Efficient model reduction of parametrized systems by matrix discrete empirical interpolation

NASA Astrophysics Data System (ADS)

Negri, Federico; Manzoni, Andrea; Amsallem, David

2015-12-01

In this work, we apply a Matrix version of the so-called Discrete Empirical Interpolation (MDEIM) for the efficient reduction of nonaffine parametrized systems arising from the discretization of linear partial differential equations. Dealing with affinely parametrized operators is crucial in order to enhance the online solution of reduced-order models (ROMs). However, in many cases such an affine decomposition is not readily available, and must be recovered through (often) intrusive procedures, such as the empirical interpolation method (EIM) and its discrete variant DEIM. In this paper we show that MDEIM represents a very efficient approach to deal with complex physical and geometrical parametrizations in a non-intrusive, efficient and purely algebraic way. We propose different strategies to combine MDEIM with a state approximation resulting either from a reduced basis greedy approach or Proper Orthogonal Decomposition. A posteriori error estimates accounting for the MDEIM error are also developed in the case of parametrized elliptic and parabolic equations. Finally, the capability of MDEIM to generate accurate and efficient ROMs is demonstrated on the solution of two computationally-intensive classes of problems occurring in engineering contexts, namely PDE-constrained shape optimization and parametrized coupled problems.

PolyWaTT: A polynomial water travel time estimator based on Derivative Dynamic Time Warping and Perceptually Important Points

NASA Astrophysics Data System (ADS)

Claure, Yuri Navarro; Matsubara, Edson Takashi; Padovani, Carlos; Prati, Ronaldo Cristiano

2018-03-01

Traditional methods for estimating timing parameters in hydrological science require a rigorous study of the relations of flow resistance, slope, flow regime, watershed size, water velocity, and other local variables. These studies are mostly based on empirical observations, where the timing parameter is estimated using empirically derived formulas. The application of these studies to other locations is not always direct. The locations in which equations are used should have comparable characteristics to the locations from which such equations have been derived. To overcome this barrier, in this work, we developed a data-driven approach to estimate timing parameters such as travel time. Our proposal estimates timing parameters using historical data of the location without the need of adapting or using empirical formulas from other locations. The proposal only uses one variable measured at two different locations on the same river (for instance, two river-level measurements, one upstream and the other downstream on the same river). The recorded data from each location generates two time series. Our method aligns these two time series using derivative dynamic time warping (DDTW) and perceptually important points (PIP). Using data from timing parameters, a polynomial function generalizes the data by inducing a polynomial water travel time estimator, called PolyWaTT. To evaluate the potential of our proposal, we applied PolyWaTT to three different watersheds: a floodplain ecosystem located in the part of Brazil known as Pantanal, the world's largest tropical wetland area; and the Missouri River and the Pearl River, in United States of America. We compared our proposal with empirical formulas and a data-driven state-of-the-art method. The experimental results demonstrate that PolyWaTT showed a lower mean absolute error than all other methods tested in this study, and for longer distances the mean absolute error achieved by PolyWaTT is three times smaller than empirical formulas.

Nuclear binding energy using semi empirical mass formula

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

Ankita,, E-mail: ankitagoyal@gmail.com; Suthar, B.

2016-05-06

In the present communication, semi empirical mass formula using the liquid drop model has been presented. Nuclear binding energies are calculated using semi empirical mass formula with various constants given by different researchers. We also compare these calculated values with experimental data and comparative study for finding suitable constants is added using the error plot. The study is extended to find the more suitable constant to reduce the error.

Use of Numerical Groundwater Model and Analytical Empirical Orthogonal Function for Calibrating Spatiotemporal pattern of Pumpage, Recharge and Parameter

NASA Astrophysics Data System (ADS)

Huang, C. L.; Hsu, N. S.; Hsu, F. C.; Liu, H. J.

2016-12-01

This study develops a novel methodology for the spatiotemporal groundwater calibration of mega-quantitative recharge and parameters by coupling a specialized numerical model and analytical empirical orthogonal function (EOF). The actual spatiotemporal patterns of groundwater pumpage are estimated by an originally developed back propagation neural network-based response matrix with the electrical consumption analysis. The spatiotemporal patterns of the recharge from surface water and hydrogeological parameters (i.e. horizontal hydraulic conductivity and vertical leakance) are calibrated by EOF with the simulated error hydrograph of groundwater storage, in order to qualify the multiple error sources and quantify the revised volume. The objective function of the optimization model is minimizing the root mean square error of the simulated storage error percentage across multiple aquifers, meanwhile subject to mass balance of groundwater budget and the governing equation in transient state. The established method was applied on the groundwater system of Chou-Shui River Alluvial Fan. The simulated period is from January 2012 to December 2014. The total numbers of hydraulic conductivity, vertical leakance and recharge from surface water among four aquifers are 126, 96 and 1080, respectively. Results showed that the RMSE during the calibration process was decreased dramatically and can quickly converse within 6th iteration, because of efficient filtration of the transmission induced by the estimated error and recharge across the boundary. Moreover, the average simulated error percentage according to groundwater level corresponding to the calibrated budget variables and parameters of aquifer one is as small as 0.11%. It represent that the developed methodology not only can effectively detect the flow tendency and error source in all aquifers to achieve accurately spatiotemporal calibration, but also can capture the peak and fluctuation of groundwater level in shallow aquifer.

System Related Interventions to Reduce Diagnostic Error: A Narrative Review

PubMed Central

Singh, Hardeep; Graber, Mark L.; Kissam, Stephanie M.; Sorensen, Asta V.; Lenfestey, Nancy F.; Tant, Elizabeth M.; Henriksen, Kerm; LaBresh, Kenneth A.

2013-01-01

Background Diagnostic errors (missed, delayed, or wrong diagnosis) have gained recent attention and are associated with significant preventable morbidity and mortality. We reviewed the recent literature to identify interventions that have been, or could be, implemented to address systems-related factors that contribute directly to diagnostic error. Methods We conducted a comprehensive search using multiple search strategies. We first identified candidate articles in English between 2000 and 2009 from a PubMed search that exclusively evaluated for articles related to diagnostic error or delay. We then sought additional papers from references in the initial dataset, searches of additional databases, and subject matter experts. Articles were included if they formally evaluated an intervention to prevent or reduce diagnostic error; however, we also included papers if interventions were suggested and not tested in order to inform the state-of-the science on the topic. We categorized interventions according to the step in the diagnostic process they targeted: patient-provider encounter, performance and interpretation of diagnostic tests, follow-up and tracking of diagnostic information, subspecialty and referral-related; and patient-specific. Results We identified 43 articles for full review, of which 6 reported tested interventions and 37 contained suggestions for possible interventions. Empirical studies, though somewhat positive, were non-experimental or quasi-experimental and included a small number of clinicians or health care sites. Outcome measures in general were underdeveloped and varied markedly between studies, depending on the setting or step in the diagnostic process involved. Conclusions Despite a number of suggested interventions in the literature, few empirical studies have tested interventions to reduce diagnostic error in the last decade. Advancing the science of diagnostic error prevention will require more robust study designs and rigorous definitions of diagnostic processes and outcomes to measure intervention effects. PMID:22129930

[Empirical therapeutic approach to infection by resistant gram positive (acute bacterial skin and skin structure infections and health care pneumonia). Value of risk factors].

PubMed

González-DelCastillo, J; Núñez-Orantos, M J; Candel, F J; Martín-Sánchez, F J

2016-09-01

Antibiotic treatment inadequacy is common in these sites of infection and may have implications for the patient's prognosis. In acute bacterial skin and skin structure infections, the document states that for the establishment of an adequate treatment it must be assessed the severity, the patient comorbidity and the risk factors for multidrug-resistant microorganism. The concept of health care-associated pneumonia is discussed and leads to errors in the etiologic diagnosis and therefore in the selection of antibiotic treatment. This paper discusses how to perform this approach to the possible etiology to guide empirical treatment.

Most Common Formal Grammatical Errors Committed by Authors

ERIC Educational Resources Information Center

Onwuegbuzie, Anthony J.

2017-01-01

Empirical evidence has been provided about the importance of avoiding American Psychological Association (APA) errors in the abstract, body, reference list, and table sections of empirical research articles. Specifically, authors are significantly more likely to have their manuscripts rejected for publication if they commit numerous APA…

When do latent class models overstate accuracy for diagnostic and other classifiers in the absence of a gold standard?

PubMed

Spencer, Bruce D

2012-06-01

Latent class models are increasingly used to assess the accuracy of medical diagnostic tests and other classifications when no gold standard is available and the true state is unknown. When the latent class is treated as the true class, the latent class models provide measures of components of accuracy including specificity and sensitivity and their complements, type I and type II error rates. The error rates according to the latent class model differ from the true error rates, however, and empirical comparisons with a gold standard suggest the true error rates often are larger. We investigate conditions under which the true type I and type II error rates are larger than those provided by the latent class models. Results from Uebersax (1988, Psychological Bulletin 104, 405-416) are extended to accommodate random effects and covariates affecting the responses. The results are important for interpreting the results of latent class analyses. An error decomposition is presented that incorporates an error component from invalidity of the latent class model. © 2011, The International Biometric Society.

Determination of errors in derived magnetic field directions in geosynchronous orbit: results from a statistical approach

NASA Astrophysics Data System (ADS)

Chen, Yue; Cunningham, Gregory; Henderson, Michael

2016-09-01

This study aims to statistically estimate the errors in local magnetic field directions that are derived from electron directional distributions measured by Los Alamos National Laboratory geosynchronous (LANL GEO) satellites. First, by comparing derived and measured magnetic field directions along the GEO orbit to those calculated from three selected empirical global magnetic field models (including a static Olson and Pfitzer 1977 quiet magnetic field model, a simple dynamic Tsyganenko 1989 model, and a sophisticated dynamic Tsyganenko 2001 storm model), it is shown that the errors in both derived and modeled directions are at least comparable. Second, using a newly developed proxy method as well as comparing results from empirical models, we are able to provide for the first time circumstantial evidence showing that derived magnetic field directions should statistically match the real magnetic directions better, with averaged errors < ˜ 2°, than those from the three empirical models with averaged errors > ˜ 5°. In addition, our results suggest that the errors in derived magnetic field directions do not depend much on magnetospheric activity, in contrast to the empirical field models. Finally, as applications of the above conclusions, we show examples of electron pitch angle distributions observed by LANL GEO and also take the derived magnetic field directions as the real ones so as to test the performance of empirical field models along the GEO orbits, with results suggesting dependence on solar cycles as well as satellite locations. This study demonstrates the validity and value of the method that infers local magnetic field directions from particle spin-resolved distributions.

Determination of errors in derived magnetic field directions in geosynchronous orbit: results from a statistical approach

DOE PAGES

Chen, Yue; Cunningham, Gregory; Henderson, Michael

2016-09-21

Our study aims to statistically estimate the errors in local magnetic field directions that are derived from electron directional distributions measured by Los Alamos National Laboratory geosynchronous (LANL GEO) satellites. First, by comparing derived and measured magnetic field directions along the GEO orbit to those calculated from three selected empirical global magnetic field models (including a static Olson and Pfitzer 1977 quiet magnetic field model, a simple dynamic Tsyganenko 1989 model, and a sophisticated dynamic Tsyganenko 2001 storm model), it is shown that the errors in both derived and modeled directions are at least comparable. Furthermore, using a newly developedmore » proxy method as well as comparing results from empirical models, we are able to provide for the first time circumstantial evidence showing that derived magnetic field directions should statistically match the real magnetic directions better, with averaged errors < ~2°, than those from the three empirical models with averaged errors > ~5°. In addition, our results suggest that the errors in derived magnetic field directions do not depend much on magnetospheric activity, in contrast to the empirical field models. Finally, as applications of the above conclusions, we show examples of electron pitch angle distributions observed by LANL GEO and also take the derived magnetic field directions as the real ones so as to test the performance of empirical field models along the GEO orbits, with results suggesting dependence on solar cycles as well as satellite locations. Finally, this study demonstrates the validity and value of the method that infers local magnetic field directions from particle spin-resolved distributions.« less

Determination of errors in derived magnetic field directions in geosynchronous orbit: results from a statistical approach

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

Chen, Yue; Cunningham, Gregory; Henderson, Michael

Our study aims to statistically estimate the errors in local magnetic field directions that are derived from electron directional distributions measured by Los Alamos National Laboratory geosynchronous (LANL GEO) satellites. First, by comparing derived and measured magnetic field directions along the GEO orbit to those calculated from three selected empirical global magnetic field models (including a static Olson and Pfitzer 1977 quiet magnetic field model, a simple dynamic Tsyganenko 1989 model, and a sophisticated dynamic Tsyganenko 2001 storm model), it is shown that the errors in both derived and modeled directions are at least comparable. Furthermore, using a newly developedmore » proxy method as well as comparing results from empirical models, we are able to provide for the first time circumstantial evidence showing that derived magnetic field directions should statistically match the real magnetic directions better, with averaged errors < ~2°, than those from the three empirical models with averaged errors > ~5°. In addition, our results suggest that the errors in derived magnetic field directions do not depend much on magnetospheric activity, in contrast to the empirical field models. Finally, as applications of the above conclusions, we show examples of electron pitch angle distributions observed by LANL GEO and also take the derived magnetic field directions as the real ones so as to test the performance of empirical field models along the GEO orbits, with results suggesting dependence on solar cycles as well as satellite locations. Finally, this study demonstrates the validity and value of the method that infers local magnetic field directions from particle spin-resolved distributions.« less

Improved estimation of subject-level functional connectivity using full and partial correlation with empirical Bayes shrinkage.

PubMed

Mejia, Amanda F; Nebel, Mary Beth; Barber, Anita D; Choe, Ann S; Pekar, James J; Caffo, Brian S; Lindquist, Martin A

2018-05-15

Reliability of subject-level resting-state functional connectivity (FC) is determined in part by the statistical techniques employed in its estimation. Methods that pool information across subjects to inform estimation of subject-level effects (e.g., Bayesian approaches) have been shown to enhance reliability of subject-level FC. However, fully Bayesian approaches are computationally demanding, while empirical Bayesian approaches typically rely on using repeated measures to estimate the variance components in the model. Here, we avoid the need for repeated measures by proposing a novel measurement error model for FC describing the different sources of variance and error, which we use to perform empirical Bayes shrinkage of subject-level FC towards the group average. In addition, since the traditional intra-class correlation coefficient (ICC) is inappropriate for biased estimates, we propose a new reliability measure denoted the mean squared error intra-class correlation coefficient (ICC MSE ) to properly assess the reliability of the resulting (biased) estimates. We apply the proposed techniques to test-retest resting-state fMRI data on 461 subjects from the Human Connectome Project to estimate connectivity between 100 regions identified through independent components analysis (ICA). We consider both correlation and partial correlation as the measure of FC and assess the benefit of shrinkage for each measure, as well as the effects of scan duration. We find that shrinkage estimates of subject-level FC exhibit substantially greater reliability than traditional estimates across various scan durations, even for the most reliable connections and regardless of connectivity measure. Additionally, we find partial correlation reliability to be highly sensitive to the choice of penalty term, and to be generally worse than that of full correlations except for certain connections and a narrow range of penalty values. This suggests that the penalty needs to be chosen carefully when using partial correlations. Copyright © 2018. Published by Elsevier Inc.

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

PubMed Central

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

2014-01-01

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

Optimizing the learning rate for adaptive estimation of neural encoding models

PubMed Central

2018-01-01

Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neural activity to the brain state, and is used for brain state decoding. The speed and accuracy of adaptive learning algorithms are critically affected by the learning rate, which dictates how fast model parameters are updated based on new observations. Despite the importance of the learning rate, currently an analytical approach for its selection is largely lacking and existing signal processing methods vastly tune it empirically or heuristically. Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. We formulate the problem through a fundamental trade-off that learning rate introduces between the steady-state error and the convergence time of the estimated model parameters. We derive explicit functions that predict the effect of learning rate on error and convergence time. Using these functions, our calibration algorithm can keep the steady-state parameter error covariance smaller than a desired upper-bound while minimizing the convergence time, or keep the convergence time faster than a desired value while minimizing the error. We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. Moreover, the calibration algorithm allows for fast and accurate learning of the encoding model and for fast convergence of decoding to accurate performance. Finally, larger learning rates result in inaccurate encoding models and decoders, and smaller learning rates delay their convergence. The calibration algorithm provides a novel analytical approach to predictably achieve a desired level of error and convergence time in adaptive learning, with application to closed-loop neurotechnologies and other signal processing domains. PMID:29813069

Optimizing the learning rate for adaptive estimation of neural encoding models.

PubMed

Hsieh, Han-Lin; Shanechi, Maryam M

2018-05-01

Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neural activity to the brain state, and is used for brain state decoding. The speed and accuracy of adaptive learning algorithms are critically affected by the learning rate, which dictates how fast model parameters are updated based on new observations. Despite the importance of the learning rate, currently an analytical approach for its selection is largely lacking and existing signal processing methods vastly tune it empirically or heuristically. Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. We formulate the problem through a fundamental trade-off that learning rate introduces between the steady-state error and the convergence time of the estimated model parameters. We derive explicit functions that predict the effect of learning rate on error and convergence time. Using these functions, our calibration algorithm can keep the steady-state parameter error covariance smaller than a desired upper-bound while minimizing the convergence time, or keep the convergence time faster than a desired value while minimizing the error. We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. Moreover, the calibration algorithm allows for fast and accurate learning of the encoding model and for fast convergence of decoding to accurate performance. Finally, larger learning rates result in inaccurate encoding models and decoders, and smaller learning rates delay their convergence. The calibration algorithm provides a novel analytical approach to predictably achieve a desired level of error and convergence time in adaptive learning, with application to closed-loop neurotechnologies and other signal processing domains.

Administration and Organizational Influences on AFDC Case Decision Errors: An Empirical Analysis.

ERIC Educational Resources Information Center

Piliavin, Irving; And Others

The quality of effort among public assistance personnel has been criticized virtually since the inception of welfare programs for the poor. However, until recently, empirical information on the performance of these workers has been nonexistent. The present study, concerned with Aid to Families with Dependent Children (AFDC) case decision errors,…

Worldwide Ocean Optics Database (WOOD)

DTIC Science & Technology

2001-09-30

user can obtain values computed from empirical algorithms (e.g., beam attenuation estimated from diffuse attenuation and backscatter data). Error ...from empirical algorithms (e.g., beam attenuation estimated from diffuse attenuation and backscatter data). Error estimates will also be provided for...properties, including diffuse attenuation, beam attenuation, and scattering. The database shall be easy to use, Internet accessible, and frequently updated

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

NASA Astrophysics Data System (ADS)

Pernot, Pascal; Savin, Andreas

2018-06-01

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

#2 - An Empirical Assessment of Exposure Measurement Error and Effect Attenuation in Bi-Pollutant Epidemiologic Models

EPA Science Inventory

Background• Differing degrees of exposure error acrosspollutants• Previous focus on quantifying and accounting forexposure error in single-pollutant models• Examine exposure errors for multiple pollutantsand provide insights on the potential for bias andattenuation...

Analysis of a Statistical Relationship Between Dose and Error Tallies in Semiconductor Digital Integrated Circuits for Application to Radiation Monitoring Over a Wireless Sensor Network

NASA Astrophysics Data System (ADS)

Colins, Karen; Li, Liqian; Liu, Yu

2017-05-01

Mass production of widely used semiconductor digital integrated circuits (ICs) has lowered unit costs to the level of ordinary daily consumables of a few dollars. It is therefore reasonable to contemplate the idea of an engineered system that consumes unshielded low-cost ICs for the purpose of measuring gamma radiation dose. Underlying the idea is the premise of a measurable correlation between an observable property of ICs and radiation dose. Accumulation of radiation-damage-induced state changes or error events is such a property. If correct, the premise could make possible low-cost wide-area radiation dose measurement systems, instantiated as wireless sensor networks (WSNs) with unshielded consumable ICs as nodes, communicating error events to a remote base station. The premise has been investigated quantitatively for the first time in laboratory experiments and related analyses performed at the Canadian Nuclear Laboratories. State changes or error events were recorded in real time during irradiation of samples of ICs of different types in a 60Co gamma cell. From the error-event sequences, empirical distribution functions of dose were generated. The distribution functions were inverted and probabilities scaled by total error events, to yield plots of the relationship between dose and error tallies. Positive correlation was observed, and discrete functional dependence of dose quantiles on error tallies was measured, demonstrating the correctness of the premise. The idea of an engineered system that consumes unshielded low-cost ICs in a WSN, for the purpose of measuring gamma radiation dose over wide areas, is therefore tenable.

Climate Prediction for Brazil's Nordeste: Performance of Empirical and Numerical Modeling Methods.

NASA Astrophysics Data System (ADS)

Moura, Antonio Divino; Hastenrath, Stefan

2004-07-01

Comparisons of performance of climate forecast methods require consistency in the predictand and a long common reference period. For Brazil's Nordeste, empirical methods developed at the University of Wisconsin use preseason (October January) rainfall and January indices of the fields of meridional wind component and sea surface temperature (SST) in the tropical Atlantic and the equatorial Pacific as input to stepwise multiple regression and neural networking. These are used to predict the March June rainfall at a network of 27 stations. An experiment at the International Research Institute for Climate Prediction, Columbia University, with a numerical model (ECHAM4.5) used global SST information through February to predict the March June rainfall at three grid points in the Nordeste. The predictands for the empirical and numerical model forecasts are correlated at +0.96, and the period common to the independent portion of record of the empirical prediction and the numerical modeling is 1968 99. Over this period, predicted versus observed rainfall are evaluated in terms of correlation, root-mean-square error, absolute error, and bias. Performance is high for both approaches. Numerical modeling produces a correlation of +0.68, moderate errors, and strong negative bias. For the empirical methods, errors and bias are small, and correlations of +0.73 and +0.82 are reached between predicted and observed rainfall.

Beyond alpha: an empirical examination of the effects of different sources of measurement error on reliability estimates for measures of individual differences constructs.

PubMed

Schmidt, Frank L; Le, Huy; Ilies, Remus

2003-06-01

On the basis of an empirical study of measures of constructs from the cognitive domain, the personality domain, and the domain of affective traits, the authors of this study examine the implications of transient measurement error for the measurement of frequently studied individual differences variables. The authors clarify relevant reliability concepts as they relate to transient error and present a procedure for estimating the coefficient of equivalence and stability (L. J. Cronbach, 1947), the only classical reliability coefficient that assesses all 3 major sources of measurement error (random response, transient, and specific factor errors). The authors conclude that transient error exists in all 3 trait domains and is especially large in the domain of affective traits. Their findings indicate that the nearly universal use of the coefficient of equivalence (Cronbach's alpha; L. J. Cronbach, 1951), which fails to assess transient error, leads to overestimates of reliability and undercorrections for biases due to measurement error.

Diagnosing Model Errors in Simulations of Solar Radiation on Inclined Surfaces: Preprint

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

Xie, Yu; Sengupta, Manajit

2016-06-01

Transposition models have been widely used in the solar energy industry to simulate solar radiation on inclined PV panels. Following numerous studies comparing the performance of transposition models, this paper aims to understand the quantitative uncertainty in the state-of-the-art transposition models and the sources leading to the uncertainty. Our results suggest that an isotropic transposition model developed by Badescu substantially underestimates diffuse plane-of-array (POA) irradiances when diffuse radiation is perfectly isotropic. In the empirical transposition models, the selection of empirical coefficients and land surface albedo can both result in uncertainty in the output. This study can be used as amore » guide for future development of physics-based transposition models.« less

Diagnosing Model Errors in Simulation of Solar Radiation on Inclined Surfaces

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

Xie, Yu; Sengupta, Manajit

2016-11-21

Transposition models have been widely used in the solar energy industry to simulate solar radiation on inclined PV panels. Following numerous studies comparing the performance of transposition models, this paper aims to understand the quantitative uncertainty in the state-of-the-art transposition models and the sources leading to the uncertainty. Our results show significant differences between two highly used isotropic transposition models with one substantially underestimating the diffuse plane-of-array (POA) irradiances when diffuse radiation is perfectly isotropic. In the empirical transposition models, the selection of empirical coefficients and land surface albedo can both result in uncertainty in the output. This study canmore » be used as a guide for future development of physics-based transposition models.« less

Estimating standard errors in feature network models.

PubMed

Frank, Laurence E; Heiser, Willem J

2007-05-01

Feature network models are graphical structures that represent proximity data in a discrete space while using the same formalism that is the basis of least squares methods employed in multidimensional scaling. Existing methods to derive a network model from empirical data only give the best-fitting network and yield no standard errors for the parameter estimates. The additivity properties of networks make it possible to consider the model as a univariate (multiple) linear regression problem with positivity restrictions on the parameters. In the present study, both theoretical and empirical standard errors are obtained for the constrained regression parameters of a network model with known features. The performance of both types of standard error is evaluated using Monte Carlo techniques.

Clinical decision support alert malfunctions: analysis and empirically derived taxonomy.

PubMed

Wright, Adam; Ai, Angela; Ash, Joan; Wiesen, Jane F; Hickman, Thu-Trang T; Aaron, Skye; McEvoy, Dustin; Borkowsky, Shane; Dissanayake, Pavithra I; Embi, Peter; Galanter, William; Harper, Jeremy; Kassakian, Steve Z; Ramoni, Rachel; Schreiber, Richard; Sirajuddin, Anwar; Bates, David W; Sittig, Dean F

2018-05-01

To develop an empirically derived taxonomy of clinical decision support (CDS) alert malfunctions. We identified CDS alert malfunctions using a mix of qualitative and quantitative methods: (1) site visits with interviews of chief medical informatics officers, CDS developers, clinical leaders, and CDS end users; (2) surveys of chief medical informatics officers; (3) analysis of CDS firing rates; and (4) analysis of CDS overrides. We used a multi-round, manual, iterative card sort to develop a multi-axial, empirically derived taxonomy of CDS malfunctions. We analyzed 68 CDS alert malfunction cases from 14 sites across the United States with diverse electronic health record systems. Four primary axes emerged: the cause of the malfunction, its mode of discovery, when it began, and how it affected rule firing. Build errors, conceptualization errors, and the introduction of new concepts or terms were the most frequent causes. User reports were the predominant mode of discovery. Many malfunctions within our database caused rules to fire for patients for whom they should not have (false positives), but the reverse (false negatives) was also common. Across organizations and electronic health record systems, similar malfunction patterns recurred. Challenges included updates to code sets and values, software issues at the time of system upgrades, difficulties with migration of CDS content between computing environments, and the challenge of correctly conceptualizing and building CDS. CDS alert malfunctions are frequent. The empirically derived taxonomy formalizes the common recurring issues that cause these malfunctions, helping CDS developers anticipate and prevent CDS malfunctions before they occur or detect and resolve them expediently.

Perspectives on empirical approaches for ocean color remote sensing of chlorophyll in a changing climate.

PubMed

Dierssen, Heidi M

2010-10-05

Phytoplankton biomass and productivity have been continuously monitored from ocean color satellites for over a decade. Yet, the most widely used empirical approach for estimating chlorophyll a (Chl) from satellites can be in error by a factor of 5 or more. Such variability is due to differences in absorption and backscattering properties of phytoplankton and related concentrations of colored-dissolved organic matter (CDOM) and minerals. The empirical algorithms have built-in assumptions that follow the basic precept of biological oceanography--namely, oligotrophic regions with low phytoplankton biomass are populated with small phytoplankton, whereas more productive regions contain larger bloom-forming phytoplankton. With a changing world ocean, phytoplankton composition may shift in response to altered environmental forcing, and CDOM and mineral concentrations may become uncoupled from phytoplankton stocks, creating further uncertainty and error in the empirical approaches. Hence, caution is warranted when using empirically derived Chl to infer climate-related changes in ocean biology. The Southern Ocean is already experiencing climatic shifts and shows substantial errors in satellite-derived Chl for different phytoplankton assemblages. Accurate global assessments of phytoplankton will require improved technology and modeling, enhanced field observations, and ongoing validation of our "eyes in space."

Automatically generated acceptance test: A software reliability experiment

NASA Technical Reports Server (NTRS)

Protzel, Peter W.

1988-01-01

This study presents results of a software reliability experiment investigating the feasibility of a new error detection method. The method can be used as an acceptance test and is solely based on empirical data about the behavior of internal states of a program. The experimental design uses the existing environment of a multi-version experiment previously conducted at the NASA Langley Research Center, in which the launch interceptor problem is used as a model. This allows the controlled experimental investigation of versions with well-known single and multiple faults, and the availability of an oracle permits the determination of the error detection performance of the test. Fault interaction phenomena are observed that have an amplifying effect on the number of error occurrences. Preliminary results indicate that all faults examined so far are detected by the acceptance test. This shows promise for further investigations, and for the employment of this test method on other applications.

Correcting intensity loss errors in the absence of texture-free reference samples during pole figure measurement

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

Saleh, Ahmed A., E-mail: asaleh@uow.edu.au

Even with the use of X-ray polycapillary lenses, sample tilting during pole figure measurement results in a decrease in the recorded X-ray intensity. The magnitude of this error is affected by the sample size and/or the finite detector size. These errors can be typically corrected by measuring the intensity loss as a function of the tilt angle using a texture-free reference sample (ideally made of the same alloy as the investigated material). Since texture-free reference samples are not readily available for all alloys, the present study employs an empirical procedure to estimate the correction curve for a particular experimental configuration.more » It involves the use of real texture-free reference samples that pre-exist in any X-ray diffraction laboratory to first establish the empirical correlations between X-ray intensity, sample tilt and their Bragg angles and thereafter generate correction curves for any Bragg angle. It will be shown that the empirically corrected textures are in very good agreement with the experimentally corrected ones. - Highlights: •Sample tilting during X-ray pole figure measurement leads to intensity loss errors. •Texture-free reference samples are typically used to correct the pole figures. •An empirical correction procedure is proposed in the absence of reference samples. •The procedure relies on reference samples that pre-exist in any texture laboratory. •Experimentally and empirically corrected textures are in very good agreement.« less

Ozone Trend Detectability

NASA Technical Reports Server (NTRS)

Campbell, J. W. (Editor)

1981-01-01

The detection of anthropogenic disturbances in the Earth's ozone layer was studied. Two topics were addressed: (1) the level at which a trend in total ozoning is detected by existing data sources; and (2) empirical evidence in the prediction of the depletion in total ozone. Error sources are identified. The predictability of climatological series, whether empirical models can be trusted, and how errors in the Dobson total ozone data impact trend detectability, are discussed.

Empirical source noise prediction method with application to subsonic coaxial jet mixing noise

NASA Technical Reports Server (NTRS)

Zorumski, W. E.; Weir, D. S.

1982-01-01

A general empirical method, developed for source noise predictions, uses tensor splines to represent the dependence of the acoustic field on frequency and direction and Taylor's series to represent the dependence on source state parameters. The method is applied to prediction of mixing noise from subsonic circular and coaxial jets. A noise data base of 1/3-octave-band sound pressure levels (SPL's) from 540 tests was gathered from three countries: United States, United Kingdom, and France. The SPL's depend on seven variables: frequency, polar direction angle, and five source state parameters: inner and outer nozzle pressure ratios, inner and outer stream total temperatures, and nozzle area ratio. A least-squares seven-dimensional curve fit defines a table of constants which is used for the prediction method. The resulting prediction has a mean error of 0 dB and a standard deviation of 1.2 dB. The prediction method is used to search for a coaxial jet which has the greatest coaxial noise benefit as compared with an equivalent single jet. It is found that benefits of about 6 dB are possible.

Positive Beliefs about Errors as an Important Element of Adaptive Individual Dealing with Errors during Academic Learning

ERIC Educational Resources Information Center

Tulis, Maria; Steuer, Gabriele; Dresel, Markus

2018-01-01

Research on learning from errors gives reason to assume that errors provide a high potential to facilitate deep learning if students are willing and able to take these learning opportunities. The first aim of this study was to analyse whether beliefs about errors as learning opportunities can be theoretically and empirically distinguished from…

Improved Orbit Determination and Forecasts with an Assimilative Tool for Atmospheric Density and Satellite Drag Specification

NASA Astrophysics Data System (ADS)

Crowley, G.; Pilinski, M.; Sutton, E. K.; Codrescu, M.; Fuller-Rowell, T. J.; Matsuo, T.; Fedrizzi, M.; Solomon, S. C.; Qian, L.; Thayer, J. P.

2016-12-01

Much as aircraft are affected by the prevailing winds and weather conditions in which they fly, satellites are affected by the variability in density and motion of the near earth space environment. Drastic changes in the neutral density of the thermosphere, caused by geomagnetic storms or other phenomena, result in perturbations of LEO satellite motions through drag on the satellite surfaces. This can lead to difficulties in locating important satellites, temporarily losing track of satellites, and errors when predicting collisions in space. We describe ongoing work to build a comprehensive nowcast and forecast system for specifying the neutral atmospheric state related to orbital drag conditions. The system outputs include neutral density, winds, temperature, composition, and the satellite drag derived from these parameters. This modeling tool is based on several state-of-the-art coupled models of the thermosphere-ionosphere as well as several empirical models running in real-time and uses assimilative techniques to produce a thermospheric nowcast. This software will also produce 72 hour predictions of the global thermosphere-ionosphere system using the nowcast as the initial condition and using near real-time and predicted space weather data and indices as the inputs. Features of this technique include: • Satellite drag specifications with errors lower than current models • Altitude coverage up to 1000km • Background state representation using both first principles and empirical models • Assimilation of satellite drag and other datatypes • Real time capability • Ability to produce 72-hour forecasts of the atmospheric state In this paper, we will summarize the model design and assimilative architecture, and present preliminary validation results. Validation results will be presented in the context of satellite orbit errors and compared with several leading atmospheric models including the High Accuracy Satellite Drag Model, which is currently used operationally by the Air Force to specify neutral densities. As part of the analysis, we compare the drag observed by a variety of satellites which were not used as part of the assimilation-dataset and whose perigee altitudes span a range from 200km to 700 km.

Tourism forecasting using modified empirical mode decomposition and group method of data handling

NASA Astrophysics Data System (ADS)

Yahya, N. A.; Samsudin, R.; Shabri, A.

2017-09-01

In this study, a hybrid model using modified Empirical Mode Decomposition (EMD) and Group Method of Data Handling (GMDH) model is proposed for tourism forecasting. This approach reconstructs intrinsic mode functions (IMFs) produced by EMD using trial and error method. The new component and the remaining IMFs is then predicted respectively using GMDH model. Finally, the forecasted results for each component are aggregated to construct an ensemble forecast. The data used in this experiment are monthly time series data of tourist arrivals from China, Thailand and India to Malaysia from year 2000 to 2016. The performance of the model is evaluated using Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) where conventional GMDH model and EMD-GMDH model are used as benchmark models. Empirical results proved that the proposed model performed better forecasts than the benchmarked models.

Structure and Processing in Tunisian Arabic: Speech Error Data

ERIC Educational Resources Information Center

Hamrouni, Nadia

2010-01-01

This dissertation presents experimental research on speech errors in Tunisian Arabic. The nonconcatenative morphology of Arabic shows interesting interactions of phrasal and lexical constraints with morphological structure during language production. The central empirical questions revolve around properties of "exchange errors". These…

A Semi-Empirical Formula of the Dependence of the Fluorescence Intensity of Naphthalene on Temperature and the Oxygen Concentration

NASA Astrophysics Data System (ADS)

An, B.; Wang, Z.-G.; Yang, L.-C.; Li, X.-P.

2017-09-01

Two-ring aromatics, such as naphthalene, are important fluorescent components of kerosene in the planar laser-induced fluorescent (PLIF) technique. Quantifying measurements of kerosene vapor concentrations by PLIF require a prior knowledge of the fluorescence intensity of naphthalene over a wide temperature and oxygen concentration range. To promote the application of PLIF, a semi-empirical formula based on the collision theory and experimental data at the laser wavelength of 266 nm and a pressure of 0.1 MPa is established to predict the fluorescence intensity of naphthalene at different temperatures and oxygen concentrations. This formula takes vibrational states, temperature, and oxygen quenching into account. Verified by published experimental data, the formula can predict the fluorescence intensity of naphthalene with an error less than 9%.

The Relevance of Second Language Acquisition Theory to the Written Error Correction Debate

ERIC Educational Resources Information Center

Polio, Charlene

2012-01-01

The controversies surrounding written error correction can be traced to Truscott (1996) in his polemic against written error correction. He claimed that empirical studies showed that error correction was ineffective and that this was to be expected "given the nature of the correction process and "the nature of language learning" (p. 328, emphasis…

Selecting a restoration technique to minimize OCR error.

PubMed

Cannon, M; Fugate, M; Hush, D R; Scovel, C

2003-01-01

This paper introduces a learning problem related to the task of converting printed documents to ASCII text files. The goal of the learning procedure is to produce a function that maps documents to restoration techniques in such a way that on average the restored documents have minimum optical character recognition error. We derive a general form for the optimal function and use it to motivate the development of a nonparametric method based on nearest neighbors. We also develop a direct method of solution based on empirical error minimization for which we prove a finite sample bound on estimation error that is independent of distribution. We show that this empirical error minimization problem is an extension of the empirical optimization problem for traditional M-class classification with general loss function and prove computational hardness for this problem. We then derive a simple iterative algorithm called generalized multiclass ratchet (GMR) and prove that it produces an optimal function asymptotically (with probability 1). To obtain the GMR algorithm we introduce a new data map that extends Kesler's construction for the multiclass problem and then apply an algorithm called Ratchet to this mapped data, where Ratchet is a modification of the Pocket algorithm . Finally, we apply these methods to a collection of documents and report on the experimental results.

Imaginary-frequency polarizability and van der Waals force constants of two-electron atoms, with rigorous bounds

NASA Technical Reports Server (NTRS)

Glover, R. M.; Weinhold, F.

1977-01-01

Variational functionals of Braunn and Rebane (1972) for the imagery-frequency polarizability (IFP) have been generalized by the method of Gramian inequalities to give rigorous upper and lower bounds, valid even when the true (but unknown) unperturbed wavefunction must be represented by a variational approximation. Using these formulas in conjunction with flexible variational trial functions, tight error bounds are computed for the IFP and the associated two- and three-body van der Waals interaction constants of the ground 1(1S) and metastable 2(1,3S) states of He and Li(+). These bounds generally establish the ground-state properties to within a fraction of a per cent and metastable properties to within a few per cent, permitting a comparative assessment of competing theoretical methods at this level of accuracy. Unlike previous 'error bounds' for these properties, the present results have a completely a priori theoretical character, with no empirical input data.

Semi-empirical model for retrieval of soil moisture using RISAT-1 C-Band SAR data over a sub-tropical semi-arid area of Rewari district, Haryana (India)

NASA Astrophysics Data System (ADS)

Rawat, Kishan Singh; Sehgal, Vinay Kumar; Pradhan, Sanatan; Ray, Shibendu S.

2018-03-01

We have estimated soil moisture (SM) by using circular horizontal polarization backscattering coefficient (σ o_{RH}), differences of circular vertical and horizontal σ o (σ o_{RV} {-} σ o_{RH}) from FRS-1 data of Radar Imaging Satellite (RISAT-1) and surface roughness in terms of RMS height ({RMS}_{height}). We examined the performance of FRS-1 in retrieving SM under wheat crop at tillering stage. Results revealed that it is possible to develop a good semi-empirical model (SEM) to estimate SM of the upper soil layer using RISAT-1 SAR data rather than using existing empirical model based on only single parameter, i.e., σ o. Near surface SM measurements were related to σ o_{RH}, σ o_{RV} {-} σ o_{RH} derived using 5.35 GHz (C-band) image of RISAT-1 and {RMS}_{height}. The roughness component derived in terms of {RMS}_{height} showed a good positive correlation with σ o_{RV} {-} σ o_{RH} (R2 = 0.65). By considering all the major influencing factors (σ o_{RH}, σ o_{RV} {-} σ o_{RH}, and {RMS}_{height}), an SEM was developed where SM (volumetric) predicted values depend on σ o_{RH}, σ o_{RV} {-} σ o_{RH}, and {RMS}_{height}. This SEM showed R2 of 0.87 and adjusted R2 of 0.85, multiple R=0.94 and with standard error of 0.05 at 95% confidence level. Validation of the SM derived from semi-empirical model with observed measurement ({SM}_{Observed}) showed root mean square error (RMSE) = 0.06, relative-RMSE (R-RMSE) = 0.18, mean absolute error (MAE) = 0.04, normalized RMSE (NRMSE) = 0.17, Nash-Sutcliffe efficiency (NSE) = 0.91 ({≈ } 1), index of agreement (d) = 1, coefficient of determination (R2) = 0.87, mean bias error (MBE) = 0.04, standard error of estimate (SEE) = 0.10, volume error (VE) = 0.15, variance of the distribution of differences ({S}d2) = 0.004. The developed SEM showed better performance in estimating SM than Topp empirical model which is based only on σ o. By using the developed SEM, top soil SM can be estimated with low mean absolute percent error (MAPE) = 1.39 and can be used for operational applications.

Investigation of empirical damping laws for the space shuttle

NASA Technical Reports Server (NTRS)

Bernstein, E. L.

1973-01-01

An analysis of dynamic test data from vibration testing of a number of aerospace vehicles was made to develop an empirical structural damping law. A systematic attempt was made to fit dissipated energy/cycle to combinations of all dynamic variables. The best-fit laws for bending, torsion, and longitudinal motion are given, with error bounds. A discussion and estimate are made of error sources. Programs are developed for predicting equivalent linear structural damping coefficients and finding the response of nonlinearly damped structures.

Factor Rotation and Standard Errors in Exploratory Factor Analysis

ERIC Educational Resources Information Center

Zhang, Guangjian; Preacher, Kristopher J.

2015-01-01

In this article, we report a surprising phenomenon: Oblique CF-varimax and oblique CF-quartimax rotation produced similar point estimates for rotated factor loadings and factor correlations but different standard error estimates in an empirical example. Influences of factor rotation on asymptotic standard errors are investigated using a numerical…

Derivation of respiration rate from ambulatory ECG and PPG using Ensemble Empirical Mode Decomposition: Comparison and fusion.

PubMed

Orphanidou, Christina

2017-02-01

A new method for extracting the respiratory rate from ECG and PPG obtained via wearable sensors is presented. The proposed technique employs Ensemble Empirical Mode Decomposition in order to identify the respiration "mode" from the noise-corrupted Heart Rate Variability/Pulse Rate Variability and Amplitude Modulation signals extracted from ECG and PPG signals. The technique was validated with respect to a Respiratory Impedance Pneumography (RIP) signal using the mean absolute and the average relative errors for a group ambulatory hospital patients. We compared approaches using single respiration-induced modulations on the ECG and PPG signals with approaches fusing the different modulations. Additionally, we investigated whether the presence of both the simultaneously recorded ECG and PPG signals provided a benefit in the overall system performance. Our method outperformed state-of-the-art ECG- and PPG-based algorithms and gave the best results over the whole database with a mean error of 1.8bpm for 1min estimates when using the fused ECG modulations, which was a relative error of 10.3%. No statistically significant differences were found when comparing the ECG-, PPG- and ECG/PPG-based approaches, indicating that the PPG can be used as a valid alternative to the ECG for applications using wearable sensors. While the presence of both the ECG and PPG signals did not provide an improvement in the estimation error, it increased the proportion of windows for which an estimate was obtained by at least 9%, indicating that the use of two simultaneously recorded signals might be desirable in high-acuity cases where an RR estimate is required more frequently. Copyright © 2016 Elsevier Ltd. All rights reserved.

Using Fault Trees to Advance Understanding of Diagnostic Errors.

PubMed

Rogith, Deevakar; Iyengar, M Sriram; Singh, Hardeep

2017-11-01

Diagnostic errors annually affect at least 5% of adults in the outpatient setting in the United States. Formal analytic techniques are only infrequently used to understand them, in part because of the complexity of diagnostic processes and clinical work flows involved. In this article, diagnostic errors were modeled using fault tree analysis (FTA), a form of root cause analysis that has been successfully used in other high-complexity, high-risk contexts. How factors contributing to diagnostic errors can be systematically modeled by FTA to inform error understanding and error prevention is demonstrated. A team of three experts reviewed 10 published cases of diagnostic error and constructed fault trees. The fault trees were modeled according to currently available conceptual frameworks characterizing diagnostic error. The 10 trees were then synthesized into a single fault tree to identify common contributing factors and pathways leading to diagnostic error. FTA is a visual, structured, deductive approach that depicts the temporal sequence of events and their interactions in a formal logical hierarchy. The visual FTA enables easier understanding of causative processes and cognitive and system factors, as well as rapid identification of common pathways and interactions in a unified fashion. In addition, it enables calculation of empirical estimates for causative pathways. Thus, fault trees might provide a useful framework for both quantitative and qualitative analysis of diagnostic errors. Future directions include establishing validity and reliability by modeling a wider range of error cases, conducting quantitative evaluations, and undertaking deeper exploration of other FTA capabilities. Copyright © 2017 The Joint Commission. Published by Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

2016-08-01

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

Case Mis-Conceptualization in Psychological Treatment: An Enduring Clinical Problem.

PubMed

Ridley, Charles R; Jeffrey, Christina E; Roberson, Richard B

2017-04-01

Case conceptualization, an integral component of mental health treatment, aims to facilitate therapeutic gains by formulating a clear picture of a client's psychological presentation. However, despite numerous attempts to improve this clinical activity, it remains unclear how well existing methods achieve their purported purpose. Case formulation is inconsistently defined in the literature and implemented in practice, with many methods varying in complexity, theoretical grounding, and empirical support. In addition, many of the methods demand a precise clinical acumen that is easily influenced by judgmental and inferential errors. These errors occur regardless of clinicians' level of training or amount of clinical experience. Overall, the lack of a consensus definition, a diversity of methods, and susceptibility of clinicians to errors are manifestations of the state of crisis in case conceptualization. This article, the 2nd in a series of 5 on thematic mapping, argues the need for more reliable and valid models of case conceptualization. © 2017 Wiley Periodicals, Inc.

A highly accurate ab initio potential energy surface for methane.

PubMed

Owens, Alec; Yurchenko, Sergei N; Yachmenev, Andrey; Tennyson, Jonathan; Thiel, Walter

2016-09-14

A new nine-dimensional potential energy surface (PES) for methane has been generated using state-of-the-art ab initio theory. The PES is based on explicitly correlated coupled cluster calculations with extrapolation to the complete basis set limit and incorporates a range of higher-level additive energy corrections. These include core-valence electron correlation, higher-order coupled cluster terms beyond perturbative triples, scalar relativistic effects, and the diagonal Born-Oppenheimer correction. Sub-wavenumber accuracy is achieved for the majority of experimentally known vibrational energy levels with the four fundamentals of (12)CH4 reproduced with a root-mean-square error of 0.70 cm(-1). The computed ab initio equilibrium C-H bond length is in excellent agreement with previous values despite pure rotational energies displaying minor systematic errors as J (rotational excitation) increases. It is shown that these errors can be significantly reduced by adjusting the equilibrium geometry. The PES represents the most accurate ab initio surface to date and will serve as a good starting point for empirical refinement.

Accounting for sampling error when inferring population synchrony from time-series data: a Bayesian state-space modelling approach with applications.

PubMed

Santin-Janin, Hugues; Hugueny, Bernard; Aubry, Philippe; Fouchet, David; Gimenez, Olivier; Pontier, Dominique

2014-01-01

Data collected to inform time variations in natural population size are tainted by sampling error. Ignoring sampling error in population dynamics models induces bias in parameter estimators, e.g., density-dependence. In particular, when sampling errors are independent among populations, the classical estimator of the synchrony strength (zero-lag correlation) is biased downward. However, this bias is rarely taken into account in synchrony studies although it may lead to overemphasizing the role of intrinsic factors (e.g., dispersal) with respect to extrinsic factors (the Moran effect) in generating population synchrony as well as to underestimating the extinction risk of a metapopulation. The aim of this paper was first to illustrate the extent of the bias that can be encountered in empirical studies when sampling error is neglected. Second, we presented a space-state modelling approach that explicitly accounts for sampling error when quantifying population synchrony. Third, we exemplify our approach with datasets for which sampling variance (i) has been previously estimated, and (ii) has to be jointly estimated with population synchrony. Finally, we compared our results to those of a standard approach neglecting sampling variance. We showed that ignoring sampling variance can mask a synchrony pattern whatever its true value and that the common practice of averaging few replicates of population size estimates poorly performed at decreasing the bias of the classical estimator of the synchrony strength. The state-space model used in this study provides a flexible way of accurately quantifying the strength of synchrony patterns from most population size data encountered in field studies, including over-dispersed count data. We provided a user-friendly R-program and a tutorial example to encourage further studies aiming at quantifying the strength of population synchrony to account for uncertainty in population size estimates.

Accounting for Sampling Error When Inferring Population Synchrony from Time-Series Data: A Bayesian State-Space Modelling Approach with Applications

PubMed Central

Santin-Janin, Hugues; Hugueny, Bernard; Aubry, Philippe; Fouchet, David; Gimenez, Olivier; Pontier, Dominique

2014-01-01

Background Data collected to inform time variations in natural population size are tainted by sampling error. Ignoring sampling error in population dynamics models induces bias in parameter estimators, e.g., density-dependence. In particular, when sampling errors are independent among populations, the classical estimator of the synchrony strength (zero-lag correlation) is biased downward. However, this bias is rarely taken into account in synchrony studies although it may lead to overemphasizing the role of intrinsic factors (e.g., dispersal) with respect to extrinsic factors (the Moran effect) in generating population synchrony as well as to underestimating the extinction risk of a metapopulation. Methodology/Principal findings The aim of this paper was first to illustrate the extent of the bias that can be encountered in empirical studies when sampling error is neglected. Second, we presented a space-state modelling approach that explicitly accounts for sampling error when quantifying population synchrony. Third, we exemplify our approach with datasets for which sampling variance (i) has been previously estimated, and (ii) has to be jointly estimated with population synchrony. Finally, we compared our results to those of a standard approach neglecting sampling variance. We showed that ignoring sampling variance can mask a synchrony pattern whatever its true value and that the common practice of averaging few replicates of population size estimates poorly performed at decreasing the bias of the classical estimator of the synchrony strength. Conclusion/Significance The state-space model used in this study provides a flexible way of accurately quantifying the strength of synchrony patterns from most population size data encountered in field studies, including over-dispersed count data. We provided a user-friendly R-program and a tutorial example to encourage further studies aiming at quantifying the strength of population synchrony to account for uncertainty in population size estimates. PMID:24489839

Distribution of the two-sample t-test statistic following blinded sample size re-estimation.

PubMed

Lu, Kaifeng

2016-05-01

We consider the blinded sample size re-estimation based on the simple one-sample variance estimator at an interim analysis. We characterize the exact distribution of the standard two-sample t-test statistic at the final analysis. We describe a simulation algorithm for the evaluation of the probability of rejecting the null hypothesis at given treatment effect. We compare the blinded sample size re-estimation method with two unblinded methods with respect to the empirical type I error, the empirical power, and the empirical distribution of the standard deviation estimator and final sample size. We characterize the type I error inflation across the range of standardized non-inferiority margin for non-inferiority trials, and derive the adjusted significance level to ensure type I error control for given sample size of the internal pilot study. We show that the adjusted significance level increases as the sample size of the internal pilot study increases. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A five-step procedure for the clinical use of the MPD in neuropsychological assessment of children.

PubMed

Wallbrown, F H; Fuller, G B

1984-01-01

Described a five-step procedure that can be used to detect organicity on the basis of children's performance on the Minnesota Percepto Diagnostic Test (MPD). The first step consists of examining the T score for rotations to determine whether it is below the cut-off score, which has been established empirically as an indicator of organicity. The second step consists of matching the examinee's configuration of error scores, separation of circle-diamond (SpCD), distortion of circle-diamond (DCD), and distortion of dots (DD), with empirically derived tables. The third step consists of considering the T score for rotations and error configuration jointly. The fourth step consists of using empirically established discriminant equations, and the fifth step involves using data from limits testing and other data sources. The clinical and empirical bases for the five-step procedure also are discussed.

A second generation experiment in fault-tolerant software

NASA Technical Reports Server (NTRS)

Knight, J. C.

1986-01-01

Information was collected on the efficacy of fault-tolerant software by conducting two large-scale controlled experiments. In the first, an empirical study of multi-version software (MVS) was conducted. The second experiment is an empirical evaluation of self testing as a method of error detection (STED). The purpose ot the MVS experiment was to obtain empirical measurement of the performance of multi-version systems. Twenty versions of a program were prepared at four different sites under reasonably realistic development conditions from the same specifications. The purpose of the STED experiment was to obtain empirical measurements of the performance of assertions in error detection. Eight versions of a program were modified to include assertions at two different sites under controlled conditions. The overall structure of the testing environment for the MVS experiment and its status are described. Work to date in the STED experiment is also presented.

Protograph-Based Raptor-Like Codes

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Chen, Tsung-Yi; Wang, Jiadong; Wesel, Richard D.

2014-01-01

Theoretical analysis has long indicated that feedback improves the error exponent but not the capacity of pointto- point memoryless channels. The analytic and empirical results indicate that at short blocklength regime, practical rate-compatible punctured convolutional (RCPC) codes achieve low latency with the use of noiseless feedback. In 3GPP, standard rate-compatible turbo codes (RCPT) did not outperform the convolutional codes in the short blocklength regime. The reason is the convolutional codes for low number of states can be decoded optimally using Viterbi decoder. Despite excellent performance of convolutional codes at very short blocklengths, the strength of convolutional codes does not scale with the blocklength for a fixed number of states in its trellis.

The effects of time-varying observation errors on semi-empirical sea-level projections

DOE PAGES

Ruckert, Kelsey L.; Guan, Yawen; Bakker, Alexander M. R.; ...

2016-11-30

Sea-level rise is a key driver of projected flooding risks. The design of strategies to manage these risks often hinges on projections that inform decision-makers about the surrounding uncertainties. Producing semi-empirical sea-level projections is difficult, for example, due to the complexity of the error structure of the observations, such as time-varying (heteroskedastic) observation errors and autocorrelation of the data-model residuals. This raises the question of how neglecting the error structure impacts hindcasts and projections. Here, we quantify this effect on sea-level projections and parameter distributions by using a simple semi-empirical sea-level model. Specifically, we compare three model-fitting methods: a frequentistmore » bootstrap as well as a Bayesian inversion with and without considering heteroskedastic residuals. All methods produce comparable hindcasts, but the parametric distributions and projections differ considerably based on methodological choices. In conclusion, our results show that the differences based on the methodological choices are enhanced in the upper tail projections. For example, the Bayesian inversion accounting for heteroskedasticity increases the sea-level anomaly with a 1% probability of being equaled or exceeded in the year 2050 by about 34% and about 40% in the year 2100 compared to a frequentist bootstrap. These results indicate that neglecting known properties of the observation errors and the data-model residuals can lead to low-biased sea-level projections.« less

The effects of time-varying observation errors on semi-empirical sea-level projections

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

Ruckert, Kelsey L.; Guan, Yawen; Bakker, Alexander M. R.

Sea-level rise is a key driver of projected flooding risks. The design of strategies to manage these risks often hinges on projections that inform decision-makers about the surrounding uncertainties. Producing semi-empirical sea-level projections is difficult, for example, due to the complexity of the error structure of the observations, such as time-varying (heteroskedastic) observation errors and autocorrelation of the data-model residuals. This raises the question of how neglecting the error structure impacts hindcasts and projections. Here, we quantify this effect on sea-level projections and parameter distributions by using a simple semi-empirical sea-level model. Specifically, we compare three model-fitting methods: a frequentistmore » bootstrap as well as a Bayesian inversion with and without considering heteroskedastic residuals. All methods produce comparable hindcasts, but the parametric distributions and projections differ considerably based on methodological choices. In conclusion, our results show that the differences based on the methodological choices are enhanced in the upper tail projections. For example, the Bayesian inversion accounting for heteroskedasticity increases the sea-level anomaly with a 1% probability of being equaled or exceeded in the year 2050 by about 34% and about 40% in the year 2100 compared to a frequentist bootstrap. These results indicate that neglecting known properties of the observation errors and the data-model residuals can lead to low-biased sea-level projections.« less

An empirical model for estimating solar radiation in the Algerian Sahara

NASA Astrophysics Data System (ADS)

Benatiallah, Djelloul; Benatiallah, Ali; Bouchouicha, Kada; Hamouda, Messaoud; Nasri, Bahous

2018-05-01

The present work aims to determine the empirical model R.sun that will allow us to evaluate the solar radiation flues on a horizontal plane and in clear-sky on the located Adrar city (27°18 N and 0°11 W) of Algeria and compare with the results measured at the localized site. The expected results of this comparison are of importance for the investment study of solar systems (solar power plants for electricity production, CSP) and also for the design and performance analysis of any system using the solar energy. Statistical indicators used to evaluate the accuracy of the model where the mean bias error (MBE), root mean square error (RMSE) and coefficient of determination. The results show that for global radiation, the daily correlation coefficient is 0.9984. The mean absolute percentage error is 9.44 %. The daily mean bias error is -7.94 %. The daily root mean square error is 12.31 %.

Research and application of a novel hybrid decomposition-ensemble learning paradigm with error correction for daily PM10 forecasting

NASA Astrophysics Data System (ADS)

Luo, Hongyuan; Wang, Deyun; Yue, Chenqiang; Liu, Yanling; Guo, Haixiang

2018-03-01

In this paper, a hybrid decomposition-ensemble learning paradigm combining error correction is proposed for improving the forecast accuracy of daily PM10 concentration. The proposed learning paradigm is consisted of the following two sub-models: (1) PM10 concentration forecasting model; (2) error correction model. In the proposed model, fast ensemble empirical mode decomposition (FEEMD) and variational mode decomposition (VMD) are applied to disassemble original PM10 concentration series and error sequence, respectively. The extreme learning machine (ELM) model optimized by cuckoo search (CS) algorithm is utilized to forecast the components generated by FEEMD and VMD. In order to prove the effectiveness and accuracy of the proposed model, two real-world PM10 concentration series respectively collected from Beijing and Harbin located in China are adopted to conduct the empirical study. The results show that the proposed model performs remarkably better than all other considered models without error correction, which indicates the superior performance of the proposed model.

SAMPLING DISTRIBUTIONS OF ERROR IN MULTIDIMENSIONAL SCALING.

ERIC Educational Resources Information Center

STAKE, ROBERT E.; AND OTHERS

AN EMPIRICAL STUDY WAS MADE OF THE ERROR FACTORS IN MULTIDIMENSIONAL SCALING (MDS) TO REFINE THE USE OF MDS FOR MORE EXPERT MANIPULATION OF SCALES USED IN EDUCATIONAL MEASUREMENT. THE PURPOSE OF THE RESEARCH WAS TO GENERATE TABLES OF THE SAMPLING DISTRIBUTIONS THAT ARE NECESSARY FOR DISCRIMINATING BETWEEN ERROR AND NONERROR MDS DIMENSIONS. THE…

Estimation of an Occupational Choice Model when Occupations Are Misclassified

ERIC Educational Resources Information Center

Sullivan, Paul

2009-01-01

This paper develops an empirical occupational choice model that corrects for misclassification in occupational choices and measurement error in occupation-specific work experience. The model is used to estimate the extent of measurement error in occupation data and quantify the bias that results from ignoring measurement error in occupation codes…

A Unified Approach to Measurement Error and Missing Data: Details and Extensions

ERIC Educational Resources Information Center

Blackwell, Matthew; Honaker, James; King, Gary

2017-01-01

We extend a unified and easy-to-use approach to measurement error and missing data. In our companion article, Blackwell, Honaker, and King give an intuitive overview of the new technique, along with practical suggestions and empirical applications. Here, we offer more precise technical details, more sophisticated measurement error model…

A simulation study to quantify the impacts of exposure measurement error on air pollution health risk estimates in copollutant time-series models.

EPA Science Inventory

BackgroundExposure measurement error in copollutant epidemiologic models has the potential to introduce bias in relative risk (RR) estimates. A simulation study was conducted using empirical data to quantify the impact of correlated measurement errors in time-series analyses of a...

Learning from Errors in Dual Vocational Education: Video-Enhanced Instructional Strategies

ERIC Educational Resources Information Center

Cattaneo, Alberto A. P.; Boldrini, Elena

2017-01-01

Purpose: Starting from the identification of some theoretically driven instructional principles, this paper presents a set of empirical cases based on strategies to learn from errors. The purpose of this paper is to provide first evidence about the feasibility and the effectiveness for learning of video-enhanced error-based strategies in…

A simulation study to quantify the impacts of exposure ...

EPA Pesticide Factsheets

BackgroundExposure measurement error in copollutant epidemiologic models has the potential to introduce bias in relative risk (RR) estimates. A simulation study was conducted using empirical data to quantify the impact of correlated measurement errors in time-series analyses of air pollution and health.MethodsZIP-code level estimates of exposure for six pollutants (CO, NOx, EC, PM2.5, SO4, O3) from 1999 to 2002 in the Atlanta metropolitan area were used to calculate spatial, population (i.e. ambient versus personal), and total exposure measurement error.Empirically determined covariance of pollutant concentration pairs and the associated measurement errors were used to simulate true exposure (exposure without error) from observed exposure. Daily emergency department visits for respiratory diseases were simulated using a Poisson time-series model with a main pollutant RR = 1.05 per interquartile range, and a null association for the copollutant (RR = 1). Monte Carlo experiments were used to evaluate the impacts of correlated exposure errors of different copollutant pairs.ResultsSubstantial attenuation of RRs due to exposure error was evident in nearly all copollutant pairs studied, ranging from 10 to 40% attenuation for spatial error, 3–85% for population error, and 31–85% for total error. When CO, NOx or EC is the main pollutant, we demonstrated the possibility of false positives, specifically identifying significant, positive associations for copoll

Improved model predictive control of resistive wall modes by error field estimator in EXTRAP T2R

NASA Astrophysics Data System (ADS)

Setiadi, A. C.; Brunsell, P. R.; Frassinetti, L.

2016-12-01

Many implementations of a model-based approach for toroidal plasma have shown better control performance compared to the conventional type of feedback controller. One prerequisite of model-based control is the availability of a control oriented model. This model can be obtained empirically through a systematic procedure called system identification. Such a model is used in this work to design a model predictive controller to stabilize multiple resistive wall modes in EXTRAP T2R reversed-field pinch. Model predictive control is an advanced control method that can optimize the future behaviour of a system. Furthermore, this paper will discuss an additional use of the empirical model which is to estimate the error field in EXTRAP T2R. Two potential methods are discussed that can estimate the error field. The error field estimator is then combined with the model predictive control and yields better radial magnetic field suppression.

Error catastrophe and phase transition in the empirical fitness landscape of HIV

NASA Astrophysics Data System (ADS)

Hart, Gregory R.; Ferguson, Andrew L.

2015-03-01

We have translated clinical sequence databases of the p6 HIV protein into an empirical fitness landscape quantifying viral replicative capacity as a function of the amino acid sequence. We show that the viral population resides close to a phase transition in sequence space corresponding to an "error catastrophe" beyond which there is lethal accumulation of mutations. Our model predicts that the phase transition may be induced by drug therapies that elevate the mutation rate, or by forcing mutations at particular amino acids. Applying immune pressure to any combination of killer T-cell targets cannot induce the transition, providing a rationale for why the viral protein can exist close to the error catastrophe without sustaining fatal fitness penalties due to adaptive immunity.

Children and adults both see 'pirates' in 'parties': letter-position effects for developing readers and skilled adult readers.

PubMed

Paterson, Kevin B; Read, Josephine; McGowan, Victoria A; Jordan, Timothy R

2015-03-01

Developing readers often make anagrammatical errors (e.g. misreading pirates as parties), suggesting they use letter position flexibly during word recognition. However, while it is widely assumed that the occurrence of these errors decreases with increases in reading skill, empirical evidence to support this distinction is lacking. Accordingly, we compared the performance of developing child readers (aged 8-10 years) against the end-state performance of skilled adult readers in a timed naming task, employing anagrams used previously in this area of research. Moreover, to explore the use of letter position by developing readers and skilled adult readers more fully, we used anagrams which, to form another word, required letter transpositions over only interior letter positions, or both interior and exterior letter positions. The patterns of effects across these two anagram types for the two groups of readers were very similar. In particular, both groups showed similarly slowed response times (and developing readers increased errors) for anagrams requiring only interior letter transpositions but not for anagrams that required exterior letter transpositions. This similarity in the naming performance of developing readers and skilled adult readers suggests that the end-state skilled use of letter position is established earlier during reading development than is widely assumed. © 2014 John Wiley & Sons Ltd.

A probabilistic tornado wind hazard model for the continental United States

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

Hossain, Q; Kimball, J; Mensing, R

A probabilistic tornado wind hazard model for the continental United States (CONUS) is described. The model incorporates both aleatory (random) and epistemic uncertainties associated with quantifying the tornado wind hazard parameters. The temporal occurrences of tornadoes within the continental United States (CONUS) is assumed to be a Poisson process. A spatial distribution of tornado touchdown locations is developed empirically based on the observed historical events within the CONUS. The hazard model is an aerial probability model that takes into consideration the size and orientation of the facility, the length and width of the tornado damage area (idealized as a rectanglemore » and dependent on the tornado intensity scale), wind speed variation within the damage area, tornado intensity classification errors (i.e.,errors in assigning a Fujita intensity scale based on surveyed damage), and the tornado path direction. Epistemic uncertainties in describing the distributions of the aleatory variables are accounted for by using more than one distribution model to describe aleatory variations. The epistemic uncertainties are based on inputs from a panel of experts. A computer program, TORNADO, has been developed incorporating this model; features of this program are also presented.« less

Quantification of LiDAR measurement uncertainty through propagation of errors due to sensor sub-systems and terrain morphology

NASA Astrophysics Data System (ADS)

Goulden, T.; Hopkinson, C.

2013-12-01

The quantification of LiDAR sensor measurement uncertainty is important for evaluating the quality of derived DEM products, compiling risk assessment of management decisions based from LiDAR information, and enhancing LiDAR mission planning capabilities. Current quality assurance estimates of LiDAR measurement uncertainty are limited to post-survey empirical assessments or vendor estimates from commercial literature. Empirical evidence can provide valuable information for the performance of the sensor in validated areas; however, it cannot characterize the spatial distribution of measurement uncertainty throughout the extensive coverage of typical LiDAR surveys. Vendor advertised error estimates are often restricted to strict and optimal survey conditions, resulting in idealized values. Numerical modeling of individual pulse uncertainty provides an alternative method for estimating LiDAR measurement uncertainty. LiDAR measurement uncertainty is theoretically assumed to fall into three distinct categories, 1) sensor sub-system errors, 2) terrain influences, and 3) vegetative influences. This research details the procedures for numerical modeling of measurement uncertainty from the sensor sub-system (GPS, IMU, laser scanner, laser ranger) and terrain influences. Results show that errors tend to increase as the laser scan angle, altitude or laser beam incidence angle increase. An experimental survey over a flat and paved runway site, performed with an Optech ALTM 3100 sensor, showed an increase in modeled vertical errors of 5 cm, at a nadir scan orientation, to 8 cm at scan edges; for an aircraft altitude of 1200 m and half scan angle of 15°. In a survey with the same sensor, at a highly sloped glacial basin site absent of vegetation, modeled vertical errors reached over 2 m. Validation of error models within the glacial environment, over three separate flight lines, respectively showed 100%, 85%, and 75% of elevation residuals fell below error predictions. Future work in LiDAR sensor measurement uncertainty must focus on the development of vegetative error models to create more robust error prediction algorithms. To achieve this objective, comprehensive empirical exploratory analysis is recommended to relate vegetative parameters to observed errors.

Estimating Concentrations of Road-Salt Constituents in Highway-Runoff from Measurements of Specific Conductance

USGS Publications Warehouse

Granato, Gregory E.; Smith, Kirk P.

1999-01-01

Discrete or composite samples of highway runoff may not adequately represent in-storm water-quality fluctuations because continuous records of water stage, specific conductance, pH, and temperature of the runoff indicate that these properties fluctuate substantially during a storm. Continuous records of water-quality properties can be used to maximize the information obtained about the stormwater runoff system being studied and can provide the context needed to interpret analyses of water samples. Concentrations of the road-salt constituents calcium, sodium, and chloride in highway runoff were estimated from theoretical and empirical relations between specific conductance and the concentrations of these ions. These relations were examined using the analysis of 233 highwayrunoff samples collected from August 1988 through March 1995 at four highway-drainage monitoring stations along State Route 25 in southeastern Massachusetts. Theoretically, the specific conductance of a water sample is the sum of the individual conductances attributed to each ionic species in solution-the product of the concentrations of each ion in milliequivalents per liter (meq/L) multiplied by the equivalent ionic conductance at infinite dilution-thereby establishing the principle of superposition. Superposition provides an estimate of actual specific conductance that is within measurement error throughout the conductance range of many natural waters, with errors of less than ?5 percent below 1,000 microsiemens per centimeter (?S/cm) and ?10 percent between 1,000 and 4,000 ?S/cm if all major ionic constituents are accounted for. A semi-empirical method (adjusted superposition) was used to adjust for concentration effects-superposition-method prediction errors at high and low concentrations-and to relate measured specific conductance to that calculated using superposition. The adjusted superposition method, which was developed to interpret the State Route 25 highway-runoff records, accounts for contributions of constituents other than calcium, sodium, and chloride in dilute waters. The adjusted superposition method also accounts for the attenuation of each constituent's contribution to conductance as ionic strength increases. Use of the adjusted superposition method generally reduced predictive error to within measurement error throughout the range of specific conductance (from 37 to 51,500 ?S/cm) in the highway runoff samples. The effects of pH, temperature, and organic constituents on the relation between concentrations of dissolved constituents and measured specific conductance were examined but these properties did not substantially affect interpretation of the Route 25 data set. Predictive abilities of the adjusted superposition method were similar to results obtained by standard regression techniques, but the adjusted superposition method has several advantages. Adjusted superposition can be applied using available published data about the constituents in precipitation, highway runoff, and the deicing chemicals applied to a highway. This semi-empirical method can be used as a predictive and diagnostic tool before a substantial number of samples are collected, but the power of the regression method is based upon a large number of water-quality analyses that may be affected by a bias in the data.

An experimental study of fault propagation in a jet-engine controller. M.S. Thesis

NASA Technical Reports Server (NTRS)

Choi, Gwan Seung

1990-01-01

An experimental analysis of the impact of transient faults on a microprocessor-based jet engine controller, used in the Boeing 747 and 757 aircrafts is described. A hierarchical simulation environment which allows the injection of transients during run-time and the tracing of their impact is described. Verification of the accuracy of this approach is also provided. A determination of the probability that a transient results in latch, pin or functional errors is made. Given a transient fault, there is approximately an 80 percent chance that there is no impact on the chip. An empirical model to depict the process of error exploration and degeneration in the target system is derived. The model shows that, if no latch errors occur within eight clock cycles, no significant damage is likely to happen. Thus, the overall impact of a transient is well contained. A state transition model is also derived from the measured data, to describe the error propagation characteristics within the chip, and to quantify the impact of transients on the external environment. The model is used to identify and isolate the critical fault propagation paths, the module most sensitive to fault propagation and the module with the highest potential of causing external pin errors.

High performance of chlorophyll-a prediction algorithms based on simulated OLCI Sentinel-3A bands in cyanobacteria-dominated inland waters

NASA Astrophysics Data System (ADS)

Watanabe, Fernanda Sayuri Yoshino; Alcântara, Enner; Stech, José Luiz

2018-07-01

In this research, we have investigated whether the chlorophyll-a (chl a) retrieval algorithms based on OLCI Sentinel-3A bands are suitable for cyanobacteria-dominated waters. Phytoplankton assemblages model optical properties of the water, influencing the performance of bio-optical algorithms. Understanding these processes is important to improve the prediction of photoactive pigments in order to use them as a proxy for trophic state and harmful algal bloom. So that, both empirical and semi-analytical approaches designed for different inland waters were tested. In addition, empirical models were tuned based on dataset collected in situ. The study was conducted in the Funil hydroelectric reservoir, where chl a ranged from 2.33 to 208.68 mg m-3 in May 2012 (austral fall) and 4.37 to 306.03 mg m-3 in October 2012 (austral spring). OLCI Sentinel-3A bands were tested in existing algorithms developed for other sensors and new band combinations were compared to analyze the errors produced. Normalized Difference Chlorophyll Index (NDCI) exhibited the best performance, with a Normalized Root Mean Square Error (NRMSE) of 9.30%. Result showed that wavelength at 665 nm is adequate to estimate chl a, although the maximum pigment absorption band is shifted due to phycocyanin fluorescence at approximately 650 nm.

Inflation of the type I error: investigations on regulatory recommendations for bioequivalence of highly variable drugs.

PubMed

Wonnemann, Meinolf; Frömke, Cornelia; Koch, Armin

2015-01-01

We investigated different evaluation strategies for bioequivalence trials with highly variable drugs on their resulting empirical type I error and empirical power. The classical 'unscaled' crossover design with average bioequivalence evaluation, the Add-on concept of the Japanese guideline, and the current 'scaling' approach of EMA were compared. Simulation studies were performed based on the assumption of a single dose drug administration while changing the underlying intra-individual variability. Inclusion of Add-on subjects following the Japanese concept led to slight increases of the empirical α-error (≈7.5%). For the approach of EMA we noted an unexpected tremendous increase of the rejection rate at a geometric mean ratio of 1.25. Moreover, we detected error rates slightly above the pre-set limit of 5% even at the proposed 'scaled' bioequivalence limits. With the classical 'unscaled' approach and the Japanese guideline concept the goal of reduced subject numbers in bioequivalence trials of HVDs cannot be achieved. On the other hand, widening the acceptance range comes at the price that quite a number of products will be accepted bioequivalent that had not been accepted in the past. A two-stage design with control of the global α therefore seems the better alternative.

Accounting for Sampling Error in Genetic Eigenvalues Using Random Matrix Theory.

PubMed

Sztepanacz, Jacqueline L; Blows, Mark W

2017-07-01

The distribution of genetic variance in multivariate phenotypes is characterized by the empirical spectral distribution of the eigenvalues of the genetic covariance matrix. Empirical estimates of genetic eigenvalues from random effects linear models are known to be overdispersed by sampling error, where large eigenvalues are biased upward, and small eigenvalues are biased downward. The overdispersion of the leading eigenvalues of sample covariance matrices have been demonstrated to conform to the Tracy-Widom (TW) distribution. Here we show that genetic eigenvalues estimated using restricted maximum likelihood (REML) in a multivariate random effects model with an unconstrained genetic covariance structure will also conform to the TW distribution after empirical scaling and centering. However, where estimation procedures using either REML or MCMC impose boundary constraints, the resulting genetic eigenvalues tend not be TW distributed. We show how using confidence intervals from sampling distributions of genetic eigenvalues without reference to the TW distribution is insufficient protection against mistaking sampling error as genetic variance, particularly when eigenvalues are small. By scaling such sampling distributions to the appropriate TW distribution, the critical value of the TW statistic can be used to determine if the magnitude of a genetic eigenvalue exceeds the sampling error for each eigenvalue in the spectral distribution of a given genetic covariance matrix. Copyright © 2017 by the Genetics Society of America.

Using non-empirically tuned range-separated functionals with simulated emission bands to model fluorescence lifetimes.

PubMed

Wong, Z C; Fan, W Y; Chwee, T S; Sullivan, Michael B

2017-08-09

Fluorescence lifetimes were evaluated using TD-DFT under different approximations for the emitting molecule and various exchange-correlation functionals, such as B3LYP, BMK, CAM-B3LYP, LC-BLYP, M06, M06-2X, M11, PBE0, ωB97, ωB97X, LC-BLYP*, and ωB97X* where the range-separation parameters in the last two functionals were tuned in a non-empirical fashion. Changes in the optimised molecular geometries between the ground and electronically excited states were found to affect the quality of the calculated lifetimes significantly, while the inclusion of vibronic features led to further improvements over the assumption of a vertical electronic transition. The LC-BLYP* functional was found to return the most accurate fluorescence lifetimes with unsigned errors that are mostly within 1.5 ns of experimental values.

Household and Living Arrangement Projections at the Subnational Level: An Extended Cohort-Component Approach

PubMed Central

Zeng, Yi; Land, Kenneth C.; Wang, Zhenglian; Gu, Danan

2012-01-01

This article presents the core methodological ideas, empirical assessments, and applications of an extended cohort-component approach (known as the “ProFamy model”) to simultaneously project household composition, living arrangements, and population sizes at the subnational level in the United States. Comparisons of projections from 1990 to 2000 using this approach with census counts in 2000 for each of the 50 states and Washington, DC show that 68.0 %, 17.0 %, 11.2 %, and 3.8 % of the absolute percentage errors are <3.0 %, 3.0 % to 4.99 %, 5.0 % to 9.99 %, and ≥10.0 %, respectively. Another analysis compares average forecast errors between the extended cohort-component approach and the still widely used classic headship-rate method, by projecting number-of-bedrooms–specific housing demands from 1990 to 2000 and then comparing those projections with census counts in 2000 for each of the 50 states and Washington, DC. The results demonstrate that, compared with the extended cohort-component approach, the headship-rate method produces substantially more serious forecast errors because it cannot project households by size while the extended cohort-component approach projects detailed household sizes. We also present illustrative household and living arrangement projections for the five decades from 2000 to 2050, with medium-, small-, and large-family scenarios for each of the 50 states; Washington, DC; six counties of southern California, and the Minneapolis–St. Paul metropolitan area. Among many interesting numerical outcomes of household and living arrangement projections with medium, low, and high bounds, the aging of American households over the next few decades across all states/areas is particularly striking. Finally, the limitations of the present study and potential future lines of research are discussed. PMID:23208782

A Comparison of Full and Empirical Bayes Techniques for Inferring Sea Level Changes from Tide Gauge Records

NASA Astrophysics Data System (ADS)

Piecuch, C. G.; Huybers, P. J.; Tingley, M.

2016-12-01

Sea level observations from coastal tide gauges are some of the longest instrumental records of the ocean. However, these data can be noisy, biased, and gappy, featuring missing values, and reflecting land motion and local effects. Coping with these issues in a formal manner is a challenging task. Some studies use Bayesian approaches to estimate sea level from tide gauge records, making inference probabilistically. Such methods are typically empirically Bayesian in nature: model parameters are treated as known and assigned point values. But, in reality, parameters are not perfectly known. Empirical Bayes methods thus neglect a potentially important source of uncertainty, and so may overestimate the precision (i.e., underestimate the uncertainty) of sea level estimates. We consider whether empirical Bayes methods underestimate uncertainty in sea level from tide gauge data, comparing to a full Bayes method that treats parameters as unknowns to be solved for along with the sea level field. We develop a hierarchical algorithm that we apply to tide gauge data on the North American northeast coast over 1893-2015. The algorithm is run in full Bayes mode, solving for the sea level process and parameters, and in empirical mode, solving only for the process using fixed parameter values. Error bars on sea level from the empirical method are smaller than from the full Bayes method, and the relative discrepancies increase with time; the 95% credible interval on sea level values from the empirical Bayes method in 1910 and 2010 is 23% and 56% narrower, respectively, than from the full Bayes approach. To evaluate the representativeness of the credible intervals, empirical Bayes and full Bayes methods are applied to corrupted data of a known surrogate field. Using rank histograms to evaluate the solutions, we find that the full Bayes method produces generally reliable error bars, whereas the empirical Bayes method gives too-narrow error bars, such that the 90% credible interval only encompasses 70% of true process values. Results demonstrate that parameter uncertainty is an important source of process uncertainty, and advocate for the fully Bayesian treatment of tide gauge records in ocean circulation and climate studies.

An Alternate Method for Estimating Dynamic Height from XBT Profiles Using Empirical Vertical Modes

NASA Technical Reports Server (NTRS)

Lagerloef, Gary S. E.

1994-01-01

A technique is presented that applies modal decomposition to estimate dynamic height (0-450 db) from Expendable BathyThermograph (XBT) temperature profiles. Salinity-Temperature-Depth (STD) data are used to establish empirical relationships between vertically integrated temperature profiles and empirical dynamic height modes. These are then applied to XBT data to estimate dynamic height. A standard error of 0.028 dynamic meters is obtained for the waters of the Gulf of Alaska- an ocean region subject to substantial freshwater buoyancy forcing and with a T-S relationship that has considerable scatter. The residual error is a substantial improvement relative to the conventional T-S correlation technique when applied to this region. Systematic errors between estimated and true dynamic height were evaluated. The 20-year-long time series at Ocean Station P (50 deg N, 145 deg W) indicated weak variations in the error interannually, but not seasonally. There were no evident systematic alongshore variations in the error in the ocean boundary current regime near the perimeter of the Alaska gyre. The results prove satisfactory for the purpose of this work, which is to generate dynamic height from XBT data for coanalysis with satellite altimeter data, given that the altimeter height precision is likewise on the order of 2-3 cm. While the technique has not been applied to other ocean regions where the T-S relation has less scatter, it is suggested that it could provide some improvement over previously applied methods, as well.

Revealed and stated preference valuation and transfer: A within-sample comparison of water quality improvement values

NASA Astrophysics Data System (ADS)

Ferrini, Silvia; Schaafsma, Marije; Bateman, Ian

2014-06-01

Benefit transfer (BT) methods are becoming increasingly important for environmental policy, but the empirical findings regarding transfer validity are mixed. A novel valuation survey was designed to obtain both stated preference (SP) and revealed preference (RP) data concerning river water quality values from a large sample of households. Both dichotomous choice and payment card contingent valuation (CV) and travel cost (TC) data were collected. Resulting valuations were directly compared and used for BT analyses using both unit value and function transfer approaches. WTP estimates are found to pass the convergence validity test. BT results show that the CV data produce lower transfer errors, below 20% for both unit value and function transfer, than TC data especially when using function transfer. Further, comparison of WTP estimates suggests that in all cases, differences between methods are larger than differences between study areas. Results show that when multiple studies are available, using welfare estimates from the same area but based on a different method consistently results in larger errors than transfers across space keeping the method constant.

On the role of cost-sensitive learning in multi-class brain-computer interfaces.

PubMed

Devlaminck, Dieter; Waegeman, Willem; Wyns, Bart; Otte, Georges; Santens, Patrick

2010-06-01

Brain-computer interfaces (BCIs) present an alternative way of communication for people with severe disabilities. One of the shortcomings in current BCI systems, recently put forward in the fourth BCI competition, is the asynchronous detection of motor imagery versus resting state. We investigated this extension to the three-class case, in which the resting state is considered virtually lying between two motor classes, resulting in a large penalty when one motor task is misclassified into the other motor class. We particularly focus on the behavior of different machine-learning techniques and on the role of multi-class cost-sensitive learning in such a context. To this end, four different kernel methods are empirically compared, namely pairwise multi-class support vector machines (SVMs), two cost-sensitive multi-class SVMs and kernel-based ordinal regression. The experimental results illustrate that ordinal regression performs better than the other three approaches when a cost-sensitive performance measure such as the mean-squared error is considered. By contrast, multi-class cost-sensitive learning enables us to control the number of large errors made between two motor tasks.

Error Rates in Measuring Teacher and School Performance Based on Student Test Score Gains. NCEE 2010-4004

ERIC Educational Resources Information Center

Schochet, Peter Z.; Chiang, Hanley S.

2010-01-01

This paper addresses likely error rates for measuring teacher and school performance in the upper elementary grades using value-added models applied to student test score gain data. Using realistic performance measurement system schemes based on hypothesis testing, we develop error rate formulas based on OLS and Empirical Bayes estimators.…

A simulation study to quantify the impacts of exposure measurement error on air pollution health risk estimates in copollutant time-series models.

PubMed

Dionisio, Kathie L; Chang, Howard H; Baxter, Lisa K

2016-11-25

Exposure measurement error in copollutant epidemiologic models has the potential to introduce bias in relative risk (RR) estimates. A simulation study was conducted using empirical data to quantify the impact of correlated measurement errors in time-series analyses of air pollution and health. ZIP-code level estimates of exposure for six pollutants (CO, NO x , EC, PM 2.5 , SO 4 , O 3 ) from 1999 to 2002 in the Atlanta metropolitan area were used to calculate spatial, population (i.e. ambient versus personal), and total exposure measurement error. Empirically determined covariance of pollutant concentration pairs and the associated measurement errors were used to simulate true exposure (exposure without error) from observed exposure. Daily emergency department visits for respiratory diseases were simulated using a Poisson time-series model with a main pollutant RR = 1.05 per interquartile range, and a null association for the copollutant (RR = 1). Monte Carlo experiments were used to evaluate the impacts of correlated exposure errors of different copollutant pairs. Substantial attenuation of RRs due to exposure error was evident in nearly all copollutant pairs studied, ranging from 10 to 40% attenuation for spatial error, 3-85% for population error, and 31-85% for total error. When CO, NO x or EC is the main pollutant, we demonstrated the possibility of false positives, specifically identifying significant, positive associations for copollutants based on the estimated type I error rate. The impact of exposure error must be considered when interpreting results of copollutant epidemiologic models, due to the possibility of attenuation of main pollutant RRs and the increased probability of false positives when measurement error is present.

A Physiologically Based Pharmacokinetic Model to Predict the Pharmacokinetics of Highly Protein-Bound Drugs and Impact of Errors in Plasma Protein Binding

PubMed Central

Ye, Min; Nagar, Swati; Korzekwa, Ken

2015-01-01

Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data was often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding, and blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for terminal elimination half-life (t1/2, 100% of drugs), peak plasma concentration (Cmax, 100%), area under the plasma concentration-time curve (AUC0–t, 95.4%), clearance (CLh, 95.4%), mean retention time (MRT, 95.4%), and steady state volume (Vss, 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. PMID:26531057

Applications systems verification and transfer project. Volume 1: Operational applications of satellite snow cover observations: Executive summary. [usefulness of satellite snow-cover data for water yield prediction

NASA Technical Reports Server (NTRS)

Rango, A.

1981-01-01

Both LANDSAT and NOAA satellite data were used in improving snowmelt runoff forecasts. When the satellite snow cover data were tested in both empirical seasonal runoff estimation and short term modeling approaches, a definite potential for reducing forecast error was evident. A cost benefit analysis run in conjunction with the snow mapping indicated a $36.5 million annual benefit accruing from a one percent improvement in forecast accuracy using the snow cover data for the western United States. The annual cost of employing the system would be $505,000. The snow mapping has proven that satellite snow cover data can be used to reduce snowmelt runoff forecast error in a cost effective manner once all operational satellite data are available within 72 hours after acquisition. Executive summaries of the individual snow mapping projects are presented.

Thermospheric density variations: Observability using precision satellite orbits and effects on orbit propagation

NASA Astrophysics Data System (ADS)

Lechtenberg, Travis; McLaughlin, Craig A.; Locke, Travis; Krishna, Dhaval Mysore

2013-01-01

paper examines atmospheric density estimated using precision orbit ephemerides (POE) from the CHAMP and GRACE satellites during short periods of greater atmospheric density variability. The results of the calibration of CHAMP densities derived using POEs with those derived using accelerometers are examined for three different types of density perturbations, [traveling atmospheric disturbances (TADs), geomagnetic cusp phenomena, and midnight density maxima] in order to determine the temporal resolution of POE solutions. In addition, the densities are compared to High-Accuracy Satellite Drag Model (HASDM) densities to compare temporal resolution for both types of corrections. The resolution for these models of thermospheric density was found to be inadequate to sufficiently characterize the short-term density variations examined here. Also examined in this paper is the effect of differing density estimation schemes by propagating an initial orbit state forward in time and examining induced errors. The propagated POE-derived densities incurred errors of a smaller magnitude than the empirical models and errors on the same scale or better than those incurred using the HASDM model.

Quantifying the burden of opioid medication errors in adult oncology and palliative care settings: A systematic review.

PubMed

Heneka, Nicole; Shaw, Tim; Rowett, Debra; Phillips, Jane L

2016-06-01

Opioids are the primary pharmacological treatment for cancer pain and, in the palliative care setting, are routinely used to manage symptoms at the end of life. Opioids are one of the most frequently reported drug classes in medication errors causing patient harm. Despite their widespread use, little is known about the incidence and impact of opioid medication errors in oncology and palliative care settings. To determine the incidence, types and impact of reported opioid medication errors in adult oncology and palliative care patient settings. A systematic review. Five electronic databases and the grey literature were searched from 1980 to August 2014. Empirical studies published in English, reporting data on opioid medication error incidence, types or patient impact, within adult oncology and/or palliative care services, were included. Popay's narrative synthesis approach was used to analyse data. Five empirical studies were included in this review. Opioid error incidence rate was difficult to ascertain as each study focussed on a single narrow area of error. The predominant error type related to deviation from opioid prescribing guidelines, such as incorrect dosing intervals. None of the included studies reported the degree of patient harm resulting from opioid errors. This review has highlighted the paucity of the literature examining opioid error incidence, types and patient impact in adult oncology and palliative care settings. Defining, identifying and quantifying error reporting practices for these populations should be an essential component of future oncology and palliative care quality and safety initiatives. © The Author(s) 2015.

An empirical assessment of exposure measurement errors and effect attenuation in bi-pollutant epidemiologic models

EPA Science Inventory

Using multipollutant models to understand the combined health effects of exposure to multiple pollutants is becoming more common. However, the complex relationships between pollutants and differing degrees of exposure error across pollutants can make health effect estimates from ...

An empirical assessment of exposure measurement error and effect attenuation in bi-pollutant epidemiologic models

EPA Science Inventory

Background: Using multipollutant models to understand combined health effects of exposure to multiple pollutants is becoming more common. However, complex relationships between pollutants and differing degrees of exposure error across pollutants can make health effect estimates f...

Simultaneous treatment of unspecified heteroskedastic model error distribution and mismeasured covariates for restricted moment models.

PubMed

Garcia, Tanya P; Ma, Yanyuan

2017-10-01

We develop consistent and efficient estimation of parameters in general regression models with mismeasured covariates. We assume the model error and covariate distributions are unspecified, and the measurement error distribution is a general parametric distribution with unknown variance-covariance. We construct root- n consistent, asymptotically normal and locally efficient estimators using the semiparametric efficient score. We do not estimate any unknown distribution or model error heteroskedasticity. Instead, we form the estimator under possibly incorrect working distribution models for the model error, error-prone covariate, or both. Empirical results demonstrate robustness to different incorrect working models in homoscedastic and heteroskedastic models with error-prone covariates.

Stated Choice design comparison in a developing country: recall and attribute nonattendance

PubMed Central

2014-01-01

Background Experimental designs constitute a vital component of all Stated Choice (aka discrete choice experiment) studies. However, there exists limited empirical evaluation of the statistical benefits of Stated Choice (SC) experimental designs that employ non-zero prior estimates in constructing non-orthogonal constrained designs. This paper statistically compares the performance of contrasting SC experimental designs. In so doing, the effect of respondent literacy on patterns of Attribute non-Attendance (ANA) across fractional factorial orthogonal and efficient designs is also evaluated. The study uses a ‘real’ SC design to model consumer choice of primary health care providers in rural north India. A total of 623 respondents were sampled across four villages in Uttar Pradesh, India. Methods Comparison of orthogonal and efficient SC experimental designs is based on several measures. Appropriate comparison of each design’s respective efficiency measure is made using D-error results. Standardised Akaike Information Criteria are compared between designs and across recall periods. Comparisons control for stated and inferred ANA. Coefficient and standard error estimates are also compared. Results The added complexity of the efficient SC design, theorised elsewhere, is reflected in higher estimated amounts of ANA among illiterate respondents. However, controlling for ANA using stated and inferred methods consistently shows that the efficient design performs statistically better. Modelling SC data from the orthogonal and efficient design shows that model-fit of the efficient design outperform the orthogonal design when using a 14-day recall period. The performance of the orthogonal design, with respect to standardised AIC model-fit, is better when longer recall periods of 30-days, 6-months and 12-months are used. Conclusions The effect of the efficient design’s cognitive demand is apparent among literate and illiterate respondents, although, more pronounced among illiterate respondents. This study empirically confirms that relaxing the orthogonality constraint of SC experimental designs increases the information collected in choice tasks, subject to the accuracy of the non-zero priors in the design and the correct specification of a ‘real’ SC recall period. PMID:25386388

New GRACE-Derived Storage Change Estimates Using Empirical Mode Extraction

NASA Astrophysics Data System (ADS)

Aierken, A.; Lee, H.; Yu, H.; Ate, P.; Hossain, F.; Basnayake, S. B.; Jayasinghe, S.; Saah, D. S.; Shum, C. K.

2017-12-01

Estimated mass change from GRACE spherical harmonic solutions have north/south stripes and east/west banded errors due to random noise and modeling errors. Low pass filters like decorrelation and Gaussian smoothing are typically applied to reduce noise and errors. However, these filters introduce leakage errors that need to be addressed. GRACE mascon estimates (JPL and CSR mascon solutions) do not need decorrelation or Gaussian smoothing and offer larger signal magnitudes compared to the GRACE spherical harmonics (SH) filtered results. However, a recent study [Chen et al., JGR, 2017] demonstrated that both JPL and CSR mascon solutions also have leakage errors. We developed a new postprocessing method based on empirical mode decomposition to estimate mass change from GRACE SH solutions without decorrelation and Gaussian smoothing, the two main sources of leakage errors. We found that, without any post processing, the noise and errors in spherical harmonic solutions introduced very clear high frequency components in the spatial domain. By removing these high frequency components and reserve the overall pattern of the signal, we obtained better mass estimates with minimum leakage errors. The new global mass change estimates captured all the signals observed by GRACE without the stripe errors. Results were compared with traditional methods over the Tonle Sap Basin in Cambodia, Northwestern India, Central Valley in California, and the Caspian Sea. Our results provide larger signal magnitudes which are in good agreement with the leakage corrected (forward modeled) SH results.

Linkage analysis of quantitative refraction and refractive errors in the Beaver Dam Eye Study.

PubMed

Klein, Alison P; Duggal, Priya; Lee, Kristine E; Cheng, Ching-Yu; Klein, Ronald; Bailey-Wilson, Joan E; Klein, Barbara E K

2011-07-13

Refraction, as measured by spherical equivalent, is the need for an external lens to focus images on the retina. While genetic factors play an important role in the development of refractive errors, few susceptibility genes have been identified. However, several regions of linkage have been reported for myopia (2q, 4q, 7q, 12q, 17q, 18p, 22q, and Xq) and for quantitative refraction (1p, 3q, 4q, 7p, 8p, and 11p). To replicate previously identified linkage peaks and to identify novel loci that influence quantitative refraction and refractive errors, linkage analysis of spherical equivalent, myopia, and hyperopia in the Beaver Dam Eye Study was performed. Nonparametric, sibling-pair, genome-wide linkage analyses of refraction (spherical equivalent adjusted for age, education, and nuclear sclerosis), myopia and hyperopia in 834 sibling pairs within 486 extended pedigrees were performed. Suggestive evidence of linkage was found for hyperopia on chromosome 3, region q26 (empiric P = 5.34 × 10(-4)), a region that had shown significant genome-wide evidence of linkage to refraction and some evidence of linkage to hyperopia. In addition, the analysis replicated previously reported genome-wide significant linkages to 22q11 of adjusted refraction and myopia (empiric P = 4.43 × 10(-3) and 1.48 × 10(-3), respectively) and to 7p15 of refraction (empiric P = 9.43 × 10(-4)). Evidence was also found of linkage to refraction on 7q36 (empiric P = 2.32 × 10(-3)), a region previously linked to high myopia. The findings provide further evidence that genes controlling refractive errors are located on 3q26, 7p15, 7p36, and 22q11.

Modelling vertical error in LiDAR-derived digital elevation models

NASA Astrophysics Data System (ADS)

Aguilar, Fernando J.; Mills, Jon P.; Delgado, Jorge; Aguilar, Manuel A.; Negreiros, J. G.; Pérez, José L.

2010-01-01

A hybrid theoretical-empirical model has been developed for modelling the error in LiDAR-derived digital elevation models (DEMs) of non-open terrain. The theoretical component seeks to model the propagation of the sample data error (SDE), i.e. the error from light detection and ranging (LiDAR) data capture of ground sampled points in open terrain, towards interpolated points. The interpolation methods used for infilling gaps may produce a non-negligible error that is referred to as gridding error. In this case, interpolation is performed using an inverse distance weighting (IDW) method with the local support of the five closest neighbours, although it would be possible to utilize other interpolation methods. The empirical component refers to what is known as "information loss". This is the error purely due to modelling the continuous terrain surface from only a discrete number of points plus the error arising from the interpolation process. The SDE must be previously calculated from a suitable number of check points located in open terrain and assumes that the LiDAR point density was sufficiently high to neglect the gridding error. For model calibration, data for 29 study sites, 200×200 m in size, belonging to different areas around Almeria province, south-east Spain, were acquired by means of stereo photogrammetric methods. The developed methodology was validated against two different LiDAR datasets. The first dataset used was an Ordnance Survey (OS) LiDAR survey carried out over a region of Bristol in the UK. The second dataset was an area located at Gador mountain range, south of Almería province, Spain. Both terrain slope and sampling density were incorporated in the empirical component through the calibration phase, resulting in a very good agreement between predicted and observed data (R2 = 0.9856 ; p < 0.001). In validation, Bristol observed vertical errors, corresponding to different LiDAR point densities, offered a reasonably good fit to the predicted errors. Even better results were achieved in the more rugged morphology of the Gador mountain range dataset. The findings presented in this article could be used as a guide for the selection of appropriate operational parameters (essentially point density in order to optimize survey cost), in projects related to LiDAR survey in non-open terrain, for instance those projects dealing with forestry applications.

Action errors, error management, and learning in organizations.

PubMed

Frese, Michael; Keith, Nina

2015-01-03

Every organization is confronted with errors. Most errors are corrected easily, but some may lead to negative consequences. Organizations often focus on error prevention as a single strategy for dealing with errors. Our review suggests that error prevention needs to be supplemented by error management--an approach directed at effectively dealing with errors after they have occurred, with the goal of minimizing negative and maximizing positive error consequences (examples of the latter are learning and innovations). After defining errors and related concepts, we review research on error-related processes affected by error management (error detection, damage control). Empirical evidence on positive effects of error management in individuals and organizations is then discussed, along with emotional, motivational, cognitive, and behavioral pathways of these effects. Learning from errors is central, but like other positive consequences, learning occurs under certain circumstances--one being the development of a mind-set of acceptance of human error.

Efficacy of monitoring and empirical predictive modeling at improving public health protection at Chicago beaches

USGS Publications Warehouse

Nevers, Meredith B.; Whitman, Richard L.

2011-01-01

Efforts to improve public health protection in recreational swimming waters have focused on obtaining real-time estimates of water quality. Current monitoring techniques rely on the time-intensive culturing of fecal indicator bacteria (FIB) from water samples, but rapidly changing FIB concentrations result in management errors that lead to the public being exposed to high FIB concentrations (type II error) or beaches being closed despite acceptable water quality (type I error). Empirical predictive models may provide a rapid solution, but their effectiveness at improving health protection has not been adequately assessed. We sought to determine if emerging monitoring approaches could effectively reduce risk of illness exposure by minimizing management errors. We examined four monitoring approaches (inactive, current protocol, a single predictive model for all beaches, and individual models for each beach) with increasing refinement at 14 Chicago beaches using historical monitoring and hydrometeorological data and compared management outcomes using different standards for decision-making. Predictability (R2) of FIB concentration improved with model refinement at all beaches but one. Predictive models did not always reduce the number of management errors and therefore the overall illness burden. Use of a Chicago-specific single-sample standard-rather than the default 235 E. coli CFU/100 ml widely used-together with predictive modeling resulted in the greatest number of open beach days without any increase in public health risk. These results emphasize that emerging monitoring approaches such as empirical models are not equally applicable at all beaches, and combining monitoring approaches may expand beach access.

Evaluation of a new model of aeolian transport in the presence of vegetation

USGS Publications Warehouse

Li, Junran; Okin, Gregory S.; Herrick, Jeffrey E.; Belnap, Jayne; Miller, Mark E.; Vest, Kimberly; Draut, Amy E.

2013-01-01

Aeolian transport is an important characteristic of many arid and semiarid regions worldwide that affects dust emission and ecosystem processes. The purpose of this paper is to evaluate a recent model of aeolian transport in the presence of vegetation. This approach differs from previous models by accounting for how vegetation affects the distribution of shear velocity on the surface rather than merely calculating the average effect of vegetation on surface shear velocity or simply using empirical relationships. Vegetation, soil, and meteorological data at 65 field sites with measurements of horizontal aeolian flux were collected from the Western United States. Measured fluxes were tested against modeled values to evaluate model performance, to obtain a set of optimum model parameters, and to estimate the uncertainty in these parameters. The same field data were used to model horizontal aeolian flux using three other schemes. Our results show that the model can predict horizontal aeolian flux with an approximate relative error of 2.1 and that further empirical corrections can reduce the approximate relative error to 1.0. The level of error is within what would be expected given uncertainties in threshold shear velocity and wind speed at our sites. The model outperforms the alternative schemes both in terms of approximate relative error and the number of sites at which threshold shear velocity was exceeded. These results lend support to an understanding of the physics of aeolian transport in which (1) vegetation's impact on transport is dependent upon the distribution of vegetation rather than merely its average lateral cover and (2) vegetation impacts surface shear stress locally by depressing it in the immediate lee of plants rather than by changing the bulk surface's threshold shear velocity. Our results also suggest that threshold shear velocity is exceeded more than might be estimated by single measurements of threshold shear stress and roughness length commonly associated with vegetated surfaces, highlighting the variation of threshold shear velocity with space and time in real landscapes.

High incorrect use of the standard error of the mean (SEM) in original articles in three cardiovascular journals evaluated for 2012.

PubMed

Wullschleger, Marcel; Aghlmandi, Soheila; Egger, Marcel; Zwahlen, Marcel

2014-01-01

In biomedical journals authors sometimes use the standard error of the mean (SEM) for data description, which has been called inappropriate or incorrect. To assess the frequency of incorrect use of SEM in articles in three selected cardiovascular journals. All original journal articles published in 2012 in Cardiovascular Research, Circulation: Heart Failure and Circulation Research were assessed by two assessors for inappropriate use of SEM when providing descriptive information of empirical data. We also assessed whether the authors state in the methods section that the SEM will be used for data description. Of 441 articles included in this survey, 64% (282 articles) contained at least one instance of incorrect use of the SEM, with two journals having a prevalence above 70% and "Circulation: Heart Failure" having the lowest value (27%). In 81% of articles with incorrect use of SEM, the authors had explicitly stated that they use the SEM for data description and in 89% SEM bars were also used instead of 95% confidence intervals. Basic science studies had a 7.4-fold higher level of inappropriate SEM use (74%) than clinical studies (10%). The selection of the three cardiovascular journals was based on a subjective initial impression of observing inappropriate SEM use. The observed results are not representative for all cardiovascular journals. In three selected cardiovascular journals we found a high level of inappropriate SEM use and explicit methods statements to use it for data description, especially in basic science studies. To improve on this situation, these and other journals should provide clear instructions to authors on how to report descriptive information of empirical data.

Empirically Defined Patterns of Executive Function Deficits in Schizophrenia and Their Relation to Everyday Functioning: A Person-Centered Approach

PubMed Central

Iampietro, Mary; Giovannetti, Tania; Drabick, Deborah A. G.; Kessler, Rachel K.

2013-01-01

Executive function (EF) deficits in schizophrenia (SZ) are well documented, although much less is known about patterns of EF deficits and their association to differential impairments in everyday functioning. The present study empirically defined SZ groups based on measures of various EF abilities and then compared these EF groups on everyday action errors. Participants (n=45) completed various subtests from the Delis–Kaplan Executive Function System (D-KEFS) and the Naturalistic Action Test (NAT), a performance-based measure of everyday action that yields scores reflecting total errors and a range of different error types (e.g., omission, perseveration). Results of a latent class analysis revealed three distinct EF groups, characterized by (a) multiple EF deficits, (b) relatively spared EF, and (c) perseverative responding. Follow-up analyses revealed that the classes differed significantly on NAT total errors, total commission errors, and total perseveration errors; the two classes with EF impairment performed comparably on the NAT but performed worse than the class with relatively spared EF. In sum, people with SZ demonstrate variable patterns of EF deficits, and distinct aspects of these EF deficit patterns (i.e., poor mental control abilities) may be associated with everyday functioning capabilities. PMID:23035705

Spatial Resolution, Grayscale, and Error Diffusion Trade-offs: Impact on Display System Design

NASA Technical Reports Server (NTRS)

Gille, Jennifer L. (Principal Investigator)

1996-01-01

We examine technology trade-offs related to grayscale resolution, spatial resolution, and error diffusion for tessellated display systems. We present new empirical results from our psychophysical study of these trade-offs and compare them to the predictions of a model of human vision.

Wind Power Forecasting Error Frequency Analyses for Operational Power System Studies: Preprint

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

Florita, A.; Hodge, B. M.; Milligan, M.

2012-08-01

The examination of wind power forecasting errors is crucial for optimal unit commitment and economic dispatch of power systems with significant wind power penetrations. This scheduling process includes both renewable and nonrenewable generators, and the incorporation of wind power forecasts will become increasingly important as wind fleets constitute a larger portion of generation portfolios. This research considers the Western Wind and Solar Integration Study database of wind power forecasts and numerical actualizations. This database comprises more than 30,000 locations spread over the western United States, with a total wind power capacity of 960 GW. Error analyses for individual sites andmore » for specific balancing areas are performed using the database, quantifying the fit to theoretical distributions through goodness-of-fit metrics. Insights into wind-power forecasting error distributions are established for various levels of temporal and spatial resolution, contrasts made among the frequency distribution alternatives, and recommendations put forth for harnessing the results. Empirical data are used to produce more realistic site-level forecasts than previously employed, such that higher resolution operational studies are possible. This research feeds into a larger work of renewable integration through the links wind power forecasting has with various operational issues, such as stochastic unit commitment and flexible reserve level determination.« less

Application of empirical and dynamical closure methods to simple climate models

NASA Astrophysics Data System (ADS)

Padilla, Lauren Elizabeth

This dissertation applies empirically- and physically-based methods for closure of uncertain parameters and processes to three model systems that lie on the simple end of climate model complexity. Each model isolates one of three sources of closure uncertainty: uncertain observational data, large dimension, and wide ranging length scales. They serve as efficient test systems toward extension of the methods to more realistic climate models. The empirical approach uses the Unscented Kalman Filter (UKF) to estimate the transient climate sensitivity (TCS) parameter in a globally-averaged energy balance model. Uncertainty in climate forcing and historical temperature make TCS difficult to determine. A range of probabilistic estimates of TCS computed for various assumptions about past forcing and natural variability corroborate ranges reported in the IPCC AR4 found by different means. Also computed are estimates of how quickly uncertainty in TCS may be expected to diminish in the future as additional observations become available. For higher system dimensions the UKF approach may become prohibitively expensive. A modified UKF algorithm is developed in which the error covariance is represented by a reduced-rank approximation, substantially reducing the number of model evaluations required to provide probability densities for unknown parameters. The method estimates the state and parameters of an abstract atmospheric model, known as Lorenz 96, with accuracy close to that of a full-order UKF for 30-60% rank reduction. The physical approach to closure uses the Multiscale Modeling Framework (MMF) to demonstrate closure of small-scale, nonlinear processes that would not be resolved directly in climate models. A one-dimensional, abstract test model with a broad spatial spectrum is developed. The test model couples the Kuramoto-Sivashinsky equation to a transport equation that includes cloud formation and precipitation-like processes. In the test model, three main sources of MMF error are evaluated independently. Loss of nonlinear multi-scale interactions and periodic boundary conditions in closure models were dominant sources of error. Using a reduced order modeling approach to maximize energy content allowed reduction of the closure model dimension up to 75% without loss in accuracy. MMF and a comparable alternative model peformed equally well compared to direct numerical simulation.

Precise leveling, space geodesy and geodynamics

NASA Technical Reports Server (NTRS)

Reilinger, R.

1981-01-01

The implications of currently available leveling data on understanding the crustal dynamics of the continental United States are investigated. Neotectonic deformation, near surface movements, systematic errors in releveling measurements, and the implications of this information for earthquake prediction are described. Vertical crustal movements in the vicinity of the 1931 Valentine, Texas, earthquake which may represent coseismic deformation are investigated. The detection of vertical fault displacements by precise leveling in western Kentucky is reported. An empirical basis for defining releveling anomalies and its implications for crustal deformation in southern California is presented. Releveling measurements in the eastern United States and their meaning in the context of possible crustal deformation, including uplift of the Appalachian Mountains, eastward tilting of the Atlantic Coastal Plain, and apparent movements associated with a number of structural features along the east coast, are reported.

Get Over It! A Multilevel Threshold Autoregressive Model for State-Dependent Affect Regulation.

PubMed

De Haan-Rietdijk, Silvia; Gottman, John M; Bergeman, Cindy S; Hamaker, Ellen L

2016-03-01

Intensive longitudinal data provide rich information, which is best captured when specialized models are used in the analysis. One of these models is the multilevel autoregressive model, which psychologists have applied successfully to study affect regulation as well as alcohol use. A limitation of this model is that the autoregressive parameter is treated as a fixed, trait-like property of a person. We argue that the autoregressive parameter may be state-dependent, for example, if the strength of affect regulation depends on the intensity of affect experienced. To allow such intra-individual variation, we propose a multilevel threshold autoregressive model. Using simulations, we show that this model can be used to detect state-dependent regulation with adequate power and Type I error. The potential of the new modeling approach is illustrated with two empirical applications that extend the basic model to address additional substantive research questions.

Practical guidance on representing the heteroscedasticity of residual errors of hydrological predictions

NASA Astrophysics Data System (ADS)

McInerney, David; Thyer, Mark; Kavetski, Dmitri; Kuczera, George

2016-04-01

Appropriate representation of residual errors in hydrological modelling is essential for accurate and reliable probabilistic streamflow predictions. In particular, residual errors of hydrological predictions are often heteroscedastic, with large errors associated with high runoff events. Although multiple approaches exist for representing this heteroscedasticity, few if any studies have undertaken a comprehensive evaluation and comparison of these approaches. This study fills this research gap by evaluating a range of approaches for representing heteroscedasticity in residual errors. These approaches include the 'direct' weighted least squares approach and 'transformational' approaches, such as logarithmic, Box-Cox (with and without fitting the transformation parameter), logsinh and the inverse transformation. The study reports (1) theoretical comparison of heteroscedasticity approaches, (2) empirical evaluation of heteroscedasticity approaches using a range of multiple catchments / hydrological models / performance metrics and (3) interpretation of empirical results using theory to provide practical guidance on the selection of heteroscedasticity approaches. Importantly, for hydrological practitioners, the results will simplify the choice of approaches to represent heteroscedasticity. This will enhance their ability to provide hydrological probabilistic predictions with the best reliability and precision for different catchment types (e.g. high/low degree of ephemerality).

Large-scale compensation of errors in pairwise-additive empirical force fields: comparison of AMBER intermolecular terms with rigorous DFT-SAPT calculations.

PubMed

Zgarbová, Marie; Otyepka, Michal; Sponer, Jirí; Hobza, Pavel; Jurecka, Petr

2010-09-21

The intermolecular interaction energy components for several molecular complexes were calculated using force fields available in the AMBER suite of programs and compared with Density Functional Theory-Symmetry Adapted Perturbation Theory (DFT-SAPT) values. The extent to which such comparison is meaningful is discussed. The comparability is shown to depend strongly on the intermolecular distance, which means that comparisons made at one distance only are of limited value. At large distances the coulombic and van der Waals 1/r(6) empirical terms correspond fairly well with the DFT-SAPT electrostatics and dispersion terms, respectively. At the onset of electronic overlap the empirical values deviate from the reference values considerably. However, the errors in the force fields tend to cancel out in a systematic manner at equilibrium distances. Thus, the overall performance of the force fields displays errors an order of magnitude smaller than those of the individual interaction energy components. The repulsive 1/r(12) component of the van der Waals expression seems to be responsible for a significant part of the deviation of the force field results from the reference values. We suggest that further improvement of the force fields for intermolecular interactions would require replacement of the nonphysical 1/r(12) term by an exponential function. Dispersion anisotropy and its effects are discussed. Our analysis is intended to show that although comparing the empirical and non-empirical interaction energy components is in general problematic, it might bring insights useful for the construction of new force fields. Our results are relevant to often performed force-field-based interaction energy decompositions.

Analysis of basic clustering algorithms for numerical estimation of statistical averages in biomolecules.

PubMed

Anandakrishnan, Ramu; Onufriev, Alexey

2008-03-01

In statistical mechanics, the equilibrium properties of a physical system of particles can be calculated as the statistical average over accessible microstates of the system. In general, these calculations are computationally intractable since they involve summations over an exponentially large number of microstates. Clustering algorithms are one of the methods used to numerically approximate these sums. The most basic clustering algorithms first sub-divide the system into a set of smaller subsets (clusters). Then, interactions between particles within each cluster are treated exactly, while all interactions between different clusters are ignored. These smaller clusters have far fewer microstates, making the summation over these microstates, tractable. These algorithms have been previously used for biomolecular computations, but remain relatively unexplored in this context. Presented here, is a theoretical analysis of the error and computational complexity for the two most basic clustering algorithms that were previously applied in the context of biomolecular electrostatics. We derive a tight, computationally inexpensive, error bound for the equilibrium state of a particle computed via these clustering algorithms. For some practical applications, it is the root mean square error, which can be significantly lower than the error bound, that may be more important. We how that there is a strong empirical relationship between error bound and root mean square error, suggesting that the error bound could be used as a computationally inexpensive metric for predicting the accuracy of clustering algorithms for practical applications. An example of error analysis for such an application-computation of average charge of ionizable amino-acids in proteins-is given, demonstrating that the clustering algorithm can be accurate enough for practical purposes.

A physiologically based pharmacokinetic model to predict the pharmacokinetics of highly protein-bound drugs and the impact of errors in plasma protein binding.

PubMed

Ye, Min; Nagar, Swati; Korzekwa, Ken

2016-04-01

Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data were often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding and the blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate the model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for the terminal elimination half-life (t1/2 , 100% of drugs), peak plasma concentration (Cmax , 100%), area under the plasma concentration-time curve (AUC0-t , 95.4%), clearance (CLh , 95.4%), mean residence time (MRT, 95.4%) and steady state volume (Vss , 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Methods to achieve accurate projection of regional and global raster databases

USGS Publications Warehouse

Usery, E.L.; Seong, J.C.; Steinwand, D.R.; Finn, M.P.

2002-01-01

This research aims at building a decision support system (DSS) for selecting an optimum projection considering various factors, such as pixel size, areal extent, number of categories, spatial pattern of categories, resampling methods, and error correction methods. Specifically, this research will investigate three goals theoretically and empirically and, using the already developed empirical base of knowledge with these results, develop an expert system for map projection of raster data for regional and global database modeling. The three theoretical goals are as follows: (1) The development of a dynamic projection that adjusts projection formulas for latitude on the basis of raster cell size to maintain equal-sized cells. (2) The investigation of the relationships between the raster representation and the distortion of features, number of categories, and spatial pattern. (3) The development of an error correction and resampling procedure that is based on error analysis of raster projection.

Estimation of pulse rate from ambulatory PPG using ensemble empirical mode decomposition and adaptive thresholding.

PubMed

Pittara, Melpo; Theocharides, Theocharis; Orphanidou, Christina

2017-07-01

A new method for deriving pulse rate from PPG obtained from ambulatory patients is presented. The method employs Ensemble Empirical Mode Decomposition to identify the pulsatile component from noise-corrupted PPG, and then uses a set of physiologically-relevant rules followed by adaptive thresholding, in order to estimate the pulse rate in the presence of noise. The method was optimized and validated using 63 hours of data obtained from ambulatory hospital patients. The F1 score obtained with respect to expertly annotated data was 0.857 and the mean absolute errors of estimated pulse rates with respect to heart rates obtained from ECG collected in parallel were 1.72 bpm for "good" quality PPG and 4.49 bpm for "bad" quality PPG. Both errors are within the clinically acceptable margin-of-error for pulse rate/heart rate measurements, showing the promise of the proposed approach for inclusion in next generation wearable sensors.

A study of digital holographic filters generation. Phase 2: Digital data communication system, volume 1

NASA Technical Reports Server (NTRS)

Ingels, F. M.; Mo, C. D.

1978-01-01

An empirical study of the performance of the Viterbi decoders in bursty channels was carried out and an improved algebraic decoder for nonsystematic codes was developed. The hybrid algorithm was simulated for the (2,1), k = 7 code on a computer using 20 channels having various error statistics, ranging from pure random error to pure bursty channels. The hybrid system outperformed both the algebraic and the Viterbi decoders in every case, except the 1% random error channel where the Viterbi decoder had one bit less decoding error.

Accurate 3D reconstruction by a new PDS-OSEM algorithm for HRRT

NASA Astrophysics Data System (ADS)

Chen, Tai-Been; Horng-Shing Lu, Henry; Kim, Hang-Keun; Son, Young-Don; Cho, Zang-Hee

2014-03-01

State-of-the-art high resolution research tomography (HRRT) provides high resolution PET images with full 3D human brain scanning. But, a short time frame in dynamic study causes many problems related to the low counts in the acquired data. The PDS-OSEM algorithm was proposed to reconstruct the HRRT image with a high signal-to-noise ratio that provides accurate information for dynamic data. The new algorithm was evaluated by simulated image, empirical phantoms, and real human brain data. Meanwhile, the time activity curve was adopted to validate a reconstructed performance of dynamic data between PDS-OSEM and OP-OSEM algorithms. According to simulated and empirical studies, the PDS-OSEM algorithm reconstructs images with higher quality, higher accuracy, less noise, and less average sum of square error than those of OP-OSEM. The presented algorithm is useful to provide quality images under the condition of low count rates in dynamic studies with a short scan time.

A framework for simulating map error in ecosystem models

Treesearch

Sean P. Healey; Shawn P. Urbanski; Paul L. Patterson; Chris Garrard

2014-01-01

The temporal depth and spatial breadth of observations from platforms such as Landsat provide unique perspective on ecosystem dynamics, but the integration of these observations into formal decision support will rely upon improved uncertainty accounting. Monte Carlo (MC) simulations offer a practical, empirical method of accounting for potential map errors in broader...

An improved empirical model for diversity gain on Earth-space propagation paths

NASA Technical Reports Server (NTRS)

Hodge, D. B.

1981-01-01

An empirical model was generated to estimate diversity gain on Earth-space propagation paths as a function of Earth terminal separation distance, link frequency, elevation angle, and angle between the baseline and the path azimuth. The resulting model reproduces the entire experimental data set with an RMS error of 0.73 dB.

A Robust Semi-Parametric Test for Detecting Trait-Dependent Diversification.

PubMed

Rabosky, Daniel L; Huang, Huateng

2016-03-01

Rates of species diversification vary widely across the tree of life and there is considerable interest in identifying organismal traits that correlate with rates of speciation and extinction. However, it has been challenging to develop methodological frameworks for testing hypotheses about trait-dependent diversification that are robust to phylogenetic pseudoreplication and to directionally biased rates of character change. We describe a semi-parametric test for trait-dependent diversification that explicitly requires replicated associations between character states and diversification rates to detect effects. To use the method, diversification rates are reconstructed across a phylogenetic tree with no consideration of character states. A test statistic is then computed to measure the association between species-level traits and the corresponding diversification rate estimates at the tips of the tree. The empirical value of the test statistic is compared to a null distribution that is generated by structured permutations of evolutionary rates across the phylogeny. The test is applicable to binary discrete characters as well as continuous-valued traits and can accommodate extremely sparse sampling of character states at the tips of the tree. We apply the test to several empirical data sets and demonstrate that the method has acceptable Type I error rates. © The Author(s) 2015. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Losses from effluent taxes and quotas under uncertainty

USGS Publications Warehouse

Watson, W.D.; Ridker, R.G.

1984-01-01

Recent theoretical papers by Adar and Griffin (J. Environ. Econ. Manag.3, 178-188 (1976)), Fishelson (J. Environ. Econ. Manag.3, 189-197 (1976)), and Weitzman (Rev. Econ. Studies41, 477-491 (1974)) show that,different expected social losses arise from using effluent taxes and quotas as alternative control instruments when marginal control costs are uncertain. Key assumptions in these analyses are linear marginal cost and benefit functions and an additive error for the marginal cost function (to reflect uncertainty). In this paper, empirically derived nonlinear functions and more realistic multiplicative error terms are used to estimate expected control and damage costs and to identify (empirically) the mix of control instruments that minimizes expected losses. ?? 1984.

Mapping from disease-specific measures to health-state utility values in individuals with migraine.

PubMed

Gillard, Patrick J; Devine, Beth; Varon, Sepideh F; Liu, Lei; Sullivan, Sean D

2012-05-01

The objective of this study was to develop empirical algorithms that estimate health-state utility values from disease-specific quality-of-life scores in individuals with migraine. Data from a cross-sectional, multicountry study were used. Individuals with episodic and chronic migraine were randomly assigned to training or validation samples. Spearman's correlation coefficients between paired EuroQol five-dimensional (EQ-5D) questionnaire utility values and both Headache Impact Test (HIT-6) scores and Migraine-Specific Quality-of-Life Questionnaire version 2.1 (MSQ) domain scores (role restrictive, role preventive, and emotional function) were examined. Regression models were constructed to estimate EQ-5D questionnaire utility values from the HIT-6 score or the MSQ domain scores. Preferred algorithms were confirmed in the validation samples. In episodic migraine, the preferred HIT-6 and MSQ algorithms explained 22% and 25% of the variance (R(2)) in the training samples, respectively, and had similar prediction errors (root mean square errors of 0.30). In chronic migraine, the preferred HIT-6 and MSQ algorithms explained 36% and 45% of the variance in the training samples, respectively, and had similar prediction errors (root mean square errors 0.31 and 0.29). In episodic and chronic migraine, no statistically significant differences were observed between the mean observed and the mean estimated EQ-5D questionnaire utility values for the preferred HIT-6 and MSQ algorithms in the validation samples. The relationship between the EQ-5D questionnaire and the HIT-6 or the MSQ is adequate to use regression equations to estimate EQ-5D questionnaire utility values. The preferred HIT-6 and MSQ algorithms will be useful in estimating health-state utilities in migraine trials in which no preference-based measure is present. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

An Empirically Derived Taxonomy of Factors Affecting Physicians' Willingness to Disclose Medical Errors

PubMed Central

Kaldjian, Lauris C; Jones, Elizabeth W; Rosenthal, Gary E; Tripp-Reimer, Toni; Hillis, Stephen L

2006-01-01

BACKGROUND Physician disclosure of medical errors to institutions, patients, and colleagues is important for patient safety, patient care, and professional education. However, the variables that may facilitate or impede disclosure are diverse and lack conceptual organization. OBJECTIVE To develop an empirically derived, comprehensive taxonomy of factors that affects voluntary disclosure of errors by physicians. DESIGN A mixed-methods study using qualitative data collection (structured literature search and exploratory focus groups), quantitative data transformation (sorting and hierarchical cluster analysis), and validation procedures (confirmatory focus groups and expert review). RESULTS Full-text review of 316 articles identified 91 impeding or facilitating factors affecting physicians' willingness to disclose errors. Exploratory focus groups identified an additional 27 factors. Sorting and hierarchical cluster analysis organized factors into 8 domains. Confirmatory focus groups and expert review relocated 6 factors, removed 2 factors, and modified 4 domain names. The final taxonomy contained 4 domains of facilitating factors (responsibility to patient, responsibility to self, responsibility to profession, responsibility to community), and 4 domains of impeding factors (attitudinal barriers, uncertainties, helplessness, fears and anxieties). CONCLUSIONS A taxonomy of facilitating and impeding factors provides a conceptual framework for a complex field of variables that affects physicians' willingness to disclose errors to institutions, patients, and colleagues. This taxonomy can be used to guide the design of studies to measure the impact of different factors on disclosure, to assist in the design of error-reporting systems, and to inform educational interventions to promote the disclosure of errors to patients. PMID:16918739

Sources of Error in Substance Use Prevalence Surveys

PubMed Central

Johnson, Timothy P.

2014-01-01

Population-based estimates of substance use patterns have been regularly reported now for several decades. Concerns with the quality of the survey methodologies employed to produce those estimates date back almost as far. Those concerns have led to a considerable body of research specifically focused on understanding the nature and consequences of survey-based errors in substance use epidemiology. This paper reviews and summarizes that empirical research by organizing it within a total survey error model framework that considers multiple types of representation and measurement errors. Gaps in our knowledge of error sources in substance use surveys and areas needing future research are also identified. PMID:27437511

Improving probabilistic prediction of daily streamflow by identifying Pareto optimal approaches for modeling heteroscedastic residual errors

NASA Astrophysics Data System (ADS)

McInerney, David; Thyer, Mark; Kavetski, Dmitri; Lerat, Julien; Kuczera, George

2017-03-01

Reliable and precise probabilistic prediction of daily catchment-scale streamflow requires statistical characterization of residual errors of hydrological models. This study focuses on approaches for representing error heteroscedasticity with respect to simulated streamflow, i.e., the pattern of larger errors in higher streamflow predictions. We evaluate eight common residual error schemes, including standard and weighted least squares, the Box-Cox transformation (with fixed and calibrated power parameter λ) and the log-sinh transformation. Case studies include 17 perennial and 6 ephemeral catchments in Australia and the United States, and two lumped hydrological models. Performance is quantified using predictive reliability, precision, and volumetric bias metrics. We find the choice of heteroscedastic error modeling approach significantly impacts on predictive performance, though no single scheme simultaneously optimizes all performance metrics. The set of Pareto optimal schemes, reflecting performance trade-offs, comprises Box-Cox schemes with λ of 0.2 and 0.5, and the log scheme (λ = 0, perennial catchments only). These schemes significantly outperform even the average-performing remaining schemes (e.g., across ephemeral catchments, median precision tightens from 105% to 40% of observed streamflow, and median biases decrease from 25% to 4%). Theoretical interpretations of empirical results highlight the importance of capturing the skew/kurtosis of raw residuals and reproducing zero flows. Paradoxically, calibration of λ is often counterproductive: in perennial catchments, it tends to overfit low flows at the expense of abysmal precision in high flows. The log-sinh transformation is dominated by the simpler Pareto optimal schemes listed above. Recommendations for researchers and practitioners seeking robust residual error schemes for practical work are provided.

The impact of 14-nm photomask uncertainties on computational lithography solutions

NASA Astrophysics Data System (ADS)

Sturtevant, John; Tejnil, Edita; Lin, Tim; Schultze, Steffen; Buck, Peter; Kalk, Franklin; Nakagawa, Kent; Ning, Guoxiang; Ackmann, Paul; Gans, Fritz; Buergel, Christian

2013-04-01

Computational lithography solutions rely upon accurate process models to faithfully represent the imaging system output for a defined set of process and design inputs. These models, which must balance accuracy demands with simulation runtime boundary conditions, rely upon the accurate representation of multiple parameters associated with the scanner and the photomask. While certain system input variables, such as scanner numerical aperture, can be empirically tuned to wafer CD data over a small range around the presumed set point, it can be dangerous to do so since CD errors can alias across multiple input variables. Therefore, many input variables for simulation are based upon designed or recipe-requested values or independent measurements. It is known, however, that certain measurement methodologies, while precise, can have significant inaccuracies. Additionally, there are known errors associated with the representation of certain system parameters. With shrinking total CD control budgets, appropriate accounting for all sources of error becomes more important, and the cumulative consequence of input errors to the computational lithography model can become significant. In this work, we examine with a simulation sensitivity study, the impact of errors in the representation of photomask properties including CD bias, corner rounding, refractive index, thickness, and sidewall angle. The factors that are most critical to be accurately represented in the model are cataloged. CD Bias values are based on state of the art mask manufacturing data and other variables changes are speculated, highlighting the need for improved metrology and awareness.

Calculation of Host-Guest Binding Affinities Using a Quantum-Mechanical Energy Model.

PubMed

Muddana, Hari S; Gilson, Michael K

2012-06-12

The prediction of protein-ligand binding affinities is of central interest in computer-aided drug discovery, but it is still difficult to achieve a high degree of accuracy. Recent studies suggesting that available force fields may be a key source of error motivate the present study, which reports the first mining minima (M2) binding affinity calculations based on a quantum mechanical energy model, rather than an empirical force field. We apply a semi-empirical quantum-mechanical energy function, PM6-DH+, coupled with the COSMO solvation model, to 29 host-guest systems with a wide range of measured binding affinities. After correction for a systematic error, which appears to derive from the treatment of polar solvation, the computed absolute binding affinities agree well with experimental measurements, with a mean error 1.6 kcal/mol and a correlation coefficient of 0.91. These calculations also delineate the contributions of various energy components, including solute energy, configurational entropy, and solvation free energy, to the binding free energies of these host-guest complexes. Comparison with our previous calculations, which used empirical force fields, point to significant differences in both the energetic and entropic components of the binding free energy. The present study demonstrates successful combination of a quantum mechanical Hamiltonian with the M2 affinity method.

Reverse Transcription Errors and RNA-DNA Differences at Short Tandem Repeats.

PubMed

Fungtammasan, Arkarachai; Tomaszkiewicz, Marta; Campos-Sánchez, Rebeca; Eckert, Kristin A; DeGiorgio, Michael; Makova, Kateryna D

2016-10-01

Transcript variation has important implications for organismal function in health and disease. Most transcriptome studies focus on assessing variation in gene expression levels and isoform representation. Variation at the level of transcript sequence is caused by RNA editing and transcription errors, and leads to nongenetically encoded transcript variants, or RNA-DNA differences (RDDs). Such variation has been understudied, in part because its detection is obscured by reverse transcription (RT) and sequencing errors. It has only been evaluated for intertranscript base substitution differences. Here, we investigated transcript sequence variation for short tandem repeats (STRs). We developed the first maximum-likelihood estimator (MLE) to infer RT error and RDD rates, taking next generation sequencing error rates into account. Using the MLE, we empirically evaluated RT error and RDD rates for STRs in a large-scale DNA and RNA replicated sequencing experiment conducted in a primate species. The RT error rates increased exponentially with STR length and were biased toward expansions. The RDD rates were approximately 1 order of magnitude lower than the RT error rates. The RT error rates estimated with the MLE from a primate data set were concordant with those estimated with an independent method, barcoded RNA sequencing, from a Caenorhabditis elegans data set. Our results have important implications for medical genomics, as STR allelic variation is associated with >40 diseases. STR nonallelic transcript variation can also contribute to disease phenotype. The MLE and empirical rates presented here can be used to evaluate the probability of disease-associated transcripts arising due to RDD. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Effect of Box-Cox transformation on power of Haseman-Elston and maximum-likelihood variance components tests to detect quantitative trait Loci.

PubMed

Etzel, C J; Shete, S; Beasley, T M; Fernandez, J R; Allison, D B; Amos, C I

2003-01-01

Non-normality of the phenotypic distribution can affect power to detect quantitative trait loci in sib pair studies. Previously, we observed that Winsorizing the sib pair phenotypes increased the power of quantitative trait locus (QTL) detection for both Haseman-Elston (HE) least-squares tests [Hum Hered 2002;53:59-67] and maximum likelihood-based variance components (MLVC) analysis [Behav Genet (in press)]. Winsorizing the phenotypes led to a slight increase in type 1 error in H-E tests and a slight decrease in type I error for MLVC analysis. Herein, we considered transforming the sib pair phenotypes using the Box-Cox family of transformations. Data were simulated for normal and non-normal (skewed and kurtic) distributions. Phenotypic values were replaced by Box-Cox transformed values. Twenty thousand replications were performed for three H-E tests of linkage and the likelihood ratio test (LRT), the Wald test and other robust versions based on the MLVC method. We calculated the relative nominal inflation rate as the ratio of observed empirical type 1 error divided by the set alpha level (5, 1 and 0.1% alpha levels). MLVC tests applied to non-normal data had inflated type I errors (rate ratio greater than 1.0), which were controlled best by Box-Cox transformation and to a lesser degree by Winsorizing. For example, for non-transformed, skewed phenotypes (derived from a chi2 distribution with 2 degrees of freedom), the rates of empirical type 1 error with respect to set alpha level=0.01 were 0.80, 4.35 and 7.33 for the original H-E test, LRT and Wald test, respectively. For the same alpha level=0.01, these rates were 1.12, 3.095 and 4.088 after Winsorizing and 0.723, 1.195 and 1.905 after Box-Cox transformation. Winsorizing reduced inflated error rates for the leptokurtic distribution (derived from a Laplace distribution with mean 0 and variance 8). Further, power (adjusted for empirical type 1 error) at the 0.01 alpha level ranged from 4.7 to 17.3% across all tests using the non-transformed, skewed phenotypes, from 7.5 to 20.1% after Winsorizing and from 12.6 to 33.2% after Box-Cox transformation. Likewise, power (adjusted for empirical type 1 error) using leptokurtic phenotypes at the 0.01 alpha level ranged from 4.4 to 12.5% across all tests with no transformation, from 7 to 19.2% after Winsorizing and from 4.5 to 13.8% after Box-Cox transformation. Thus the Box-Cox transformation apparently provided the best type 1 error control and maximal power among the procedures we considered for analyzing a non-normal, skewed distribution (chi2) while Winzorizing worked best for the non-normal, kurtic distribution (Laplace). We repeated the same simulations using a larger sample size (200 sib pairs) and found similar results. Copyright 2003 S. Karger AG, Basel

MIMO model of an interacting series process for Robust MPC via System Identification.

PubMed

Wibowo, Tri Chandra S; Saad, Nordin

2010-07-01

This paper discusses the empirical modeling using system identification technique with a focus on an interacting series process. The study is carried out experimentally using a gaseous pilot plant as the process, in which the dynamic of such a plant exhibits the typical dynamic of an interacting series process. Three practical approaches are investigated and their performances are evaluated. The models developed are also examined in real-time implementation of a linear model predictive control. The selected model is able to reproduce the main dynamic characteristics of the plant in open-loop and produces zero steady-state errors in closed-loop control system. Several issues concerning the identification process and the construction of a MIMO state space model for a series interacting process are deliberated. 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Asymptotic Standard Errors for Item Response Theory True Score Equating of Polytomous Items

ERIC Educational Resources Information Center

Cher Wong, Cheow

2015-01-01

Building on previous works by Lord and Ogasawara for dichotomous items, this article proposes an approach to derive the asymptotic standard errors of item response theory true score equating involving polytomous items, for equivalent and nonequivalent groups of examinees. This analytical approach could be used in place of empirical methods like…

Context Effects in Multi-Alternative Decision Making: Empirical Data and a Bayesian Model

ERIC Educational Resources Information Center

Hawkins, Guy; Brown, Scott D.; Steyvers, Mark; Wagenmakers, Eric-Jan

2012-01-01

For decisions between many alternatives, the benchmark result is Hick's Law: that response time increases log-linearly with the number of choice alternatives. Even when Hick's Law is observed for response times, divergent results have been observed for error rates--sometimes error rates increase with the number of choice alternatives, and…

A Note on the Specification of Error Structures in Latent Interaction Models

ERIC Educational Resources Information Center

Mao, Xiulin; Harring, Jeffrey R.; Hancock, Gregory R.

2015-01-01

Latent interaction models have motivated a great deal of methodological research, mainly in the area of estimating such models. Product-indicator methods have been shown to be competitive with other methods of estimation in terms of parameter bias and standard error accuracy, and their continued popularity in empirical studies is due, in part, to…

Worldwide Ocean Optics Database (WOOD)

DTIC Science & Technology

2002-09-30

attenuation estimated from diffuse attenuation and backscatter data). Error estimates will also be provided for the computed results. Extensive algorithm...empirical algorithms (e.g., beam attenuation estimated from diffuse attenuation and backscatter data). Error estimates will also be provided for the...properties, including diffuse attenuation, beam attenuation, and scattering. Data from ONR-funded bio-optical cruises will be given priority for loading

Children and Adults Both See "Pirates" in "Parties": Letter-Position Effects for Developing Readers and Skilled Adult Readers

ERIC Educational Resources Information Center

Paterson, Kevin B.; Read, Josephine; McGowan, Victoria A.; Jordan, Timothy R.

2015-01-01

Developing readers often make anagrammatical errors (e.g. misreading pirates as parties), suggesting they use letter position flexibly during word recognition. However, while it is widely assumed that the occurrence of these errors decreases with increases in reading skill, empirical evidence to support this distinction is lacking. Accordingly, we…

Influence of Additive and Multiplicative Structure and Direction of Comparison on the Reversal Error

ERIC Educational Resources Information Center

González-Calero, José Antonio; Arnau, David; Laserna-Belenguer, Belén

2015-01-01

An empirical study has been carried out to evaluate the potential of word order matching and static comparison as explanatory models of reversal error. Data was collected from 214 undergraduate students who translated a set of additive and multiplicative comparisons expressed in Spanish into algebraic language. In these multiplicative comparisons…

A systematic framework for Monte Carlo simulation of remote sensing errors map in carbon assessments

Treesearch

S. Healey; P. Patterson; S. Urbanski

2014-01-01

Remotely sensed observations can provide unique perspective on how management and natural disturbance affect carbon stocks in forests. However, integration of these observations into formal decision support will rely upon improved uncertainty accounting. Monte Carlo (MC) simulations offer a practical, empirical method of accounting for potential remote sensing errors...

Analyzing Multilevel Data: An Empirical Comparison of Parameter Estimates of Hierarchical Linear Modeling and Ordinary Least Squares Regression

ERIC Educational Resources Information Center

Rocconi, Louis M.

2011-01-01

Hierarchical linear models (HLM) solve the problems associated with the unit of analysis problem such as misestimated standard errors, heterogeneity of regression and aggregation bias by modeling all levels of interest simultaneously. Hierarchical linear modeling resolves the problem of misestimated standard errors by incorporating a unique random…

Linkage Analysis of Quantitative Refraction and Refractive Errors in the Beaver Dam Eye Study

PubMed Central

Duggal, Priya; Lee, Kristine E.; Cheng, Ching-Yu; Klein, Ronald; Bailey-Wilson, Joan E.; Klein, Barbara E. K.

2011-01-01

Purpose. Refraction, as measured by spherical equivalent, is the need for an external lens to focus images on the retina. While genetic factors play an important role in the development of refractive errors, few susceptibility genes have been identified. However, several regions of linkage have been reported for myopia (2q, 4q, 7q, 12q, 17q, 18p, 22q, and Xq) and for quantitative refraction (1p, 3q, 4q, 7p, 8p, and 11p). To replicate previously identified linkage peaks and to identify novel loci that influence quantitative refraction and refractive errors, linkage analysis of spherical equivalent, myopia, and hyperopia in the Beaver Dam Eye Study was performed. Methods. Nonparametric, sibling-pair, genome-wide linkage analyses of refraction (spherical equivalent adjusted for age, education, and nuclear sclerosis), myopia and hyperopia in 834 sibling pairs within 486 extended pedigrees were performed. Results. Suggestive evidence of linkage was found for hyperopia on chromosome 3, region q26 (empiric P = 5.34 × 10−4), a region that had shown significant genome-wide evidence of linkage to refraction and some evidence of linkage to hyperopia. In addition, the analysis replicated previously reported genome-wide significant linkages to 22q11 of adjusted refraction and myopia (empiric P = 4.43 × 10−3 and 1.48 × 10−3, respectively) and to 7p15 of refraction (empiric P = 9.43 × 10−4). Evidence was also found of linkage to refraction on 7q36 (empiric P = 2.32 × 10−3), a region previously linked to high myopia. Conclusions. The findings provide further evidence that genes controlling refractive errors are located on 3q26, 7p15, 7p36, and 22q11. PMID:21571680

Reduced-Rank Array Modes of the California Current Observing System

NASA Astrophysics Data System (ADS)

Moore, Andrew M.; Arango, Hernan G.; Edwards, Christopher A.

2018-01-01

The information content of the ocean observing array spanning the U.S. west coast is explored using the reduced-rank array modes (RAMs) derived from a four-dimensional variational (4D-Var) data assimilation system covering a period of three decades. RAMs are an extension of the original formulation of array modes introduced by Bennett (1985) but in the reduced model state-space explored by the 4D-Var system, and reveal the extent to which this space is activated by the observations. The projection of the RAMs onto the empirical orthogonal functions (EOFs) of the 4D-Var background error correlation matrix provides a quantitative measure of the effectiveness of the measurements in observing the circulation. It is found that much of the space spanned by the background error covariance is unconstrained by the present ocean observing system. The RAM spectrum is also used to introduce a new criterion to prevent 4D-Var from overfitting the model to the observations.

How Many Alternatives Can Be Ranked? A Comparison of the Paired Comparison and Ranking Methods.

PubMed

Ock, Minsu; Yi, Nari; Ahn, Jeonghoon; Jo, Min-Woo

2016-01-01

To determine the feasibility of converting ranking data into paired comparison (PC) data and suggest the number of alternatives that can be ranked by comparing a PC and a ranking method. Using a total of 222 health states, a household survey was conducted in a sample of 300 individuals from the general population. Each respondent performed a PC 15 times and a ranking method 6 times (two attempts of ranking three, four, and five health states, respectively). The health states of the PC and the ranking method were constructed to overlap each other. We converted the ranked data into PC data and examined the consistency of the response rate. Applying probit regression, we obtained the predicted probability of each method. Pearson correlation coefficients were determined between the predicted probabilities of those methods. The mean absolute error was also assessed between the observed and the predicted values. The overall consistency of the response rate was 82.8%. The Pearson correlation coefficients were 0.789, 0.852, and 0.893 for ranking three, four, and five health states, respectively. The lowest mean absolute error was 0.082 (95% confidence interval [CI] 0.074-0.090) in ranking five health states, followed by 0.123 (95% CI 0.111-0.135) in ranking four health states and 0.126 (95% CI 0.113-0.138) in ranking three health states. After empirically examining the consistency of the response rate between a PC and a ranking method, we suggest that using five alternatives in the ranking method may be superior to using three or four alternatives. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Empirical Correction to the Likelihood Ratio Statistic for Structural Equation Modeling with Many Variables.

PubMed

Yuan, Ke-Hai; Tian, Yubin; Yanagihara, Hirokazu

2015-06-01

Survey data typically contain many variables. Structural equation modeling (SEM) is commonly used in analyzing such data. The most widely used statistic for evaluating the adequacy of a SEM model is T ML, a slight modification to the likelihood ratio statistic. Under normality assumption, T ML approximately follows a chi-square distribution when the number of observations (N) is large and the number of items or variables (p) is small. However, in practice, p can be rather large while N is always limited due to not having enough participants. Even with a relatively large N, empirical results show that T ML rejects the correct model too often when p is not too small. Various corrections to T ML have been proposed, but they are mostly heuristic. Following the principle of the Bartlett correction, this paper proposes an empirical approach to correct T ML so that the mean of the resulting statistic approximately equals the degrees of freedom of the nominal chi-square distribution. Results show that empirically corrected statistics follow the nominal chi-square distribution much more closely than previously proposed corrections to T ML, and they control type I errors reasonably well whenever N ≥ max(50,2p). The formulations of the empirically corrected statistics are further used to predict type I errors of T ML as reported in the literature, and they perform well.

Improving Bayesian credibility intervals for classifier error rates using maximum entropy empirical priors.

PubMed

Gustafsson, Mats G; Wallman, Mikael; Wickenberg Bolin, Ulrika; Göransson, Hanna; Fryknäs, M; Andersson, Claes R; Isaksson, Anders

2010-06-01

Successful use of classifiers that learn to make decisions from a set of patient examples require robust methods for performance estimation. Recently many promising approaches for determination of an upper bound for the error rate of a single classifier have been reported but the Bayesian credibility interval (CI) obtained from a conventional holdout test still delivers one of the tightest bounds. The conventional Bayesian CI becomes unacceptably large in real world applications where the test set sizes are less than a few hundred. The source of this problem is that fact that the CI is determined exclusively by the result on the test examples. In other words, there is no information at all provided by the uniform prior density distribution employed which reflects complete lack of prior knowledge about the unknown error rate. Therefore, the aim of the study reported here was to study a maximum entropy (ME) based approach to improved prior knowledge and Bayesian CIs, demonstrating its relevance for biomedical research and clinical practice. It is demonstrated how a refined non-uniform prior density distribution can be obtained by means of the ME principle using empirical results from a few designs and tests using non-overlapping sets of examples. Experimental results show that ME based priors improve the CIs when employed to four quite different simulated and two real world data sets. An empirically derived ME prior seems promising for improving the Bayesian CI for the unknown error rate of a designed classifier. Copyright 2010 Elsevier B.V. All rights reserved.

Life Prediction of Large Lithium-Ion Battery Packs with Active and Passive Balancing

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

Shi, Ying; Smith, Kandler A; Zane, Regan

Lithium-ion battery packs take a major part of large-scale stationary energy storage systems. One challenge in reducing battery pack cost is to reduce pack size without compromising pack service performance and lifespan. Prognostic life model can be a powerful tool to handle the state of health (SOH) estimate and enable active life balancing strategy to reduce cell imbalance and extend pack life. This work proposed a life model using both empirical and physical-based approaches. The life model described the compounding effect of different degradations on the entire cell with an empirical model. Then its lower-level submodels considered the complex physicalmore » links between testing statistics (state of charge level, C-rate level, duty cycles, etc.) and the degradation reaction rates with respect to specific aging mechanisms. The hybrid approach made the life model generic, robust and stable regardless of battery chemistry and application usage. The model was validated with a custom pack with both passive and active balancing systems implemented, which created four different aging paths in the pack. The life model successfully captured the aging trajectories of all four paths. The life model prediction errors on capacity fade and resistance growth were within +/-3% and +/-5% of the experiment measurements.« less

Sampling errors in the estimation of empirical orthogonal functions. [for climatology studies

NASA Technical Reports Server (NTRS)

North, G. R.; Bell, T. L.; Cahalan, R. F.; Moeng, F. J.

1982-01-01

Empirical Orthogonal Functions (EOF's), eigenvectors of the spatial cross-covariance matrix of a meteorological field, are reviewed with special attention given to the necessary weighting factors for gridded data and the sampling errors incurred when too small a sample is available. The geographical shape of an EOF shows large intersample variability when its associated eigenvalue is 'close' to a neighboring one. A rule of thumb indicating when an EOF is likely to be subject to large sampling fluctuations is presented. An explicit example, based on the statistics of the 500 mb geopotential height field, displays large intersample variability in the EOF's for sample sizes of a few hundred independent realizations, a size seldom exceeded by meteorological data sets.

Estimating Climatological Bias Errors for the Global Precipitation Climatology Project (GPCP)

NASA Technical Reports Server (NTRS)

Adler, Robert; Gu, Guojun; Huffman, George

2012-01-01

A procedure is described to estimate bias errors for mean precipitation by using multiple estimates from different algorithms, satellite sources, and merged products. The Global Precipitation Climatology Project (GPCP) monthly product is used as a base precipitation estimate, with other input products included when they are within +/- 50% of the GPCP estimates on a zonal-mean basis (ocean and land separately). The standard deviation s of the included products is then taken to be the estimated systematic, or bias, error. The results allow one to examine monthly climatologies and the annual climatology, producing maps of estimated bias errors, zonal-mean errors, and estimated errors over large areas such as ocean and land for both the tropics and the globe. For ocean areas, where there is the largest question as to absolute magnitude of precipitation, the analysis shows spatial variations in the estimated bias errors, indicating areas where one should have more or less confidence in the mean precipitation estimates. In the tropics, relative bias error estimates (s/m, where m is the mean precipitation) over the eastern Pacific Ocean are as large as 20%, as compared with 10%-15% in the western Pacific part of the ITCZ. An examination of latitudinal differences over ocean clearly shows an increase in estimated bias error at higher latitudes, reaching up to 50%. Over land, the error estimates also locate regions of potential problems in the tropics and larger cold-season errors at high latitudes that are due to snow. An empirical technique to area average the gridded errors (s) is described that allows one to make error estimates for arbitrary areas and for the tropics and the globe (land and ocean separately, and combined). Over the tropics this calculation leads to a relative error estimate for tropical land and ocean combined of 7%, which is considered to be an upper bound because of the lack of sign-of-the-error canceling when integrating over different areas with a different number of input products. For the globe the calculated relative error estimate from this study is about 9%, which is also probably a slight overestimate. These tropical and global estimated bias errors provide one estimate of the current state of knowledge of the planet's mean precipitation.

You Learn by Your Mistakes. Effective Training Strategies Based on the Analysis of Video-Recorded Worked-Out Examples

ERIC Educational Resources Information Center

Cattaneo, Alberto A. P.; Boldrini, Elena

2017-01-01

This paper presents an empirical study on procedural learning from errors that was conducted within the field of vocational education. It examines whether, and to what extent, procedural learning can benefit more from the detection and written analysis of errors (experimental condition) than from the correct elements (control group). The study…

A Meta-Meta-Analysis: Empirical Review of Statistical Power, Type I Error Rates, Effect Sizes, and Model Selection of Meta-Analyses Published in Psychology

ERIC Educational Resources Information Center

Cafri, Guy; Kromrey, Jeffrey D.; Brannick, Michael T.

2010-01-01

This article uses meta-analyses published in "Psychological Bulletin" from 1995 to 2005 to describe meta-analyses in psychology, including examination of statistical power, Type I errors resulting from multiple comparisons, and model choice. Retrospective power estimates indicated that univariate categorical and continuous moderators, individual…

The Effect of Piano Playing on Preservice Teachers' Ability to Detect Errors in a Choral Score

ERIC Educational Resources Information Center

Napoles, Jessica; Babb, Sandra L.; Bowers, Judy; Hankle, Steven; Zrust, Adam

2017-01-01

The purpose of this study was to examine and empirically test the pedagogical claim that playing the piano while listening to choral singers impedes error detection ability. In a within-subjects design, participants (N = 55 preservice teachers) either listened to four excerpts of choral hymns or played a single part (soprano/bass) on the piano…

Sadrettin Celal Antel's Ten-Year Ministry Development Report: An Assessment Based on the Divisions of Educational Sciences

ERIC Educational Resources Information Center

Karagoz, Savas

2018-01-01

Except other reasons such as politics, economics and military, the decline and collapse of the Ottoman Empire are because of outdated education system. After the proclamation of the Republic, the newly established Republic of Turkey gave great importance in education with its all dimensions to not fall into that error Ottoman Empire had fallen.…

Analysis of quantum error correction with symmetric hypergraph states

NASA Astrophysics Data System (ADS)

Wagner, T.; Kampermann, H.; Bruß, D.

2018-03-01

Graph states have been used to construct quantum error correction codes for independent errors. Hypergraph states generalize graph states, and symmetric hypergraph states have been shown to allow for the correction of correlated errors. In this paper, it is shown that symmetric hypergraph states are not useful for the correction of independent errors, at least for up to 30 qubits. Furthermore, error correction for error models with protected qubits is explored. A class of known graph codes for this scenario is generalized to hypergraph codes.

Intrinsic and extrinsic motivators of attachment under active inference.

PubMed

Cittern, David; Nolte, Tobias; Friston, Karl; Edalat, Abbas

2018-01-01

This paper addresses the formation of infant attachment types within the context of active inference: a holistic account of action, perception and learning in the brain. We show how the organised forms of attachment (secure, avoidant and ambivalent) might arise in (Bayesian) infants. Specifically, we show that these distinct forms of attachment emerge from a minimisation of free energy-over interoceptive states relating to internal stress levels-when seeking proximity to caregivers who have a varying impact on these interoceptive states. In line with empirical findings in disrupted patterns of affective communication, we then demonstrate how exteroceptive cues (in the form of caregiver-mediated AMBIANCE affective communication errors, ACE) can result in disorganised forms of attachment in infants of caregivers who consistently increase stress when the infant seeks proximity, but can have an organising (towards ambivalence) effect in infants of inconsistent caregivers. In particular, we differentiate disorganised attachment from avoidance in terms of the high epistemic value of proximity seeking behaviours (resulting from the caregiver's misleading exteroceptive cues) that preclude the emergence of coherent and organised behavioural policies. Our work, the first to formulate infant attachment in terms of active inference, makes a new testable prediction with regards to the types of affective communication errors that engender ambivalent attachment.

Intrinsic and extrinsic motivators of attachment under active inference

PubMed Central

Nolte, Tobias; Friston, Karl; Edalat, Abbas

2018-01-01

This paper addresses the formation of infant attachment types within the context of active inference: a holistic account of action, perception and learning in the brain. We show how the organised forms of attachment (secure, avoidant and ambivalent) might arise in (Bayesian) infants. Specifically, we show that these distinct forms of attachment emerge from a minimisation of free energy—over interoceptive states relating to internal stress levels—when seeking proximity to caregivers who have a varying impact on these interoceptive states. In line with empirical findings in disrupted patterns of affective communication, we then demonstrate how exteroceptive cues (in the form of caregiver-mediated AMBIANCE affective communication errors, ACE) can result in disorganised forms of attachment in infants of caregivers who consistently increase stress when the infant seeks proximity, but can have an organising (towards ambivalence) effect in infants of inconsistent caregivers. In particular, we differentiate disorganised attachment from avoidance in terms of the high epistemic value of proximity seeking behaviours (resulting from the caregiver’s misleading exteroceptive cues) that preclude the emergence of coherent and organised behavioural policies. Our work, the first to formulate infant attachment in terms of active inference, makes a new testable prediction with regards to the types of affective communication errors that engender ambivalent attachment. PMID:29621266

The IPEA dilemma in CASPT2† †Electronic supplementary information (ESI) available: Original data (Table S1) and additional comments for the literature survey; note on symmetry (Table S2), geometries (Table S3), data (Tables S4–S6) and comments (Section S2) for calculations on di-/triatomic molecules; results (Tables S7–S25) and comments (Section S3) for calculations on the organic molecular data set. See DOI: 10.1039/c6sc03759c Click here for additional data file.

PubMed Central

Zobel, J. Patrick

2017-01-01

Multi-configurational second order perturbation theory (CASPT2) has become a very popular method for describing excited-state properties since its development in 1990. To account for systematic errors found in the calculation of dissociation energies, an empirical correction applied to the zeroth-order Hamiltonian, called the IPEA shift, was introduced in 2004. The errors were attributed to an unbalanced description of open-shell versus closed-shell electronic states and is believed to also lead to an underestimation of excitation energies. Here we show that the use of the IPEA shift is not justified and the IPEA should not be used to calculate excited states, at least for organic chromophores. This conclusion is the result of three extensive analyses. Firstly, we survey the literature for excitation energies of organic molecules that have been calculated with the unmodified CASPT2 method. We find that the excitation energies of 356 reference values are negligibly underestimated by 0.02 eV. This value is an order of magnitude smaller than the expected error based on the calculation of dissociation energies. Secondly, we perform benchmark full configuration interaction calculations on 137 states of 13 di- and triatomic molecules and compare the results with CASPT2. Also in this case, the excited states are underestimated by only 0.05 eV. Finally, we perform CASPT2 calculations with different IPEA shift values on 309 excited states of 28 organic small and medium-sized organic chromophores. We demonstrate that the size of the IPEA correction scales with the amount of dynamical correlation energy (and thus with the size of the system), and gets immoderate already for the molecules considered here, leading to an overestimation of the excitation energies. It is also found that the IPEA correction strongly depends on the size of the basis set. The dependency on both the size of the system and of the basis set, contradicts the idea of a universal IPEA shift which is able to compensate for systematic CASPT2 errors in the calculation of excited states. PMID:28572908

Evaluating the predictive performance of empirical estimators of natural mortality rate using information on over 200 fish species

USGS Publications Warehouse

Then, Amy Y.; Hoenig, John M; Hall, Norman G.; Hewitt, David A.

2015-01-01

Many methods have been developed in the last 70 years to predict the natural mortality rate, M, of a stock based on empirical evidence from comparative life history studies. These indirect or empirical methods are used in most stock assessments to (i) obtain estimates of M in the absence of direct information, (ii) check on the reasonableness of a direct estimate of M, (iii) examine the range of plausible M estimates for the stock under consideration, and (iv) define prior distributions for Bayesian analyses. The two most cited empirical methods have appeared in the literature over 2500 times to date. Despite the importance of these methods, there is no consensus in the literature on how well these methods work in terms of prediction error or how their performance may be ranked. We evaluate estimators based on various combinations of maximum age (tmax), growth parameters, and water temperature by seeing how well they reproduce >200 independent, direct estimates of M. We use tenfold cross-validation to estimate the prediction error of the estimators and to rank their performance. With updated and carefully reviewed data, we conclude that a tmax-based estimator performs the best among all estimators evaluated. The tmax-based estimators in turn perform better than the Alverson–Carney method based on tmax and the von Bertalanffy K coefficient, Pauly’s method based on growth parameters and water temperature and methods based just on K. It is possible to combine two independent methods by computing a weighted mean but the improvement over the tmax-based methods is slight. Based on cross-validation prediction error, model residual patterns, model parsimony, and biological considerations, we recommend the use of a tmax-based estimator (M=4.899tmax−0.916">M=4.899t−0.916maxM=4.899tmax−0.916, prediction error = 0.32) when possible and a growth-based method (M=4.118K0.73L∞−0.33">M=4.118K0.73L−0.33∞M=4.118K0.73L∞−0.33 , prediction error = 0.6, length in cm) otherwise.

Improving the spatial and temporal resolution with quantification of uncertainty and errors in earth observation data sets using Data Interpolating Empirical Orthogonal Functions methodology

NASA Astrophysics Data System (ADS)

El Serafy, Ghada; Gaytan Aguilar, Sandra; Ziemba, Alexander

2016-04-01

There is an increasing use of process-based models in the investigation of ecological systems and scenario predictions. The accuracy and quality of these models are improved when run with high spatial and temporal resolution data sets. However, ecological data can often be difficult to collect which manifests itself through irregularities in the spatial and temporal domain of these data sets. Through the use of Data INterpolating Empirical Orthogonal Functions(DINEOF) methodology, earth observation products can be improved to have full spatial coverage within the desired domain as well as increased temporal resolution to daily and weekly time step, those frequently required by process-based models[1]. The DINEOF methodology results in a degree of error being affixed to the refined data product. In order to determine the degree of error introduced through this process, the suspended particulate matter and chlorophyll-a data from MERIS is used with DINEOF to produce high resolution products for the Wadden Sea. These new data sets are then compared with in-situ and other data sources to determine the error. Also, artificial cloud cover scenarios are conducted in order to substantiate the findings from MERIS data experiments. Secondly, the accuracy of DINEOF is explored to evaluate the variance of the methodology. The degree of accuracy is combined with the overall error produced by the methodology and reported in an assessment of the quality of DINEOF when applied to resolution refinement of chlorophyll-a and suspended particulate matter in the Wadden Sea. References [1] Sirjacobs, D.; Alvera-Azcárate, A.; Barth, A.; Lacroix, G.; Park, Y.; Nechad, B.; Ruddick, K.G.; Beckers, J.-M. (2011). Cloud filling of ocean colour and sea surface temperature remote sensing products over the Southern North Sea by the Data Interpolating Empirical Orthogonal Functions methodology. J. Sea Res. 65(1): 114-130. Dx.doi.org/10.1016/j.seares.2010.08.002

Model for estimating enteric methane emissions from United States dairy and feedlot cattle.

PubMed

Kebreab, E; Johnson, K A; Archibeque, S L; Pape, D; Wirth, T

2008-10-01

Methane production from enteric fermentation in cattle is one of the major sources of anthropogenic greenhouse gas emission in the United States and worldwide. National estimates of methane emissions rely on mathematical models such as the one recommended by the Intergovernmental Panel for Climate Change (IPCC). Models used for prediction of methane emissions from cattle range from empirical to mechanistic with varying input requirements. Two empirical and 2 mechanistic models (COWPOLL and MOLLY) were evaluated for their prediction ability using individual cattle measurements. Model selection was based on mean square prediction error (MSPE), concordance correlation coefficient, and residuals vs. predicted values analyses. In dairy cattle, COWPOLL had the lowest root MSPE and greatest accuracy and precision of predicting methane emissions (correlation coefficient estimate = 0.75). The model simulated differences in diet more accurately than the other models, and the residuals vs. predicted value analysis showed no mean bias (P = 0.71). In feedlot cattle, MOLLY had the lowest root MSPE with almost all errors from random sources (correlation coefficient estimate = 0.69). The IPCC model also had good agreement with observed values, and no significant mean (P = 0.74) or linear bias (P = 0.11) was detected when residuals were plotted against predicted values. A fixed methane conversion factor (Ym) might be an easier alternative to diet-dependent variable Ym. Based on the results, the 2 mechanistic models were used to simulate methane emissions from representative US diets and were compared with the IPCC model. The average Ym in dairy cows was 5.63% of GE (range 3.78 to 7.43%) compared with 6.5% +/- 1% recommended by IPCC. In feedlot cattle, the average Ym was 3.88% (range 3.36 to 4.56%) compared with 3% +/- 1% recommended by IPCC. Based on our simulations, using IPCC values can result in an overestimate of about 12.5% and underestimate of emissions by about 9.8% for dairy and feedlot cattle, respectively. In addition to providing improved estimates of emissions based on diets, mechanistic models can be used to assess mitigation options such as changing source of carbohydrate or addition of fat to decrease methane, which is not possible with empirical models. We recommend national inventories use diet-specific Ym values predicted by mechanistic models to estimate methane emissions from cattle.

Issues with data and analyses: Errors, underlying themes, and potential solutions

PubMed Central

Allison, David B.

2018-01-01

Some aspects of science, taken at the broadest level, are universal in empirical research. These include collecting, analyzing, and reporting data. In each of these aspects, errors can and do occur. In this work, we first discuss the importance of focusing on statistical and data errors to continually improve the practice of science. We then describe underlying themes of the types of errors and postulate contributing factors. To do so, we describe a case series of relatively severe data and statistical errors coupled with surveys of some types of errors to better characterize the magnitude, frequency, and trends. Having examined these errors, we then discuss the consequences of specific errors or classes of errors. Finally, given the extracted themes, we discuss methodological, cultural, and system-level approaches to reducing the frequency of commonly observed errors. These approaches will plausibly contribute to the self-critical, self-correcting, ever-evolving practice of science, and ultimately to furthering knowledge. PMID:29531079

Proton-nucleus total inelastic cross sections - An empirical formula for E greater than 10 MeV

NASA Technical Reports Server (NTRS)

Letaw, J. R.; Silberberg, R.; Tsao, C. H.

1983-01-01

An empirical formula for the total inelastic cross section of protons on nuclei with charge greater than 1 is presented. The formula is valid with a varying degree of accuracy down to proton energies of 10 MeV. At high energies (equal to or greater than 2 GeV) the formula reproduces experimental data to within reported errors (about 2%).

Development of Items for a Pedagogical Content Knowledge Test Based on Empirical Analysis of Pupils' Errors

ERIC Educational Resources Information Center

Juttner, Melanie; Neuhaus, Birgit J.

2012-01-01

In view of the lack of instruments for measuring biology teachers' pedagogical content knowledge (PCK), this article reports on a study about the development of PCK items for measuring teachers' knowledge of pupils' errors and ways for dealing with them. This study investigated 9th and 10th grade German pupils' (n = 461) drawings in an achievement…

Empirical Synthesis of the Effect of Standard Error of Measurement on Decisions Made within Brief Experimental Analyses of Reading Fluency

ERIC Educational Resources Information Center

Burns, Matthew K.; Taylor, Crystal N.; Warmbold-Brann, Kristy L.; Preast, June L.; Hosp, John L.; Ford, Jeremy W.

2017-01-01

Intervention researchers often use curriculum-based measurement of reading fluency (CBM-R) with a brief experimental analysis (BEA) to identify an effective intervention for individual students. The current study synthesized data from 22 studies that used CBM-R data within a BEA by computing the standard error of measure (SEM) for the median data…

Adventures in Uncertainty: An Empirical Investigation of the Use of a Taylor's Series Approximation for the Assessment of Sampling Errors in Educational Research.

ERIC Educational Resources Information Center

Wilson, Mark

This study investigates the accuracy of the Woodruff-Causey technique for estimating sampling errors for complex statistics. The technique may be applied when data are collected by using multistage clustered samples. The technique was chosen for study because of its relevance to the correct use of multivariate analyses in educational survey…

Software errors and complexity: An empirical investigation

NASA Technical Reports Server (NTRS)

Basili, Victor R.; Perricone, Berry T.

1983-01-01

The distributions and relationships derived from the change data collected during the development of a medium scale satellite software project show that meaningful results can be obtained which allow an insight into software traits and the environment in which it is developed. Modified and new modules were shown to behave similarly. An abstract classification scheme for errors which allows a better understanding of the overall traits of a software project is also shown. Finally, various size and complexity metrics are examined with respect to errors detected within the software yielding some interesting results.

Software errors and complexity: An empirical investigation

NASA Technical Reports Server (NTRS)

Basili, V. R.; Perricone, B. T.

1982-01-01

The distributions and relationships derived from the change data collected during the development of a medium scale satellite software project show that meaningful results can be obtained which allow an insight into software traits and the environment in which it is developed. Modified and new modules were shown to behave similarly. An abstract classification scheme for errors which allows a better understanding of the overall traits of a software project is also shown. Finally, various size and complexity metrics are examined with respect to errors detected within the software yielding some interesting results.

Why has energy consumption increased. An energy and society approach to the American case

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

Lacy, M.G.

1981-01-01

The general intellectual debate over energy issues has not exhausted the possibilities for sociological work. Sociology can improve on such previous work by providing an empirical-analytic moment, attending to meaning adequacy, recognizing process, assessing the materially determinative character of energy, and by being critical. However, if these several dimensions are taken as prescriptive criteria, even the strictly sociological literature on energy and society has numerous errors and omissions. Based on the findings of that critical examination of the sociological energy literature, a simple formal theory is developed to attack a particular substantive problem: Why has energy consumption increased in themore » United States during the twentieth century. This formalism requires that we begin by regarding energy consumption as completely determined by population, affluence, and technology. The results of the first empirical analysis using that formalism show that rising affluence, rather than deteriorating technology, is the culprit. However, the urge to praise technology is too hasty, since a second analysis shows that there actually have been two trends in energy technology, only one of which tended to hold down energy consumption.« less

Non-empirical exchange-correlation parameterizations based on exact conditions from correlated orbital theory.

PubMed

Haiduke, Roberto Luiz A; Bartlett, Rodney J

2018-05-14

Some of the exact conditions provided by the correlated orbital theory are employed to propose new non-empirical parameterizations for exchange-correlation functionals from Density Functional Theory (DFT). This reparameterization process is based on range-separated functionals with 100% exact exchange for long-range interelectronic interactions. The functionals developed here, CAM-QTP-02 and LC-QTP, show mitigated self-interaction error, correctly predict vertical ionization potentials as the negative of eigenvalues for occupied orbitals, and provide nice excitation energies, even for challenging charge-transfer excited states. Moreover, some improvements are observed for reaction barrier heights with respect to the other functionals belonging to the quantum theory project (QTP) family. Finally, the most important achievement of these new functionals is an excellent description of vertical electron affinities (EAs) of atoms and molecules as the negative of appropriate virtual orbital eigenvalues. In this case, the mean absolute deviations for EAs in molecules are smaller than 0.10 eV, showing that physical interpretation can indeed be ascribed to some unoccupied orbitals from DFT.

Non-empirical exchange-correlation parameterizations based on exact conditions from correlated orbital theory

NASA Astrophysics Data System (ADS)

Haiduke, Roberto Luiz A.; Bartlett, Rodney J.

2018-05-01

Some of the exact conditions provided by the correlated orbital theory are employed to propose new non-empirical parameterizations for exchange-correlation functionals from Density Functional Theory (DFT). This reparameterization process is based on range-separated functionals with 100% exact exchange for long-range interelectronic interactions. The functionals developed here, CAM-QTP-02 and LC-QTP, show mitigated self-interaction error, correctly predict vertical ionization potentials as the negative of eigenvalues for occupied orbitals, and provide nice excitation energies, even for challenging charge-transfer excited states. Moreover, some improvements are observed for reaction barrier heights with respect to the other functionals belonging to the quantum theory project (QTP) family. Finally, the most important achievement of these new functionals is an excellent description of vertical electron affinities (EAs) of atoms and molecules as the negative of appropriate virtual orbital eigenvalues. In this case, the mean absolute deviations for EAs in molecules are smaller than 0.10 eV, showing that physical interpretation can indeed be ascribed to some unoccupied orbitals from DFT.

9. EMPIRE STATE MINE, BOTTOM ORE BIN/SHOOT. TIN ROOF OF ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

9. EMPIRE STATE MINE, BOTTOM ORE BIN/SHOOT. TIN ROOF OF SOUTHERN MOST BUILDING AND UPPER ORE SHOOT VISIBLE. CAMERA POINTED EAST-NORTHEAST. - Florida Mountain Mining Sites, Empire State Mine, West side of Florida Mountain, Silver City, Owyhee County, ID

Empirical prediction intervals improve energy forecasting

PubMed Central

Kaack, Lynn H.; Apt, Jay; Morgan, M. Granger; McSharry, Patrick

2017-01-01

Hundreds of organizations and analysts use energy projections, such as those contained in the US Energy Information Administration (EIA)’s Annual Energy Outlook (AEO), for investment and policy decisions. Retrospective analyses of past AEO projections have shown that observed values can differ from the projection by several hundred percent, and thus a thorough treatment of uncertainty is essential. We evaluate the out-of-sample forecasting performance of several empirical density forecasting methods, using the continuous ranked probability score (CRPS). The analysis confirms that a Gaussian density, estimated on past forecasting errors, gives comparatively accurate uncertainty estimates over a variety of energy quantities in the AEO, in particular outperforming scenario projections provided in the AEO. We report probabilistic uncertainties for 18 core quantities of the AEO 2016 projections. Our work frames how to produce, evaluate, and rank probabilistic forecasts in this setting. We propose a log transformation of forecast errors for price projections and a modified nonparametric empirical density forecasting method. Our findings give guidance on how to evaluate and communicate uncertainty in future energy outlooks. PMID:28760997

A Formal Approach to Empirical Dynamic Model Optimization and Validation

NASA Technical Reports Server (NTRS)

Crespo, Luis G; Morelli, Eugene A.; Kenny, Sean P.; Giesy, Daniel P.

2014-01-01

A framework was developed for the optimization and validation of empirical dynamic models subject to an arbitrary set of validation criteria. The validation requirements imposed upon the model, which may involve several sets of input-output data and arbitrary specifications in time and frequency domains, are used to determine if model predictions are within admissible error limits. The parameters of the empirical model are estimated by finding the parameter realization for which the smallest of the margins of requirement compliance is as large as possible. The uncertainty in the value of this estimate is characterized by studying the set of model parameters yielding predictions that comply with all the requirements. Strategies are presented for bounding this set, studying its dependence on admissible prediction error set by the analyst, and evaluating the sensitivity of the model predictions to parameter variations. This information is instrumental in characterizing uncertainty models used for evaluating the dynamic model at operating conditions differing from those used for its identification and validation. A practical example based on the short period dynamics of the F-16 is used for illustration.

Semi-empirical estimation of organic compound fugacity ratios at environmentally relevant system temperatures.

PubMed

van Noort, Paul C M

2009-06-01

Fugacity ratios of organic compounds are used to calculate (subcooled) liquid properties, such as solubility or vapour pressure, from solid properties and vice versa. They can be calculated from the entropy of fusion, the melting temperature, and heat capacity data for the solid and the liquid. For many organic compounds, values for the fusion entropy are lacking. Heat capacity data are even scarcer. In the present study, semi-empirical compound class specific equations were derived to estimate fugacity ratios from molecular weight and melting temperature for polycyclic aromatic hydrocarbons and polychlorinated benzenes, biphenyls, dibenzo[p]dioxins and dibenzofurans. These equations estimate fugacity ratios with an average standard error of about 0.05 log units. In addition, for compounds with known fusion entropy values, a general semi-empirical correction equation based on molecular weight and melting temperature was derived for estimation of the contribution of heat capacity differences to the fugacity ratio. This equation estimates the heat capacity contribution correction factor with an average standard error of 0.02 log units for polycyclic aromatic hydrocarbons, polychlorinated benzenes, biphenyls, dibenzo[p]dioxins and dibenzofurans.

GPS-Derived Precipitable Water Compared with the Air Force Weather Agency’s MM5 Model Output

DTIC Science & Technology

2002-03-26

and less then 100 sensors are available throughout Europe . While the receiver density is currently comparable to the upper-air sounding network...profiles from 38 upper air sites throughout Europe . Based on these empirical formulae and simplifications, Bevis (1992) has determined that the error...Alaska using Bevis’ (1992) empirical correlation based on 8718 radiosonde calculations over 2 years. Other studies have been conducted in Europe and

Empirical Analysis of Systematic Communication Errors.

DTIC Science & Technology

1981-09-01

human o~ . .... 8 components in communication systems. (Systematic errors were defined to be those that occur regularly in human communication links...phase of the human communication process and focuses on the linkage between a specific piece of information (and the receiver) and the transmission...communication flow. (2) Exchange. Exchange is the next phase in human communication and entails a concerted effort on the part of the sender and receiver to share

Effect of cephalometer misalignment on calculations of facial asymmetry.

PubMed

Lee, Ki-Heon; Hwang, Hyeon-Shik; Curry, Sean; Boyd, Robert L; Norris, Kevin; Baumrind, Sheldon

2007-07-01

In this study, we evaluated errors introduced into the interpretation of facial asymmetry on posteroanterior (PA) cephalograms due to malpositioning of the x-ray emitter focal spot. We tested the hypothesis that horizontal displacements of the emitter from its ideal position would produce systematic displacements of skull landmarks that could be fully accounted for by the rules of projective geometry alone. A representative dry skull with 22 metal markers was used to generate a series of PA images from different emitter positions by using a fully calibrated stereo cephalometer. Empirical measurements of the resulting cephalograms were compared with mathematical predictions based solely on geometric rules. The empirical measurements matched the mathematical predictions within the limits of measurement error (x= 0.23 mm), thus supporting the hypothesis. Based upon this finding, we generated a completely symmetrical mathematical skull and calculated the expected errors for focal spots of several different magnitudes. Quantitative data were computed for focal spot displacements of different magnitudes. Misalignment of the x-ray emitter focal spot introduces systematic errors into the interpretation of facial asymmetry on PA cephalograms. For misalignments of less than 20 mm, the effect is small in individual cases. However, misalignments as small as 10 mm can introduce spurious statistical findings of significant asymmetry when mean values for large groups of PA images are evaluated.

Effective empirical corrections for basis set superposition error in the def2-SVPD basis: gCP and DFT-C

NASA Astrophysics Data System (ADS)

Witte, Jonathon; Neaton, Jeffrey B.; Head-Gordon, Martin

2017-06-01

With the aim of mitigating the basis set error in density functional theory (DFT) calculations employing local basis sets, we herein develop two empirical corrections for basis set superposition error (BSSE) in the def2-SVPD basis, a basis which—when stripped of BSSE—is capable of providing near-complete-basis DFT results for non-covalent interactions. Specifically, we adapt the existing pairwise geometrical counterpoise (gCP) approach to the def2-SVPD basis, and we develop a beyond-pairwise approach, DFT-C, which we parameterize across a small set of intermolecular interactions. Both gCP and DFT-C are evaluated against the traditional Boys-Bernardi counterpoise correction across a set of 3402 non-covalent binding energies and isomerization energies. We find that the DFT-C method represents a significant improvement over gCP, particularly for non-covalently-interacting molecular clusters. Moreover, DFT-C is transferable among density functionals and can be combined with existing functionals—such as B97M-V—to recover large-basis results at a fraction of the cost.

Experimental investigation of heat transfer coefficient of mini-channel PCHE (printed circuit heat exchanger)

NASA Astrophysics Data System (ADS)

Kwon, Dohoon; Jin, Lingxue; Jung, WooSeok; Jeong, Sangkwon

2018-06-01

Heat transfer coefficient of a mini-channel printed circuit heat exchanger (PCHE) with counter-flow configuration is investigated. The PCHE used in the experiments is two layered (10 channels per layer) and has the hydraulic diameter of 1.83 mm. Experiments are conducted under various cryogenic heat transfer conditions: single-phase, boiling and condensation heat transfer. Heat transfer coefficients of each experiments are presented and compared with established correlations. In the case of the single-phase experiment, empiricial correlation of modified Dittus-Boelter correlation was proposed, which predicts the experimental results with 5% error at Reynolds number range from 8500 to 17,000. In the case of the boiling experiment, film boiling phenomenon occurred dominantly due to large temperature difference between the hot side and the cold side fluids. Empirical correlation is proposed which predicts experimental results with 20% error at Reynolds number range from 2100 to 2500. In the case of the condensation experiment, empirical correlation of modified Akers correlation was proposed, which predicts experimental results with 10% error at Reynolds number range from 3100 to 6200.

Optimizing Blasting’s Air Overpressure Prediction Model using Swarm Intelligence

NASA Astrophysics Data System (ADS)

Nur Asmawisham Alel, Mohd; Ruben Anak Upom, Mark; Asnida Abdullah, Rini; Hazreek Zainal Abidin, Mohd

2018-04-01

Air overpressure (AOp) resulting from blasting can cause damage and nuisance to nearby civilians. Thus, it is important to be able to predict AOp accurately. In this study, 8 different Artificial Neural Network (ANN) were developed for the purpose of prediction of AOp. The ANN models were trained using different variants of Particle Swarm Optimization (PSO) algorithm. AOp predictions were also made using an empirical equation, as suggested by United States Bureau of Mines (USBM), to serve as a benchmark. In order to develop the models, 76 blasting operations in Hulu Langat were investigated. All the ANN models were found to outperform the USBM equation in three performance metrics; root mean square error (RMSE), mean absolute percentage error (MAPE) and coefficient of determination (R2). Using a performance ranking method, MSO-Rand-Mut was determined to be the best prediction model for AOp with a performance metric of RMSE=2.18, MAPE=1.73% and R2=0.97. The result shows that ANN models trained using PSO are capable of predicting AOp with great accuracy.

A new stochastic model considering satellite clock interpolation errors in precise point positioning

NASA Astrophysics Data System (ADS)

Wang, Shengli; Yang, Fanlin; Gao, Wang; Yan, Lizi; Ge, Yulong

2018-03-01

Precise clock products are typically interpolated based on the sampling interval of the observational data when they are used for in precise point positioning. However, due to the occurrence of white noise in atomic clocks, a residual component of such noise will inevitable reside within the observations when clock errors are interpolated, and such noise will affect the resolution of the positioning results. In this paper, which is based on a twenty-one-week analysis of the atomic clock noise characteristics of numerous satellites, a new stochastic observation model that considers satellite clock interpolation errors is proposed. First, the systematic error of each satellite in the IGR clock product was extracted using a wavelet de-noising method to obtain the empirical characteristics of atomic clock noise within each clock product. Then, based on those empirical characteristics, a stochastic observation model was structured that considered the satellite clock interpolation errors. Subsequently, the IGR and IGS clock products at different time intervals were used for experimental validation. A verification using 179 stations worldwide from the IGS showed that, compared with the conventional model, the convergence times using the stochastic model proposed in this study were respectively shortened by 4.8% and 4.0% when the IGR and IGS 300-s-interval clock products were used and by 19.1% and 19.4% when the 900-s-interval clock products were used. Furthermore, the disturbances during the initial phase of the calculation were also effectively improved.

The cost of misremembering: Inferring the loss function in visual working memory.

PubMed

Sims, Chris R

2015-03-04

Visual working memory (VWM) is a highly limited storage system. A basic consequence of this fact is that visual memories cannot perfectly encode or represent the veridical structure of the world. However, in natural tasks, some memory errors might be more costly than others. This raises the intriguing possibility that the nature of memory error reflects the costs of committing different kinds of errors. Many existing theories assume that visual memories are noise-corrupted versions of afferent perceptual signals. However, this additive noise assumption oversimplifies the problem. Implicit in the behavioral phenomena of visual working memory is the concept of a loss function: a mathematical entity that describes the relative cost to the organism of making different types of memory errors. An optimally efficient memory system is one that minimizes the expected loss according to a particular loss function, while subject to a constraint on memory capacity. This paper describes a novel theoretical framework for characterizing visual working memory in terms of its implicit loss function. Using inverse decision theory, the empirical loss function is estimated from the results of a standard delayed recall visual memory experiment. These results are compared to the predicted behavior of a visual working memory system that is optimally efficient for a previously identified natural task, gaze correction following saccadic error. Finally, the approach is compared to alternative models of visual working memory, and shown to offer a superior account of the empirical data across a range of experimental datasets. © 2015 ARVO.

Error simulation of paired-comparison-based scaling methods

NASA Astrophysics Data System (ADS)

Cui, Chengwu

2000-12-01

Subjective image quality measurement usually resorts to psycho physical scaling. However, it is difficult to evaluate the inherent precision of these scaling methods. Without knowing the potential errors of the measurement, subsequent use of the data can be misleading. In this paper, the errors on scaled values derived form paired comparison based scaling methods are simulated with randomly introduced proportion of choice errors that follow the binomial distribution. Simulation results are given for various combinations of the number of stimuli and the sampling size. The errors are presented in the form of average standard deviation of the scaled values and can be fitted reasonably well with an empirical equation that can be sued for scaling error estimation and measurement design. The simulation proves paired comparison based scaling methods can have large errors on the derived scaled values when the sampling size and the number of stimuli are small. Examples are also given to show the potential errors on actually scaled values of color image prints as measured by the method of paired comparison.

Bioethics for clinicians: 23. Disclosure of medical error

PubMed Central

Hébert, Philip C.; Levin, Alex V.; Robertson, Gerald

2001-01-01

ADVERSE EVENTS AND MEDICAL ERRORS ARE NOT UNCOMMON. In this article we review the literature on such events and discuss the ethical, legal and practical aspects of whether and how they should be disclosed to patients. Ethics, professional policy and the law, as well as the relevant empirical literature, suggest that timely and candid disclosure should be standard practice. Candour about error may lessen, rather than increase, the medicolegal liability of the health care professionals and may help to alleviate the patient's concerns. Guidelines for disclosure to patients, and their families if necessary, are proposed. PMID:11233873

An empirical assessment of taxic paleobiology.

PubMed

Adrain, J M; Westrop, S R

2000-07-07

The analysis of major changes in faunal diversity through time is a central theme of analytical paleobiology. The most important sources of data are literature-based compilations of stratigraphic ranges of fossil taxa. The levels of error in these compilations and the possible effects of such error have often been discussed but never directly assessed. We compared our comprehensive database of trilobites to the equivalent portion of J. J. Sepkoski Jr.'s widely used global genus database. More than 70% of entries in the global database are inaccurate; however, as predicted, the error is randomly distributed and does not introduce bias.

Small field detector correction factors kQclin,Qmsr (fclin,fmsr) for silicon-diode and diamond detectors with circular 6 MV fields derived using both empirical and numerical methods.

PubMed

O'Brien, D J; León-Vintró, L; McClean, B

2016-01-01

The use of radiotherapy fields smaller than 3 cm in diameter has resulted in the need for accurate detector correction factors for small field dosimetry. However, published factors do not always agree and errors introduced by biased reference detectors, inaccurate Monte Carlo models, or experimental errors can be difficult to distinguish. The aim of this study was to provide a robust set of detector-correction factors for a range of detectors using numerical, empirical, and semiempirical techniques under the same conditions and to examine the consistency of these factors between techniques. Empirical detector correction factors were derived based on small field output factor measurements for circular field sizes from 3.1 to 0.3 cm in diameter performed with a 6 MV beam. A PTW 60019 microDiamond detector was used as the reference dosimeter. Numerical detector correction factors for the same fields were derived based on calculations from a geant4 Monte Carlo model of the detectors and the Linac treatment head. Semiempirical detector correction factors were derived from the empirical output factors and the numerical dose-to-water calculations. The PTW 60019 microDiamond was found to over-respond at small field sizes resulting in a bias in the empirical detector correction factors. The over-response was similar in magnitude to that of the unshielded diode. Good agreement was generally found between semiempirical and numerical detector correction factors except for the PTW 60016 Diode P, where the numerical values showed a greater over-response than the semiempirical values by a factor of 3.7% for a 1.1 cm diameter field and higher for smaller fields. Detector correction factors based solely on empirical measurement or numerical calculation are subject to potential bias. A semiempirical approach, combining both empirical and numerical data, provided the most reliable results.

Assessing differential expression in two-color microarrays: a resampling-based empirical Bayes approach.

PubMed

Li, Dongmei; Le Pape, Marc A; Parikh, Nisha I; Chen, Will X; Dye, Timothy D

2013-01-01

Microarrays are widely used for examining differential gene expression, identifying single nucleotide polymorphisms, and detecting methylation loci. Multiple testing methods in microarray data analysis aim at controlling both Type I and Type II error rates; however, real microarray data do not always fit their distribution assumptions. Smyth's ubiquitous parametric method, for example, inadequately accommodates violations of normality assumptions, resulting in inflated Type I error rates. The Significance Analysis of Microarrays, another widely used microarray data analysis method, is based on a permutation test and is robust to non-normally distributed data; however, the Significance Analysis of Microarrays method fold change criteria are problematic, and can critically alter the conclusion of a study, as a result of compositional changes of the control data set in the analysis. We propose a novel approach, combining resampling with empirical Bayes methods: the Resampling-based empirical Bayes Methods. This approach not only reduces false discovery rates for non-normally distributed microarray data, but it is also impervious to fold change threshold since no control data set selection is needed. Through simulation studies, sensitivities, specificities, total rejections, and false discovery rates are compared across the Smyth's parametric method, the Significance Analysis of Microarrays, and the Resampling-based empirical Bayes Methods. Differences in false discovery rates controls between each approach are illustrated through a preterm delivery methylation study. The results show that the Resampling-based empirical Bayes Methods offer significantly higher specificity and lower false discovery rates compared to Smyth's parametric method when data are not normally distributed. The Resampling-based empirical Bayes Methods also offers higher statistical power than the Significance Analysis of Microarrays method when the proportion of significantly differentially expressed genes is large for both normally and non-normally distributed data. Finally, the Resampling-based empirical Bayes Methods are generalizable to next generation sequencing RNA-seq data analysis.

Reconsidering the use of rankings in the valuation of health states: a model for estimating cardinal values from ordinal data

PubMed Central

Salomon, Joshua A

2003-01-01

Background In survey studies on health-state valuations, ordinal ranking exercises often are used as precursors to other elicitation methods such as the time trade-off (TTO) or standard gamble, but the ranking data have not been used in deriving cardinal valuations. This study reconsiders the role of ordinal ranks in valuing health and introduces a new approach to estimate interval-scaled valuations based on aggregate ranking data. Methods Analyses were undertaken on data from a previously published general population survey study in the United Kingdom that included rankings and TTO values for hypothetical states described using the EQ-5D classification system. The EQ-5D includes five domains (mobility, self-care, usual activities, pain/discomfort and anxiety/depression) with three possible levels on each. Rank data were analysed using a random utility model, operationalized through conditional logit regression. In the statistical model, probabilities of observed rankings were related to the latent utilities of different health states, modeled as a linear function of EQ-5D domain scores, as in previously reported EQ-5D valuation functions. Predicted valuations based on the conditional logit model were compared to observed TTO values for the 42 states in the study and to predictions based on a model estimated directly from the TTO values. Models were evaluated using the intraclass correlation coefficient (ICC) between predictions and mean observations, and the root mean squared error of predictions at the individual level. Results Agreement between predicted valuations from the rank model and observed TTO values was very high, with an ICC of 0.97, only marginally lower than for predictions based on the model estimated directly from TTO values (ICC = 0.99). Individual-level errors were also comparable in the two models, with root mean squared errors of 0.503 and 0.496 for the rank-based and TTO-based predictions, respectively. Conclusions Modeling health-state valuations based on ordinal ranks can provide results that are similar to those obtained from more widely analyzed valuation techniques such as the TTO. The information content in aggregate ranking data is not currently exploited to full advantage. The possibility of estimating cardinal valuations from ordinal ranks could also simplify future data collection dramatically and facilitate wider empirical study of health-state valuations in diverse settings and population groups. PMID:14687419

The causes of and factors associated with prescribing errors in hospital inpatients: a systematic review.

PubMed

Tully, Mary P; Ashcroft, Darren M; Dornan, Tim; Lewis, Penny J; Taylor, David; Wass, Val

2009-01-01

Prescribing errors are common, they result in adverse events and harm to patients and it is unclear how best to prevent them because recommendations are more often based on surmized rather than empirically collected data. The aim of this systematic review was to identify all informative published evidence concerning the causes of and factors associated with prescribing errors in specialist and non-specialist hospitals, collate it, analyse it qualitatively and synthesize conclusions from it. Seven electronic databases were searched for articles published between 1985-July 2008. The reference lists of all informative studies were searched for additional citations. To be included, a study had to be of handwritten prescriptions for adult or child inpatients that reported empirically collected data on the causes of or factors associated with errors. Publications in languages other than English and studies that evaluated errors for only one disease, one route of administration or one type of prescribing error were excluded. Seventeen papers reporting 16 studies, selected from 1268 papers identified by the search, were included in the review. Studies from the US and the UK in university-affiliated hospitals predominated (10/16 [62%]). The definition of a prescribing error varied widely and the included studies were highly heterogeneous. Causes were grouped according to Reason's model of accident causation into active failures, error-provoking conditions and latent conditions. The active failure most frequently cited was a mistake due to inadequate knowledge of the drug or the patient. Skills-based slips and memory lapses were also common. Where error-provoking conditions were reported, there was at least one per error. These included lack of training or experience, fatigue, stress, high workload for the prescriber and inadequate communication between healthcare professionals. Latent conditions included reluctance to question senior colleagues and inadequate provision of training. Prescribing errors are often multifactorial, with several active failures and error-provoking conditions often acting together to cause them. In the face of such complexity, solutions addressing a single cause, such as lack of knowledge, are likely to have only limited benefit. Further rigorous study, seeking potential ways of reducing error, needs to be conducted. Multifactorial interventions across many parts of the system are likely to be required.

A theoretical basis for the analysis of multiversion software subject to coincident errors

NASA Technical Reports Server (NTRS)

Eckhardt, D. E., Jr.; Lee, L. D.

1985-01-01

Fundamental to the development of redundant software techniques (known as fault-tolerant software) is an understanding of the impact of multiple joint occurrences of errors, referred to here as coincident errors. A theoretical basis for the study of redundant software is developed which: (1) provides a probabilistic framework for empirically evaluating the effectiveness of a general multiversion strategy when component versions are subject to coincident errors, and (2) permits an analytical study of the effects of these errors. An intensity function, called the intensity of coincident errors, has a central role in this analysis. This function describes the propensity of programmers to introduce design faults in such a way that software components fail together when executing in the application environment. A condition under which a multiversion system is a better strategy than relying on a single version is given.

Characterization of in Band Stray Light in SBUV-2 Instruments

NASA Technical Reports Server (NTRS)

Huang, L. K.; DeLand, M. T.; Taylor, S. L.; Flynn, L. E.

2014-01-01

Significant in-band stray light (IBSL) error at solar zenith angle (SZA) values larger than 77deg near sunset in 4 SBUV/2 (Solar Backscattered Ultraviolet) instruments, on board the NOAA-14, 17, 18 and 19 satellites, has been characterized. The IBSL error is caused by large surface reflection and scattering of the air-gapped depolarizer in front of the instrument's monochromator aperture. The source of the IBSL error is direct solar illumination of instrument components near the aperture rather than from earth shine. The IBSL contamination at 273 nm can reach 40% of earth radiance near sunset, which results in as much as a 50% error in the retrieved ozone from the upper stratosphere. We have analyzed SBUV/2 albedo measurements on both the dayside and nightside to develop an empirical model for the IBSL error. This error has been corrected in the V8.6 SBUV/2 ozone retrieval.

Theory of mind in schizophrenia: error types and associations with symptoms.

PubMed

Fretland, Ragnhild A; Andersson, Stein; Sundet, Kjetil; Andreassen, Ole A; Melle, Ingrid; Vaskinn, Anja

2015-03-01

Social cognition is an important determinant of functioning in schizophrenia. However, how social cognition relates to the clinical symptoms of schizophrenia is still unclear. The aim of this study was to explore the relationship between a social cognition domain, Theory of Mind (ToM), and the clinical symptoms of schizophrenia. Specifically, we investigated the associations between three ToM error types; 1) "overmentalizing" 2) "reduced ToM and 3) "no ToM", and positive, negative and disorganized symptoms. Fifty-two participants with a diagnosis of schizophrenia or schizoaffective disorder were assessed with the Movie for the Assessment of Social Cognition (MASC), a video-based ToM measure. An empirically validated five-factor model of the Positive and Negative Syndrome Scale (PANSS) was used to assess clinical symptoms. There was a significant, small-moderate association between overmentalizing and positive symptoms (rho=.28, p=.04). Disorganized symptoms correlated at a trend level with "reduced ToM" (rho=.27, p=.05). There were no other significant correlations between ToM impairments and symptom levels. Positive/disorganized symptoms did not contribute significantly in explaining total ToM performance, whereas IQ did (B=.37, p=.01). Within the undermentalizing domain, participants performed more "reduced ToM" errors than "no ToM" errors. Overmentalizing was associated with positive symptoms. The undermentalizing error types were unrelated to symptoms, but "reduced ToM" was somewhat associated to disorganization. The higher number of "reduced ToM" responses suggests that schizophrenia is characterized by accuracy problems rather than a fundamental lack of mental state concept. The findings call for the use of more sensitive measures when investigating ToM in schizophrenia to avoid the "right/wrong ToM"-dichotomy. Copyright © 2015 Elsevier B.V. All rights reserved.

Error Estimation of An Ensemble Statistical Seasonal Precipitation Prediction Model

NASA Technical Reports Server (NTRS)

Shen, Samuel S. P.; Lau, William K. M.; Kim, Kyu-Myong; Li, Gui-Long

2001-01-01

This NASA Technical Memorandum describes an optimal ensemble canonical correlation forecasting model for seasonal precipitation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. Since new CCA scheme is derived for continuous fields of predictor and predictand, an area-factor is automatically included. Thus our model is an improvement of the spectral CCA scheme of Barnett and Preisendorfer. The improvements include (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States (US) precipitation field. The predictor is the sea surface temperature (SST). The US Climate Prediction Center's reconstructed SST is used as the predictor's historical data. The US National Center for Environmental Prediction's optimally interpolated precipitation (1951-2000) is used as the predictand's historical data. Our forecast experiments show that the new ensemble canonical correlation scheme renders a reasonable forecasting skill. For example, when using September-October-November SST to predict the next season December-January-February precipitation, the spatial pattern correlation between the observed and predicted are positive in 46 years among the 50 years of experiments. The positive correlations are close to or greater than 0.4 in 29 years, which indicates excellent performance of the forecasting model. The forecasting skill can be further enhanced when several predictors are used.

Improving Empirical Magnetic Field Models by Fitting to In Situ Data Using an Optimized Parameter Approach

DOE PAGES

Brito, Thiago V.; Morley, Steven K.

2017-10-25

A method for comparing and optimizing the accuracy of empirical magnetic field models using in situ magnetic field measurements is presented in this paper. The optimization method minimizes a cost function—τ—that explicitly includes both a magnitude and an angular term. A time span of 21 days, including periods of mild and intense geomagnetic activity, was used for this analysis. A comparison between five magnetic field models (T96, T01S, T02, TS04, and TS07) widely used by the community demonstrated that the T02 model was, on average, the most accurate when driven by the standard model input parameters. The optimization procedure, performedmore » in all models except TS07, generally improved the results when compared to unoptimized versions of the models. Additionally, using more satellites in the optimization procedure produces more accurate results. This procedure reduces the number of large errors in the model, that is, it reduces the number of outliers in the error distribution. The TS04 model shows the most accurate results after the optimization in terms of both the magnitude and direction, when using at least six satellites in the fitting. It gave a smaller error than its unoptimized counterpart 57.3% of the time and outperformed the best unoptimized model (T02) 56.2% of the time. Its median percentage error in |B| was reduced from 4.54% to 3.84%. Finally, the difference among the models analyzed, when compared in terms of the median of the error distributions, is not very large. However, the unoptimized models can have very large errors, which are much reduced after the optimization.« less

Improving Empirical Magnetic Field Models by Fitting to In Situ Data Using an Optimized Parameter Approach

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

Brito, Thiago V.; Morley, Steven K.

A method for comparing and optimizing the accuracy of empirical magnetic field models using in situ magnetic field measurements is presented in this paper. The optimization method minimizes a cost function—τ—that explicitly includes both a magnitude and an angular term. A time span of 21 days, including periods of mild and intense geomagnetic activity, was used for this analysis. A comparison between five magnetic field models (T96, T01S, T02, TS04, and TS07) widely used by the community demonstrated that the T02 model was, on average, the most accurate when driven by the standard model input parameters. The optimization procedure, performedmore » in all models except TS07, generally improved the results when compared to unoptimized versions of the models. Additionally, using more satellites in the optimization procedure produces more accurate results. This procedure reduces the number of large errors in the model, that is, it reduces the number of outliers in the error distribution. The TS04 model shows the most accurate results after the optimization in terms of both the magnitude and direction, when using at least six satellites in the fitting. It gave a smaller error than its unoptimized counterpart 57.3% of the time and outperformed the best unoptimized model (T02) 56.2% of the time. Its median percentage error in |B| was reduced from 4.54% to 3.84%. Finally, the difference among the models analyzed, when compared in terms of the median of the error distributions, is not very large. However, the unoptimized models can have very large errors, which are much reduced after the optimization.« less

Automatic design of basin-specific drought indexes for highly regulated water systems

NASA Astrophysics Data System (ADS)

Zaniolo, Marta; Giuliani, Matteo; Castelletti, Andrea Francesco; Pulido-Velazquez, Manuel

2018-04-01

Socio-economic costs of drought are progressively increasing worldwide due to undergoing alterations of hydro-meteorological regimes induced by climate change. Although drought management is largely studied in the literature, traditional drought indexes often fail at detecting critical events in highly regulated systems, where natural water availability is conditioned by the operation of water infrastructures such as dams, diversions, and pumping wells. Here, ad hoc index formulations are usually adopted based on empirical combinations of several, supposed-to-be significant, hydro-meteorological variables. These customized formulations, however, while effective in the design basin, can hardly be generalized and transferred to different contexts. In this study, we contribute FRIDA (FRamework for Index-based Drought Analysis), a novel framework for the automatic design of basin-customized drought indexes. In contrast to ad hoc empirical approaches, FRIDA is fully automated, generalizable, and portable across different basins. FRIDA builds an index representing a surrogate of the drought conditions of the basin, computed by combining all the relevant available information about the water circulating in the system identified by means of a feature extraction algorithm. We used the Wrapper for Quasi-Equally Informative Subset Selection (W-QEISS), which features a multi-objective evolutionary algorithm to find Pareto-efficient subsets of variables by maximizing the wrapper accuracy, minimizing the number of selected variables, and optimizing relevance and redundancy of the subset. The preferred variable subset is selected among the efficient solutions and used to formulate the final index according to alternative model structures. We apply FRIDA to the case study of the Jucar river basin (Spain), a drought-prone and highly regulated Mediterranean water resource system, where an advanced drought management plan relying on the formulation of an ad hoc state index is used for triggering drought management measures. The state index was constructed empirically with a trial-and-error process begun in the 1980s and finalized in 2007, guided by the experts from the Confederación Hidrográfica del Júcar (CHJ). Our results show that the automated variable selection outcomes align with CHJ's 25-year-long empirical refinement. In addition, the resultant FRIDA index outperforms the official State Index in terms of accuracy in reproducing the target variable and cardinality of the selected inputs set.

New dimension analyses with error analysis for quaking aspen and black spruce

NASA Technical Reports Server (NTRS)

Woods, K. D.; Botkin, D. B.; Feiveson, A. H.

1987-01-01

Dimension analysis for black spruce in wetland stands and trembling aspen are reported, including new approaches in error analysis. Biomass estimates for sacrificed trees have standard errors of 1 to 3%; standard errors for leaf areas are 10 to 20%. Bole biomass estimation accounts for most of the error for biomass, while estimation of branch characteristics and area/weight ratios accounts for the leaf area error. Error analysis provides insight for cost effective design of future analyses. Predictive equations for biomass and leaf area, with empirically derived estimators of prediction error, are given. Systematic prediction errors for small aspen trees and for leaf area of spruce from different site-types suggest a need for different predictive models within species. Predictive equations are compared with published equations; significant differences may be due to species responses to regional or site differences. Proportional contributions of component biomass in aspen change in ways related to tree size and stand development. Spruce maintains comparatively constant proportions with size, but shows changes corresponding to site. This suggests greater morphological plasticity of aspen and significance for spruce of nutrient conditions.

Empires, Exceptions, and Anglo-Saxons: Race and Rule between the British and Unites States Empires, 1880-1910. Teaching the JAH.

ERIC Educational Resources Information Center

OAH Magazine of History, 2002

2002-01-01

Summarizes a teaching document that is part of "Teaching the JAH" (Journal of American History) which corresponds to the article, "Empires, Exceptions, and Anglo-Saxons: Race and Rule between the British and Unites States Empires, 1880-1910" (Paul A. Kramer). Provides the Web site address for the complete installment. (CMK)

Improvements in GRACE Gravity Field Determination through Stochastic Observation Modeling

NASA Astrophysics Data System (ADS)

McCullough, C.; Bettadpur, S. V.

2016-12-01

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

Controls of channel morphology and sediment concentration on flow resistance in a large sand-bed river: A case study of the lower Yellow River

NASA Astrophysics Data System (ADS)

Ma, Yuanxu; Huang, He Qing

2016-07-01

Accurate estimation of flow resistance is crucial for flood routing, flow discharge and velocity estimation, and engineering design. Various empirical and semiempirical flow resistance models have been developed during the past century; however, a universal flow resistance model for varying types of rivers has remained difficult to be achieved to date. In this study, hydrometric data sets from six stations in the lower Yellow River during 1958-1959 are used to calibrate three empirical flow resistance models (Eqs. (5)-(7)) and evaluate their predictability. A group of statistical measures have been used to evaluate the goodness of fit of these models, including root mean square error (RMSE), coefficient of determination (CD), the Nash coefficient (NA), mean relative error (MRE), mean symmetry error (MSE), percentage of data with a relative error ≤ 50% and 25% (P50, P25), and percentage of data with overestimated error (POE). Three model selection criterions are also employed to assess the model predictability: Akaike information criterion (AIC), Bayesian information criterion (BIC), and a modified model selection criterion (MSC). The results show that mean flow depth (d) and water surface slope (S) can only explain a small proportion of variance in flow resistance. When channel width (w) and suspended sediment concentration (SSC) are involved, the new model (7) achieves a better performance than the previous ones. The MRE of model (7) is generally < 20%, which is apparently better than that reported by previous studies. This model is validated using the data sets from the corresponding stations during 1965-1966, and the results show larger uncertainties than the calibrating model. This probably resulted from the temporal shift of dominant controls caused by channel change resulting from varying flow regime. With the advancements of earth observation techniques, information about channel width, mean flow depth, and suspended sediment concentration can be effectively extracted from multisource satellite images. We expect that the empirical methods developed in this study can be used as an effective surrogate in estimation of flow resistance in the large sand-bed rivers like the lower Yellow River.

Measurements of the toroidal torque balance of error field penetration locked modes

DOE PAGES

Shiraki, Daisuke; Paz-Soldan, Carlos; Hanson, Jeremy M.; ...

2015-01-05

Here, detailed measurements from the DIII-D tokamak of the toroidal dynamics of error field penetration locked modes under the influence of slowly evolving external fields, enable study of the toroidal torques on the mode, including interaction with the intrinsic error field. The error field in these low density Ohmic discharges is well known based on the mode penetration threshold, allowing resonant and non-resonant torque effects to be distinguished. These m/n = 2/1 locked modes are found to be well described by a toroidal torque balance between the resonant interaction with n = 1 error fields, and a viscous torque inmore » the electron diamagnetic drift direction which is observed to scale as the square of the perturbed field due to the island. Fitting to this empirical torque balance allows a time-resolved measurement of the intrinsic error field of the device, providing evidence for a time-dependent error field in DIII-D due to ramping of the Ohmic coil current.« less

3. VIEW OF EMPIRE STATE MINE WITH TAILING PILE IN ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

3. VIEW OF EMPIRE STATE MINE WITH TAILING PILE IN BOTTOM LEFT AND COLLAPSED ADIT LOCATED BELOW DARK SHADOWS IN FAR RIGHT/LOWER THIRD. COLLAPSED BUILDING AND PARTIAL VIEW OF ORE CHUTE/BIN IS VISIBLE ON HILLSIDE ABOVE TAILINGS. CAMERA POINTED NORTH/NORTHWEST. - Florida Mountain Mining Sites, Empire State Mine, West side of Florida Mountain, Silver City, Owyhee County, ID

Software reliability: Additional investigations into modeling with replicated experiments

NASA Technical Reports Server (NTRS)

Nagel, P. M.; Schotz, F. M.; Skirvan, J. A.

1984-01-01

The effects of programmer experience level, different program usage distributions, and programming languages are explored. All these factors affect performance, and some tentative relational hypotheses are presented. An analytic framework for replicated and non-replicated (traditional) software experiments is presented. A method of obtaining an upper bound on the error rate of the next error is proposed. The method was validated empirically by comparing forecasts with actual data. In all 14 cases the bound exceeded the observed parameter, albeit somewhat conservatively. Two other forecasting methods are proposed and compared to observed results. Although demonstrated relative to this framework that stages are neither independent nor exponentially distributed, empirical estimates show that the exponential assumption is nearly valid for all but the extreme tails of the distribution. Except for the dependence in the stage probabilities, Cox's model approximates to a degree what is being observed.

Adaptive Automation and Cue Invocation: The Effect of Cue Timing on Operator Error

DTIC Science & Technology

2013-05-01

129. 5. Parasuraman, R. (2000). Designing automation for human use: Empirical studies and quantitative models. Ergonomics , 43, 931-951. 6...Prospective memory errors involve memory for intended actions that are planned to be performed at some designated point in the future [20]. In the DMOO...RESCHU) [21] was used in this study. A Navy pilot who is familiar with supervisory control tasks designed the RESCHU task and the task has been

Influence of uncertainties of the empirical models for inferring the E-region electric fields at the dip equator

NASA Astrophysics Data System (ADS)

Moro, Juliano; Denardini, Clezio Marcos; Resende, Laysa Cristina Araújo; Chen, Sony Su; Schuch, Nelson Jorge

2016-06-01

Daytime E-region electric fields play a crucial role in the ionospheric dynamics at the geomagnetic dip latitudes. Due to their importance, there is an interest in accurately measuring and modeling the electric fields for both climatological and near real-time studies. In this work, we present the daytime vertical ( Ez) and eastward ( Ey) electric fields for a reference quiet day (February 7, 2001) at the São Luís Space Observatory, Brazil (SLZ, 2.31°S, 44.16°W). The component Ez is inferred from Doppler shifts of type II echoes (gradient drift instability) and the anisotropic factor, which is computed from ion and electron gyro frequencies as well as ion and electron collision frequencies with neutral molecules. The component Ey depends on the ratio of Hall and Pedersen conductivities and Ez. A magnetic field-line-integrated conductivity model is used to obtain the anisotropic factor for calculating Ez and the ionospheric conductivities for calculating Ey. This model uses the NRLMSISE-00, IRI-2007, and IGRF-11 empirical models as input parameters for neutral atmosphere, ionosphere, and geomagnetic field, respectively. Consequently, it is worth determining the uncertainties (or errors) in Ey and Ez associated with these empirical model outputs in order to precisely define the confidence limit for the estimated electric field components. For this purpose, errors of ±10 % were artificially introduced in the magnitude of each empirical model output before estimating Ey and Ez. The corresponding uncertainties in the ionospheric conductivity and electric field are evaluated considering the individual and cumulative contribution of the artificial errors. The results show that the neutral densities and temperature may be responsible for the largest changes in Ey and Ez, followed by changes in the geomagnetic field intensity and electron and ions compositions.

Interprofessional conflict and medical errors: results of a national multi-specialty survey of hospital residents in the US.

PubMed

Baldwin, Dewitt C; Daugherty, Steven R

2008-12-01

Clear communication is considered the sine qua non of effective teamwork. Breakdowns in communication resulting from interprofessional conflict are believed to potentiate errors in the care of patients, although there is little supportive empirical evidence. In 1999, we surveyed a national, multi-specialty sample of 6,106 residents (64.2% response rate). Three questions inquired about "serious conflict" with another staff member. Residents were also asked whether they had made a "significant medical error" (SME) during their current year of training, and whether this resulted in an "adverse patient outcome" (APO). Just over 20% (n = 722) reported "serious conflict" with another staff member. Ten percent involved another resident, 8.3% supervisory faculty, and 8.9% nursing staff. Of the 2,813 residents reporting no conflict with other professional colleagues, 669, or 23.8%, recorded having made an SME, with 3.4% APOs. By contrast, the 523 residents who reported conflict with at least one other professional had 36.4% SMEs and 8.3% APOs. For the 187 reporting conflict with two or more other professionals, the SME rate was 51%, with 16% APOs. The empirical association between interprofessional conflict and medical errors is both alarming and intriguing, although the exact nature of this relationship cannot currently be determined from these data. Several theoretical constructs are advanced to assist our thinking about this complex issue.

Vast Portfolio Selection with Gross-exposure Constraints*

PubMed Central

Fan, Jianqing; Zhang, Jingjin; Yu, Ke

2012-01-01

We introduce the large portfolio selection using gross-exposure constraints. We show that with gross-exposure constraint the empirically selected optimal portfolios based on estimated covariance matrices have similar performance to the theoretical optimal ones and there is no error accumulation effect from estimation of vast covariance matrices. This gives theoretical justification to the empirical results in Jagannathan and Ma (2003). We also show that the no-short-sale portfolio can be improved by allowing some short positions. The applications to portfolio selection, tracking, and improvements are also addressed. The utility of our new approach is illustrated by simulation and empirical studies on the 100 Fama-French industrial portfolios and the 600 stocks randomly selected from Russell 3000. PMID:23293404

Empirical Observations on the Sensitivity of Hot Cathode Ionization Type Vacuum Gages

NASA Technical Reports Server (NTRS)

Summers, R. L.

1969-01-01

A study of empirical methods of predicting tile relative sensitivities of hot cathode ionization gages is presented. Using previously published gage sensitivities, several rules for predicting relative sensitivity are tested. The relative sensitivity to different gases is shown to be invariant with gage type, in the linear range of gage operation. The total ionization cross section, molecular and molar polarizability, and refractive index are demonstrated to be useful parameters for predicting relative gage sensitivity. Using data from the literature, the probable error of predictions of relative gage sensitivity based on these molecular properties is found to be about 10 percent. A comprehensive table of predicted relative sensitivities, based on empirical methods, is presented.

Modeling of Principal Flank Wear: An Empirical Approach Combining the Effect of Tool, Environment and Workpiece Hardness

NASA Astrophysics Data System (ADS)

Mia, Mozammel; Al Bashir, Mahmood; Dhar, Nikhil Ranjan

2016-10-01

Hard turning is increasingly employed in machining, lately, to replace time-consuming conventional turning followed by grinding process. An excessive amount of tool wear in hard turning is one of the main hurdles to be overcome. Many researchers have developed tool wear model, but most of them developed it for a particular work-tool-environment combination. No aggregate model is developed that can be used to predict the amount of principal flank wear for specific machining time. An empirical model of principal flank wear (VB) has been developed for the different hardness of workpiece (HRC40, HRC48 and HRC56) while turning by coated carbide insert with different configurations (SNMM and SNMG) under both dry and high pressure coolant conditions. Unlike other developed model, this model includes the use of dummy variables along with the base empirical equation to entail the effect of any changes in the input conditions on the response. The base empirical equation for principal flank wear is formulated adopting the Exponential Associate Function using the experimental results. The coefficient of dummy variable reflects the shifting of the response from one set of machining condition to another set of machining condition which is determined by simple linear regression. The independent cutting parameters (speed, rate, depth of cut) are kept constant while formulating and analyzing this model. The developed model is validated with different sets of machining responses in turning hardened medium carbon steel by coated carbide inserts. For any particular set, the model can be used to predict the amount of principal flank wear for specific machining time. Since the predicted results exhibit good resemblance with experimental data and the average percentage error is <10 %, this model can be used to predict the principal flank wear for stated conditions.

Semi-empirical and phenomenological instrument functions for the scanning tunneling microscope

NASA Astrophysics Data System (ADS)

Feuchtwang, T. E.; Cutler, P. H.; Notea, A.

1988-08-01

Recent progress in the development of a convenient algorithm for the determination of a quantitative local density of states (LDOS) of the sample, from data measured in the STM, is reviewd. It is argued that the sample LDOS strikes a good balance between the information content of a surface characteristic and effort required to obtain it experimentally. Hence, procedures to determine the sample LDOS as directly and as tip-model independently as possible are emphasized. The solution of the STM's "inverse" problem in terms of novel versions of the instrument (or Green) function technique is considered in preference to the well known, more direct solutions. Two types of instrument functions are considered: Approximations of the basic tip-instrument function obtained from the transfer Hamiltonian theory of the STM-STS. And, phenomenological instrument functions devised as a systematic scheme for semi-empirical first order corrections of "ideal" models. The instrument function, in this case, describes the corrections as the response of an independent component of the measuring apparatus inserted between the "ideal" instrument and the measured data. This linear response theory of measurement is reviewed and applied. A procedure for the estimation of the consistency of the model and the systematic errors due to the use of an approximate instrument function is presented. The independence of the instrument function techniques from explicit microscopic models of the tip is noted. The need for semi-empirical, as opposed to strictly empirical or analytical determination of the instrument function is discussed. The extension of the theory to the scanning tunneling spectrometer is noted, as well as its use in a theory of resolution.

Inference With Difference-in-Differences With a Small Number of Groups: A Review, Simulation Study, and Empirical Application Using SHARE Data.

PubMed

Rokicki, Slawa; Cohen, Jessica; Fink, Günther; Salomon, Joshua A; Landrum, Mary Beth

2018-01-01

Difference-in-differences (DID) estimation has become increasingly popular as an approach to evaluate the effect of a group-level policy on individual-level outcomes. Several statistical methodologies have been proposed to correct for the within-group correlation of model errors resulting from the clustering of data. Little is known about how well these corrections perform with the often small number of groups observed in health research using longitudinal data. First, we review the most commonly used modeling solutions in DID estimation for panel data, including generalized estimating equations (GEE), permutation tests, clustered standard errors (CSE), wild cluster bootstrapping, and aggregation. Second, we compare the empirical coverage rates and power of these methods using a Monte Carlo simulation study in scenarios in which we vary the degree of error correlation, the group size balance, and the proportion of treated groups. Third, we provide an empirical example using the Survey of Health, Ageing, and Retirement in Europe. When the number of groups is small, CSE are systematically biased downwards in scenarios when data are unbalanced or when there is a low proportion of treated groups. This can result in over-rejection of the null even when data are composed of up to 50 groups. Aggregation, permutation tests, bias-adjusted GEE, and wild cluster bootstrap produce coverage rates close to the nominal rate for almost all scenarios, though GEE may suffer from low power. In DID estimation with a small number of groups, analysis using aggregation, permutation tests, wild cluster bootstrap, or bias-adjusted GEE is recommended.

Quantifying uncertainty in climate change science through empirical information theory.

PubMed

Majda, Andrew J; Gershgorin, Boris

2010-08-24

Quantifying the uncertainty for the present climate and the predictions of climate change in the suite of imperfect Atmosphere Ocean Science (AOS) computer models is a central issue in climate change science. Here, a systematic approach to these issues with firm mathematical underpinning is developed through empirical information theory. An information metric to quantify AOS model errors in the climate is proposed here which incorporates both coarse-grained mean model errors as well as covariance ratios in a transformation invariant fashion. The subtle behavior of model errors with this information metric is quantified in an instructive statistically exactly solvable test model with direct relevance to climate change science including the prototype behavior of tracer gases such as CO(2). Formulas for identifying the most sensitive climate change directions using statistics of the present climate or an AOS model approximation are developed here; these formulas just involve finding the eigenvector associated with the largest eigenvalue of a quadratic form computed through suitable unperturbed climate statistics. These climate change concepts are illustrated on a statistically exactly solvable one-dimensional stochastic model with relevance for low frequency variability of the atmosphere. Viable algorithms for implementation of these concepts are discussed throughout the paper.

Correction techniques for depth errors with stereo three-dimensional graphic displays

NASA Technical Reports Server (NTRS)

Parrish, Russell V.; Holden, Anthony; Williams, Steven P.

1992-01-01

Three-dimensional (3-D), 'real-world' pictorial displays that incorporate 'true' depth cues via stereopsis techniques have proved effective for displaying complex information in a natural way to enhance situational awareness and to improve pilot/vehicle performance. In such displays, the display designer must map the depths in the real world to the depths available with the stereo display system. However, empirical data have shown that the human subject does not perceive the information at exactly the depth at which it is mathematically placed. Head movements can also seriously distort the depth information that is embedded in stereo 3-D displays because the transformations used in mapping the visual scene to the depth-viewing volume (DVV) depend intrinsically on the viewer location. The goal of this research was to provide two correction techniques; the first technique corrects the original visual scene to the DVV mapping based on human perception errors, and the second (which is based on head-positioning sensor input data) corrects for errors induced by head movements. Empirical data are presented to validate both correction techniques. A combination of the two correction techniques effectively eliminates the distortions of depth information embedded in stereo 3-D displays.

An evaluation of space time cube representation of spatiotemporal patterns.

PubMed

Kristensson, Per Ola; Dahlbäck, Nils; Anundi, Daniel; Björnstad, Marius; Gillberg, Hanna; Haraldsson, Jonas; Mårtensson, Ingrid; Nordvall, Mathias; Ståhl, Josefine

2009-01-01

Space time cube representation is an information visualization technique where spatiotemporal data points are mapped into a cube. Information visualization researchers have previously argued that space time cube representation is beneficial in revealing complex spatiotemporal patterns in a data set to users. The argument is based on the fact that both time and spatial information are displayed simultaneously to users, an effect difficult to achieve in other representations. However, to our knowledge the actual usefulness of space time cube representation in conveying complex spatiotemporal patterns to users has not been empirically validated. To fill this gap, we report on a between-subjects experiment comparing novice users' error rates and response times when answering a set of questions using either space time cube or a baseline 2D representation. For some simple questions, the error rates were lower when using the baseline representation. For complex questions where the participants needed an overall understanding of the spatiotemporal structure of the data set, the space time cube representation resulted in on average twice as fast response times with no difference in error rates compared to the baseline. These results provide an empirical foundation for the hypothesis that space time cube representation benefits users analyzing complex spatiotemporal patterns.

Sensorimotor Grounding of Musical Embodiment and the Role of Prediction: A Review

PubMed Central

Maes, Pieter-Jan

2016-01-01

In a previous article, we reviewed empirical evidence demonstrating action-based effects on music perception to substantiate the musical embodiment thesis (Maes et al., 2014). Evidence was largely based on studies demonstrating that music perception automatically engages motor processes, or that body states/movements influence music perception. Here, we argue that more rigorous evidence is needed before any decisive conclusion in favor of a “radical” musical embodiment thesis can be posited. In the current article, we provide a focused review of recent research to collect further evidence for the “radical” embodiment thesis that music perception is a dynamic process firmly rooted in the natural disposition of sounds and the human auditory and motor system. Though, we emphasize that, on top of these natural dispositions, long-term processes operate, rooted in repeated sensorimotor experiences and leading to learning, prediction, and error minimization. This approach sheds new light on the development of musical repertoires, and may refine our understanding of action-based effects on music perception as discussed in our previous article (Maes et al., 2014). Additionally, we discuss two of our recent empirical studies demonstrating that music performance relies on similar principles of sensorimotor dynamics and predictive processing. PMID:26973587

Sensorimotor Grounding of Musical Embodiment and the Role of Prediction: A Review.

PubMed

Maes, Pieter-Jan

2016-01-01

In a previous article, we reviewed empirical evidence demonstrating action-based effects on music perception to substantiate the musical embodiment thesis (Maes et al., 2014). Evidence was largely based on studies demonstrating that music perception automatically engages motor processes, or that body states/movements influence music perception. Here, we argue that more rigorous evidence is needed before any decisive conclusion in favor of a "radical" musical embodiment thesis can be posited. In the current article, we provide a focused review of recent research to collect further evidence for the "radical" embodiment thesis that music perception is a dynamic process firmly rooted in the natural disposition of sounds and the human auditory and motor system. Though, we emphasize that, on top of these natural dispositions, long-term processes operate, rooted in repeated sensorimotor experiences and leading to learning, prediction, and error minimization. This approach sheds new light on the development of musical repertoires, and may refine our understanding of action-based effects on music perception as discussed in our previous article (Maes et al., 2014). Additionally, we discuss two of our recent empirical studies demonstrating that music performance relies on similar principles of sensorimotor dynamics and predictive processing.

Van Allen Probes Observations of Plasmasphere Refilling Inside and Outside the Plasmapause

NASA Astrophysics Data System (ADS)

De Pascuale, S.; Kletzing, C.; Kurth, W. S.; Jordanova, V. K.

2017-12-01

We survey several geomagnetic storms observed by the Van Allen Probes to determine the rate of plasmasphere refilling following the initial erosion of the plasmapause region. The EMFISIS instrument on board the spacecraft provides near-equatorial in situ electron density measurements, which are accurate to 10% error in the detectable range 2 < L < 6. Two-dimensional plasmasphere density simulations, providing global context of local observations, are driven by the incident solar wind electric field as a proxy for geomagnetic activity. The simulations utilize a semi-empirical model of convection and a semi-empirical model of ionospheric outflow to dynamically evolve plasmaspheric densities. We find that at high L the plasmasphere undergoes orders of magnitude density depletion (from 100s - 10s cm-3) in response to a geomagnetic event and recovers to pre-storm levels over many days. At low L ( 1000s cm-3), and within the plasmapause, the plasmasphere loses density by a factor of 2 to 3 (from 3000 - 1000 cm-3) producing a depletion that can persist over weeks during sustained geomagnetic activity. We describe the impact of these results on the challenge of defining a saturated quiet state of the plasmasphere.

An Empirical Approach to Ocean Color Data: Reducing Bias and the Need for Post-Launch Radiometric Re-Calibration

NASA Technical Reports Server (NTRS)

Gregg, Watson W.; Casey, Nancy W.; O'Reilly, John E.; Esaias, Wayne E.

2009-01-01

A new empirical approach is developed for ocean color remote sensing. Called the Empirical Satellite Radiance-In situ Data (ESRID) algorithm, the approach uses relationships between satellite water-leaving radiances and in situ data after full processing, i.e., at Level-3, to improve estimates of surface variables while relaxing requirements on post-launch radiometric re-calibration. The approach is evaluated using SeaWiFS chlorophyll, which is the longest time series of the most widely used ocean color geophysical product. The results suggest that ESRID 1) drastically reduces the bias of ocean chlorophyll, most impressively in coastal regions, 2) modestly improves the uncertainty, and 3) reduces the sensitivity of global annual median chlorophyll to changes in radiometric re-calibration. Simulated calibration errors of 1% or less produce small changes in global median chlorophyll (less than 2.7%). In contrast, the standard NASA algorithm set is highly sensitive to radiometric calibration: similar 1% calibration errors produce changes in global median chlorophyll up to nearly 25%. We show that 0.1% radiometric calibration error (about 1% in water-leaving radiance) is needed to prevent radiometric calibration errors from changing global annual median chlorophyll more than the maximum interannual variability observed in the SeaWiFS 9-year record (+/- 3%), using the standard method. This is much more stringent than the goal for SeaWiFS of 5% uncertainty for water leaving radiance. The results suggest ocean color programs might consider less emphasis of expensive efforts to improve post-launch radiometric re-calibration in favor of increased efforts to characterize in situ observations of ocean surface geophysical products. Although the results here are focused on chlorophyll, in principle the approach described by ESRID can be applied to any surface variable potentially observable by visible remote sensing.

Communication: Evaluating non-empirical double hybrid functionals for spin-state energetics in transition-metal complexes

NASA Astrophysics Data System (ADS)

Wilbraham, Liam; Adamo, Carlo; Ciofini, Ilaria

2018-01-01

The computationally assisted, accelerated design of inorganic functional materials often relies on the ability of a given electronic structure method to return the correct electronic ground state of the material in question. Outlining difficulties with current density functionals and wave function-based approaches, we highlight why double hybrid density functionals represent promising candidates for this purpose. In turn, we show that PBE0-DH (and PBE-QIDH) offers a significant improvement over its hybrid parent functional PBE0 [as well as B3LYP* and coupled cluster singles and doubles with perturbative triples (CCSD(T))] when computing spin-state splitting energies, using high-level diffusion Monte Carlo calculations as a reference. We refer to the opposing influence of Hartree-Fock (HF) exchange and MP2, which permits higher levels of HF exchange and a concomitant reduction in electronic density error, as the reason for the improved performance of double-hybrid functionals relative to hybrid functionals. Additionally, using 16 transition metal (Fe and Co) complexes, we show that low-spin states are stabilised by increasing contributions from MP2 within the double hybrid formulation. Furthermore, this stabilisation effect is more prominent for high field strength ligands than low field strength ligands.

Restrictive Factors and Output Forecast of Green Development of Agricultural Industry Based on Gray System

NASA Astrophysics Data System (ADS)

Sun, Fengru

2018-01-01

This paper analyzes the characteristics of agricultural products from the perspective of agricultural production, farmers’ income, adjustment of agricultural structure and environmental improvement, and analyzes the characteristics of agricultural products in LanZhou area. Through data mining and empirical analysis, the regional agriculture (1) forecasting model of gray system with dynamic data processing, combined with the output data of lily in 2004-2003, the yield prediction is predicted and the fitting state is good and the error is small. Finally, combined with the relevant characteristics of the local characteristics of the agricultural industry to make reference, by changing the characteristics of agricultural production as the center of the mindset, and agricultural industrialization and organic combination, take the characteristics of efficient industrialization of agricultural products.

Theory of mind in social anxiety disorder, depression, and comorbid conditions.

PubMed

Washburn, Dustin; Wilson, Gillian; Roes, Meighen; Rnic, Katerina; Harkness, Kate Leslie

2016-01-01

Social anxiety disorder is characterized by marked interpersonal impairment, particularly when presenting with comorbid major depression. However, the foundational social-cognitive skills that underlie interpersonal impairment in comorbid and non-comorbid manifestations of SAD has to date received very little empirical investigation. In a sample of 119 young adults, the current study examined differences in theory of mind (ToM), defined as the ability to decode and reason about others' mental states, across four groups: (a) non-comorbid SAD; (b) non-comorbid Lifetime MDD; (c) comorbid SAD and Lifetime MDD; and (d) healthy control. The non-comorbid SAD group was significantly less accurate at decoding mental states than the non-comorbid MDD and control groups. Further, both the comorbid and non-comorbid SAD groups made significantly more 'excessive' ToM reasoning errors than the non-comorbid MDD group, suggesting a pattern of over-mentalizing. Findings are discussed in terms of their implications for understanding the social cognitive foundations of social anxiety. Copyright © 2015 Elsevier Ltd. All rights reserved.

Estimating the designated use attainment decision error rates of US Environmental Protection Agency's proposed numeric total phosphorus criteria for Florida, USA, colored lakes.

PubMed

McLaughlin, Douglas B

2012-01-01

The utility of numeric nutrient criteria established for certain surface waters is likely to be affected by the uncertainty that exists in the presence of a causal link between nutrient stressor variables and designated use-related biological responses in those waters. This uncertainty can be difficult to characterize, interpret, and communicate to a broad audience of environmental stakeholders. The US Environmental Protection Agency (USEPA) has developed a systematic planning process to support a variety of environmental decisions, but this process is not generally applied to the development of national or state-level numeric nutrient criteria. This article describes a method for implementing such an approach and uses it to evaluate the numeric total P criteria recently proposed by USEPA for colored lakes in Florida, USA. An empirical, log-linear relationship between geometric mean concentrations of total P (a potential stressor variable) and chlorophyll a (a nutrient-related response variable) in these lakes-that is assumed to be causal in nature-forms the basis for the analysis. The use of the geometric mean total P concentration of a lake to correctly indicate designated use status, defined in terms of a 20 µg/L geometric mean chlorophyll a threshold, is evaluated. Rates of decision errors analogous to the Type I and Type II error rates familiar in hypothesis testing, and a 3rd error rate, E(ni) , referred to as the nutrient criterion-based impairment error rate, are estimated. The results show that USEPA's proposed "baseline" and "modified" nutrient criteria approach, in which data on both total P and chlorophyll a may be considered in establishing numeric nutrient criteria for a given lake within a specified range, provides a means for balancing and minimizing designated use attainment decision errors. Copyright © 2011 SETAC.

New empirically-derived solar radiation pressure model for GPS satellites

NASA Technical Reports Server (NTRS)

Bar-Sever, Y.; Kuang, D.

2003-01-01

Solar radiation pressure force is the second largest perturbation acting on GPS satellites, after the gravitational attraction from the Earth, Sun, and Moon. It is the largest error source in the modeling of GPS orbital dynamics.

Incorporating measurement error in n = 1 psychological autoregressive modeling.

PubMed

Schuurman, Noémi K; Houtveen, Jan H; Hamaker, Ellen L

2015-01-01

Measurement error is omnipresent in psychological data. However, the vast majority of applications of autoregressive time series analyses in psychology do not take measurement error into account. Disregarding measurement error when it is present in the data results in a bias of the autoregressive parameters. We discuss two models that take measurement error into account: An autoregressive model with a white noise term (AR+WN), and an autoregressive moving average (ARMA) model. In a simulation study we compare the parameter recovery performance of these models, and compare this performance for both a Bayesian and frequentist approach. We find that overall, the AR+WN model performs better. Furthermore, we find that for realistic (i.e., small) sample sizes, psychological research would benefit from a Bayesian approach in fitting these models. Finally, we illustrate the effect of disregarding measurement error in an AR(1) model by means of an empirical application on mood data in women. We find that, depending on the person, approximately 30-50% of the total variance was due to measurement error, and that disregarding this measurement error results in a substantial underestimation of the autoregressive parameters.

Improved prediction of tacrolimus concentrations early after kidney transplantation using theory-based pharmacokinetic modelling.

PubMed

Størset, Elisabet; Holford, Nick; Hennig, Stefanie; Bergmann, Troels K; Bergan, Stein; Bremer, Sara; Åsberg, Anders; Midtvedt, Karsten; Staatz, Christine E

2014-09-01

The aim was to develop a theory-based population pharmacokinetic model of tacrolimus in adult kidney transplant recipients and to externally evaluate this model and two previous empirical models. Data were obtained from 242 patients with 3100 tacrolimus whole blood concentrations. External evaluation was performed by examining model predictive performance using Bayesian forecasting. Pharmacokinetic disposition parameters were estimated based on tacrolimus plasma concentrations, predicted from whole blood concentrations, haematocrit and literature values for tacrolimus binding to red blood cells. Disposition parameters were allometrically scaled to fat free mass. Tacrolimus whole blood clearance/bioavailability standardized to haematocrit of 45% and fat free mass of 60 kg was estimated to be 16.1 l h−1 [95% CI 12.6, 18.0 l h−1]. Tacrolimus clearance was 30% higher (95% CI 13, 46%) and bioavailability 18% lower (95% CI 2, 29%) in CYP3A5 expressers compared with non-expressers. An Emax model described decreasing tacrolimus bioavailability with increasing prednisolone dose. The theory-based model was superior to the empirical models during external evaluation displaying a median prediction error of −1.2% (95% CI −3.0, 0.1%). Based on simulation, Bayesian forecasting led to 65% (95% CI 62, 68%) of patients achieving a tacrolimus average steady-state concentration within a suggested acceptable range. A theory-based population pharmacokinetic model was superior to two empirical models for prediction of tacrolimus concentrations and seemed suitable for Bayesian prediction of tacrolimus doses early after kidney transplantation.

Predicting Pilot Error in Nextgen: Pilot Performance Modeling and Validation Efforts

NASA Technical Reports Server (NTRS)

Wickens, Christopher; Sebok, Angelia; Gore, Brian; Hooey, Becky

2012-01-01

We review 25 articles presenting 5 general classes of computational models to predict pilot error. This more targeted review is placed within the context of the broader review of computational models of pilot cognition and performance, including such aspects as models of situation awareness or pilot-automation interaction. Particular emphasis is placed on the degree of validation of such models against empirical pilot data, and the relevance of the modeling and validation efforts to Next Gen technology and procedures.

An Empirical Study of Re-sampling Techniques as a Method for Improving Error Estimates in Split-plot Designs

DTIC Science & Technology

2010-03-01

sufficient replications often lead to models that lack precision in error estimation and thus imprecision in corresponding conclusions. This work develops...v Preface This work is dedicated to all who gave and continue to give in order for me to achieve some semblance of success. Benjamin M. Lee vi...develop, examine and test methodologies for an- alyzing test results from split-plot designs. In particular, this work determines the applicability

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.

Online Deviation Detection for Medical Processes

PubMed Central

Christov, Stefan C.; Avrunin, George S.; Clarke, Lori A.

2014-01-01

Human errors are a major concern in many medical processes. To help address this problem, we are investigating an approach for automatically detecting when performers of a medical process deviate from the acceptable ways of performing that process as specified by a detailed process model. Such deviations could represent errors and, thus, detecting and reporting deviations as they occur could help catch errors before harm is done. In this paper, we identify important issues related to the feasibility of the proposed approach and empirically evaluate the approach for two medical procedures, chemotherapy and blood transfusion. For the evaluation, we use the process models to generate sample process executions that we then seed with synthetic errors. The process models describe the coordination of activities of different process performers in normal, as well as in exceptional situations. The evaluation results suggest that the proposed approach could be applied in clinical settings to help catch errors before harm is done. PMID:25954343

Measurement-based quantum communication with resource states generated by entanglement purification

NASA Astrophysics Data System (ADS)

Wallnöfer, J.; Dür, W.

2017-01-01

We investigate measurement-based quantum communication with noisy resource states that are generated by entanglement purification. We consider the transmission of encoded information via noisy quantum channels using a measurement-based implementation of encoding, error correction, and decoding. We show that such an approach offers advantages over direct transmission, gate-based error correction, and measurement-based schemes with direct generation of resource states. We analyze the noise structure of resource states generated by entanglement purification and show that a local error model, i.e., noise acting independently on all qubits of the resource state, is a good approximation in general, and provides an exact description for Greenberger-Horne-Zeilinger states. The latter are resources for a measurement-based implementation of error-correction codes for bit-flip or phase-flip errors. This provides an approach to link the recently found very high thresholds for fault-tolerant measurement-based quantum information processing based on local error models for resource states with error thresholds for gate-based computational models.

Five-wave-packet quantum error correction based on continuous-variable cluster entanglement

PubMed Central

Hao, Shuhong; Su, Xiaolong; Tian, Caixing; Xie, Changde; Peng, Kunchi

2015-01-01

Quantum error correction protects the quantum state against noise and decoherence in quantum communication and quantum computation, which enables one to perform fault-torrent quantum information processing. We experimentally demonstrate a quantum error correction scheme with a five-wave-packet code against a single stochastic error, the original theoretical model of which was firstly proposed by S. L. Braunstein and T. A. Walker. Five submodes of a continuous variable cluster entangled state of light are used for five encoding channels. Especially, in our encoding scheme the information of the input state is only distributed on three of the five channels and thus any error appearing in the remained two channels never affects the output state, i.e. the output quantum state is immune from the error in the two channels. The stochastic error on a single channel is corrected for both vacuum and squeezed input states and the achieved fidelities of the output states are beyond the corresponding classical limit. PMID:26498395

Microscopic saw mark analysis: an empirical approach.

PubMed

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.

Balancing aggregation and smoothing errors in inverse models

DOE PAGES

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.

Computation of Standard Errors

PubMed Central

Dowd, Bryan E; Greene, William H; Norton, Edward C

2014-01-01

Objectives We discuss the problem of computing the standard errors of functions involving estimated parameters and provide the relevant computer code for three different computational approaches using two popular computer packages. Study Design We show how to compute the standard errors of several functions of interest: the predicted value of the dependent variable for a particular subject, and the effect of a change in an explanatory variable on the predicted value of the dependent variable for an individual subject and average effect for a sample of subjects. Empirical Application Using a publicly available dataset, we explain three different methods of computing standard errors: the delta method, Krinsky–Robb, and bootstrapping. We provide computer code for Stata 12 and LIMDEP 10/NLOGIT 5. Conclusions In most applications, choice of the computational method for standard errors of functions of estimated parameters is a matter of convenience. However, when computing standard errors of the sample average of functions that involve both estimated parameters and nonstochastic explanatory variables, it is important to consider the sources of variation in the function's values. PMID:24800304

Tests for detecting overdispersion in models with measurement error in covariates.

PubMed

Yang, Yingsi; Wong, Man Yu

2015-11-30

Measurement error in covariates can affect the accuracy in count data modeling and analysis. In overdispersion identification, the true mean-variance relationship can be obscured under the influence of measurement error in covariates. In this paper, we propose three tests for detecting overdispersion when covariates are measured with error: a modified score test and two score tests based on the proposed approximate likelihood and quasi-likelihood, respectively. The proposed approximate likelihood is derived under the classical measurement error model, and the resulting approximate maximum likelihood estimator is shown to have superior efficiency. Simulation results also show that the score test based on approximate likelihood outperforms the test based on quasi-likelihood and other alternatives in terms of empirical power. By analyzing a real dataset containing the health-related quality-of-life measurements of a particular group of patients, we demonstrate the importance of the proposed methods by showing that the analyses with and without measurement error correction yield significantly different results. Copyright © 2015 John Wiley & Sons, Ltd.

Developing a Data Driven Process-Based Model for Remote Sensing of Ecosystem Production

NASA Astrophysics Data System (ADS)

Elmasri, B.; Rahman, A. F.

2010-12-01

Estimating ecosystem carbon fluxes at various spatial and temporal scales is essential for quantifying the global carbon cycle. Numerous models have been developed for this purpose using several environmental variables as well as vegetation indices derived from remotely sensed data. Here we present a data driven modeling approach for gross primary production (GPP) that is based on a process based model BIOME-BGC. The proposed model was run using available remote sensing data and it does not depend on look-up tables. Furthermore, this approach combines the merits of both empirical and process models, and empirical models were used to estimate certain input variables such as light use efficiency (LUE). This was achieved by using remotely sensed data to the mathematical equations that represent biophysical photosynthesis processes in the BIOME-BGC model. Moreover, a new spectral index for estimating maximum photosynthetic activity, maximum photosynthetic rate index (MPRI), is also developed and presented here. This new index is based on the ratio between the near infrared and the green bands (ρ858.5/ρ555). The model was tested and validated against MODIS GPP product and flux measurements from two eddy covariance flux towers located at Morgan Monroe State Forest (MMSF) in Indiana and Harvard Forest in Massachusetts. Satellite data acquired by the Advanced Microwave Scanning Radiometer (AMSR-E) and MODIS were used. The data driven model showed a strong correlation between the predicted and measured GPP at the two eddy covariance flux towers sites. This methodology produced better predictions of GPP than did the MODIS GPP product. Moreover, the proportion of error in the predicted GPP for MMSF and Harvard forest was dominated by unsystematic errors suggesting that the results are unbiased. The analysis indicated that maintenance respiration is one of the main factors that dominate the overall model outcome errors and improvement in maintenance respiration estimation will result in improved GPP predictions. Although there might be a room for improvements in our model outcomes through improved parameterization, our results suggest that such a methodology for running BIOME-BGC model based entirely on routinely available data can produce good predictions of GPP.

A suite of global reconstructed precipitation products and their error estimate by multivariate regression using empirical orthogonal functions: 1850-present

NASA Astrophysics Data System (ADS)

Shen, S. S.

2014-12-01

This presentation describes a suite of global precipitation products reconstructed by a multivariate regression method using an empirical orthogonal function (EOF) expansion. The sampling errors of the reconstruction are estimated for each product datum entry. The maximum temporal coverage is 1850-present and the spatial coverage is quasi-global (75S, 75N). The temporal resolution ranges from 5-day, monthly, to seasonal and annual. The Global Precipitation Climatology Project (GPCP) precipitation data from 1979-2008 are used to calculate the EOFs. The Global Historical Climatology Network (GHCN) gridded data are used to calculate the regression coefficients for reconstructions. The sampling errors of the reconstruction are analyzed in detail for different EOF modes. Our reconstructed 1900-2011 time series of the global average annual precipitation shows a 0.024 (mm/day)/100a trend, which is very close to the trend derived from the mean of 25 models of the CMIP5 (Coupled Model Intercomparison Project Phase 5). Our reconstruction examples of 1983 El Niño precipitation and 1917 La Niña precipitation (Figure 1) demonstrate that the El Niño and La Niña precipitation patterns are well reflected in the first two EOFs. The validation of our reconstruction results with GPCP makes it possible to use the reconstruction as the benchmark data for climate models. This will help the climate modeling community to improve model precipitation mechanisms and reduce the systematic difference between observed global precipitation, which hovers at around 2.7 mm/day for reconstructions and GPCP, and model precipitations, which have a range of 2.6-3.3 mm/day for CMIP5. Our precipitation products are publically available online, including digital data, precipitation animations, computer codes, readme files, and the user manual. This work is a joint effort between San Diego State University (Sam Shen, Nancy Tafolla, Barbara Sperberg, and Melanie Thorn) and University of Maryland (Phil Arkin, Tom Smith, Li Ren, and Li Dai) and supported in part by the U.S. National Science Foundation (Awards No. AGS-1015926 and AGS-1015957).

Ancient numerical daemons of conceptual hydrological modeling: 2. Impact of time stepping schemes on model analysis and prediction

NASA Astrophysics Data System (ADS)

Kavetski, Dmitri; Clark, Martyn P.

2010-10-01

Despite the widespread use of conceptual hydrological models in environmental research and operations, they remain frequently implemented using numerically unreliable methods. This paper considers the impact of the time stepping scheme on model analysis (sensitivity analysis, parameter optimization, and Markov chain Monte Carlo-based uncertainty estimation) and prediction. It builds on the companion paper (Clark and Kavetski, 2010), which focused on numerical accuracy, fidelity, and computational efficiency. Empirical and theoretical analysis of eight distinct time stepping schemes for six different hydrological models in 13 diverse basins demonstrates several critical conclusions. (1) Unreliable time stepping schemes, in particular, fixed-step explicit methods, suffer from troublesome numerical artifacts that severely deform the objective function of the model. These deformations are not rare isolated instances but can arise in any model structure, in any catchment, and under common hydroclimatic conditions. (2) Sensitivity analysis can be severely contaminated by numerical errors, often to the extent that it becomes dominated by the sensitivity of truncation errors rather than the model equations. (3) Robust time stepping schemes generally produce "better behaved" objective functions, free of spurious local optima, and with sufficient numerical continuity to permit parameter optimization using efficient quasi Newton methods. When implemented within a multistart framework, modern Newton-type optimizers are robust even when started far from the optima and provide valuable diagnostic insights not directly available from evolutionary global optimizers. (4) Unreliable time stepping schemes lead to inconsistent and biased inferences of the model parameters and internal states. (5) Even when interactions between hydrological parameters and numerical errors provide "the right result for the wrong reason" and the calibrated model performance appears adequate, unreliable time stepping schemes make the model unnecessarily fragile in predictive mode, undermining validation assessments and operational use. Erroneous or misleading conclusions of model analysis and prediction arising from numerical artifacts in hydrological models are intolerable, especially given that robust numerics are accepted as mainstream in other areas of science and engineering. We hope that the vivid empirical findings will encourage the conceptual hydrological community to close its Pandora's box of numerical problems, paving the way for more meaningful model application and interpretation.

Long-term care physical environments--effect on medication errors.

PubMed

Mahmood, Atiya; Chaudhury, Habib; Gaumont, Alana; Rust, Tiana

2012-01-01

Few studies examine physical environmental factors and their effects on staff health, effectiveness, work errors and job satisfaction. To address this gap, this study aims to examine environmental features and their role in medication and nursing errors in long-term care facilities. A mixed methodological strategy was used. Data were collected via focus groups, observing medication preparation and administration, and a nursing staff survey in four facilities. The paper reveals that, during the medication preparation phase, physical design, such as medication room layout, is a major source of potential errors. During medication administration, social environment is more likely to contribute to errors. Interruptions, noise and staff shortages were particular problems. The survey's relatively small sample size needs to be considered when interpreting the findings. Also, actual error data could not be included as existing records were incomplete. The study offers several relatively low-cost recommendations to help staff reduce medication errors. Physical environmental factors are important when addressing measures to reduce errors. The findings of this study underscore the fact that the physical environment's influence on the possibility of medication errors is often neglected. This study contributes to the scarce empirical literature examining the relationship between physical design and patient safety.

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.

Uncertainty vs. Information (Invited)

NASA Astrophysics Data System (ADS)

Nearing, Grey

2017-04-01

Information theory is the branch of logic that describes how rational epistemic states evolve in the presence of empirical data (Knuth, 2005), and any logic of science is incomplete without such a theory. Developing a formal philosophy of science that recognizes this fact results in essentially trivial solutions to several longstanding problems are generally considered intractable, including: • Alleviating the need for any likelihood function or error model. • Derivation of purely logical falsification criteria for hypothesis testing. • Specification of a general quantitative method for process-level model diagnostics. More generally, I make the following arguments: 1. Model evaluation should not proceed by quantifying and/or reducing error or uncertainty, and instead should be approached as a problem of ensuring that our models contain as much information as our experimental data. I propose that the latter is the only question a scientist actually has the ability to ask. 2. Instead of building geophysical models as solutions to differential equations that represent conservation laws, we should build models as maximum entropy distributions constrained by conservation symmetries. This will allow us to derive predictive probabilities directly from first principles. Knuth, K. H. (2005) 'Lattice duality: The origin of probability and entropy', Neurocomputing, 67, pp. 245-274.

Organisational sources of safety and danger: sociological contributions to the study of adverse events

PubMed Central

West, E.

2000-01-01

Organisational sociology has long accepted that mistakes of all kinds are a common, even normal, part of work. Medical work may be particularly prone to error because of its complexity and technological sophistication. The results can be tragic for individuals and families. This paper describes four intrinsic characteristics of organisations that are relevant to the level of risk and danger in healthcare settings—namely, the division of labour and "structural secrecy" in complex organisations; the homophily principle and social structural barriers to communication; diffusion of responsibility and the "problem of many hands"; and environmental or other pressures leading to goal displacement when organisations take their "eyes off the ball". The paper argues that each of these four intrinsic characteristics invokes specific mechanisms that increase danger in healthcare organisations but also offer the possibility of devising strategies and behaviours to increase patient safety. Stated as hypotheses, these ideas could be tested empirically, thus adding to the evidence on which the avoidance of adverse events in healthcare settings is based and contributing to the development of theory in this important area. (Quality in Health Care 2000;9:120–126) Key Words: organisation; safety; errors; adverse events PMID:11067250

Software IV and V Research Priorities and Applied Program Accomplishments Within NASA

NASA Technical Reports Server (NTRS)

Blazy, Louis J.

2000-01-01

The mission of this research is to be world-class creators and facilitators of innovative, intelligent, high performance, reliable information technologies that enable NASA missions to (1) increase software safety and quality through error avoidance, early detection and resolution of errors, by utilizing and applying empirically based software engineering best practices; (2) ensure customer software risks are identified and/or that requirements are met and/or exceeded; (3) research, develop, apply, verify, and publish software technologies for competitive advantage and the advancement of science; and (4) facilitate the transfer of science and engineering data, methods, and practices to NASA, educational institutions, state agencies, and commercial organizations. The goals are to become a national Center Of Excellence (COE) in software and system independent verification and validation, and to become an international leading force in the field of software engineering for improving the safety, quality, reliability, and cost performance of software systems. This project addresses the following problems: Ensure safety of NASA missions, ensure requirements are met, minimize programmatic and technological risks of software development and operations, improve software quality, reduce costs and time to delivery, and improve the science of software engineering

Comprehensive Modeling of Temperature-Dependent Degradation Mechanisms in Lithium Iron Phosphate Batteries

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

Schimpe, Michael; von Kuepach, M. E.; Naumann, M.

For reliable lifetime predictions of lithium-ion batteries, models for cell degradation are required. A comprehensive semi-empirical model based on a reduced set of internal cell parameters and physically justified degradation functions for the capacity loss is developed and presented for a commercial lithium iron phosphate/graphite cell. One calendar and several cycle aging effects are modeled separately. Emphasis is placed on the varying degradation at different temperatures. Degradation mechanisms for cycle aging at high and low temperatures as well as the increased cycling degradation at high state of charge are calculated separately. For parameterization, a lifetime test study is conducted includingmore » storage and cycle tests. Additionally, the model is validated through a dynamic current profile based on real-world application in a stationary energy storage system revealing the accuracy. Tests for validation are continued for up to 114 days after the longest parametrization tests. In conclusion, the model error for the cell capacity loss in the application-based tests is at the end of testing below 1% of the original cell capacity and the maximum relative model error is below 21%.« less

Comprehensive Modeling of Temperature-Dependent Degradation Mechanisms in Lithium Iron Phosphate Batteries

DOE PAGES

Schimpe, Michael; von Kuepach, M. E.; Naumann, M.; ...

2018-01-12

For reliable lifetime predictions of lithium-ion batteries, models for cell degradation are required. A comprehensive semi-empirical model based on a reduced set of internal cell parameters and physically justified degradation functions for the capacity loss is developed and presented for a commercial lithium iron phosphate/graphite cell. One calendar and several cycle aging effects are modeled separately. Emphasis is placed on the varying degradation at different temperatures. Degradation mechanisms for cycle aging at high and low temperatures as well as the increased cycling degradation at high state of charge are calculated separately. For parameterization, a lifetime test study is conducted includingmore » storage and cycle tests. Additionally, the model is validated through a dynamic current profile based on real-world application in a stationary energy storage system revealing the accuracy. Tests for validation are continued for up to 114 days after the longest parametrization tests. In conclusion, the model error for the cell capacity loss in the application-based tests is at the end of testing below 1% of the original cell capacity and the maximum relative model error is below 21%.« less

A stale challenge to the philosophy of science: commentary on "Is psychology based on a methodological error?" by Michael Schwarz.

PubMed

Ruck, Nora; Slunecko, Thomas

2010-06-01

In his article "Is psychology based on a methodological error?" and based on a quite convincing empirical basis, Michael Schwarz offers a methodological critique of one of mainstream psychology's key test theoretical axioms, i.e., that of the in principle normal distribution of personality variables. It is characteristic of this paper--and at first seems to be a strength of it--that the author positions his critique within a frame of philosophy of science, particularly positioning himself in the tradition of Karl Popper's critical rationalism. When scrutinizing Schwarz's arguments, however, we find Schwarz's critique profound only as an immanent critique of test theoretical axioms. We raise doubts, however, as to Schwarz's alleged 'challenge' to the philosophy of science because the author not at all seems to be in touch with the state of the art of contemporary philosophy of science. Above all, we question the universalist undercurrent that Schwarz's 'bio-psycho-social model' of human judgment boils down to. In contrast to such position, we close our commentary with a plea for a context- and culture sensitive philosophy of science.

Are stock market returns related to the weather effects? Empirical evidence from Taiwan

NASA Astrophysics Data System (ADS)

Chang, Tsangyao; Nieh, Chien-Chung; Yang, Ming Jing; Yang, Tse-Yu

2006-05-01

In this study, we employ a recently developed econometric technique of the threshold model with the GJR-GARCH process on error terms to investigate the relationships between weather factors and stock market returns in Taiwan using daily data for the period of 1 July 1997-22 October 2003. The major weather factors studied include temperature, humidity, and cloud cover. Our empirical evidence shows that temperature and cloud cover are two important weather factors that affect the stock returns in Taiwan. Our empirical findings further support the previous arguments that advocate the inclusion of economically neutral behavioral variables in asset pricing models. These results also have significant implications for individual investors and financial institutions planning to invest in the Taiwan stock market.

The spectral basis of optimal error field correction on DIII-D

DOE PAGES

Paz-Soldan, Carlos A.; Buttery, Richard J.; Garofalo, Andrea M.; ...

2014-04-28

Here, experimental optimum error field correction (EFC) currents found in a wide breadth of dedicated experiments on DIII-D are shown to be consistent with the currents required to null the poloidal harmonics of the vacuum field which drive the kink mode near the plasma edge. This allows the identification of empirical metrics which predict optimal EFC currents with accuracy comparable to that of first- principles modeling which includes the ideal plasma response. While further metric refinements are desirable, this work suggests optimal EFC currents can be effectively fed-forward based purely on knowledge of the vacuum error field and basic equilibriummore » properties which are routinely calculated in real-time.« less

Estimation of clear-sky insolation using satellite and ground meteorological data

NASA Technical Reports Server (NTRS)

Staylor, W. F.; Darnell, W. L.; Gupta, S. K.

1983-01-01

Ground based pyranometer measurements were combined with meteorological data from the Tiros N satellite in order to estimate clear-sky insolations at five U.S. sites for five weeks during the spring of 1979. The estimates were used to develop a semi-empirical model of clear-sky insolation for the interpretation of input data from the Tiros Operational Vertical Sounder (TOVS). Using only satellite data, the estimated standard errors in the model were about 2 percent. The introduction of ground based data reduced errors to around 1 percent. It is shown that although the errors in the model were reduced by only 1 percent, TOVS data products are still adequate for estimating clear-sky insolation.

Directional variance adjustment: bias reduction in covariance matrices based on factor analysis with an application to portfolio optimization.

PubMed

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.

Directional Variance Adjustment: Bias Reduction in Covariance Matrices Based on Factor Analysis with an Application to Portfolio Optimization

PubMed Central

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

Observing Reasonable Consumers.

ERIC Educational Resources Information Center

Silber, Norman I.

1991-01-01

Although courts and legislators usually set legal standards that correspond to empirical knowledge of human behavior, recent developments in behavioral psychology have led courts to appreciate the limits and errors in consumer decision making. "Reasonable consumer" standards that are congruent with cognitive reality should be developed.…

Observations concerning Research Literature on Neuro-Linguistic Programming.

ERIC Educational Resources Information Center

Einspruch, Eric L.; Forman, Bruce D.

1985-01-01

Identifies six categories of design and methodological errors contained in the 39 empirical studies of neurolinguistic programming (NLP) documented through April 1984. Representative reports reflecting each category are discussed. Suggestions are offered for improving the quality of research on NLP. (Author/MCF)

Multivariate Error Covariance Estimates by Monte-Carlo Simulation for Assimilation Studies in the Pacific Ocean

NASA Technical Reports Server (NTRS)

Borovikov, Anna; Rienecker, Michele M.; Keppenne, Christian; Johnson, Gregory C.

2004-01-01

One of the most difficult aspects of ocean state estimation is the prescription of the model forecast error covariances. The paucity of ocean observations limits our ability to estimate the covariance structures from model-observation differences. In most practical applications, simple covariances are usually prescribed. Rarely are cross-covariances between different model variables used. Here a comparison is made between a univariate Optimal Interpolation (UOI) scheme and a multivariate OI algorithm (MvOI) in the assimilation of ocean temperature. In the UOI case only temperature is updated using a Gaussian covariance function and in the MvOI salinity, zonal and meridional velocities as well as temperature, are updated using an empirically estimated multivariate covariance matrix. Earlier studies have shown that a univariate OI has a detrimental effect on the salinity and velocity fields of the model. Apparently, in a sequential framework it is important to analyze temperature and salinity together. For the MvOI an estimation of the model error statistics is made by Monte-Carlo techniques from an ensemble of model integrations. An important advantage of using an ensemble of ocean states is that it provides a natural way to estimate cross-covariances between the fields of different physical variables constituting the model state vector, at the same time incorporating the model's dynamical and thermodynamical constraints as well as the effects of physical boundaries. Only temperature observations from the Tropical Atmosphere-Ocean array have been assimilated in this study. In order to investigate the efficacy of the multivariate scheme two data assimilation experiments are validated with a large independent set of recently published subsurface observations of salinity, zonal velocity and temperature. For reference, a third control run with no data assimilation is used to check how the data assimilation affects systematic model errors. While the performance of the UOI and MvOI is similar with respect to the temperature field, the salinity and velocity fields are greatly improved when multivariate correction is used, as evident from the analyses of the rms differences of these fields and independent observations. The MvOI assimilation is found to improve upon the control run in generating the water masses with properties close to the observed, while the UOI failed to maintain the temperature and salinity structure.

Statistically Self-Consistent and Accurate Errors for SuperDARN Data

NASA Astrophysics Data System (ADS)

Reimer, A. S.; Hussey, G. C.; McWilliams, K. A.

2018-01-01

The Super Dual Auroral Radar Network (SuperDARN)-fitted data products (e.g., spectral width and velocity) are produced using weighted least squares fitting. We present a new First-Principles Fitting Methodology (FPFM) that utilizes the first-principles approach of Reimer et al. (2016) to estimate the variance of the real and imaginary components of the mean autocorrelation functions (ACFs) lags. SuperDARN ACFs fitted by the FPFM do not use ad hoc or empirical criteria. Currently, the weighting used to fit the ACF lags is derived from ad hoc estimates of the ACF lag variance. Additionally, an overcautious lag filtering criterion is used that sometimes discards data that contains useful information. In low signal-to-noise (SNR) and/or low signal-to-clutter regimes the ad hoc variance and empirical criterion lead to underestimated errors for the fitted parameter because the relative contributions of signal, noise, and clutter to the ACF variance is not taken into consideration. The FPFM variance expressions include contributions of signal, noise, and clutter. The clutter is estimated using the maximal power-based self-clutter estimator derived by Reimer and Hussey (2015). The FPFM was successfully implemented and tested using synthetic ACFs generated with the radar data simulator of Ribeiro, Ponomarenko, et al. (2013). The fitted parameters and the fitted-parameter errors produced by the FPFM are compared with the current SuperDARN fitting software, FITACF. Using self-consistent statistical analysis, the FPFM produces reliable or trustworthy quantitative measures of the errors of the fitted parameters. For an SNR in excess of 3 dB and velocity error below 100 m/s, the FPFM produces 52% more data points than FITACF.

Modeling conflict and error in the medial frontal cortex.

PubMed

Mayer, Andrew R; Teshiba, Terri M; Franco, Alexandre R; Ling, Josef; Shane, Matthew S; Stephen, Julia M; Jung, Rex E

2012-12-01

Despite intensive study, the role of the dorsal medial frontal cortex (dMFC) in error monitoring and conflict processing remains actively debated. The current experiment manipulated conflict type (stimulus conflict only or stimulus and response selection conflict) and utilized a novel modeling approach to isolate error and conflict variance during a multimodal numeric Stroop task. Specifically, hemodynamic response functions resulting from two statistical models that either included or isolated variance arising from relatively few error trials were directly contrasted. Twenty-four participants completed the task while undergoing event-related functional magnetic resonance imaging on a 1.5-Tesla scanner. Response times monotonically increased based on the presence of pure stimulus or stimulus and response selection conflict. Functional results indicated that dMFC activity was present during trials requiring response selection and inhibition of competing motor responses, but absent during trials involving pure stimulus conflict. A comparison of the different statistical models suggested that relatively few error trials contributed to a disproportionate amount of variance (i.e., activity) throughout the dMFC, but particularly within the rostral anterior cingulate gyrus (rACC). Finally, functional connectivity analyses indicated that an empirically derived seed in the dorsal ACC/pre-SMA exhibited strong connectivity (i.e., positive correlation) with prefrontal and inferior parietal cortex but was anti-correlated with the default-mode network. An empirically derived seed from the rACC exhibited the opposite pattern, suggesting that sub-regions of the dMFC exhibit different connectivity patterns with other large scale networks implicated in internal mentations such as daydreaming (default-mode) versus the execution of top-down attentional control (fronto-parietal). Copyright © 2011 Wiley Periodicals, Inc.

Peak fitting and integration uncertainties for the Aerodyne Aerosol Mass Spectrometer

NASA Astrophysics Data System (ADS)

Corbin, J. C.; Othman, A.; Haskins, J. D.; Allan, J. D.; Sierau, B.; Worsnop, D. R.; Lohmann, U.; Mensah, A. A.

2015-04-01

The errors inherent in the fitting and integration of the pseudo-Gaussian ion peaks in Aerodyne High-Resolution Aerosol Mass Spectrometers (HR-AMS's) have not been previously addressed as a source of imprecision for these instruments. This manuscript evaluates the significance of these uncertainties and proposes a method for their estimation in routine data analysis. Peak-fitting uncertainties, the most complex source of integration uncertainties, are found to be dominated by errors in m/z calibration. These calibration errors comprise significant amounts of both imprecision and bias, and vary in magnitude from ion to ion. The magnitude of these m/z calibration errors is estimated for an exemplary data set, and used to construct a Monte Carlo model which reproduced well the observed trends in fits to the real data. The empirically-constrained model is used to show that the imprecision in the fitted height of isolated peaks scales linearly with the peak height (i.e., as n1), thus contributing a constant-relative-imprecision term to the overall uncertainty. This constant relative imprecision term dominates the Poisson counting imprecision term (which scales as n0.5) at high signals. The previous HR-AMS uncertainty model therefore underestimates the overall fitting imprecision. The constant relative imprecision in fitted peak height for isolated peaks in the exemplary data set was estimated as ~4% and the overall peak-integration imprecision was approximately 5%. We illustrate the importance of this constant relative imprecision term by performing Positive Matrix Factorization (PMF) on a~synthetic HR-AMS data set with and without its inclusion. Finally, the ability of an empirically-constrained Monte Carlo approach to estimate the fitting imprecision for an arbitrary number of known overlapping peaks is demonstrated. Software is available upon request to estimate these error terms in new data sets.

Matching on the Disease Risk Score in Comparative Effectiveness Research of New Treatments

PubMed Central

Wyss, Richard; Ellis, Alan R.; Brookhart, M. Alan; Funk, Michele Jonsson; Girman, Cynthia J.; Simpson, Ross J.; Stürmer, Til

2016-01-01

Purpose We use simulations and an empirical example to evaluate the performance of disease risk score (DRS) matching compared with propensity score (PS) matching when controlling large numbers of covariates in settings involving newly introduced treatments. Methods We simulated a dichotomous treatment, a dichotomous outcome, and 100 baseline covariates that included both continuous and dichotomous random variables. For the empirical example, we evaluated the comparative effectiveness of dabigatran versus warfarin in preventing combined ischemic stroke and all-cause mortality. We matched treatment groups on a historically estimated DRS and again on the PS. We controlled for a high-dimensional set of covariates using 20% and 1% samples of Medicare claims data from October 2010 through December 2012. Results In simulations, matching on the DRS versus the PS generally yielded matches for more treated individuals and improved precision of the effect estimate. For the empirical example, PS and DRS matching in the 20% sample resulted in similar hazard ratios (0.88 and 0.87) and standard errors (0.04 for both methods). In the 1% sample, PS matching resulted in matches for only 92.0% of the treated population and a hazard ratio and standard error of 0.89 and 0.19, respectively, while DRS matching resulted in matches for 98.5% and a hazard ratio and standard error of 0.85 and 0.16, respectively. Conclusions When PS distributions are separated, DRS matching can improve the precision of effect estimates and allow researchers to evaluate the treatment effect in a larger proportion of the treated population. However, accurately modeling the DRS can be challenging compared with the PS. PMID:26112690

Matching on the disease risk score in comparative effectiveness research of new treatments.

PubMed

Wyss, Richard; Ellis, Alan R; Brookhart, M Alan; Jonsson Funk, Michele; Girman, Cynthia J; Simpson, Ross J; Stürmer, Til

2015-09-01

We use simulations and an empirical example to evaluate the performance of disease risk score (DRS) matching compared with propensity score (PS) matching when controlling large numbers of covariates in settings involving newly introduced treatments. We simulated a dichotomous treatment, a dichotomous outcome, and 100 baseline covariates that included both continuous and dichotomous random variables. For the empirical example, we evaluated the comparative effectiveness of dabigatran versus warfarin in preventing combined ischemic stroke and all-cause mortality. We matched treatment groups on a historically estimated DRS and again on the PS. We controlled for a high-dimensional set of covariates using 20% and 1% samples of Medicare claims data from October 2010 through December 2012. In simulations, matching on the DRS versus the PS generally yielded matches for more treated individuals and improved precision of the effect estimate. For the empirical example, PS and DRS matching in the 20% sample resulted in similar hazard ratios (0.88 and 0.87) and standard errors (0.04 for both methods). In the 1% sample, PS matching resulted in matches for only 92.0% of the treated population and a hazard ratio and standard error of 0.89 and 0.19, respectively, while DRS matching resulted in matches for 98.5% and a hazard ratio and standard error of 0.85 and 0.16, respectively. When PS distributions are separated, DRS matching can improve the precision of effect estimates and allow researchers to evaluate the treatment effect in a larger proportion of the treated population. However, accurately modeling the DRS can be challenging compared with the PS. Copyright © 2015 John Wiley & Sons, Ltd.

Automated error correction in IBM quantum computer and explicit generalization

NASA Astrophysics Data System (ADS)

Ghosh, Debjit; Agarwal, Pratik; Pandey, Pratyush; Behera, Bikash K.; Panigrahi, Prasanta K.

2018-06-01

Construction of a fault-tolerant quantum computer remains a challenging problem due to unavoidable noise and fragile quantum states. However, this goal can be achieved by introducing quantum error-correcting codes. Here, we experimentally realize an automated error correction code and demonstrate the nondestructive discrimination of GHZ states in IBM 5-qubit quantum computer. After performing quantum state tomography, we obtain the experimental results with a high fidelity. Finally, we generalize the investigated code for maximally entangled n-qudit case, which could both detect and automatically correct any arbitrary phase-change error, or any phase-flip error, or any bit-flip error, or combined error of all types of error.

Transfer Alignment Error Compensator Design Based on Robust State Estimation

NASA Astrophysics Data System (ADS)

Lyou, Joon; Lim, You-Chol

This paper examines the transfer alignment problem of the StrapDown Inertial Navigation System (SDINS), which is subject to the ship’s roll and pitch. Major error sources for velocity and attitude matching are lever arm effect, measurement time delay and ship-body flexure. To reduce these alignment errors, an error compensation method based on state augmentation and robust state estimation is devised. A linearized error model for the velocity and attitude matching transfer alignment system is derived first by linearizing the nonlinear measurement equation with respect to its time delay and dominant Y-axis flexure, and by augmenting the delay state and flexure state into conventional linear state equations. Then an H∞ filter is introduced to account for modeling uncertainties of time delay and the ship-body flexure. The simulation results show that this method considerably decreases azimuth alignment errors considerably.

On the error probability of general tree and trellis codes with applications to sequential decoding

NASA Technical Reports Server (NTRS)

Johannesson, R.

1973-01-01

An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random binary tree codes is derived and shown to be independent of the length of the tree. An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random L-branch binary trellis codes of rate R = 1/n is derived which separates the effects of the tail length T and the memory length M of the code. It is shown that the bound is independent of the length L of the information sequence. This implication is investigated by computer simulations of sequential decoding utilizing the stack algorithm. These simulations confirm the implication and further suggest an empirical formula for the true undetected decoding error probability with sequential decoding.

Instrument Reflections and Scene Amplitude Modulation in a Polychromatic Microwave Quadrature Interferometer

NASA Technical Reports Server (NTRS)

Dobson, Chris C.; Jones, Jonathan E.; Chavers, Greg

2003-01-01

A polychromatic microwave quadrature interferometer has been characterized using several laboratory plasmas. Reflections between the transmitter and the receiver have been observed, and the effects of including reflection terms in the data reduction equation have been examined. An error analysis which includes the reflections, modulation of the scene beam amplitude by the plasma, and simultaneous measurements at two frequencies has been applied to the empirical database, and the results are summarized. For reflection amplitudes around 1096, the reflection terms were found to reduce the calculated error bars for electron density measurements by about a factor of 2. The impact of amplitude modulation is also quantified. In the complete analysis, the mean error bar for high- density measurements is 7.596, and the mean phase shift error for low-density measurements is 1.2". .

A cognitive taxonomy of medical errors.

PubMed

Zhang, Jiajie; Patel, Vimla L; Johnson, Todd R; Shortliffe, Edward H

2004-06-01

Propose a cognitive taxonomy of medical errors at the level of individuals and their interactions with technology. Use cognitive theories of human error and human action to develop the theoretical foundations of the taxonomy, develop the structure of the taxonomy, populate the taxonomy with examples of medical error cases, identify cognitive mechanisms for each category of medical error under the taxonomy, and apply the taxonomy to practical problems. Four criteria were used to evaluate the cognitive taxonomy. The taxonomy should be able (1) to categorize major types of errors at the individual level along cognitive dimensions, (2) to associate each type of error with a specific underlying cognitive mechanism, (3) to describe how and explain why a specific error occurs, and (4) to generate intervention strategies for each type of error. The proposed cognitive taxonomy largely satisfies the four criteria at a theoretical and conceptual level. Theoretically, the proposed cognitive taxonomy provides a method to systematically categorize medical errors at the individual level along cognitive dimensions, leads to a better understanding of the underlying cognitive mechanisms of medical errors, and provides a framework that can guide future studies on medical errors. Practically, it provides guidelines for the development of cognitive interventions to decrease medical errors and foundation for the development of medical error reporting system that not only categorizes errors but also identifies problems and helps to generate solutions. To validate this model empirically, we will next be performing systematic experimental studies.

Simulator for beam-based LHC collimator alignment

NASA Astrophysics Data System (ADS)

Valentino, Gianluca; Aßmann, Ralph; Redaelli, Stefano; Sammut, Nicholas

2014-02-01

In the CERN Large Hadron Collider, collimators need to be set up to form a multistage hierarchy to ensure efficient multiturn cleaning of halo particles. Automatic algorithms were introduced during the first run to reduce the beam time required for beam-based setup, improve the alignment accuracy, and reduce the risk of human errors. Simulating the alignment procedure would allow for off-line tests of alignment policies and algorithms. A simulator was developed based on a diffusion beam model to generate the characteristic beam loss signal spike and decay produced when a collimator jaw touches the beam, which is observed in a beam loss monitor (BLM). Empirical models derived from the available measurement data are used to simulate the steady-state beam loss and crosstalk between multiple BLMs. The simulator design is presented, together with simulation results and comparison to measurement data.

Forensic Entomology: Evaluating Uncertainty Associated With Postmortem Interval (PMI) Estimates With Ecological Models.

PubMed

Faris, A M; Wang, H-H; Tarone, A M; Grant, W E

2016-05-31

Estimates of insect age can be informative in death investigations and, when certain assumptions are met, can be useful for estimating the postmortem interval (PMI). Currently, the accuracy and precision of PMI estimates is unknown, as error can arise from sources of variation such as measurement error, environmental variation, or genetic variation. Ecological models are an abstract, mathematical representation of an ecological system that can make predictions about the dynamics of the real system. To quantify the variation associated with the pre-appearance interval (PAI), we developed an ecological model that simulates the colonization of vertebrate remains by Cochliomyia macellaria (Fabricius) (Diptera: Calliphoridae), a primary colonizer in the southern United States. The model is based on a development data set derived from a local population and represents the uncertainty in local temperature variability to address PMI estimates at local sites. After a PMI estimate is calculated for each individual, the model calculates the maximum, minimum, and mean PMI, as well as the range and standard deviation for stadia collected. The model framework presented here is one manner by which errors in PMI estimates can be addressed in court when no empirical data are available for the parameter of interest. We show that PAI is a potential important source of error and that an ecological model is one way to evaluate its impact. Such models can be re-parameterized with any development data set, PAI function, temperature regime, assumption of interest, etc., to estimate PMI and quantify uncertainty that arises from specific prediction systems. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Analyzing human errors in flight mission operations

NASA Technical Reports Server (NTRS)

Bruno, Kristin J.; Welz, Linda L.; Barnes, G. Michael; Sherif, Josef

1993-01-01

A long-term program is in progress at JPL to reduce cost and risk of flight mission operations through a defect prevention/error management program. The main thrust of this program is to create an environment in which the performance of the total system, both the human operator and the computer system, is optimized. To this end, 1580 Incident Surprise Anomaly reports (ISA's) from 1977-1991 were analyzed from the Voyager and Magellan projects. A Pareto analysis revealed that 38 percent of the errors were classified as human errors. A preliminary cluster analysis based on the Magellan human errors (204 ISA's) is presented here. The resulting clusters described the underlying relationships among the ISA's. Initial models of human error in flight mission operations are presented. Next, the Voyager ISA's will be scored and included in the analysis. Eventually, these relationships will be used to derive a theoretically motivated and empirically validated model of human error in flight mission operations. Ultimately, this analysis will be used to make continuous process improvements continuous process improvements to end-user applications and training requirements. This Total Quality Management approach will enable the management and prevention of errors in the future.

Incorporating measurement error in n = 1 psychological autoregressive modeling

PubMed Central

Schuurman, Noémi K.; Houtveen, Jan H.; Hamaker, Ellen L.

2015-01-01

Measurement error is omnipresent in psychological data. However, the vast majority of applications of autoregressive time series analyses in psychology do not take measurement error into account. Disregarding measurement error when it is present in the data results in a bias of the autoregressive parameters. We discuss two models that take measurement error into account: An autoregressive model with a white noise term (AR+WN), and an autoregressive moving average (ARMA) model. In a simulation study we compare the parameter recovery performance of these models, and compare this performance for both a Bayesian and frequentist approach. We find that overall, the AR+WN model performs better. Furthermore, we find that for realistic (i.e., small) sample sizes, psychological research would benefit from a Bayesian approach in fitting these models. Finally, we illustrate the effect of disregarding measurement error in an AR(1) model by means of an empirical application on mood data in women. We find that, depending on the person, approximately 30–50% of the total variance was due to measurement error, and that disregarding this measurement error results in a substantial underestimation of the autoregressive parameters. PMID:26283988

Modeling, simulation, and estimation of optical turbulence

NASA Astrophysics Data System (ADS)

Formwalt, Byron Paul

This dissertation documents three new contributions to simulation and modeling of optical turbulence. The first contribution is the formalization, optimization, and validation of a modeling technique called successively conditioned rendering (SCR). The SCR technique is empirically validated by comparing the statistical error of random phase screens generated with the technique. The second contribution is the derivation of the covariance delineation theorem, which provides theoretical bounds on the error associated with SCR. It is shown empirically that the theoretical bound may be used to predict relative algorithm performance. Therefore, the covariance delineation theorem is a powerful tool for optimizing SCR algorithms. For the third contribution, we introduce a new method for passively estimating optical turbulence parameters, and demonstrate the method using experimental data. The technique was demonstrated experimentally, using a 100 m horizontal path at 1.25 m above sun-heated tarmac on a clear afternoon. For this experiment, we estimated C2n ≈ 6.01 · 10-9 m-23 , l0 ≈ 17.9 mm, and L0 ≈ 15.5 m.

Empirical calibration of the near-infrared Ca ii triplet - I. The stellar library and index definition

NASA Astrophysics Data System (ADS)

Cenarro, A. J.; Cardiel, N.; Gorgas, J.; Peletier, R. F.; Vazdekis, A.; Prada, F.

2001-09-01

A new stellar library at the near-IR spectral region developed for the empirical calibration of the Caii triplet and stellar population synthesis modelling is presented. The library covers the range λλ8348-9020 at 1.5-Å (FWHM) spectral resolution, and consists of 706 stars spanning a wide range in atmospheric parameters. We have defined a new set of near-IR indices, CaT*, CaT and PaT, which mostly overcome the limitations of previous definitions, the former being specially suited for the measurement of the Caii triplet strength corrected for the contamination from Paschen lines. We also present a comparative study of the new and the previous Ca indices, as well as the corresponding transformations between the different systems. A thorough analysis of the sources of index errors and the procedure to calculate them is given. Finally, index and error measurements for the whole stellar library are provided together with the final spectra.

Kalman Filter for Spinning Spacecraft Attitude Estimation

NASA Technical Reports Server (NTRS)

Markley, F. Landis; Sedlak, Joseph E.

2008-01-01

This paper presents a Kalman filter using a seven-component attitude state vector comprising the angular momentum components in an inertial reference frame, the angular momentum components in the body frame, and a rotation angle. The relatively slow variation of these parameters makes this parameterization advantageous for spinning spacecraft attitude estimation. The filter accounts for the constraint that the magnitude of the angular momentum vector is the same in the inertial and body frames by employing a reduced six-component error state. Four variants of the filter, defined by different choices for the reduced error state, are tested against a quaternion-based filter using simulated data for the THEMIS mission. Three of these variants choose three of the components of the error state to be the infinitesimal attitude error angles, facilitating the computation of measurement sensitivity matrices and causing the usual 3x3 attitude covariance matrix to be a submatrix of the 6x6 covariance of the error state. These variants differ in their choice for the other three components of the error state. The variant employing the infinitesimal attitude error angles and the angular momentum components in an inertial reference frame as the error state shows the best combination of robustness and efficiency in the simulations. Attitude estimation results using THEMIS flight data are also presented.

Modified empirical Solar Radiation Pressure model for IRNSS constellation

NASA Astrophysics Data System (ADS)

Rajaiah, K.; Manamohan, K.; Nirmala, S.; Ratnakara, S. C.

2017-11-01

Navigation with Indian Constellation (NAVIC) also known as Indian Regional Navigation Satellite System (IRNSS) is India's regional navigation system designed to provide position accuracy better than 20 m over India and the region extending to 1500 km around India. The reduced dynamic precise orbit estimation is utilized to determine the orbit broadcast parameters for IRNSS constellation. The estimation is mainly affected by the parameterization of dynamic models especially Solar Radiation Pressure (SRP) model which is a non-gravitational force depending on shape and attitude dynamics of the spacecraft. An empirical nine parameter solar radiation pressure model is developed for IRNSS constellation, using two-way range measurements from IRNSS C-band ranging system. The paper addresses the development of modified SRP empirical model for IRNSS (IRNSS SRP Empirical Model, ISEM). The performance of the ISEM was assessed based on overlap consistency, long term prediction, Satellite Laser Ranging (SLR) residuals and compared with ECOM9, ECOM5 and new-ECOM9 models developed by Center for Orbit Determination in Europe (CODE). For IRNSS Geostationary Earth Orbit (GEO) and Inclined Geosynchronous Orbit (IGSO) satellites, ISEM has shown promising results with overlap RMS error better than 5.3 m and 3.5 m respectively. Long term orbit prediction using numerical integration has improved with error better than 80%, 26% and 7.8% in comparison to ECOM9, ECOM5 and new-ECOM9 respectively. Further, SLR based orbit determination with ISEM shows 70%, 47% and 39% improvement over 10 days orbit prediction in comparison to ECOM9, ECOM5 and new-ECOM9 respectively and also highlights the importance of wide baseline tracking network.

On the use of the covariance matrix to fit correlated data

NASA Astrophysics Data System (ADS)

D'Agostini, G.

1994-07-01

Best fits to data which are affected by systematic uncertainties on the normalization factor have the tendency to produce curves lower than expected if the covariance matrix of the data points is used in the definition of the χ2. This paper shows that the effect is a direct consequence of the hypothesis used to estimate the empirical covariance matrix, namely the linearization on which the usual error propagation relies. The bias can become unacceptable if the normalization error is large, or a large number of data points are fitted.

ON NONSTATIONARY STOCHASTIC MODELS FOR EARTHQUAKES.

USGS Publications Warehouse

Safak, Erdal; Boore, David M.

1986-01-01

A seismological stochastic model for earthquake ground-motion description is presented. Seismological models are based on the physical properties of the source and the medium and have significant advantages over the widely used empirical models. The model discussed here provides a convenient form for estimating structural response by using random vibration theory. A commonly used random process for ground acceleration, filtered white-noise multiplied by an envelope function, introduces some errors in response calculations for structures whose periods are longer than the faulting duration. An alternate random process, filtered shot-noise process, eliminates these errors.

A Bayesian approach to parameter and reliability estimation in the Poisson distribution.

NASA Technical Reports Server (NTRS)

Canavos, G. C.

1972-01-01

For life testing procedures, a Bayesian analysis is developed with respect to a random intensity parameter in the Poisson distribution. Bayes estimators are derived for the Poisson parameter and the reliability function based on uniform and gamma prior distributions of that parameter. A Monte Carlo procedure is implemented to make possible an empirical mean-squared error comparison between Bayes and existing minimum variance unbiased, as well as maximum likelihood, estimators. As expected, the Bayes estimators have mean-squared errors that are appreciably smaller than those of the other two.

Threshold detection in an on-off binary communications channel with atmospheric scintillation

NASA Technical Reports Server (NTRS)

Webb, W. E.

1975-01-01

The optimum detection threshold in an on-off binary optical communications system operating in the presence of atmospheric turbulence was investigated assuming a poisson detection process and log normal scintillation. The dependence of the probability of bit error on log amplitude variance and received signal strength was analyzed and semi-empirical relationships to predict the optimum detection threshold derived. On the basis of this analysis a piecewise linear model for an adaptive threshold detection system is presented. The bit error probabilities for nonoptimum threshold detection systems were also investigated.

Impact of round-the-clock CSF Gram stain on empirical therapy for suspected central nervous system infections.

PubMed

Tissot, F; Prod'hom, G; Manuel, O; Greub, G

2015-09-01

The impact of round-the-clock cerebrospinal fluid (CSF) Gram stain on overnight empirical therapy for suspected central nervous system (CNS) infections was investigated. All consecutive overnight CSF Gram stains between 2006 and 2011 were included. The impact of a positive or a negative test on empirical therapy was evaluated and compared to other clinical and biological indications based on institutional guidelines. Bacterial CNS infection was documented in 51/241 suspected cases. Overnight CSF Gram stain was positive in 24/51. Upon validation, there were two false-positive and one false-negative results. The sensitivity and specificity were 41 and 99 %, respectively. All patients but one had other indications for empirical therapy than Gram stain alone. Upon obtaining the Gram result, empirical therapy was modified in 7/24, including the addition of an appropriate agent (1), addition of unnecessary agents (3) and simplification of unnecessary combination therapy (3/11). Among 74 cases with a negative CSF Gram stain and without formal indication for empirical therapy, antibiotics were withheld in only 29. Round-the-clock CSF Gram stain had a low impact on overnight empirical therapy for suspected CNS infections and was associated with several misinterpretation errors. Clinicians showed little confidence in CSF direct examination for simplifying or withholding therapy before definite microbiological results.

The Evolution of a More Rigorous Approach to Benefit Transfer: Benefit Function Transfer

NASA Astrophysics Data System (ADS)

Loomis, John B.

1992-03-01

The desire for economic values of recreation for unstudied recreation resources dates back to the water resource development benefit-cost analyses of the early 1960s. Rather than simply applying existing estimates of benefits per trip to the study site, a fairly rigorous approach was developed by a number of economists. This approach involves application of travel cost demand equations and contingent valuation benefit functions from existing sites to the new site. In this way the spatial market of the new site (i.e., its differing own price, substitute prices and population distribution) is accounted for in the new estimate of total recreation benefits. The assumptions of benefit transfer from recreation sites in one state to another state for the same recreation activity is empirically tested. The equality of demand coefficients for ocean sport salmon fishing in Oregon versus Washington and for freshwater steelhead fishing in Oregon versus Idaho is rejected. Thus transfer of either demand equations or average benefits per trip are likely to be in error. Using the Oregon steelhead equation, benefit transfers to rivers within the state are shown to be accurate to within 5-15%.

A Multicenter Evaluation of Prolonged Empiric Antibiotic Therapy in Adult ICUs in the United States.

PubMed

Thomas, Zachariah; Bandali, Farooq; Sankaranarayanan, Jayashri; Reardon, Tom; Olsen, Keith M

2015-12-01

The purpose of this study is to determine the rate of prolonged empiric antibiotic therapy in adult ICUs in the United States. Our secondary objective is to examine the relationship between the prolonged empiric antibiotic therapy rate and certain ICU characteristics. Multicenter, prospective, observational, 72-hour snapshot study. Sixty-seven ICUs from 32 hospitals in the United States. Nine hundred ninety-eight patients admitted to the ICU between midnight on June 20, 2011, and June 21, 2011, were included in the study. None. Antibiotic orders were categorized as prophylactic, definitive, empiric, or prolonged empiric antibiotic therapy. Prolonged empiric antibiotic therapy was defined as empiric antibiotics that continued for at least 72 hours in the absence of adjudicated infection. Standard definitions from the Centers for Disease Control and Prevention were used to determine infection. Prolonged empiric antibiotic therapy rate was determined as the ratio of the total number of empiric antibiotics continued for at least 72 hours divided by the total number of empiric antibiotics. Univariate analysis of factors associated with the ICU prolonged empiric antibiotic therapy rate was conducted using Student t test. A total of 660 unique antibiotics were prescribed as empiric therapy to 364 patients. Of the empiric antibiotics, 333 of 660 (50%) were continued for at least 72 hours in instances where Centers for Disease Control and Prevention infection criteria were not met. Suspected pneumonia accounted for approximately 60% of empiric antibiotic use. The most frequently prescribed empiric antibiotics were vancomycin and piperacillin/tazobactam. ICUs that utilized invasive techniques for the diagnosis of ventilator-associated pneumonia had lower rates of prolonged empiric antibiotic therapy than those that did not, 45.1% versus 59.5% (p = 0.03). No other institutional factor was significantly associated with prolonged empiric antibiotic therapy rate. Half of all empiric antibiotics ordered in critically ill patients are continued for at least 72 hours in absence of adjudicated infection. Additional studies are needed to confirm these findings and determine the risks and benefits of prolonged empiric therapy in the critically ill.

An Empirical Examination of Weiner's Critique of Attribution Research.

ERIC Educational Resources Information Center

Covington, Martin V.; Omelich, Carol L.

1984-01-01

Weiner's allegations of errors in testing his theory (presumed detrimental effects of investigating a restricted range of variables, use of expectancy changes as a mediating variable, and presumed inappropriateness of classroom performance as a dependent variable) are evaluated. Disconfirmation of Weiner's predictions occurs irrespective of…

Ability Self-Estimates and Self-Efficacy: Meaningfully Distinct?

ERIC Educational Resources Information Center

Bubany, Shawn T.; Hansen, Jo-Ida C.

2010-01-01

Conceptual differences between self-efficacy and ability self-estimate scores, used in vocational psychology and career counseling, were examined with confirmatory factor analysis, discriminate relations, and reliability analysis. Results suggest that empirical differences may be due to measurement error or scale content, rather than due to the…

Bio-Optical Data Assimilation With Observational Error Covariance Derived From an Ensemble of Satellite Images

NASA Astrophysics Data System (ADS)

Shulman, Igor; Gould, Richard W.; Frolov, Sergey; McCarthy, Sean; Penta, Brad; Anderson, Stephanie; Sakalaukus, Peter

2018-03-01

An ensemble-based approach to specify observational error covariance in the data assimilation of satellite bio-optical properties is proposed. The observational error covariance is derived from statistical properties of the generated ensemble of satellite MODIS-Aqua chlorophyll (Chl) images. The proposed observational error covariance is used in the Optimal Interpolation scheme for the assimilation of MODIS-Aqua Chl observations. The forecast error covariance is specified in the subspace of the multivariate (bio-optical, physical) empirical orthogonal functions (EOFs) estimated from a month-long model run. The assimilation of surface MODIS-Aqua Chl improved surface and subsurface model Chl predictions. Comparisons with surface and subsurface water samples demonstrate that data assimilation run with the proposed observational error covariance has higher RMSE than the data assimilation run with "optimistic" assumption about observational errors (10% of the ensemble mean), but has smaller or comparable RMSE than data assimilation run with an assumption that observational errors equal to 35% of the ensemble mean (the target error for satellite data product for chlorophyll). Also, with the assimilation of the MODIS-Aqua Chl data, the RMSE between observed and model-predicted fractions of diatoms to the total phytoplankton is reduced by a factor of two in comparison to the nonassimilative run.

A method of bias correction for maximal reliability with dichotomous measures.

PubMed

Penev, Spiridon; Raykov, Tenko

2010-02-01

This paper is concerned with the reliability of weighted combinations of a given set of dichotomous measures. Maximal reliability for such measures has been discussed in the past, but the pertinent estimator exhibits a considerable bias and mean squared error for moderate sample sizes. We examine this bias, propose a procedure for bias correction, and develop a more accurate asymptotic confidence interval for the resulting estimator. In most empirically relevant cases, the bias correction and mean squared error correction can be performed simultaneously. We propose an approximate (asymptotic) confidence interval for the maximal reliability coefficient, discuss the implementation of this estimator, and investigate the mean squared error of the associated asymptotic approximation. We illustrate the proposed methods using a numerical example.

Determination of suitable drying curve model for bread moisture loss during baking

NASA Astrophysics Data System (ADS)

Soleimani Pour-Damanab, A. R.; Jafary, A.; Rafiee, S.

2013-03-01

This study presents mathematical modelling of bread moisture loss or drying during baking in a conventional bread baking process. In order to estimate and select the appropriate moisture loss curve equation, 11 different models, semi-theoretical and empirical, were applied to the experimental data and compared according to their correlation coefficients, chi-squared test and root mean square error which were predicted by nonlinear regression analysis. Consequently, of all the drying models, a Page model was selected as the best one, according to the correlation coefficients, chi-squared test, and root mean square error values and its simplicity. Mean absolute estimation error of the proposed model by linear regression analysis for natural and forced convection modes was 2.43, 4.74%, respectively.

An empirical comparison of a dynamic software testability metric to static cyclomatic complexity

NASA Technical Reports Server (NTRS)

Voas, Jeffrey M.; Miller, Keith W.; Payne, Jeffrey E.

1993-01-01

This paper compares the dynamic testability prediction technique termed 'sensitivity analysis' to the static testability technique termed cyclomatic complexity. The application that we chose in this empirical study is a CASE generated version of a B-737 autoland system. For the B-737 system we analyzed, we isolated those functions that we predict are more prone to hide errors during system/reliability testing. We also analyzed the code with several other well-known static metrics. This paper compares and contrasts the results of sensitivity analysis to the results of the static metrics.

Comparison of ensemble post-processing approaches, based on empirical and dynamical error modelisation of rainfall-runoff model forecasts

NASA Astrophysics Data System (ADS)

Chardon, J.; Mathevet, T.; Le Lay, M.; Gailhard, J.

2012-04-01

In the context of a national energy company (EDF : Electricité de France), hydro-meteorological forecasts are necessary to ensure safety and security of installations, meet environmental standards and improve water ressources management and decision making. Hydrological ensemble forecasts allow a better representation of meteorological and hydrological forecasts uncertainties and improve human expertise of hydrological forecasts, which is essential to synthesize available informations, coming from different meteorological and hydrological models and human experience. An operational hydrological ensemble forecasting chain has been developed at EDF since 2008 and is being used since 2010 on more than 30 watersheds in France. This ensemble forecasting chain is characterized ensemble pre-processing (rainfall and temperature) and post-processing (streamflow), where a large human expertise is solicited. The aim of this paper is to compare 2 hydrological ensemble post-processing methods developed at EDF in order improve ensemble forecasts reliability (similar to Monatanari &Brath, 2004; Schaefli et al., 2007). The aim of the post-processing methods is to dress hydrological ensemble forecasts with hydrological model uncertainties, based on perfect forecasts. The first method (called empirical approach) is based on a statistical modelisation of empirical error of perfect forecasts, by streamflow sub-samples of quantile class and lead-time. The second method (called dynamical approach) is based on streamflow sub-samples of quantile class and streamflow variation, and lead-time. On a set of 20 watersheds used for operational forecasts, results show that both approaches are necessary to ensure a good post-processing of hydrological ensemble, allowing a good improvement of reliability, skill and sharpness of ensemble forecasts. The comparison of the empirical and dynamical approaches shows the limits of the empirical approach which is not able to take into account hydrological dynamic and processes, i. e. sample heterogeneity. For a same streamflow range corresponds different processes such as rising limbs or recession, where uncertainties are different. The dynamical approach improves reliability, skills and sharpness of forecasts and globally reduces confidence intervals width. When compared in details, the dynamical approach allows a noticeable reduction of confidence intervals during recessions where uncertainty is relatively lower and a slight increase of confidence intervals during rising limbs or snowmelt where uncertainty is greater. The dynamic approach, validated by forecaster's experience that considered the empirical approach not discriminative enough, improved forecaster's confidence and communication of uncertainties. Montanari, A. and Brath, A., (2004). A stochastic approach for assessing the uncertainty of rainfall-runoff simulations. Water Resources Research, 40, W01106, doi:10.1029/2003WR002540. Schaefli, B., Balin Talamba, D. and Musy, A., (2007). Quantifying hydrological modeling errors through a mixture of normal distributions. Journal of Hydrology, 332, 303-315.

On the Error State Selection for Stationary SINS Alignment and Calibration Kalman Filters—Part II: Observability/Estimability Analysis

PubMed Central

Silva, Felipe O.; Hemerly, Elder M.; Leite Filho, Waldemar C.

2017-01-01

This paper presents the second part of a study aiming at the error state selection in Kalman filters applied to the stationary self-alignment and calibration (SSAC) problem of strapdown inertial navigation systems (SINS). The observability properties of the system are systematically investigated, and the number of unobservable modes is established. Through the analytical manipulation of the full SINS error model, the unobservable modes of the system are determined, and the SSAC error states (except the velocity errors) are proven to be individually unobservable. The estimability of the system is determined through the examination of the major diagonal terms of the covariance matrix and their eigenvalues/eigenvectors. Filter order reduction based on observability analysis is shown to be inadequate, and several misconceptions regarding SSAC observability and estimability deficiencies are removed. As the main contributions of this paper, we demonstrate that, except for the position errors, all error states can be minimally estimated in the SSAC problem and, hence, should not be removed from the filter. Corroborating the conclusions of the first part of this study, a 12-state Kalman filter is found to be the optimal error state selection for SSAC purposes. Results from simulated and experimental tests support the outlined conclusions. PMID:28241494

Therapeutic self-disclosure in integrative psychotherapy: When is this a clinical error?

PubMed

Ziv-Beiman, Sharon; Shahar, Golan

2016-09-01

Ascending to prominence in virtually all forms of psychotherapy, therapist self-disclosure (TSD) has recently been identified as a primarily integrative intervention (Ziv-Beiman, 2013). In the present article, we discuss various instances in which using TSD in integrative psychotherapy might constitute a clinical error. First, we briefly review extant theory and empirical research on TSD, followed by our preferred version of integrative psychotherapy (i.e., a version of Wachtel's Cyclical Psychodynamics [Wachtel, 1977, 1997, 2014]), which we title cognitive existential psychodynamics. Next, we provide and discuss three examples in which implementing TSD constitutes a clinical error. In essence, we submit that using TSD constitutes an error when patients, constrained by their representational structures (object relations), experience the subjectivity of the other as impinging, and thus propels them to "react" instead of "emerge." (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The Clinical Assessment in the Legal Field: An Empirical Study of Bias and Limitations in Forensic Expertise

PubMed Central

Iudici, Antonio; Salvini, Alessandro; Faccio, Elena; Castelnuovo, Gianluca

2015-01-01

According to the literature, psychological assessment in forensic contexts is one of the most controversial application areas for clinical psychology. This paper presents a review of systematic judgment errors in the forensic field. Forty-six psychological reports written by psychologists, court consultants, have been analyzed with content analysis to identify typical judgment errors related to the following areas: (a) distortions in the attribution of causality, (b) inferential errors, and (c) epistemological inconsistencies. Results indicated that systematic errors of judgment, usually referred also as “the man in the street,” are widely present in the forensic evaluations of specialist consultants. Clinical and practical implications are taken into account. This article could lead to significant benefits for clinical psychologists who want to deal with this sensitive issue and are interested in improving the quality of their contribution to the justice system. PMID:26648892

Analytic score distributions for a spatially continuous tridirectional Monte Carol transport problem

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

Booth, T.E.

1996-01-01

The interpretation of the statistical error estimates produced by Monte Carlo transport codes is still somewhat of an art. Empirically, there are variance reduction techniques whose error estimates are almost always reliable, and there are variance reduction techniques whose error estimates are often unreliable. Unreliable error estimates usually result from inadequate large-score sampling from the score distribution`s tail. Statisticians believe that more accurate confidence interval statements are possible if the general nature of the score distribution can be characterized. Here, the analytic score distribution for the exponential transform applied to a simple, spatially continuous Monte Carlo transport problem is provided.more » Anisotropic scattering and implicit capture are included in the theory. In large part, the analytic score distributions that are derived provide the basis for the ten new statistical quality checks in MCNP.« less

#2 - An Empirical Assessment of Exposure Measurement Error ...

EPA Pesticide Factsheets

Background• Differing degrees of exposure error acrosspollutants• Previous focus on quantifying and accounting forexposure error in single-pollutant models• Examine exposure errors for multiple pollutantsand provide insights on the potential for bias andattenuation of effect estimates in single and bipollutantepidemiological models The National Exposure Research Laboratory (NERL) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA mission to protect human health and the environment. HEASD research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose. The impact of these tools is improved regulatory programs and policies for EPA.

A misleading review of response bias: comment on McGrath, Mitchell, Kim, and Hough (2010).

PubMed

Rohling, Martin L; Larrabee, Glenn J; Greiffenstein, Manfred F; Ben-Porath, Yossef S; Lees-Haley, Paul; Green, Paul; Greve, Kevin W

2011-07-01

In the May 2010 issue of Psychological Bulletin, R. E. McGrath, M. Mitchell, B. H. Kim, and L. Hough published an article entitled "Evidence for Response Bias as a Source of Error Variance in Applied Assessment" (pp. 450-470). They argued that response bias indicators used in a variety of settings typically have insufficient data to support such use in everyday clinical practice. Furthermore, they claimed that despite 100 years of research into the use of response bias indicators, "a sufficient justification for [their] use… in applied settings remains elusive" (p. 450). We disagree with McGrath et al.'s conclusions. In fact, we assert that the relevant and voluminous literature that has addressed the issues of response bias substantiates validity of these indicators. In addition, we believe that response bias measures should be used in clinical and research settings on a regular basis. Finally, the empirical evidence for the use of response bias measures is strongest in clinical neuropsychology. We argue that McGrath et al.'s erroneous perspective on response bias measures is a result of 3 errors in their research methodology: (a) inclusion criteria for relevant studies that are too narrow; (b) errors in interpreting results of the empirical research they did include; (c) evidence of a confirmatory bias in selectively citing the literature, as evidence of moderation appears to have been overlooked. Finally, their acknowledging experts in the field who might have highlighted these errors prior to publication may have prevented critiques during the review process.

The Elegance of Disordered Granular Packings: A Validation of Edwards' Hypothesis

NASA Technical Reports Server (NTRS)

Metzger, Philip T.; Donahue, Carly M.

2004-01-01

We have found a way to analyze Edwards' density of states for static granular packings in the special case of round, rigid, frictionless grains assuming constant coordination number. It obtains the most entropic density of single grain states, which predicts several observables including the distribution of contact forces. We compare these results against empirical data obtained in dynamic simulations of granular packings. The agreement between theory and the empirics is quite good, helping validate the use of statistical mechanics methods in granular physics. The differences between theory and empirics are mainly due to the variable coordination number, and when the empirical data are sorted by that number we obtain several insights that suggest an underlying elegance in the density of states

42 CFR 431.992 - Corrective action plan.

Code of Federal Regulations, 2010 CFR

2010-10-01

... CMS, designed to reduce improper payments in each program based on its analysis of the error causes in... State must take the following actions: (1) Data analysis. States must conduct data analysis such as reviewing clusters of errors, general error causes, characteristics, and frequency of errors that are...

42 CFR 431.992 - Corrective action plan.

Code of Federal Regulations, 2011 CFR

2011-10-01

... CMS, designed to reduce improper payments in each program based on its analysis of the error causes in... State must take the following actions: (1) Data analysis. States must conduct data analysis such as reviewing clusters of errors, general error causes, characteristics, and frequency of errors that are...

Mentoring Nontraditional Undergraduate Students: A Case Study in Higher Education

ERIC Educational Resources Information Center

Langer, Arthur M.

2010-01-01

The purpose of this study was to investigate an institution that has mandated mentoring as part of its mission and to examine students' perceptions of the mentoring received. The author selected Empire State College (ESC), a college that is part of the State of New York University system in the United States. Empire State is an institution with a…

Native Reactions to Non-Native Speech: A Review of Empirical Research.

ERIC Educational Resources Information Center

Eisenstein, Miriam

1983-01-01

Recent research on native speakers' reactions to nonnative speech that views listeners, speakers, and language from a variety of perspectives using both objective and subjective research paradigms is reviewed. Studies of error gravity, relative intelligibility of language samples, the role of accent, speakers' characteristics, and context in which…

Prediction of Breakthrough Curves for Conservative and Reactive Transport from the Structural Parameters of Highly Heterogeneous Media

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

Hansen, Scott; Haslauer, Claus P.; Cirpka, Olaf A.

2017-01-05

The key points of this presentation were to approach the problem of linking breakthrough curve shape (RP-CTRW transition distribution) to structural parameters from a Monte Carlo approach and to use the Monte Carlo analysis to determine any empirical error

Interactions of Task and Subject Variables among Continuous Performance Tests

ERIC Educational Resources Information Center

Denney, Colin B.; Rapport, Mark D.; Chung, Kyong-Mee

2005-01-01

Background: Contemporary models of working memory suggest that target paradigm (TP) and target density (TD) should interact as influences on error rates derived from continuous performance tests (CPTs). The present study evaluated this hypothesis empirically in a typically developing, ethnically diverse sample of children. The extent to which…

Quantum error-correcting code for ternary logic

NASA Astrophysics Data System (ADS)

Majumdar, Ritajit; Basu, Saikat; Ghosh, Shibashis; Sur-Kolay, Susmita

2018-05-01

Ternary quantum systems are being studied because they provide more computational state space per unit of information, known as qutrit. A qutrit has three basis states, thus a qubit may be considered as a special case of a qutrit where the coefficient of one of the basis states is zero. Hence both (2 ×2 ) -dimensional and (3 ×3 ) -dimensional Pauli errors can occur on qutrits. In this paper, we (i) explore the possible (2 ×2 ) -dimensional as well as (3 ×3 ) -dimensional Pauli errors in qutrits and show that any pairwise bit swap error can be expressed as a linear combination of shift errors and phase errors, (ii) propose a special type of error called a quantum superposition error and show its equivalence to arbitrary rotation, (iii) formulate a nine-qutrit code which can correct a single error in a qutrit, and (iv) provide its stabilizer and circuit realization.

Medical Error and Moral Luck.

PubMed

Hubbeling, Dieneke

2016-09-01

This paper addresses the concept of moral luck. Moral luck is discussed in the context of medical error, especially an error of omission that occurs frequently, but only rarely has adverse consequences. As an example, a failure to compare the label on a syringe with the drug chart results in the wrong medication being administered and the patient dies. However, this error may have previously occurred many times with no tragic consequences. Discussions on moral luck can highlight conflicting intuitions. Should perpetrators receive a harsher punishment because of an adverse outcome, or should they be dealt with in the same way as colleagues who have acted similarly, but with no adverse effects? An additional element to the discussion, specifically with medical errors, is that according to the evidence currently available, punishing individual practitioners does not seem to be effective in preventing future errors. The following discussion, using relevant philosophical and empirical evidence, posits a possible solution for the moral luck conundrum in the context of medical error: namely, making a distinction between the duty to make amends and assigning blame. Blame should be assigned on the basis of actual behavior, while the duty to make amends is dependent on the outcome.

Accounting for Non-Gaussian Sources of Spatial Correlation in Parametric Functional Magnetic Resonance Imaging Paradigms I: Revisiting Cluster-Based Inferences.

PubMed

Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Sathian, K

2018-02-01

In a recent study, Eklund et al. employed resting-state functional magnetic resonance imaging data as a surrogate for null functional magnetic resonance imaging (fMRI) datasets and posited that cluster-wise family-wise error (FWE) rate-corrected inferences made by using parametric statistical methods in fMRI studies over the past two decades may have been invalid, particularly for cluster defining thresholds less stringent than p < 0.001; this was principally because the spatial autocorrelation functions (sACF) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggested otherwise. Here, we show that accounting for non-Gaussian signal components such as those arising from resting-state neural activity as well as physiological responses and motion artifacts in the null fMRI datasets yields first- and second-level general linear model analysis residuals with nearly uniform and Gaussian sACF. Further comparison with nonparametric permutation tests indicates that cluster-based FWE corrected inferences made with Gaussian spatial noise approximations are valid.

Impact and quantification of the sources of error in DNA pooling designs.

PubMed

Jawaid, A; Sham, P

2009-01-01

The analysis of genome wide variation offers the possibility of unravelling the genes involved in the pathogenesis of disease. Genome wide association studies are also particularly useful for identifying and validating targets for therapeutic intervention as well as for detecting markers for drug efficacy and side effects. The cost of such large-scale genetic association studies may be reduced substantially by the analysis of pooled DNA from multiple individuals. However, experimental errors inherent in pooling studies lead to a potential increase in the false positive rate and a loss in power compared to individual genotyping. Here we quantify various sources of experimental error using empirical data from typical pooling experiments and corresponding individual genotyping counts using two statistical methods. We provide analytical formulas for calculating these different errors in the absence of complete information, such as replicate pool formation, and for adjusting for the errors in the statistical analysis. We demonstrate that DNA pooling has the potential of estimating allele frequencies accurately, and adjusting the pooled allele frequency estimates for differential allelic amplification considerably improves accuracy. Estimates of the components of error show that differential allelic amplification is the most important contributor to the error variance in absolute allele frequency estimation, followed by allele frequency measurement and pool formation errors. Our results emphasise the importance of minimising experimental errors and obtaining correct error estimates in genetic association studies.

Mechanistic-empirical Pavement Design Guide Implementation

DOT National Transportation Integrated Search

2010-06-01

The recently introduced Mechanistic-Empirical Pavement Design Guide (MEPDG) and associated computer software provides a state-of-practice mechanistic-empirical highway pavement design methodology. The MEPDG methodology is based on pavement responses ...

Joint estimation over multiple individuals improves behavioural state inference from animal movement data.

PubMed

Jonsen, Ian

2016-02-08

State-space models provide a powerful way to scale up inference of movement behaviours from individuals to populations when the inference is made across multiple individuals. Here, I show how a joint estimation approach that assumes individuals share identical movement parameters can lead to improved inference of behavioural states associated with different movement processes. I use simulated movement paths with known behavioural states to compare estimation error between nonhierarchical and joint estimation formulations of an otherwise identical state-space model. Behavioural state estimation error was strongly affected by the degree of similarity between movement patterns characterising the behavioural states, with less error when movements were strongly dissimilar between states. The joint estimation model improved behavioural state estimation relative to the nonhierarchical model for simulated data with heavy-tailed Argos location errors. When applied to Argos telemetry datasets from 10 Weddell seals, the nonhierarchical model estimated highly uncertain behavioural state switching probabilities for most individuals whereas the joint estimation model yielded substantially less uncertainty. The joint estimation model better resolved the behavioural state sequences across all seals. Hierarchical or joint estimation models should be the preferred choice for estimating behavioural states from animal movement data, especially when location data are error-prone.

A silver lining to higher prices at the pump? Gasoline prices and teen driving behaviors.

PubMed

Sen, Bisakha; Patidar, Nitish; Thomas, Sheikilya

2014-01-01

Existing literature shows negative relationships between gasoline price and motor vehicle crashes, particularly among teens. This paper extends that literature by evaluating the relationship between gasoline price and self-reported risky driving among teens. Observational study using multivariate empirical analysis, using pooled data from the Youth Risk Behavior Survey, waves 2003-2009. Secondary data from survey administered in private and public high schools across the United States. Students in grades 9 through 12, surveyed biennially from 2003 to 2009 (n = 58,749). Outcomes are (self-reported) driving without seatbelts, driving after consuming alcohol, and moderate physical activity (like walking or bicycling). State-level retail gasoline prices constitute the main predictor variable. Multivariate logistic models are estimated for the full sample, as well as by gender, race/ethnicity, and age. Individual characteristics, state unemployment, and state driving policies are controlled for. Standard errors are clustered at the state level. Results are reported in form of risk differences. Higher gasoline prices are negatively and significantly associated with driving without seatbelts. Associations are particularly strong for males and minorities. There are fewer statistical associations between gasoline prices and driving after drinking. Higher gasoline prices are positively associated with more moderate physical activity. Higher gasoline prices are associated with less risky driving behaviors among teens, and they may be associated with more active forms of transportation, like walking and bicycling. The study limitations are discussed.

Assessment of Current Jet Noise Prediction Capabilities

NASA Technical Reports Server (NTRS)

Hunter, Craid A.; Bridges, James E.; Khavaran, Abbas

2008-01-01

An assessment was made of the capability of jet noise prediction codes over a broad range of jet flows, with the objective of quantifying current capabilities and identifying areas requiring future research investment. Three separate codes in NASA s possession, representative of two classes of jet noise prediction codes, were evaluated, one empirical and two statistical. The empirical code is the Stone Jet Noise Module (ST2JET) contained within the ANOPP aircraft noise prediction code. It is well documented, and represents the state of the art in semi-empirical acoustic prediction codes where virtual sources are attributed to various aspects of noise generation in each jet. These sources, in combination, predict the spectral directivity of a jet plume. A total of 258 jet noise cases were examined on the ST2JET code, each run requiring only fractions of a second to complete. Two statistical jet noise prediction codes were also evaluated, JeNo v1, and Jet3D. Fewer cases were run for the statistical prediction methods because they require substantially more resources, typically a Reynolds-Averaged Navier-Stokes solution of the jet, volume integration of the source statistical models over the entire plume, and a numerical solution of the governing propagation equation within the jet. In the evaluation process, substantial justification of experimental datasets used in the evaluations was made. In the end, none of the current codes can predict jet noise within experimental uncertainty. The empirical code came within 2dB on a 1/3 octave spectral basis for a wide range of flows. The statistical code Jet3D was within experimental uncertainty at broadside angles for hot supersonic jets, but errors in peak frequency and amplitude put it out of experimental uncertainty at cooler, lower speed conditions. Jet3D did not predict changes in directivity in the downstream angles. The statistical code JeNo,v1 was within experimental uncertainty predicting noise from cold subsonic jets at all angles, but did not predict changes with heating of the jet and did not account for directivity changes at supersonic conditions. Shortcomings addressed here give direction for future work relevant to the statistical-based prediction methods. A full report will be released as a chapter in a NASA publication assessing the state of the art in aircraft noise prediction.

Combining empirical approaches and error modelling to enhance predictive uncertainty estimation in extrapolation for operational flood forecasting. Tests on flood events on the Loire basin, France.

NASA Astrophysics Data System (ADS)

Berthet, Lionel; Marty, Renaud; Bourgin, François; Viatgé, Julie; Piotte, Olivier; Perrin, Charles

2017-04-01

An increasing number of operational flood forecasting centres assess the predictive uncertainty associated with their forecasts and communicate it to the end users. This information can match the end-users needs (i.e. prove to be useful for an efficient crisis management) only if it is reliable: reliability is therefore a key quality for operational flood forecasts. In 2015, the French flood forecasting national and regional services (Vigicrues network; www.vigicrues.gouv.fr) implemented a framework to compute quantitative discharge and water level forecasts and to assess the predictive uncertainty. Among the possible technical options to achieve this goal, a statistical analysis of past forecasting errors of deterministic models has been selected (QUOIQUE method, Bourgin, 2014). It is a data-based and non-parametric approach based on as few assumptions as possible about the forecasting error mathematical structure. In particular, a very simple assumption is made regarding the predictive uncertainty distributions for large events outside the range of the calibration data: the multiplicative error distribution is assumed to be constant, whatever the magnitude of the flood. Indeed, the predictive distributions may not be reliable in extrapolation. However, estimating the predictive uncertainty for these rare events is crucial when major floods are of concern. In order to improve the forecasts reliability for major floods, an attempt at combining the operational strength of the empirical statistical analysis and a simple error modelling is done. Since the heteroscedasticity of forecast errors can considerably weaken the predictive reliability for large floods, this error modelling is based on the log-sinh transformation which proved to reduce significantly the heteroscedasticity of the transformed error in a simulation context, even for flood peaks (Wang et al., 2012). Exploratory tests on some operational forecasts issued during the recent floods experienced in France (major spring floods in June 2016 on the Loire river tributaries and flash floods in fall 2016) will be shown and discussed. References Bourgin, F. (2014). How to assess the predictive uncertainty in hydrological modelling? An exploratory work on a large sample of watersheds, AgroParisTech Wang, Q. J., Shrestha, D. L., Robertson, D. E. and Pokhrel, P (2012). A log-sinh transformation for data normalization and variance stabilization. Water Resources Research, , W05514, doi:10.1029/2011WR010973

A procedure for the significance testing of unmodeled errors in GNSS observations

NASA Astrophysics Data System (ADS)

Li, Bofeng; Zhang, Zhetao; Shen, Yunzhong; Yang, Ling

2018-01-01

It is a crucial task to establish a precise mathematical model for global navigation satellite system (GNSS) observations in precise positioning. Due to the spatiotemporal complexity of, and limited knowledge on, systematic errors in GNSS observations, some residual systematic errors would inevitably remain even after corrected with empirical model and parameterization. These residual systematic errors are referred to as unmodeled errors. However, most of the existing studies mainly focus on handling the systematic errors that can be properly modeled and then simply ignore the unmodeled errors that may actually exist. To further improve the accuracy and reliability of GNSS applications, such unmodeled errors must be handled especially when they are significant. Therefore, a very first question is how to statistically validate the significance of unmodeled errors. In this research, we will propose a procedure to examine the significance of these unmodeled errors by the combined use of the hypothesis tests. With this testing procedure, three components of unmodeled errors, i.e., the nonstationary signal, stationary signal and white noise, are identified. The procedure is tested by using simulated data and real BeiDou datasets with varying error sources. The results show that the unmodeled errors can be discriminated by our procedure with approximately 90% confidence. The efficiency of the proposed procedure is further reassured by applying the time-domain Allan variance analysis and frequency-domain fast Fourier transform. In summary, the spatiotemporally correlated unmodeled errors are commonly existent in GNSS observations and mainly governed by the residual atmospheric biases and multipath. Their patterns may also be impacted by the receiver.

State space truncation with quantified errors for accurate solutions to discrete Chemical Master Equation

PubMed Central

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

State Space Truncation with Quantified Errors for Accurate Solutions to Discrete Chemical Master Equation

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

State Space Truncation with Quantified Errors for Accurate Solutions to Discrete Chemical Master Equation

DOE PAGES

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

Empirical mono- versus combination antibiotic therapy in adult intensive care patients with severe sepsis - A systematic review with meta-analysis and trial sequential analysis.

PubMed

Sjövall, Fredrik; Perner, Anders; Hylander Møller, Morten

2017-04-01

To assess benefits and harms of empirical mono- vs. combination antibiotic therapy in adult patients with severe sepsis in the intensive care unit (ICU). We performed a systematic review according to the Cochrane Collaboration methodology, including meta-analysis, risk of bias assessment and trial sequential analysis (TSA). We included randomised clinical trials (RCT) assessing empirical mono-antibiotic therapy versus a combination of two or more antibiotics in adult ICU patients with severe sepsis. We exclusively assessed patient-important outcomes, including mortality. Two reviewers independently evaluated studies for inclusion, extracted data, and assessed risk of bias. Risk ratios (RRs) with 95% confidence intervals (CIs) were estimated and the risk of random errors was assessed by TSA. Thirteen RCTs (n = 2633) were included; all were judged as having high risk of bias. Carbapenems were the most frequently used mono-antibiotic (8 of 13 trials). There was no difference in mortality (RR 1.11, 95% CI 0.95-1.29; p = 0.19) or in any other patient-important outcomes between mono- vs. combination therapy. In TSA of mortality, the Z-curve reached the futility area, indicating that a 20% relative risk difference in mortality may be excluded between the two groups. For the other outcomes, TSA indicated lack of data and high risk of random errors. This systematic review of RCTs with meta-analysis and TSA demonstrated no differences in mortality or other patient-important outcomes between empirical mono- vs. combination antibiotic therapy in adult ICU patients with severe sepsis. The quantity and quality of data was low without firm evidence for benefit or harm of combination therapy. Copyright © 2016 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

Development of a Coordinate Transformation method for direct georeferencing in map projection frames

NASA Astrophysics Data System (ADS)

Zhao, Haitao; Zhang, Bing; Wu, Changshan; Zuo, Zhengli; Chen, Zhengchao

2013-03-01

This paper develops a novel Coordinate Transformation method (CT-method), with which the orientation angles (roll, pitch, heading) of the local tangent frame of the GPS/INS system are transformed into those (omega, phi, kappa) of the map projection frame for direct georeferencing (DG). Especially, the orientation angles in the map projection frame were derived from a sequence of coordinate transformations. The effectiveness of orientation angles transformation was verified through comparing with DG results obtained from conventional methods (Legat method and POSPac method) using empirical data. Moreover, the CT-method was also validated with simulated data. One advantage of the proposed method is that the orientation angles can be acquired simultaneously while calculating position elements of exterior orientation (EO) parameters and auxiliary points coordinates by coordinate transformation. These three methods were demonstrated and compared using empirical data. Empirical results show that the CT-method is both as sound and effective as Legat method. Compared with POSPac method, the CT-method is more suitable for calculating EO parameters for DG in map projection frames. DG accuracy of the CT-method and Legat method are at the same level. DG results of all these three methods have systematic errors in height due to inconsistent length projection distortion in the vertical and horizontal components, and these errors can be significantly reduced using the EO height correction technique in Legat's approach. Similar to the results obtained with empirical data, the effectiveness of the CT-method was also proved with simulated data. POSPac method: The method is presented by Applanix POSPac software technical note (Hutton and Savina, 1997). It is implemented in the POSEO module of POSPac software.

A model of two-way selection system for human behavior.

PubMed

Zhou, Bin; Qin, Shujia; Han, Xiao-Pu; He, Zhe; Xie, Jia-Rong; Wang, Bing-Hong

2014-01-01

Two-way selection is a common phenomenon in nature and society. It appears in the processes like choosing a mate between men and women, making contracts between job hunters and recruiters, and trading between buyers and sellers. In this paper, we propose a model of two-way selection system, and present its analytical solution for the expectation of successful matching total and the regular pattern that the matching rate trends toward an inverse proportion to either the ratio between the two sides or the ratio of the state total to the smaller group's people number. The proposed model is verified by empirical data of the matchmaking fairs. Results indicate that the model well predicts this typical real-world two-way selection behavior to the bounded error extent, thus it is helpful for understanding the dynamics mechanism of the real-world two-way selection system.

SPIN or LURCH : a Comparative Assessment of Model Checking and Stochastic Search for Temporal Properties in Procedural Code

NASA Technical Reports Server (NTRS)

Powell, John D.; Owens, David; Menzies, Tim

2004-01-01

The difficulty of how to test large systems, such as the one on board a NASA robotic remote explorer (RRE) vehicle, is fundamentally a search issue: the global state space representing all possible has yet to be solved, even after many decades of work. Randomized algorithms have been known to outperform their deterministic counterparts for search problems representing a wide range of applications. In the case study presented here, the LURCH randomized algorithm proved to be adequate to the task of testing a NASA RRE vehicle. LURCH found all the errors found by an earlier analysis of a more complete method (SPIN). Our empirical results are that LURCH can scale to much larger models than standard model checkers like SMV and SPIN. Further, the LURCH analysis was simpler than the SPIN analysis. The simplicity and scalability of LURCH are two compelling reasons for experimenting further with this tool.

Testing manifest monotonicity using order-constrained statistical inference.

PubMed

Tijmstra, Jesper; Hessen, David J; van der Heijden, Peter G M; Sijtsma, Klaas

2013-01-01

Most dichotomous item response models share the assumption of latent monotonicity, which states that the probability of a positive response to an item is a nondecreasing function of a latent variable intended to be measured. Latent monotonicity cannot be evaluated directly, but it implies manifest monotonicity across a variety of observed scores, such as the restscore, a single item score, and in some cases the total score. In this study, we show that manifest monotonicity can be tested by means of the order-constrained statistical inference framework. We propose a procedure that uses this framework to determine whether manifest monotonicity should be rejected for specific items. This approach provides a likelihood ratio test for which the p-value can be approximated through simulation. A simulation study is presented that evaluates the Type I error rate and power of the test, and the procedure is applied to empirical data.

Generalized Constitutive-Based Theoretical and Empirical Models for Hot Working Behavior of Functionally Graded Steels

NASA Astrophysics Data System (ADS)

Vanini, Seyed Ali Sadough; Abolghasemzadeh, Mohammad; Assadi, Abbas

2013-07-01

Functionally graded steels with graded ferritic and austenitic regions including bainite and martensite intermediate layers produced by electroslag remelting have attracted much attention in recent years. In this article, an empirical model based on the Zener-Hollomon (Z-H) constitutive equation with generalized material constants is presented to investigate the effects of temperature and strain rate on the hot working behavior of functionally graded steels. Next, a theoretical model, generalized by strain compensation, is developed for the flow stress estimation of functionally graded steels under hot compression based on the phase mixture rule and boundary layer characteristics. The model is used for different strains and grading configurations. Specifically, the results for αβγMγ steels from empirical and theoretical models showed excellent agreement with those of experiments of other references within acceptable error.

From Heuristic to Mathematical Modeling of Drugs Dissolution Profiles: Application of Artificial Neural Networks and Genetic Programming

PubMed Central

Mendyk, Aleksander; Güres, Sinan; Szlęk, Jakub; Wiśniowska, Barbara; Kleinebudde, Peter

2015-01-01

The purpose of this work was to develop a mathematical model of the drug dissolution (Q) from the solid lipid extrudates based on the empirical approach. Artificial neural networks (ANNs) and genetic programming (GP) tools were used. Sensitivity analysis of ANNs provided reduction of the original input vector. GP allowed creation of the mathematical equation in two major approaches: (1) direct modeling of Q versus extrudate diameter (d) and the time variable (t) and (2) indirect modeling through Weibull equation. ANNs provided also information about minimum achievable generalization error and the way to enhance the original dataset used for adjustment of the equations' parameters. Two inputs were found important for the drug dissolution: d and t. The extrudates length (L) was found not important. Both GP modeling approaches allowed creation of relatively simple equations with their predictive performance comparable to the ANNs (root mean squared error (RMSE) from 2.19 to 2.33). The direct mode of GP modeling of Q versus d and t resulted in the most robust model. The idea of how to combine ANNs and GP in order to escape ANNs' black-box drawback without losing their superior predictive performance was demonstrated. Open Source software was used to deliver the state-of-the-art models and modeling strategies. PMID:26101544

From Heuristic to Mathematical Modeling of Drugs Dissolution Profiles: Application of Artificial Neural Networks and Genetic Programming.

PubMed

Mendyk, Aleksander; Güres, Sinan; Jachowicz, Renata; Szlęk, Jakub; Polak, Sebastian; Wiśniowska, Barbara; Kleinebudde, Peter

2015-01-01

The purpose of this work was to develop a mathematical model of the drug dissolution (Q) from the solid lipid extrudates based on the empirical approach. Artificial neural networks (ANNs) and genetic programming (GP) tools were used. Sensitivity analysis of ANNs provided reduction of the original input vector. GP allowed creation of the mathematical equation in two major approaches: (1) direct modeling of Q versus extrudate diameter (d) and the time variable (t) and (2) indirect modeling through Weibull equation. ANNs provided also information about minimum achievable generalization error and the way to enhance the original dataset used for adjustment of the equations' parameters. Two inputs were found important for the drug dissolution: d and t. The extrudates length (L) was found not important. Both GP modeling approaches allowed creation of relatively simple equations with their predictive performance comparable to the ANNs (root mean squared error (RMSE) from 2.19 to 2.33). The direct mode of GP modeling of Q versus d and t resulted in the most robust model. The idea of how to combine ANNs and GP in order to escape ANNs' black-box drawback without losing their superior predictive performance was demonstrated. Open Source software was used to deliver the state-of-the-art models and modeling strategies.

Local air gap thickness and contact area models for realistic simulation of human thermo-physiological response

NASA Astrophysics Data System (ADS)

Psikuta, Agnes; Mert, Emel; Annaheim, Simon; Rossi, René M.

2018-02-01

To evaluate the quality of new energy-saving and performance-supporting building and urban settings, the thermal sensation and comfort models are often used. The accuracy of these models is related to accurate prediction of the human thermo-physiological response that, in turn, is highly sensitive to the local effect of clothing. This study aimed at the development of an empirical regression model of the air gap thickness and the contact area in clothing to accurately simulate human thermal and perceptual response. The statistical model predicted reliably both parameters for 14 body regions based on the clothing ease allowances. The effect of the standard error in air gap prediction on the thermo-physiological response was lower than the differences between healthy humans. It was demonstrated that currently used assumptions and methods for determination of the air gap thickness can produce a substantial error for all global, mean, and local physiological parameters, and hence, lead to false estimation of the resultant physiological state of the human body, thermal sensation, and comfort. Thus, this model may help researchers to strive for improvement of human thermal comfort, health, productivity, safety, and overall sense of well-being with simultaneous reduction of energy consumption and costs in built environment.

Signs of universality in the structure of culture

NASA Astrophysics Data System (ADS)

Băbeanu, Alexandru-Ionuţ; Talman, Leandros; Garlaschelli, Diego

2017-11-01

Understanding the dynamics of opinions, preferences and of culture as whole requires more use of empirical data than has been done so far. It is clear that an important role in driving this dynamics is played by social influence, which is the essential ingredient of many quantitative models. Such models require that all traits are fixed when specifying the "initial cultural state". Typically, this initial state is randomly generated, from a uniform distribution over the set of possible combinations of traits. However, recent work has shown that the outcome of social influence dynamics strongly depends on the nature of the initial state. If the latter is sampled from empirical data instead of being generated in a uniformly random way, a higher level of cultural diversity is found after long-term dynamics, for the same level of propensity towards collective behavior in the short-term. Moreover, if the initial state is randomized by shuffling the empirical traits among people, the level of long-term cultural diversity is in-between those obtained for the empirical and uniformly random counterparts. The current study repeats the analysis for multiple empirical data sets, showing that the results are remarkably similar, although the matrix of correlations between cultural variables clearly differs across data sets. This points towards robust structural properties inherent in empirical cultural states, possibly due to universal laws governing the dynamics of culture in the real world. The results also suggest that this dynamics might be characterized by criticality and involve mechanisms beyond social influence.

On land-use modeling: A treatise of satellite imagery data and misclassification error

NASA Astrophysics Data System (ADS)

Sandler, Austin M.

Recent availability of satellite-based land-use data sets, including data sets with contiguous spatial coverage over large areas, relatively long temporal coverage, and fine-scale land cover classifications, is providing new opportunities for land-use research. However, care must be used when working with these datasets due to misclassification error, which causes inconsistent parameter estimates in the discrete choice models typically used to model land-use. I therefore adapt the empirical correction methods developed for other contexts (e.g., epidemiology) so that they can be applied to land-use modeling. I then use a Monte Carlo simulation, and an empirical application using actual satellite imagery data from the Northern Great Plains, to compare the results of a traditional model ignoring misclassification to those from models accounting for misclassification. Results from both the simulation and application indicate that ignoring misclassification will lead to biased results. Even seemingly insignificant levels of misclassification error (e.g., 1%) result in biased parameter estimates, which alter marginal effects enough to affect policy inference. At the levels of misclassification typical in current satellite imagery datasets (e.g., as high as 35%), ignoring misclassification can lead to systematically erroneous land-use probabilities and substantially biased marginal effects. The correction methods I propose, however, generate consistent parameter estimates and therefore consistent estimates of marginal effects and predicted land-use probabilities.

Pre-processing by data augmentation for improved ellipse fitting.

PubMed

Kumar, Pankaj; Belchamber, Erika R; Miklavcic, Stanley J

2018-01-01

Ellipse fitting is a highly researched and mature topic. Surprisingly, however, no existing method has thus far considered the data point eccentricity in its ellipse fitting procedure. Here, we introduce the concept of eccentricity of a data point, in analogy with the idea of ellipse eccentricity. We then show empirically that, irrespective of ellipse fitting method used, the root mean square error (RMSE) of a fit increases with the eccentricity of the data point set. The main contribution of the paper is based on the hypothesis that if the data point set were pre-processed to strategically add additional data points in regions of high eccentricity, then the quality of a fit could be improved. Conditional validity of this hypothesis is demonstrated mathematically using a model scenario. Based on this confirmation we propose an algorithm that pre-processes the data so that data points with high eccentricity are replicated. The improvement of ellipse fitting is then demonstrated empirically in real-world application of 3D reconstruction of a plant root system for phenotypic analysis. The degree of improvement for different underlying ellipse fitting methods as a function of data noise level is also analysed. We show that almost every method tested, irrespective of whether it minimizes algebraic error or geometric error, shows improvement in the fit following data augmentation using the proposed pre-processing algorithm.

Wind tunnel seeding particles for laser velocimeter

NASA Technical Reports Server (NTRS)

Ghorieshi, Anthony

1992-01-01

The design of an optimal air foil has been a major challenge for aerospace industries. The main objective is to reduce the drag force while increasing the lift force in various environmental air conditions. Experimental verification of theoretical and computational results is a crucial part of the analysis because of errors buried in the solutions, due to the assumptions made in theoretical work. Experimental studies are an integral part of a good design procedure; however, empirical data are not always error free due to environmental obstacles or poor execution, etc. The reduction of errors in empirical data is a major challenge in wind tunnel testing. One of the recent advances of particular interest is the use of a non-intrusive measurement technique known as laser velocimetry (LV) which allows for obtaining quantitative flow data without introducing flow disturbing probes. The laser velocimeter technique is based on measurement of scattered light by the particles present in the flow but not the velocity of the flow. Therefore, for an accurate flow velocity measurement with laser velocimeters, two criterion are investigated: (1) how well the particles track the local flow field, and (2) the requirement of light scattering efficiency to obtain signals with the LV. In order to demonstrate the concept of predicting the flow velocity by velocity measurement of particle seeding, the theoretical velocity of the gas flow is computed and compared with experimentally obtained velocity of particle seeding.

HSE management standards and stress-related work outcomes.

PubMed

Kerr, Robert; McHugh, Marie; McCrory, Mark

2009-12-01

The UK Health and Safety Executive's (HSE) Management Standards (MS) approach has been developed to help organizations manage potential sources of work-related stress. Although there is general support for the assessment model adopted by this approach, to date, there has been no empirical investigation of the relationship between the actual MS (as measured by the final revised version of the HSE Indicator Tool) and stress-related work outcomes. To investigate the relationship between the HSE MS and the following stress-related work outcomes: 'job satisfaction', job-related anxiety and depression and errors/near misses. An anonymous cross-sectional questionnaire was distributed by either e-mail or post to all employees within a community-based Health and Social Services Trust. Respondents completed the HSE Indicator Tool, a job-related anxiety and depression scale, a job satisfaction scale and an aggregated measure of the number of errors/near misses witnessed. Associations between the HSE Indicator Tool responses and stress-related work outcomes were analysed with regression statistics. A total of 707 employees completed the questionnaire, representing a low response rate of 29%. Controlling for age, gender and contract type, the HSE MS (as measured by the HSE Indicator Tool) were positively associated with job satisfaction and negatively associated with 'job-related anxiety', 'job-related depression' and 'witnessed errors/near misses'. This study provides empirical evidence to support the use of the MS approach in tackling workplace stress.

Disturbance torque rejection properties of the NASA/JPL 70-meter antenna axis servos

NASA Technical Reports Server (NTRS)

Hill, R. E.

1989-01-01

Analytic methods for evaluating pointing errors caused by external disturbance torques are developed and applied to determine the effects of representative values of wind and friction torque. The expressions relating pointing errors to disturbance torques are shown to be strongly dependent upon the state estimator parameters, as well as upon the state feedback gain and the flow versus pressure characteristics of the hydraulic system. Under certain conditions, when control is derived from an uncorrected estimate of integral position error, the desired type 2 servo properties are not realized and finite steady-state position errors result. Methods for reducing these errors to negligible proportions through the proper selection of control gain and estimator correction parameters are demonstrated. The steady-state error produced by a disturbance torque is found to be directly proportional to the hydraulic internal leakage. This property can be exploited to provide a convenient method of determining system leakage from field measurements of estimator error, axis rate, and hydraulic differential pressure.

Simultaneous Control of Error Rates in fMRI Data Analysis

PubMed Central

Kang, Hakmook; Blume, Jeffrey; Ombao, Hernando; Badre, David

2015-01-01

The key idea of statistical hypothesis testing is to fix, and thereby control, the Type I error (false positive) rate across samples of any size. Multiple comparisons inflate the global (family-wise) Type I error rate and the traditional solution to maintaining control of the error rate is to increase the local (comparison-wise) Type II error (false negative) rates. However, in the analysis of human brain imaging data, the number of comparisons is so large that this solution breaks down: the local Type II error rate ends up being so large that scientifically meaningful analysis is precluded. Here we propose a novel solution to this problem: allow the Type I error rate to converge to zero along with the Type II error rate. It works because when the Type I error rate per comparison is very small, the accumulation (or global) Type I error rate is also small. This solution is achieved by employing the Likelihood paradigm, which uses likelihood ratios to measure the strength of evidence on a voxel-by-voxel basis. In this paper, we provide theoretical and empirical justification for a likelihood approach to the analysis of human brain imaging data. In addition, we present extensive simulations that show the likelihood approach is viable, leading to ‘cleaner’ looking brain maps and operationally superiority (lower average error rate). Finally, we include a case study on cognitive control related activation in the prefrontal cortex of the human brain. PMID:26272730

Gaming against medical errors: methods and results from a design game on CPOE.

PubMed

Kanstrup, Anne Marie; Nøhr, Christian

2009-01-01

The paper presents design game as a technique for participatory design for a Computerized Decision Support System (CDSS) for minimizing medical errors. Design game is used as a technique for working with the skills of users, the complexity of the use practice and the negotiation of design here within the challenging domain of medication. The paper presents a developed design game based on game inspiration from a computer game, theoretical inspiration on electronic decision support, and empirical grounding in scenarios of medical errors. The game has been played in a two-hour workshop with six clinicians. The result is presented as a list of central themes for design of CDSS and derived design principles from these themes. These principles are currently under further exploration in follow up prototype based activities.

Error compensation of single-antenna attitude determination using GNSS for Low-dynamic applications

NASA Astrophysics Data System (ADS)

Chen, Wen; Yu, Chao; Cai, Miaomiao

2017-04-01

GNSS-based single-antenna pseudo-attitude determination method has attracted more and more attention from the field of high-dynamic navigation due to its low cost, low system complexity, and no temporal accumulated errors. Related researches indicate that this method can be an important complement or even an alternative to the traditional sensors for general accuracy requirement (such as small UAV navigation). The application of single-antenna attitude determining method to low-dynamic carrier has just started. Different from the traditional multi-antenna attitude measurement technique, the pseudo-attitude attitude determination method calculates the rotation angle of the carrier trajectory relative to the earth. Thus it inevitably contains some deviations comparing with the real attitude angle. In low-dynamic application, these deviations are particularly noticeable, which may not be ignored. The causes of the deviations can be roughly classified into three categories, including the measurement error, the offset error, and the lateral error. Empirical correction strategies for the formal two errors have been promoted in previous study, but lack of theoretical support. In this paper, we will provide quantitative description of the three type of errors and discuss the related error compensation methods. Vehicle and shipborne experiments were carried out to verify the feasibility of the proposed correction methods. Keywords: Error compensation; Single-antenna; GNSS; Attitude determination; Low-dynamic

Accurate Temperature Feedback Control for MRI-Guided, Phased Array HICU Endocavitary Therapy

NASA Astrophysics Data System (ADS)

Salomir, Rares; Rata, Mihaela; Cadis, Daniela; Lafon, Cyril; Chapelon, Jean Yves; Cotton, François; Bonmartin, Alain; Cathignol, Dominique

2007-05-01

Effective treatment of malignant tumours demands well controlled energy deposition in the region of interest. Generally, two major steps must be fulfilled: 1. pre-operative optimal planning of the thermal dosimetry and 2. per-operative active spatial-and-temporal control of the delivered thermal dose. The second issue is made possible by using fast MR thermometry data and adjusting on line the sonication parameters. This approach is addressed here in the particular case of the ultrasound therapy for endocavitary tumours (oesophagus, colon or rectum) with phased array cylindrical applicators of High Intensity Contact Ultrasound (HICU). Two specific methodological objectives have been defined for this study: 1. to implement a robust and effective temperature controller for the specific geometry of endocavitary HICU and 2. to determine the stability (ie convergence) domain of the controller with respect to possible errors affecting the empirical parameters of the underlying physical model. Experimental setup included a Philips 1.5T clinical MR scanner and a cylindrical phased array transducer (64 elements) driven by a computer-controlled multi-channel generator. Performance of the temperature controller was tested ex vivo on fresh meat samples with planar and slightly focused beams, for a temperature elevation range from 10°C to 30°C. During the steady state regime, typical error of the temperature mean value was inferior to 1%, while the typical standard deviation of the temperature was inferior to 2% (relative to the targeted temperature elevation). Further, the empirical parameters of the physical model have been deliberately set to erroneous values and the impact on the controller stability was evaluated. Excellent tolerance of the controller was demonstrated, as this one failed to performed stable feedback only in the extreme case of a strong underestimation for the ultrasound absorption parameter by a factor of 4 or more.

Proximal antecedents and correlates of adopted error approach: a self-regulatory perspective.

PubMed

Van Dyck, Cathy; Van Hooft, Edwin; De Gilder, Dick; Liesveld, Lillian

2010-01-01

The current study aims to further investigate earlier established advantages of an error mastery approach over an error aversion approach. The two main purposes of the study relate to (1) self-regulatory traits (i.e., goal orientation and action-state orientation) that may predict which error approach (mastery or aversion) is adopted, and (2) proximal, psychological processes (i.e., self-focused attention and failure attribution) that relate to adopted error approach. In the current study participants' goal orientation and action-state orientation were assessed, after which they worked on an error-prone task. Results show that learning goal orientation related to error mastery, while state orientation related to error aversion. Under a mastery approach, error occurrence did not result in cognitive resources "wasted" on self-consciousness. Rather, attention went to internal-unstable, thus controllable, improvement oriented causes of error. Participants that had adopted an aversion approach, in contrast, experienced heightened self-consciousness and attributed failure to internal-stable or external causes. These results imply that when working on an error-prone task, people should be stimulated to take on a mastery rather than an aversion approach towards errors.

Utility of the Mantel-Haenszel Procedure for Detecting Differential Item Functioning in Small Samples

ERIC Educational Resources Information Center

Fidalgo, Angel M.; Ferreres, Doris; Muniz, Jose

2004-01-01

Sample-size restrictions limit the contingency table approaches based on asymptotic distributions, such as the Mantel-Haenszel (MH) procedure, for detecting differential item functioning (DIF) in many practical applications. Within this framework, the present study investigated the power and Type I error performance of empirical and inferential…

Communication Vagueness in the Literature Review Section of Journal Article Submissions

ERIC Educational Resources Information Center

Onwuegbuzie, Anthony J.

2018-01-01

Evidence has been provided about the importance of avoiding American Psychological Association (APA) errors in the abstract, body, reference list, and table sections of empirical research articles. Specifically, authors are significantly more likely to have their manuscripts rejected for publication if they fail to avoid APA violations--and, thus,…

Applying Generalizability Theory To Evaluate Treatment Effect in Single-Subject Research.

ERIC Educational Resources Information Center

Lefebvre, Daniel J.; Suen, Hoi K.

An empirical investigation of methodological issues associated with evaluating treatment effect in single-subject research (SSR) designs is presented. This investigation: (1) conducted a generalizability (G) study to identify the sources of systematic and random measurement error (SRME); (2) used an analytic approach based on G theory to integrate…

Interpreting Self-Directed Search Profiles: Validity of the "Rule of Eight"

ERIC Educational Resources Information Center

Glavin, Kevin W.; Savickas, Mark L.

2011-01-01

Based on the standard error of measurement, Holland (1985) suggested the "rule of eight" for determining the meaningfulness of differences between two summary scores on the Self Directed Search. The present study empirically examined the rule's validity for practice. The participants were 2397 (1497 females and 900 males) undergraduate…

Markers, Models, and Measurement Error: Exploring the Links between Attention Deficits and Language Impairments

ERIC Educational Resources Information Center

Redmond, Sean M.

2016-01-01

Purpose: The empirical record regarding the expected co-occurrence of attention-deficit/hyperactivity disorder (ADHD) and specific language impairment is confusing and contradictory. A research plan is presented that has the potential to untangle links between these 2 common neurodevelopmental disorders. Method: Data from completed and ongoing…

Analyzing Multivariate Repeated Measures Designs: A Comparison of Two Approximate Degrees of Freedom Procedures

ERIC Educational Resources Information Center

Lix, Lisa M.; Algina, James; Keselman, H. J.

2003-01-01

The approximate degrees of freedom Welch-James (WJ) and Brown-Forsythe (BF) procedures for testing within-subjects effects in multivariate groups by trials repeated measures designs were investigated under departures from covariance homogeneity and normality. Empirical Type I error and power rates were obtained for least-squares estimators and…

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

Vasylkivska, Veronika S.; Huerta, Nicolas J.

Determining the spatiotemporal characteristics of natural and induced seismic events holds the opportunity to gain new insights into why these events occur. Linking the seismicity characteristics with other geologic, geographic, natural, or anthropogenic factors could help to identify the causes and suggest mitigation strategies that reduce the risk associated with such events. The nearest-neighbor approach utilized in this work represents a practical first step toward identifying statistically correlated clusters of recorded earthquake events. Detailed study of the Oklahoma earthquake catalog’s inherent errors, empirical model parameters, and model assumptions is presented. We found that the cluster analysis results are stable withmore » respect to empirical parameters (e.g., fractal dimension) but were sensitive to epicenter location errors and seismicity rates. Most critically, we show that the patterns in the distribution of earthquake clusters in Oklahoma are primarily defined by spatial relationships between events. This observation is a stark contrast to California (also known for induced seismicity) where a comparable cluster distribution is defined by both spatial and temporal interactions between events. These results highlight the difficulty in understanding the mechanisms and behavior of induced seismicity but provide insights for future work.« less

More sound of church bells: Authors' correction

NASA Astrophysics Data System (ADS)

Vogt, Patrik; Kasper, Lutz; Burde, Jan-Philipp

2016-01-01

In the recently published article "The Sound of Church Bells: Tracking Down the Secret of a Traditional Arts and Crafts Trade," the bell frequencies have been erroneously oversimplified. The problem affects Eqs. (2) and (3), which were derived from the elementary "coffee mug model" and in which we used the speed of sound in air. However, this does not make sense from a physical point of view, since air only acts as a sound carrier, not as a sound source in the case of bells. Due to the excellent fit of the theoretical model with the empirical data, we unfortunately failed to notice this error before publication. However, all other equations, e.g., the introduction of the correction factor in Eq. (4) and the estimation of the mass in Eqs. (5) and (6) are not affected by this error, since they represent empirical models. However, it is unfortunate to introduce the speed of sound in air as a constant in Eqs. (4) and (6). Instead, we suggest the following simple rule of thumb for relating the radius of a church bell R to its humming frequency fhum:

Model uncertainty of various settlement estimation methods in shallow tunnels excavation; case study: Qom subway tunnel

NASA Astrophysics Data System (ADS)

Khademian, Amir; Abdollahipour, Hamed; Bagherpour, Raheb; Faramarzi, Lohrasb

2017-10-01

In addition to the numerous planning and executive challenges, underground excavation in urban areas is always followed by certain destructive effects especially on the ground surface; ground settlement is the most important of these effects for which estimation there exist different empirical, analytical and numerical methods. Since geotechnical models are associated with considerable model uncertainty, this study characterized the model uncertainty of settlement estimation models through a systematic comparison between model predictions and past performance data derived from instrumentation. To do so, the amount of surface settlement induced by excavation of the Qom subway tunnel was estimated via empirical (Peck), analytical (Loganathan and Poulos) and numerical (FDM) methods; the resulting maximum settlement value of each model were 1.86, 2.02 and 1.52 cm, respectively. The comparison of these predicted amounts with the actual data from instrumentation was employed to specify the uncertainty of each model. The numerical model outcomes, with a relative error of 3.8%, best matched the reality and the analytical method, with a relative error of 27.8%, yielded the highest level of model uncertainty.

Application of Ensemble Kalman Filter in Power System State Tracking and Sensitivity

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

Li, Yulan; Huang, Zhenyu; Zhou, Ning

2012-05-01

Ensemble Kalman Filter (EnKF) is proposed to track dynamic states of generators. The algorithm of EnKF and its application to generator state tracking are presented in detail. The accuracy and sensitivity of the method are analyzed with respect to initial state errors, measurement noise, unknown fault locations, time steps and parameter errors. It is demonstrated through simulation studies that even with some errors in the parameters, the developed EnKF can effectively track generator dynamic states using disturbance data.

National Aeronautics and Space Administration "threat and error" model applied to pediatric cardiac surgery: error cycles precede ∼85% of patient deaths.

PubMed

Hickey, Edward J; Nosikova, Yaroslavna; Pham-Hung, Eric; Gritti, Michael; Schwartz, Steven; Caldarone, Christopher A; Redington, Andrew; Van Arsdell, Glen S

2015-02-01

We hypothesized that the National Aeronautics and Space Administration "threat and error" model (which is derived from analyzing >30,000 commercial flights, and explains >90% of crashes) is directly applicable to pediatric cardiac surgery. We implemented a unit-wide performance initiative, whereby every surgical admission constitutes a "flight" and is tracked in real time, with the aim of identifying errors. The first 500 consecutive patients (524 flights) were analyzed, with an emphasis on the relationship between error cycles and permanent harmful outcomes. Among 524 patient flights (risk adjustment for congenital heart surgery category: 1-6; median: 2) 68 (13%) involved residual hemodynamic lesions, 13 (2.5%) permanent end-organ injuries, and 7 deaths (1.3%). Preoperatively, 763 threats were identified in 379 (72%) flights. Only 51% of patient flights (267) were error free. In the remaining 257 flights, 430 errors occurred, most commonly related to proficiency (280; 65%) or judgment (69, 16%). In most flights with errors (173 of 257; 67%), an unintended clinical state resulted, ie, the error was consequential. In 60% of consequential errors (n = 110; 21% of total), subsequent cycles of additional error/unintended states occurred. Cycles, particularly those containing multiple errors, were very significantly associated with permanent harmful end-states, including residual hemodynamic lesions (P < .0001), end-organ injury (P < .0001), and death (P < .0001). Deaths were almost always preceded by cycles (6 of 7; P < .0001). Human error, if not mitigated, often leads to cycles of error and unintended patient states, which are dangerous and precede the majority of harmful outcomes. Efforts to manage threats and error cycles (through crew resource management techniques) are likely to yield large increases in patient safety. Copyright © 2015. Published by Elsevier Inc.

False alarms and missed events: the impact and origins of perceived inaccuracy in tornado warning systems.

PubMed

Ripberger, Joseph T; Silva, Carol L; Jenkins-Smith, Hank C; Carlson, Deven E; James, Mark; Herron, Kerry G

2015-01-01

Theory and conventional wisdom suggest that errors undermine the credibility of tornado warning systems and thus decrease the probability that individuals will comply (i.e., engage in protective action) when future warnings are issued. Unfortunately, empirical research on the influence of warning system accuracy on public responses to tornado warnings is incomplete and inconclusive. This study adds to existing research by analyzing two sets of relationships. First, we assess the relationship between perceptions of accuracy, credibility, and warning response. Using data collected via a large regional survey, we find that trust in the National Weather Service (NWS; the agency responsible for issuing tornado warnings) increases the likelihood that an individual will opt for protective action when responding to a hypothetical warning. More importantly, we find that subjective perceptions of warning system accuracy are, as theory suggests, systematically related to trust in the NWS and (by extension) stated responses to future warnings. The second half of the study matches survey data against NWS warning and event archives to investigate a critical follow-up question--Why do some people perceive that their warning system is accurate, whereas others perceive that their system is error prone? We find that subjective perceptions are--in part-a function of objective experience, knowledge, and demographic characteristics. When considered in tandem, these findings support the proposition that errors influence perceptions about the accuracy of warning systems, which in turn impact the credibility that people assign to information provided by systems and, ultimately, public decisions about how to respond when warnings are issued. © 2014 Society for Risk Analysis.

Analytic Empirical Potential and its Comparison to State of the Art ab initio Calculations for the 6e^- Excited b(1^3Π_u)-STATE of Li_2.

NASA Astrophysics Data System (ADS)

Dattani, Nikesh S.; Le Roy, Robert J.

2015-06-01

Despite only having 6e^-, the most sophisticated Li_2(b,1^3Π_u) calculation has an r_e that disagrees with the empirical value by over 1500% of the latter's uncertainty, and energy spacings that disagree with those of the empirical potential by up to over 1.5cm-1. The discrepancy here is far more than for the ground state of the 5e^- system BeH, for which the best ab initio calculation gives an r_e which disagrees with the empirical value by less than 200% of the latter's uncertainty. In addition to this discrepancy, other reasons motivating the construction of an analytic empirical potential for Li_2(b,1^3Π_u) include (1) the fact that it is the most deeply bound Li_2 state, (2) it is the only Li_2 state out of the lowest five, for which no analytic empirical potential has yet been built, (3) the state it mixes with, the A(1^1σ_u)-state, is one of the most thoroughly characterized molecular states, but has a small gap of missing data in part of the region where it mixes with the b-state, and (4) it is one of the states accessible by new ultra-high precision techniques based on photoassociation. Finally (5) there is currently a discrepancy between the most sophisticated 3e- ab initio calculation, and the most current empirical value, for the first Li(^2S)-Li(^2P) interaction term (C_3), despite the latter being the most precise experimentally determined oscillator strength for any system, by an order of magnitude^e. The b-state is one of the states that has this exact C_3 interaction term. Musial & Kucharski (2014) J. Chem. Theor. Comp. 10, 1200. Dattani N. S. (2015) J. Mol. Spec. http://dx.doi.org/10.1016/j.jms.2014.09.005. Semczuk M., Li X., Gunton W., Haw M., Dattani N. S., Witz J., Mills A., Jones D. J., Madison K. W. (2013) Phys. Rev. A 87, 052505 Gunton W., Semczuk M., Dattani N. S., Madison K. W. (2013) Phys. Rev. A 88, 062510 Tang L.-Y., Yan Z.-C., Shi T.-Y., Mitroy J (2011) Phys. Rev. A 84, 052502. Le Roy R. J., Dattani N. S., Coxon J. A., Ross A. J., Crozet P., Linton C. (2009) J. Chem Phys. 131, 204309

Responses to Error: Sentence-Level Error and the Teacher of Basic Writing

ERIC Educational Resources Information Center

Foltz-Gray, Dan

2012-01-01

In this article, the author talks about sentence-level error, error in grammar, mechanics, punctuation, usage, and the teacher of basic writing. He states that communities are crawling with teachers and administrators and parents and state legislators and school board members who are engaged in sometimes rancorous debate over what to do about…

Concentration Dependences of the Surface Tension and Density of Solutions of Acetone-Ethanol-Water Systems at 293 K

NASA Astrophysics Data System (ADS)

Dadashev, R. Kh.; Dzhambulatov, R. S.; Mezhidov, V. Kh.; Elimkhanov, D. Z.

2018-05-01

Concentration dependences of the surface tension and density of solutions of three-component acetone-ethanol-water systems and the bounding binary systems at 273 K are studied. The molar volume, adsorption, and composition of surface layers are calculated. Experimental data and calculations show that three-component solutions are close to ideal ones. The surface tensions of these solutions are calculated using semi-empirical and theoretical equations. Theoretical equations qualitatively convey the concentration dependence of surface tension. A semi-empirical method based on the Köhler equation allows us to predict the concentration dependence of surface tension within the experimental error.

Gram-stain plus MALDI-TOF MS (Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry) for a rapid diagnosis of urinary tract infection.

PubMed

Burillo, Almudena; Rodríguez-Sánchez, Belén; Ramiro, Ana; Cercenado, Emilia; Rodríguez-Créixems, Marta; Bouza, Emilio

2014-01-01

Microbiological confirmation of a urinary tract infection (UTI) takes 24-48 h. In the meantime, patients are usually given empirical antibiotics, sometimes inappropriately. We assessed the feasibility of sequentially performing a Gram stain and MALDI-TOF MS mass spectrometry (MS) on urine samples to anticipate clinically useful information. In May-June 2012, we randomly selected 1000 urine samples from patients with suspected UTI. All were Gram stained and those yielding bacteria of a single morphotype were processed for MALDI-TOF MS. Our sequential algorithm was correlated with the standard semiquantitative urine culture result as follows: Match, the information provided was anticipative of culture result; Minor error, the information provided was partially anticipative of culture result; Major error, the information provided was incorrect, potentially leading to inappropriate changes in antimicrobial therapy. A positive culture was obtained in 242/1000 samples. The Gram stain revealed a single morphotype in 207 samples, which were subjected to MALDI-TOF MS. The diagnostic performance of the Gram stain was: sensitivity (Se) 81.3%, specificity (Sp) 93.2%, positive predictive value (PPV) 81.3%, negative predictive value (NPV) 93.2%, positive likelihood ratio (+LR) 11.91, negative likelihood ratio (-LR) 0.20 and accuracy 90.0% while that of MALDI-TOF MS was: Se 79.2%, Sp 73.5, +LR 2.99, -LR 0.28 and accuracy 78.3%. The use of both techniques provided information anticipative of the culture result in 82.7% of cases, information with minor errors in 13.4% and information with major errors in 3.9%. Results were available within 1 h. Our serial algorithm provided information that was consistent or showed minor errors for 96.1% of urine samples from patients with suspected UTI. The clinical impacts of this rapid UTI diagnosis strategy need to be assessed through indicators of adequacy of treatment such as a reduced time to appropriate empirical treatment or earlier withdrawal of unnecessary antibiotics.

Genetic Algorithm-Based Model Order Reduction of Aeroservoelastic Systems with Consistant States

NASA Technical Reports Server (NTRS)

Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter M.; Brenner, Martin J.

2017-01-01

This paper presents a model order reduction framework to construct linear parameter-varying reduced-order models of flexible aircraft for aeroservoelasticity analysis and control synthesis in broad two-dimensional flight parameter space. Genetic algorithms are used to automatically determine physical states for reduction and to generate reduced-order models at grid points within parameter space while minimizing the trial-and-error process. In addition, balanced truncation for unstable systems is used in conjunction with the congruence transformation technique to achieve locally optimal realization and weak fulfillment of state consistency across the entire parameter space. Therefore, aeroservoelasticity reduced-order models at any flight condition can be obtained simply through model interpolation. The methodology is applied to the pitch-plant model of the X-56A Multi-Use Technology Testbed currently being tested at NASA Armstrong Flight Research Center for flutter suppression and gust load alleviation. The present studies indicate that the reduced-order model with more than 12× reduction in the number of states relative to the original model is able to accurately predict system response among all input-output channels. The genetic-algorithm-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The interpolated aeroservoelasticity reduced order models exhibit smooth pole transition and continuously varying gains along a set of prescribed flight conditions, which verifies consistent state representation obtained by congruence transformation. The present model order reduction framework can be used by control engineers for robust aeroservoelasticity controller synthesis and novel vehicle design.

Asymmetric soft-error resistant memory

NASA Technical Reports Server (NTRS)

Buehler, Martin G. (Inventor); Perlman, Marvin (Inventor)

1991-01-01

A memory system is provided, of the type that includes an error-correcting circuit that detects and corrects, that more efficiently utilizes the capacity of a memory formed of groups of binary cells whose states can be inadvertently switched by ionizing radiation. Each memory cell has an asymmetric geometry, so that ionizing radiation causes a significantly greater probability of errors in one state than in the opposite state (e.g., an erroneous switch from '1' to '0' is far more likely than a switch from '0' to'1'. An asymmetric error correcting coding circuit can be used with the asymmetric memory cells, which requires fewer bits than an efficient symmetric error correcting code.

Evaluating multiple indices of agricultural water use efficiency and productivity to improve comparisons between sites and trends

NASA Astrophysics Data System (ADS)

Levy, M. C.

2012-12-01

Approximately 70% of global available freshwater supplies are used in the agricultural sector. Increased demands for water to meet growing population food requirements, and expected changes in the reliability of freshwater supplies due to climate change, threaten the sustainability of water supplies worldwide - not only on farms, but in connected cities and industries. Researchers concerned with agricultural water use sustainability use a variety of theoretical and empirical measures of efficiency and productivity to gain insight into the sustainability of agricultural water use. However, definitions of measures, or indices, vary between different natural and political boundaries, across regions, states and nations and between their respective research, industry, and environmental groups. Index development responds to local data availability and local agendas, and there is debate about the validity of various indices. However, real differences in empirical index measures are not well-understood across the multiple disciplines that study agricultural water use, including engineering and hydrology, agronomy, climate and soil sciences, and economics. Nevertheless reliable, accessible, and generalizable indices are required for planners and policymakers to promote sustainable water use systems. This study synthesizes a set of water use efficiency and productivity indices based on academic, industry and government literature in California and Australia, two locations with similarly water-stressed and valuable agricultural industries under pressure to achieve optimal water use efficiency and productivity. Empirical data at the irrigation district level from the California San Joaquin Valley and Murray Darling Basin states of Victoria and New South Wales in Australia are used to compute indices that estimate efficiency, yield productivity, and economic productivity of agricultural water use. Multiple index estimates of same time-series data demonstrate historical spread in efficiency and productivity measures in different agricultural regions. Individual indices consistently over- or under- estimate trends in efficiency and productivity by their construction, and may provide inaccurate results in years with extreme climatic events, such as droughts. By treating multiple indices as an "ensemble" of measures, analogous to the treatment of multiple climate model predictions, this study quantifies likely "true" states of efficiency and productivity in the selected agricultural regions, and error in individual indices. While different individual indices are preferable at different scales, and relative to the quality of available input data, ensemble indices can be more reliably used in comparative study across different agricultural regions, and for prediction.

Quantum state discrimination bounds for finite sample size

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

Audenaert, Koenraad M. R.; Mosonyi, Milan; Mathematical Institute, Budapest University of Technology and Economics, Egry Jozsef u 1., Budapest 1111

2012-12-15

In the problem of quantum state discrimination, one has to determine by measurements the state of a quantum system, based on the a priori side information that the true state is one of the two given and completely known states, {rho} or {sigma}. In general, it is not possible to decide the identity of the true state with certainty, and the optimal measurement strategy depends on whether the two possible errors (mistaking {rho} for {sigma}, or the other way around) are treated as of equal importance or not. Results on the quantum Chernoff and Hoeffding bounds and the quantum Stein'smore » lemma show that, if several copies of the system are available then the optimal error probabilities decay exponentially in the number of copies, and the decay rate is given by a certain statistical distance between {rho} and {sigma} (the Chernoff distance, the Hoeffding distances, and the relative entropy, respectively). While these results provide a complete solution to the asymptotic problem, they are not completely satisfying from a practical point of view. Indeed, in realistic scenarios one has access only to finitely many copies of a system, and therefore it is desirable to have bounds on the error probabilities for finite sample size. In this paper we provide finite-size bounds on the so-called Stein errors, the Chernoff errors, the Hoeffding errors, and the mixed error probabilities related to the Chernoff and the Hoeffding errors.« less

Improving the prediction of going concern of Taiwanese listed companies using a hybrid of LASSO with data mining techniques.

PubMed

Goo, Yeung-Ja James; Chi, Der-Jang; Shen, Zong-De

2016-01-01

The purpose of this study is to establish rigorous and reliable going concern doubt (GCD) prediction models. This study first uses the least absolute shrinkage and selection operator (LASSO) to select variables and then applies data mining techniques to establish prediction models, such as neural network (NN), classification and regression tree (CART), and support vector machine (SVM). The samples of this study include 48 GCD listed companies and 124 NGCD (non-GCD) listed companies from 2002 to 2013 in the TEJ database. We conduct fivefold cross validation in order to identify the prediction accuracy. According to the empirical results, the prediction accuracy of the LASSO-NN model is 88.96 % (Type I error rate is 12.22 %; Type II error rate is 7.50 %), the prediction accuracy of the LASSO-CART model is 88.75 % (Type I error rate is 13.61 %; Type II error rate is 14.17 %), and the prediction accuracy of the LASSO-SVM model is 89.79 % (Type I error rate is 10.00 %; Type II error rate is 15.83 %).

Reconstruction of regional mean temperature for East Asia since 1900s and its uncertainties

NASA Astrophysics Data System (ADS)

Hua, W.

2017-12-01

Regional average surface air temperature (SAT) is one of the key variables often used to investigate climate change. Unfortunately, because of the limited observations over East Asia, there were also some gaps in the observation data sampling for regional mean SAT analysis, which was important to estimate past climate change. In this study, the regional average temperature of East Asia since 1900s is calculated by the Empirical Orthogonal Function (EOF)-based optimal interpolation (OA) method with considering the data errors. The results show that our estimate is more precise and robust than the results from simple average, which provides a better way for past climate reconstruction. In addition to the reconstructed regional average SAT anomaly time series, we also estimated uncertainties of reconstruction. The root mean square error (RMSE) results show that the the error decreases with respect to time, and are not sufficiently large to alter the conclusions on the persist warming in East Asia during twenty-first century. Moreover, the test of influence of data error on reconstruction clearly shows the sensitivity of reconstruction to the size of the data error.

Developing a generalized allometric equation for aboveground biomass estimation

NASA Astrophysics Data System (ADS)

Xu, Q.; Balamuta, J. J.; Greenberg, J. A.; Li, B.; Man, A.; Xu, Z.

2015-12-01

A key potential uncertainty in estimating carbon stocks across multiple scales stems from the use of empirically calibrated allometric equations, which estimate aboveground biomass (AGB) from plant characteristics such as diameter at breast height (DBH) and/or height (H). The equations themselves contain significant and, at times, poorly characterized errors. Species-specific equations may be missing. Plant responses to their local biophysical environment may lead to spatially varying allometric relationships. The structural predictor may be difficult or impossible to measure accurately, particularly when derived from remote sensing data. All of these issues may lead to significant and spatially varying uncertainties in the estimation of AGB that are unexplored in the literature. We sought to quantify the errors in predicting AGB at the tree and plot level for vegetation plots in California. To accomplish this, we derived a generalized allometric equation (GAE) which we used to model the AGB on a full set of tree information such as DBH, H, taxonomy, and biophysical environment. The GAE was derived using published allometric equations in the GlobAllomeTree database. The equations were sparse in details about the error since authors provide the coefficient of determination (R2) and the sample size. A more realistic simulation of tree AGB should also contain the noise that was not captured by the allometric equation. We derived an empirically corrected variance estimate for the amount of noise to represent the errors in the real biomass. Also, we accounted for the hierarchical relationship between different species by treating each taxonomic level as a covariate nested within a higher taxonomic level (e.g. species < genus). This approach provides estimation under incomplete tree information (e.g. missing species) or blurred information (e.g. conjecture of species), plus the biophysical environment. The GAE allowed us to quantify contribution of each different covariate in estimating the AGB of trees. Lastly, we applied the GAE to an existing vegetation plot database - Forest Inventory and Analysis database - to derive per-tree and per-plot AGB estimations, their errors, and how much the error could be contributed to the original equations, the plant's taxonomy, and their biophysical environment.

The effects of errors on children's performance on a circle-ellipse discrimination.

PubMed

Stoddard, L T; Sidman, M

1967-05-01

Children first learned by means of a teaching program to discriminate a circle from relatively flat ellipses. Children in the control group then proceeded into a program which gradually reduced the difference between the circle and the ellipses. They advanced to a finer discrimination when they made a correct choice, and reversed to an easier discrimination after making errors ("backup" procedure). The children made relatively few errors until they approached the region of their difference threshold (empirically determined under the conditions described). When they could no longer discriminate the forms, they learned other bases for responding that could be classified as specifiable error patterns. Children in the experimental group, having learned the preliminary circle-ellipse discrimination, were started at the upper end of the ellipse series, where it was impossible for them to discriminate the forms. The backup procedure returned them to an easier discrimination after they made errors. They made many errors and reversed down through the ellipse series. Eventually, most of the children reached a point in the ellipse series where they abandoned their systematic errors and began to make correct first choices; then they advanced upward through the program. All of the children advanced to ellipse sizes that were much larger than the ellipse size at the point of their furthest descent.

Model Error Estimation for the CPTEC Eta Model

NASA Technical Reports Server (NTRS)

Tippett, Michael K.; daSilva, Arlindo

1999-01-01

Statistical data assimilation systems require the specification of forecast and observation error statistics. Forecast error is due to model imperfections and differences between the initial condition and the actual state of the atmosphere. Practical four-dimensional variational (4D-Var) methods try to fit the forecast state to the observations and assume that the model error is negligible. Here with a number of simplifying assumption, a framework is developed for isolating the model error given the forecast error at two lead-times. Two definitions are proposed for the Talagrand ratio tau, the fraction of the forecast error due to model error rather than initial condition error. Data from the CPTEC Eta Model running operationally over South America are used to calculate forecast error statistics and lower bounds for tau.

Human Error as an Emergent Property of Action Selection and Task Place-Holding.

PubMed

Tamborello, Franklin P; Trafton, J Gregory

2017-05-01

A computational process model could explain how the dynamic interaction of human cognitive mechanisms produces each of multiple error types. With increasing capability and complexity of technological systems, the potential severity of consequences of human error is magnified. Interruption greatly increases people's error rates, as does the presence of other information to maintain in an active state. The model executed as a software-instantiated Monte Carlo simulation. It drew on theoretical constructs such as associative spreading activation for prospective memory, explicit rehearsal strategies as a deliberate cognitive operation to aid retrospective memory, and decay. The model replicated the 30% effect of interruptions on postcompletion error in Ratwani and Trafton's Stock Trader task, the 45% interaction effect on postcompletion error of working memory capacity and working memory load from Byrne and Bovair's Phaser Task, as well as the 5% perseveration and 3% omission effects of interruption from the UNRAVEL Task. Error classes including perseveration, omission, and postcompletion error fall naturally out of the theory. The model explains post-interruption error in terms of task state representation and priming for recall of subsequent steps. Its performance suggests that task environments providing more cues to current task state will mitigate error caused by interruption. For example, interfaces could provide labeled progress indicators or facilities for operators to quickly write notes about their task states when interrupted.

Effect of deformable registration on the dose calculated in radiation therapy planning CT scans of lung cancer patients

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

Cunliffe, Alexandra R.; Armato, Samuel G.; White, Bradley

2015-01-15

Purpose: To characterize the effects of deformable image registration of serial computed tomography (CT) scans on the radiation dose calculated from a treatment planning scan. Methods: Eighteen patients who received curative doses (≥60 Gy, 2 Gy/fraction) of photon radiation therapy for lung cancer treatment were retrospectively identified. For each patient, a diagnostic-quality pretherapy (4–75 days) CT scan and a treatment planning scan with an associated dose map were collected. To establish correspondence between scan pairs, a researcher manually identified anatomically corresponding landmark point pairs between the two scans. Pretherapy scans then were coregistered with planning scans (and associated dose maps)more » using the demons deformable registration algorithm and two variants of the Fraunhofer MEVIS algorithm (“Fast” and “EMPIRE10”). Landmark points in each pretherapy scan were automatically mapped to the planning scan using the displacement vector field output from each of the three algorithms. The Euclidean distance between manually and automatically mapped landmark points (d{sub E}) and the absolute difference in planned dose (|ΔD|) were calculated. Using regression modeling, |ΔD| was modeled as a function of d{sub E}, dose (D), dose standard deviation (SD{sub dose}) in an eight-pixel neighborhood, and the registration algorithm used. Results: Over 1400 landmark point pairs were identified, with 58–93 (median: 84) points identified per patient. Average |ΔD| across patients was 3.5 Gy (range: 0.9–10.6 Gy). Registration accuracy was highest using the Fraunhofer MEVIS EMPIRE10 algorithm, with an average d{sub E} across patients of 5.2 mm (compared with >7 mm for the other two algorithms). Consequently, average |ΔD| was also lowest using the Fraunhofer MEVIS EMPIRE10 algorithm. |ΔD| increased significantly as a function of d{sub E} (0.42 Gy/mm), D (0.05 Gy/Gy), SD{sub dose} (1.4 Gy/Gy), and the algorithm used (≤1 Gy). Conclusions: An average error of <4 Gy in radiation dose was introduced when points were mapped between CT scan pairs using deformable registration, with the majority of points yielding dose-mapping error <2 Gy (approximately 3% of the total prescribed dose). Registration accuracy was highest using the Fraunhofer MEVIS EMPIRE10 algorithm, resulting in the smallest errors in mapped dose. Dose differences following registration increased significantly with increasing spatial registration errors, dose, and dose gradient (i.e., SD{sub dose}). This model provides a measurement of the uncertainty in the radiation dose when points are mapped between serial CT scans through deformable registration.« less

Application of Consider Covariance to the Extended Kalman Filter

NASA Technical Reports Server (NTRS)

Lundberg, John B.

1996-01-01

The extended Kalman filter (EKF) is the basis for many applications of filtering theory to real-time problems where estimates of the state of a dynamical system are to be computed based upon some set of observations. The form of the EKF may vary somewhat from one application to another, but the fundamental principles are typically unchanged among these various applications. As is the case in many filtering applications, models of the dynamical system (differential equations describing the state variables) and models of the relationship between the observations and the state variables are created. These models typically employ a set of constants whose values are established my means of theory or experimental procedure. Since the estimates of the state are formed assuming that the models are perfect, any modeling errors will affect the accuracy of the computed estimates. Note that the modeling errors may be errors of commission (errors in terms included in the model) or omission (errors in terms excluded from the model). Consequently, it becomes imperative when evaluating the performance of real-time filters to evaluate the effect of modeling errors on the estimates of the state.

Intrinsic fluorescence of protein in turbid media using empirical relation based on Monte Carlo lookup table

NASA Astrophysics Data System (ADS)

Einstein, Gnanatheepam; Udayakumar, Kanniyappan; Aruna, Prakasarao; Ganesan, Singaravelu

2017-03-01

Fluorescence of Protein has been widely used in diagnostic oncology for characterizing cellular metabolism. However, the intensity of fluorescence emission is affected due to the absorbers and scatterers in tissue, which may lead to error in estimating exact protein content in tissue. Extraction of intrinsic fluorescence from measured fluorescence has been achieved by different methods. Among them, Monte Carlo based method yields the highest accuracy for extracting intrinsic fluorescence. In this work, we have attempted to generate a lookup table for Monte Carlo simulation of fluorescence emission by protein. Furthermore, we fitted the generated lookup table using an empirical relation. The empirical relation between measured and intrinsic fluorescence is validated using tissue phantom experiments. The proposed relation can be used for estimating intrinsic fluorescence of protein for real-time diagnostic applications and thereby improving the clinical interpretation of fluorescence spectroscopic data.

Modified retrieval algorithm for three types of precipitation distribution using x-band synthetic aperture radar

NASA Astrophysics Data System (ADS)

Xie, Yanan; Zhou, Mingliang; Pan, Dengke

2017-10-01

The forward-scattering model is introduced to describe the response of normalized radar cross section (NRCS) of precipitation with synthetic aperture radar (SAR). Since the distribution of near-surface rainfall is related to the rate of near-surface rainfall and horizontal distribution factor, a retrieval algorithm called modified regression empirical and model-oriented statistical (M-M) based on the volterra integration theory is proposed. Compared with the model-oriented statistical and volterra integration (MOSVI) algorithm, the biggest difference is that the M-M algorithm is based on the modified regression empirical algorithm rather than the linear regression formula to retrieve the value of near-surface rainfall rate. Half of the empirical parameters are reduced in the weighted integral work and a smaller average relative error is received while the rainfall rate is less than 100 mm/h. Therefore, the algorithm proposed in this paper can obtain high-precision rainfall information.

Using snowball sampling method with nurses to understand medication administration errors.

PubMed

Sheu, Shuh-Jen; Wei, Ien-Lan; Chen, Ching-Huey; Yu, Shu; Tang, Fu-In

2009-02-01

We aimed to encourage nurses to release information about drug administration errors to increase understanding of error-related circumstances and to identify high-alert situations. Drug administration errors represent the majority of medication errors, but errors are underreported. Effective ways are lacking to encourage nurses to actively report errors. Snowball sampling was conducted to recruit participants. A semi-structured questionnaire was used to record types of error, hospital and nurse backgrounds, patient consequences, error discovery mechanisms and reporting rates. Eighty-five nurses participated, reporting 328 administration errors (259 actual, 69 near misses). Most errors occurred in medical surgical wards of teaching hospitals, during day shifts, committed by nurses working fewer than two years. Leading errors were wrong drugs and doses, each accounting for about one-third of total errors. Among 259 actual errors, 83.8% resulted in no adverse effects; among remaining 16.2%, 6.6% had mild consequences and 9.6% had serious consequences (severe reaction, coma, death). Actual errors and near misses were discovered mainly through double-check procedures by colleagues and nurses responsible for errors; reporting rates were 62.5% (162/259) vs. 50.7% (35/69) and only 3.5% (9/259) vs. 0% (0/69) were disclosed to patients and families. High-alert situations included administration of 15% KCl, insulin and Pitocin; using intravenous pumps; and implementation of cardiopulmonary resuscitation (CPR). Snowball sampling proved to be an effective way to encourage nurses to release details concerning medication errors. Using empirical data, we identified high-alert situations. Strategies for reducing drug administration errors by nurses are suggested. Survey results suggest that nurses should double check medication administration in known high-alert situations. Nursing management can use snowball sampling to gather error details from nurses in a non-reprimanding atmosphere, helping to establish standard operational procedures for known high-alert situations.

Unbiased Estimation of Refractive State of Aberrated Eyes

PubMed Central

Martin, Jesson; Vasudevan, Balamurali; Himebaugh, Nikole; Bradley, Arthur; Thibos, Larry

2011-01-01

To identify unbiased methods for estimating the target vergence required to maximize visual acuity based on wavefront aberration measurements. Experiments were designed to minimize the impact of confounding factors that have hampered previous research. Objective wavefront refractions and subjective acuity refractions were obtained for the same monochromatic wavelength. Accommodation and pupil fluctuations were eliminated by cycloplegia. Unbiased subjective refractions that maximize visual acuity for high contrast letters were performed with a computer controlled forced choice staircase procedure, using 0.125 diopter steps of defocus. All experiments were performed for two pupil diameters (3mm and 6mm). As reported in the literature, subjective refractive error does not change appreciably when the pupil dilates. For 3 mm pupils most metrics yielded objective refractions that were about 0.1D more hyperopic than subjective acuity refractions. When pupil diameter increased to 6 mm, this bias changed in the myopic direction and the variability between metrics also increased. These inaccuracies were small compared to the precision of the measurements, which implies that most metrics provided unbiased estimates of refractive state for medium and large pupils. A variety of image quality metrics may be used to determine ocular refractive state for monochromatic (635nm) light, thereby achieving accurate results without the need for empirical correction factors. PMID:21777601

An empirical approach to improving tidal predictions using recent real-time tide gauge data

NASA Astrophysics Data System (ADS)

Hibbert, Angela; Royston, Samantha; Horsburgh, Kevin J.; Leach, Harry

2014-05-01

Classical harmonic methods of tidal prediction are often problematic in estuarine environments due to the distortion of tidal fluctuations in shallow water, which results in a disparity between predicted and observed sea levels. This is of particular concern in the Bristol Channel, where the error associated with tidal predictions is potentially greater due to an unusually large tidal range of around 12m. As such predictions are fundamental to the short-term forecasting of High Water (HW) extremes, it is vital that alternative solutions are found. In a pilot study, using a year-long observational sea level record from the Port of Avonmouth in the Bristol Channel, the UK National Tidal and Sea Level Facility (NTSLF) tested the potential for reducing tidal prediction errors, using three alternatives to the Harmonic Method of tidal prediction. The three methods evaluated were (1) the use of Artificial Neural Network (ANN) models, (2) the Species Concordance technique and (3) a simple empirical procedure for correcting Harmonic Method High Water predictions based upon a few recent observations (referred to as the Empirical Correction Method). This latter method was then successfully applied to sea level records from an additional 42 of the 45 tide gauges that comprise the UK Tide Gauge Network. Consequently, it is to be incorporated into the operational systems of the UK Coastal Monitoring and Forecasting Partnership in order to improve short-term sea level predictions for the UK and in particular, the accurate estimation of HW extremes.

Generalized Bootstrap Method for Assessment of Uncertainty in Semivariogram Inference

USGS Publications Warehouse

Olea, R.A.; Pardo-Iguzquiza, E.

2011-01-01

The semivariogram and its related function, the covariance, play a central role in classical geostatistics for modeling the average continuity of spatially correlated attributes. Whereas all methods are formulated in terms of the true semivariogram, in practice what can be used are estimated semivariograms and models based on samples. A generalized form of the bootstrap method to properly model spatially correlated data is used to advance knowledge about the reliability of empirical semivariograms and semivariogram models based on a single sample. Among several methods available to generate spatially correlated resamples, we selected a method based on the LU decomposition and used several examples to illustrate the approach. The first one is a synthetic, isotropic, exhaustive sample following a normal distribution, the second example is also a synthetic but following a non-Gaussian random field, and a third empirical sample consists of actual raingauge measurements. Results show wider confidence intervals than those found previously by others with inadequate application of the bootstrap. Also, even for the Gaussian example, distributions for estimated semivariogram values and model parameters are positively skewed. In this sense, bootstrap percentile confidence intervals, which are not centered around the empirical semivariogram and do not require distributional assumptions for its construction, provide an achieved coverage similar to the nominal coverage. The latter cannot be achieved by symmetrical confidence intervals based on the standard error, regardless if the standard error is estimated from a parametric equation or from bootstrap. ?? 2010 International Association for Mathematical Geosciences.

Quantum mechanics and reality: An interpretation of Everett's theory

NASA Astrophysics Data System (ADS)

Lehner, Christoph Albert

The central part of Everett's formulation of quantum mechanics is a quantum mechanical model of memory and of observation as the recording of information in a memory. To use this model as an answer to the measurement problem, Everett has to assume that a conscious observer can be in a superposition of such memory states and be unaware of it. This assumption has puzzled generations of readers. The fundamental aim of this dissertation is to find a set of simpler assumptions which are sufficient to show that Everett's model is empirically adequate. I argue that Everett's model needs three assumptions to account for the process of observation: an assumption of decoherence of observers as quantum mechanical systems; an assumption of supervenience of mental states (qualities) over quantum mechanical properties; and an assumption about the interpretation of quantum mechanical states in general: quantum mechanical states describe ensembles of states of affairs coexisting in the same system. I argue that the only plausible understanding of such ensembles is as ensembles of possibilities, and that all standard no-collapse interpretations agree in this reading of quantum mechanical states. Their differences can be understood as different theories about what marks the real state within this ensemble, and Everett's theory as the claim that no additional 'mark of reality' is necessary. Using the three assumptions, I argue that introspection cannot determine the objective quantum mechanical state of an observer. Rather, the introspective qualities of a quantum mechanical state can be represented by a (classical) statistical ensemble of subjective states. An analysis of these subjective states and their dynamics leads to the conclusion that they suffice to give empirically correct predictions. The argument for the empirical adequacy of the subjective state entails that knowledge of the objective quantum mechanical state is impossible in principle. Empirical reality for a conscious observer is not described by the objective state, but by a Everettian relative state conditional on the subjective state, and no theoretical 'mark of reality' is necessary for this concept of reality. I compare the resulting concept of reality to Kant's distinction between empirical and transcendental reality.

Improving the quality of marine geophysical track line data: Along-track analysis

NASA Astrophysics Data System (ADS)

Chandler, Michael T.; Wessel, Paul

2008-02-01

We have examined 4918 track line geophysics cruises archived at the U.S. National Geophysical Data Center (NGDC) using comprehensive error checking methods. Each cruise was checked for observation outliers, excessive gradients, metadata consistency, and general agreement with satellite altimetry-derived gravity and predicted bathymetry grids. Thresholds for error checking were determined empirically through inspection of histograms for all geophysical values, gradients, and differences with gridded data sampled along ship tracks. Robust regression was used to detect systematic scale and offset errors found by comparing ship bathymetry and free-air anomalies to the corresponding values from global grids. We found many recurring error types in the NGDC archive, including poor navigation, inappropriately scaled or offset data, excessive gradients, and extended offsets in depth and gravity when compared to global grids. While ˜5-10% of bathymetry and free-air gravity records fail our conservative tests, residual magnetic errors may exceed twice this proportion. These errors hinder the effective use of the data and may lead to mistakes in interpretation. To enable the removal of gross errors without over-writing original cruise data, we developed an errata system that concisely reports all errors encountered in a cruise. With such errata files, scientists may share cruise corrections, thereby preventing redundant processing. We have implemented these quality control methods in the modified MGD77 supplement to the Generic Mapping Tools software suite.

Visualizing Coastal Erosion, Overwash and Coastal Flooding in New England

NASA Astrophysics Data System (ADS)

Young Morse, R.; Shyka, T.

2017-12-01

Powerful East Coast storms and their associated storm tides and large, battering waves can lead to severe coastal change through erosion and re-deposition of beach sediment. The United States Geological Survey (USGS) has modeled such potential for geological response using a storm-impact scale that compares predicted elevations of hurricane-induced water levels and associated wave action to known elevations of coastal topography. The resulting storm surge and wave run-up hindcasts calculate dynamic surf zone collisions with dune structures using discrete regime categories of; "collision" (dune erosion), "overwash" and "inundation". The National Weather Service (NWS) recently began prototyping this empirical technique under the auspices of the North Atlantic Regional Team (NART). Real-time erosion and inundation forecasts were expanded to include both tropical and extra-tropical cyclones along vulnerable beaches (hotspots) on the New England coast. Preliminary results showed successful predictions of impact during hurricane Sandy and several intense Nor'easters. The forecasts were verified using observational datasets, including "ground truth" reports from Emergency Managers and storm-based, dune profile measurements organized through a Maine Sea Grant partnership. In an effort to produce real-time visualizations of this forecast output, the Northeastern Regional Association of Coastal Ocean Observing Systems (NERACOOS) and the Gulf of Maine Research Institute (GMRI) partnered with NART to create graphical products of wave run-up levels for each New England "hotspot". The resulting prototype system updates the forecasts twice daily and allows users the ability to adjust atmospheric and sea state input into the calculations to account for model errors and forecast uncertainty. This talk will provide an overview of the empirical wave run-up calculations, the system used to produce forecast output and a demonstration of the new web based tool.

Optimal Design of Low-Density SNP Arrays for Genomic Prediction: Algorithm and Applications.

PubMed

Wu, Xiao-Lin; Xu, Jiaqi; Feng, Guofei; Wiggans, George R; Taylor, Jeremy F; He, Jun; Qian, Changsong; Qiu, Jiansheng; Simpson, Barry; Walker, Jeremy; Bauck, Stewart

2016-01-01

Low-density (LD) single nucleotide polymorphism (SNP) arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for the optimal design of LD SNP chips. A multiple-objective, local optimization (MOLO) algorithm was developed for design of optimal LD SNP chips that can be imputed accurately to medium-density (MD) or high-density (HD) SNP genotypes for genomic prediction. The objective function facilitates maximization of non-gap map length and system information for the SNP chip, and the latter is computed either as locus-averaged (LASE) or haplotype-averaged Shannon entropy (HASE) and adjusted for uniformity of the SNP distribution. HASE performed better than LASE with ≤1,000 SNPs, but required considerably more computing time. Nevertheless, the differences diminished when >5,000 SNPs were selected. Optimization was accomplished conditionally on the presence of SNPs that were obligated to each chromosome. The frame location of SNPs on a chip can be either uniform (evenly spaced) or non-uniform. For the latter design, a tunable empirical Beta distribution was used to guide location distribution of frame SNPs such that both ends of each chromosome were enriched with SNPs. The SNP distribution on each chromosome was finalized through the objective function that was locally and empirically maximized. This MOLO algorithm was capable of selecting a set of approximately evenly-spaced and highly-informative SNPs, which in turn led to increased imputation accuracy compared with selection solely of evenly-spaced SNPs. Imputation accuracy increased with LD chip size, and imputation error rate was extremely low for chips with ≥3,000 SNPs. Assuming that genotyping or imputation error occurs at random, imputation error rate can be viewed as the upper limit for genomic prediction error. Our results show that about 25% of imputation error rate was propagated to genomic prediction in an Angus population. The utility of this MOLO algorithm was also demonstrated in a real application, in which a 6K SNP panel was optimized conditional on 5,260 obligatory SNP selected based on SNP-trait association in U.S. Holstein animals. With this MOLO algorithm, both imputation error rate and genomic prediction error rate were minimal.

Computational modeling of bedform evolution in rivers with implications for predictions of flood stage and bed evolution

USGS Publications Warehouse

Nelson, Jonathan M.; Shimizu, Yasuyuki; Giri, Sanjay; McDonald, Richard R.

2010-01-01

Uncertainties in flood stage prediction and bed evolution in rivers are frequently associated with the evolution of bedforms over a hydrograph. For the case of flood prediction, the evolution of the bedforms may alter the effective bed roughness, so predictions of stage and velocity based on assuming bedforms retain the same size and shape over a hydrograph will be incorrect. These same effects will produce errors in the prediction of the sediment transport and bed evolution, but in this latter case the errors are typically larger, as even small errors in the prediction of bedform form drag can make very large errors in predicting the rates of sediment motion and the associated erosion and deposition. In situations where flows change slowly, it may be possible to use empirical results that relate bedform morphology to roughness and effective form drag to avoid these errors; but in many cases where the bedforms evolve rapidly and are in disequilibrium with the instantaneous flow, these empirical methods cannot be accurately applied. Over the past few years, computational models for bedform development, migration, and adjustment to varying flows have been developed and tested with a variety of laboratory and field data. These models, which are based on detailed multidimensional flow modeling incorporating large eddy simulation, appear to be capable of predicting bedform dimensions during steady flows as well as their time dependence during discharge variations. In the work presented here, models of this type are used to investigate the impacts of bedform on stage and bed evolution in rivers during flood hydrographs. The method is shown to reproduce hysteresis in rating curves as well as other more subtle effects in the shape of flood waves. Techniques for combining the bedform evolution models with larger-scale models for river reach flow, sediment transport, and bed evolution are described and used to show the importance of including dynamic bedform effects in river modeling. For example calculations for a flood on the Kootenai River, errors of almost 1m in predicted stage and errors of about a factor of two in the predicted maximum depths of erosion can be attributed to bedform evolution. Thus, treating bedforms explicitly in flood and bed evolution models can decrease uncertainty and increase the accuracy of predictions.

Optimal Design of Low-Density SNP Arrays for Genomic Prediction: Algorithm and Applications

PubMed Central

Wu, Xiao-Lin; Xu, Jiaqi; Feng, Guofei; Wiggans, George R.; Taylor, Jeremy F.; He, Jun; Qian, Changsong; Qiu, Jiansheng; Simpson, Barry; Walker, Jeremy; Bauck, Stewart

2016-01-01

Low-density (LD) single nucleotide polymorphism (SNP) arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for the optimal design of LD SNP chips. A multiple-objective, local optimization (MOLO) algorithm was developed for design of optimal LD SNP chips that can be imputed accurately to medium-density (MD) or high-density (HD) SNP genotypes for genomic prediction. The objective function facilitates maximization of non-gap map length and system information for the SNP chip, and the latter is computed either as locus-averaged (LASE) or haplotype-averaged Shannon entropy (HASE) and adjusted for uniformity of the SNP distribution. HASE performed better than LASE with ≤1,000 SNPs, but required considerably more computing time. Nevertheless, the differences diminished when >5,000 SNPs were selected. Optimization was accomplished conditionally on the presence of SNPs that were obligated to each chromosome. The frame location of SNPs on a chip can be either uniform (evenly spaced) or non-uniform. For the latter design, a tunable empirical Beta distribution was used to guide location distribution of frame SNPs such that both ends of each chromosome were enriched with SNPs. The SNP distribution on each chromosome was finalized through the objective function that was locally and empirically maximized. This MOLO algorithm was capable of selecting a set of approximately evenly-spaced and highly-informative SNPs, which in turn led to increased imputation accuracy compared with selection solely of evenly-spaced SNPs. Imputation accuracy increased with LD chip size, and imputation error rate was extremely low for chips with ≥3,000 SNPs. Assuming that genotyping or imputation error occurs at random, imputation error rate can be viewed as the upper limit for genomic prediction error. Our results show that about 25% of imputation error rate was propagated to genomic prediction in an Angus population. The utility of this MOLO algorithm was also demonstrated in a real application, in which a 6K SNP panel was optimized conditional on 5,260 obligatory SNP selected based on SNP-trait association in U.S. Holstein animals. With this MOLO algorithm, both imputation error rate and genomic prediction error rate were minimal. PMID:27583971

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

PubMed

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

2013-11-01

Underlying systems factors have been seen to be crucial contributors to the occurrence of medication errors. By understanding the causes of these errors, the most appropriate interventions can be designed and implemented to minimise their occurrence. This study aimed to systematically review and appraise empirical evidence relating to the causes of medication administration errors (MAEs) in hospital settings. Nine electronic databases (MEDLINE, EMBASE, International Pharmaceutical Abstracts, ASSIA, PsycINFO, British Nursing Index, CINAHL, Health Management Information Consortium and Social Science Citations Index) were searched between 1985 and May 2013. Inclusion and exclusion criteria were applied to identify eligible publications through title analysis followed by abstract and then full text examination. English language publications reporting empirical data on causes of MAEs were included. Reference lists of included articles and relevant review papers were hand searched for additional studies. Studies were excluded if they did not report data on specific MAEs, used accounts from individuals not directly involved in the MAE concerned or were presented as conference abstracts with insufficient detail. A total of 54 unique studies were included. Causes of MAEs were categorised according to Reason's model of accident causation. Studies were assessed to determine relevance to the research question and how likely the results were to reflect the potential underlying causes of MAEs based on the method(s) used. Slips and lapses were the most commonly reported unsafe acts, followed by knowledge-based mistakes and deliberate violations. Error-provoking conditions influencing administration errors included inadequate written communication (prescriptions, documentation, transcription), problems with medicines supply and storage (pharmacy dispensing errors and ward stock management), high perceived workload, problems with ward-based equipment (access, functionality), patient factors (availability, acuity), staff health status (fatigue, stress) and interruptions/distractions during drug administration. Few studies sought to determine the causes of intravenous MAEs. A number of latent pathway conditions were less well explored, including local working culture and high-level managerial decisions. Causes were often described superficially; this may be related to the use of quantitative surveys and observation methods in many studies, limited use of established error causation frameworks to analyse data and a predominant focus on issues other than the causes of MAEs among studies. As only English language publications were included, some relevant studies may have been missed. Limited evidence from studies included in this systematic review suggests that MAEs are influenced by multiple systems factors, but if and how these arise and interconnect to lead to errors remains to be fully determined. Further research with a theoretical focus is needed to investigate the MAE causation pathway, with an emphasis on ensuring interventions designed to minimise MAEs target recognised underlying causes of errors to maximise their impact.

GEOS-C altimeter attitude bias error correction. [gate-tracking radar

NASA Technical Reports Server (NTRS)

Marini, J. W.

1974-01-01

A pulse-limited split-gate-tracking radar altimeter was flown on Skylab and will be used aboard GEOS-C. If such an altimeter were to employ a hypothetical isotropic antenna, the altimeter output would be independent of spacecraft orientation. To reduce power requirements the gain of the altimeter antenna proposed is increased to the point where its beamwidth is only a few degrees. The gain of the antenna consequently varies somewhat over the pulse-limited illuminated region of the ocean below the altimeter, and the altimeter output varies with antenna orientation. The error introduced into the altimeter data is modeled empirically, but close agreements with the expected errors was not realized. The attitude error effects expected with the GEOS-C altimeter are modelled using a form suggested by an analytical derivation. The treatment is restricted to the case of a relatively smooth sea, where the height of the ocean waves are small relative to the spatial length (pulse duration times speed of light) of the transmitted pulse.

Relative-Error-Covariance Algorithms

NASA Technical Reports Server (NTRS)

Bierman, Gerald J.; Wolff, Peter J.

1991-01-01

Two algorithms compute error covariance of difference between optimal estimates, based on data acquired during overlapping or disjoint intervals, of state of discrete linear system. Provides quantitative measure of mutual consistency or inconsistency of estimates of states. Relative-error-covariance concept applied, to determine degree of correlation between trajectories calculated from two overlapping sets of measurements and construct real-time test of consistency of state estimates based upon recently acquired data.

Quantum-state comparison and discrimination

NASA Astrophysics Data System (ADS)

Hayashi, A.; Hashimoto, T.; Horibe, M.

2018-05-01

We investigate the performance of discrimination strategy in the comparison task of known quantum states. In the discrimination strategy, one infers whether or not two quantum systems are in the same state on the basis of the outcomes of separate discrimination measurements on each system. In some cases with more than two possible states, the optimal strategy in minimum-error comparison is that one should infer the two systems are in different states without any measurement, implying that the discrimination strategy performs worse than the trivial "no-measurement" strategy. We present a sufficient condition for this phenomenon to happen. For two pure states with equal prior probabilities, we determine the optimal comparison success probability with an error margin, which interpolates the minimum-error and unambiguous comparison. We find that the discrimination strategy is not optimal except for the minimum-error case.

Method, apparatus and system to compensate for drift by physically unclonable function circuitry

DOEpatents

Hamlet, Jason

2016-11-22

Techniques and mechanisms to detect and compensate for drift by a physically uncloneable function (PUF) circuit. In an embodiment, first state information is registered as reference information to be made available for subsequent evaluation of whether drift by PUF circuitry has occurred. The first state information is associated with a first error correction strength. The first state information is generated based on a first PUF value output by the PUF circuitry. In another embodiment, second state information is determined based on a second PUF value that is output by the PUF circuitry. An evaluation of whether drift has occurred is performed based on the first state information and the second state information, the evaluation including determining whether a threshold error correction strength is exceeded concurrent with a magnitude of error being less than the first error correction strength.

Optimal post-experiment estimation of poorly modeled dynamic systems

NASA Technical Reports Server (NTRS)

Mook, D. Joseph

1988-01-01

Recently, a novel strategy for post-experiment state estimation of discretely-measured dynamic systems has been developed. The method accounts for errors in the system dynamic model equations in a more general and rigorous manner than do filter-smoother algorithms. The dynamic model error terms do not require the usual process noise assumptions of zero-mean, symmetrically distributed random disturbances. Instead, the model error terms require no prior assumptions other than piecewise continuity. The resulting state estimates are more accurate than filters for applications in which the dynamic model error clearly violates the typical process noise assumptions, and the available measurements are sparse and/or noisy. Estimates of the dynamic model error, in addition to the states, are obtained as part of the solution of a two-point boundary value problem, and may be exploited for numerous reasons. In this paper, the basic technique is explained, and several example applications are given. Included among the examples are both state estimation and exploitation of the model error estimates.

Defining near misses: towards a sharpened definition based on empirical data about error handling processes.

PubMed

Kessels-Habraken, Marieke; Van der Schaaf, Tjerk; De Jonge, Jan; Rutte, Christel

2010-05-01

Medical errors in health care still occur frequently. Unfortunately, errors cannot be completely prevented and 100% safety can never be achieved. Therefore, in addition to error reduction strategies, health care organisations could also implement strategies that promote timely error detection and correction. Reporting and analysis of so-called near misses - usually defined as incidents without adverse consequences for patients - are necessary to gather information about successful error recovery mechanisms. This study establishes the need for a clearer and more consistent definition of near misses to enable large-scale reporting and analysis in order to obtain such information. Qualitative incident reports and interviews were collected on four units of two Dutch general hospitals. Analysis of the 143 accompanying error handling processes demonstrated that different incident types each provide unique information about error handling. Specifically, error handling processes underlying incidents that did not reach the patient differed significantly from those of incidents that reached the patient, irrespective of harm, because of successful countermeasures that had been taken after error detection. We put forward two possible definitions of near misses and argue that, from a practical point of view, the optimal definition may be contingent on organisational context. Both proposed definitions could yield large-scale reporting of near misses. Subsequent analysis could enable health care organisations to improve the safety and quality of care proactively by (1) eliminating failure factors before real accidents occur, (2) enhancing their ability to intercept errors in time, and (3) improving their safety culture. Copyright 2010 Elsevier Ltd. All rights reserved.

Efficient error correction for next-generation sequencing of viral amplicons

PubMed Central

2012-01-01

Background Next-generation sequencing allows the analysis of an unprecedented number of viral sequence variants from infected patients, presenting a novel opportunity for understanding virus evolution, drug resistance and immune escape. However, sequencing in bulk is error prone. Thus, the generated data require error identification and correction. Most error-correction methods to date are not optimized for amplicon analysis and assume that the error rate is randomly distributed. Recent quality assessment of amplicon sequences obtained using 454-sequencing showed that the error rate is strongly linked to the presence and size of homopolymers, position in the sequence and length of the amplicon. All these parameters are strongly sequence specific and should be incorporated into the calibration of error-correction algorithms designed for amplicon sequencing. Results In this paper, we present two new efficient error correction algorithms optimized for viral amplicons: (i) k-mer-based error correction (KEC) and (ii) empirical frequency threshold (ET). Both were compared to a previously published clustering algorithm (SHORAH), in order to evaluate their relative performance on 24 experimental datasets obtained by 454-sequencing of amplicons with known sequences. All three algorithms show similar accuracy in finding true haplotypes. However, KEC and ET were significantly more efficient than SHORAH in removing false haplotypes and estimating the frequency of true ones. Conclusions Both algorithms, KEC and ET, are highly suitable for rapid recovery of error-free haplotypes obtained by 454-sequencing of amplicons from heterogeneous viruses. The implementations of the algorithms and data sets used for their testing are available at: http://alan.cs.gsu.edu/NGS/?q=content/pyrosequencing-error-correction-algorithm PMID:22759430

Efficient error correction for next-generation sequencing of viral amplicons.

PubMed

Skums, Pavel; Dimitrova, Zoya; Campo, David S; Vaughan, Gilberto; Rossi, Livia; Forbi, Joseph C; Yokosawa, Jonny; Zelikovsky, Alex; Khudyakov, Yury

2012-06-25

Next-generation sequencing allows the analysis of an unprecedented number of viral sequence variants from infected patients, presenting a novel opportunity for understanding virus evolution, drug resistance and immune escape. However, sequencing in bulk is error prone. Thus, the generated data require error identification and correction. Most error-correction methods to date are not optimized for amplicon analysis and assume that the error rate is randomly distributed. Recent quality assessment of amplicon sequences obtained using 454-sequencing showed that the error rate is strongly linked to the presence and size of homopolymers, position in the sequence and length of the amplicon. All these parameters are strongly sequence specific and should be incorporated into the calibration of error-correction algorithms designed for amplicon sequencing. In this paper, we present two new efficient error correction algorithms optimized for viral amplicons: (i) k-mer-based error correction (KEC) and (ii) empirical frequency threshold (ET). Both were compared to a previously published clustering algorithm (SHORAH), in order to evaluate their relative performance on 24 experimental datasets obtained by 454-sequencing of amplicons with known sequences. All three algorithms show similar accuracy in finding true haplotypes. However, KEC and ET were significantly more efficient than SHORAH in removing false haplotypes and estimating the frequency of true ones. Both algorithms, KEC and ET, are highly suitable for rapid recovery of error-free haplotypes obtained by 454-sequencing of amplicons from heterogeneous viruses.The implementations of the algorithms and data sets used for their testing are available at: http://alan.cs.gsu.edu/NGS/?q=content/pyrosequencing-error-correction-algorithm.

Modeling the probability distribution of positional errors incurred by residential address geocoding.

PubMed

Zimmerman, Dale L; Fang, Xiangming; Mazumdar, Soumya; Rushton, Gerard

2007-01-10

The assignment of a point-level geocode to subjects' residences is an important data assimilation component of many geographic public health studies. Often, these assignments are made by a method known as automated geocoding, which attempts to match each subject's address to an address-ranged street segment georeferenced within a streetline database and then interpolate the position of the address along that segment. Unfortunately, this process results in positional errors. Our study sought to model the probability distribution of positional errors associated with automated geocoding and E911 geocoding. Positional errors were determined for 1423 rural addresses in Carroll County, Iowa as the vector difference between each 100%-matched automated geocode and its true location as determined by orthophoto and parcel information. Errors were also determined for 1449 60%-matched geocodes and 2354 E911 geocodes. Huge (> 15 km) outliers occurred among the 60%-matched geocoding errors; outliers occurred for the other two types of geocoding errors also but were much smaller. E911 geocoding was more accurate (median error length = 44 m) than 100%-matched automated geocoding (median error length = 168 m). The empirical distributions of positional errors associated with 100%-matched automated geocoding and E911 geocoding exhibited a distinctive Greek-cross shape and had many other interesting features that were not capable of being fitted adequately by a single bivariate normal or t distribution. However, mixtures of t distributions with two or three components fit the errors very well. Mixtures of bivariate t distributions with few components appear to be flexible enough to fit many positional error datasets associated with geocoding, yet parsimonious enough to be feasible for nascent applications of measurement-error methodology to spatial epidemiology.

Distinct Regions within Medial Prefrontal Cortex Process Pain and Cognition

PubMed Central

Jahn, Andrew; Nee, Derek Evan; Alexander, William H.

2016-01-01

Neuroimaging studies of the medial prefrontal cortex (mPFC) suggest that the dorsal anterior cingulate cortex (dACC) region is responsive to a wide variety of stimuli and psychological states, such as pain, cognitive control, and prediction error (PE). In contrast, a recent meta-analysis argues that the dACC is selective for pain, whereas the supplementary motor area (SMA) and pre-SMA are specifically associated with higher-level cognitive processes (Lieberman and Eisenberger, 2015). To empirically test this claim, we manipulated effects of pain, conflict, and PE in a single experiment using human subjects. We observed a robust dorsal-ventral dissociation within the mPFC with cognitive effects of PE and conflict overlapping dorsally and pain localized more ventrally. Classification of subjects based on the presence or absence of a paracingulate sulcus showed that PE effects extended across the dorsal area of the dACC and into the pre-SMA. These results begin to resolve recent controversies by showing the following: (1) the mPFC includes dissociable regions for pain and cognitive processing; and (2) meta-analyses are correct in localizing cognitive effects to the dACC, although these effects extend to the pre-SMA as well. These results both provide evidence distinguishing between different theories of mPFC function and highlight the importance of taking individual anatomical variability into account when conducting empirical studies of the mPFC. SIGNIFICANCE STATEMENT Decades of neuroimaging research have shown the mPFC to represent a wide variety of stimulus processing and cognitive states. However, recently it has been argued whether distinct regions of the mPFC separately process pain and cognitive phenomena. To address this controversy, this study directly compared pain and cognitive processes within subjects. We found a double dissociation within the mPFC with pain localized ventral to the cingulate sulcus and cognitive effects localized more dorsally within the dACC and spreading into the pre-supplementary motor area. This provides empirical evidence to help resolve the current debate about the functional architecture of the mPFC. PMID:27807031

MPI Runtime Error Detection with MUST: Advances in Deadlock Detection

DOE PAGES

Hilbrich, Tobias; Protze, Joachim; Schulz, Martin; ...

2013-01-01

The widely used Message Passing Interface (MPI) is complex and rich. As a result, application developers require automated tools to avoid and to detect MPI programming errors. We present the Marmot Umpire Scalable Tool (MUST) that detects such errors with significantly increased scalability. We present improvements to our graph-based deadlock detection approach for MPI, which cover future MPI extensions. Our enhancements also check complex MPI constructs that no previous graph-based detection approach handled correctly. Finally, we present optimizations for the processing of MPI operations that reduce runtime deadlock detection overheads. Existing approaches often require ( p ) analysis time permore » MPI operation, for p processes. We empirically observe that our improvements lead to sub-linear or better analysis time per operation for a wide range of real world applications.« less

Pattern placement errors: application of in-situ interferometer-determined Zernike coefficients in determining printed image deviations

NASA Astrophysics Data System (ADS)

Roberts, William R.; Gould, Christopher J.; Smith, Adlai H.; Rebitz, Ken

2000-08-01

Several ideas have recently been presented which attempt to measure and predict lens aberrations for new low k1 imaging systems. Abbreviated sets of Zernike coefficients have been produced and used to predict Across Chip Linewidth Variation. Empirical use of the wavefront aberrations can now be used in commercially available lithography simulators to predict pattern distortion and placement errors. Measurement and Determination of Zernike coefficients has been a significant effort of many. However the use of this data has generally been limited to matching lenses or picking best fit lense pairs. We will use wavefront aberration data collected using the Litel InspecStep in-situ Interferometer as input data for Prolith/3D to model and predict pattern placement errors and intrafield overlay variation. Experiment data will be collected and compared to the simulated predictions.

Differential sea-state bias: A case study using TOPEX/POSEIDON data

NASA Technical Reports Server (NTRS)

Stewart, Robert H.; Devalla, B.

1994-01-01

We used selected data from the NASA altimeter TOPEX/POSEIDON to calculate differences in range measured by the C and Ku-band altimeters when the satellite overflew 5 to 15 m waves late at night. The range difference is due to free electrons in the ionosphere and to errors in sea-state bias. For the selected data the ionospheric influence on Ku range is less than 2 cm. Any difference in range over short horizontal distances is due only to a small along-track variability of the ionosphere and to errors in calculating the differential sea-state bias. We find that there is a barely detectable error in the bias in the geophysical data records. The wave-induced error in the ionospheric correction is less than 0.2% of significant wave height. The equivalent error in differential range is less than 1% of wave height. Errors in the differential sea-state bias calculations appear to be small even for extreme wave heights that greatly exceed the conditions on which the bias is based. The results also improved our confidence in the sea-state bias correction used for calculating the geophysical data records. Any error in the correction must influence Ku and C-band ranges almost equally.

Empirical radio propagation model for DTV applied to non-homogeneous paths and different climates using machine learning techniques.

PubMed

Gomes, Igor Ruiz; Gomes, Cristiane Ruiz; Gomes, Herminio Simões; Cavalcante, Gervásio Protásio Dos Santos

2018-01-01

The establishment and improvement of transmission systems rely on models that take into account, (among other factors), the geographical features of the region, as these can lead to signal degradation. This is particularly important in Brazil, where there is a great diversity of scenery and climates. This article proposes an outdoor empirical radio propagation model for Ultra High Frequency (UHF) band, that estimates received power values that can be applied to non-homogeneous paths and different climates, this last being of an innovative character for the UHF band. Different artificial intelligence techniques were chosen on a theoretical and computational basis and made it possible to introduce, organize and describe quantitative and qualitative data quickly and efficiently, and thus determine the received power in a wide range of settings and climates. The proposed model was applied to a city in the Amazon region with heterogeneous paths, wooded urban areas and fractions of freshwater among other factors. Measurement campaigns were conducted to obtain data signals from two digital TV stations in the metropolitan area of the city of Belém, in the State of Pará, to design, compare and validate the model. The results are consistent since the model shows a clear difference between the two seasons of the studied year and small RMS errors in all the cases studied.

Empirical radio propagation model for DTV applied to non-homogeneous paths and different climates using machine learning techniques

PubMed Central

Gomes, Herminio Simões; Cavalcante, Gervásio Protásio dos Santos

2018-01-01

The establishment and improvement of transmission systems rely on models that take into account, (among other factors), the geographical features of the region, as these can lead to signal degradation. This is particularly important in Brazil, where there is a great diversity of scenery and climates. This article proposes an outdoor empirical radio propagation model for Ultra High Frequency (UHF) band, that estimates received power values that can be applied to non-homogeneous paths and different climates, this last being of an innovative character for the UHF band. Different artificial intelligence techniques were chosen on a theoretical and computational basis and made it possible to introduce, organize and describe quantitative and qualitative data quickly and efficiently, and thus determine the received power in a wide range of settings and climates. The proposed model was applied to a city in the Amazon region with heterogeneous paths, wooded urban areas and fractions of freshwater among other factors. Measurement campaigns were conducted to obtain data signals from two digital TV stations in the metropolitan area of the city of Belém, in the State of Pará, to design, compare and validate the model. The results are consistent since the model shows a clear difference between the two seasons of the studied year and small RMS errors in all the cases studied. PMID:29596503

Dynamical influences on thermospheric composition: implications for semi-empirical models

NASA Astrophysics Data System (ADS)

Sutton, E. K.; Solomon, S. C.

2014-12-01

The TIE-GCM was recently augmented to include helium and argon, two approximately inert species that can be used as tracers of dynamics in the thermosphere. The former species is treated as a major species due to its large abundance near the upper boundary. The effects of exospheric transport are also included in order to simulate realistic seasonal and latitudinal helium distributions. The latter species is treated as a classical minor species, imparting absolutely no forces on the background atmosphere. In this study, we examine the interplay of the various dynamical terms - i.e. background circulation, molecular and Eddy diffusion - as they drive departures from the distributions that would be expected under the assumption of diffusive equilibrium. As this has implications on the formulation of all empirical thermospheric models, we use this understanding to address the following questions: (1) how do errors caused by the assumption of diffusive equilibrium manifest within empirical models of the thermosphere? and (2) where and when does an empirical model's output disagree with its underlying datasets due to the inherent limitations of said model's formulation?

Syllabification of Final Consonant Clusters: A Salient Pronunciation Problem of Kurdish EFL Learners

ERIC Educational Resources Information Center

Keshavarz, Mohammad Hossein

2017-01-01

While there is a plethora of research on pronunciation problems of EFL learners with different L1 backgrounds, published empirical studies on syllabification errors of Iraqi Kurdish EFL learners are scarce. Therefore, to contribute to this line of research, the present study set out to investigate difficulties of this group of learners in the…

A Quantitative Study of the Impact of an Empirically Validated Empathy Training Program on Pre-Med Students

ERIC Educational Resources Information Center

Nonnenkamp, Donna J.

2013-01-01

Medical educators recognize the need for empathetic physicians, and empathy has been considered to be extremely important in medical education. Research has shown that empathy can lead to positive patient outcomes, greater patient satisfaction, and compliance, lower malpractice litigation, reduced cost of care and fewer medical errors. The purpose…

Implementing an Equilibrium Law Teaching Sequence for Secondary School Students to Learn Chemical Equilibrium

ERIC Educational Resources Information Center

Ghirardi, Marco; Marchetti, Fabio; Pettinari, Claudio; Regis, Alberto; Roletto, Ezio

2015-01-01

A didactic sequence is proposed for the teaching of chemical equilibrium law. In this approach, we have avoided the kinetic derivation and the thermodynamic justification of the equilibrium constant. The equilibrium constant expression is established empirically by a trial-and-error approach. Additionally, students learn to use the criterion of…

Effects of Covariance Heterogeneity on Three Procedures for Analyzing Multivariate Repeated Measures Designs.

ERIC Educational Resources Information Center

Vallejo, Guillermo; Fidalgo, Angel; Fernandez, Paula

2001-01-01

Estimated empirical Type I error rate and power rate for three procedures for analyzing multivariate repeated measures designs: (1) the doubly multivariate model; (2) the Welch-James multivariate solution (H. Keselman, M. Carriere, a nd L. Lix, 1993); and (3) the multivariate version of the modified Brown-Forsythe procedure (M. Brown and A.…

Turkish Language and Literature Education in Turkey (Brief History-Problems-Recommendations)

ERIC Educational Resources Information Center

Beyreli, Latif

2009-01-01

Language and literature education in Turkey has searched its way through a variety of trials and errors since 1923, when the education heritage inherited from the Ottoman Empire was rebuilt upon a contemporary and laic foundation, and established upon modern foundations in 2005 with the assistance of a variety of curricula used after a long…

An Old Problem with a New Solution, Raising Classical Questions: A Commentary on Humphry

ERIC Educational Resources Information Center

Heene, Moritz

2011-01-01

Humphry (this issue) deserves credit for drawing attention to the long-neglected fact that differences in item discrimination parameters are often due to empirical factors and not the product of random error components. In doing so, Humphry offers a psychometrically elegant, coherent, and practically important new model that is more flexible while…

Perceived Social Support and Subjective States in Urban Adolescent Girls.

ERIC Educational Resources Information Center

Procidano, Mary E.; And Others

While prospective investigations of social support, coping, and stress are accumulating, there is relatively little empirical knowledge regarding how these variables are related to each other among adolescents, and virtually no empirical knowledge regarding their relationship to subjective states in that population. This study examined the…

Foreign Language Research in Cross-Cultural Perspective. Volume 2.

ERIC Educational Resources Information Center

de Bot, Kees, Ed.; And Others

Papers from a conference on empirical research on foreign language instruction in Europe and the United States include: "Foreign Language Instruction and Second Language Acquisition Research in the United States" (Charles A. Fergurson, Thom Huebner); "Empirical Foreign Language Research in Europe" (Theo van Els, Kees de Bot,…

A Novel Hybrid Data-Driven Model for Daily Land Surface Temperature Forecasting Using Long Short-Term Memory Neural Network Based on Ensemble Empirical Mode Decomposition

PubMed Central

Zhang, Xike; Zhang, Qiuwen; Zhang, Gui; Nie, Zhiping; Gui, Zifan; Que, Huafei

2018-01-01

Daily land surface temperature (LST) forecasting is of great significance for application in climate-related, agricultural, eco-environmental, or industrial studies. Hybrid data-driven prediction models using Ensemble Empirical Mode Composition (EEMD) coupled with Machine Learning (ML) algorithms are useful for achieving these purposes because they can reduce the difficulty of modeling, require less history data, are easy to develop, and are less complex than physical models. In this article, a computationally simple, less data-intensive, fast and efficient novel hybrid data-driven model called the EEMD Long Short-Term Memory (LSTM) neural network, namely EEMD-LSTM, is proposed to reduce the difficulty of modeling and to improve prediction accuracy. The daily LST data series from the Mapoling and Zhijiang stations in the Dongting Lake basin, central south China, from 1 January 2014 to 31 December 2016 is used as a case study. The EEMD is firstly employed to decompose the original daily LST data series into many Intrinsic Mode Functions (IMFs) and a single residue item. Then, the Partial Autocorrelation Function (PACF) is used to obtain the number of input data sample points for LSTM models. Next, the LSTM models are constructed to predict the decompositions. All the predicted results of the decompositions are aggregated as the final daily LST. Finally, the prediction performance of the hybrid EEMD-LSTM model is assessed in terms of the Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), Pearson Correlation Coefficient (CC) and Nash-Sutcliffe Coefficient of Efficiency (NSCE). To validate the hybrid data-driven model, the hybrid EEMD-LSTM model is compared with the Recurrent Neural Network (RNN), LSTM and Empirical Mode Decomposition (EMD) coupled with RNN, EMD-LSTM and EEMD-RNN models, and their comparison results demonstrate that the hybrid EEMD-LSTM model performs better than the other five models. The scatterplots of the predicted results of the six models versus the original daily LST data series show that the hybrid EEMD-LSTM model is superior to the other five models. It is concluded that the proposed hybrid EEMD-LSTM model in this study is a suitable tool for temperature forecasting. PMID:29883381

A Novel Hybrid Data-Driven Model for Daily Land Surface Temperature Forecasting Using Long Short-Term Memory Neural Network Based on Ensemble Empirical Mode Decomposition.

PubMed

Zhang, Xike; Zhang, Qiuwen; Zhang, Gui; Nie, Zhiping; Gui, Zifan; Que, Huafei

2018-05-21

Daily land surface temperature (LST) forecasting is of great significance for application in climate-related, agricultural, eco-environmental, or industrial studies. Hybrid data-driven prediction models using Ensemble Empirical Mode Composition (EEMD) coupled with Machine Learning (ML) algorithms are useful for achieving these purposes because they can reduce the difficulty of modeling, require less history data, are easy to develop, and are less complex than physical models. In this article, a computationally simple, less data-intensive, fast and efficient novel hybrid data-driven model called the EEMD Long Short-Term Memory (LSTM) neural network, namely EEMD-LSTM, is proposed to reduce the difficulty of modeling and to improve prediction accuracy. The daily LST data series from the Mapoling and Zhijaing stations in the Dongting Lake basin, central south China, from 1 January 2014 to 31 December 2016 is used as a case study. The EEMD is firstly employed to decompose the original daily LST data series into many Intrinsic Mode Functions (IMFs) and a single residue item. Then, the Partial Autocorrelation Function (PACF) is used to obtain the number of input data sample points for LSTM models. Next, the LSTM models are constructed to predict the decompositions. All the predicted results of the decompositions are aggregated as the final daily LST. Finally, the prediction performance of the hybrid EEMD-LSTM model is assessed in terms of the Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), Pearson Correlation Coefficient (CC) and Nash-Sutcliffe Coefficient of Efficiency (NSCE). To validate the hybrid data-driven model, the hybrid EEMD-LSTM model is compared with the Recurrent Neural Network (RNN), LSTM and Empirical Mode Decomposition (EMD) coupled with RNN, EMD-LSTM and EEMD-RNN models, and their comparison results demonstrate that the hybrid EEMD-LSTM model performs better than the other five models. The scatterplots of the predicted results of the six models versus the original daily LST data series show that the hybrid EEMD-LSTM model is superior to the other five models. It is concluded that the proposed hybrid EEMD-LSTM model in this study is a suitable tool for temperature forecasting.

Certified dual-corrected radiation patterns of phased antenna arrays by offline–online order reduction of finite-element models

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

Sommer, A., E-mail: a.sommer@lte.uni-saarland.de; Farle, O., E-mail: o.farle@lte.uni-saarland.de; Dyczij-Edlinger, R., E-mail: edlinger@lte.uni-saarland.de

2015-10-15

This paper presents a fast numerical method for computing certified far-field patterns of phased antenna arrays over broad frequency bands as well as wide ranges of steering and look angles. The proposed scheme combines finite-element analysis, dual-corrected model-order reduction, and empirical interpolation. To assure the reliability of the results, improved a posteriori error bounds for the radiated power and directive gain are derived. Both the reduced-order model and the error-bounds algorithm feature offline–online decomposition. A real-world example is provided to demonstrate the efficiency and accuracy of the suggested approach.

Applying EVM to Satellite on Ground and In-Orbit Testing - Better Data in Less Time

NASA Technical Reports Server (NTRS)

Peters, Robert; Lebbink, Elizabeth-Klein; Lee, Victor; Model, Josh; Wezalis, Robert; Taylor, John

2008-01-01

Using Error Vector Magnitude (EVM) in satellite integration and test allows rapid verification of the Bit Error Rate (BER) performance of a satellite link and is particularly well suited to measurement of low bit rate satellite links where it can result in a major reduction in test time (about 3 weeks per satellite for the Geosynchronous Operational Environmental Satellite [GOES] satellites during ground test) and can provide diagnostic information. Empirical techniques developed to predict BER performance from EVM measurements and lessons learned about applying these techniques during GOES N, O, and P integration test and post launch testing, are discussed.

Error-trellis Syndrome Decoding Techniques for Convolutional Codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1984-01-01

An error-trellis syndrome decoding technique for convolutional codes is developed. This algorithm is then applied to the entire class of systematic convolutional codes and to the high-rate, Wyner-Ash convolutional codes. A special example of the one-error-correcting Wyner-Ash code, a rate 3/4 code, is treated. The error-trellis syndrome decoding method applied to this example shows in detail how much more efficient syndrome decoding is than Viterbi decoding if applied to the same problem. For standard Viterbi decoding, 64 states are required, whereas in the example only 7 states are needed. Also, within the 7 states required for decoding, many fewer transitions are needed between the states.

Error-trellis syndrome decoding techniques for convolutional codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1985-01-01

An error-trellis syndrome decoding technique for convolutional codes is developed. This algorithm is then applied to the entire class of systematic convolutional codes and to the high-rate, Wyner-Ash convolutional codes. A special example of the one-error-correcting Wyner-Ash code, a rate 3/4 code, is treated. The error-trellis syndrome decoding method applied to this example shows in detail how much more efficient syndrome decordig is than Viterbi decoding if applied to the same problem. For standard Viterbi decoding, 64 states are required, whereas in the example only 7 states are needed. Also, within the 7 states required for decoding, many fewer transitions are needed between the states.

xEMD procedures as a data - Assisted filtering method

NASA Astrophysics Data System (ADS)

Machrowska, Anna; Jonak, Józef

2018-01-01

The article presents the possibility of using Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD), Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Improved Complete Ensemble Empirical Mode Decomposition (ICEEMD) algorithms for mechanical system condition monitoring applications. There were presented the results of the xEMD procedures used for vibration signals of system in different states of wear.

Experimental magic state distillation for fault-tolerant quantum computing.

PubMed

Souza, Alexandre M; Zhang, Jingfu; Ryan, Colm A; Laflamme, Raymond

2011-01-25

Any physical quantum device for quantum information processing (QIP) is subject to errors in implementation. In order to be reliable and efficient, quantum computers will need error-correcting or error-avoiding methods. Fault-tolerance achieved through quantum error correction will be an integral part of quantum computers. Of the many methods that have been discovered to implement it, a highly successful approach has been to use transversal gates and specific initial states. A critical element for its implementation is the availability of high-fidelity initial states, such as |0〉 and the 'magic state'. Here, we report an experiment, performed in a nuclear magnetic resonance (NMR) quantum processor, showing sufficient quantum control to improve the fidelity of imperfect initial magic states by distilling five of them into one with higher fidelity.

State estimation for autopilot control of small unmanned aerial vehicles in windy conditions

NASA Astrophysics Data System (ADS)

Poorman, David Paul

The use of small unmanned aerial vehicles (UAVs) both in the military and civil realms is growing. This is largely due to the proliferation of inexpensive sensors and the increase in capability of small computers that has stemmed from the personal electronic device market. Methods for performing accurate state estimation for large scale aircraft have been well known and understood for decades, which usually involve a complex array of expensive high accuracy sensors. Performing accurate state estimation for small unmanned aircraft is a newer area of study and often involves adapting known state estimation methods to small UAVs. State estimation for small UAVs can be more difficult than state estimation for larger UAVs due to small UAVs employing limited sensor suites due to cost, and the fact that small UAVs are more susceptible to wind than large aircraft. The purpose of this research is to evaluate the ability of existing methods of state estimation for small UAVs to accurately capture the states of the aircraft that are necessary for autopilot control of the aircraft in a Dryden wind field. The research begins by showing which aircraft states are necessary for autopilot control in Dryden wind. Then two state estimation methods that employ only accelerometer, gyro, and GPS measurements are introduced. The first method uses assumptions on aircraft motion to directly solve for attitude information and smooth GPS data, while the second method integrates sensor data to propagate estimates between GPS measurements and then corrects those estimates with GPS information. The performance of both methods is analyzed with and without Dryden wind, in straight and level flight, in a coordinated turn, and in a wings level ascent. It is shown that in zero wind, the first method produces significant steady state attitude errors in both a coordinated turn and in a wings level ascent. In Dryden wind, it produces large noise on the estimates for its attitude states, and has a non-zero mean error that increases when gyro bias is increased. The second method is shown to not exhibit any steady state error in the tested scenarios that is inherent to its design. The second method can correct for attitude errors that arise from both integration error and gyro bias states, but it suffers from lack of attitude error observability. The attitude errors are shown to be more observable in wind, but increased integration error in wind outweighs the increase in attitude corrections that such increased observability brings, resulting in larger attitude errors in wind. Overall, this work highlights many technical deficiencies of both of these methods of state estimation that could be improved upon in the future to enhance state estimation for small UAVs in windy conditions.

Galaxy–galaxy lensing estimators and their covariance properties

DOE PAGES

Singh, Sukhdeep; Mandelbaum, Rachel; Seljak, Uros; ...

2017-07-21

Here, we study the covariance properties of real space correlation function estimators – primarily galaxy–shear correlations, or galaxy–galaxy lensing – using SDSS data for both shear catalogues and lenses (specifically the BOSS LOWZ sample). Using mock catalogues of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the lens density field instead of the lens overdensity field. While the measurement using the lens densitymore » field is unbiased (in the absence of systematics), its error is significantly larger due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the overdensity, we find that the errors are dominated by the shape noise and lens clustering, which empirically estimated covariances (jackknife and standard deviation across mocks) that are consistent with theoretical estimates, and that both the connected parts of the four-point function and the supersample covariance can be neglected for the current levels of noise. While the trade-off between different terms in the covariance depends on the survey configuration (area, source number density), the diagnostics that we use in this work should be useful for future works to test their empirically determined covariances.« less

Galaxy–galaxy lensing estimators and their covariance properties

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

Singh, Sukhdeep; Mandelbaum, Rachel; Seljak, Uros

Here, we study the covariance properties of real space correlation function estimators – primarily galaxy–shear correlations, or galaxy–galaxy lensing – using SDSS data for both shear catalogues and lenses (specifically the BOSS LOWZ sample). Using mock catalogues of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the lens density field instead of the lens overdensity field. While the measurement using the lens densitymore » field is unbiased (in the absence of systematics), its error is significantly larger due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the overdensity, we find that the errors are dominated by the shape noise and lens clustering, which empirically estimated covariances (jackknife and standard deviation across mocks) that are consistent with theoretical estimates, and that both the connected parts of the four-point function and the supersample covariance can be neglected for the current levels of noise. While the trade-off between different terms in the covariance depends on the survey configuration (area, source number density), the diagnostics that we use in this work should be useful for future works to test their empirically determined covariances.« less

Error estimates for (semi-)empirical dispersion terms and large biomacromolecules.

PubMed

Korth, Martin

2013-10-14

The first-principles modeling of biomaterials has made tremendous advances over the last few years with the ongoing growth of computing power and impressive developments in the application of density functional theory (DFT) codes to large systems. One important step forward was the development of dispersion corrections for DFT methods, which account for the otherwise neglected dispersive van der Waals (vdW) interactions. Approaches at different levels of theory exist, with the most often used (semi-)empirical ones based on pair-wise interatomic C6R(-6) terms. Similar terms are now also used in connection with semiempirical QM (SQM) methods and density functional tight binding methods (SCC-DFTB). Their basic structure equals the attractive term in Lennard-Jones potentials, common to most force field approaches, but they usually use some type of cutoff function to make the mixing of the (long-range) dispersion term with the already existing (short-range) dispersion and exchange-repulsion effects from the electronic structure theory methods possible. All these dispersion approximations were found to perform accurately for smaller systems, but error estimates for larger systems are very rare and completely missing for really large biomolecules. We derive such estimates for the dispersion terms of DFT, SQM and MM methods using error statistics for smaller systems and dispersion contribution estimates for the PDBbind database of protein-ligand interactions. We find that dispersion terms will usually not be a limiting factor for reaching chemical accuracy, though some force fields and large ligand sizes are problematic.

Galaxy-galaxy lensing estimators and their covariance properties

NASA Astrophysics Data System (ADS)

Singh, Sukhdeep; Mandelbaum, Rachel; Seljak, Uroš; Slosar, Anže; Vazquez Gonzalez, Jose

2017-11-01

We study the covariance properties of real space correlation function estimators - primarily galaxy-shear correlations, or galaxy-galaxy lensing - using SDSS data for both shear catalogues and lenses (specifically the BOSS LOWZ sample). Using mock catalogues of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the lens density field instead of the lens overdensity field. While the measurement using the lens density field is unbiased (in the absence of systematics), its error is significantly larger due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the overdensity, we find that the errors are dominated by the shape noise and lens clustering, which empirically estimated covariances (jackknife and standard deviation across mocks) that are consistent with theoretical estimates, and that both the connected parts of the four-point function and the supersample covariance can be neglected for the current levels of noise. While the trade-off between different terms in the covariance depends on the survey configuration (area, source number density), the diagnostics that we use in this work should be useful for future works to test their empirically determined covariances.

Relative importance and utility of positive worker states: a review and empirical examination.

PubMed

Steele, John P; Rupayana, Disha D; Mills, Maura J; Smith, Michael R; Wefald, Andrew; Downey, Ronald G

2012-01-01

Our purpose was to identity the unique contribution, relative importance, and utility of positive worker states. Using Luthans et al.'s (2007) five positive organizational behavior criteria, a variety of positive worker states were reviewed and then empirically tested to establish if they met these criteria. Data were collected from 724 restaurant employees. Positive worker states included: job involvement, perceived organizational support, engagement, and vigor. Criteria were self-reported performance, customer service, turnover intention, satisfaction, and quality of life. Our review indicated consistency between predictor adequacy of meeting the criteria and their empirical relationship with key outcomes. This research found the positive worker states to be independent constructs that had differential effects depending on the focused outcome. Regression and relative weights analyses showed involvement was a weak predictor of outcomes, while perceived organizational support was the most consistent predictor. Vigor was most useful when predicting job performance. Quality of life was poorly explained.

Two States Mapping Based Time Series Neural Network Model for Compensation Prediction Residual Error

NASA Astrophysics Data System (ADS)

Jung, Insung; Koo, Lockjo; Wang, Gi-Nam

2008-11-01

The objective of this paper was to design a model of human bio signal data prediction system for decreasing of prediction error using two states mapping based time series neural network BP (back-propagation) model. Normally, a lot of the industry has been applied neural network model by training them in a supervised manner with the error back-propagation algorithm for time series prediction systems. However, it still has got a residual error between real value and prediction result. Therefore, we designed two states of neural network model for compensation residual error which is possible to use in the prevention of sudden death and metabolic syndrome disease such as hypertension disease and obesity. We determined that most of the simulation cases were satisfied by the two states mapping based time series prediction model. In particular, small sample size of times series were more accurate than the standard MLP model.

Software Would Largely Automate Design of Kalman Filter

NASA Technical Reports Server (NTRS)

Chuang, Jason C. H.; Negast, William J.

2005-01-01

Embedded Navigation Filter Automatic Designer (ENFAD) is a computer program being developed to automate the most difficult tasks in designing embedded software to implement a Kalman filter in a navigation system. The most difficult tasks are selection of error states of the filter and tuning of filter parameters, which are timeconsuming trial-and-error tasks that require expertise and rarely yield optimum results. An optimum selection of error states and filter parameters depends on navigation-sensor and vehicle characteristics, and on filter processing time. ENFAD would include a simulation module that would incorporate all possible error states with respect to a given set of vehicle and sensor characteristics. The first of two iterative optimization loops would vary the selection of error states until the best filter performance was achieved in Monte Carlo simulations. For a fixed selection of error states, the second loop would vary the filter parameter values until an optimal performance value was obtained. Design constraints would be satisfied in the optimization loops. Users would supply vehicle and sensor test data that would be used to refine digital models in ENFAD. Filter processing time and filter accuracy would be computed by ENFAD.

Second generation experiments in fault tolerant software

NASA Technical Reports Server (NTRS)

Knight, J. C.

1987-01-01

The purpose of the Multi-Version Software (MVS) experiment is to obtain empirical measurements of the performance of multi-version systems. Twenty version of a program were prepared under reasonably realistic development conditions from the same specifications. The overall structure of the testing environment for the MVS experiment and its status are described. A preliminary version of the control system is described that was implemented for the MVS experiment to allow the experimenter to have control over the details of the testing. The results of an empirical study of error detection using self checks are also presented. The analysis of the checks revealed that there are great differences in the ability of individual programmers to design effective checks.

Determinants of the rate of protein sequence evolution

PubMed Central

Zhang, Jianzhi; Yang, Jian-Rong

2015-01-01

The rate and mechanism of protein sequence evolution have been central questions in evolutionary biology since the 1960s. Although the rate of protein sequence evolution depends primarily on the level of functional constraint, exactly what constitutes functional constraint has remained unclear. The increasing availability of genomic data has allowed for much needed empirical examinations on the nature of functional constraint. These studies found that the evolutionary rate of a protein is predominantly influenced by its expression level rather than functional importance. A combination of theoretical and empirical analyses have identified multiple mechanisms behind these observations and demonstrated a prominent role that selection against errors in molecular and cellular processes plays in protein evolution. PMID:26055156

Mental workload prediction based on attentional resource allocation and information processing.

PubMed

Xiao, Xu; Wanyan, Xiaoru; Zhuang, Damin

2015-01-01

Mental workload is an important component in complex human-machine systems. The limited applicability of empirical workload measures produces the need for workload modeling and prediction methods. In the present study, a mental workload prediction model is built on the basis of attentional resource allocation and information processing to ensure pilots' accuracy and speed in understanding large amounts of flight information on the cockpit display interface. Validation with an empirical study of an abnormal attitude recovery task showed that this model's prediction of mental workload highly correlated with experimental results. This mental workload prediction model provides a new tool for optimizing human factors interface design and reducing human errors.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

The goodness-of-fit indicator, i.e. efficiency criterion, is very important for model calibration. However, recently the knowledge about the goodness-of-fit indicators is all empirical and lacks a theoretical support. Based on the likelihood theory, a unified distance-based goodness-of-fit indicator termed BC-GED model is proposed, which uses the Box-Cox (BC) transformation to remove the heteroscedasticity of model errors and the generalized error distribution (GED) with zero-mean to fit the distribution of model errors after BC. The BC-GED model can unify all recent distance-based goodness-of-fit indicators, and reveals the mean square error (MSE) and the mean absolute error (MAE) that are widely used goodness-of-fit indicators imply statistic assumptions that the model errors follow the Gaussian distribution and the Laplace distribution with zero-mean, respectively. The empirical knowledge about goodness-of-fit indicators can be also easily interpreted by BC-GED model, e.g. the sensitivity to high flow of the goodness-of-fit indicators with large power of model errors results from the low probability of large model error in the assumed distribution of these indicators. In order to assess the effect of the parameters (i.e. the BC transformation parameter λ and the GED kurtosis coefficient β also termed the power of model errors) of BC-GED model on hydrologic model calibration, six cases of BC-GED model were applied in Baocun watershed (East China) with SWAT-WB-VSA model. Comparison of the inferred model parameters and model simulation results among the six indicators demonstrates these indicators can be clearly separated two classes by the GED kurtosis β: β >1 and β ≤ 1. SWAT-WB-VSA calibrated by the class β >1 of distance-based goodness-of-fit indicators captures high flow very well and mimics the baseflow very badly, but it calibrated by the class β ≤ 1 mimics the baseflow very well, because first the larger value of β, the greater emphasis is put on high flow and second the derivative of GED probability density function at zero is zero as β >1, but discontinuous as β ≤ 1, and even infinity as β < 1 with which the maximum likelihood estimation can guarantee the model errors approach zero as well as possible. The BC-GED that estimates the parameters (i.e. λ and β) of BC-GED model as well as hydrologic model parameters is the best distance-based goodness-of-fit indicator because not only the model validation using groundwater levels is very good, but also the model errors fulfill the statistic assumption best. However, in some cases of model calibration with a few observations e.g. calibration of single-event model, for avoiding estimation of the parameters of BC-GED model the MAE i.e. the boundary indicator (β = 1) of the two classes, can replace the BC-GED, because the model validation of MAE is best.

Women's Studies at Empire State College.

ERIC Educational Resources Information Center

Lester, Virginia L.

Because of the unique program of Empire State College, the problem of providing compensatory courses about women and developing a strategy for eventually having them incorporated into the curriculum of a discipline has been avoided. The focus at this college has been taken from the teacher and placed on the student, giving the student the primary…

Equity, Inclusion, and Beyond: Today's Urban Chief Diversity Officer

ERIC Educational Resources Information Center

Hancock, Merodie A.

2018-01-01

This paper, based primarily on the author's perspective as president of SUNY Empire State College, will explore the need for, and means of leveraging, the chief diversity officer's role in creating an equitable and inclusive environment within the distributed world that is Empire State College's "campus" and, specifically, within SUNY…

Wavelet modeling and prediction of the stability of states: the Roman Empire and the European Union

NASA Astrophysics Data System (ADS)

Yaroshenko, Tatyana Y.; Krysko, Dmitri V.; Dobriyan, Vitalii; Zhigalov, Maksim V.; Vos, Hendrik; Vandenabeele, Peter; Krysko, Vadim A.

2015-09-01

How can the stability of a state be quantitatively determined and its future stability predicted? The rise and collapse of empires and states is very complex, and it is exceedingly difficult to understand and predict it. Existing theories are usually formulated as verbal models and, consequently, do not yield sharply defined, quantitative prediction that can be unambiguously validated with data. Here we describe a model that determines whether the state is in a stable or chaotic condition and predicts its future condition. The central model, which we test, is that growth and collapse of states is reflected by the changes of their territories, populations and budgets. The model was simulated within the historical societies of the Roman Empire (400 BC to 400 AD) and the European Union (1957-2007) by using wavelets and analysis of the sign change of the spectrum of Lyapunov exponents. The model matches well with the historical events. During wars and crises, the state becomes unstable; this is reflected in the wavelet analysis by a significant increase in the frequency ω (t) and wavelet coefficients W (ω, t) and the sign of the largest Lyapunov exponent becomes positive, indicating chaos. We successfully reconstructed and forecasted time series in the Roman Empire and the European Union by applying artificial neural network. The proposed model helps to quantitatively determine and forecast the stability of a state.

Measurement-device-independent quantum key distribution with source state errors and statistical fluctuation

NASA Astrophysics Data System (ADS)

Jiang, Cong; Yu, Zong-Wen; Wang, Xiang-Bin

2017-03-01

We show how to calculate the secure final key rate in the four-intensity decoy-state measurement-device-independent quantum key distribution protocol with both source errors and statistical fluctuations with a certain failure probability. Our results rely only on the range of only a few parameters in the source state. All imperfections in this protocol have been taken into consideration without assuming any specific error patterns of the source.

Prediction of winter wheat high yield from remote sensing based model: application in United States and Ukraine

NASA Astrophysics Data System (ADS)

Franch, B.; Vermote, E.; Roger, J. C.; Skakun, S.; Becker-Reshef, I.; Justice, C. O.

2017-12-01

Accurate and timely crop yield forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. In Becker-Reshef et al. (2010) and Franch et al. (2015) we developed an empirical generalized model for forecasting winter wheat yield. It is based on the relationship between the Normalized Difference Vegetation Index (NDVI) at the peak of the growing season and the Growing Degree Day (GDD) information extracted from NCEP/NCAR reanalysis data. These methods were applied to MODIS CMG data in Ukraine, the US and China with errors around 10%. However, the NDVI is saturated for yield values higher than 4 MT/ha. As a consequence, the model had to be re-calibrated in each country and the validation of the national yields showed low correlation coefficients. In this study we present a new model based on the extrapolation of the pure wheat signal (100% of wheat within the pixel) from MODIS data at 1km resolution and using the Difference Vegetation Index (DVI). The model has been applied to monitor the national yield of winter wheat in the United States and Ukraine from 2001 to 2016.

A global/local affinity graph for image segmentation.

PubMed

Xiaofang Wang; Yuxing Tang; Masnou, Simon; Liming Chen

2015-04-01

Construction of a reliable graph capturing perceptual grouping cues of an image is fundamental for graph-cut based image segmentation methods. In this paper, we propose a novel sparse global/local affinity graph over superpixels of an input image to capture both short- and long-range grouping cues, and thereby enabling perceptual grouping laws, including proximity, similarity, continuity, and to enter in action through a suitable graph-cut algorithm. Moreover, we also evaluate three major visual features, namely, color, texture, and shape, for their effectiveness in perceptual segmentation and propose a simple graph fusion scheme to implement some recent findings from psychophysics, which suggest combining these visual features with different emphases for perceptual grouping. In particular, an input image is first oversegmented into superpixels at different scales. We postulate a gravitation law based on empirical observations and divide superpixels adaptively into small-, medium-, and large-sized sets. Global grouping is achieved using medium-sized superpixels through a sparse representation of superpixels' features by solving a ℓ0-minimization problem, and thereby enabling continuity or propagation of local smoothness over long-range connections. Small- and large-sized superpixels are then used to achieve local smoothness through an adjacent graph in a given feature space, and thus implementing perceptual laws, for example, similarity and proximity. Finally, a bipartite graph is also introduced to enable propagation of grouping cues between superpixels of different scales. Extensive experiments are carried out on the Berkeley segmentation database in comparison with several state-of-the-art graph constructions. The results show the effectiveness of the proposed approach, which outperforms state-of-the-art graphs using four different objective criteria, namely, the probabilistic rand index, the variation of information, the global consistency error, and the boundary displacement error.

Removing non-urban roads from the National Land Cover Database to create improved urban maps for the United States, 1992-2011

USGS Publications Warehouse

Soulard, Christopher E.; Acevedo, William; Stehman, Stephen V.

2018-01-01

Quantifying change in urban land provides important information to create empirical models examining the effects of human land use. Maps of developed land from the National Land Cover Database (NLCD) of the conterminous United States include rural roads in the developed land class and therefore overestimate the amount of urban land. To better map the urban class and understand how urban lands change over time, we removed rural roads and small patches of rural development from the NLCD developed class and created four wall-to-wall maps (1992, 2001, 2006, and 2011) of urban land. Removing rural roads from the NLCD developed class involved a multi-step filtering process, data fusion using geospatial road and developed land data, and manual editing. Reference data classified as urban or not urban from a stratified random sample was used to assess the accuracy of the 2001 and 2006 urban and NLCD maps. The newly created urban maps had higher overall accuracy (98.7 percent) than the NLCD maps (96.2 percent). More importantly, the urban maps resulted in lower commission error of the urban class (23 percent versus 57 percent for the NLCD in 2006) with the trade-off of slightly inflated omission error (20 percent for the urban map, 16 percent for NLCD in 2006). The removal of approximately 230,000 km2 of rural roads from the NLCD developed class resulted in maps that better characterize the urban footprint. These urban maps are more suited to modeling applications and policy decisions that rely on quantitative and spatially explicit information regarding urban lands.

Performance Monitoring Applied to System Supervision

PubMed Central

Somon, Bertille; Campagne, Aurélie; Delorme, Arnaud; Berberian, Bruno

2017-01-01

Nowadays, automation is present in every aspect of our daily life and has some benefits. Nonetheless, empirical data suggest that traditional automation has many negative performance and safety consequences as it changed task performers into task supervisors. In this context, we propose to use recent insights into the anatomical and neurophysiological substrates of action monitoring in humans, to help further characterize performance monitoring during system supervision. Error monitoring is critical for humans to learn from the consequences of their actions. A wide variety of studies have shown that the error monitoring system is involved not only in our own errors, but also in the errors of others. We hypothesize that the neurobiological correlates of the self-performance monitoring activity can be applied to system supervision. At a larger scale, a better understanding of system supervision may allow its negative effects to be anticipated or even countered. This review is divided into three main parts. First, we assess the neurophysiological correlates of self-performance monitoring and their characteristics during error execution. Then, we extend these results to include performance monitoring and error observation of others or of systems. Finally, we provide further directions in the study of system supervision and assess the limits preventing us from studying a well-known phenomenon: the Out-Of-the-Loop (OOL) performance problem. PMID:28744209

Using APEX to Model Anticipated Human Error: Analysis of a GPS Navigational Aid

NASA Technical Reports Server (NTRS)

VanSelst, Mark; Freed, Michael; Shefto, Michael (Technical Monitor)

1997-01-01

The interface development process can be dramatically improved by predicting design facilitated human error at an early stage in the design process. The approach we advocate is to SIMULATE the behavior of a human agent carrying out tasks with a well-specified user interface, ANALYZE the simulation for instances of human error, and then REFINE the interface or protocol to minimize predicted error. This approach, incorporated into the APEX modeling architecture, differs from past approaches to human simulation in Its emphasis on error rather than e.g. learning rate or speed of response. The APEX model consists of two major components: (1) a powerful action selection component capable of simulating behavior in complex, multiple-task environments; and (2) a resource architecture which constrains cognitive, perceptual, and motor capabilities to within empirically demonstrated limits. The model mimics human errors arising from interactions between limited human resources and elements of the computer interface whose design falls to anticipate those limits. We analyze the design of a hand-held Global Positioning System (GPS) device used for radical and navigational decisions in small yacht recalls. The analysis demonstrates how human system modeling can be an effective design aid, helping to accelerate the process of refining a product (or procedure).

7 CFR 275.23 - Determination of State agency program performance.

Code of Federal Regulations, 2011 CFR

2011-01-01

... NUTRITION SERVICE, DEPARTMENT OF AGRICULTURE FOOD STAMP AND FOOD DISTRIBUTION PROGRAM PERFORMANCE REPORTING... section, the adjusted regressed payment error rate shall be calculated to yield the State agency's payment error rate. The adjusted regressed payment error rate is given by r 1″ + r 2″. (ii) If FNS determines...

Measurement of thermal conductivity and thermal diffusivity using a thermoelectric module

NASA Astrophysics Data System (ADS)

Beltrán-Pitarch, Braulio; Márquez-García, Lourdes; Min, Gao; García-Cañadas, Jorge

2017-04-01

A proof of concept of using a thermoelectric module to measure both thermal conductivity and thermal diffusivity of bulk disc samples at room temperature is demonstrated. The method involves the calculation of the integral area from an impedance spectrum, which empirically correlates with the thermal properties of the sample through an exponential relationship. This relationship was obtained employing different reference materials. The impedance spectroscopy measurements are performed in a very simple setup, comprising a thermoelectric module, which is soldered at its bottom side to a Cu block (heat sink) and thermally connected with the sample at its top side employing thermal grease. Random and systematic errors of the method were calculated for the thermal conductivity (18.6% and 10.9%, respectively) and thermal diffusivity (14.2% and 14.7%, respectively) employing a BCR724 standard reference material. Although errors are somewhat high, the technique could be useful for screening purposes or high-throughput measurements at its current state. This new method establishes a new application for thermoelectric modules as thermal properties sensors. It involves the use of a very simple setup in conjunction with a frequency response analyzer, which provides a low cost alternative to most of currently available apparatus in the market. In addition, impedance analyzers are reliable and widely spread equipment, which facilities the sometimes difficult access to thermal conductivity facilities.

Improving validation methods for molecular diagnostics: application of Bland-Altman, Deming and simple linear regression analyses in assay comparison and evaluation for next-generation sequencing.

PubMed

Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L

2018-02-01

A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R 2 ), using R 2 as the primary metric of assay agreement. However, the use of R 2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Turtle: identifying frequent k-mers with cache-efficient algorithms.

PubMed

Roy, Rajat Shuvro; Bhattacharya, Debashish; Schliep, Alexander

2014-07-15

Counting the frequencies of k-mers in read libraries is often a first step in the analysis of high-throughput sequencing data. Infrequent k-mers are assumed to be a result of sequencing errors. The frequent k-mers constitute a reduced but error-free representation of the experiment, which can inform read error correction or serve as the input to de novo assembly methods. Ideally, the memory requirement for counting should be linear in the number of frequent k-mers and not in the, typically much larger, total number of k-mers in the read library. We present a novel method that balances time, space and accuracy requirements to efficiently extract frequent k-mers even for high-coverage libraries and large genomes such as human. Our method is designed to minimize cache misses in a cache-efficient manner by using a pattern-blocked Bloom filter to remove infrequent k-mers from consideration in combination with a novel sort-and-compact scheme, instead of a hash, for the actual counting. Although this increases theoretical complexity, the savings in cache misses reduce the empirical running times. A variant of method can resort to a counting Bloom filter for even larger savings in memory at the expense of false-negative rates in addition to the false-positive rates common to all Bloom filter-based approaches. A comparison with the state-of-the-art shows reduced memory requirements and running times. The tools are freely available for download at http://bioinformatics.rutgers.edu/Software/Turtle and http://figshare.com/articles/Turtle/791582. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

When Help Becomes Hindrance: Unexpected Errors of Omission and Commission in Eyewitness Memory Resulting from Change Temporal Order at Retrieval?

ERIC Educational Resources Information Center

Dando, Coral J.; Ormerod, Thomas C.; Wilcock, Rachel; Milne, Rebecca

2011-01-01

An experimental mock eyewitness study is reported that compared Free and reverse order recall of an empirically informed scripted crime event. Proponents of reverse order recall suggest it facilitates recovery of script incidental information and increases the total amount of information recalled. However, compared with free recall it was found to…

Selection Devices for User of an Electronic Encyclopedia: An Empirical Comparison of Four Possibilities.

ERIC Educational Resources Information Center

Ostroff, Daniel; Shneiderman, Ben

1988-01-01

Describes a study that measured the speed, error rates, and subjective evaluation of arrow jump keys, a jump mouse, number keys, and a touch screen in an interactive encyclopedia. The results of previous studies are discussed as well as the findings of this study. Improvements in selection devices are suggested. (41 references) (Author/CLB)

The Bauschinger Effect in Autofrettaged Tubes- A Comparison of Models Including the ASME Code

DTIC Science & Technology

1998-06-01

possible error in Division 3 of Section Vm of the ASME Boiler and Pressure Vessel Code . They show that the empirical method used in the code to...Discussion presented by DP Kendall We appreciate the acknowledgement in the Kendall discussion that Division 3 of Section VIII of the ASME Boiler and Pressure Vessel Code may

A three stage sampling model for remote sensing applications

NASA Technical Reports Server (NTRS)

Eisgruber, L. M.

1972-01-01

A conceptual model and an empirical application of the relationship between the manner of selecting observations and its effect on the precision of estimates from remote sensing are reported. This three stage sampling scheme considers flightlines, segments within flightlines, and units within these segments. The error of estimate is dependent on the number of observations in each of the stages.

Spatio-temporal distribution of Oklahoma earthquakes: Exploring relationships using a nearest-neighbor approach: Nearest-neighbor analysis of Oklahoma

DOE PAGES

Vasylkivska, Veronika S.; Huerta, Nicolas J.

2017-06-24

Determining the spatiotemporal characteristics of natural and induced seismic events holds the opportunity to gain new insights into why these events occur. Linking the seismicity characteristics with other geologic, geographic, natural, or anthropogenic factors could help to identify the causes and suggest mitigation strategies that reduce the risk associated with such events. The nearest-neighbor approach utilized in this work represents a practical first step toward identifying statistically correlated clusters of recorded earthquake events. Detailed study of the Oklahoma earthquake catalog’s inherent errors, empirical model parameters, and model assumptions is presented. We found that the cluster analysis results are stable withmore » respect to empirical parameters (e.g., fractal dimension) but were sensitive to epicenter location errors and seismicity rates. Most critically, we show that the patterns in the distribution of earthquake clusters in Oklahoma are primarily defined by spatial relationships between events. This observation is a stark contrast to California (also known for induced seismicity) where a comparable cluster distribution is defined by both spatial and temporal interactions between events. These results highlight the difficulty in understanding the mechanisms and behavior of induced seismicity but provide insights for future work.« less

Spatiotemporal distribution of Oklahoma earthquakes: Exploring relationships using a nearest-neighbor approach

NASA Astrophysics Data System (ADS)

Vasylkivska, Veronika S.; Huerta, Nicolas J.

2017-07-01

Determining the spatiotemporal characteristics of natural and induced seismic events holds the opportunity to gain new insights into why these events occur. Linking the seismicity characteristics with other geologic, geographic, natural, or anthropogenic factors could help to identify the causes and suggest mitigation strategies that reduce the risk associated with such events. The nearest-neighbor approach utilized in this work represents a practical first step toward identifying statistically correlated clusters of recorded earthquake events. Detailed study of the Oklahoma earthquake catalog's inherent errors, empirical model parameters, and model assumptions is presented. We found that the cluster analysis results are stable with respect to empirical parameters (e.g., fractal dimension) but were sensitive to epicenter location errors and seismicity rates. Most critically, we show that the patterns in the distribution of earthquake clusters in Oklahoma are primarily defined by spatial relationships between events. This observation is a stark contrast to California (also known for induced seismicity) where a comparable cluster distribution is defined by both spatial and temporal interactions between events. These results highlight the difficulty in understanding the mechanisms and behavior of induced seismicity but provide insights for future work.

Spatio-temporal distribution of Oklahoma earthquakes: Exploring relationships using a nearest-neighbor approach: Nearest-neighbor analysis of Oklahoma

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

Vasylkivska, Veronika S.; Huerta, Nicolas J.

Determining the spatiotemporal characteristics of natural and induced seismic events holds the opportunity to gain new insights into why these events occur. Linking the seismicity characteristics with other geologic, geographic, natural, or anthropogenic factors could help to identify the causes and suggest mitigation strategies that reduce the risk associated with such events. The nearest-neighbor approach utilized in this work represents a practical first step toward identifying statistically correlated clusters of recorded earthquake events. Detailed study of the Oklahoma earthquake catalog’s inherent errors, empirical model parameters, and model assumptions is presented. We found that the cluster analysis results are stable withmore » respect to empirical parameters (e.g., fractal dimension) but were sensitive to epicenter location errors and seismicity rates. Most critically, we show that the patterns in the distribution of earthquake clusters in Oklahoma are primarily defined by spatial relationships between events. This observation is a stark contrast to California (also known for induced seismicity) where a comparable cluster distribution is defined by both spatial and temporal interactions between events. These results highlight the difficulty in understanding the mechanisms and behavior of induced seismicity but provide insights for future work.« less

Identification of factors which affect the tendency towards and attitudes of emergency unit nurses to make medical errors.

PubMed

Kiymaz, Dilek; Koç, Zeliha

2018-03-01

To determine individual and professional factors affecting the tendency of emergency unit nurses to make medical errors and their attitudes towards these errors in Turkey. Compared with other units, the emergency unit is an environment where there is an increased tendency for making medical errors due to its intensive and rapid pace, noise and complex and dynamic structure. A descriptive cross-sectional study. The study was carried out from 25 July 2014-16 September 2015 with the participation of 284 nurses who volunteered to take part in the study. Data were gathered using the data collection survey for nurses, the Medical Error Tendency Scale and the Medical Error Attitude Scale. It was determined that 40.1% of the nurses previously witnessed medical errors, 19.4% made a medical error in the last year, 17.6% of medical errors were caused by medication errors where the wrong medication was administered in the wrong dose, and none of the nurses filled out a case report form about the medical errors they made. Regarding the factors that caused medical errors in the emergency unit, 91.2% of the nurses stated excessive workload as a cause; 85.1% stated an insufficient number of nurses; and 75.4% stated fatigue, exhaustion and burnout. The study showed that nurses who loved their job were satisfied with their unit and who always worked during day shifts had a lower medical error tendency. It is suggested to consider the following actions: increase awareness about medical errors, organise training to reduce errors in medication administration, develop procedures and protocols specific to the emergency unit health care and create an environment which is not punitive wherein nurses can safely report medical errors. © 2017 John Wiley & Sons Ltd.

Error properties of Argos satellite telemetry locations using least squares and Kalman filtering.

PubMed

Boyd, Janice D; Brightsmith, Donald J

2013-01-01

Study of animal movements is key for understanding their ecology and facilitating their conservation. The Argos satellite system is a valuable tool for tracking species which move long distances, inhabit remote areas, and are otherwise difficult to track with traditional VHF telemetry and are not suitable for GPS systems. Previous research has raised doubts about the magnitude of position errors quoted by the satellite service provider CLS. In addition, no peer-reviewed publications have evaluated the usefulness of the CLS supplied error ellipses nor the accuracy of the new Kalman filtering (KF) processing method. Using transmitters hung from towers and trees in southeastern Peru, we show the Argos error ellipses generally contain <25% of the true locations and therefore do not adequately describe the true location errors. We also find that KF processing does not significantly increase location accuracy. The errors for both LS and KF processing methods were found to be lognormally distributed, which has important repercussions for error calculation, statistical analysis, and data interpretation. In brief, "good" positions (location codes 3, 2, 1, A) are accurate to about 2 km, while 0 and B locations are accurate to about 5-10 km. However, due to the lognormal distribution of the errors, larger outliers are to be expected in all location codes and need to be accounted for in the user's data processing. We evaluate five different empirical error estimates and find that 68% lognormal error ellipses provided the most useful error estimates. Longitude errors are larger than latitude errors by a factor of 2 to 3, supporting the use of elliptical error ellipses. Numerous studies over the past 15 years have also found fault with the CLS-claimed error estimates yet CLS has failed to correct their misleading information. We hope this will be reversed in the near future.

Local Linear Regression for Data with AR Errors.

PubMed

Li, Runze; Li, Yan

2009-07-01

In many statistical applications, data are collected over time, and they are likely correlated. In this paper, we investigate how to incorporate the correlation information into the local linear regression. Under the assumption that the error process is an auto-regressive process, a new estimation procedure is proposed for the nonparametric regression by using local linear regression method and the profile least squares techniques. We further propose the SCAD penalized profile least squares method to determine the order of auto-regressive process. Extensive Monte Carlo simulation studies are conducted to examine the finite sample performance of the proposed procedure, and to compare the performance of the proposed procedures with the existing one. From our empirical studies, the newly proposed procedures can dramatically improve the accuracy of naive local linear regression with working-independent error structure. We illustrate the proposed methodology by an analysis of real data set.

Reduction of Non-uniform Beam Filling Effects by Vertical Decorrelation: Theory and Simulations

NASA Technical Reports Server (NTRS)

Short, David; Nakagawa, Katsuhiro; Iguchi, Toshio

2013-01-01

Algorithms for estimating precipitation rates from spaceborne radar observations of apparent radar reflectivity depend on attenuation correction procedures. The algorithm suite for the Ku-band precipitation radar aboard the Tropical Rainfall Measuring Mission satellite is one such example. The well-known problem of nonuniform beam filling is a source of error in the estimates, especially in regions where intense deep convection occurs. The error is caused by unresolved horizontal variability in precipitation characteristics such as specific attenuation, rain rate, and effective reflectivity factor. This paper proposes the use of vertical decorrelation for correcting the nonuniform beam filling error developed under the assumption of a perfect vertical correlation. Empirical tests conducted using ground-based radar observations in the current simulation study show that decorrelation effects are evident in tilted convective cells. However, the problem of obtaining reasonable estimates of a governing parameter from the satellite data remains unresolved.

Bayesian analysis of stochastic volatility-in-mean model with leverage and asymmetrically heavy-tailed error using generalized hyperbolic skew Student’s t-distribution*

PubMed Central

Leão, William L.; Chen, Ming-Hui

2017-01-01

A stochastic volatility-in-mean model with correlated errors using the generalized hyperbolic skew Student-t (GHST) distribution provides a robust alternative to the parameter estimation for daily stock returns in the absence of normality. An efficient Markov chain Monte Carlo (MCMC) sampling algorithm is developed for parameter estimation. The deviance information, the Bayesian predictive information and the log-predictive score criterion are used to assess the fit of the proposed model. The proposed method is applied to an analysis of the daily stock return data from the Standard & Poor’s 500 index (S&P 500). The empirical results reveal that the stochastic volatility-in-mean model with correlated errors and GH-ST distribution leads to a significant improvement in the goodness-of-fit for the S&P 500 index returns dataset over the usual normal model. PMID:29333210

Hypothesis-Testing Demands Trustworthy Data—A Simulation Approach to Inferential Statistics Advocating the Research Program Strategy

PubMed Central

Krefeld-Schwalb, Antonia; Witte, Erich H.; Zenker, Frank

2018-01-01

In psychology as elsewhere, the main statistical inference strategy to establish empirical effects is null-hypothesis significance testing (NHST). The recent failure to replicate allegedly well-established NHST-results, however, implies that such results lack sufficient statistical power, and thus feature unacceptably high error-rates. Using data-simulation to estimate the error-rates of NHST-results, we advocate the research program strategy (RPS) as a superior methodology. RPS integrates Frequentist with Bayesian inference elements, and leads from a preliminary discovery against a (random) H0-hypothesis to a statistical H1-verification. Not only do RPS-results feature significantly lower error-rates than NHST-results, RPS also addresses key-deficits of a “pure” Frequentist and a standard Bayesian approach. In particular, RPS aggregates underpowered results safely. RPS therefore provides a tool to regain the trust the discipline had lost during the ongoing replicability-crisis. PMID:29740363

Smoothing of the bivariate LOD score for non-normal quantitative traits.

PubMed

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.

Using Computational Cognitive Modeling to Diagnose Possible Sources of Aviation Error

NASA Technical Reports Server (NTRS)

Byrne, M. D.; Kirlik, Alex

2003-01-01

We present a computational model of a closed-loop, pilot-aircraft-visual scene-taxiway system created to shed light on possible sources of taxi error. Creating the cognitive aspects of the model using ACT-R required us to conduct studies with subject matter experts to identify experiential adaptations pilots bring to taxiing. Five decision strategies were found, ranging from cognitively-intensive but precise, to fast, frugal but robust. We provide evidence for the model by comparing its behavior to a NASA Ames Research Center simulation of Chicago O'Hare surface operations. Decision horizons were highly variable; the model selected the most accurate strategy given time available. We found a signature in the simulation data of the use of globally robust heuristics to cope with short decision horizons as revealed by errors occurring most frequently at atypical taxiway geometries or clearance routes. These data provided empirical support for the model.

The effects of missing data on global ozone estimates

NASA Technical Reports Server (NTRS)

Drewry, J. W.; Robbins, J. L.

1981-01-01

The effects of missing data and model truncation on estimates of the global mean, zonal distribution, and global distribution of ozone are considered. It is shown that missing data can introduce biased estimates with errors that are not accounted for in the accuracy calculations of empirical modeling techniques. Data-fill techniques are introduced and used for evaluating error bounds and constraining the estimate in areas of sparse and missing data. It is found that the accuracy of the global mean estimate is more dependent on data distribution than model size. Zonal features can be accurately described by 7th order models over regions of adequate data distribution. Data variance accounted for by higher order models appears to represent climatological features of columnar ozone rather than pure error. Data-fill techniques can prevent artificial feature generation in regions of sparse or missing data without degrading high order estimates over dense data regions.

High-speed photogrammetry system for measuring the kinematics of insect wings

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

Wallace, Iain D.; Lawson, Nicholas J.; Harvey, Andrew R.

2006-06-10

We describe and characterize an experimental system to perform shape measurements on deformable objects using high-speed close-range photogrammetry. The eventual application is to extract the kinematics of several marked points on an insect wing during tethered and hovering flight. We investigate the performance of the system with a small number of views and determine an empirical relation between the mean pixel error of the optimization routine and the position error. Velocity and acceleration are calculated by numerical differencing, and their relation to the position errors is verified. For a field of view of {approx}40mmx40 mm, a rms accuracy of 30more » {mu}m in position, 150 mm/s in velocity, and 750 m/s2 in acceleration at 5000 frames/s is achieved. This accuracy is sufficient to measure the kinematics of hoverfly flight.« less

Hypothesis-Testing Demands Trustworthy Data-A Simulation Approach to Inferential Statistics Advocating the Research Program Strategy.

PubMed

Krefeld-Schwalb, Antonia; Witte, Erich H; Zenker, Frank

2018-01-01

In psychology as elsewhere, the main statistical inference strategy to establish empirical effects is null-hypothesis significance testing (NHST). The recent failure to replicate allegedly well-established NHST-results, however, implies that such results lack sufficient statistical power, and thus feature unacceptably high error-rates. Using data-simulation to estimate the error-rates of NHST-results, we advocate the research program strategy (RPS) as a superior methodology. RPS integrates Frequentist with Bayesian inference elements, and leads from a preliminary discovery against a (random) H 0 -hypothesis to a statistical H 1 -verification. Not only do RPS-results feature significantly lower error-rates than NHST-results, RPS also addresses key-deficits of a "pure" Frequentist and a standard Bayesian approach. In particular, RPS aggregates underpowered results safely. RPS therefore provides a tool to regain the trust the discipline had lost during the ongoing replicability-crisis.

Bayesian analysis of stochastic volatility-in-mean model with leverage and asymmetrically heavy-tailed error using generalized hyperbolic skew Student's t-distribution.

PubMed

Leão, William L; Abanto-Valle, Carlos A; Chen, Ming-Hui

2017-01-01

A stochastic volatility-in-mean model with correlated errors using the generalized hyperbolic skew Student-t (GHST) distribution provides a robust alternative to the parameter estimation for daily stock returns in the absence of normality. An efficient Markov chain Monte Carlo (MCMC) sampling algorithm is developed for parameter estimation. The deviance information, the Bayesian predictive information and the log-predictive score criterion are used to assess the fit of the proposed model. The proposed method is applied to an analysis of the daily stock return data from the Standard & Poor's 500 index (S&P 500). The empirical results reveal that the stochastic volatility-in-mean model with correlated errors and GH-ST distribution leads to a significant improvement in the goodness-of-fit for the S&P 500 index returns dataset over the usual normal model.

The Combined Effects of Measurement Error and Omitting Confounders in the Single-Mediator Model

PubMed Central

Fritz, Matthew S.; Kenny, David A.; MacKinnon, David P.

2016-01-01

Mediation analysis requires a number of strong assumptions be met in order to make valid causal inferences. Failing to account for violations of these assumptions, such as not modeling measurement error or omitting a common cause of the effects in the model, can bias the parameter estimates of the mediated effect. When the independent variable is perfectly reliable, for example when participants are randomly assigned to levels of treatment, measurement error in the mediator tends to underestimate the mediated effect, while the omission of a confounding variable of the mediator to outcome relation tends to overestimate the mediated effect. Violations of these two assumptions often co-occur, however, in which case the mediated effect could be overestimated, underestimated, or even, in very rare circumstances, unbiased. In order to explore the combined effect of measurement error and omitted confounders in the same model, the impact of each violation on the single-mediator model is first examined individually. Then the combined effect of having measurement error and omitted confounders in the same model is discussed. Throughout, an empirical example is provided to illustrate the effect of violating these assumptions on the mediated effect. PMID:27739903

ANALYZING NUMERICAL ERRORS IN DOMAIN HEAT TRANSPORT MODELS USING THE CVBEM.

USGS Publications Warehouse

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.

Dissociating response conflict and error likelihood in anterior cingulate cortex.

PubMed

Yeung, Nick; Nieuwenhuis, Sander

2009-11-18

Neuroimaging studies consistently report activity in anterior cingulate cortex (ACC) in conditions of high cognitive demand, leading to the view that ACC plays a crucial role in the control of cognitive processes. According to one prominent theory, the sensitivity of ACC to task difficulty reflects its role in monitoring for the occurrence of competition, or "conflict," between responses to signal the need for increased cognitive control. However, a contrasting theory proposes that ACC is the recipient rather than source of monitoring signals, and that ACC activity observed in relation to task demand reflects the role of this region in learning about the likelihood of errors. Response conflict and error likelihood are typically confounded, making the theories difficult to distinguish empirically. The present research therefore used detailed computational simulations to derive contrasting predictions regarding ACC activity and error rate as a function of response speed. The simulations demonstrated a clear dissociation between conflict and error likelihood: fast response trials are associated with low conflict but high error likelihood, whereas slow response trials show the opposite pattern. Using the N2 component as an index of ACC activity, an EEG study demonstrated that when conflict and error likelihood are dissociated in this way, ACC activity tracks conflict and is negatively correlated with error likelihood. These findings support the conflict-monitoring theory and suggest that, in speeded decision tasks, ACC activity reflects current task demands rather than the retrospective coding of past performance.

Optical dosimetry probes to validate Monte Carlo and empirical-method-based NIR dose planning in the brain.

PubMed

Verleker, Akshay Prabhu; Shaffer, Michael; Fang, Qianqian; Choi, Mi-Ran; Clare, Susan; Stantz, Keith M

2016-12-01

A three-dimensional photon dosimetry in tissues is critical in designing optical therapeutic protocols to trigger light-activated drug release. The objective of this study is to investigate the feasibility of a Monte Carlo-based optical therapy planning software by developing dosimetry tools to characterize and cross-validate the local photon fluence in brain tissue, as part of a long-term strategy to quantify the effects of photoactivated drug release in brain tumors. An existing GPU-based 3D Monte Carlo (MC) code was modified to simulate near-infrared photon transport with differing laser beam profiles within phantoms of skull bone (B), white matter (WM), and gray matter (GM). A novel titanium-based optical dosimetry probe with isotropic acceptance was used to validate the local photon fluence, and an empirical model of photon transport was developed to significantly decrease execution time for clinical application. Comparisons between the MC and the dosimetry probe measurements were on an average 11.27%, 13.25%, and 11.81% along the illumination beam axis, and 9.4%, 12.06%, 8.91% perpendicular to the beam axis for WM, GM, and B phantoms, respectively. For a heterogeneous head phantom, the measured % errors were 17.71% and 18.04% along and perpendicular to beam axis. The empirical algorithm was validated by probe measurements and matched the MC results (R²0.99), with average % error of 10.1%, 45.2%, and 22.1% relative to probe measurements, and 22.6%, 35.8%, and 21.9% relative to the MC, for WM, GM, and B phantoms, respectively. The simulation time for the empirical model was 6 s versus 8 h for the GPU-based Monte Carlo for a head phantom simulation. These tools provide the capability to develop and optimize treatment plans for optimal release of pharmaceuticals in the treatment of cancer. Future work will test and validate these novel delivery and release mechanisms in vivo.

Assessment of Nitrogen deposition effects and empirical critical loads of Nitrogen for ecoregions of the United States

Treesearch

L.H. Pardo; M.J. Robin-Abbott; C.T., eds. Driscoll

2011-01-01

This report synthesizes current research relating atmospheric nitrogen (N) deposition to effects on terrestrial and aquatic ecosystems in the United States and to identify empirical critical loads for atmospheric N deposition. The report evaluates the following receptors: freshwater diatoms, mycorrhizal fungi and other soil microbes, lichens, herbaceous plants, shrubs...

Development of a simplified flexible pavement design protocol for New York State Department of Transportation based on the AASHTO mechanistic-empirical pavement design guide : final report.

DOT National Transportation Integrated Search

2017-01-01

The New York State Department of Transportation (NYSDOT) has used the AASHTO 1993 Design Guide for the design of new flexible pavement structures for more than two decades. The AASHTO 1993 Guide is based on the empirical design equations developed fr...

Current State of History of Psychology Teaching and Education in Argentina: An Empirical Bibliometric Investigation

ERIC Educational Resources Information Center

Fierro, Catriel; Ostrovsky, Ana Elisa; Di Doménico, María Cristina

2018-01-01

This study is an empirical analysis of the field's current state in Argentinian universities. Bibliometric parameters were used to retrieve the total listed texts (N = 797) of eight undergraduate history courses' syllabi from Argentina's most populated public university psychology programs. Then, professors in charge of the selected courses (N =…

Corruption in Higher Education: Some Findings from the States of the Former Soviet Union

ERIC Educational Resources Information Center

Temple, Paul; Petrov, Georgy

2004-01-01

Many observers have noted that corruption in higher education is widespread in the states of the former Soviet Union. Little empirical evidence is available, however. This article examines some theoretical approaches to the study of corruption, and presents empirical data on corruption in higher education from Russia and Azerbaijan, collected by…

The estimation error covariance matrix for the ideal state reconstructor with measurement noise

NASA Technical Reports Server (NTRS)

Polites, Michael E.

1988-01-01

A general expression is derived for the state estimation error covariance matrix for the Ideal State Reconstructor when the input measurements are corrupted by measurement noise. An example is presented which shows that the more measurements used in estimating the state at a given time, the better the estimator.

State Comments on Frozen Data - 2008 | ECHO | US EPA

EPA Pesticide Factsheets

website. Several states indicated that errors existed at the time the data were frozen. States that identified problems with the data were asked to send either a data file with corrected information, or a link to a state website that explained data errors or corrections. This page provides comments on 2008 frozen data.

Anatomy of an error: a bidirectional state model of task engagement/disengagement and attention-related errors.

PubMed

Allan Cheyne, J; Solman, Grayden J F; Carriere, Jonathan S A; Smilek, Daniel

2009-04-01

We present arguments and evidence for a three-state attentional model of task engagement/disengagement. The model postulates three states of mind-wandering: occurrent task inattention, generic task inattention, and response disengagement. We hypothesize that all three states are both causes and consequences of task performance outcomes and apply across a variety of experimental and real-world tasks. We apply this model to the analysis of a widely used GO/NOGO task, the Sustained Attention to Response Task (SART). We identify three performance characteristics of the SART that map onto the three states of the model: RT variability, anticipations, and omissions. Predictions based on the model are tested, and largely corroborated, via regression and lag-sequential analyses of both successful and unsuccessful withholding on NOGO trials as well as self-reported mind-wandering and everyday cognitive errors. The results revealed theoretically consistent temporal associations among the state indicators and between these and SART errors as well as with self-report measures. Lag analysis was consistent with the hypotheses that temporal transitions among states are often extremely abrupt and that the association between mind-wandering and performance is bidirectional. The bidirectional effects suggest that errors constitute important occasions for reactive mind-wandering. The model also enables concrete phenomenological, behavioral, and physiological predictions for future research.

Data on empirically estimated corporate survival rate in Russia.

PubMed

Kuzmin, Evgeny A

2018-02-01

The article presents data on the corporate survival rate in Russia in 1991-2014. The empirical survey was based on a random sample with the average number of non-repeated observations (number of companies) for the survey each year equal to 75,958 (24,236 minimum and 126,953 maximum). The actual limiting mean error ∆ p was 2.24% with 99% integrity. The survey methodology was based on a cross joining of various formal periods in the corporate life cycles (legal and business), which makes it possible to talk about a conventionally active time life of companies' existence with a number of assumptions. The empirical survey values were grouped by Russian regions and industries according to the classifier and consolidated into a single database for analysing the corporate life cycle and their survival rate and searching for deviation dependencies in calculated parameters. Preliminary and incomplete figures were available in the paper entitled "Survival Rate and Lifecycle in Terms of Uncertainty: Review of Companies from Russia and Eastern Europe" (Kuzmin and Guseva, 2016) [3]. The further survey led to filtered processed data with clerical errors excluded. These particular values are available in the article. The survey intended to fill a fact-based gap in various fundamental surveys that involved matters of the corporate life cycle in Russia within the insufficient statistical framework. The data are of interest for an analysis of Russian entrepreneurship, assessment of the market development and incorporation risks in the current business environment. A further heuristic potential is achievable through an ability of forecasted changes in business demography and model building based on the representative data set.

Assessment of microclimate conditions under artificial shades in a ginseng field.

PubMed

Lee, Kyu Jong; Lee, Byun-Woo; Kang, Je Yong; Lee, Dong Yun; Jang, Soo Won; Kim, Kwang Soo

2016-01-01

Knowledge on microclimate conditions under artificial shades in a ginseng field would facilitate climate-aware management of ginseng production. Weather data were measured under the shade and outside the shade at two fields located in Gochang-gun and Jeongeup-si, Korea, in 2011 and 2012 seasons to assess temperature and humidity conditions under the shade. An empirical approach was developed and validated for the estimation of leaf wetness duration (LWD) using weather measurements outside the shade as inputs to the model. Air temperature and relative humidity were similar between under the shade and outside the shade. For example, temperature conditions favorable for ginseng growth, e.g., between 8°C and 27°C, occurred slightly less frequently in hours during night times under the shade (91%) than outside (92%). Humidity conditions favorable for development of a foliar disease, e.g., relative humidity > 70%, occurred slightly more frequently under the shade (84%) than outside (82%). Effectiveness of correction schemes to an empirical LWD model differed by rainfall conditions for the estimation of LWD under the shade using weather measurements outside the shade as inputs to the model. During dew eligible days, a correction scheme to an empirical LWD model was slightly effective (10%) in reducing estimation errors under the shade. However, another correction approach during rainfall eligible days reduced errors of LWD estimation by 17%. Weather measurements outside the shade and LWD estimates derived from these measurements would be useful as inputs for decision support systems to predict ginseng growth and disease development.

The valuation of equity warrants under the fractional Vasicek process of the short-term interest rate

NASA Astrophysics Data System (ADS)

Xiao, Weilin; Zhang, Weiguo; Zhang, Xili; Chen, Xiaoyan

2014-01-01

Motivated by the empirical evidence of long range dependence in short-term interest rates and considering the long maturities of equity warrants, we propose the fractional Vasicek model to describe the dynamics of the short rate in the pricing environment of equity warrants. Using the partial differential equation approach, we present a valuation model for equity warrants under the assumption that the short rate follows the fractional Vasicek process. After identifying the pricing model for equity warrants, we provide the parameter estimation procedure for the proposed pricing model. Since obtaining the values of equity warrants from the proposed model needs to solve a nonlinear equation, we employ a hybrid intelligent algorithm to get around this optimization problem. Furthermore, to illustrate the practicality of our proposed model, we conduct an empirical study to ascertain the performance of our proposed model using the data from China’s warrant market and the China Foreign Exchange Trade System. The comparison of traditional models (such as the Black-Scholes model, the Noreen-Wolfson model, the Lauterbach-Schultz model, and the Ukhov model) with our proposed model is also presented. The empirical results show that the mean absolute percentage error of our pricing model is 10.30%. By contrast, the Black-Scholes model, the Noreen-Wolfson model, the Lauterbach-Schultz model, and the Ukhov model applied to the same warrant produce mean absolute errors of 35.26%, 37.67%, 33.40%, 32.81%, respectively. Thus the long memory property in stochastic interest rates cannot be ignored in determining the valuation of equity warrants.

Assessment of microclimate conditions under artificial shades in a ginseng field

PubMed Central

Lee, Kyu Jong; Lee, Byun-Woo; Kang, Je Yong; Lee, Dong Yun; Jang, Soo Won; Kim, Kwang Soo

2015-01-01

Background Knowledge on microclimate conditions under artificial shades in a ginseng field would facilitate climate-aware management of ginseng production. Methods Weather data were measured under the shade and outside the shade at two fields located in Gochang-gun and Jeongeup-si, Korea, in 2011 and 2012 seasons to assess temperature and humidity conditions under the shade. An empirical approach was developed and validated for the estimation of leaf wetness duration (LWD) using weather measurements outside the shade as inputs to the model. Results Air temperature and relative humidity were similar between under the shade and outside the shade. For example, temperature conditions favorable for ginseng growth, e.g., between 8°C and 27°C, occurred slightly less frequently in hours during night times under the shade (91%) than outside (92%). Humidity conditions favorable for development of a foliar disease, e.g., relative humidity > 70%, occurred slightly more frequently under the shade (84%) than outside (82%). Effectiveness of correction schemes to an empirical LWD model differed by rainfall conditions for the estimation of LWD under the shade using weather measurements outside the shade as inputs to the model. During dew eligible days, a correction scheme to an empirical LWD model was slightly effective (10%) in reducing estimation errors under the shade. However, another correction approach during rainfall eligible days reduced errors of LWD estimation by 17%. Conclusion Weather measurements outside the shade and LWD estimates derived from these measurements would be useful as inputs for decision support systems to predict ginseng growth and disease development. PMID:26843827

Enhancing interferometer phase estimation, sensing sensitivity, and resolution using robust entangled states

NASA Astrophysics Data System (ADS)

Smith, James F.

2017-11-01

With the goal of designing interferometers and interferometer sensors, e.g., LADARs with enhanced sensitivity, resolution, and phase estimation, states using quantum entanglement are discussed. These states include N00N states, plain M and M states (PMMSs), and linear combinations of M and M states (LCMMS). Closed form expressions for the optimal detection operators; visibility, a measure of the state's robustness to loss and noise; a resolution measure; and phase estimate error, are provided in closed form. The optimal resolution for the maximum visibility and minimum phase error are found. For the visibility, comparisons between PMMSs, LCMMS, and N00N states are provided. For the minimum phase error, comparisons between LCMMS, PMMSs, N00N states, separate photon states (SPSs), the shot noise limit (SNL), and the Heisenberg limit (HL) are provided. A representative collection of computational results illustrating the superiority of LCMMS when compared to PMMSs and N00N states is given. It is found that for a resolution 12 times the classical result LCMMS has visibility 11 times that of N00N states and 4 times that of PMMSs. For the same case, the minimum phase error for LCMMS is 10.7 times smaller than that of PMMS and 29.7 times smaller than that of N00N states.

Calibration of visually guided reaching is driven by error-corrective learning and internal dynamics.

PubMed

Cheng, Sen; Sabes, Philip N

2007-04-01

The sensorimotor calibration of visually guided reaching changes on a trial-to-trial basis in response to random shifts in the visual feedback of the hand. We show that a simple linear dynamical system is sufficient to model the dynamics of this adaptive process. In this model, an internal variable represents the current state of sensorimotor calibration. Changes in this state are driven by error feedback signals, which consist of the visually perceived reach error, the artificial shift in visual feedback, or both. Subjects correct for > or =20% of the error observed on each movement, despite being unaware of the visual shift. The state of adaptation is also driven by internal dynamics, consisting of a decay back to a baseline state and a "state noise" process. State noise includes any source of variability that directly affects the state of adaptation, such as variability in sensory feedback processing, the computations that drive learning, or the maintenance of the state. This noise is accumulated in the state across trials, creating temporal correlations in the sequence of reach errors. These correlations allow us to distinguish state noise from sensorimotor performance noise, which arises independently on each trial from random fluctuations in the sensorimotor pathway. We show that these two noise sources contribute comparably to the overall magnitude of movement variability. Finally, the dynamics of adaptation measured with random feedback shifts generalizes to the case of constant feedback shifts, allowing for a direct comparison of our results with more traditional blocked-exposure experiments.

Error Management Practices Interacting with National and Organizational Culture: The Case of Two State University Departments in Turkey

ERIC Educational Resources Information Center

Göktürk, Söheyda; Bozoglu, Oguzhan; Günçavdi, Gizem

2017-01-01

Purpose: Elements of national and organizational cultures can contribute much to the success of error management in organizations. Accordingly, this study aims to consider how errors were approached in two state university departments in Turkey in relation to their specific organizational and national cultures. Design/methodology/approach: The…

Signed reward prediction errors drive declarative learning

PubMed Central

Naert, Lien; Janssens, Clio; Talsma, Durk; Van Opstal, Filip; Verguts, Tom

2018-01-01

Reward prediction errors (RPEs) are thought to drive learning. This has been established in procedural learning (e.g., classical and operant conditioning). However, empirical evidence on whether RPEs drive declarative learning–a quintessentially human form of learning–remains surprisingly absent. We therefore coupled RPEs to the acquisition of Dutch-Swahili word pairs in a declarative learning paradigm. Signed RPEs (SRPEs; “better-than-expected” signals) during declarative learning improved recognition in a follow-up test, with increasingly positive RPEs leading to better recognition. In addition, classic declarative memory mechanisms such as time-on-task failed to explain recognition performance. The beneficial effect of SRPEs on recognition was subsequently affirmed in a replication study with visual stimuli. PMID:29293493

An investigation into exoplanet transits and uncertainties

NASA Astrophysics Data System (ADS)

Ji, Y.; Banks, T.; Budding, E.; Rhodes, M. D.

2017-06-01

A simple transit model is described along with tests of this model against published results for 4 exoplanet systems (Kepler-1, 2, 8, and 77). Data from the Kepler mission are used. The Markov Chain Monte Carlo (MCMC) method is applied to obtain realistic error estimates. Optimisation of limb darkening coefficients is subject to data quality. It is more likely for MCMC to derive an empirical limb darkening coefficient for light curves with S/N (signal to noise) above 15. Finally, the model is applied to Kepler data for 4 Kepler candidate systems (KOI 760.01, 767.01, 802.01, and 824.01) with previously unpublished results. Error estimates for these systems are obtained via the MCMC method.

Signed reward prediction errors drive declarative learning.

PubMed

De Loof, Esther; Ergo, Kate; Naert, Lien; Janssens, Clio; Talsma, Durk; Van Opstal, Filip; Verguts, Tom

2018-01-01

Reward prediction errors (RPEs) are thought to drive learning. This has been established in procedural learning (e.g., classical and operant conditioning). However, empirical evidence on whether RPEs drive declarative learning-a quintessentially human form of learning-remains surprisingly absent. We therefore coupled RPEs to the acquisition of Dutch-Swahili word pairs in a declarative learning paradigm. Signed RPEs (SRPEs; "better-than-expected" signals) during declarative learning improved recognition in a follow-up test, with increasingly positive RPEs leading to better recognition. In addition, classic declarative memory mechanisms such as time-on-task failed to explain recognition performance. The beneficial effect of SRPEs on recognition was subsequently affirmed in a replication study with visual stimuli.

Experimental measurement and theoretical modeling of microwave scattering and the structure of the sea surface influencing radar observations from space

NASA Technical Reports Server (NTRS)

Arnold, David; Kong, J. A.

1992-01-01

The electromagnetic bias is an error present in radar altimetry of the ocean due to the non-uniform reflection from wave troughs and crests. A study of the electromagnetic bias became necessary to permit error reduction in mean sea level measurements of satellite radar altimeters. Satellite radar altimeters have been used to find the upper and lower bounds for the electromagnetic bias. This report will present a theory using physical optics scattering and an empirical model of the short wave modulation to predict the electromagnetic bias. The predicted electromagnetic bias will be compared to measurements at C and Ku bands.

A comparison of advanced overlay technologies

NASA Astrophysics Data System (ADS)

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

2010-03-01

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

Using Resistivity to Measure H/Pd and D/Pd Loading:. Method and Significance

NASA Astrophysics Data System (ADS)

McKubre, M. C. H.; Tanzella, F. L.

The resistance ratio method is the most frequent technique used to determine the extent of interstitial loading of hydrogen or deuterium atoms into palladium electrodes, or extended structures used in electrolytic or gas phase cold fusion experiments. Specifically, advantage is taken of an empirical relationship between the measured resistance, R, normalized to that of the same body at the same temperature in the absence of hydrogen isotope, R0, hence R/R0, and the atomic fraction occupancy of octahedral interstitials, x = H/Pd or D/Pd. This method was first suggested and employed in cold fusion studies by the present authors, and received immediate and widespread acceptance because of the ease with which this experimental technique could be used to make in situ, real-time measurements of a parameter, D/Pd, anticipated or hypothesized at that time to relate to cold fusion heat excess or nuclear production. We take up this topic again 15 years later in an attempt to clear up some errors and misunderstandings regarding the resistance ratio method and its application in cold fusion studies. The relationship between R/R0 and x is empirical. That is, calibrations are only as good as the experiments that support the shape of the curve and cannot be used outside the range (P, T, x) in which data are taken. The original calibration (unaccountably and erroneously immortalized as the "famous Baranowski curve") involved an extrapolation of known data into the region of cold fusion interest in the D-Pd system, at x > 0.6. Present theory and results focus new attention on the very high loading region as x approaches or even exceeds unity, where double occupation of octahedral sites, tetrahedral site occupancy, new phase formation or new electrical states, may be relevant to the underlying physical process of excess heat and nuclear production. Rather than simply using the resistance ratio as a qualitative tool to determine whether an electrode is better or lesser loaded, it is now important to obtain accurate quantitative information for x close to unity. With further experimentation and analysis of published data it is apparent that the curve originally published in 1990 is in error in the high loading condition. This paper describes how this empirical fit has been improved over the years for both H/Pd and D/Pd by employing new data, new analysis of old data, new experimental methods and results.

The Rise and Fall of Andean Empires: El Nino History Lessons.

ERIC Educational Resources Information Center

Wright, Kenneth R.

2000-01-01

Provides information on El Nino and the methods for investigating ancient climate record. Traces the rise and fall of the Andean empires focusing on the climatic forces that each empire (Tiwanaku, Wari, Moche, and Inca) endured. States that modern societies should learn from the experiences of these ancient civilizations. (CMK)

Comprehensive Modeling of Temperature-Dependent Degradation Mechanisms in Lithium Iron Phosphate Batteries

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

Smith, Kandler A; Schimpe, Michael; von Kuepach, Markus Edler

For reliable lifetime predictions of lithium-ion batteries, models for cell degradation are required. A comprehensive semi-empirical model based on a reduced set of internal cell parameters and physically justified degradation functions for the capacity loss is developed and presented for a commercial lithium iron phosphate/graphite cell. One calendar and several cycle aging effects are modeled separately. Emphasis is placed on the varying degradation at different temperatures. Degradation mechanisms for cycle aging at high and low temperatures as well as the increased cycling degradation at high state of charge are calculated separately.For parameterization, a lifetime test study is conducted including storagemore » and cycle tests. Additionally, the model is validated through a dynamic current profile based on real-world application in a stationary energy storage system revealing the accuracy. The model error for the cell capacity loss in the application-based tests is at the end of testing below 1 % of the original cell capacity.« less

Data Assimilation - Advances and Applications

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

Williams, Brian J.

2014-07-30

This presentation provides an overview of data assimilation (model calibration) for complex computer experiments. Calibration refers to the process of probabilistically constraining uncertain physics/engineering model inputs to be consistent with observed experimental data. An initial probability distribution for these parameters is updated using the experimental information. Utilization of surrogate models and empirical adjustment for model form error in code calibration form the basis for the statistical methodology considered. The role of probabilistic code calibration in supporting code validation is discussed. Incorporation of model form uncertainty in rigorous uncertainty quantification (UQ) analyses is also addressed. Design criteria used within a batchmore » sequential design algorithm are introduced for efficiently achieving predictive maturity and improved code calibration. Predictive maturity refers to obtaining stable predictive inference with calibrated computer codes. These approaches allow for augmentation of initial experiment designs for collecting new physical data. A standard framework for data assimilation is presented and techniques for updating the posterior distribution of the state variables based on particle filtering and the ensemble Kalman filter are introduced.« less

Symbolic Analysis of Concurrent Programs with Polymorphism

NASA Technical Reports Server (NTRS)

Rungta, Neha Shyam

2010-01-01

The current trend of multi-core and multi-processor computing is causing a paradigm shift from inherently sequential to highly concurrent and parallel applications. Certain thread interleavings, data input values, or combinations of both often cause errors in the system. Systematic verification techniques such as explicit state model checking and symbolic execution are extensively used to detect errors in such systems [7, 9]. Explicit state model checking enumerates possible thread schedules and input data values of a program in order to check for errors [3, 9]. To partially mitigate the state space explosion from data input values, symbolic execution techniques substitute data input values with symbolic values [5, 7, 6]. Explicit state model checking and symbolic execution techniques used in conjunction with exhaustive search techniques such as depth-first search are unable to detect errors in medium to large-sized concurrent programs because the number of behaviors caused by data and thread non-determinism is extremely large. We present an overview of abstraction-guided symbolic execution for concurrent programs that detects errors manifested by a combination of thread schedules and data values [8]. The technique generates a set of key program locations relevant in testing the reachability of the target locations. The symbolic execution is then guided along these locations in an attempt to generate a feasible execution path to the error state. This allows the execution to focus in parts of the behavior space more likely to contain an error.

The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian-Laird method

PubMed Central

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

Translating Climate Projections for Bridge Engineering

NASA Astrophysics Data System (ADS)

Anderson, C.; Takle, E. S.; Krajewski, W.; Mantilla, R.; Quintero, F.

2015-12-01

A bridge vulnerability pilot study was conducted by Iowa Department of Transportation (IADOT) as one of nineteen pilots supported by the Federal Highway Administration Climate Change Resilience Pilots. Our pilot study team consisted of the IADOT senior bridge engineer who is the preliminary design section leader as well as climate and hydrological scientists. The pilot project culminated in a visual graphic designed by the bridge engineer (Figure 1), and an evaluation framework for bridge engineering design. The framework has four stages. The first two stages evaluate the spatial and temporal resolution needed in climate projection data in order to be suitable for input to a hydrology model. The framework separates streamflow simulation error into errors from the streamflow model and from the coarseness of input weather data series. In the final two stages, the framework evaluates credibility of climate projection streamflow simulations. Using an empirically downscaled data set, projection streamflow is generated. Error is computed in two time frames: the training period of the empirical downscaling methodology, and an out-of-sample period. If large errors in projection streamflow were observed during the training period, it would indicate low accuracy and, therefore, low credibility. If large errors in streamflow were observed during the out-of-sample period, it would mean the approach may not include some causes of change and, therefore, the climate projections would have limited credibility for setting expectations for changes. We address uncertainty with confidence intervals on quantiles of streamflow discharge. The results show the 95% confidence intervals have significant overlap. Nevertheless, the use of confidence intervals enabled engineering judgement. In our discussions, we noted the consistency in direction of change across basins, though the flood mechanism was different across basins, and the high bound of bridge lifetime period quantiles exceeded that of the historical period. This suggested the change was not isolated, and it systemically altered the risk profile. One suggestion to incorporate engineering judgement was to consider degrees of vulnerability using the median discharge of the historical period and the upper bound discharge for the bridge lifetime period.

Upper bounds on the error probabilities and asymptotic error exponents in quantum multiple state discrimination

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

Audenaert, Koenraad M. R., E-mail: koenraad.audenaert@rhul.ac.uk; Department of Physics and Astronomy, University of Ghent, S9, Krijgslaan 281, B-9000 Ghent; Mosonyi, Milán, E-mail: milan.mosonyi@gmail.com

2014-10-01

We consider the multiple hypothesis testing problem for symmetric quantum state discrimination between r given states σ₁, …, σ{sub r}. By splitting up the overall test into multiple binary tests in various ways we obtain a number of upper bounds on the optimal error probability in terms of the binary error probabilities. These upper bounds allow us to deduce various bounds on the asymptotic error rate, for which it has been hypothesized that it is given by the multi-hypothesis quantum Chernoff bound (or Chernoff divergence) C(σ₁, …, σ{sub r}), as recently introduced by Nussbaum and Szkoła in analogy with Salikhov'smore » classical multi-hypothesis Chernoff bound. This quantity is defined as the minimum of the pairwise binary Chernoff divergences min{sub j« less

Compensation for loads during arm movements using equilibrium-point control.

PubMed

Gribble, P L; Ostry, D J

2000-12-01

A significant problem in motor control is how information about movement error is used to modify control signals to achieve desired performance. A potential source of movement error and one that is readily controllable experimentally relates to limb dynamics and associated movement-dependent loads. In this paper, we have used a position control model to examine changes to control signals for arm movements in the context of movement-dependent loads. In the model, based on the equilibrium-point hypothesis, equilibrium shifts are adjusted directly in proportion to the positional error between desired and actual movements. The model is used to simulate multi-joint movements in the presence of both "internal" loads due to joint interaction torques, and externally applied loads resulting from velocity-dependent force fields. In both cases it is shown that the model can achieve close correspondence to empirical data using a simple linear adaptation procedure. An important feature of the model is that it achieves compensation for loads during movement without the need for either coordinate transformations between positional error and associated corrective forces, or inverse dynamics calculations.

Bayesian correction for covariate measurement error: A frequentist evaluation and comparison with regression calibration.

PubMed

Bartlett, Jonathan W; Keogh, Ruth H

2018-06-01

Bayesian approaches for handling covariate measurement error are well established and yet arguably are still relatively little used by researchers. For some this is likely due to unfamiliarity or disagreement with the Bayesian inferential paradigm. For others a contributory factor is the inability of standard statistical packages to perform such Bayesian analyses. In this paper, we first give an overview of the Bayesian approach to handling covariate measurement error, and contrast it with regression calibration, arguably the most commonly adopted approach. We then argue why the Bayesian approach has a number of statistical advantages compared to regression calibration and demonstrate that implementing the Bayesian approach is usually quite feasible for the analyst. Next, we describe the closely related maximum likelihood and multiple imputation approaches and explain why we believe the Bayesian approach to generally be preferable. We then empirically compare the frequentist properties of regression calibration and the Bayesian approach through simulation studies. The flexibility of the Bayesian approach to handle both measurement error and missing data is then illustrated through an analysis of data from the Third National Health and Nutrition Examination Survey.

Anatomy of an Error: A Bidirectional State Model of Task Engagement/Disengagement and Attention-Related Errors

ERIC Educational Resources Information Center

Cheyne, J. Allan; Solman, Grayden J. F.; Carriere, Jonathan S. A.; Smilek, Daniel

2009-01-01

We present arguments and evidence for a three-state attentional model of task engagement/disengagement. The model postulates three states of mind-wandering: occurrent task inattention, generic task inattention, and response disengagement. We hypothesize that all three states are both causes and consequences of task performance outcomes and apply…

MEDICAL ERROR: CIVIL AND LEGAL ASPECT.

PubMed

Buletsa, S; Drozd, O; Yunin, O; Mohilevskyi, L

2018-03-01

The scientific article is focused on the research of the notion of medical error, medical and legal aspects of this notion have been considered. The necessity of the legislative consolidation of the notion of «medical error» and criteria of its legal estimation have been grounded. In the process of writing a scientific article, we used the empirical method, general scientific and comparative legal methods. A comparison of the concept of medical error in civil and legal aspects was made from the point of view of Ukrainian, European and American scientists. It has been marked that the problem of medical errors is known since ancient times and in the whole world, in fact without regard to the level of development of medicine, there is no country, where doctors never make errors. According to the statistics, medical errors in the world are included in the first five reasons of death rate. At the same time the grant of medical services practically concerns all people. As a man and his life, health in Ukraine are acknowledged by a higher social value, medical services must be of high-quality and effective. The grant of not quality medical services causes harm to the health, and sometimes the lives of people; it may result in injury or even death. The right to the health protection is one of the fundamental human rights assured by the Constitution of Ukraine; therefore the issue of medical errors and liability for them is extremely relevant. The authors make conclusions, that the definition of the notion of «medical error» must get the legal consolidation. Besides, the legal estimation of medical errors must be based on the single principles enshrined in the legislation and confirmed by judicial practice.

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.

The scale-dependent market trend: Empirical evidences using the lagged DFA method

NASA Astrophysics Data System (ADS)

Li, Daye; Kou, Zhun; Sun, Qiankun

2015-09-01

In this paper we make an empirical research and test the efficiency of 44 important market indexes in multiple scales. A modified method based on the lagged detrended fluctuation analysis is utilized to maximize the information of long-term correlations from the non-zero lags and keep the margin of errors small when measuring the local Hurst exponent. Our empirical result illustrates that a common pattern can be found in the majority of the measured market indexes which tend to be persistent (with the local Hurst exponent > 0.5) in the small time scale, whereas it displays significant anti-persistent characteristics in large time scales. Moreover, not only the stock markets but also the foreign exchange markets share this pattern. Considering that the exchange markets are only weakly synchronized with the economic cycles, it can be concluded that the economic cycles can cause anti-persistence in the large time scale but there are also other factors at work. The empirical result supports the view that financial markets are multi-fractal and it indicates that deviations from efficiency and the type of model to describe the trend of market price are dependent on the forecasting horizon.

Optimized retrievals of precipitable water from the VAS 'split window'

NASA Technical Reports Server (NTRS)

Chesters, Dennis; Robinson, Wayne D.; Uccellini, Louis W.

1987-01-01

Precipitable water fields have been retrieved from the VISSR Atmospheric Sounder (VAS) using a radiation transfer model for the differential water vapor absorption between the 11- and 12-micron 'split window' channels. Previous moisture retrievals using only the split window channels provided very good space-time continuity but poor absolute accuracy. This note describes how retrieval errors can be significantly reduced from plus or minus 0.9 to plus or minus 0.6 gm/sq cm by empirically optimizing the effective air temperature and absorption coefficients used in the two-channel model. The differential absorption between the VAS 11- and 12-micron channels, empirically estimated from 135 colocated VAS-RAOB observations, is found to be approximately 50 percent smaller than the theoretical estimates. Similar discrepancies have been noted previously between theoretical and empirical absorption coefficients applied to the retrieval of sea surface temperatures using radiances observed by VAS and polar-orbiting satellites. These discrepancies indicate that radiation transfer models for the 11-micron window appear to be less accurate than the satellite observations.

Empirical mass-loss rates for 25 O and early B stars, derived from Copernicus observations

NASA Technical Reports Server (NTRS)

Gathier, R.; Lamers, H. J. G. L. M.; Snow, T. P.

1981-01-01

Ultraviolet line profiles are fitted with theoretical line profiles in the cases of 25 stars covering a spectral type range from O4 to B1, including all luminosity classes. Ion column densities are compared for the determination of wind ionization, and it is found that the O VI/N V ratio is dependent on the mean density of the wind and not on effective temperature value, while the Si IV/N V ratio is temperature-dependent. The column densities are used to derive a mass-loss rate parameter that is empirically correlated against the mass-loss rate by means of standard stars with well-determined rates from IR or radio data. The empirical mass-loss rates obtained are compared with those derived by others and found to vary by as much as a factor of 10, which is shown to be due to uncertainties or errors in the ionization fractions of models used for wind ionization balance prediction.