodeled systematic error effects in the data is analyzed and an optimum weighting technique is developed for these conditions. This technique yields an internal self-calibration of the error model, a process which GEM-T1 is shown to approximate.
Underlying risk factors for prescribing errors in long-term aged care: a qualitative study.
Tariq, Amina; Georgiou, Andrew; Raban, Magdalena; Baysari, Melissa Therese; Westbrook, Johanna
2016-09-01
To identify system-related risk factors perceived to contribute to prescribing errors in Australian long-term care settings, that is, residential aged care facilities (RACFs). The study used qualitative methods to explore factors that contribute to unsafe prescribing in RACFs. Data were collected at three RACFs in metropolitan Sydney, Australia between May and November 2011. Participants included RACF managers, doctors, pharmacists and RACF staff actively involved in prescribing-related processes. Methods included non-participant observations (74 h), in-depth semistructured interviews (n=25) and artefact analysis. Detailed process activity models were developed for observed prescribing episodes supplemented by triangulated analysis using content analysis methods. System-related factors perceived to increase the risk of prescribing errors in RACFs were classified into three overarching themes: communication systems, team coordination and staff management. Factors associated with communication systems included limited point-of-care access to information, inadequate handovers, information storage across different media (paper, electronic and memory), poor legibility of charts, information double handling, multiple faxing of medication charts and reliance on manual chart reviews. Team factors included lack of established lines of responsibility, inadequate team communication and limited participation of doctors in multidisciplinary initiatives like medication advisory committee meetings. Factors related to staff management and workload included doctors' time constraints and their accessibility, lack of trained RACF staff and high RACF staff turnover. The study highlights several system-related factors including laborious methods for exchanging medication information, which often act together to contribute to prescribing errors. Multiple interventions (eg, technology systems, team communication protocols) are required to support the collaborative nature of RACF prescribing. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Insar Unwrapping Error Correction Based on Quasi-Accurate Detection of Gross Errors (quad)
NASA Astrophysics Data System (ADS)
Kang, Y.; Zhao, C. Y.; Zhang, Q.; Yang, C. S.
2018-04-01
Unwrapping error is a common error in the InSAR processing, which will seriously degrade the accuracy of the monitoring results. Based on a gross error correction method, Quasi-accurate detection (QUAD), the method for unwrapping errors automatic correction is established in this paper. This method identifies and corrects the unwrapping errors by establishing a functional model between the true errors and interferograms. The basic principle and processing steps are presented. Then this method is compared with the L1-norm method with simulated data. Results show that both methods can effectively suppress the unwrapping error when the ratio of the unwrapping errors is low, and the two methods can complement each other when the ratio of the unwrapping errors is relatively high. At last the real SAR data is tested for the phase unwrapping error correction. Results show that this new method can correct the phase unwrapping errors successfully in the practical application.
Ferreira, Tiago B; Ribeiro, Paulo; Ribeiro, Filomena J; O'Neill, João G
2017-12-01
To compare the prediction error in the calculation of toric intraocular lenses (IOLs) associated with methods that estimate the power of the posterior corneal surface (ie, Barrett toric calculator and Abulafia-Koch formula) with that of methods that consider real measures obtained using Scheimpflug imaging: a software that uses vectorial calculation (Panacea toric calculator: http://www.panaceaiolandtoriccalculator.com) and a ray tracing software (PhacoOptics, Aarhus Nord, Denmark). In 107 eyes of 107 patients undergoing cataract surgery with toric IOL implantation (Acrysof IQ Toric; Alcon Laboratories, Inc., Fort Worth, TX), predicted residual astigmatism by each calculation method was compared with manifest refractive astigmatism. Prediction error in residual astigmatism was calculated using vector analysis. All calculation methods resulted in overcorrection of with-the-rule astigmatism and undercorrection of against-the-rule astigmatism. Both estimation methods resulted in lower mean and centroid astigmatic prediction errors, and a larger number of eyes within 0.50 diopters (D) of absolute prediction error than methods considering real measures (P < .001). Centroid prediction error (CPE) was 0.07 D at 172° for the Barrett toric calculator and 0.13 D at 174° for the Abulafia-Koch formula (combined with Holladay calculator). For methods using real posterior corneal surface measurements, CPE was 0.25 D at 173° for the Panacea calculator and 0.29 D at 171° for the ray tracing software. The Barrett toric calculator and Abulafia-Koch formula yielded the lowest astigmatic prediction errors. Directly evaluating total corneal power for toric IOL calculation was not superior to estimating it. [J Refract Surg. 2017;33(12):794-800.]. Copyright 2017, SLACK Incorporated.
[Refractive errors in patients with cerebral palsy].
Mrugacz, Małgorzata; Bandzul, Krzysztof; Kułak, Wojciech; Poppe, Ewa; Jurowski, Piotr
2013-04-01
Ocular changes are common in patients with cerebral palsy (CP) and they exist in about 50% of cases. The most common are refractive errors and strabismus disease. The aim of the paper was to estimate the relativeness between refractive errors and neurological pathologies in patients with selected types of CP. MATERIAL AND METHODS. The subject of the analysis was showing refractive errors in patients within two groups of CP: diplegia spastica and tetraparesis, with nervous system pathologies taken into account. Results. This study was proven some correlations between refractive errors and type of CP and severity of the CP classified in GMFCS scale. Refractive errors were more common in patients with tetraparesis than with diplegia spastica. In the group with diplegia spastica more common were myopia and astigmatism, however in tetraparesis - hyperopia.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Niemeyer, Kyle E.; Sung, Chih-Jen; Raju, Mandhapati P.
2010-09-15
A novel implementation for the skeletal reduction of large detailed reaction mechanisms using the directed relation graph with error propagation and sensitivity analysis (DRGEPSA) is developed and presented with examples for three hydrocarbon components, n-heptane, iso-octane, and n-decane, relevant to surrogate fuel development. DRGEPSA integrates two previously developed methods, directed relation graph-aided sensitivity analysis (DRGASA) and directed relation graph with error propagation (DRGEP), by first applying DRGEP to efficiently remove many unimportant species prior to sensitivity analysis to further remove unimportant species, producing an optimally small skeletal mechanism for a given error limit. It is illustrated that the combination ofmore » the DRGEP and DRGASA methods allows the DRGEPSA approach to overcome the weaknesses of each, specifically that DRGEP cannot identify all unimportant species and that DRGASA shields unimportant species from removal. Skeletal mechanisms for n-heptane and iso-octane generated using the DRGEP, DRGASA, and DRGEPSA methods are presented and compared to illustrate the improvement of DRGEPSA. From a detailed reaction mechanism for n-alkanes covering n-octane to n-hexadecane with 2115 species and 8157 reactions, two skeletal mechanisms for n-decane generated using DRGEPSA, one covering a comprehensive range of temperature, pressure, and equivalence ratio conditions for autoignition and the other limited to high temperatures, are presented and validated. The comprehensive skeletal mechanism consists of 202 species and 846 reactions and the high-temperature skeletal mechanism consists of 51 species and 256 reactions. Both mechanisms are further demonstrated to well reproduce the results of the detailed mechanism in perfectly-stirred reactor and laminar flame simulations over a wide range of conditions. The comprehensive and high-temperature n-decane skeletal mechanisms are included as supplementary material with this article. (author)« less
Calibrated Bayes Factors Should Not Be Used: A Reply to Hoijtink, van Kooten, and Hulsker.
Morey, Richard D; Wagenmakers, Eric-Jan; Rouder, Jeffrey N
2016-01-01
Hoijtink, Kooten, and Hulsker ( 2016 ) present a method for choosing the prior distribution for an analysis with Bayes factor that is based on controlling error rates, which they advocate as an alternative to our more subjective methods (Morey & Rouder, 2014 ; Rouder, Speckman, Sun, Morey, & Iverson, 2009 ; Wagenmakers, Wetzels, Borsboom, & van der Maas, 2011 ). We show that the method they advocate amounts to a simple significance test, and that the resulting Bayes factors are not interpretable. Additionally, their method fails in common circumstances, and has the potential to yield arbitrarily high Type II error rates. After critiquing their method, we outline the position on subjectivity that underlies our advocacy of Bayes factors.
NASA Astrophysics Data System (ADS)
Gidey, Amanuel
2018-06-01
Determining suitability and vulnerability of groundwater quality for irrigation use is a key alarm and first aid for careful management of groundwater resources to diminish the impacts on irrigation. This study was conducted to determine the overall suitability of groundwater quality for irrigation use and to generate their spatial distribution maps in Elala catchment, Northern Ethiopia. Thirty-nine groundwater samples were collected to analyze and map the water quality variables. Atomic absorption spectrophotometer, ultraviolet spectrophotometer, titration and calculation methods were used for laboratory groundwater quality analysis. Arc GIS, geospatial analysis tools, semivariogram model types and interpolation methods were used to generate geospatial distribution maps. Twelve and eight water quality variables were used to produce weighted overlay and irrigation water quality index models, respectively. Root-mean-square error, mean square error, absolute square error, mean error, root-mean-square standardized error, measured values versus predicted values were used for cross-validation. The overall weighted overlay model result showed that 146 km2 areas are highly suitable, 135 km2 moderately suitable and 60 km2 area unsuitable for irrigation use. The result of irrigation water quality index confirms 10.26% with no restriction, 23.08% with low restriction, 20.51% with moderate restriction, 15.38% with high restriction and 30.76% with the severe restriction for irrigation use. GIS and irrigation water quality index are better methods for irrigation water resources management to achieve a full yield irrigation production to improve food security and to sustain it for a long period, to avoid the possibility of increasing environmental problems for the future generation.
Ten years of preanalytical monitoring and control: Synthetic Balanced Score Card Indicator
López-Garrigós, Maite; Flores, Emilio; Santo-Quiles, Ana; Gutierrez, Mercedes; Lugo, Javier; Lillo, Rosa; Leiva-Salinas, Carlos
2015-01-01
Introduction Preanalytical control and monitoring continue to be an important issue for clinical laboratory professionals. The aim of the study was to evaluate a monitoring system of preanalytical errors regarding not suitable samples for analysis, based on different indicators; to compare such indicators in different phlebotomy centres; and finally to evaluate a single synthetic preanalytical indicator that may be included in the balanced scorecard management system (BSC). Materials and methods We collected individual and global preanalytical errors in haematology, coagulation, chemistry, and urine samples analysis. We also analyzed a synthetic indicator that represents the sum of all types of preanalytical errors, expressed in a sigma level. We studied the evolution of those indicators over time and compared indicator results by way of the comparison of proportions and Chi-square. Results There was a decrease in the number of errors along the years (P < 0.001). This pattern was confirmed in primary care patients, inpatients and outpatients. In blood samples, fewer errors occurred in outpatients, followed by inpatients. Conclusion We present a practical and effective methodology to monitor unsuitable sample preanalytical errors. The synthetic indicator results summarize overall preanalytical sample errors, and can be used as part of BSC management system. PMID:25672466
Very-short-term wind power prediction by a hybrid model with single- and multi-step approaches
NASA Astrophysics Data System (ADS)
Mohammed, E.; Wang, S.; Yu, J.
2017-05-01
Very-short-term wind power prediction (VSTWPP) has played an essential role for the operation of electric power systems. This paper aims at improving and applying a hybrid method of VSTWPP based on historical data. The hybrid method is combined by multiple linear regressions and least square (MLR&LS), which is intended for reducing prediction errors. The predicted values are obtained through two sub-processes:1) transform the time-series data of actual wind power into the power ratio, and then predict the power ratio;2) use the predicted power ratio to predict the wind power. Besides, the proposed method can include two prediction approaches: single-step prediction (SSP) and multi-step prediction (MSP). WPP is tested comparatively by auto-regressive moving average (ARMA) model from the predicted values and errors. The validity of the proposed hybrid method is confirmed in terms of error analysis by using probability density function (PDF), mean absolute percent error (MAPE) and means square error (MSE). Meanwhile, comparison of the correlation coefficients between the actual values and the predicted values for different prediction times and window has confirmed that MSP approach by using the hybrid model is the most accurate while comparing to SSP approach and ARMA. The MLR&LS is accurate and promising for solving problems in WPP.
Kuselman, Ilya; Pennecchi, Francesca; Epstein, Malka; Fajgelj, Ales; Ellison, Stephen L R
2014-12-01
Monte Carlo simulation of expert judgments on human errors in a chemical analysis was used for determination of distributions of the error quantification scores (scores of likelihood and severity, and scores of effectiveness of a laboratory quality system in prevention of the errors). The simulation was based on modeling of an expert behavior: confident, reasonably doubting and irresolute expert judgments were taken into account by means of different probability mass functions (pmfs). As a case study, 36 scenarios of human errors which may occur in elemental analysis of geological samples by ICP-MS were examined. Characteristics of the score distributions for three pmfs of an expert behavior were compared. Variability of the scores, as standard deviation of the simulated score values from the distribution mean, was used for assessment of the score robustness. A range of the score values, calculated directly from elicited data and simulated by a Monte Carlo method for different pmfs, was also discussed from the robustness point of view. It was shown that robustness of the scores, obtained in the case study, can be assessed as satisfactory for the quality risk management and improvement of a laboratory quality system against human errors. Copyright © 2014 Elsevier B.V. All rights reserved.
Multifractal diffusion entropy analysis: Optimal bin width of probability histograms
NASA Astrophysics Data System (ADS)
Jizba, Petr; Korbel, Jan
2014-11-01
In the framework of Multifractal Diffusion Entropy Analysis we propose a method for choosing an optimal bin-width in histograms generated from underlying probability distributions of interest. The method presented uses techniques of Rényi’s entropy and the mean squared error analysis to discuss the conditions under which the error in the multifractal spectrum estimation is minimal. We illustrate the utility of our approach by focusing on a scaling behavior of financial time series. In particular, we analyze the S&P500 stock index as sampled at a daily rate in the time period 1950-2013. In order to demonstrate a strength of the method proposed we compare the multifractal δ-spectrum for various bin-widths and show the robustness of the method, especially for large values of q. For such values, other methods in use, e.g., those based on moment estimation, tend to fail for heavy-tailed data or data with long correlations. Connection between the δ-spectrum and Rényi’s q parameter is also discussed and elucidated on a simple example of multiscale time series.
Improving the Accuracy of Software-Based Energy Analysis for Residential Buildings (Presentation)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Polly, B.
2011-09-01
This presentation describes the basic components of software-based energy analysis for residential buildings, explores the concepts of 'error' and 'accuracy' when analysis predictions are compared to measured data, and explains how NREL is working to continuously improve the accuracy of energy analysis methods.
Statistical process control methods allow the analysis and improvement of anesthesia care.
Fasting, Sigurd; Gisvold, Sven E
2003-10-01
Quality aspects of the anesthetic process are reflected in the rate of intraoperative adverse events. The purpose of this report is to illustrate how the quality of the anesthesia process can be analyzed using statistical process control methods, and exemplify how this analysis can be used for quality improvement. We prospectively recorded anesthesia-related data from all anesthetics for five years. The data included intraoperative adverse events, which were graded into four levels, according to severity. We selected four adverse events, representing important quality and safety aspects, for statistical process control analysis. These were: inadequate regional anesthesia, difficult emergence from general anesthesia, intubation difficulties and drug errors. We analyzed the underlying process using 'p-charts' for statistical process control. In 65,170 anesthetics we recorded adverse events in 18.3%; mostly of lesser severity. Control charts were used to define statistically the predictable normal variation in problem rate, and then used as a basis for analysis of the selected problems with the following results: Inadequate plexus anesthesia: stable process, but unacceptably high failure rate; Difficult emergence: unstable process, because of quality improvement efforts; Intubation difficulties: stable process, rate acceptable; Medication errors: methodology not suited because of low rate of errors. By applying statistical process control methods to the analysis of adverse events, we have exemplified how this allows us to determine if a process is stable, whether an intervention is required, and if quality improvement efforts have the desired effect.
Geometric analysis and restitution of digital multispectral scanner data arrays
NASA Technical Reports Server (NTRS)
Baker, J. R.; Mikhail, E. M.
1975-01-01
An investigation was conducted to define causes of geometric defects within digital multispectral scanner (MSS) data arrays, to analyze the resulting geometric errors, and to investigate restitution methods to correct or reduce these errors. Geometric transformation relationships for scanned data, from which collinearity equations may be derived, served as the basis of parametric methods of analysis and restitution of MSS digital data arrays. The linearization of these collinearity equations is presented. Algorithms considered for use in analysis and restitution included the MSS collinearity equations, piecewise polynomials based on linearized collinearity equations, and nonparametric algorithms. A proposed system for geometric analysis and restitution of MSS digital data arrays was used to evaluate these algorithms, utilizing actual MSS data arrays. It was shown that collinearity equations and nonparametric algorithms both yield acceptable results, but nonparametric algorithms possess definite advantages in computational efficiency. Piecewise polynomials were found to yield inferior results.
NASA Astrophysics Data System (ADS)
Baron, J.; Campbell, W. C.; DeMille, D.; Doyle, J. M.; Gabrielse, G.; Gurevich, Y. V.; Hess, P. W.; Hutzler, N. R.; Kirilov, E.; Kozyryev, I.; O'Leary, B. R.; Panda, C. D.; Parsons, M. F.; Spaun, B.; Vutha, A. C.; West, A. D.; West, E. P.; ACME Collaboration
2017-07-01
We recently set a new limit on the electric dipole moment of the electron (eEDM) (J Baron et al and ACME collaboration 2014 Science 343 269-272), which represented an order-of-magnitude improvement on the previous limit and placed more stringent constraints on many charge-parity-violating extensions to the standard model. In this paper we discuss the measurement in detail. The experimental method and associated apparatus are described, together with the techniques used to isolate the eEDM signal. In particular, we detail the way experimental switches were used to suppress effects that can mimic the signal of interest. The methods used to search for systematic errors, and models explaining observed systematic errors, are also described. We briefly discuss possible improvements to the experiment.
Assessment of Computational Fluid Dynamics (CFD) Models for Shock Boundary-Layer Interaction
NASA Technical Reports Server (NTRS)
DeBonis, James R.; Oberkampf, William L.; Wolf, Richard T.; Orkwis, Paul D.; Turner, Mark G.; Babinsky, Holger
2011-01-01
A workshop on the computational fluid dynamics (CFD) prediction of shock boundary-layer interactions (SBLIs) was held at the 48th AIAA Aerospace Sciences Meeting. As part of the workshop numerous CFD analysts submitted solutions to four experimentally measured SBLIs. This paper describes the assessment of the CFD predictions. The assessment includes an uncertainty analysis of the experimental data, the definition of an error metric and the application of that metric to the CFD solutions. The CFD solutions provided very similar levels of error and in general it was difficult to discern clear trends in the data. For the Reynolds Averaged Navier-Stokes methods the choice of turbulence model appeared to be the largest factor in solution accuracy. Large-eddy simulation methods produced error levels similar to RANS methods but provided superior predictions of normal stresses.
Linear least-squares method for global luminescent oil film skin friction field analysis
NASA Astrophysics Data System (ADS)
Lee, Taekjin; Nonomura, Taku; Asai, Keisuke; Liu, Tianshu
2018-06-01
A data analysis method based on the linear least-squares (LLS) method was developed for the extraction of high-resolution skin friction fields from global luminescent oil film (GLOF) visualization images of a surface in an aerodynamic flow. In this method, the oil film thickness distribution and its spatiotemporal development are measured by detecting the luminescence intensity of the thin oil film. From the resulting set of GLOF images, the thin oil film equation is solved to obtain an ensemble-averaged (steady) skin friction field as an inverse problem. In this paper, the formulation of a discrete linear system of equations for the LLS method is described, and an error analysis is given to identify the main error sources and the relevant parameters. Simulations were conducted to evaluate the accuracy of the LLS method and the effects of the image patterns, image noise, and sample numbers on the results in comparison with the previous snapshot-solution-averaging (SSA) method. An experimental case is shown to enable the comparison of the results obtained using conventional oil flow visualization and those obtained using both the LLS and SSA methods. The overall results show that the LLS method is more reliable than the SSA method and the LLS method can yield a more detailed skin friction topology in an objective way.
Topology of modified helical gears and Tooth Contact Analysis (TCA) program
NASA Technical Reports Server (NTRS)
Litvin, Faydor L.; Zhang, Jiao
1989-01-01
The contents of this report covers: (1) development of optimal geometries for crowned helical gears; (2) a method for their generation; (3) tooth contact analysis (TCA) computer programs for the analysis of meshing and bearing contact of the crowned helical gears; and (4) modelling and simulation of gear shaft deflection. The developed method for synthesis was used to determine the optimal geometry for a crowned helical pinion surface and was directed to localize the bearing contact and guarantee favorable shape and a low level of transmission errors. Two new methods for generation of the crowned helical pinion surface are proposed. One is based on the application of a tool with a surface of revolution that slightly deviates from a regular cone surface. The tool can be used as a grinding wheel or as a shaver. The other is based on a crowning pinion tooth surface with predesigned transmission errors. The pinion tooth surface can be generated by a computer-controlled automatic grinding machine. The TCA program simulates the meshing and bearing contact of the misaligned gears. The transmission errors are also determined. The gear shaft deformation was modelled and investigated. It was found that the deflection of gear shafts has the same effect as gear misalignment.
Sensitivity analysis of non-cohesive sediment transport formulae
NASA Astrophysics Data System (ADS)
Pinto, Lígia; Fortunato, André B.; Freire, Paula
2006-10-01
Sand transport models are often based on semi-empirical equilibrium transport formulae that relate sediment fluxes to physical properties such as velocity, depth and characteristic sediment grain sizes. In engineering applications, errors in these physical properties affect the accuracy of the sediment fluxes. The present analysis quantifies error propagation from the input physical properties to the sediment fluxes, determines which ones control the final errors, and provides insight into the relative strengths, weaknesses and limitations of four total load formulae (Ackers and White, Engelund and Hansen, van Rijn, and Karim and Kennedy) and one bed load formulation (van Rijn). The various sources of uncertainty are first investigated individually, in order to pinpoint the key physical properties that control the errors. Since the strong non-linearity of most sand transport formulae precludes analytical approaches, a Monte Carlo method is validated and used in the analysis. Results show that the accuracy in total sediment transport evaluations is mainly determined by errors in the current velocity and in the sediment median grain size. For the bed load transport using the van Rijn formula, errors in the current velocity alone control the final accuracy. In a final set of tests, all physical properties are allowed to vary simultaneously in order to analyze the combined effect of errors. The combined effect of errors in all the physical properties is then compared to an estimate of the errors due to the intrinsic limitations of the formulae. Results show that errors in the physical properties can be dominant for typical uncertainties associated with these properties, particularly for small depths. A comparison between the various formulae reveals that the van Rijn formula is more sensitive to basic physical properties. Hence, it should only be used when physical properties are known with precision.
Hsu, Chi-Pin; Lin, Shang-Chih; Shih, Kao-Shang; Huang, Chang-Hung; Lee, Chian-Her
2014-12-01
After total knee replacement, the model-based Roentgen stereophotogrammetric analysis (RSA) technique has been used to monitor the status of prosthetic wear, misalignment, and even failure. However, the overlap of the prosthetic outlines inevitably increases errors in the estimation of prosthetic poses due to the limited amount of available outlines. In the literature, quite a few studies have investigated the problems induced by the overlapped outlines, and manual adjustment is still the mainstream. This study proposes two methods to automate the image processing of overlapped outlines prior to the pose registration of prosthetic models. The outline-separated method defines the intersected points and segments the overlapped outlines. The feature-recognized method uses the point and line features of the remaining outlines to initiate registration. Overlap percentage is defined as the ratio of overlapped to non-overlapped outlines. The simulated images with five overlapping percentages are used to evaluate the robustness and accuracy of the proposed methods. Compared with non-overlapped images, overlapped images reduce the number of outlines available for model-based RSA calculation. The maximum and root mean square errors for a prosthetic outline are 0.35 and 0.04 mm, respectively. The mean translation and rotation errors are 0.11 mm and 0.18°, respectively. The errors of the model-based RSA results are increased when the overlap percentage is beyond about 9%. In conclusion, both outline-separated and feature-recognized methods can be seamlessly integrated to automate the calculation of rough registration. This can significantly increase the clinical practicability of the model-based RSA technique.
Modeling coherent errors in quantum error correction
NASA Astrophysics Data System (ADS)
Greenbaum, Daniel; Dutton, Zachary
2018-01-01
Analysis of quantum error correcting codes is typically done using a stochastic, Pauli channel error model for describing the noise on physical qubits. However, it was recently found that coherent errors (systematic rotations) on physical data qubits result in both physical and logical error rates that differ significantly from those predicted by a Pauli model. Here we examine the accuracy of the Pauli approximation for noise containing coherent errors (characterized by a rotation angle ɛ) under the repetition code. We derive an analytic expression for the logical error channel as a function of arbitrary code distance d and concatenation level n, in the small error limit. We find that coherent physical errors result in logical errors that are partially coherent and therefore non-Pauli. However, the coherent part of the logical error is negligible at fewer than {ε }-({dn-1)} error correction cycles when the decoder is optimized for independent Pauli errors, thus providing a regime of validity for the Pauli approximation. Above this number of correction cycles, the persistent coherent logical error will cause logical failure more quickly than the Pauli model would predict, and this may need to be combated with coherent suppression methods at the physical level or larger codes.
Fisseni, Gregor; Pentzek, Michael; Abholz, Heinz-Harald
2008-02-01
GPs' recollections about their 'most serious errors in treatment' and about the consequences for themselves. Does it make a difference, who (else) contributed to the error, or to its discovery or disclosure? Anonymous questionnaire study concerning the 'three most serious errors in your career as a GP'. The participating doctors were given an operational definition of 'serious error'. They applied a special recall technique, using patient-induced associations to bring to mind former 'serious errors'. The recall method and the semi-structured 25-item questionnaire used were developed and piloted by the authors. The items were analysed quantitatively and by qualitative content analysis. General practices in the North Rhine region in Germany: 32 GPs anonymously reported about 75 'most serious errors'. In more than half of the cases analysed, other people contributed considerably to the GPs' serious errors. Most of the errors were discovered and disclosed to the patient by doctors: either by the GPs themselves, or by colleagues. A lot of GPs suffered loss of reputation and loss of patients. However, the number of patients staying with their GP clearly exceeded the number leaving their GP, depending on who else contributed to the error, who discovered it and who disclosed it to the patient. The majority of patients still trusted their GP after a serious error, especially if the GP was not the only one who contributed to the error and if the GP played an active role in the discovery and disclosure or the error.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Unseren, M.A.
The report discusses the orientation tracking control problem for a kinematically redundant, autonomous manipulator moving in a three dimensional workspace. The orientation error is derived using the normalized quaternion error method of Ickes, the Luh, Walker, and Paul error method, and a method suggested here utilizing the Rodrigues parameters, all of which are expressed in terms of normalized quaternions. The analytical time derivatives of the orientation errors are determined. The latter, along with the translational velocity error, form a dosed loop kinematic velocity model of the manipulator using normalized quaternion and translational position feedback. An analysis of the singularities associatedmore » with expressing the models in a form suitable for solving the inverse kinematics problem is given. Two redundancy resolution algorithms originally developed using an open loop kinematic velocity model of the manipulator are extended to properly take into account the orientation tracking control problem. This report furnishes the necessary mathematical framework required prior to experimental implementation of the orientation tracking control schemes on the seven axis CESARm research manipulator or on the seven-axis Robotics Research K1207i dexterous manipulator, the latter of which is to be delivered to the Oak Ridge National Laboratory in 1993.« less
Influences of optical-spectrum errors on excess relative intensity noise in a fiber-optic gyroscope
NASA Astrophysics Data System (ADS)
Zheng, Yue; Zhang, Chunxi; Li, Lijing
2018-03-01
The excess relative intensity noise (RIN) generated from broadband sources degrades the angular-random-walk performance of a fiber-optic gyroscope dramatically. Many methods have been proposed and managed to suppress the excess RIN. However, the properties of the excess RIN under the influences of different optical errors in the fiber-optic gyroscope have not been systematically investigated. Therefore, it is difficult for the existing RIN-suppression methods to achieve the optimal results in practice. In this work, the influences of different optical-spectrum errors on the power spectral density of the excess RIN are theoretically analyzed. In particular, the properties of the excess RIN affected by the raised-cosine-type ripples in the optical spectrum are elaborately investigated. Experimental measurements of the excess RIN corresponding to different optical-spectrum errors are in good agreement with our theoretical analysis, demonstrating its validity. This work provides a comprehensive understanding of the properties of the excess RIN under the influences of different optical-spectrum errors. Potentially, it can be utilized to optimize the configurations of the existing RIN-suppression methods by accurately evaluating the power spectral density of the excess RIN.
GIZMO: Multi-method magneto-hydrodynamics+gravity code
NASA Astrophysics Data System (ADS)
Hopkins, Philip F.
2014-10-01
GIZMO is a flexible, multi-method magneto-hydrodynamics+gravity code that solves the hydrodynamic equations using a variety of different methods. It introduces new Lagrangian Godunov-type methods that allow solving the fluid equations with a moving particle distribution that is automatically adaptive in resolution and avoids the advection errors, angular momentum conservation errors, and excessive diffusion problems that seriously limit the applicability of “adaptive mesh” (AMR) codes, while simultaneously avoiding the low-order errors inherent to simpler methods like smoothed-particle hydrodynamics (SPH). GIZMO also allows the use of SPH either in “traditional” form or “modern” (more accurate) forms, or use of a mesh. Self-gravity is solved quickly with a BH-Tree (optionally a hybrid PM-Tree for periodic boundaries) and on-the-fly adaptive gravitational softenings. The code is descended from P-GADGET, itself descended from GADGET-2 (ascl:0003.001), and many of the naming conventions remain (for the sake of compatibility with the large library of GADGET work and analysis software).
XCO2 Retrieval Errors from a PCA-based Approach to Fast Radiative Transfer
NASA Astrophysics Data System (ADS)
Somkuti, Peter; Boesch, Hartmut; Natraj, Vijay; Kopparla, Pushkar
2017-04-01
Multiple-scattering radiative transfer (RT) calculations are an integral part of forward models used to infer greenhouse gas concentrations in the shortwave-infrared spectral range from satellite missions such as GOSAT or OCO-2. Such calculations are, however, computationally expensive and, combined with the recent growth in data volume, necessitate the use of acceleration methods in order to make retrievals feasible on an operational level. The principle component analysis (PCA)-based approach to fast radiative transfer introduced by Natraj et al. 2005 is a spectral binning method, in which the many line-by-line monochromatic calculations are replaced by a small set of representative ones. From the PCA performed on the optical layer properties for a scene-dependent atmosphere, the results of the representative calculations are mapped onto all spectral points in the given band. Since this RT scheme is an approximation, the computed top-of-atmosphere radiances exhibit errors compared to the "full" line-by-line calculation. These errors ultimately propagate into the final retrieved greenhouse gas concentrations, and their magnitude depends on scene-dependent parameters such as aerosol loadings or viewing geometry. An advantage of this method is the ability to choose the degree of accuracy by increasing or decreasing the number of empirical orthogonal functions used for the reconstruction of the radiances. We have performed a large set of global simulations based on real GOSAT scenes and assess the retrieval errors induced by the fast RT approximation through linear error analysis. We find that across a wide range of geophysical parameters, the errors are for the most part smaller than ± 0.2 ppm and ± 0.06 ppm (out of roughly 400 ppm) for ocean and land scenes respectively. A fast RT scheme that produces low errors is important, since regional biases in XCO2 even in the low sub-ppm range can cause significant changes in carbon fluxes obtained from inversions (Chevallier et al. 2007).
ANALYZING NUMERICAL ERRORS IN DOMAIN HEAT TRANSPORT MODELS USING THE CVBEM.
Hromadka, T.V.
1987-01-01
Besides providing an exact solution for steady-state heat conduction processes (Laplace-Poisson equations), the CVBEM (complex variable boundary element method) can be used for the numerical error analysis of domain model solutions. For problems where soil-water phase change latent heat effects dominate the thermal regime, heat transport can be approximately modeled as a time-stepped steady-state condition in the thawed and frozen regions, respectively. The CVBEM provides an exact solution of the two-dimensional steady-state heat transport problem, and also provides the error in matching the prescribed boundary conditions by the development of a modeling error distribution or an approximate boundary generation.
Inherent Conservatism in Deterministic Quasi-Static Structural Analysis
NASA Technical Reports Server (NTRS)
Verderaime, V.
1997-01-01
The cause of the long-suspected excessive conservatism in the prevailing structural deterministic safety factor has been identified as an inherent violation of the error propagation laws when reducing statistical data to deterministic values and then combining them algebraically through successive structural computational processes. These errors are restricted to the applied stress computations, and because mean and variations of the tolerance limit format are added, the errors are positive, serially cumulative, and excessively conservative. Reliability methods circumvent these errors and provide more efficient and uniform safe structures. The document is a tutorial on the deficiencies and nature of the current safety factor and of its improvement and transition to absolute reliability.
The Use of Time Series Analysis and t Tests with Serially Correlated Data Tests.
ERIC Educational Resources Information Center
Nicolich, Mark J.; Weinstein, Carol S.
1981-01-01
Results of three methods of analysis applied to simulated autocorrelated data sets with an intervention point (varying in autocorrelation degree, variance of error term, and magnitude of intervention effect) are compared and presented. The three methods are: t tests; maximum likelihood Box-Jenkins (ARIMA); and Bayesian Box Jenkins. (Author/AEF)
NASA Astrophysics Data System (ADS)
Zapata, N.; Martínez-Cob, A.
2001-12-01
This paper reports a study undertaken to evaluate the feasibility of the surface renewal method to accurately estimate long-term evaporation from the playa and margins of an endorreic salty lagoon (Gallocanta lagoon, Spain) under semiarid conditions. High-frequency temperature readings were taken for two time lags ( r) and three measurement heights ( z) in order to get surface renewal sensible heat flux ( HSR) values. These values were compared against eddy covariance sensible heat flux ( HEC) values for a calibration period (25-30 July 2000). Error analysis statistics (index of agreement, IA; root mean square error, RMSE; and systematic mean square error, MSEs) showed that the agreement between HSR and HEC improved as measurement height decreased and time lag increased. Calibration factors α were obtained for all analyzed cases. The best results were obtained for the z=0.9 m ( r=0.75 s) case for which α=1.0 was observed. In this case, uncertainty was about 10% in terms of relative error ( RE). Latent heat flux values were obtained by solving the energy balance equation for both the surface renewal ( LESR) and the eddy covariance ( LEEC) methods, using HSR and HEC, respectively, and measurements of net radiation and soil heat flux. For the calibration period, error analysis statistics for LESR were quite similar to those for HSR, although errors were mostly at random. LESR uncertainty was less than 9%. Calibration factors were applied for a validation data subset (30 July-4 August 2000) for which meteorological conditions were somewhat different (higher temperatures and wind speed and lower solar and net radiation). Error analysis statistics for both HSR and LESR were quite good for all cases showing the goodness of the calibration factors. Nevertheless, the results obtained for the z=0.9 m ( r=0.75 s) case were still the best ones.
Global Warming Estimation From Microwave Sounding Unit
NASA Technical Reports Server (NTRS)
Prabhakara, C.; Iacovazzi, R., Jr.; Yoo, J.-M.; Dalu, G.
1998-01-01
Microwave Sounding Unit (MSU) Ch 2 data sets, collected from sequential, polar-orbiting, Sun-synchronous National Oceanic and Atmospheric Administration operational satellites, contain systematic calibration errors that are coupled to the diurnal temperature cycle over the globe. Since these coupled errors in MSU data differ between successive satellites, it is necessary to make compensatory adjustments to these multisatellite data sets in order to determine long-term global temperature change. With the aid of the observations during overlapping periods of successive satellites, we can determine such adjustments and use them to account for the coupled errors in the long-term time series of MSU Ch 2 global temperature. In turn, these adjusted MSU Ch 2 data sets can be used to yield global temperature trend. In a pioneering study, Spencer and Christy (SC) (1990) developed a procedure to derive the global temperature trend from MSU Ch 2 data. Such a procedure can leave unaccounted residual errors in the time series of the temperature anomalies deduced by SC, which could lead to a spurious long-term temperature trend derived from their analysis. In the present study, we have developed a method that avoids the shortcomings of the SC procedure, the magnitude of the coupled errors is not determined explicitly. Furthermore, based on some assumptions, these coupled errors are eliminated in three separate steps. Such a procedure can leave unaccounted residual errors in the time series of the temperature anomalies deduced by SC, which could lead to a spurious long-term temperature trend derived from their analysis. In the present study, we have developed a method that avoids the shortcomings of the SC procedures. Based on our analysis, we find there is a global warming of 0.23+/-0.12 K between 1980 and 1991. Also, in this study, the time series of global temperature anomalies constructed by removing the global mean annual temperature cycle compares favorably with a similar time series obtained from conventional observations of temperature.
Biometrics encryption combining palmprint with two-layer error correction codes
NASA Astrophysics Data System (ADS)
Li, Hengjian; Qiu, Jian; Dong, Jiwen; Feng, Guang
2017-07-01
To bridge the gap between the fuzziness of biometrics and the exactitude of cryptography, based on combining palmprint with two-layer error correction codes, a novel biometrics encryption method is proposed. Firstly, the randomly generated original keys are encoded by convolutional and cyclic two-layer coding. The first layer uses a convolution code to correct burst errors. The second layer uses cyclic code to correct random errors. Then, the palmprint features are extracted from the palmprint images. Next, they are fused together by XORing operation. The information is stored in a smart card. Finally, the original keys extraction process is the information in the smart card XOR the user's palmprint features and then decoded with convolutional and cyclic two-layer code. The experimental results and security analysis show that it can recover the original keys completely. The proposed method is more secure than a single password factor, and has higher accuracy than a single biometric factor.
Coherent detection of position errors in inter-satellite laser communications
NASA Astrophysics Data System (ADS)
Xu, Nan; Liu, Liren; Liu, De'an; Sun, Jianfeng; Luan, Zhu
2007-09-01
Due to the improved receiver sensitivity and wavelength selectivity, coherent detection became an attractive alternative to direct detection in inter-satellite laser communications. A novel method to coherent detection of position errors information is proposed. Coherent communication system generally consists of receive telescope, local oscillator, optical hybrid, photoelectric detector and optical phase lock loop (OPLL). Based on the system composing, this method adds CCD and computer as position error detector. CCD captures interference pattern while detection of transmission data from the transmitter laser. After processed and analyzed by computer, target position information is obtained from characteristic parameter of the interference pattern. The position errors as the control signal of PAT subsystem drive the receiver telescope to keep tracking to the target. Theoretical deviation and analysis is presented. The application extends to coherent laser rang finder, in which object distance and position information can be obtained simultaneously.
[Quantitative surface analysis of Pt-Co, Cu-Au and Cu-Ag alloy films by XPS and AES].
Li, Lian-Zhong; Zhuo, Shang-Jun; Shen, Ru-Xiang; Qian, Rong; Gao, Jie
2013-11-01
In order to improve the quantitative analysis accuracy of AES, We associated XPS with AES and studied the method to reduce the error of AES quantitative analysis, selected Pt-Co, Cu-Au and Cu-Ag binary alloy thin-films as the samples, used XPS to correct AES quantitative analysis results by changing the auger sensitivity factors to make their quantitative analysis results more similar. Then we verified the accuracy of the quantitative analysis of AES when using the revised sensitivity factors by other samples with different composition ratio, and the results showed that the corrected relative sensitivity factors can reduce the error in quantitative analysis of AES to less than 10%. Peak defining is difficult in the form of the integral spectrum of AES analysis since choosing the starting point and ending point when determining the characteristic auger peak intensity area with great uncertainty, and to make analysis easier, we also processed data in the form of the differential spectrum, made quantitative analysis on the basis of peak to peak height instead of peak area, corrected the relative sensitivity factors, and verified the accuracy of quantitative analysis by the other samples with different composition ratio. The result showed that the analytical error in quantitative analysis of AES reduced to less than 9%. It showed that the accuracy of AES quantitative analysis can be highly improved by the way of associating XPS with AES to correct the auger sensitivity factors since the matrix effects are taken into account. Good consistency was presented, proving the feasibility of this method.