Genomic selection in a commercial winter wheat population.

PubMed

He, Sang; Schulthess, Albert Wilhelm; Mirdita, Vilson; Zhao, Yusheng; Korzun, Viktor; Bothe, Reiner; Ebmeyer, Erhard; Reif, Jochen C; Jiang, Yong

2016-03-01

Genomic selection models can be trained using historical data and filtering genotypes based on phenotyping intensity and reliability criterion are able to increase the prediction ability. We implemented genomic selection based on a large commercial population incorporating 2325 European winter wheat lines. Our objectives were (1) to study whether modeling epistasis besides additive genetic effects results in enhancement on prediction ability of genomic selection, (2) to assess prediction ability when training population comprised historical or less-intensively phenotyped lines, and (3) to explore the prediction ability in subpopulations selected based on the reliability criterion. We found a 5 % increase in prediction ability when shifting from additive to additive plus epistatic effects models. In addition, only a marginal loss from 0.65 to 0.50 in accuracy was observed using the data collected from 1 year to predict genotypes of the following year, revealing that stable genomic selection models can be accurately calibrated to predict subsequent breeding stages. Moreover, prediction ability was maximized when the genotypes evaluated in a single location were excluded from the training set but subsequently decreased again when the phenotyping intensity was increased above two locations, suggesting that the update of the training population should be performed considering all the selected genotypes but excluding those evaluated in a single location. The genomic prediction ability was substantially higher in subpopulations selected based on the reliability criterion, indicating that phenotypic selection for highly reliable individuals could be directly replaced by applying genomic selection to them. We empirically conclude that there is a high potential to assist commercial wheat breeding programs employing genomic selection approaches.

Physical employment standards for U.K. fire and rescue service personnel.

PubMed

Blacker, S D; Rayson, M P; Wilkinson, D M; Carter, J M; Nevill, A M; Richmond, V L

2016-01-01

Evidence-based physical employment standards are vital for recruiting, training and maintaining the operational effectiveness of personnel in physically demanding occupations. (i) Develop criterion tests for in-service physical assessment, which simulate the role-related physical demands of UK fire and rescue service (UK FRS) personnel. (ii) Develop practical physical selection tests for FRS applicants. (iii) Evaluate the validity of the selection tests to predict criterion test performance. Stage 1: we conducted a physical demands analysis involving seven workshops and an expert panel to document the key physical tasks required of UK FRS personnel and to develop 'criterion' and 'selection' tests. Stage 2: we measured the performance of 137 trainee and 50 trained UK FRS personnel on selection, criterion and 'field' measures of aerobic power, strength and body size. Statistical models were developed to predict criterion test performance. Stage 3: matter experts derived minimum performance standards. We developed single person simulations of the key physical tasks required of UK FRS personnel as criterion and selection tests (rural fire, domestic fire, ladder lift, ladder extension, ladder climb, pump assembly, enclosed space search). Selection tests were marginally stronger predictors of criterion test performance (r = 0.88-0.94, 95% Limits of Agreement [LoA] 7.6-14.0%) than field test scores (r = 0.84-0.94, 95% LoA 8.0-19.8%) and offered greater face and content validity and more practical implementation. This study outlines the development of role-related, gender-free physical employment tests for the UK FRS, which conform to equal opportunities law. © The Author 2015. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Model selection and model averaging in phylogenetics: advantages of akaike information criterion and bayesian approaches over likelihood ratio tests.

PubMed

Posada, David; Buckley, Thomas R

2004-10-01

Model selection is a topic of special relevance in molecular phylogenetics that affects many, if not all, stages of phylogenetic inference. Here we discuss some fundamental concepts and techniques of model selection in the context of phylogenetics. We start by reviewing different aspects of the selection of substitution models in phylogenetics from a theoretical, philosophical and practical point of view, and summarize this comparison in table format. We argue that the most commonly implemented model selection approach, the hierarchical likelihood ratio test, is not the optimal strategy for model selection in phylogenetics, and that approaches like the Akaike Information Criterion (AIC) and Bayesian methods offer important advantages. In particular, the latter two methods are able to simultaneously compare multiple nested or nonnested models, assess model selection uncertainty, and allow for the estimation of phylogenies and model parameters using all available models (model-averaged inference or multimodel inference). We also describe how the relative importance of the different parameters included in substitution models can be depicted. To illustrate some of these points, we have applied AIC-based model averaging to 37 mitochondrial DNA sequences from the subgenus Ohomopterus(genus Carabus) ground beetles described by Sota and Vogler (2001).

Adaptive model training system and method

DOEpatents

Bickford, Randall L; Palnitkar, Rahul M; Lee, Vo

2014-04-15

An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.

Adaptive model training system and method

DOEpatents

Bickford, Randall L; Palnitkar, Rahul M

2014-11-18

An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.

Model selection with multiple regression on distance matrices leads to incorrect inferences.

PubMed

Franckowiak, Ryan P; Panasci, Michael; Jarvis, Karl J; Acuña-Rodriguez, Ian S; Landguth, Erin L; Fortin, Marie-Josée; Wagner, Helene H

2017-01-01

In landscape genetics, model selection procedures based on Information Theoretic and Bayesian principles have been used with multiple regression on distance matrices (MRM) to test the relationship between multiple vectors of pairwise genetic, geographic, and environmental distance. Using Monte Carlo simulations, we examined the ability of model selection criteria based on Akaike's information criterion (AIC), its small-sample correction (AICc), and the Bayesian information criterion (BIC) to reliably rank candidate models when applied with MRM while varying the sample size. The results showed a serious problem: all three criteria exhibit a systematic bias toward selecting unnecessarily complex models containing spurious random variables and erroneously suggest a high level of support for the incorrectly ranked best model. These problems effectively increased with increasing sample size. The failure of AIC, AICc, and BIC was likely driven by the inflated sample size and different sum-of-squares partitioned by MRM, and the resulting effect on delta values. Based on these findings, we strongly discourage the continued application of AIC, AICc, and BIC for model selection with MRM.

Predictability of Seasonal Rainfall over the Greater Horn of Africa

NASA Astrophysics Data System (ADS)

Ngaina, J. N.

2016-12-01

The El Nino-Southern Oscillation (ENSO) is a primary mode of climate variability in the Greater of Africa (GHA). The expected impacts of climate variability and change on water, agriculture, and food resources in GHA underscore the importance of reliable and accurate seasonal climate predictions. The study evaluated different model selection criteria which included the Coefficient of determination (R2), Akaike's Information Criterion (AIC), Bayesian Information Criterion (BIC), and the Fisher information approximation (FIA). A forecast scheme based on the optimal model was developed to predict the October-November-December (OND) and March-April-May (MAM) rainfall. The predictability of GHA rainfall based on ENSO was quantified based on composite analysis, correlations and contingency tables. A test for field-significance considering the properties of finiteness and interdependence of the spatial grid was applied to avoid correlations by chance. The study identified FIA as the optimal model selection criterion. However, complex model selection criteria (FIA followed by BIC) performed better compared to simple approach (R2 and AIC). Notably, operational seasonal rainfall predictions over the GHA makes of simple model selection procedures e.g. R2. Rainfall is modestly predictable based on ENSO during OND and MAM seasons. El Nino typically leads to wetter conditions during OND and drier conditions during MAM. The correlations of ENSO indices with rainfall are statistically significant for OND and MAM seasons. Analysis based on contingency tables shows higher predictability of OND rainfall with the use of ENSO indices derived from the Pacific and Indian Oceans sea surfaces showing significant improvement during OND season. The predictability based on ENSO for OND rainfall is robust on a decadal scale compared to MAM. An ENSO-based scheme based on an optimal model selection criterion can thus provide skillful rainfall predictions over GHA. This study concludes that the negative phase of ENSO (La Niña) leads to dry conditions while the positive phase of ENSO (El Niño) anticipates enhanced wet conditions

76 FR 15961 - Funding Priorities and Selection Criterion; Disability and Rehabilitation Research Projects and...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-22

... least one, but no more than two, site-specific research projects to test innovative approaches to... Criterion; Disability and Rehabilitation Research Projects and Spinal Cord Injury Model Systems Centers and Multi-Site Collaborative Research Projects AGENCY: Office of Special Education and Rehabilitative...

Human striatal activation during adjustment of the response criterion in visual word recognition.

PubMed

Kuchinke, Lars; Hofmann, Markus J; Jacobs, Arthur M; Frühholz, Sascha; Tamm, Sascha; Herrmann, Manfred

2011-02-01

Results of recent computational modelling studies suggest that a general function of the striatum in human cognition is related to shifting decision criteria in selection processes. We used functional magnetic resonance imaging (fMRI) in 21 healthy subjects to examine the hemodynamic responses when subjects shift their response criterion on a trial-by-trial basis in the lexical decision paradigm. Trial-by-trial criterion setting is obtained when subjects respond faster in trials following a word trial than in trials following nonword trials - irrespective of the lexicality of the current trial. Since selection demands are equally high in the current trials, we expected to observe neural activations that are related to response criterion shifting. The behavioural data show sequential effects with faster responses in trials following word trials compared to trials following nonword trials, suggesting that subjects shifted their response criterion on a trial-by-trial basis. The neural responses revealed a signal increase in the striatum only in trials following word trials. This striatal activation is therefore likely to be related to response criterion setting. It demonstrates a role of the striatum in shifting decision criteria in visual word recognition, which cannot be attributed to pure error-related processing or the selection of a preferred response. Copyright © 2010 Elsevier Inc. All rights reserved.

Effects of error covariance structure on estimation of model averaging weights and predictive performance

USGS Publications Warehouse

Lu, Dan; Ye, Ming; Meyer, Philip D.; Curtis, Gary P.; Shi, Xiaoqing; Niu, Xu-Feng; Yabusaki, Steve B.

2013-01-01

When conducting model averaging for assessing groundwater conceptual model uncertainty, the averaging weights are often evaluated using model selection criteria such as AIC, AICc, BIC, and KIC (Akaike Information Criterion, Corrected Akaike Information Criterion, Bayesian Information Criterion, and Kashyap Information Criterion, respectively). However, this method often leads to an unrealistic situation in which the best model receives overwhelmingly large averaging weight (close to 100%), which cannot be justified by available data and knowledge. It was found in this study that this problem was caused by using the covariance matrix, CE, of measurement errors for estimating the negative log likelihood function common to all the model selection criteria. This problem can be resolved by using the covariance matrix, Cek, of total errors (including model errors and measurement errors) to account for the correlation between the total errors. An iterative two-stage method was developed in the context of maximum likelihood inverse modeling to iteratively infer the unknown Cek from the residuals during model calibration. The inferred Cek was then used in the evaluation of model selection criteria and model averaging weights. While this method was limited to serial data using time series techniques in this study, it can be extended to spatial data using geostatistical techniques. The method was first evaluated in a synthetic study and then applied to an experimental study, in which alternative surface complexation models were developed to simulate column experiments of uranium reactive transport. It was found that the total errors of the alternative models were temporally correlated due to the model errors. The iterative two-stage method using Cekresolved the problem that the best model receives 100% model averaging weight, and the resulting model averaging weights were supported by the calibration results and physical understanding of the alternative models. Using Cek obtained from the iterative two-stage method also improved predictive performance of the individual models and model averaging in both synthetic and experimental studies.

Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models

PubMed Central

2013-01-01

Background Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring. PMID:23827014

Cold formability prediction by the modified maximum force criterion with a non-associated Hill48 model accounting for anisotropic hardening

NASA Astrophysics Data System (ADS)

Lian, J.; Ahn, D. C.; Chae, D. C.; Münstermann, S.; Bleck, W.

2016-08-01

Experimental and numerical investigations on the characterisation and prediction of cold formability of a ferritic steel sheet are performed in this study. Tensile tests and Nakajima tests were performed for the plasticity characterisation and the forming limit diagram determination. In the numerical prediction, the modified maximum force criterion is selected as the localisation criterion. For the plasticity model, a non-associated formulation of the Hill48 model is employed. With the non-associated flow rule, the model can result in a similar predictive capability of stress and r-value directionality to the advanced non-quadratic associated models. To accurately characterise the anisotropy evolution during hardening, the anisotropic hardening is also calibrated and implemented into the model for the prediction of the formability.

A Model for Investigating Predictive Validity at Highly Selective Institutions.

ERIC Educational Resources Information Center

Gross, Alan L.; And Others

A statistical model for investigating predictive validity at highly selective institutions is described. When the selection ratio is small, one must typically deal with a data set containing relatively large amounts of missing data on both criterion and predictor variables. Standard statistical approaches are based on the strong assumption that…

A reduced-order model for compressible flows with buffeting condition using higher order dynamic mode decomposition with a mode selection criterion

NASA Astrophysics Data System (ADS)

Kou, Jiaqing; Le Clainche, Soledad; Zhang, Weiwei

2018-01-01

This study proposes an improvement in the performance of reduced-order models (ROMs) based on dynamic mode decomposition to model the flow dynamics of the attractor from a transient solution. By combining higher order dynamic mode decomposition (HODMD) with an efficient mode selection criterion, the HODMD with criterion (HODMDc) ROM is able to identify dominant flow patterns with high accuracy. This helps us to develop a more parsimonious ROM structure, allowing better predictions of the attractor dynamics. The method is tested in the solution of a NACA0012 airfoil buffeting in a transonic flow, and its good performance in both the reconstruction of the original solution and the prediction of the permanent dynamics is shown. In addition, the robustness of the method has been successfully tested using different types of parameters, indicating that the proposed ROM approach is a tool promising for using in both numerical simulations and experimental data.

Maximum likelihood-based analysis of single-molecule photon arrival trajectories

NASA Astrophysics Data System (ADS)

Hajdziona, Marta; Molski, Andrzej

2011-02-01

In this work we explore the statistical properties of the maximum likelihood-based analysis of one-color photon arrival trajectories. This approach does not involve binning and, therefore, all of the information contained in an observed photon strajectory is used. We study the accuracy and precision of parameter estimates and the efficiency of the Akaike information criterion and the Bayesian information criterion (BIC) in selecting the true kinetic model. We focus on the low excitation regime where photon trajectories can be modeled as realizations of Markov modulated Poisson processes. The number of observed photons is the key parameter in determining model selection and parameter estimation. For example, the BIC can select the true three-state model from competing two-, three-, and four-state kinetic models even for relatively short trajectories made up of 2 × 103 photons. When the intensity levels are well-separated and 104 photons are observed, the two-state model parameters can be estimated with about 10% precision and those for a three-state model with about 20% precision.

Confident difference criterion: a new Bayesian differentially expressed gene selection algorithm with applications.

PubMed

Yu, Fang; Chen, Ming-Hui; Kuo, Lynn; Talbott, Heather; Davis, John S

2015-08-07

Recently, the Bayesian method becomes more popular for analyzing high dimensional gene expression data as it allows us to borrow information across different genes and provides powerful estimators for evaluating gene expression levels. It is crucial to develop a simple but efficient gene selection algorithm for detecting differentially expressed (DE) genes based on the Bayesian estimators. In this paper, by extending the two-criterion idea of Chen et al. (Chen M-H, Ibrahim JG, Chi Y-Y. A new class of mixture models for differential gene expression in DNA microarray data. J Stat Plan Inference. 2008;138:387-404), we propose two new gene selection algorithms for general Bayesian models and name these new methods as the confident difference criterion methods. One is based on the standardized differences between two mean expression values among genes; the other adds the differences between two variances to it. The proposed confident difference criterion methods first evaluate the posterior probability of a gene having different gene expressions between competitive samples and then declare a gene to be DE if the posterior probability is large. The theoretical connection between the proposed first method based on the means and the Bayes factor approach proposed by Yu et al. (Yu F, Chen M-H, Kuo L. Detecting differentially expressed genes using alibrated Bayes factors. Statistica Sinica. 2008;18:783-802) is established under the normal-normal-model with equal variances between two samples. The empirical performance of the proposed methods is examined and compared to those of several existing methods via several simulations. The results from these simulation studies show that the proposed confident difference criterion methods outperform the existing methods when comparing gene expressions across different conditions for both microarray studies and sequence-based high-throughput studies. A real dataset is used to further demonstrate the proposed methodology. In the real data application, the confident difference criterion methods successfully identified more clinically important DE genes than the other methods. The confident difference criterion method proposed in this paper provides a new efficient approach for both microarray studies and sequence-based high-throughput studies to identify differentially expressed genes.

Model selection for the North American Breeding Bird Survey: A comparison of methods

USGS Publications Warehouse

Link, William; Sauer, John; Niven, Daniel

2017-01-01

The North American Breeding Bird Survey (BBS) provides data for >420 bird species at multiple geographic scales over 5 decades. Modern computational methods have facilitated the fitting of complex hierarchical models to these data. It is easy to propose and fit new models, but little attention has been given to model selection. Here, we discuss and illustrate model selection using leave-one-out cross validation, and the Bayesian Predictive Information Criterion (BPIC). Cross-validation is enormously computationally intensive; we thus evaluate the performance of the Watanabe-Akaike Information Criterion (WAIC) as a computationally efficient approximation to the BPIC. Our evaluation is based on analyses of 4 models as applied to 20 species covered by the BBS. Model selection based on BPIC provided no strong evidence of one model being consistently superior to the others; for 14/20 species, none of the models emerged as superior. For the remaining 6 species, a first-difference model of population trajectory was always among the best fitting. Our results show that WAIC is not reliable as a surrogate for BPIC. Development of appropriate model sets and their evaluation using BPIC is an important innovation for the analysis of BBS data.

New Stopping Criteria for Segmenting DNA Sequences

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

Li, Wentian

2001-06-18

We propose a solution on the stopping criterion in segmenting inhomogeneous DNA sequences with complex statistical patterns. This new stopping criterion is based on Bayesian information criterion in the model selection framework. When this criterion is applied to telomere of S.cerevisiae and the complete sequence of E.coli, borders of biologically meaningful units were identified, and a more reasonable number of domains was obtained. We also introduce a measure called segmentation strength which can be used to control the delineation of large domains. The relationship between the average domain size and the threshold of segmentation strength is determined for several genomemore » sequences.« less

Modelling on optimal portfolio with exchange rate based on discontinuous stochastic process

NASA Astrophysics Data System (ADS)

Yan, Wei; Chang, Yuwen

2016-12-01

Considering the stochastic exchange rate, this paper is concerned with the dynamic portfolio selection in financial market. The optimal investment problem is formulated as a continuous-time mathematical model under mean-variance criterion. These processes follow jump-diffusion processes (Weiner process and Poisson process). Then the corresponding Hamilton-Jacobi-Bellman(HJB) equation of the problem is presented and its efferent frontier is obtained. Moreover, the optimal strategy is also derived under safety-first criterion.

Comparison of Selection Procedures and Validation of Criterion Used in Selection of Significant Control Variates of a Simulation Model

DTIC Science & Technology

1990-03-01

and M.H. Knuter. Applied Linear Regression Models. Homewood IL: Richard D. Erwin Inc., 1983. Pritsker, A. Alan B. Introduction to Simulation and SLAM...Control Variates in Simulation," European Journal of Operational Research, 42: (1989). Neter, J., W. Wasserman, and M.H. Xnuter. Applied Linear Regression Models

Test Design Optimization in CAT Early Stage with the Nominal Response Model

ERIC Educational Resources Information Center

Passos, Valeria Lima; Berger, Martijn P. F.; Tan, Frans E.

2007-01-01

The early stage of computerized adaptive testing (CAT) refers to the phase of the trait estimation during the administration of only a few items. This phase can be characterized by bias and instability of estimation. In this study, an item selection criterion is introduced in an attempt to lessen this instability: the D-optimality criterion. A…

The Development of a Model for Construction of Criterion Referenced System Achievement Tests for the Strategic Weapon System Training Program.

ERIC Educational Resources Information Center

Cantor, Jeffrey A.; Hobson, Edward N.

The development of a test design methodology used to construct a criterion-referenced System Achievement Test (CR-SAT) for selected Naval enlisted classification (NEC) in the Strategic Weapon System (SWS) of the United States Navy is described. Subject matter experts, training data analysts and educational specialists developed a comprehensive…

Interaction Effects Between Selected Cognitive Abilities and Instructional Treatment in Algebra: An ATI Study.

ERIC Educational Resources Information Center

Webb, Leland F.

The purpose of this study was to confirm or deny Carry's findings in an earlier Aptitude Treatment Interaction (ATI) study by implementing his suggestions to: (1) revise instructional treatments, (2) improve the criterion measures, (3) use four predictor tests, (4) add time to criterion measure, and (5) use a theoretical model to identify relevant…

Model weights and the foundations of multimodel inference

USGS Publications Warehouse

Link, W.A.; Barker, R.J.

2006-01-01

Statistical thinking in wildlife biology and ecology has been profoundly influenced by the introduction of AIC (Akaike?s information criterion) as a tool for model selection and as a basis for model averaging. In this paper, we advocate the Bayesian paradigm as a broader framework for multimodel inference, one in which model averaging and model selection are naturally linked, and in which the performance of AIC-based tools is naturally evaluated. Prior model weights implicitly associated with the use of AIC are seen to highly favor complex models: in some cases, all but the most highly parameterized models in the model set are virtually ignored a priori. We suggest the usefulness of the weighted BIC (Bayesian information criterion) as a computationally simple alternative to AIC, based on explicit selection of prior model probabilities rather than acceptance of default priors associated with AIC. We note, however, that both procedures are only approximate to the use of exact Bayes factors. We discuss and illustrate technical difficulties associated with Bayes factors, and suggest approaches to avoiding these difficulties in the context of model selection for a logistic regression. Our example highlights the predisposition of AIC weighting to favor complex models and suggests a need for caution in using the BIC for computing approximate posterior model weights.

Maximum likelihood-based analysis of single-molecule photon arrival trajectories.

PubMed

Hajdziona, Marta; Molski, Andrzej

2011-02-07

In this work we explore the statistical properties of the maximum likelihood-based analysis of one-color photon arrival trajectories. This approach does not involve binning and, therefore, all of the information contained in an observed photon strajectory is used. We study the accuracy and precision of parameter estimates and the efficiency of the Akaike information criterion and the Bayesian information criterion (BIC) in selecting the true kinetic model. We focus on the low excitation regime where photon trajectories can be modeled as realizations of Markov modulated Poisson processes. The number of observed photons is the key parameter in determining model selection and parameter estimation. For example, the BIC can select the true three-state model from competing two-, three-, and four-state kinetic models even for relatively short trajectories made up of 2 × 10(3) photons. When the intensity levels are well-separated and 10(4) photons are observed, the two-state model parameters can be estimated with about 10% precision and those for a three-state model with about 20% precision.

Stochastic isotropic hyperelastic materials: constitutive calibration and model selection

NASA Astrophysics Data System (ADS)

Mihai, L. Angela; Woolley, Thomas E.; Goriely, Alain

2018-03-01

Biological and synthetic materials often exhibit intrinsic variability in their elastic responses under large strains, owing to microstructural inhomogeneity or when elastic data are extracted from viscoelastic mechanical tests. For these materials, although hyperelastic models calibrated to mean data are useful, stochastic representations accounting also for data dispersion carry extra information about the variability of material properties found in practical applications. We combine finite elasticity and information theories to construct homogeneous isotropic hyperelastic models with random field parameters calibrated to discrete mean values and standard deviations of either the stress-strain function or the nonlinear shear modulus, which is a function of the deformation, estimated from experimental tests. These quantities can take on different values, corresponding to possible outcomes of the experiments. As multiple models can be derived that adequately represent the observed phenomena, we apply Occam's razor by providing an explicit criterion for model selection based on Bayesian statistics. We then employ this criterion to select a model among competing models calibrated to experimental data for rubber and brain tissue under single or multiaxial loads.

Information-theoretic model selection for optimal prediction of stochastic dynamical systems from data

NASA Astrophysics Data System (ADS)

Darmon, David

2018-03-01

In the absence of mechanistic or phenomenological models of real-world systems, data-driven models become necessary. The discovery of various embedding theorems in the 1980s and 1990s motivated a powerful set of tools for analyzing deterministic dynamical systems via delay-coordinate embeddings of observations of their component states. However, in many branches of science, the condition of operational determinism is not satisfied, and stochastic models must be brought to bear. For such stochastic models, the tool set developed for delay-coordinate embedding is no longer appropriate, and a new toolkit must be developed. We present an information-theoretic criterion, the negative log-predictive likelihood, for selecting the embedding dimension for a predictively optimal data-driven model of a stochastic dynamical system. We develop a nonparametric estimator for the negative log-predictive likelihood and compare its performance to a recently proposed criterion based on active information storage. Finally, we show how the output of the model selection procedure can be used to compare candidate predictors for a stochastic system to an information-theoretic lower bound.

Support Vector Feature Selection for Early Detection of Anastomosis Leakage From Bag-of-Words in Electronic Health Records.

PubMed

Soguero-Ruiz, Cristina; Hindberg, Kristian; Rojo-Alvarez, Jose Luis; Skrovseth, Stein Olav; Godtliebsen, Fred; Mortensen, Kim; Revhaug, Arthur; Lindsetmo, Rolv-Ole; Augestad, Knut Magne; Jenssen, Robert

2016-09-01

The free text in electronic health records (EHRs) conveys a huge amount of clinical information about health state and patient history. Despite a rapidly growing literature on the use of machine learning techniques for extracting this information, little effort has been invested toward feature selection and the features' corresponding medical interpretation. In this study, we focus on the task of early detection of anastomosis leakage (AL), a severe complication after elective surgery for colorectal cancer (CRC) surgery, using free text extracted from EHRs. We use a bag-of-words model to investigate the potential for feature selection strategies. The purpose is earlier detection of AL and prediction of AL with data generated in the EHR before the actual complication occur. Due to the high dimensionality of the data, we derive feature selection strategies using the robust support vector machine linear maximum margin classifier, by investigating: 1) a simple statistical criterion (leave-one-out-based test); 2) an intensive-computation statistical criterion (Bootstrap resampling); and 3) an advanced statistical criterion (kernel entropy). Results reveal a discriminatory power for early detection of complications after CRC (sensitivity 100%; specificity 72%). These results can be used to develop prediction models, based on EHR data, that can support surgeons and patients in the preoperative decision making phase.

How Many Separable Sources? Model Selection In Independent Components Analysis

PubMed Central

Woods, Roger P.; Hansen, Lars Kai; Strother, Stephen

2015-01-01

Unlike mixtures consisting solely of non-Gaussian sources, mixtures including two or more Gaussian components cannot be separated using standard independent components analysis methods that are based on higher order statistics and independent observations. The mixed Independent Components Analysis/Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from among potential model categories with differing numbers of Gaussian components. Based on simulation studies, the assumptions and approximations underlying the Akaike Information Criterion do not hold in this setting, even with a very large number of observations. Cross-validation is a suitable, though computationally intensive alternative for model selection. Application of the algorithm is illustrated using Fisher's iris data set and Howells' craniometric data set. Mixed ICA/PCA is of potential interest in any field of scientific investigation where the authenticity of blindly separated non-Gaussian sources might otherwise be questionable. Failure of the Akaike Information Criterion in model selection also has relevance in traditional independent components analysis where all sources are assumed non-Gaussian. PMID:25811988

Congruence analysis of geodetic networks - hypothesis tests versus model selection by information criteria

NASA Astrophysics Data System (ADS)

Lehmann, Rüdiger; Lösler, Michael

2017-12-01

Geodetic deformation analysis can be interpreted as a model selection problem. The null model indicates that no deformation has occurred. It is opposed to a number of alternative models, which stipulate different deformation patterns. A common way to select the right model is the usage of a statistical hypothesis test. However, since we have to test a series of deformation patterns, this must be a multiple test. As an alternative solution for the test problem, we propose the p-value approach. Another approach arises from information theory. Here, the Akaike information criterion (AIC) or some alternative is used to select an appropriate model for a given set of observations. Both approaches are discussed and applied to two test scenarios: A synthetic levelling network and the Delft test data set. It is demonstrated that they work but behave differently, sometimes even producing different results. Hypothesis tests are well-established in geodesy, but may suffer from an unfavourable choice of the decision error rates. The multiple test also suffers from statistical dependencies between the test statistics, which are neglected. Both problems are overcome by applying information criterions like AIC.

The System of Objectified Judgement Analysis (SOJA). A tool in rational drug selection for formulary inclusion.

PubMed

Janknegt, R; Steenhoek, A

1997-04-01

Rational drug selection for formulary purposes is important. Besides rational selection criteria, other factors play a role in drug decision making, such as emotional, personal financial and even unconscious criteria. It is agreed that these factors should be excluded as much as possible in the decision making process. A model for drug decision making for formulary purposes is described, the System of Objectified Judgement Analysis (SOJA). In the SOJA method, selection criteria for a given group of drugs are prospectively defined and the extent to which each drug fulfils the requirements for each criterion is determined. Each criterion is given a relative weight, i.e. the more important a given selection criterion is considered, the higher the relative weight. Both the relative scores for each drug per selection criterion and the relative weight of each criterion are determined by a panel of experts in this field. The following selection criteria are applied in all SOJA scores: clinical efficacy, incidence and severity of adverse effects, dosage frequency, drug interactions, acquisition cost, documentation, pharmacokinetics and pharmaceutical aspects. Besides these criteria, group specific criteria are also used, such as development of resistance when a SOJA score was made for antimicrobial agents. The relative weight that is assigned to each criterion will always be a subject of discussion. Therefore, interactive software programs for use on a personal computer have been developed, in which the user of the system may enter their own personal relative weight to each selection criterion and make their own personal SOJA score. The main advantage of the SOJA method is that all nonrational selection criteria are excluded and that drug decision making is based solely on rational criteria. The use of the interactive SOJA discs makes the decision process fully transparent as it becomes clear on which criteria and weighting decisions are based. We have seen that the use of this method for drug decision making greatly aids the discussion in the formulary committee, as discussion becomes much more concrete. The SOJA method is time dependent. Documentation on most products is still increasing and the score for this criterion will therefore change continuously. New products are introduced and prices are also subject to change. To overcome the time-dependence of the SOJA method, regular updates of interactive software programs are being made, in which changes in acquisition cost, documentation or a different weighting of criteria are included, as well as newly introduced products. The possibility of changing the official acquisition cost into the actual purchasing costs for the hospital in question provides a tailor-made interactive program.

Variable selection with stepwise and best subset approaches

PubMed Central

2016-01-01

While purposeful selection is performed partly by software and partly by hand, the stepwise and best subset approaches are automatically performed by software. Two R functions stepAIC() and bestglm() are well designed for stepwise and best subset regression, respectively. The stepAIC() function begins with a full or null model, and methods for stepwise regression can be specified in the direction argument with character values “forward”, “backward” and “both”. The bestglm() function begins with a data frame containing explanatory variables and response variables. The response variable should be in the last column. Varieties of goodness-of-fit criteria can be specified in the IC argument. The Bayesian information criterion (BIC) usually results in more parsimonious model than the Akaike information criterion. PMID:27162786

Drinking Water Quality Criterion - Based site Selection of Aquifer Storage and Recovery Scheme in Chou-Shui River Alluvial Fan

NASA Astrophysics Data System (ADS)

Huang, H. E.; Liang, C. P.; Jang, C. S.; Chen, J. S.

2015-12-01

Land subsidence due to groundwater exploitation is an urgent environmental problem in Choushui river alluvial fan in Taiwan. Aquifer storage and recovery (ASR), where excess surface water is injected into subsurface aquifers for later recovery, is one promising strategy for managing surplus water and may overcome water shortages. The performance of an ASR scheme is generally evaluated in terms of recovery efficiency, which is defined as percentage of water injected in to a system in an ASR site that fulfills the targeted water quality criterion. Site selection of an ASR scheme typically faces great challenges, due to the spatial variability of groundwater quality and hydrogeological condition. This study proposes a novel method for the ASR site selection based on drinking quality criterion. Simplified groundwater flow and contaminant transport model spatial distributions of the recovery efficiency with the help of the groundwater quality, hydrological condition, ASR operation. The results of this study may provide government administrator for establishing reliable ASR scheme.

Empirical extensions of the lasso penalty to reduce the false discovery rate in high-dimensional Cox regression models.

PubMed

Ternès, Nils; Rotolo, Federico; Michiels, Stefan

2016-07-10

Correct selection of prognostic biomarkers among multiple candidates is becoming increasingly challenging as the dimensionality of biological data becomes higher. Therefore, minimizing the false discovery rate (FDR) is of primary importance, while a low false negative rate (FNR) is a complementary measure. The lasso is a popular selection method in Cox regression, but its results depend heavily on the penalty parameter λ. Usually, λ is chosen using maximum cross-validated log-likelihood (max-cvl). However, this method has often a very high FDR. We review methods for a more conservative choice of λ. We propose an empirical extension of the cvl by adding a penalization term, which trades off between the goodness-of-fit and the parsimony of the model, leading to the selection of fewer biomarkers and, as we show, to the reduction of the FDR without large increase in FNR. We conducted a simulation study considering null and moderately sparse alternative scenarios and compared our approach with the standard lasso and 10 other competitors: Akaike information criterion (AIC), corrected AIC, Bayesian information criterion (BIC), extended BIC, Hannan and Quinn information criterion (HQIC), risk information criterion (RIC), one-standard-error rule, adaptive lasso, stability selection, and percentile lasso. Our extension achieved the best compromise across all the scenarios between a reduction of the FDR and a limited raise of the FNR, followed by the AIC, the RIC, and the adaptive lasso, which performed well in some settings. We illustrate the methods using gene expression data of 523 breast cancer patients. In conclusion, we propose to apply our extension to the lasso whenever a stringent FDR with a limited FNR is targeted. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Fuzzy approaches to supplier selection problem

NASA Astrophysics Data System (ADS)

Ozkok, Beyza Ahlatcioglu; Kocken, Hale Gonce

2013-09-01

Supplier selection problem is a multi-criteria decision making problem which includes both qualitative and quantitative factors. In the selection process many criteria may conflict with each other, therefore decision-making process becomes complicated. In this study, we handled the supplier selection problem under uncertainty. In this context; we used minimum criterion, arithmetic mean criterion, regret criterion, optimistic criterion, geometric mean and harmonic mean. The membership functions created with the help of the characteristics of used criteria, and we tried to provide consistent supplier selection decisions by using these memberships for evaluating alternative suppliers. During the analysis, no need to use expert opinion is a strong aspect of the methodology used in the decision-making.

Economic weights for genetic improvement of lactation persistency and milk yield.

PubMed

Togashi, K; Lin, C Y

2009-06-01

This study aimed to establish a criterion for measuring the relative weight of lactation persistency (the ratio of yield at 280 d in milk to peak yield) in restricted selection index for the improvement of net merit comprising 3-parity total yield and total lactation persistency. The restricted selection index was compared with selection based on first-lactation total milk yield (I(1)), the first-two-lactation total yield (I(2)), and first-three-lactation total yield (I(3)). Results show that genetic response in net merit due to selection on restricted selection index could be greater than, equal to, or less than that due to the unrestricted index depending upon the relative weight of lactation persistency and the restriction level imposed. When the relative weight of total lactation persistency is equal to the criterion, the restricted selection index is equal to the selection method compared (I(1), I(2), or I(3)). The restricted selection index yielded a greater response when the relative weight of total lactation persistency was above the criterion, but a lower response when it was below the criterion. The criterion varied depending upon the restriction level (c) imposed and the selection criteria compared. A curvilinear relationship (concave curve) exists between the criterion and the restricted level. The criterion increases as the restriction level deviates in either direction from 1.5. Without prior information of the economic weight of lactation persistency, the imposition of the restriction level of 1.5 on lactation persistency would maximize change in net merit. The procedure presented allows for simultaneous modification of multi-parity lactation curves.

Model selection for marginal regression analysis of longitudinal data with missing observations and covariate measurement error.

PubMed

Shen, Chung-Wei; Chen, Yi-Hau

2015-10-01

Missing observations and covariate measurement error commonly arise in longitudinal data. However, existing methods for model selection in marginal regression analysis of longitudinal data fail to address the potential bias resulting from these issues. To tackle this problem, we propose a new model selection criterion, the Generalized Longitudinal Information Criterion, which is based on an approximately unbiased estimator for the expected quadratic error of a considered marginal model accounting for both data missingness and covariate measurement error. The simulation results reveal that the proposed method performs quite well in the presence of missing data and covariate measurement error. On the contrary, the naive procedures without taking care of such complexity in data may perform quite poorly. The proposed method is applied to data from the Taiwan Longitudinal Study on Aging to assess the relationship of depression with health and social status in the elderly, accommodating measurement error in the covariate as well as missing observations. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Objective Model Selection for Identifying the Human Feedforward Response in Manual Control.

PubMed

Drop, Frank M; Pool, Daan M; van Paassen, Marinus Rene M; Mulder, Max; Bulthoff, Heinrich H

2018-01-01

Realistic manual control tasks typically involve predictable target signals and random disturbances. The human controller (HC) is hypothesized to use a feedforward control strategy for target-following, in addition to feedback control for disturbance-rejection. Little is known about human feedforward control, partly because common system identification methods have difficulty in identifying whether, and (if so) how, the HC applies a feedforward strategy. In this paper, an identification procedure is presented that aims at an objective model selection for identifying the human feedforward response, using linear time-invariant autoregressive with exogenous input models. A new model selection criterion is proposed to decide on the model order (number of parameters) and the presence of feedforward in addition to feedback. For a range of typical control tasks, it is shown by means of Monte Carlo computer simulations that the classical Bayesian information criterion (BIC) leads to selecting models that contain a feedforward path from data generated by a pure feedback model: "false-positive" feedforward detection. To eliminate these false-positives, the modified BIC includes an additional penalty on model complexity. The appropriate weighting is found through computer simulations with a hypothesized HC model prior to performing a tracking experiment. Experimental human-in-the-loop data will be considered in future work. With appropriate weighting, the method correctly identifies the HC dynamics in a wide range of control tasks, without false-positive results.

Genetic parameters for growth characteristics of free-range chickens under univariate random regression models.

PubMed

Rovadoscki, Gregori A; Petrini, Juliana; Ramirez-Diaz, Johanna; Pertile, Simone F N; Pertille, Fábio; Salvian, Mayara; Iung, Laiza H S; Rodriguez, Mary Ana P; Zampar, Aline; Gaya, Leila G; Carvalho, Rachel S B; Coelho, Antonio A D; Savino, Vicente J M; Coutinho, Luiz L; Mourão, Gerson B

2016-09-01

Repeated measures from the same individual have been analyzed by using repeatability and finite dimension models under univariate or multivariate analyses. However, in the last decade, the use of random regression models for genetic studies with longitudinal data have become more common. Thus, the aim of this research was to estimate genetic parameters for body weight of four experimental chicken lines by using univariate random regression models. Body weight data from hatching to 84 days of age (n = 34,730) from four experimental free-range chicken lines (7P, Caipirão da ESALQ, Caipirinha da ESALQ and Carijó Barbado) were used. The analysis model included the fixed effects of contemporary group (gender and rearing system), fixed regression coefficients for age at measurement, and random regression coefficients for permanent environmental effects and additive genetic effects. Heterogeneous variances for residual effects were considered, and one residual variance was assigned for each of six subclasses of age at measurement. Random regression curves were modeled by using Legendre polynomials of the second and third orders, with the best model chosen based on the Akaike Information Criterion, Bayesian Information Criterion, and restricted maximum likelihood. Multivariate analyses under the same animal mixed model were also performed for the validation of the random regression models. The Legendre polynomials of second order were better for describing the growth curves of the lines studied. Moderate to high heritabilities (h(2) = 0.15 to 0.98) were estimated for body weight between one and 84 days of age, suggesting that selection for body weight at all ages can be used as a selection criteria. Genetic correlations among body weight records obtained through multivariate analyses ranged from 0.18 to 0.96, 0.12 to 0.89, 0.06 to 0.96, and 0.28 to 0.96 in 7P, Caipirão da ESALQ, Caipirinha da ESALQ, and Carijó Barbado chicken lines, respectively. Results indicate that genetic gain for body weight can be achieved by selection. Also, selection for body weight at 42 days of age can be maintained as a selection criterion. © 2016 Poultry Science Association Inc.

Optimal experimental designs for fMRI when the model matrix is uncertain.

PubMed

Kao, Ming-Hung; Zhou, Lin

2017-07-15

This study concerns optimal designs for functional magnetic resonance imaging (fMRI) experiments when the model matrix of the statistical model depends on both the selected stimulus sequence (fMRI design), and the subject's uncertain feedback (e.g. answer) to each mental stimulus (e.g. question) presented to her/him. While practically important, this design issue is challenging. This mainly is because that the information matrix cannot be fully determined at the design stage, making it difficult to evaluate the quality of the selected designs. To tackle this challenging issue, we propose an easy-to-use optimality criterion for evaluating the quality of designs, and an efficient approach for obtaining designs optimizing this criterion. Compared with a previously proposed method, our approach requires a much less computing time to achieve designs with high statistical efficiencies. Copyright © 2017 Elsevier Inc. All rights reserved.

Validation by simulation of a clinical trial model using the standardized mean and variance criteria.

PubMed

Abbas, Ismail; Rovira, Joan; Casanovas, Josep

2006-12-01

To develop and validate a model of a clinical trial that evaluates the changes in cholesterol level as a surrogate marker for lipodystrophy in HIV subjects under alternative antiretroviral regimes, i.e., treatment with Protease Inhibitors vs. a combination of nevirapine and other antiretroviral drugs. Five simulation models were developed based on different assumptions, on treatment variability and pattern of cholesterol reduction over time. The last recorded cholesterol level, the difference from the baseline, the average difference from the baseline and level evolution, are the considered endpoints. Specific validation criteria based on a 10% minus or plus standardized distance in means and variances were used to compare the real and the simulated data. The validity criterion was met by all models for considered endpoints. However, only two models met the validity criterion when all endpoints were considered. The model based on the assumption that within-subjects variability of cholesterol levels changes over time is the one that minimizes the validity criterion, standardized distance equal to or less than 1% minus or plus. Simulation is a useful technique for calibration, estimation, and evaluation of models, which allows us to relax the often overly restrictive assumptions regarding parameters required by analytical approaches. The validity criterion can also be used to select the preferred model for design optimization, until additional data are obtained allowing an external validation of the model.

Systematic narrative review of decision frameworks to select the appropriate modelling approaches for health economic evaluations.

PubMed

Tsoi, B; O'Reilly, D; Jegathisawaran, J; Tarride, J-E; Blackhouse, G; Goeree, R

2015-06-17

In constructing or appraising a health economic model, an early consideration is whether the modelling approach selected is appropriate for the given decision problem. Frameworks and taxonomies that distinguish between modelling approaches can help make this decision more systematic and this study aims to identify and compare the decision frameworks proposed to date on this topic area. A systematic review was conducted to identify frameworks from peer-reviewed and grey literature sources. The following databases were searched: OVID Medline and EMBASE; Wiley's Cochrane Library and Health Economic Evaluation Database; PubMed; and ProQuest. Eight decision frameworks were identified, each focused on a different set of modelling approaches and employing a different collection of selection criterion. The selection criteria can be categorized as either: (i) structural features (i.e. technical elements that are factual in nature) or (ii) practical considerations (i.e. context-dependent attributes). The most commonly mentioned structural features were population resolution (i.e. aggregate vs. individual) and interactivity (i.e. static vs. dynamic). Furthermore, understanding the needs of the end-users and stakeholders was frequently incorporated as a criterion within these frameworks. There is presently no universally-accepted framework for selecting an economic modelling approach. Rather, each highlights different criteria that may be of importance when determining whether a modelling approach is appropriate. Further discussion is thus necessary as the modelling approach selected will impact the validity of the underlying economic model and have downstream implications on its efficiency, transparency and relevance to decision-makers.

Model selection for semiparametric marginal mean regression accounting for within-cluster subsampling variability and informative cluster size.

PubMed

Shen, Chung-Wei; Chen, Yi-Hau

2018-03-13

We propose a model selection criterion for semiparametric marginal mean regression based on generalized estimating equations. The work is motivated by a longitudinal study on the physical frailty outcome in the elderly, where the cluster size, that is, the number of the observed outcomes in each subject, is "informative" in the sense that it is related to the frailty outcome itself. The new proposal, called Resampling Cluster Information Criterion (RCIC), is based on the resampling idea utilized in the within-cluster resampling method (Hoffman, Sen, and Weinberg, 2001, Biometrika 88, 1121-1134) and accommodates informative cluster size. The implementation of RCIC, however, is free of performing actual resampling of the data and hence is computationally convenient. Compared with the existing model selection methods for marginal mean regression, the RCIC method incorporates an additional component accounting for variability of the model over within-cluster subsampling, and leads to remarkable improvements in selecting the correct model, regardless of whether the cluster size is informative or not. Applying the RCIC method to the longitudinal frailty study, we identify being female, old age, low income and life satisfaction, and chronic health conditions as significant risk factors for physical frailty in the elderly. © 2018, The International Biometric Society.

Robust check loss-based variable selection of high-dimensional single-index varying-coefficient model

NASA Astrophysics Data System (ADS)

Song, Yunquan; Lin, Lu; Jian, Ling

2016-07-01

Single-index varying-coefficient model is an important mathematical modeling method to model nonlinear phenomena in science and engineering. In this paper, we develop a variable selection method for high-dimensional single-index varying-coefficient models using a shrinkage idea. The proposed procedure can simultaneously select significant nonparametric components and parametric components. Under defined regularity conditions, with appropriate selection of tuning parameters, the consistency of the variable selection procedure and the oracle property of the estimators are established. Moreover, due to the robustness of the check loss function to outliers in the finite samples, our proposed variable selection method is more robust than the ones based on the least squares criterion. Finally, the method is illustrated with numerical simulations.

An Integrated model for Product Quality Development—A case study on Quality functions deployment and AHP based approach

NASA Astrophysics Data System (ADS)

Maitra, Subrata; Banerjee, Debamalya

2010-10-01

Present article is based on application of the product quality and improvement of design related with the nature of failure of machineries and plant operational problems of an industrial blower fan Company. The project aims at developing the product on the basis of standardized production parameters for selling its products in the market. Special attention is also being paid to the blower fans which have been ordered directly by the customer on the basis of installed capacity of air to be provided by the fan. Application of quality function deployment is primarily a customer oriented approach. Proposed model of QFD integrated with AHP to select and rank the decision criterions on the commercial and technical factors and the measurement of the decision parameters for selection of best product in the compettitive environment. The present AHP-QFD model justifies the selection of a blower fan with the help of the group of experts' opinion by pairwise comparison of the customer's and ergonomy based technical design requirements. The steps invoved in implementation of the QFD—AHP and selection of weighted criterion may be helpful for all similar purpose industries maintaining cost and utility for competitive product.

Comparison and continuous estimates of fecal coliform and Escherichia coli bacteria in selected Kansas streams, May 1999 through April 2002

USGS Publications Warehouse

Rasmussen, Patrick P.; Ziegler, Andrew C.

2003-01-01

The sanitary quality of water and its use as a public-water supply and for recreational activities, such as swimming, wading, boating, and fishing, can be evaluated on the basis of fecal coliform and Escherichia coli (E. coli) bacteria densities. This report describes the overall sanitary quality of surface water in selected Kansas streams, the relation between fecal coliform and E. coli, the relation between turbidity and bacteria densities, and how continuous bacteria estimates can be used to evaluate the water-quality conditions in selected Kansas streams. Samples for fecal coliform and E. coli were collected at 28 surface-water sites in Kansas. Of the 318 samples collected, 18 percent exceeded the current Kansas Department of Health and Environment (KDHE) secondary contact recreational, single-sample criterion for fecal coliform (2,000 colonies per 100 milliliters of water). Of the 219 samples collected during the recreation months (April 1 through October 31), 21 percent exceeded the current (2003) KDHE single-sample fecal coliform criterion for secondary contact rec-reation (2,000 colonies per 100 milliliters of water) and 36 percent exceeded the U.S. Environmental Protection Agency (USEPA) recommended single-sample primary contact recreational criterion for E. coli (576 colonies per 100 milliliters of water). Comparisons of fecal coliform and E. coli criteria indicated that more than one-half of the streams sampled could exceed USEPA recommended E. coli criteria more frequently than the current KDHE fecal coliform criteria. In addition, the ratios of E. coli to fecal coliform (EC/FC) were smallest for sites with slightly saline water (specific conductance greater than 1,000 microsiemens per centimeter at 25 degrees Celsius), indicating that E. coli may not be a good indicator of sanitary quality for those streams. Enterococci bacteria may provide a more accurate assessment of the potential for swimming-related illnesses in these streams. Ratios of EC/FC and linear regression models were developed for estimating E. coli densities on the basis of measured fecal coliform densities for six individual and six groups of surface-water sites. Regression models developed for the six individual surface-water sites and six groups of sites explain at least 89 percent of the variability in E. coli densities. The EC/FC ratios and regression models are site specific and make it possible to convert historic fecal coliform bacteria data to estimated E. coli densities for the selected sites. The EC/FC ratios can be used to estimate E. coli for any range of historical fecal coliform densities, and in some cases with less error than the regression models. The basin- and statewide regression models explained at least 93 percent of the variance and best represent the sites where a majority of the data used to develop the models were collected (Kansas and Little Arkansas Basins). Comparison of the current (2003) KDHE geometric-mean primary contact criterion for fecal coliform bacteria of 200 col/100 mL to the 2002 USEPA recommended geometric-mean criterion of 126 col/100 mL for E. coli results in an EC/FC ratio of 0.63. The geometric-mean EC/FC ratio for all sites except Rattlesnake Creek (site 21) is 0.77, indicating that considerably more than 63 percent of the fecal coliform is E. coli. This potentially could lead to more exceedances of the recommended E. coli criterion, where the water now meets the current (2003) 200-col/100 mL fecal coliform criterion. In this report, turbidity was found to be a reliable estimator of bacteria densities. Regression models are provided for estimating fecal coliform and E. coli bacteria densities using continuous turbidity measurements. Prediction intervals also are provided to show the uncertainty associated with using the regression models. Eighty percent of all measured sample densities and individual turbidity-based estimates from the regression models were in agreement as exceedi

The optimal code searching method with an improved criterion of coded exposure for remote sensing image restoration

NASA Astrophysics Data System (ADS)

He, Lirong; Cui, Guangmang; Feng, Huajun; Xu, Zhihai; Li, Qi; Chen, Yueting

2015-03-01

Coded exposure photography makes the motion de-blurring a well-posed problem. The integration pattern of light is modulated using the method of coded exposure by opening and closing the shutter within the exposure time, changing the traditional shutter frequency spectrum into a wider frequency band in order to preserve more image information in frequency domain. The searching method of optimal code is significant for coded exposure. In this paper, an improved criterion of the optimal code searching is proposed by analyzing relationship between code length and the number of ones in the code, considering the noise effect on code selection with the affine noise model. Then the optimal code is obtained utilizing the method of genetic searching algorithm based on the proposed selection criterion. Experimental results show that the time consuming of searching optimal code decreases with the presented method. The restoration image is obtained with better subjective experience and superior objective evaluation values.

[On the problems of the evolutionary optimization of life history. II. To justification of optimization criterion for nonlinear Leslie model].

PubMed

Pasekov, V P

2013-03-01

The paper considers the problems in the adaptive evolution of life-history traits for individuals in the nonlinear Leslie model of age-structured population. The possibility to predict adaptation results as the values of organism's traits (properties) that provide for the maximum of a certain function of traits (optimization criterion) is studied. An ideal criterion of this type is Darwinian fitness as a characteristic of success of an individual's life history. Criticism of the optimization approach is associated with the fact that it does not take into account the changes in the environmental conditions (in a broad sense) caused by evolution, thereby leading to losses in the adequacy of the criterion. In addition, the justification for this criterion under stationary conditions is not usually rigorous. It has been suggested to overcome these objections in terms of the adaptive dynamics theory using the concept of invasive fitness. The reasons are given that favor the application of the average number of offspring for an individual, R(L), as an optimization criterion in the nonlinear Leslie model. According to the theory of quantitative genetics, the selection for fertility (that is, for a set of correlated quantitative traits determined by both multiple loci and the environment) leads to an increase in R(L). In terms of adaptive dynamics, the maximum R(L) corresponds to the evolutionary stability and, in certain cases, convergent stability of the values for traits. The search for evolutionarily stable values on the background of limited resources for reproduction is a problem of linear programming.

Data mining in soft computing framework: a survey.

PubMed

Mitra, S; Pal, S K; Mitra, P

2002-01-01

The present article provides a survey of the available literature on data mining using soft computing. A categorization has been provided based on the different soft computing tools and their hybridizations used, the data mining function implemented, and the preference criterion selected by the model. The utility of the different soft computing methodologies is highlighted. Generally fuzzy sets are suitable for handling the issues related to understandability of patterns, incomplete/noisy data, mixed media information and human interaction, and can provide approximate solutions faster. Neural networks are nonparametric, robust, and exhibit good learning and generalization capabilities in data-rich environments. Genetic algorithms provide efficient search algorithms to select a model, from mixed media data, based on some preference criterion/objective function. Rough sets are suitable for handling different types of uncertainty in data. Some challenges to data mining and the application of soft computing methodologies are indicated. An extensive bibliography is also included.

Can we use genetic and genomic approaches to identify candidate animals for targeted selective treatment.

PubMed

Laurenson, Yan C S M; Kyriazakis, Ilias; Bishop, Stephen C

2013-10-18

Estimated breeding values (EBV) for faecal egg count (FEC) and genetic markers for host resistance to nematodes may be used to identify resistant animals for selective breeding programmes. Similarly, targeted selective treatment (TST) requires the ability to identify the animals that will benefit most from anthelmintic treatment. A mathematical model was used to combine the concepts and evaluate the potential of using genetic-based methods to identify animals for a TST regime. EBVs obtained by genomic prediction were predicted to be the best determinant criterion for TST in terms of the impact on average empty body weight and average FEC, whereas pedigree-based EBVs for FEC were predicted to be marginally worse than using phenotypic FEC as a determinant criterion. Whilst each method has financial implications, if the identification of host resistance is incorporated into a wider genomic selection indices or selective breeding programmes, then genetic or genomic information may be plausibly included in TST regimes. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

Improving data analysis in herpetology: Using Akaike's information criterion (AIC) to assess the strength of biological hypotheses

USGS Publications Warehouse

Mazerolle, M.J.

2006-01-01

In ecology, researchers frequently use observational studies to explain a given pattern, such as the number of individuals in a habitat patch, with a large number of explanatory (i.e., independent) variables. To elucidate such relationships, ecologists have long relied on hypothesis testing to include or exclude variables in regression models, although the conclusions often depend on the approach used (e.g., forward, backward, stepwise selection). Though better tools have surfaced in the mid 1970's, they are still underutilized in certain fields, particularly in herpetology. This is the case of the Akaike information criterion (AIC) which is remarkably superior in model selection (i.e., variable selection) than hypothesis-based approaches. It is simple to compute and easy to understand, but more importantly, for a given data set, it provides a measure of the strength of evidence for each model that represents a plausible biological hypothesis relative to the entire set of models considered. Using this approach, one can then compute a weighted average of the estimate and standard error for any given variable of interest across all the models considered. This procedure, termed model-averaging or multimodel inference, yields precise and robust estimates. In this paper, I illustrate the use of the AIC in model selection and inference, as well as the interpretation of results analysed in this framework with two real herpetological data sets. The AIC and measures derived from it is should be routinely adopted by herpetologists. ?? Koninklijke Brill NV 2006.

Management of California Oak Woodlands: Uncertainties and Modeling

Treesearch

Jay E. Noel; Richard P. Thompson

1995-01-01

A mathematical policy model of oak woodlands is presented. The model illustrates the policy uncertainties that exist in the management of oak woodlands. These uncertainties include: (1) selection of a policy criterion function, (2) woodland dynamics, (3) initial and final state of the woodland stock. The paper provides a review of each of the uncertainty issues. The...

Heuristic Bayesian segmentation for discovery of coexpressed genes within genomic regions.

PubMed

Pehkonen, Petri; Wong, Garry; Törönen, Petri

2010-01-01

Segmentation aims to separate homogeneous areas from the sequential data, and plays a central role in data mining. It has applications ranging from finance to molecular biology, where bioinformatics tasks such as genome data analysis are active application fields. In this paper, we present a novel application of segmentation in locating genomic regions with coexpressed genes. We aim at automated discovery of such regions without requirement for user-given parameters. In order to perform the segmentation within a reasonable time, we use heuristics. Most of the heuristic segmentation algorithms require some decision on the number of segments. This is usually accomplished by using asymptotic model selection methods like the Bayesian information criterion. Such methods are based on some simplification, which can limit their usage. In this paper, we propose a Bayesian model selection to choose the most proper result from heuristic segmentation. Our Bayesian model presents a simple prior for the segmentation solutions with various segment numbers and a modified Dirichlet prior for modeling multinomial data. We show with various artificial data sets in our benchmark system that our model selection criterion has the best overall performance. The application of our method in yeast cell-cycle gene expression data reveals potential active and passive regions of the genome.

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

NASA Technical Reports Server (NTRS)

Brecher, S. M.

1972-01-01

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

Optimization of multi-environment trials for genomic selection based on crop models.

PubMed

Rincent, R; Kuhn, E; Monod, H; Oury, F-X; Rousset, M; Allard, V; Le Gouis, J

2017-08-01

We propose a statistical criterion to optimize multi-environment trials to predict genotype × environment interactions more efficiently, by combining crop growth models and genomic selection models. Genotype × environment interactions (GEI) are common in plant multi-environment trials (METs). In this context, models developed for genomic selection (GS) that refers to the use of genome-wide information for predicting breeding values of selection candidates need to be adapted. One promising way to increase prediction accuracy in various environments is to combine ecophysiological and genetic modelling thanks to crop growth models (CGM) incorporating genetic parameters. The efficiency of this approach relies on the quality of the parameter estimates, which depends on the environments composing this MET used for calibration. The objective of this study was to determine a method to optimize the set of environments composing the MET for estimating genetic parameters in this context. A criterion called OptiMET was defined to this aim, and was evaluated on simulated and real data, with the example of wheat phenology. The MET defined with OptiMET allowed estimating the genetic parameters with lower error, leading to higher QTL detection power and higher prediction accuracies. MET defined with OptiMET was on average more efficient than random MET composed of twice as many environments, in terms of quality of the parameter estimates. OptiMET is thus a valuable tool to determine optimal experimental conditions to best exploit MET and the phenotyping tools that are currently developed.

Application of linear mixed-effects model with LASSO to identify metal components associated with cardiac autonomic responses among welders: a repeated measures study

PubMed Central

Zhang, Jinming; Cavallari, Jennifer M; Fang, Shona C; Weisskopf, Marc G; Lin, Xihong; Mittleman, Murray A; Christiani, David C

2017-01-01

Background Environmental and occupational exposure to metals is ubiquitous worldwide, and understanding the hazardous metal components in this complex mixture is essential for environmental and occupational regulations. Objective To identify hazardous components from metal mixtures that are associated with alterations in cardiac autonomic responses. Methods Urinary concentrations of 16 types of metals were examined and ‘acceleration capacity’ (AC) and ‘deceleration capacity’ (DC), indicators of cardiac autonomic effects, were quantified from ECG recordings among 54 welders. We fitted linear mixed-effects models with least absolute shrinkage and selection operator (LASSO) to identify metal components that are associated with AC and DC. The Bayesian Information Criterion was used as the criterion for model selection procedures. Results Mercury and chromium were selected for DC analysis, whereas mercury, chromium and manganese were selected for AC analysis through the LASSO approach. When we fitted the linear mixed-effects models with ‘selected’ metal components only, the effect of mercury remained significant. Every 1 µg/L increase in urinary mercury was associated with −0.58 ms (−1.03, –0.13) changes in DC and 0.67 ms (0.25, 1.10) changes in AC. Conclusion Our study suggests that exposure to several metals is associated with impaired cardiac autonomic functions. Our findings should be replicated in future studies with larger sample sizes. PMID:28663305

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

Sills, Alison; Glebbeek, Evert; Chatterjee, Sourav

We created artificial color-magnitude diagrams of Monte Carlo dynamical models of globular clusters and then used observational methods to determine the number of blue stragglers in those clusters. We compared these blue stragglers to various cluster properties, mimicking work that has been done for blue stragglers in Milky Way globular clusters to determine the dominant formation mechanism(s) of this unusual stellar population. We find that a mass-based prescription for selecting blue stragglers will select approximately twice as many blue stragglers than a selection criterion that was developed for observations of real clusters. However, the two numbers of blue stragglers aremore » well-correlated, so either selection criterion can be used to characterize the blue straggler population of a cluster. We confirm previous results that the simplified prescription for the evolution of a collision or merger product in the BSE code overestimates their lifetimes. We show that our model blue stragglers follow similar trends with cluster properties (core mass, binary fraction, total mass, collision rate) as the true Milky Way blue stragglers as long as we restrict ourselves to model clusters with an initial binary fraction higher than 5%. We also show that, in contrast to earlier work, the number of blue stragglers in the cluster core does have a weak dependence on the collisional parameter Γ in both our models and in Milky Way globular clusters.« less

Selecting Items for Criterion-Referenced Tests.

ERIC Educational Resources Information Center

Mellenbergh, Gideon J.; van der Linden, Wim J.

1982-01-01

Three item selection methods for criterion-referenced tests are examined: the classical theory of item difficulty and item-test correlation; the latent trait theory of item characteristic curves; and a decision-theoretic approach for optimal item selection. Item contribution to the standardized expected utility of mastery testing is discussed. (CM)

A Permutation Approach for Selecting the Penalty Parameter in Penalized Model Selection

PubMed Central

Sabourin, Jeremy A; Valdar, William; Nobel, Andrew B

2015-01-01

Summary We describe a simple, computationally effcient, permutation-based procedure for selecting the penalty parameter in LASSO penalized regression. The procedure, permutation selection, is intended for applications where variable selection is the primary focus, and can be applied in a variety of structural settings, including that of generalized linear models. We briefly discuss connections between permutation selection and existing theory for the LASSO. In addition, we present a simulation study and an analysis of real biomedical data sets in which permutation selection is compared with selection based on the following: cross-validation (CV), the Bayesian information criterion (BIC), Scaled Sparse Linear Regression, and a selection method based on recently developed testing procedures for the LASSO. PMID:26243050

Criterion-Referenced Testing in Foreign Language Teaching.

ERIC Educational Resources Information Center

Takala, Sauli

A review of literature serves as the basis for a discussion of various aspects of criterion-referenced tests. The aspects discussed are: teaching and evaluation objectives, criterion- and norm-referenced measurement, stages in construction of criterion-referenced tests, construction and selection of items, test validity, and test reliability.…

Methods for selecting fixed-effect models for heterogeneous codon evolution, with comments on their application to gene and genome data.

PubMed

Bao, Le; Gu, Hong; Dunn, Katherine A; Bielawski, Joseph P

2007-02-08

Models of codon evolution have proven useful for investigating the strength and direction of natural selection. In some cases, a priori biological knowledge has been used successfully to model heterogeneous evolutionary dynamics among codon sites. These are called fixed-effect models, and they require that all codon sites are assigned to one of several partitions which are permitted to have independent parameters for selection pressure, evolutionary rate, transition to transversion ratio or codon frequencies. For single gene analysis, partitions might be defined according to protein tertiary structure, and for multiple gene analysis partitions might be defined according to a gene's functional category. Given a set of related fixed-effect models, the task of selecting the model that best fits the data is not trivial. In this study, we implement a set of fixed-effect codon models which allow for different levels of heterogeneity among partitions in the substitution process. We describe strategies for selecting among these models by a backward elimination procedure, Akaike information criterion (AIC) or a corrected Akaike information criterion (AICc). We evaluate the performance of these model selection methods via a simulation study, and make several recommendations for real data analysis. Our simulation study indicates that the backward elimination procedure can provide a reliable method for model selection in this setting. We also demonstrate the utility of these models by application to a single-gene dataset partitioned according to tertiary structure (abalone sperm lysin), and a multi-gene dataset partitioned according to the functional category of the gene (flagellar-related proteins of Listeria). Fixed-effect models have advantages and disadvantages. Fixed-effect models are desirable when data partitions are known to exhibit significant heterogeneity or when a statistical test of such heterogeneity is desired. They have the disadvantage of requiring a priori knowledge for partitioning sites. We recommend: (i) selection of models by using backward elimination rather than AIC or AICc, (ii) use a stringent cut-off, e.g., p = 0.0001, and (iii) conduct sensitivity analysis of results. With thoughtful application, fixed-effect codon models should provide a useful tool for large scale multi-gene analyses.

Analyzing The Uncertainty Of Diameter Growth Model Predictions

Treesearch

Ronald E. McRoberts; Veronica C. Lessard; Margaret R. Holdaway

1999-01-01

The North Central Research Station of the USDA Forest Service is developing a new set of individual tree, diameter growth models to be used as a component of an annual forest inventory system. The criterion for selection of predictor variables for these models is the uncertainty in 5-, 10-, and 20-year diameter growth predictions estimated using Monte Carlo simulations...

Identification of confounders in the assessment of the relationship between lead exposure and child development.

PubMed

Tong, I S; Lu, Y

2001-01-01

To explore the best approach to identify and adjust for confounders in epidemiologic practice. In the Port Pirie cohort study, the selection of covariates was based on both a priori and an empirical consideration. In an assessment of the relationship between exposure to environmental lead and child development, change-in-estimate (CE) and significance testing (ST) criteria were compared in identifying potential confounders. The Pearson correlation coefficients were used to evaluate the potential for collinearity between pairs of major quantitative covariates. In multivariate analyses, the effects of confounding factors were assessed with multiple linear regression models. The nature and number of covariates selected varied with different confounder selection criteria and different cutoffs. Four covariates (i.e., quality of home environment, socioeconomic status (SES), maternal intelligence, and parental smoking behaviour) met the conventional CE criterion (> or =10%), whereas 14 variables met the ST criterion (p < or = 0.25). However, the magnitude of the relationship between blood lead concentration and children's IQ differed slightly after adjustment for confounding, using either the CE (partial regression coefficient: -4.4; 95% confidence interval (CI): -0.5 to -8.3) or ST criterion (-4.3; 95% CI: -0.2 to -8.4). Identification and selection of confounding factors need to be viewed cautiously in epidemiologic studies. Either the CE (e.g., > or = 10%) or ST (e.g., p < or = 0.25) criterion may be implemented in identification of a potential confounder if a study sample is sufficiently large, and both the methods are subject to arbitrariness of selecting a cut-off point. In this study, the CE criterion (i.e., > or = 10%) appears to be more stringent than the ST method (i.e., p < or = 0.25) in the identification of confounders. However, the ST rule cannot be used to determine the trueness of confounding because it cannot reflect the causal relationship between the confounder and outcome. This study shows the complexities one can expect to encounter in the identification of and adjustment for confounders.

34 CFR 389.30 - What additional selection criterion is used under this program?

Code of Federal Regulations, 2011 CFR

2011-07-01

... 34 Education 2 2011-07-01 2010-07-01 true What additional selection criterion is used under this program? 389.30 Section 389.30 Education Regulations of the Offices of the Department of Education... CONTINUING EDUCATION PROGRAMS How Does the Secretary Make a Grant? § 389.30 What additional selection...

34 CFR 389.30 - What additional selection criterion is used under this program?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 34 Education 2 2010-07-01 2010-07-01 false What additional selection criterion is used under this program? 389.30 Section 389.30 Education Regulations of the Offices of the Department of Education... CONTINUING EDUCATION PROGRAMS How Does the Secretary Make a Grant? § 389.30 What additional selection...

Comparing simple respiration models for eddy flux and dynamic chamber data

Treesearch

Andrew D. Richardson; Bobby H. Braswell; David Y. Hollinger; Prabir Burman; Eric A. Davidson; Robert S. Evans; Lawrence B. Flanagan; J. William Munger; Kathleen Savage; Shawn P. Urbanski; Steven C. Wofsy

2006-01-01

Selection of an appropriate model for respiration (R) is important for accurate gap-filling of CO2 flux data, and for partitioning measurements of net ecosystem exchange (NEE) to respiration and gross ecosystem exchange (GEE). Using cross-validation methods and a version of Akaike's Information Criterion (AIC), we evaluate a wide range of...

Evaluation of the best fit distribution for partial duration series of daily rainfall in Madinah, western Saudi Arabia

NASA Astrophysics Data System (ADS)

Alahmadi, F.; Rahman, N. A.; Abdulrazzak, M.

2014-09-01

Rainfall frequency analysis is an essential tool for the design of water related infrastructure. It can be used to predict future flood magnitudes for a given magnitude and frequency of extreme rainfall events. This study analyses the application of rainfall partial duration series (PDS) in the vast growing urban Madinah city located in the western part of Saudi Arabia. Different statistical distributions were applied (i.e. Normal, Log Normal, Extreme Value type I, Generalized Extreme Value, Pearson Type III, Log Pearson Type III) and their distribution parameters were estimated using L-moments methods. Also, different selection criteria models are applied, e.g. Akaike Information Criterion (AIC), Corrected Akaike Information Criterion (AICc), Bayesian Information Criterion (BIC) and Anderson-Darling Criterion (ADC). The analysis indicated the advantage of Generalized Extreme Value as the best fit statistical distribution for Madinah partial duration daily rainfall series. The outcome of such an evaluation can contribute toward better design criteria for flood management, especially flood protection measures.

Fatigue Assessment of Nickel-Titanium Peripheral Stents: Comparison of Multi-Axial Fatigue Models

NASA Astrophysics Data System (ADS)

Allegretti, Dario; Berti, Francesca; Migliavacca, Francesco; Pennati, Giancarlo; Petrini, Lorenza

2018-03-01

Peripheral Nickel-Titanium (NiTi) stents exploit super-elasticity to treat femoropopliteal artery atherosclerosis. The stent is subject to cyclic loads, which may lead to fatigue fracture and treatment failure. The complexity of the loading conditions and device geometry, coupled with the nonlinear material behavior, may induce multi-axial and non-proportional deformation. Finite element analysis can assess the fatigue risk, by comparing the device state of stress with the material fatigue limit. The most suitable fatigue model is not fully understood for NiTi devices, due to its complex thermo-mechanical behavior. This paper assesses the fatigue behavior of NiTi stents through computational models and experimental validation. Four different strain-based models are considered: the von Mises criterion and three critical plane models (Fatemi-Socie, Brown-Miller, and Smith-Watson-Topper models). Two stents, made of the same material with different cell geometries are manufactured, and their fatigue behavior is experimentally characterized. The comparison between experimental and numerical results highlights an overestimation of the failure risk by the von Mises criterion. On the contrary, the selected critical plane models, even if based on different damage mechanisms, give a better fatigue life estimation. Further investigations on crack propagation mechanisms of NiTi stents are required to properly select the most reliable fatigue model.

Fatigue Assessment of Nickel-Titanium Peripheral Stents: Comparison of Multi-Axial Fatigue Models

NASA Astrophysics Data System (ADS)

Allegretti, Dario; Berti, Francesca; Migliavacca, Francesco; Pennati, Giancarlo; Petrini, Lorenza

2018-02-01

Peripheral Nickel-Titanium (NiTi) stents exploit super-elasticity to treat femoropopliteal artery atherosclerosis. The stent is subject to cyclic loads, which may lead to fatigue fracture and treatment failure. The complexity of the loading conditions and device geometry, coupled with the nonlinear material behavior, may induce multi-axial and non-proportional deformation. Finite element analysis can assess the fatigue risk, by comparing the device state of stress with the material fatigue limit. The most suitable fatigue model is not fully understood for NiTi devices, due to its complex thermo-mechanical behavior. This paper assesses the fatigue behavior of NiTi stents through computational models and experimental validation. Four different strain-based models are considered: the von Mises criterion and three critical plane models (Fatemi-Socie, Brown-Miller, and Smith-Watson-Topper models). Two stents, made of the same material with different cell geometries are manufactured, and their fatigue behavior is experimentally characterized. The comparison between experimental and numerical results highlights an overestimation of the failure risk by the von Mises criterion. On the contrary, the selected critical plane models, even if based on different damage mechanisms, give a better fatigue life estimation. Further investigations on crack propagation mechanisms of NiTi stents are required to properly select the most reliable fatigue model.

MICROPIK: A Multiple-Alternatives, Criterion-Referenced Decisioning Model for Evaluating CAI Software and Microcomputer Hardware Against Selected Curriculum Instructional Objectives. Paper and Report Series No. 73.

ERIC Educational Resources Information Center

Wholeben, Brent Edward

This report describing the use of operations research techniques to determine which courseware packages or what microcomputer systems best address varied instructional objectives focuses on the MICROPIK model, a highly structured evaluation technique for making such complex instructional decisions. MICROPIK is a multiple alternatives model (MAA)…

The role of selective predation in harmful algal blooms

NASA Astrophysics Data System (ADS)

Solé, Jordi; Garcia-Ladona, Emilio; Estrada, Marta

2006-08-01

A feature of marine plankton communities is the occurrence of rapid population explosions. When the blooming species are directly or indirectly noxious for humans, these proliferations are denoted as harmful algal blooms (HAB). The importance of biological interactions for the appearance of HABs, in particular when the proliferating microalgae produce toxins that affect other organisms in the food web, remains still poorly understood. Here we analyse the role of toxins produced by a microalgal species and affecting its predators, in determining the success of that species as a bloom former. A three-species predator-prey model is used to define a criterion that determines whether a toxic microalga will be able to initiate a bloom in competition against a non-toxic one with higher growth rate. Dominance of the toxic species depends on a critical parameter that defines the degree of feeding selectivity by grazers. The criterion is applied to a particular simplified model and to numerical simulations of a full marine ecosystem model. The results suggest that the release of toxic compounds affecting predators may be a plausible biological factor in allowing the development of HABs.

Effects of task-irrelevant grouping on visual selection in partial report.

PubMed

Lunau, Rasmus; Habekost, Thomas

2017-07-01

Perceptual grouping modulates performance in attention tasks such as partial report and change detection. Specifically, grouping of search items according to a task-relevant feature improves the efficiency of visual selection. However, the role of task-irrelevant feature grouping is not clearly understood. In the present study, we investigated whether grouping of targets by a task-irrelevant feature influences performance in a partial-report task. In this task, participants must report as many target letters as possible from a briefly presented circular display. The crucial manipulation concerned the color of the elements in these trials. In the sorted-color condition, the color of the display elements was arranged according to the selection criterion, and in the unsorted-color condition, colors were randomly assigned. The distractor cost was inferred by subtracting performance in partial-report trials from performance in a control condition that had no distractors in the display. Across five experiments, we manipulated trial order, selection criterion, and exposure duration, and found that attentional selectivity was improved in sorted-color trials when the exposure duration was 200 ms and the selection criterion was luminance. This effect was accompanied by impaired selectivity in unsorted-color trials. Overall, the results suggest that the benefit of task-irrelevant color grouping of targets is contingent on the processing locus of the selection criterion.

Shape selection criterion for cellular array during constrained growth of binary alloys - Need for low gravity experiment

NASA Technical Reports Server (NTRS)

Tewari, Surendra N.; Trivedi, Rohit

1991-01-01

Development of steady-state periodic cellular array is one of the critical problems in the study of nonlinear pattern formation during directional solidification of binary alloys. The criterion which establishes the values of cell tip radius and spacing under given growth condition is not known. Theoretical models, such as marginal stability and microscopic solvability, have been developed for purely diffusive regime. However, the experimental conditions where cellular structures are stable are precisely the ones where the convection effects are predominant. Thus, the critical data for meaningful evaluation of cellular array growth models can only be obtained by partial directional solidification and quenching experiments carried out in the low gravity environment of space.

45 CFR 1151.33 - Employment criteria.

Code of Federal Regulations, 2013 CFR

2013-10-01

... HUMANITIES NATIONAL ENDOWMENT FOR THE ARTS NONDISCRIMINATION ON THE BASIS OF HANDICAP Discrimination... or other selection criterion that screens out or tends to screen out handicapped persons or any class of handicapped persons unless: (1) The test score or other selection criterion, as used by the...

45 CFR 1151.33 - Employment criteria.

Code of Federal Regulations, 2014 CFR

2014-10-01

... HUMANITIES NATIONAL ENDOWMENT FOR THE ARTS NONDISCRIMINATION ON THE BASIS OF HANDICAP Discrimination... or other selection criterion that screens out or tends to screen out handicapped persons or any class of handicapped persons unless: (1) The test score or other selection criterion, as used by the...

45 CFR 1151.33 - Employment criteria.

Code of Federal Regulations, 2012 CFR

2012-10-01

... HUMANITIES NATIONAL ENDOWMENT FOR THE ARTS NONDISCRIMINATION ON THE BASIS OF HANDICAP Discrimination... or other selection criterion that screens out or tends to screen out handicapped persons or any class of handicapped persons unless: (1) The test score or other selection criterion, as used by the...

Evaluation of entropy and JM-distance criterions as features selection methods using spectral and spatial features derived from LANDSAT images

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Dutra, L. V.; Mascarenhas, N. D. A.; Mitsuo, Fernando Augusta, II

1984-01-01

A study area near Ribeirao Preto in Sao Paulo state was selected, with predominance in sugar cane. Eight features were extracted from the 4 original bands of LANDSAT image, using low-pass and high-pass filtering to obtain spatial features. There were 5 training sites in order to acquire the necessary parameters. Two groups of four channels were selected from 12 channels using JM-distance and entropy criterions. The number of selected channels was defined by physical restrictions of the image analyzer and computacional costs. The evaluation was performed by extracting the confusion matrix for training and tests areas, with a maximum likelihood classifier, and by defining performance indexes based on those matrixes for each group of channels. Results show that in spatial features and supervised classification, the entropy criterion is better in the sense that allows a more accurate and generalized definition of class signature. On the other hand, JM-distance criterion strongly reduces the misclassification within training areas.

Criterion- Referenced Measurement; A Bibliography.

ERIC Educational Resources Information Center

Keller, Claudia Merkel

This bibliography lists selected articles, research reports, monographs, books, and reference works related to criterion-referenced measurement. It is limited primarily to material which deals directly with criterion-referenced tests and testing procedures, and includes reports on computer-assisted test construction and the adaptation of…

MISFITS: evaluating the goodness of fit between a phylogenetic model and an alignment.

PubMed

Nguyen, Minh Anh Thi; Klaere, Steffen; von Haeseler, Arndt

2011-01-01

As models of sequence evolution become more and more complicated, many criteria for model selection have been proposed, and tools are available to select the best model for an alignment under a particular criterion. However, in many instances the selected model fails to explain the data adequately as reflected by large deviations between observed pattern frequencies and the corresponding expectation. We present MISFITS, an approach to evaluate the goodness of fit (http://www.cibiv.at/software/misfits). MISFITS introduces a minimum number of "extra substitutions" on the inferred tree to provide a biologically motivated explanation why the alignment may deviate from expectation. These extra substitutions plus the evolutionary model then fully explain the alignment. We illustrate the method on several examples and then give a survey about the goodness of fit of the selected models to the alignments in the PANDIT database.

Wavelength selection in injection-driven Hele-Shaw flows: A maximum amplitude criterion

NASA Astrophysics Data System (ADS)

Dias, Eduardo; Miranda, Jose

2013-11-01

As in most interfacial flow problems, the standard theoretical procedure to establish wavelength selection in the viscous fingering instability is to maximize the linear growth rate. However, there are important discrepancies between previous theoretical predictions and existing experimental data. In this work we perform a linear stability analysis of the radial Hele-Shaw flow system that takes into account the combined action of viscous normal stresses and wetting effects. Most importantly, we introduce an alternative selection criterion for which the selected wavelength is determined by the maximum of the interfacial perturbation amplitude. The effectiveness of such a criterion is substantiated by the significantly improved agreement between theory and experiments. We thank CNPq (Brazilian Sponsor) for financial support.

A selection criterion for patterns in reaction–diffusion systems

PubMed Central

2014-01-01

Background Alan Turing’s work in Morphogenesis has received wide attention during the past 60 years. The central idea behind his theory is that two chemically interacting diffusible substances are able to generate stable spatial patterns, provided certain conditions are met. Ever since, extensive work on several kinds of pattern-generating reaction diffusion systems has been done. Nevertheless, prediction of specific patterns is far from being straightforward, and a great deal of interest in deciphering how to generate specific patterns under controlled conditions prevails. Results Techniques allowing one to predict what kind of spatial structure will emerge from reaction–diffusion systems remain unknown. In response to this need, we consider a generalized reaction diffusion system on a planar domain and provide an analytic criterion to determine whether spots or stripes will be formed. Our criterion is motivated by the existence of an associated energy function that allows bringing in the intuition provided by phase transitions phenomena. Conclusions Our criterion is proved rigorously in some situations, generalizing well-known results for the scalar equation where the pattern selection process can be understood in terms of a potential. In more complex settings it is investigated numerically. Our work constitutes a first step towards rigorous pattern prediction in arbitrary geometries/conditions. Advances in this direction are highly applicable to the efficient design of Biotechnology and Developmental Biology experiments, as well as in simplifying the analysis of morphogenetic models. PMID:24476200

14 CFR 1251.202 - Employment criteria.

Code of Federal Regulations, 2011 CFR

2011-01-01

... HANDICAP Employment Practices § 1251.202 Employment criteria. (a) A recipient may not make use of any employment test or other selection criterion that screens out or tends to screen out handicapped persons or any class of handicapped persons unless: (1) The test score or other selection criterion, as used by...

14 CFR 1251.202 - Employment criteria.

Code of Federal Regulations, 2013 CFR

2013-01-01

... HANDICAP Employment Practices § 1251.202 Employment criteria. (a) A recipient may not make use of any employment test or other selection criterion that screens out or tends to screen out handicapped persons or any class of handicapped persons unless: (1) The test score or other selection criterion, as used by...

14 CFR 1251.202 - Employment criteria.

Code of Federal Regulations, 2010 CFR

2010-01-01

... HANDICAP Employment Practices § 1251.202 Employment criteria. (a) A recipient may not make use of any employment test or other selection criterion that screens out or tends to screen out handicapped persons or any class of handicapped persons unless: (1) The test score or other selection criterion, as used by...

14 CFR 1251.202 - Employment criteria.

Code of Federal Regulations, 2012 CFR

2012-01-01

... HANDICAP Employment Practices § 1251.202 Employment criteria. (a) A recipient may not make use of any employment test or other selection criterion that screens out or tends to screen out handicapped persons or any class of handicapped persons unless: (1) The test score or other selection criterion, as used by...

14 CFR § 1251.202 - Employment criteria.

Code of Federal Regulations, 2014 CFR

2014-01-01

... OF HANDICAP Employment Practices § 1251.202 Employment criteria. (a) A recipient may not make use of any employment test or other selection criterion that screens out or tends to screen out handicapped persons or any class of handicapped persons unless: (1) The test score or other selection criterion, as...

A new failure mechanism in thin film by collaborative fracture and delamination: Interacting duos of cracks

NASA Astrophysics Data System (ADS)

Marthelot, Joël; Bico, José; Melo, Francisco; Roman, Benoît

2015-11-01

When a thin film moderately adherent to a substrate is subjected to residual stress, the cooperation between fracture and delamination leads to unusual fracture patterns, such as spirals, alleys of crescents and various types of strips, all characterized by a robust characteristic length scale. We focus on the propagation of a duo of cracks: two fractures in the film connected by a delamination front and progressively detaching a strip. We show experimentally that the system selects an equilibrium width on the order of 25 times the thickness of the coating and independent of both fracture and adhesion energies. We investigate numerically the selection of the width and the condition for propagation by considering Griffith's criterion and the principle of local symmetry. In addition, we propose a simplified model based on the criterion of maximum of energy release rate, which provides insights of the physical mechanisms leading to these regular patterns, and predicts the effect of material properties on the selected width of the detaching strip.

Neutrality and evolvability of designed protein sequences

NASA Astrophysics Data System (ADS)

Bhattacherjee, Arnab; Biswas, Parbati

2010-07-01

The effect of foldability on protein’s evolvability is analyzed by a two-prong approach consisting of a self-consistent mean-field theory and Monte Carlo simulations. Theory and simulation models representing protein sequences with binary patterning of amino acid residues compatible with a particular foldability criteria are used. This generalized foldability criterion is derived using the high temperature cumulant expansion approximating the free energy of folding. The effect of cumulative point mutations on these designed proteins is studied under neutral condition. The robustness, protein’s ability to tolerate random point mutations is determined with a selective pressure of stability (ΔΔG) for the theory designed sequences, which are found to be more robust than that of Monte Carlo and mean-field-biased Monte Carlo generated sequences. The results show that this foldability criterion selects viable protein sequences more effectively compared to the Monte Carlo method, which has a marked effect on how the selective pressure shapes the evolutionary sequence space. These observations may impact de novo sequence design and its applications in protein engineering.

Storage Optimization of Educational System Data

ERIC Educational Resources Information Center

Boja, Catalin

2006-01-01

There are described methods used to minimize data files dimension. There are defined indicators for measuring size of files and databases. The storage optimization process is based on selecting from a multitude of data storage models the one that satisfies the propose problem objective, maximization or minimization of the optimum criterion that is…

Spotted Towhee population dynamics in a riparian restoration context

Treesearch

Stacy L. Small; Frank R., III Thompson; Geoffery R. Geupel; John Faaborg

2007-01-01

We investigated factors at multiple scales that might influence nest predation risk for Spotted Towhees (Pipilo maculates) along the Sacramento River, California, within the context of large-scale riparian habitat restoration. We used the logistic-exposure method and Akaike's information criterion (AIC) for model selection to compare predator...

Structural Identification and Comparison of Intelligent Mobile Learning Environment

ERIC Educational Resources Information Center

Upadhyay, Nitin; Agarwal, Vishnu Prakash

2007-01-01

This paper proposes a methodology using graph theory, matrix algebra and permanent function to compare different architecture (structure) design of intelligent mobile learning environment. The current work deals with the development/selection of optimum architecture (structural) model of iMLE. This can be done using the criterion as discussed in…

On the predictive information criteria for model determination in seismic hazard analysis

NASA Astrophysics Data System (ADS)

Varini, Elisa; Rotondi, Renata

2016-04-01

Many statistical tools have been developed for evaluating, understanding, and comparing models, from both frequentist and Bayesian perspectives. In particular, the problem of model selection can be addressed according to whether the primary goal is explanation or, alternatively, prediction. In the former case, the criteria for model selection are defined over the parameter space whose physical interpretation can be difficult; in the latter case, they are defined over the space of the observations, which has a more direct physical meaning. In the frequentist approaches, model selection is generally based on an asymptotic approximation which may be poor for small data sets (e.g. the F-test, the Kolmogorov-Smirnov test, etc.); moreover, these methods often apply under specific assumptions on models (e.g. models have to be nested in the likelihood ratio test). In the Bayesian context, among the criteria for explanation, the ratio of the observed marginal densities for two competing models, named Bayes Factor (BF), is commonly used for both model choice and model averaging (Kass and Raftery, J. Am. Stat. Ass., 1995). But BF does not apply to improper priors and, even when the prior is proper, it is not robust to the specification of the prior. These limitations can be extended to two famous penalized likelihood methods as the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), since they are proved to be approximations of -2log BF . In the perspective that a model is as good as its predictions, the predictive information criteria aim at evaluating the predictive accuracy of Bayesian models or, in other words, at estimating expected out-of-sample prediction error using a bias-correction adjustment of within-sample error (Gelman et al., Stat. Comput., 2014). In particular, the Watanabe criterion is fully Bayesian because it averages the predictive distribution over the posterior distribution of parameters rather than conditioning on a point estimate, but it is hardly applicable to data which are not independent given parameters (Watanabe, J. Mach. Learn. Res., 2010). A solution is given by Ando and Tsay criterion where the joint density may be decomposed into the product of the conditional densities (Ando and Tsay, Int. J. Forecast., 2010). The above mentioned criteria are global summary measures of model performance, but more detailed analysis could be required to discover the reasons for poor global performance. In this latter case, a retrospective predictive analysis is performed on each individual observation. In this study we performed the Bayesian analysis of Italian data sets by four versions of a long-term hazard model known as the stress release model (Vere-Jones, J. Physics Earth, 1978; Bebbington and Harte, Geophys. J. Int., 2003; Varini and Rotondi, Environ. Ecol. Stat., 2015). Then we illustrate the results on their performance evaluated by Bayes Factor, predictive information criteria and retrospective predictive analysis.

Convergent, discriminant, and criterion validity of DSM-5 traits.

PubMed

Yalch, Matthew M; Hopwood, Christopher J

2016-10-01

Section III of the Diagnostic and Statistical Manual of Mental Disorders (5th edi.; DSM-5; American Psychiatric Association, 2013) contains a system for diagnosing personality disorder based in part on assessing 25 maladaptive traits. Initial research suggests that this aspect of the system improves the validity and clinical utility of the Section II Model. The Computer Adaptive Test of Personality Disorder (CAT-PD; Simms et al., 2011) contains many similar traits as the DSM-5, as well as several additional traits seemingly not covered in the DSM-5. In this study we evaluate the convergent and discriminant validity between the DSM-5 traits, as assessed by the Personality Inventory for DSM-5 (PID-5; Krueger et al., 2012), and CAT-PD in an undergraduate sample, and test whether traits included in the CAT-PD but not the DSM-5 provide incremental validity in association with clinically relevant criterion variables. Results supported the convergent and discriminant validity of the PID-5 and CAT-PD scales in their assessment of 23 out of 25 DSM-5 traits. DSM-5 traits were consistently associated with 11 criterion variables, despite our having intentionally selected clinically relevant criterion constructs not directly assessed by DSM-5 traits. However, the additional CAT-PD traits provided incremental information above and beyond the DSM-5 traits for all criterion variables examined. These findings support the validity of pathological trait models in general and the DSM-5 and CAT-PD models in particular, while also suggesting that the CAT-PD may include additional traits for consideration in future iterations of the DSM-5 system. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A data driven partial ambiguity resolution: Two step success rate criterion, and its simulation demonstration

NASA Astrophysics Data System (ADS)

Hou, Yanqing; Verhagen, Sandra; Wu, Jie

2016-12-01

Ambiguity Resolution (AR) is a key technique in GNSS precise positioning. In case of weak models (i.e., low precision of data), however, the success rate of AR may be low, which may consequently introduce large errors to the baseline solution in cases of wrong fixing. Partial Ambiguity Resolution (PAR) is therefore proposed such that the baseline precision can be improved by fixing only a subset of ambiguities with high success rate. This contribution proposes a new PAR strategy, allowing to select the subset such that the expected precision gain is maximized among a set of pre-selected subsets, while at the same time the failure rate is controlled. These pre-selected subsets are supposed to obtain the highest success rate among those with the same subset size. The strategy is called Two-step Success Rate Criterion (TSRC) as it will first try to fix a relatively large subset with the fixed failure rate ratio test (FFRT) to decide on acceptance or rejection. In case of rejection, a smaller subset will be fixed and validated by the ratio test so as to fulfill the overall failure rate criterion. It is shown how the method can be practically used, without introducing a large additional computation effort. And more importantly, how it can improve (or at least not deteriorate) the availability in terms of baseline precision comparing to classical Success Rate Criterion (SRC) PAR strategy, based on a simulation validation. In the simulation validation, significant improvements are obtained for single-GNSS on short baselines with dual-frequency observations. For dual-constellation GNSS, the improvement for single-frequency observations on short baselines is very significant, on average 68%. For the medium- to long baselines, with dual-constellation GNSS the average improvement is around 20-30%.

Evaluation of Regression Models of Balance Calibration Data Using an Empirical Criterion

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert; Volden, Thomas R.

2012-01-01

An empirical criterion for assessing the significance of individual terms of regression models of wind tunnel strain gage balance outputs is evaluated. The criterion is based on the percent contribution of a regression model term. It considers a term to be significant if its percent contribution exceeds the empirical threshold of 0.05%. The criterion has the advantage that it can easily be computed using the regression coefficients of the gage outputs and the load capacities of the balance. First, a definition of the empirical criterion is provided. Then, it is compared with an alternate statistical criterion that is widely used in regression analysis. Finally, calibration data sets from a variety of balances are used to illustrate the connection between the empirical and the statistical criterion. A review of these results indicated that the empirical criterion seems to be suitable for a crude assessment of the significance of a regression model term as the boundary between a significant and an insignificant term cannot be defined very well. Therefore, regression model term reduction should only be performed by using the more universally applicable statistical criterion.

Multivariate random regression analysis for body weight and main morphological traits in genetically improved farmed tilapia (Oreochromis niloticus).

PubMed

He, Jie; Zhao, Yunfeng; Zhao, Jingli; Gao, Jin; Han, Dandan; Xu, Pao; Yang, Runqing

2017-11-02

Because of their high economic importance, growth traits in fish are under continuous improvement. For growth traits that are recorded at multiple time-points in life, the use of univariate and multivariate animal models is limited because of the variable and irregular timing of these measures. Thus, the univariate random regression model (RRM) was introduced for the genetic analysis of dynamic growth traits in fish breeding. We used a multivariate random regression model (MRRM) to analyze genetic changes in growth traits recorded at multiple time-point of genetically-improved farmed tilapia. Legendre polynomials of different orders were applied to characterize the influences of fixed and random effects on growth trajectories. The final MRRM was determined by optimizing the univariate RRM for the analyzed traits separately via penalizing adaptively the likelihood statistical criterion, which is superior to both the Akaike information criterion and the Bayesian information criterion. In the selected MRRM, the additive genetic effects were modeled by Legendre polynomials of three orders for body weight (BWE) and body length (BL) and of two orders for body depth (BD). By using the covariance functions of the MRRM, estimated heritabilities were between 0.086 and 0.628 for BWE, 0.155 and 0.556 for BL, and 0.056 and 0.607 for BD. Only heritabilities for BD measured from 60 to 140 days of age were consistently higher than those estimated by the univariate RRM. All genetic correlations between growth time-points exceeded 0.5 for either single or pairwise time-points. Moreover, correlations between early and late growth time-points were lower. Thus, for phenotypes that are measured repeatedly in aquaculture, an MRRM can enhance the efficiency of the comprehensive selection for BWE and the main morphological traits.

The effects of Georgia's Choice curricular reform model on third grade science scores on the Georgia Criterion Referenced Competency Test

NASA Astrophysics Data System (ADS)

Phemister, Art W.

The purpose of this study was to evaluate the effectiveness of the Georgia's Choice reading curriculum on third grade science scores on the Georgia Criterion Referenced Competency Test from 2002 to 2008. In assessing the effectiveness of the Georgia's Choice curriculum model this causal comparative study examined the 105 elementary schools that implemented Georgia's Choice and 105 randomly selected elementary schools that did not elect to use Georgia's Choice. The Georgia's Choice reading program used intensified instruction in an effort to increase reading levels for all students. The study used a non-equivalent control group with a pretest and posttest design to determine the effectiveness of the Georgia's Choice curriculum model. Findings indicated that third grade students in Non-Georgia's Choice schools outscored third grade students in Georgia's Choice schools across the span of the study.

VARIABLE SELECTION FOR REGRESSION MODELS WITH MISSING DATA

PubMed Central

Garcia, Ramon I.; Ibrahim, Joseph G.; Zhu, Hongtu

2009-01-01

We consider the variable selection problem for a class of statistical models with missing data, including missing covariate and/or response data. We investigate the smoothly clipped absolute deviation penalty (SCAD) and adaptive LASSO and propose a unified model selection and estimation procedure for use in the presence of missing data. We develop a computationally attractive algorithm for simultaneously optimizing the penalized likelihood function and estimating the penalty parameters. Particularly, we propose to use a model selection criterion, called the ICQ statistic, for selecting the penalty parameters. We show that the variable selection procedure based on ICQ automatically and consistently selects the important covariates and leads to efficient estimates with oracle properties. The methodology is very general and can be applied to numerous situations involving missing data, from covariates missing at random in arbitrary regression models to nonignorably missing longitudinal responses and/or covariates. Simulations are given to demonstrate the methodology and examine the finite sample performance of the variable selection procedures. Melanoma data from a cancer clinical trial is presented to illustrate the proposed methodology. PMID:20336190

Multimodel predictive system for carbon dioxide solubility in saline formation waters.

PubMed

Wang, Zan; Small, Mitchell J; Karamalidis, Athanasios K

2013-02-05

The prediction of carbon dioxide solubility in brine at conditions relevant to carbon sequestration (i.e., high temperature, pressure, and salt concentration (T-P-X)) is crucial when this technology is applied. Eleven mathematical models for predicting CO(2) solubility in brine are compared and considered for inclusion in a multimodel predictive system. Model goodness of fit is evaluated over the temperature range 304-433 K, pressure range 74-500 bar, and salt concentration range 0-7 m (NaCl equivalent), using 173 published CO(2) solubility measurements, particularly selected for those conditions. The performance of each model is assessed using various statistical methods, including the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). Different models emerge as best fits for different subranges of the input conditions. A classification tree is generated using machine learning methods to predict the best-performing model under different T-P-X subranges, allowing development of a multimodel predictive system (MMoPS) that selects and applies the model expected to yield the most accurate CO(2) solubility prediction. Statistical analysis of the MMoPS predictions, including a stratified 5-fold cross validation, shows that MMoPS outperforms each individual model and increases the overall accuracy of CO(2) solubility prediction across the range of T-P-X conditions likely to be encountered in carbon sequestration applications.

Evaluation of Pump Pulsation in Respirable Size-Selective Sampling: Part III. Investigation of European Standard Methods

PubMed Central

Soo, Jhy-Charm; Lee, Eun Gyung; Lee, Larry A.; Kashon, Michael L.; Harper, Martin

2015-01-01

Lee et al. (Evaluation of pump pulsation in respirable size-selective sampling: part I. Pulsation measurements. Ann Occup Hyg 2014a;58:60–73) introduced an approach to measure pump pulsation (PP) using a real-world sampling train, while the European Standards (EN) (EN 1232-1997 and EN 12919-1999) suggest measuring PP using a resistor in place of the sampler. The goal of this study is to characterize PP according to both EN methods and to determine the relationship of PP between the published method (Lee et al., 2014a) and the EN methods. Additional test parameters were investigated to determine whether the test conditions suggested by the EN methods were appropriate for measuring pulsations. Experiments were conducted using a factorial combination of personal sampling pumps (six medium- and two high-volumetric flow rate pumps), back pressures (six medium- and seven high-flow rate pumps), resistors (two types), tubing lengths between a pump and resistor (60 and 90 cm), and different flow rates (2 and 2.5 l min−1 for the medium- and 4.4, 10, and 11.2 l min−1 for the high-flow rate pumps). The selection of sampling pumps and the ranges of back pressure were based on measurements obtained in the previous study (Lee et al., 2014a). Among six medium-flow rate pumps, only the Gilian5000 and the Apex IS conformed to the 10% criterion specified in EN 1232-1997. Although the AirChek XR5000 exceeded the 10% limit, the average PP (10.9%) was close to the criterion. One high-flow rate pump, the Legacy (PP = 8.1%), conformed to the 10% criterion in EN 12919-1999, while the Elite12 did not (PP = 18.3%). Conducting supplemental tests with additional test parameters beyond those used in the two subject EN standards did not strengthen the characterization of PPs. For the selected test conditions, a linear regression model [PPEN = 0.014 + 0.375 × PPNIOSH (adjusted R2 = 0.871)] was developed to determine the PP relationship between the published method (Lee et al., 2014a) and the EN methods. The 25% PP criterion recommended by Lee et al. (2014a), average value derived from repetitive measurements, corresponds to 11% PPEN. The 10% pass/fail criterion in the EN Standards is not based on extensive laboratory evaluation and would unreasonably exclude at least one pump (i.e. AirChek XR5000 in this study) and, therefore, the more accurate criterion of average 11% from repetitive measurements should be substituted. This study suggests that users can measure PP using either a real-world sampling train or a resistor setup and obtain equivalent findings by applying the model herein derived. The findings of this study will be delivered to the consensus committees to be considered when those standards, including the EN 1232-1997, EN 12919-1999, and ISO 13137-2013, are revised. PMID:25053700

Problems in Criterion-Referenced Measurement. CSE Monograph Series in Evaluation, 3.

ERIC Educational Resources Information Center

Harris, Chester W., Ed.; And Others

Six essays on technical measurement problems in criterion referenced tests and four essays by psychometricians proposing solutions are presented: (1) "Criterion-Referenced Measurement" and Other Such Terms, by Marvin C. Alkin which is an overview of the first six papers; (2) Selecting Objectives and Generating Test Items for Objectives-Based…

Examinations Wash Back Effects: Challenges to the Criterion Referenced Assessment Model

ERIC Educational Resources Information Center

Mogapi, M.

2016-01-01

Examinations play a central role in the educational system due to the fact that information generated from examinations is used for a variety of purposes. Critical decisions such as selection, placement and determining the instructional effectives of a programme of study all depend on data generated from examinations. Numerous research studies…

Optimizing phonon space in the phonon-coupling model

NASA Astrophysics Data System (ADS)

Tselyaev, V.; Lyutorovich, N.; Speth, J.; Reinhard, P.-G.

2017-08-01

We present a new scheme to select the most relevant phonons in the phonon-coupling model, named here the time-blocking approximation (TBA). The new criterion, based on the phonon-nucleon coupling strengths rather than on B (E L ) values, is more selective and thus produces much smaller phonon spaces in the TBA. This is beneficial in two respects: first, it curbs the computational cost, and second, it reduces the danger of double counting in the expansion basis of the TBA. We use here the TBA in a form where the coupling strength is regularized to keep the given Hartree-Fock ground state stable. The scheme is implemented in a random-phase approximation and TBA code based on the Skyrme energy functional. We first explore carefully the cutoff dependence with the new criterion and can work out a natural (optimal) cutoff parameter. Then we use the freshly developed and tested scheme for a survey of giant resonances and low-lying collective states in six doubly magic nuclei looking also at the dependence of the results when varying the Skyrme parametrization.

Discriminative Projection Selection Based Face Image Hashing

NASA Astrophysics Data System (ADS)

Karabat, Cagatay; Erdogan, Hakan

Face image hashing is an emerging method used in biometric verification systems. In this paper, we propose a novel face image hashing method based on a new technique called discriminative projection selection. We apply the Fisher criterion for selecting the rows of a random projection matrix in a user-dependent fashion. Moreover, another contribution of this paper is to employ a bimodal Gaussian mixture model at the quantization step. Our simulation results on three different databases demonstrate that the proposed method has superior performance in comparison to previously proposed random projection based methods.

How good is crude MDL for solving the bias-variance dilemma? An empirical investigation based on Bayesian networks.

PubMed

Cruz-Ramírez, Nicandro; Acosta-Mesa, Héctor Gabriel; Mezura-Montes, Efrén; Guerra-Hernández, Alejandro; Hoyos-Rivera, Guillermo de Jesús; Barrientos-Martínez, Rocío Erandi; Gutiérrez-Fragoso, Karina; Nava-Fernández, Luis Alonso; González-Gaspar, Patricia; Novoa-del-Toro, Elva María; Aguilera-Rueda, Vicente Josué; Ameca-Alducin, María Yaneli

2014-01-01

The bias-variance dilemma is a well-known and important problem in Machine Learning. It basically relates the generalization capability (goodness of fit) of a learning method to its corresponding complexity. When we have enough data at hand, it is possible to use these data in such a way so as to minimize overfitting (the risk of selecting a complex model that generalizes poorly). Unfortunately, there are many situations where we simply do not have this required amount of data. Thus, we need to find methods capable of efficiently exploiting the available data while avoiding overfitting. Different metrics have been proposed to achieve this goal: the Minimum Description Length principle (MDL), Akaike's Information Criterion (AIC) and Bayesian Information Criterion (BIC), among others. In this paper, we focus on crude MDL and empirically evaluate its performance in selecting models with a good balance between goodness of fit and complexity: the so-called bias-variance dilemma, decomposition or tradeoff. Although the graphical interaction between these dimensions (bias and variance) is ubiquitous in the Machine Learning literature, few works present experimental evidence to recover such interaction. In our experiments, we argue that the resulting graphs allow us to gain insights that are difficult to unveil otherwise: that crude MDL naturally selects balanced models in terms of bias-variance, which not necessarily need be the gold-standard ones. We carry out these experiments using a specific model: a Bayesian network. In spite of these motivating results, we also should not overlook three other components that may significantly affect the final model selection: the search procedure, the noise rate and the sample size.

How Good Is Crude MDL for Solving the Bias-Variance Dilemma? An Empirical Investigation Based on Bayesian Networks

PubMed Central

Cruz-Ramírez, Nicandro; Acosta-Mesa, Héctor Gabriel; Mezura-Montes, Efrén; Guerra-Hernández, Alejandro; Hoyos-Rivera, Guillermo de Jesús; Barrientos-Martínez, Rocío Erandi; Gutiérrez-Fragoso, Karina; Nava-Fernández, Luis Alonso; González-Gaspar, Patricia; Novoa-del-Toro, Elva María; Aguilera-Rueda, Vicente Josué; Ameca-Alducin, María Yaneli

2014-01-01

The bias-variance dilemma is a well-known and important problem in Machine Learning. It basically relates the generalization capability (goodness of fit) of a learning method to its corresponding complexity. When we have enough data at hand, it is possible to use these data in such a way so as to minimize overfitting (the risk of selecting a complex model that generalizes poorly). Unfortunately, there are many situations where we simply do not have this required amount of data. Thus, we need to find methods capable of efficiently exploiting the available data while avoiding overfitting. Different metrics have been proposed to achieve this goal: the Minimum Description Length principle (MDL), Akaike’s Information Criterion (AIC) and Bayesian Information Criterion (BIC), among others. In this paper, we focus on crude MDL and empirically evaluate its performance in selecting models with a good balance between goodness of fit and complexity: the so-called bias-variance dilemma, decomposition or tradeoff. Although the graphical interaction between these dimensions (bias and variance) is ubiquitous in the Machine Learning literature, few works present experimental evidence to recover such interaction. In our experiments, we argue that the resulting graphs allow us to gain insights that are difficult to unveil otherwise: that crude MDL naturally selects balanced models in terms of bias-variance, which not necessarily need be the gold-standard ones. We carry out these experiments using a specific model: a Bayesian network. In spite of these motivating results, we also should not overlook three other components that may significantly affect the final model selection: the search procedure, the noise rate and the sample size. PMID:24671204

The Development of a Criterion Instrument for Counselor Selection.

ERIC Educational Resources Information Center

Remer, Rory; Sease, William

A measure of potential performance as a counselor is needed as an adjunct to the information presently employed in selection decisions. This article deals with one possible method of development of such a potential performance criterion and the steps taken, to date, in the attempt to validate it. It includes: the overall effectiveness of the…

Simulation of selected genealogies.

PubMed

Slade, P F

2000-02-01

Algorithms for generating genealogies with selection conditional on the sample configuration of n genes in one-locus, two-allele haploid and diploid models are presented. Enhanced integro-recursions using the ancestral selection graph, introduced by S. M. Krone and C. Neuhauser (1997, Theor. Popul. Biol. 51, 210-237), which is the non-neutral analogue of the coalescent, enables accessible simulation of the embedded genealogy. A Monte Carlo simulation scheme based on that of R. C. Griffiths and S. Tavaré (1996, Math. Comput. Modelling 23, 141-158), is adopted to consider the estimation of ancestral times under selection. Simulations show that selection alters the expected depth of the conditional ancestral trees, depending on a mutation-selection balance. As a consequence, branch lengths are shown to be an ineffective criterion for detecting the presence of selection. Several examples are given which quantify the effects of selection on the conditional expected time to the most recent common ancestor. Copyright 2000 Academic Press.

Variable screening via quantile partial correlation

PubMed Central

Ma, Shujie; Tsai, Chih-Ling

2016-01-01

In quantile linear regression with ultra-high dimensional data, we propose an algorithm for screening all candidate variables and subsequently selecting relevant predictors. Specifically, we first employ quantile partial correlation for screening, and then we apply the extended Bayesian information criterion (EBIC) for best subset selection. Our proposed method can successfully select predictors when the variables are highly correlated, and it can also identify variables that make a contribution to the conditional quantiles but are marginally uncorrelated or weakly correlated with the response. Theoretical results show that the proposed algorithm can yield the sure screening set. By controlling the false selection rate, model selection consistency can be achieved theoretically. In practice, we proposed using EBIC for best subset selection so that the resulting model is screening consistent. Simulation studies demonstrate that the proposed algorithm performs well, and an empirical example is presented. PMID:28943683

Modeling chlorophyll-a and dissolved oxygen concentration in tropical floodplain lakes (Paraná River, Brazil).

PubMed

Rocha, R R A; Thomaz, S M; Carvalho, P; Gomes, L C

2009-06-01

The need for prediction is widely recognized in limnology. In this study, data from 25 lakes of the Upper Paraná River floodplain were used to build models to predict chlorophyll-a and dissolved oxygen concentrations. Akaike's information criterion (AIC) was used as a criterion for model selection. Models were validated with independent data obtained in the same lakes in 2001. Predictor variables that significantly explained chlorophyll-a concentration were pH, electrical conductivity, total seston (positive correlation) and nitrate (negative correlation). This model explained 52% of chlorophyll variability. Variables that significantly explained dissolved oxygen concentration were pH, lake area and nitrate (all positive correlations); water temperature and electrical conductivity were negatively correlated with oxygen. This model explained 54% of oxygen variability. Validation with independent data showed that both models had the potential to predict algal biomass and dissolved oxygen concentration in these lakes. These findings suggest that multiple regression models are valuable and practical tools for understanding the dynamics of ecosystems and that predictive limnology may still be considered a powerful approach in aquatic ecology.

Experimental and statistical study on fracture boundary of non-irradiated Zircaloy-4 cladding tube under LOCA conditions

NASA Astrophysics Data System (ADS)

Narukawa, Takafumi; Yamaguchi, Akira; Jang, Sunghyon; Amaya, Masaki

2018-02-01

For estimating fracture probability of fuel cladding tube under loss-of-coolant accident conditions of light-water-reactors, laboratory-scale integral thermal shock tests were conducted on non-irradiated Zircaloy-4 cladding tube specimens. Then, the obtained binary data with respect to fracture or non-fracture of the cladding tube specimen were analyzed statistically. A method to obtain the fracture probability curve as a function of equivalent cladding reacted (ECR) was proposed using Bayesian inference for generalized linear models: probit, logit, and log-probit models. Then, model selection was performed in terms of physical characteristics and information criteria, a widely applicable information criterion and a widely applicable Bayesian information criterion. As a result, it was clarified that the log-probit model was the best among the three models to estimate the fracture probability in terms of the degree of prediction accuracy for both next data to be obtained and the true model. Using the log-probit model, it was shown that 20% ECR corresponded to a 5% probability level with a 95% confidence of fracture of the cladding tube specimens.

Model Selection in Systems Biology Depends on Experimental Design

PubMed Central

Silk, Daniel; Kirk, Paul D. W.; Barnes, Chris P.; Toni, Tina; Stumpf, Michael P. H.

2014-01-01

Experimental design attempts to maximise the information available for modelling tasks. An optimal experiment allows the inferred models or parameters to be chosen with the highest expected degree of confidence. If the true system is faithfully reproduced by one of the models, the merit of this approach is clear - we simply wish to identify it and the true parameters with the most certainty. However, in the more realistic situation where all models are incorrect or incomplete, the interpretation of model selection outcomes and the role of experimental design needs to be examined more carefully. Using a novel experimental design and model selection framework for stochastic state-space models, we perform high-throughput in-silico analyses on families of gene regulatory cascade models, to show that the selected model can depend on the experiment performed. We observe that experimental design thus makes confidence a criterion for model choice, but that this does not necessarily correlate with a model's predictive power or correctness. Finally, in the special case of linear ordinary differential equation (ODE) models, we explore how wrong a model has to be before it influences the conclusions of a model selection analysis. PMID:24922483

Model selection in systems biology depends on experimental design.

PubMed

Silk, Daniel; Kirk, Paul D W; Barnes, Chris P; Toni, Tina; Stumpf, Michael P H

2014-06-01

Experimental design attempts to maximise the information available for modelling tasks. An optimal experiment allows the inferred models or parameters to be chosen with the highest expected degree of confidence. If the true system is faithfully reproduced by one of the models, the merit of this approach is clear - we simply wish to identify it and the true parameters with the most certainty. However, in the more realistic situation where all models are incorrect or incomplete, the interpretation of model selection outcomes and the role of experimental design needs to be examined more carefully. Using a novel experimental design and model selection framework for stochastic state-space models, we perform high-throughput in-silico analyses on families of gene regulatory cascade models, to show that the selected model can depend on the experiment performed. We observe that experimental design thus makes confidence a criterion for model choice, but that this does not necessarily correlate with a model's predictive power or correctness. Finally, in the special case of linear ordinary differential equation (ODE) models, we explore how wrong a model has to be before it influences the conclusions of a model selection analysis.

Methodology of functionality selection for water management software and examples of its application.

PubMed

Vasilyev, K N

2013-01-01

When developing new software products and adapting existing software, project leaders have to decide which functionalities to keep, adapt or develop. They have to consider that the cost of making errors during the specification phase is extremely high. In this paper a formalised approach is proposed that considers the main criteria for selecting new software functions. The application of this approach minimises the chances of making errors in selecting the functions to apply. Based on the work on software development and support projects in the area of water resources and flood damage evaluation in economic terms at CH2M HILL (the developers of the flood modelling package ISIS), the author has defined seven criteria for selecting functions to be included in a software product. The approach is based on the evaluation of the relative significance of the functions to be included into the software product. Evaluation is achieved by considering each criterion and the weighting coefficients of each criterion in turn and applying the method of normalisation. This paper includes a description of this new approach and examples of its application in the development of new software products in the are of the water resources management.

DISCOVERING BRIGHT QUASARS AT INTERMEDIATE REDSHIFTS BASED ON OPTICAL/NEAR-INFRARED COLORS

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

Wu, Xue-Bing; Zuo, Wenwen; Yang, Jinyi

2013-10-01

The identification of quasars at intermediate redshifts (2.2 < z < 3.5) has been inefficient in most previous quasar surveys since the optical colors of quasars are similar to those of stars. The near-IR K-band excess technique has been suggested to overcome this difficulty. Our recent study also proposed to use optical/near-IR colors for selecting z < 4 quasars. To verify the effectiveness of this method, we selected a list of 105 unidentified bright targets with i ≤ 18.5 from the quasar candidates of SDSS DR6 with both SDSS ugriz optical and UKIDSS YJHK near-IR photometric data, which satisfy ourmore » proposed Y – K/g – z criterion and have photometric redshifts between 2.2 and 3.5 estimated from the nine-band SDSS-UKIDSS data. We observed 43 targets with the BFOSC instrument on the 2.16 m optical telescope at Xinglong station of the National Astronomical Observatory of China in the spring of 2012. We spectroscopically identified 36 targets as quasars with redshifts between 2.1 and 3.4. The high success rate of discovering these quasars in the SDSS spectroscopic surveyed area further demonstrates the robustness of both the Y – K/g – z selection criterion and the photometric redshift estimation technique. We also used the above criterion to investigate the possible stellar contamination rate among the quasar candidates of SDSS DR6, and found that the rate is much higher when selecting 3 < z < 3.5 quasar candidates than when selecting lower redshift candidates (z < 2.2). The significant improvement in the photometric redshift estimation when using the nine-band SDSS-UKIDSS data over the five-band SDSS data is demonstrated and a catalog of 7727 unidentified quasar candidates in SDSS DR6 selected with optical/near-IR colors and having photometric redshifts between 2.2 and 3.5 is provided. We also tested the Y – K/g – z selection criterion with the recently released SDSS-III/DR9 quasar catalog and found that 96.2% of 17,999 DR9 quasars with UKIDSS Y- and K-band data satisfy our criterion. With some available samples of red quasars and type II quasars, we find that 88% and 96.5% of these objects can be selected by the Y – K/g – z criterion, respectively, which supports our claim that using the Y – K/g – z criterion efficiently selects both unobscured and obscured quasars. We discuss the implications of our results on the ongoing and upcoming large optical and near-IR sky surveys.« less

The Anti-Resonance Criterion in Selecting Pick Systems for Fully Operational Cutting Machinery Used in Mining

NASA Astrophysics Data System (ADS)

Cheluszka, Piotr

2017-12-01

This article discusses the issue of selecting a pick system for cutting mining machinery, concerning the reduction of vibrations in the cutting system, particularly in a load-carrying structure at work. Numerical analysis was performed on a telescopic roadheader boom equipped with transverse heads. A frequency range of the boom's free vibrations with a set structure and dynamic properties were determined based on a dynamic model. The main components excited by boom vibrations, generated through the process of cutting rock, were identified. This was closely associated with the stereometry of the cutting heads. The impact on the pick system (the number of picks and their arrangement along the side of the cutting head) was determined by the intensity of the external boom load elements, especially in resonance zones. In terms of the anti-resonance criterion, an advantageous system of cutting head picks was determined as a result of the analysis undertaken. The correct selection of the pick system was ascertained based on a computer simulation of the dynamic loads and vibrations of a roadheader telescopic boom.

An Elasto-Plastic Damage Model for Rocks Based on a New Nonlinear Strength Criterion

NASA Astrophysics Data System (ADS)

Huang, Jingqi; Zhao, Mi; Du, Xiuli; Dai, Feng; Ma, Chao; Liu, Jingbo

2018-05-01

The strength and deformation characteristics of rocks are the most important mechanical properties for rock engineering constructions. A new nonlinear strength criterion is developed for rocks by combining the Hoek-Brown (HB) criterion and the nonlinear unified strength criterion (NUSC). The proposed criterion takes account of the intermediate principal stress effect against HB criterion, as well as being nonlinear in the meridian plane against NUSC. Only three parameters are required to be determined by experiments, including the two HB parameters σ c and m i . The failure surface of the proposed criterion is continuous, smooth and convex. The proposed criterion fits the true triaxial test data well and performs better than the other three existing criteria. Then, by introducing the Geological Strength Index, the proposed criterion is extended to rock masses and predicts the test data well. Finally, based on the proposed criterion, a triaxial elasto-plastic damage model for intact rock is developed. The plastic part is based on the effective stress, whose yield function is developed by the proposed criterion. For the damage part, the evolution function is assumed to have an exponential form. The performance of the constitutive model shows good agreement with the results of experimental tests.

[Individual growth modeling of the penshell Atrina maura (Bivalvia: Pinnidae) using a multi model inference approach].

PubMed

Aragón-Noriega, Eugenio Alberto

2013-09-01

Growth models of marine animals, for fisheries and/or aquaculture purposes, are based on the popular von Bertalanffy model. This tool is mostly used because its parameters are used to evaluate other fisheries models, such as yield per recruit; nevertheless, there are other alternatives (such as Gompertz, Logistic, Schnute) not yet used by fishery scientists, that may result useful depending on the studied species. The penshell Atrina maura, has been studied for fisheries or aquaculture supplies, but its individual growth has not yet been studied before. The aim of this study was to model the absolute growth of the penshell A. maura using length-age data. For this, five models were assessed to obtain growth parameters: von Bertalanffy, Gompertz, Logistic, Schnute case 1 and Schnute and Richards. The criterion used to select the best models was the Akaike information criterion, as well as the residual squared sum and R2 adjusted. To get the average asymptotic length, the multi model inference approach was used. According to Akaike information criteria, the Gompertz model better described the absolute growth of A. maura. Following the multi model inference approach the average asymptotic shell length was 218.9 mm (IC 212.3-225.5) of shell length. I concluded that the use of the multi model approach and the Akaike information criteria represented the most robust method for growth parameter estimation of A. maura and the von Bertalanffy growth model should not be selected a priori as the true model to obtain the absolute growth in bivalve mollusks like in the studied species in this paper.

Mixture Rasch model for guessing group identification

NASA Astrophysics Data System (ADS)

Siow, Hoo Leong; Mahdi, Rasidah; Siew, Eng Ling

2013-04-01

Several alternative dichotomous Item Response Theory (IRT) models have been introduced to account for guessing effect in multiple-choice assessment. The guessing effect in these models has been considered to be itemrelated. In the most classic case, pseudo-guessing in the three-parameter logistic IRT model is modeled to be the same for all the subjects but may vary across items. This is not realistic because subjects can guess worse or better than the pseudo-guessing. Derivation from the three-parameter logistic IRT model improves the situation by incorporating ability in guessing. However, it does not model non-monotone function. This paper proposes to study guessing from a subject-related aspect which is guessing test-taking behavior. Mixture Rasch model is employed to detect latent groups. A hybrid of mixture Rasch and 3-parameter logistic IRT model is proposed to model the behavior based guessing from the subjects' ways of responding the items. The subjects are assumed to simply choose a response at random. An information criterion is proposed to identify the behavior based guessing group. Results show that the proposed model selection criterion provides a promising method to identify the guessing group modeled by the hybrid model.

Are Centers for Disease Control and Prevention Guidelines for Preexposure Prophylaxis Specific Enough? Formulation of a Personalized HIV Risk Score for Pre-Exposure Prophylaxis Initiation.

PubMed

Beymer, Matthew R; Weiss, Robert E; Sugar, Catherine A; Bourque, Linda B; Gee, Gilbert C; Morisky, Donald E; Shu, Suzanne B; Javanbakht, Marjan; Bolan, Robert K

2017-01-01

Preexposure prophylaxis (PrEP) has emerged as a human immunodeficiency virus (HIV) prevention tool for populations at highest risk for HIV infection. Current US Centers for Disease Control and Prevention (CDC) guidelines for identifying PrEP candidates may not be specific enough to identify gay, bisexual, and other men who have sex with men (MSM) at the highest risk for HIV infection. We created an HIV risk score for HIV-negative MSM based on Syndemics Theory to develop a more targeted criterion for assessing PrEP candidacy. Behavioral risk assessment and HIV testing data were analyzed for HIV-negative MSM attending the Los Angeles LGBT Center between January 2009 and June 2014 (n = 9481). Syndemics Theory informed the selection of variables for a multivariable Cox proportional hazards model. Estimated coefficients were summed to create an HIV risk score, and model fit was compared between our model and CDC guidelines using the Akaike Information Criterion and Bayesian Information Criterion. Approximately 51% of MSM were above a cutpoint that we chose as an illustrative risk score to qualify for PrEP, identifying 75% of all seroconverting MSM. Our model demonstrated a better overall fit when compared with the CDC guidelines (Akaike Information Criterion Difference = 68) in addition to identifying a greater proportion of HIV infections. Current CDC PrEP guidelines should be expanded to incorporate substance use, partner-level, and other Syndemic variables that have been shown to contribute to HIV acquisition. Deployment of such personalized algorithms may better hone PrEP criteria and allow providers and their patients to make a more informed decision prior to PrEP use.

Single and multiple in-season measurements as indicators of at-harvest cotton boll damage caused by verde plant bug (Hemiptera: Miridae).

PubMed

Brewer, Michael J; Armstrong, J Scott; Parker, Roy D

2013-06-01

The ability to monitor verde plant bug, Creontiades signatus Distant (Hemiptera: Miridae), and the progression of cotton, Gossypium hirsutum L., boll responses to feeding and associated cotton boll rot provided opportunity to assess if single in-season measurements had value in evaluating at-harvest damage to bolls and if multiple in-season measurements enhanced their combined use. One in-season verde plant bug density measurement, three in-season plant injury measurements, and two at-harvest damage measurements were taken in 15 cotton fields in South Texas, 2010. Linear regression selected two measurements as potentially useful indicators of at-harvest damage: verde plant bug density (adjusted r2 = 0.68; P = 0.0004) and internal boll injury of the carpel wall (adjusted r2 = 0.72; P = 0.004). Considering use of multiple measurements, a stepwise multiple regression of the four in-season measurements selected a univariate model (verde plant bug density) using a 0.15 selection criterion (adjusted r2 = 0.74; P = 0.0002) and a bivariate model (verde plant bug density-internal boll injury) using a 0.25 selection criterion (adjusted r2 = 0.76; P = 0.0007) as indicators of at-harvest damage. In a validation using cultivar and water regime treatments experiencing low verde plant bug pressure in 2011 and 2012, the bivariate model performed better than models using verde plant bug density or internal boll injury separately. Overall, verde plant bug damaging cotton bolls exemplified the benefits of using multiple in-season measurements in pest monitoring programs, under the challenging situation when at-harvest damage results from a sequence of plant responses initiated by in-season insect feeding.

Assessing the formability of metallic sheets by means of localized and diffuse necking models

NASA Astrophysics Data System (ADS)

Comşa, Dan-Sorin; Lǎzǎrescu, Lucian; Banabic, Dorel

2016-10-01

The main objective of the paper consists in elaborating a unified framework that allows the theoretical assessment of sheet metal formability. Hill's localized necking model and the Extended Maximum Force Criterion proposed by Mattiasson, Sigvant, and Larsson have been selected for this purpose. Both models are thoroughly described together with their solution procedures. A comparison of the theoretical predictions with experimental data referring to the formability of a DP600 steel sheet is also presented by the authors.

Observational constraints on Hubble parameter in viscous generalized Chaplygin gas

NASA Astrophysics Data System (ADS)

Thakur, P.

2018-04-01

Cosmological model with viscous generalized Chaplygin gas (in short, VGCG) is considered here to determine observational constraints on its equation of state parameters (in short, EoS) from background data. These data consists of H(z)-z (OHD) data, Baryonic Acoustic Oscillations peak parameter, CMB shift parameter and SN Ia data (Union 2.1). Best-fit values of the EoS parameters including present Hubble parameter (H0) and their acceptable range at different confidence limits are determined. In this model the permitted range for the present Hubble parameter and the transition redshift (zt) at 1σ confidence limits are H0= 70.24^{+0.34}_{-0.36} and zt=0.76^{+0.07}_{-0.07} respectively. These EoS parameters are then compared with those of other models. Present age of the Universe (t0) have also been determined here. Akaike information criterion and Bayesian information criterion for the model selection have been adopted for comparison with other models. It is noted that VGCG model satisfactorily accommodates the present accelerating phase of the Universe.

Using a latent variable model with non-constant factor loadings to examine PM2.5 constituents related to secondary inorganic aerosols.

PubMed

Zhang, Zhenzhen; O'Neill, Marie S; Sánchez, Brisa N

2016-04-01

Factor analysis is a commonly used method of modelling correlated multivariate exposure data. Typically, the measurement model is assumed to have constant factor loadings. However, from our preliminary analyses of the Environmental Protection Agency's (EPA's) PM 2.5 fine speciation data, we have observed that the factor loadings for four constituents change considerably in stratified analyses. Since invariance of factor loadings is a prerequisite for valid comparison of the underlying latent variables, we propose a factor model that includes non-constant factor loadings that change over time and space using P-spline penalized with the generalized cross-validation (GCV) criterion. The model is implemented using the Expectation-Maximization (EM) algorithm and we select the multiple spline smoothing parameters by minimizing the GCV criterion with Newton's method during each iteration of the EM algorithm. The algorithm is applied to a one-factor model that includes four constituents. Through bootstrap confidence bands, we find that the factor loading for total nitrate changes across seasons and geographic regions.

Determine the optimal carrier selection for a logistics network based on multi-commodity reliability criterion

NASA Astrophysics Data System (ADS)

Lin, Yi-Kuei; Yeh, Cheng-Ta

2013-05-01

From the perspective of supply chain management, the selected carrier plays an important role in freight delivery. This article proposes a new criterion of multi-commodity reliability and optimises the carrier selection based on such a criterion for logistics networks with routes and nodes, over which multiple commodities are delivered. Carrier selection concerns the selection of exactly one carrier to deliver freight on each route. The capacity of each carrier has several available values associated with a probability distribution, since some of a carrier's capacity may be reserved for various orders. Therefore, the logistics network, given any carrier selection, is a multi-commodity multi-state logistics network. Multi-commodity reliability is defined as a probability that the logistics network can satisfy a customer's demand for various commodities, and is a performance indicator for freight delivery. To solve this problem, this study proposes an optimisation algorithm that integrates genetic algorithm, minimal paths and Recursive Sum of Disjoint Products. A practical example in which multi-sized LCD monitors are delivered from China to Germany is considered to illustrate the solution procedure.

Color filter array design based on a human visual model

NASA Astrophysics Data System (ADS)

Parmar, Manu; Reeves, Stanley J.

2004-05-01

To reduce cost and complexity associated with registering multiple color sensors, most consumer digital color cameras employ a single sensor. A mosaic of color filters is overlaid on a sensor array such that only one color channel is sampled per pixel location. The missing color values must be reconstructed from available data before the image is displayed. The quality of the reconstructed image depends fundamentally on the array pattern and the reconstruction technique. We present a design method for color filter array patterns that use red, green, and blue color channels in an RGB array. A model of the human visual response for luminance and opponent chrominance channels is used to characterize the perceptual error between a fully sampled and a reconstructed sparsely-sampled image. Demosaicking is accomplished using Wiener reconstruction. To ensure that the error criterion reflects perceptual effects, reconstruction is done in a perceptually uniform color space. A sequential backward selection algorithm is used to optimize the error criterion to obtain the sampling arrangement. Two different types of array patterns are designed: non-periodic and periodic arrays. The resulting array patterns outperform commonly used color filter arrays in terms of the error criterion.

Quantitative Rheological Model Selection

NASA Astrophysics Data System (ADS)

Freund, Jonathan; Ewoldt, Randy

2014-11-01

The more parameters in a rheological the better it will reproduce available data, though this does not mean that it is necessarily a better justified model. Good fits are only part of model selection. We employ a Bayesian inference approach that quantifies model suitability by balancing closeness to data against both the number of model parameters and their a priori uncertainty. The penalty depends upon prior-to-calibration expectation of the viable range of values that model parameters might take, which we discuss as an essential aspect of the selection criterion. Models that are physically grounded are usually accompanied by tighter physical constraints on their respective parameters. The analysis reflects a basic principle: models grounded in physics can be expected to enjoy greater generality and perform better away from where they are calibrated. In contrast, purely empirical models can provide comparable fits, but the model selection framework penalizes their a priori uncertainty. We demonstrate the approach by selecting the best-justified number of modes in a Multi-mode Maxwell description of PVA-Borax. We also quantify relative merits of the Maxwell model relative to powerlaw fits and purely empirical fits for PVA-Borax, a viscoelastic liquid, and gluten.

Recurrent personality dimensions in inclusive lexical studies: indications for a big six structure.

PubMed

Saucier, Gerard

2009-10-01

Previous evidence for both the Big Five and the alternative six-factor model has been drawn from lexical studies with relatively narrow selections of attributes. This study examined factors from previous lexical studies using a wider selection of attributes in 7 languages (Chinese, English, Filipino, Greek, Hebrew, Spanish, and Turkish) and found 6 recurrent factors, each with common conceptual content across most of the studies. The previous narrow-selection-based six-factor model outperformed the Big Five in capturing the content of the 6 recurrent wideband factors. Adjective markers of the 6 recurrent wideband factors showed substantial incremental prediction of important criterion variables over and above the Big Five. Correspondence between wideband 6 and narrowband 6 factors indicate they are variants of a "Big Six" model that is more general across variable-selection procedures and may be more general across languages and populations.

A Model for Estimating the Reliability and Validity of Criterion-Referenced Measures.

ERIC Educational Resources Information Center

Edmonston, Leon P.; Randall, Robert S.

A decision model designed to determine the reliability and validity of criterion referenced measures (CRMs) is presented. General procedures which pertain to the model are discussed as to: Measures of relationship, Reliability, Validity (content, criterion-oriented, and construct validation), and Item Analysis. The decision model is presented in…

Evaluation of pump pulsation in respirable size-selective sampling: Part III. Investigation of European standard methods.

PubMed

Soo, Jhy-Charm; Lee, Eun Gyung; Lee, Larry A; Kashon, Michael L; Harper, Martin

2014-10-01

Lee et al. (Evaluation of pump pulsation in respirable size-selective sampling: part I. Pulsation measurements. Ann Occup Hyg 2014a;58:60-73) introduced an approach to measure pump pulsation (PP) using a real-world sampling train, while the European Standards (EN) (EN 1232-1997 and EN 12919-1999) suggest measuring PP using a resistor in place of the sampler. The goal of this study is to characterize PP according to both EN methods and to determine the relationship of PP between the published method (Lee et al., 2014a) and the EN methods. Additional test parameters were investigated to determine whether the test conditions suggested by the EN methods were appropriate for measuring pulsations. Experiments were conducted using a factorial combination of personal sampling pumps (six medium- and two high-volumetric flow rate pumps), back pressures (six medium- and seven high-flow rate pumps), resistors (two types), tubing lengths between a pump and resistor (60 and 90 cm), and different flow rates (2 and 2.5 l min(-1) for the medium- and 4.4, 10, and 11.2 l min(-1) for the high-flow rate pumps). The selection of sampling pumps and the ranges of back pressure were based on measurements obtained in the previous study (Lee et al., 2014a). Among six medium-flow rate pumps, only the Gilian5000 and the Apex IS conformed to the 10% criterion specified in EN 1232-1997. Although the AirChek XR5000 exceeded the 10% limit, the average PP (10.9%) was close to the criterion. One high-flow rate pump, the Legacy (PP=8.1%), conformed to the 10% criterion in EN 12919-1999, while the Elite12 did not (PP=18.3%). Conducting supplemental tests with additional test parameters beyond those used in the two subject EN standards did not strengthen the characterization of PPs. For the selected test conditions, a linear regression model [PPEN=0.014+0.375×PPNIOSH (adjusted R2=0.871)] was developed to determine the PP relationship between the published method (Lee et al., 2014a) and the EN methods. The 25% PP criterion recommended by Lee et al. (2014a), average value derived from repetitive measurements, corresponds to 11% PPEN. The 10% pass/fail criterion in the EN Standards is not based on extensive laboratory evaluation and would unreasonably exclude at least one pump (i.e. AirChek XR5000 in this study) and, therefore, the more accurate criterion of average 11% from repetitive measurements should be substituted. This study suggests that users can measure PP using either a real-world sampling train or a resistor setup and obtain equivalent findings by applying the model herein derived. The findings of this study will be delivered to the consensus committees to be considered when those standards, including the EN 1232-1997, EN 12919-1999, and ISO 13137-2013, are revised. Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2014.

Polynomial order selection in random regression models via penalizing adaptively the likelihood.

PubMed

Corrales, J D; Munilla, S; Cantet, R J C

2015-08-01

Orthogonal Legendre polynomials (LP) are used to model the shape of additive genetic and permanent environmental effects in random regression models (RRM). Frequently, the Akaike (AIC) and the Bayesian (BIC) information criteria are employed to select LP order. However, it has been theoretically shown that neither AIC nor BIC is simultaneously optimal in terms of consistency and efficiency. Thus, the goal was to introduce a method, 'penalizing adaptively the likelihood' (PAL), as a criterion to select LP order in RRM. Four simulated data sets and real data (60,513 records, 6675 Colombian Holstein cows) were employed. Nested models were fitted to the data, and AIC, BIC and PAL were calculated for all of them. Results showed that PAL and BIC identified with probability of one the true LP order for the additive genetic and permanent environmental effects, but AIC tended to favour over parameterized models. Conversely, when the true model was unknown, PAL selected the best model with higher probability than AIC. In the latter case, BIC never favoured the best model. To summarize, PAL selected a correct model order regardless of whether the 'true' model was within the set of candidates. © 2015 Blackwell Verlag GmbH.

Method for Automatic Selection of Parameters in Normal Tissue Complication Probability Modeling.

PubMed

Christophides, Damianos; Appelt, Ane L; Gusnanto, Arief; Lilley, John; Sebag-Montefiore, David

2018-07-01

To present a fully automatic method to generate multiparameter normal tissue complication probability (NTCP) models and compare its results with those of a published model, using the same patient cohort. Data were analyzed from 345 rectal cancer patients treated with external radiation therapy to predict the risk of patients developing grade 1 or ≥2 cystitis. In total, 23 clinical factors were included in the analysis as candidate predictors of cystitis. Principal component analysis was used to decompose the bladder dose-volume histogram into 8 principal components, explaining more than 95% of the variance. The data set of clinical factors and principal components was divided into training (70%) and test (30%) data sets, with the training data set used by the algorithm to compute an NTCP model. The first step of the algorithm was to obtain a bootstrap sample, followed by multicollinearity reduction using the variance inflation factor and genetic algorithm optimization to determine an ordinal logistic regression model that minimizes the Bayesian information criterion. The process was repeated 100 times, and the model with the minimum Bayesian information criterion was recorded on each iteration. The most frequent model was selected as the final "automatically generated model" (AGM). The published model and AGM were fitted on the training data sets, and the risk of cystitis was calculated. The 2 models had no significant differences in predictive performance, both for the training and test data sets (P value > .05) and found similar clinical and dosimetric factors as predictors. Both models exhibited good explanatory performance on the training data set (P values > .44), which was reduced on the test data sets (P values < .05). The predictive value of the AGM is equivalent to that of the expert-derived published model. It demonstrates potential in saving time, tackling problems with a large number of parameters, and standardizing variable selection in NTCP modeling. Crown Copyright © 2018. Published by Elsevier Inc. All rights reserved.

Prediction of Fracture Initiation in Hot Compression of Burn-Resistant Ti-35V-15Cr-0.3Si-0.1C Alloy

NASA Astrophysics Data System (ADS)

Zhang, Saifei; Zeng, Weidong; Zhou, Dadi; Lai, Yunjin

2015-11-01

An important concern in hot working of metals is whether the desired deformation can be accomplished without fracture of the material. This paper builds a fracture prediction model to predict fracture initiation in hot compression of a burn-resistant beta-stabilized titanium alloy Ti-35V-15Cr-0.3Si-0.1C using a combined approach of upsetting experiments, theoretical failure criteria and finite element (FE) simulation techniques. A series of isothermal compression experiments on cylindrical specimens were conducted in temperature range of 900-1150 °C, strain rate of 0.01-10 s-1 first to obtain fracture samples and primary reduction data. Based on that, a comparison of eight commonly used theoretical failure criteria was made and Oh criterion was selected and coded into a subroutine. FE simulation of upsetting experiments on cylindrical specimens was then performed to determine the fracture threshold values of Oh criterion. By building a correlation between threshold values and the deforming parameters (temperature and strain rate, or Zener-Hollomon parameter), a new fracture prediction model based on Oh criterion was established. The new model shows an exponential decay relationship between threshold values and Zener-Hollomon parameter (Z), and the relative error of the model is less than 15%. This model was then applied successfully in the cogging of Ti-35V-15Cr-0.3Si-0.1C billet.

Crystallization of Stretched Polyimides: A Structure-Property Study

NASA Technical Reports Server (NTRS)

Hinkley, Jeffrey A.; Dezern, James F.

2002-01-01

A simple rotational isomeric state model was used to detect the degree to which polyimide repeat units might align to give an extended crystal. It was found experimentally that the hallmarks of stretch-crystallization were more likely to occur in materials whose molecules could readily give extended, aligned conformations. A proposed screening criterion was 84% accurate in selecting crystallizing molecules.

A Brief Measure of Narcissism Among Female Juvenile Delinquents and Community Youths: The Narcissistic Personality Inventory-13.

PubMed

Pechorro, Pedro; Maroco, João; Ray, James V; Gonçalves, Rui Abrunhosa; Nunes, Cristina

2018-06-01

Research on narcissism has a long tradition, but there is limited knowledge regarding its application among female youth, especially for forensic samples of incarcerated female youth. Drawing on 377 female adolescents (103 selected from forensic settings and 274 selected from school settings) from Portugal, the current study is the first to examine simultaneously the psychometric properties of a brief version of the Narcissistic Personality Inventory (NPI-13) among females drawn from incarcerated and community settings. The results support the three-factor structure model of narcissism after the removal of one item due to its low factor loading. Internal consistency, convergent validity, and discriminant validity showed promising results. In terms of criterion-related validity, significant associations were found with criterion-related variables such as age of criminal onset, conduct disorder, crime severity, violent crimes, and alcohol and drug use. The findings provide support for use of the NPI-13 among female juveniles.

Bayesian transformation cure frailty models with multivariate failure time data.

PubMed

Yin, Guosheng

2008-12-10

We propose a class of transformation cure frailty models to accommodate a survival fraction in multivariate failure time data. Established through a general power transformation, this family of cure frailty models includes the proportional hazards and the proportional odds modeling structures as two special cases. Within the Bayesian paradigm, we obtain the joint posterior distribution and the corresponding full conditional distributions of the model parameters for the implementation of Gibbs sampling. Model selection is based on the conditional predictive ordinate statistic and deviance information criterion. As an illustration, we apply the proposed method to a real data set from dentistry.

The Counselor Evaluation Rating Scale: A Valid Criterion of Counselor Effectiveness?

ERIC Educational Resources Information Center

Jones, Lawrence K.

1974-01-01

The validity of recent recommendations regarding the use of certain factors of the 16 Personality Factor Questionnaire (16PF) to select persons for counselor training programs, where the CERS was the criterion measure, is challenged. (Author)

An Interoperability Consideration in Selecting Domain Parameters for Elliptic Curve Cryptography

NASA Technical Reports Server (NTRS)

Ivancic, Will (Technical Monitor); Eddy, Wesley M.

2005-01-01

Elliptic curve cryptography (ECC) will be an important technology for electronic privacy and authentication in the near future. There are many published specifications for elliptic curve cryptosystems, most of which contain detailed descriptions of the process for the selection of domain parameters. Selecting strong domain parameters ensures that the cryptosystem is robust to attacks. Due to a limitation in several published algorithms for doubling points on elliptic curves, some ECC implementations may produce incorrect, inconsistent, and incompatible results if domain parameters are not carefully chosen under a criterion that we describe. Few documents specify the addition or doubling of points in such a manner as to avoid this problematic situation. The safety criterion we present is not listed in any ECC specification we are aware of, although several other guidelines for domain selection are discussed in the literature. We provide a simple example of how a set of domain parameters not meeting this criterion can produce catastrophic results, and outline a simple means of testing curve parameters for interoperable safety over doubling.

A comparison of peer video modeling and self video modeling to teach textual responses in children with autism.

PubMed

Marcus, Alonna; Wilder, David A

2009-01-01

Peer video modeling was compared to self video modeling to teach 3 children with autism to respond appropriately to (i.e., identify or label) novel letters. A combination multiple baseline and multielement design was used to compare the two procedures. Results showed that all 3 participants met the mastery criterion in the self-modeling condition, whereas only 1 of the participants met the mastery criterion in the peer-modeling condition. In addition, the participant who met the mastery criterion in both conditions reached the criterion more quickly in the self-modeling condition. Results are discussed in terms of their implications for teaching new skills to children with autism.

Mutual information criterion for feature selection with application to classification of breast microcalcifications

NASA Astrophysics Data System (ADS)

Diamant, Idit; Shalhon, Moran; Goldberger, Jacob; Greenspan, Hayit

2016-03-01

Classification of clustered breast microcalcifications into benign and malignant categories is an extremely challenging task for computerized algorithms and expert radiologists alike. In this paper we present a novel method for feature selection based on mutual information (MI) criterion for automatic classification of microcalcifications. We explored the MI based feature selection for various texture features. The proposed method was evaluated on a standardized digital database for screening mammography (DDSM). Experimental results demonstrate the effectiveness and the advantage of using the MI-based feature selection to obtain the most relevant features for the task and thus to provide for improved performance as compared to using all features.

The latent structure of personality functioning: Investigating criterion a from the alternative model for personality disorders in DSM-5.

PubMed

Zimmermann, Johannes; Böhnke, Jan R; Eschstruth, Rhea; Mathews, Alessa; Wenzel, Kristin; Leising, Daniel

2015-08-01

The alternative model for the classification of personality disorders (PD) in the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5) Section III comprises 2 major components: impairments in personality functioning (Criterion A) and maladaptive personality traits (Criterion B). In this study, we investigated the latent structure of Criterion A (a) within subdomains, (b) across subdomains, and (c) in conjunction with the Criterion B trait facets. Data were gathered as part of an online study that collected other-ratings by 515 laypersons and 145 therapists. Laypersons were asked to assess 1 of their personal acquaintances, whereas therapists were asked to assess 1 of their patients, using 135 items that captured features of Criteria A and B. We were able to show that (a) the structure within the Criterion A subdomains can be appropriately modeled using generalized graded unfolding models, with results suggesting that the items are indeed related to common underlying constructs but often deviate from their theoretically expected severity level; (b) the structure across subdomains is broadly in line with a model comprising 2 strongly correlated factors of self- and interpersonal functioning, with some notable deviations from the theoretical model; and (c) the joint structure of the Criterion A subdomains and the Criterion B facets broadly resembles the expected model of 2 plus 5 factors, albeit the loading pattern suggests that the distinction between Criteria A and B is somewhat blurry. Our findings provide support for several major assumptions of the alternative DSM-5 model for PD but also highlight aspects of the model that need to be further refined. (c) 2015 APA, all rights reserved).

Copula based flexible modeling of associations between clustered event times.

PubMed

Geerdens, Candida; Claeskens, Gerda; Janssen, Paul

2016-07-01

Multivariate survival data are characterized by the presence of correlation between event times within the same cluster. First, we build multi-dimensional copulas with flexible and possibly symmetric dependence structures for such data. In particular, clustered right-censored survival data are modeled using mixtures of max-infinitely divisible bivariate copulas. Second, these copulas are fit by a likelihood approach where the vast amount of copula derivatives present in the likelihood is approximated by finite differences. Third, we formulate conditions for clustered right-censored survival data under which an information criterion for model selection is either weakly consistent or consistent. Several of the familiar selection criteria are included. A set of four-dimensional data on time-to-mastitis is used to demonstrate the developed methodology.

An efficient adaptive sampling strategy for global surrogate modeling with applications in multiphase flow simulation

NASA Astrophysics Data System (ADS)

Mo, S.; Lu, D.; Shi, X.; Zhang, G.; Ye, M.; Wu, J.

2016-12-01

Surrogate models have shown remarkable computational efficiency in hydrological simulations involving design space exploration, sensitivity analysis, uncertainty quantification, etc. The central task of constructing a global surrogate models is to achieve a prescribed approximation accuracy with as few original model executions as possible, which requires a good design strategy to optimize the distribution of data points in the parameter domains and an effective stopping criterion to automatically terminate the design process when desired approximation accuracy is achieved. This study proposes a novel adaptive sampling strategy, which starts from a small number of initial samples and adaptively selects additional samples by balancing the collection in unexplored regions and refinement in interesting areas. We define an efficient and effective evaluation metric basing on Taylor expansion to select the most promising potential samples from candidate points, and propose a robust stopping criterion basing on the approximation accuracy at new points to guarantee the achievement of desired accuracy. The numerical results of several benchmark analytical functions indicate that the proposed approach is more computationally efficient and robust than the widely used maximin distance design and two other well-known adaptive sampling strategies. The application to two complicated multiphase flow problems further demonstrates the efficiency and effectiveness of our method in constructing global surrogate models for high-dimensional and highly nonlinear problems. Acknowledgements: This work was financially supported by the National Nature Science Foundation of China grants No. 41030746 and 41172206.

Modeling Dark Energy Through AN Ising Fluid with Network Interactions

NASA Astrophysics Data System (ADS)

Luongo, Orlando; Tommasini, Damiano

2014-12-01

We show that the dark energy (DE) effects can be modeled by using an Ising perfect fluid with network interactions, whose low redshift equation of state (EoS), i.e. ω0, becomes ω0 = -1 as in the ΛCDM model. In our picture, DE is characterized by a barotropic fluid on a lattice in the equilibrium configuration. Thus, mimicking the spin interaction by replacing the spin variable with an occupational number, the pressure naturally becomes negative. We find that the corresponding EoS mimics the effects of a variable DE term, whose limiting case reduces to the cosmological constant Λ. This permits us to avoid the introduction of a vacuum energy as DE source by hand, alleviating the coincidence and fine tuning problems. We find fairly good cosmological constraints, by performing three tests with supernovae Ia (SNeIa), baryonic acoustic oscillation (BAO) and cosmic microwave background (CMB) measurements. Finally, we perform the Akaike information criterion (AIC) and Bayesian information criterion (BIC) selection criteria, showing that our model is statistically favored with respect to the Chevallier-Polarsky-Linder (CPL) parametrization.

A COMPARISON OF PEER VIDEO MODELING AND SELF VIDEO MODELING TO TEACH TEXTUAL RESPONSES IN CHILDREN WITH AUTISM

PubMed Central

Marcus, Alonna; Wilder, David A

2009-01-01

Peer video modeling was compared to self video modeling to teach 3 children with autism to respond appropriately to (i.e., identify or label) novel letters. A combination multiple baseline and multielement design was used to compare the two procedures. Results showed that all 3 participants met the mastery criterion in the self-modeling condition, whereas only 1 of the participants met the mastery criterion in the peer-modeling condition. In addition, the participant who met the mastery criterion in both conditions reached the criterion more quickly in the self-modeling condition. Results are discussed in terms of their implications for teaching new skills to children with autism. PMID:19949521

A D-vine copula-based model for repeated measurements extending linear mixed models with homogeneous correlation structure.

PubMed

Killiches, Matthias; Czado, Claudia

2018-03-22

We propose a model for unbalanced longitudinal data, where the univariate margins can be selected arbitrarily and the dependence structure is described with the help of a D-vine copula. We show that our approach is an extremely flexible extension of the widely used linear mixed model if the correlation is homogeneous over the considered individuals. As an alternative to joint maximum-likelihood a sequential estimation approach for the D-vine copula is provided and validated in a simulation study. The model can handle missing values without being forced to discard data. Since conditional distributions are known analytically, we easily make predictions for future events. For model selection, we adjust the Bayesian information criterion to our situation. In an application to heart surgery data our model performs clearly better than competing linear mixed models. © 2018, The International Biometric Society.

Blunt Criterion trauma model for head and chest injury risk assessment of cal. 380 R and cal. 22 long blank cartridge actuated gundog retrieval devices.

PubMed

Frank, Matthias; Bockholdt, Britta; Peters, Dieter; Lange, Joern; Grossjohann, Rico; Ekkernkamp, Axel; Hinz, Peter

2011-05-20

Blunt ballistic impact trauma is a current research topic due to the widespread use of kinetic energy munitions in law enforcement. In the civilian setting, an automatic dummy launcher has recently been identified as source of blunt impact trauma. However, there is no data on the injury risk of conventional dummy launchers. It is the aim of this investigation to predict potential impact injury to the human head and chest on the basis of the Blunt Criterion which is an energy based blunt trauma model to assess vulnerability to blunt weapons, projectile impacts, and behind-armor-exposures. Based on experimentally investigated kinetic parameters, the injury risk of two commercially available gundog retrieval devices (Waidwerk Telebock, Germany; Turner Richards, United Kingdom) was assessed using the Blunt Criterion trauma model for blunt ballistic impact trauma to the head and chest. Assessing chest impact, the Blunt Criterion values for both shooting devices were higher than the critical Blunt Criterion value of 0.37, which represents a 50% risk of sustaining a thoracic skeletal injury of AIS 2 (moderate injury) or AIS 3 (serious injury). The maximum Blunt Criterion value (1.106) was higher than the Blunt Criterion value corresponding to AIS 4 (severe injury). With regard to the impact injury risk to the head, both devices surpass by far the critical Blunt Criterion value of 1.61, which represents a 50% risk of skull fracture. Highest Blunt Criterion values were measured for the Turner Richards Launcher (2.884) corresponding to a risk of skull fracture of higher than 80%. Even though the classification as non-guns by legal authorities might implicate harmlessness, the Blunt Criterion trauma model illustrates the hazardous potential of these shooting devices. The Blunt Criterion trauma model links the laboratory findings to the impact injury patterns of the head and chest that might be expected. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Industry Software Trustworthiness Criterion Research Based on Business Trustworthiness

NASA Astrophysics Data System (ADS)

Zhang, Jin; Liu, Jun-fei; Jiao, Hai-xing; Shen, Yi; Liu, Shu-yuan

To industry software Trustworthiness problem, an idea aiming to business to construct industry software trustworthiness criterion is proposed. Based on the triangle model of "trustworthy grade definition-trustworthy evidence model-trustworthy evaluating", the idea of business trustworthiness is incarnated from different aspects of trustworthy triangle model for special industry software, power producing management system (PPMS). Business trustworthiness is the center in the constructed industry trustworthy software criterion. Fusing the international standard and industry rules, the constructed trustworthy criterion strengthens the maneuverability and reliability. Quantitive evaluating method makes the evaluating results be intuitionistic and comparable.

An optimal strategy for functional mapping of dynamic trait loci.

PubMed

Jin, Tianbo; Li, Jiahan; Guo, Ying; Zhou, Xiaojing; Yang, Runqing; Wu, Rongling

2010-02-01

As an emerging powerful approach for mapping quantitative trait loci (QTLs) responsible for dynamic traits, functional mapping models the time-dependent mean vector with biologically meaningful equations and are likely to generate biologically relevant and interpretable results. Given the autocorrelation nature of a dynamic trait, functional mapping needs the implementation of the models for the structure of the covariance matrix. In this article, we have provided a comprehensive set of approaches for modelling the covariance structure and incorporated each of these approaches into the framework of functional mapping. The Bayesian information criterion (BIC) values are used as a model selection criterion to choose the optimal combination of the submodels for the mean vector and covariance structure. In an example for leaf age growth from a rice molecular genetic project, the best submodel combination was found between the Gaussian model for the correlation structure, power equation of order 1 for the variance and the power curve for the mean vector. Under this combination, several significant QTLs for leaf age growth trajectories were detected on different chromosomes. Our model can be well used to study the genetic architecture of dynamic traits of agricultural values.

Selecting among competing models of electro-optic, infrared camera system range performance

USGS Publications Warehouse

Nichols, Jonathan M.; Hines, James E.; Nichols, James D.

2013-01-01

Range performance is often the key requirement around which electro-optical and infrared camera systems are designed. This work presents an objective framework for evaluating competing range performance models. Model selection based on the Akaike’s Information Criterion (AIC) is presented for the type of data collected during a typical human observer and target identification experiment. These methods are then demonstrated on observer responses to both visible and infrared imagery in which one of three maritime targets was placed at various ranges. We compare the performance of a number of different models, including those appearing previously in the literature. We conclude that our model-based approach offers substantial improvements over the traditional approach to inference, including increased precision and the ability to make predictions for some distances other than the specific set for which experimental trials were conducted.

Vortex Advisory System : Volume 1. Effectiveness for Selected Airports.

DOT National Transportation Integrated Search

1980-05-01

The Vortex Advisory System (VAS) is based on wind criterion--when the wind near the runway end is outside of the criterion, all interarrival Instrument Flight Rules (IFR) aircraft separations can be set at 3 nautical miles. Five years of wind data ha...

Selection of appropriate training and validation set chemicals for modelling dermal permeability by U-optimal design.

PubMed

Xu, G; Hughes-Oliver, J M; Brooks, J D; Yeatts, J L; Baynes, R E

2013-01-01

Quantitative structure-activity relationship (QSAR) models are being used increasingly in skin permeation studies. The main idea of QSAR modelling is to quantify the relationship between biological activities and chemical properties, and thus to predict the activity of chemical solutes. As a key step, the selection of a representative and structurally diverse training set is critical to the prediction power of a QSAR model. Early QSAR models selected training sets in a subjective way and solutes in the training set were relatively homogenous. More recently, statistical methods such as D-optimal design or space-filling design have been applied but such methods are not always ideal. This paper describes a comprehensive procedure to select training sets from a large candidate set of 4534 solutes. A newly proposed 'Baynes' rule', which is a modification of Lipinski's 'rule of five', was used to screen out solutes that were not qualified for the study. U-optimality was used as the selection criterion. A principal component analysis showed that the selected training set was representative of the chemical space. Gas chromatograph amenability was verified. A model built using the training set was shown to have greater predictive power than a model built using a previous dataset [1].

A comprehensive model to determine the effects of temperature and species fluctuations on reactions in turbulent reacting flows

NASA Technical Reports Server (NTRS)

Antaki, P. J.

1981-01-01

The joint probability distribution function (pdf), which is a modification of the bivariate Gaussian pdf, is discussed and results are presented for a global reaction model using the joint pdf. An alternative joint pdf is discussed. A criterion which permits the selection of temperature pdf's in different regions of turbulent, reacting flow fields is developed. Two principal approaches to the determination of reaction rates in computer programs containing detailed chemical kinetics are outlined. These models represent a practical solution to the modeling of species reaction rates in turbulent, reacting flows.

An Innovative Structural Mode Selection Methodology: Application for the X-33 Launch Vehicle Finite Element Model

NASA Technical Reports Server (NTRS)

Hidalgo, Homero, Jr.

2000-01-01

An innovative methodology for determining structural target mode selection and mode selection based on a specific criterion is presented. An effective approach to single out modes which interact with specific locations on a structure has been developed for the X-33 Launch Vehicle Finite Element Model (FEM). We presented Root-Sum-Square (RSS) displacement method computes resultant modal displacement for each mode at selected degrees of freedom (DOF) and sorts to locate modes with highest values. This method was used to determine modes, which most influenced specific locations/points on the X-33 flight vehicle such as avionics control components, aero-surface control actuators, propellant valve and engine points for use in flight control stability analysis and for flight POGO stability analysis. Additionally, the modal RSS method allows for primary or global target vehicle modes to also be identified in an accurate and efficient manner.

The Missing Middle in Validation Research

ERIC Educational Resources Information Center

Taylor, Erwin K.; Griess, Thomas

1976-01-01

In most selection validation research, only the upper and lower tails of the criterion distribution are used, often yielding misleading or incorrect results. Provides formulas and tables which enable the researcher to account more accurately for the distribution of criterion within the middle range of population. (Author/RW)

The Gideon Criterion: The Effects of Selection Criteria on Soldier Capabilities and Battle Results

DTIC Science & Technology

1982-01-01

United States Army Recruiting Command RESEARCH MEMORANDUM 82-1 AD______ I I THE GIDEON CRITERION: THE EFFECTS OF SELECTION CRITERIA ON SOLDIER...and Evaluation Directorate Fort Sheridan, Illinois 60037 83 05 09 056 ii 1 DISCLAIMER NOTICE THIS DOCUMENT IS BEST QUALITY PRACTICABLE. THE COPY...FURNISHED TO DTIC CONTAINED A SIGNIFICANT NUMBER OF PAGES WHICH DO NOT REPRODUCE LEGIBLY. j1 ... 4 ’ t c " " .. THE GIDEON CR17RION’. THE EFFECTS OF

Predicting space telerobotic operator training performance from human spatial ability assessment

NASA Astrophysics Data System (ADS)

Liu, Andrew M.; Oman, Charles M.; Galvan, Raquel; Natapoff, Alan

2013-11-01

Our goal was to determine whether existing tests of spatial ability can predict an astronaut's qualification test performance after robotic training. Because training astronauts to be qualified robotics operators is so long and expensive, NASA is interested in tools that can predict robotics performance before training begins. Currently, the Astronaut Office does not have a validated tool to predict robotics ability as part of its astronaut selection or training process. Commonly used tests of human spatial ability may provide such a tool to predict robotics ability. We tested the spatial ability of 50 active astronauts who had completed at least one robotics training course, then used logistic regression models to analyze the correlation between spatial ability test scores and the astronauts' performance in their evaluation test at the end of the training course. The fit of the logistic function to our data is statistically significant for several spatial tests. However, the prediction performance of the logistic model depends on the criterion threshold assumed. To clarify the critical selection issues, we show how the probability of correct classification vs. misclassification varies as a function of the mental rotation test criterion level. Since the costs of misclassification are low, the logistic models of spatial ability and robotic performance are reliable enough only to be used to customize regular and remedial training. We suggest several changes in tracking performance throughout robotics training that could improve the range and reliability of predictive models.

The question of nonlinearity in the dose-response relation between particulate matter air pollution and mortality: can Akaike's Information Criterion be trusted to take the right turn?

PubMed

Roberts, Steven; Martin, Michael A

2006-12-15

The shape of the dose-response relation between particulate matter air pollution and mortality is crucial for public health assessment, and departures of this relation from linearity could have important regulatory consequences. A number of investigators have studied the shape of the particulate matter-mortality dose-response relation and concluded that the relation could be adequately described by a linear model. Some of these researchers examined the hypothesis of linearity by comparing Akaike's Information Criterion (AIC) values obtained under linear, piecewise linear, and spline alternative models. However, at the current time, the efficacy of the AIC in this context has not been assessed. The authors investigated AIC as a means of comparing competing dose-response models, using data from Cook County, Illinois, for the period 1987-2000. They found that if nonlinearities exist, the AIC is not always successful in detecting them. In a number of the scenarios considered, AIC was equivocal, picking the correct simulated dose-response model about half of the time. These findings suggest that further research into the shape of the dose-response relation using alternative model selection criteria may be warranted.

A New Multiaxial High-Cycle Fatigue Criterion Based on the Critical Plane for Ductile and Brittle Materials

NASA Astrophysics Data System (ADS)

Wang, Cong; Shang, De-Guang; Wang, Xiao-Wei

2015-02-01

An improved high-cycle multiaxial fatigue criterion based on the critical plane was proposed in this paper. The critical plane was defined as the plane of maximum shear stress (MSS) in the proposed multiaxial fatigue criterion, which is different from the traditional critical plane based on the MSS amplitude. The proposed criterion was extended as a fatigue life prediction model that can be applicable for ductile and brittle materials. The fatigue life prediction model based on the proposed high-cycle multiaxial fatigue criterion was validated with experimental results obtained from the test of 7075-T651 aluminum alloy and some references.

Reliability, Factor Structure, and Associations With Measures of Problem Relationship and Behavior of the Personality Inventory for DSM-5 in a Sample of Italian Community-Dwelling Adolescents.

PubMed

Somma, Antonella; Borroni, Serena; Maffei, Cesare; Giarolli, Laura E; Markon, Kristian E; Krueger, Robert F; Fossati, Andrea

2017-10-01

In order to assess the reliability, factorial validity, and criterion validity of the Personality Inventory for DSM-5 (PID-5) among adolescents, 1,264 Italian high school students were administered the PID-5. Participants were also administered the Questionnaire on Relationships and Substance Use as a criterion measure. In the full sample, McDonald's ω values were adequate for the PID-5 scales (median ω = .85, SD = .06), except for Suspiciousness. However, all PID-5 scales showed average inter-item correlation values in the .20-.55 range. Exploratory structural equation modeling analyses provided moderate support for the a priori model of PID-5 trait scales. Ordinal logistic regression analyses showed that selected PID-5 trait scales predicted a significant, albeit moderate (Cox & Snell R 2 values ranged from .08 to .15, all ps < .001) amount of variance in Questionnaire on Relationships and Substance Use variables.

Fisher's method of combining dependent statistics using generalizations of the gamma distribution with applications to genetic pleiotropic associations.

PubMed

Li, Qizhai; Hu, Jiyuan; Ding, Juan; Zheng, Gang

2014-04-01

A classical approach to combine independent test statistics is Fisher's combination of $p$-values, which follows the $\\chi ^2$ distribution. When the test statistics are dependent, the gamma distribution (GD) is commonly used for the Fisher's combination test (FCT). We propose to use two generalizations of the GD: the generalized and the exponentiated GDs. We study some properties of mis-using the GD for the FCT to combine dependent statistics when one of the two proposed distributions are true. Our results show that both generalizations have better control of type I error rates than the GD, which tends to have inflated type I error rates at more extreme tails. In practice, common model selection criteria (e.g. Akaike information criterion/Bayesian information criterion) can be used to help select a better distribution to use for the FCT. A simple strategy of the two generalizations of the GD in genome-wide association studies is discussed. Applications of the results to genetic pleiotrophic associations are described, where multiple traits are tested for association with a single marker.

Genetic parameters for stayability to consecutive calvings in Zebu cattle.

PubMed

Silva, D O; Santana, M L; Ayres, D R; Menezes, G R O; Silva, L O C; Nobre, P R C; Pereira, R J

2017-12-22

Longer-lived cows tend to be more profitable and the stayability trait is a selection criterion correlated to longevity. An alternative to the traditional approach to evaluate stayability is its definition based on consecutive calvings, whose main advantage is the more accurate evaluation of young bulls. However, no study using this alternative approach has been conducted for Zebu breeds. Therefore, the objective of this study was to compare linear random regression models to fit stayability to consecutive calvings of Guzerá, Nelore and Tabapuã cows and to estimate genetic parameters for this trait in the respective breeds. Data up to the eighth calving were used. The models included the fixed effects of age at first calving and year-season of birth of the cow and the random effects of contemporary group, additive genetic, permanent environmental and residual. Random regressions were modeled by orthogonal Legendre polynomials of order 1 to 4 (2 to 5 coefficients) for contemporary group, additive genetic and permanent environmental effects. Using Deviance Information Criterion as the selection criterion, the model with 4 regression coefficients for each effect was the most adequate for the Nelore and Tabapuã breeds and the model with 5 coefficients is recommended for the Guzerá breed. For Guzerá, heritabilities ranged from 0.05 to 0.08, showing a quadratic trend with a peak between the fourth and sixth calving. For the Nelore and Tabapuã breeds, the estimates ranged from 0.03 to 0.07 and from 0.03 to 0.08, respectively, and increased with increasing calving number. The additive genetic correlations exhibited a similar trend among breeds and were higher for stayability between closer calvings. Even between more distant calvings (second v. eighth), stayability showed a moderate to high genetic correlation, which was 0.77, 0.57 and 0.79 for the Guzerá, Nelore and Tabapuã breeds, respectively. For Guzerá, when the models with 4 or 5 regression coefficients were compared, the rank correlations between predicted breeding values for the intercept were always higher than 0.99, indicating the possibility of practical application of the least parameterized model. In conclusion, the model with 4 random regression coefficients is recommended for the genetic evaluation of stayability to consecutive calvings in Zebu cattle.

Model selection and Bayesian inference for high-resolution seabed reflection inversion.

PubMed

Dettmer, Jan; Dosso, Stan E; Holland, Charles W

2009-02-01

This paper applies Bayesian inference, including model selection and posterior parameter inference, to inversion of seabed reflection data to resolve sediment structure at a spatial scale below the pulse length of the acoustic source. A practical approach to model selection is used, employing the Bayesian information criterion to decide on the number of sediment layers needed to sufficiently fit the data while satisfying parsimony to avoid overparametrization. Posterior parameter inference is carried out using an efficient Metropolis-Hastings algorithm for high-dimensional models, and results are presented as marginal-probability depth distributions for sound velocity, density, and attenuation. The approach is applied to plane-wave reflection-coefficient inversion of single-bounce data collected on the Malta Plateau, Mediterranean Sea, which indicate complex fine structure close to the water-sediment interface. This fine structure is resolved in the geoacoustic inversion results in terms of four layers within the upper meter of sediments. The inversion results are in good agreement with parameter estimates from a gravity core taken at the experiment site.

A probabilistic multi-criteria decision making technique for conceptual and preliminary aerospace systems design

NASA Astrophysics Data System (ADS)

Bandte, Oliver

It has always been the intention of systems engineering to invent or produce the best product possible. Many design techniques have been introduced over the course of decades that try to fulfill this intention. Unfortunately, no technique has succeeded in combining multi-criteria decision making with probabilistic design. The design technique developed in this thesis, the Joint Probabilistic Decision Making (JPDM) technique, successfully overcomes this deficiency by generating a multivariate probability distribution that serves in conjunction with a criterion value range of interest as a universally applicable objective function for multi-criteria optimization and product selection. This new objective function constitutes a meaningful Xnetric, called Probability of Success (POS), that allows the customer or designer to make a decision based on the chance of satisfying the customer's goals. In order to incorporate a joint probabilistic formulation into the systems design process, two algorithms are created that allow for an easy implementation into a numerical design framework: the (multivariate) Empirical Distribution Function and the Joint Probability Model. The Empirical Distribution Function estimates the probability that an event occurred by counting how many times it occurred in a given sample. The Joint Probability Model on the other hand is an analytical parametric model for the multivariate joint probability. It is comprised of the product of the univariate criterion distributions, generated by the traditional probabilistic design process, multiplied with a correlation function that is based on available correlation information between pairs of random variables. JPDM is an excellent tool for multi-objective optimization and product selection, because of its ability to transform disparate objectives into a single figure of merit, the likelihood of successfully meeting all goals or POS. The advantage of JPDM over other multi-criteria decision making techniques is that POS constitutes a single optimizable function or metric that enables a comparison of all alternative solutions on an equal basis. Hence, POS allows for the use of any standard single-objective optimization technique available and simplifies a complex multi-criteria selection problem into a simple ordering problem, where the solution with the highest POS is best. By distinguishing between controllable and uncontrollable variables in the design process, JPDM can account for the uncertain values of the uncontrollable variables that are inherent to the design problem, while facilitating an easy adjustment of the controllable ones to achieve the highest possible POS. Finally, JPDM's superiority over current multi-criteria decision making techniques is demonstrated with an optimization of a supersonic transport concept and ten contrived equations as well as a product selection example, determining an airline's best choice among Boeing's B-747, B-777, Airbus' A340, and a Supersonic Transport. The optimization examples demonstrate JPDM's ability to produce a better solution with a higher POS than an Overall Evaluation Criterion or Goal Programming approach. Similarly, the product selection example demonstrates JPDM's ability to produce a better solution with a higher POS and different ranking than the Overall Evaluation Criterion or Technique for Order Preferences by Similarity to the Ideal Solution (TOPSIS) approach.

Administrative Process and Criteria Ranking for Drug Entering Health Insurance List in Iran-TOPSIS-Based Consensus Model.

PubMed

Viyanchi, Amir; Rajabzadeh Ghatari, Ali; Rasekh, Hamid Reza; SafiKhani, HamidReza

2016-01-01

The purposes of our study were to identify a drug entry process, collect, and prioritize criteria for selecting drugs for the list of basic health insurance commitments to prepare an "evidence based reimbursement eligibility plan" in Iran. The 128 noticeable criteria were found when studying the health insurance systems of developed countries. Four parts (involving criteria) formed the first questionnaire: evaluation of evidences quality, clinical evaluation, economic evaluation, and managerial appraisal. The 85 experts (purposed sampling) were asked to mark the importance of each criterion from 1 to 100 as 1 representing the least and 100 the most important criterion and 45 out of them replied completely. Then, in the next questionnaire, we evaluated the 48 remainder criteria by the same45 participants under four sub-criteria (Cost calculation simplicity, Interpretability, Precision, and Updating capability of a criterion). After collecting the replies, the remainder criteria were ranked by TOPSIS method. Softwares "SPSS" 17 and Excel 2007 were used. The ranks of the five most important criteria which were found for drug approval based on TOPSIS are as follows: 1-domestic production (0.556), 2-duration of using (0.399), 3-independence of the assessment group (0.363) 4-impact budgeting (0.362) 5-decisions of other countries about the same drug (0.358). The numbers in parenthesis are relative closeness alternatives in relation to the ideal solution. This model gave a scientific model for judging fairly on the acceptance of novelty medicines.

The Reliability of Criterion-Referenced Measures.

ERIC Educational Resources Information Center

Livingston, Samuel A.

The assumptions of the classical test-theory model are used to develop a theory of reliability for criterion-referenced measures which parallels that for norm-referenced measures. It is shown that the Spearman-Brown formula holds for criterion-referenced measures and that the criterion-referenced reliability coefficient can be used to correct…

PERIODIC AUTOREGRESSIVE-MOVING AVERAGE (PARMA) MODELING WITH APPLICATIONS TO WATER RESOURCES.

USGS Publications Warehouse

Vecchia, A.V.

1985-01-01

Results involving correlation properties and parameter estimation for autogressive-moving average models with periodic parameters are presented. A multivariate representation of the PARMA model is used to derive parameter space restrictions and difference equations for the periodic autocorrelations. Close approximation to the likelihood function for Gaussian PARMA processes results in efficient maximum-likelihood estimation procedures. Terms in the Fourier expansion of the parameters are sequentially included, and a selection criterion is given for determining the optimal number of harmonics to be included. Application of the techniques is demonstrated through analysis of a monthly streamflow time series.

Program management aid for redundancy selection and operational guidelines

NASA Technical Reports Server (NTRS)

Hodge, P. W.; Davis, W. L.; Frumkin, B.

1972-01-01

Although this criterion was developed specifically for use on the shuttle program, it has application to many other multi-missions programs (i.e. aircraft or mechanisms). The methodology employed is directly applicable even if the tools (nomographs and equations) are for mission peculiar cases. The redundancy selection criterion was developed to insure that both the design and operational cost impacts (life cycle costs) were considered in the selection of the quantity of operational redundancy. These tools were developed as aids in expediting the decision process and not intended as the automatic decision maker. This approach to redundancy selection is unique in that it enables a pseudo systems analysis to be performed on an equipment basis without waiting for all designs to be hardened.

Training set optimization under population structure in genomic selection.

PubMed

Isidro, Julio; Jannink, Jean-Luc; Akdemir, Deniz; Poland, Jesse; Heslot, Nicolas; Sorrells, Mark E

2015-01-01

Population structure must be evaluated before optimization of the training set population. Maximizing the phenotypic variance captured by the training set is important for optimal performance. The optimization of the training set (TRS) in genomic selection has received much interest in both animal and plant breeding, because it is critical to the accuracy of the prediction models. In this study, five different TRS sampling algorithms, stratified sampling, mean of the coefficient of determination (CDmean), mean of predictor error variance (PEVmean), stratified CDmean (StratCDmean) and random sampling, were evaluated for prediction accuracy in the presence of different levels of population structure. In the presence of population structure, the most phenotypic variation captured by a sampling method in the TRS is desirable. The wheat dataset showed mild population structure, and CDmean and stratified CDmean methods showed the highest accuracies for all the traits except for test weight and heading date. The rice dataset had strong population structure and the approach based on stratified sampling showed the highest accuracies for all traits. In general, CDmean minimized the relationship between genotypes in the TRS, maximizing the relationship between TRS and the test set. This makes it suitable as an optimization criterion for long-term selection. Our results indicated that the best selection criterion used to optimize the TRS seems to depend on the interaction of trait architecture and population structure.

Diurnal flight behavior of Ichneumonoidea (Insecta: Hymenoptera) related to environmental factors in a tropical dry forest.

PubMed

González-Moreno, A; Bordera, S; Leirana-Alcocer, J; Delfín-González, H

2012-06-01

The biology and behavior of insects are strongly influenced by environmental conditions such as temperature and precipitation. Because some of these factors present a within day variation, they may be causing variations on insect diurnal flight activity, but scant information exists on the issue. The aim of this work was to describe the patterns on diurnal variation of the abundance of Ichneumonoidea and their relation with relative humidity, temperature, light intensity, and wind speed. The study site was a tropical dry forest at Ría Lagartos Biosphere Reserve, Mexico; where correlations between environmental factors (relative humidity, temperature, light, and wind speed) and abundance of Ichneumonidae and Braconidae (Hymenoptera: Ichneumonoidea) were estimated. The best regression model for explaining abundance variation was selected using the second order Akaike Information Criterion. The optimum values of temperature, humidity, and light for flight activity of both families were also estimated. Ichneumonid and braconid abundances were significantly correlated to relative humidity, temperature, and light intensity; ichneumonid also showed significant correlations to wind speed. The second order Akaike Information Criterion suggests that in tropical dry conditions, relative humidity is more important that temperature for Ichneumonoidea diurnal activity. Ichneumonid wasps selected toward intermediate values of relative humidity, temperature and the lowest wind speeds; while Braconidae selected for low values of relative humidity. For light intensity, braconids presented a positive selection for moderately high values.

Development and application of course-embedded assessment system for program outcome evaluation in the Korean nursing education: A pilot study.

PubMed

Park, Jee Won; Seo, Eun Ji; You, Mi-Ae; Song, Ju-Eun

2016-03-01

Program outcome evaluation is important because it is an indicator for good quality of education. Course-embedded assessment is one of the program outcome evaluation methods. However, it is rarely used in Korean nursing education. The study purpose was to develop and apply preliminarily a course-embedded assessment system to evaluate one program outcome and to share our experiences. This was a methodological study to develop and apply the course-embedded assessment system based on the theoretical framework in one nursing program in South Korea. Scores for 77 students generated from the three practicum courses were used. The course-embedded assessment system was developed following the six steps suggested by Han's model as follows. 1) One program outcome in the undergraduate program, "nursing process application ability", was selected and 2) the three clinical practicum courses related to the selected program outcome were identified. 3) Evaluation tools including rubric and items were selected for outcome measurement and 4) performance criterion, the educational goal level for the program, was established. 5) Program outcome was actually evaluated using the rubric and evaluation items in the three practicum courses and 6) the obtained scores were analyzed to identify the achievement rate, which was compared with the performance criterion. Achievement rates for the selected program outcome in adult, maternity, and pediatric nursing practicum were 98.7%, 100%, and 66.2% in the case report and 100% for all three in the clinical practice, and 100%, 100%, and 87% respectively for the conference. These are considered as satisfactory levels when compared with the performance criterion of "at least 60% or more". Course-embedded assessment can be used as an effective and economic method to evaluate the program outcome without running an integrative course additionally. Further studies to develop course-embedded assessment systems for other program outcomes in nursing education are needed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identification of Conflicting Selective Effects on Highly Expressed Genes

PubMed Central

Higgs, Paul G.; Hao, Weilong; Golding, G. Brian

2007-01-01

Many different selective effects on DNA and proteins influence the frequency of codons and amino acids in coding sequences. Selection is often stronger on highly expressed genes. Hence, by comparing high- and low-expression genes it is possible to distinguish the factors that are selected by evolution. It has been proposed that highly expressed genes should (i) preferentially use codons matching abundant tRNAs (translational efficiency), (ii) preferentially use amino acids with low cost of synthesis, (iii) be under stronger selection to maintain the required amino acid content, and (iv) be selected for translational robustness. These effects act simultaneously and can be contradictory. We develop a model that combines these factors, and use Akaike’s Information Criterion for model selection. We consider pairs of paralogues that arose by whole-genome duplication in Saccharmyces cerevisiae. A codon-based model is used that includes asymmetric effects due to selection on highly expressed genes. The largest effect is translational efficiency, which is found to strongly influence synonymous, but not non-synonymous rates. Minimization of the cost of amino acid synthesis is implicated. However, when a more general measure of selection for amino acid usage is used, the cost minimization effect becomes redundant. Small effects that we attribute to selection for translational robustness can be identified as an improvement in the model fit on top of the effects of translational efficiency and amino acid usage. PMID:19430600

Issues and Procedures in the Development of Criterion Referenced Tests.

ERIC Educational Resources Information Center

Klein, Stephen P.; Kosecoff, Jacqueline

The basic steps and procedures in the development of criterion referenced tests (CRT), as well as the issues and problems associated with these activities are discussed. In the first section of the paper, the discussions focus upon the purpose and defining characteristics of CRTs, item construction and selection, improving item quality, content…

New bandwidth selection criterion for Kernel PCA: approach to dimensionality reduction and classification problems.

PubMed

Thomas, Minta; De Brabanter, Kris; De Moor, Bart

2014-05-10

DNA microarrays are potentially powerful technology for improving diagnostic classification, treatment selection, and prognostic assessment. The use of this technology to predict cancer outcome has a history of almost a decade. Disease class predictors can be designed for known disease cases and provide diagnostic confirmation or clarify abnormal cases. The main input to this class predictors are high dimensional data with many variables and few observations. Dimensionality reduction of these features set significantly speeds up the prediction task. Feature selection and feature transformation methods are well known preprocessing steps in the field of bioinformatics. Several prediction tools are available based on these techniques. Studies show that a well tuned Kernel PCA (KPCA) is an efficient preprocessing step for dimensionality reduction, but the available bandwidth selection method for KPCA was computationally expensive. In this paper, we propose a new data-driven bandwidth selection criterion for KPCA, which is related to least squares cross-validation for kernel density estimation. We propose a new prediction model with a well tuned KPCA and Least Squares Support Vector Machine (LS-SVM). We estimate the accuracy of the newly proposed model based on 9 case studies. Then, we compare its performances (in terms of test set Area Under the ROC Curve (AUC) and computational time) with other well known techniques such as whole data set + LS-SVM, PCA + LS-SVM, t-test + LS-SVM, Prediction Analysis of Microarrays (PAM) and Least Absolute Shrinkage and Selection Operator (Lasso). Finally, we assess the performance of the proposed strategy with an existing KPCA parameter tuning algorithm by means of two additional case studies. We propose, evaluate, and compare several mathematical/statistical techniques, which apply feature transformation/selection for subsequent classification, and consider its application in medical diagnostics. Both feature selection and feature transformation perform well on classification tasks. Due to the dynamic selection property of feature selection, it is hard to define significant features for the classifier, which predicts classes of future samples. Moreover, the proposed strategy enjoys a distinctive advantage with its relatively lesser time complexity.

Detection of Bi-Directionality in Strain-Gage Balance Calibration Data

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert

2012-01-01

An indicator variable was developed for both visualization and detection of bi-directionality in wind tunnel strain-gage balance calibration data. First, the calculation of the indicator variable is explained in detail. Then, a criterion is discussed that may be used to decide which gage outputs of a balance have bi- directional behavior. The result of this analysis could be used, for example, to justify the selection of certain absolute value or other even function terms in the regression model of gage outputs whenever the Iterative Method is chosen for the balance calibration data analysis. Calibration data of NASA s MK40 Task balance is analyzed to illustrate both the calculation of the indicator variable and the application of the proposed criterion. Finally, bi directionality characteristics of typical multi piece, hybrid, single piece, and semispan balances are determined and discussed.

Failure prediction for the optimization of stretch forming aluminium-polymer laminate foils used for pharmaceutical packaging

NASA Astrophysics Data System (ADS)

Müller, Simon; Weygand, Sabine M.

2018-05-01

Axisymmetric stretch forming processes of aluminium-polymer laminate foils (e.g. consisting of PA-Al-PVC layers) are analyzed numerically by finite element modeling of the multi-layer material as well as experimentally in order to identify a suitable damage initiation criterion. A simple ductile fracture criterion is proposed to predict the forming limits. The corresponding material constants are determined from tensile tests and then applied in forming simulations with different punch geometries. A comparison between the simulations and the experimental results shows that the determined failure constants are not applicable. Therefore, one forming experiment was selected and in the corresponding simulation the failure constant was fitted to its measured maximum stretch. With this approach it is possible to predict the forming limit of the laminate foil with satisfying accuracy for different punch geometries.

A Bayesian random effects discrete-choice model for resource selection: Population-level selection inference

USGS Publications Warehouse

Thomas, D.L.; Johnson, D.; Griffith, B.

2006-01-01

Modeling the probability of use of land units characterized by discrete and continuous measures, we present a Bayesian random-effects model to assess resource selection. This model provides simultaneous estimation of both individual- and population-level selection. Deviance information criterion (DIC), a Bayesian alternative to AIC that is sample-size specific, is used for model selection. Aerial radiolocation data from 76 adult female caribou (Rangifer tarandus) and calf pairs during 1 year on an Arctic coastal plain calving ground were used to illustrate models and assess population-level selection of landscape attributes, as well as individual heterogeneity of selection. Landscape attributes included elevation, NDVI (a measure of forage greenness), and land cover-type classification. Results from the first of a 2-stage model-selection procedure indicated that there is substantial heterogeneity among cow-calf pairs with respect to selection of the landscape attributes. In the second stage, selection of models with heterogeneity included indicated that at the population-level, NDVI and land cover class were significant attributes for selection of different landscapes by pairs on the calving ground. Population-level selection coefficients indicate that the pairs generally select landscapes with higher levels of NDVI, but the relationship is quadratic. The highest rate of selection occurs at values of NDVI less than the maximum observed. Results for land cover-class selections coefficients indicate that wet sedge, moist sedge, herbaceous tussock tundra, and shrub tussock tundra are selected at approximately the same rate, while alpine and sparsely vegetated landscapes are selected at a lower rate. Furthermore, the variability in selection by individual caribou for moist sedge and sparsely vegetated landscapes is large relative to the variability in selection of other land cover types. The example analysis illustrates that, while sometimes computationally intense, a Bayesian hierarchical discrete-choice model for resource selection can provide managers with 2 components of population-level inference: average population selection and variability of selection. Both components are necessary to make sound management decisions based on animal selection.

Energy Criterion for the Spectral Stability of Discrete Breathers.

PubMed

Kevrekidis, Panayotis G; Cuevas-Maraver, Jesús; Pelinovsky, Dmitry E

2016-08-26

Discrete breathers are ubiquitous structures in nonlinear anharmonic models ranging from the prototypical example of the Fermi-Pasta-Ulam model to Klein-Gordon nonlinear lattices, among many others. We propose a general criterion for the emergence of instabilities of discrete breathers analogous to the well-established Vakhitov-Kolokolov criterion for solitary waves. The criterion involves the change of monotonicity of the discrete breather's energy as a function of the breather frequency. Our analysis suggests and numerical results corroborate that breathers with increasing (decreasing) energy-frequency dependence are generically unstable in soft (hard) nonlinear potentials.

Data processing 1: Advancements in machine analysis of multispectral data

NASA Technical Reports Server (NTRS)

Swain, P. H.

1972-01-01

Multispectral data processing procedures are outlined beginning with the data display process used to accomplish data editing and proceeding through clustering, feature selection criterion for error probability estimation, and sample clustering and sample classification. The effective utilization of large quantities of remote sensing data by formulating a three stage sampling model for evaluation of crop acreage estimates represents an improvement in determining the cost benefit relationship associated with remote sensing technology.

Load-Based Lower Neck Injury Criteria for Females from Rear Impact from Cadaver Experiments.

PubMed

Yoganandan, Narayan; Pintar, Frank A; Banerjee, Anjishnu

2017-05-01

The objectives of this study were to derive lower neck injury metrics/criteria and injury risk curves for the force, moment, and interaction criterion in rear impacts for females. Biomechanical data were obtained from previous intact and isolated post mortem human subjects and head-neck complexes subjected to posteroanterior accelerative loading. Censored data were used in the survival analysis model. The primary shear force, sagittal bending moment, and interaction (lower neck injury criterion, LN ic ) metrics were significant predictors of injury. The most optimal distribution was selected (Weibulll, log normal, or log logistic) using the Akaike information criterion according to the latest ISO recommendations for deriving risk curves. The Kolmogorov-Smirnov test was used to quantify robustness of the assumed parametric model. The intercepts for the interaction index were extracted from the primary risk curves. Normalized confidence interval sizes (NCIS) were reported at discrete probability levels, along with the risk curves and 95% confidence intervals. The mean force of 214 N, moment of 54 Nm, and 0.89 LN ic were associated with a five percent probability of injury. The NCIS for these metrics were 0.90, 0.95, and 0.85. These preliminary results can be used as a first step in the definition of lower neck injury criteria for women under posteroanterior accelerative loading in crashworthiness evaluations.

Retrieving relevant factors with exploratory SEM and principal-covariate regression: A comparison.

PubMed

Vervloet, Marlies; Van den Noortgate, Wim; Ceulemans, Eva

2018-02-12

Behavioral researchers often linearly regress a criterion on multiple predictors, aiming to gain insight into the relations between the criterion and predictors. Obtaining this insight from the ordinary least squares (OLS) regression solution may be troublesome, because OLS regression weights show only the effect of a predictor on top of the effects of other predictors. Moreover, when the number of predictors grows larger, it becomes likely that the predictors will be highly collinear, which makes the regression weights' estimates unstable (i.e., the "bouncing beta" problem). Among other procedures, dimension-reduction-based methods have been proposed for dealing with these problems. These methods yield insight into the data by reducing the predictors to a smaller number of summarizing variables and regressing the criterion on these summarizing variables. Two promising methods are principal-covariate regression (PCovR) and exploratory structural equation modeling (ESEM). Both simultaneously optimize reduction and prediction, but they are based on different frameworks. The resulting solutions have not yet been compared; it is thus unclear what the strengths and weaknesses are of both methods. In this article, we focus on the extents to which PCovR and ESEM are able to extract the factors that truly underlie the predictor scores and can predict a single criterion. The results of two simulation studies showed that for a typical behavioral dataset, ESEM (using the BIC for model selection) in this regard is successful more often than PCovR. Yet, in 93% of the datasets PCovR performed equally well, and in the case of 48 predictors, 100 observations, and large differences in the strengths of the factors, PCovR even outperformed ESEM.

3D-QSAR and molecular docking study on bisarylmaleimide series as glycogen synthase kinase 3, cyclin dependent kinase 2 and cyclin dependent kinase 4 inhibitors: an insight into the criteria for selectivity.

PubMed

Dessalew, Nigus; Bharatam, Prasad V

2007-07-01

Selective glycogen synthase kinase 3 (GSK3) inhibition over cyclin dependent kinases such as cyclin dependent kinase 2 (CDK2) and cyclin dependent kinase 4 (CDK4) is an important requirement for improved therapeutic profile of GSK3 inhibitors. The concepts of selectivity and additivity fields have been employed in developing selective CoMFA models for these related kinases. Initially, sets of three individual CoMFA models were developed, using 36 compounds of bisarylmaleimide series to correlate with the GSK3, CDK2 and CDK4 inhibitory potencies. These models showed a satisfactory statistical significance: CoMFA-GSK3 (r(2)(con), r(2)(cv): 0.931, 0.519), CoMFA-CDK2 (0.937, 0.563), and CoMFA-CDK4 (0.892, 0.725). Three different selective CoMFA models were then developed using differences in pIC(50) values. These three models showed a superior statistical significance: (i) CoMFA-Selective1 (r(2)(con), r(2)(cv): 0.969, 0.768), (ii) CoMFA-Selective 2 (0.974, 0.835) and (iii) CoMFA-Selective3 (0.963, 0.776). The selective models were found to outperform the individual models in terms of the quality of correlation and were found to be more informative in pinpointing the structural basis for the observed quantitative differences of kinase inhibition. An in-depth comparative investigation was carried out between the individual and selective models to gain an insight into the selectivity criterion. To further validate this approach, a set of new compounds were designed which show selectivity and were docked into the active site of GSK3, using FlexX based incremental construction algorithm.

Interface Pattern Selection in Directional Solidification

NASA Technical Reports Server (NTRS)

Trivedi, Rohit; Tewari, Surendra N.

2001-01-01

The central focus of this research is to establish key scientific concepts that govern the selection of cellular and dendritic patterns during the directional solidification of alloys. Ground-based studies have established that the conditions under which cellular and dendritic microstructures form are precisely where convection effects are dominant in bulk samples. Thus, experimental data can not be obtained terrestrially under pure diffusive regime. Furthermore, reliable theoretical models are not yet possible which can quantitatively incorporate fluid flow in the pattern selection criterion. Consequently, microgravity experiments on cellular and dendritic growth are designed to obtain benchmark data under diffusive growth conditions that can be quantitatively analyzed and compared with the rigorous theoretical model to establish the fundamental principles that govern the selection of specific microstructure and its length scales. In the cellular structure, different cells in an array are strongly coupled so that the cellular pattern evolution is controlled by complex interactions between thermal diffusion, solute diffusion and interface effects. These interactions give infinity of solutions, and the system selects only a narrow band of solutions. The aim of this investigation is to obtain benchmark data and develop a rigorous theoretical model that will allow us to quantitatively establish the physics of this selection process.

Toward a Unified Representation of Atmospheric Convection in Variable-Resolution Climate Models

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

Walko, Robert

2016-11-07

The purpose of this project was to improve the representation of convection in atmospheric weather and climate models that employ computational grids with spatially-variable resolution. Specifically, our work targeted models whose grids are fine enough over selected regions that convection is resolved explicitly, while over other regions the grid is coarser and convection is represented as a subgrid-scale process. The working criterion for a successful scheme for representing convection over this range of grid resolution was that identical convective environments must produce very similar convective responses (i.e., the same precipitation amount, rate, and timing, and the same modification of themore » atmospheric profile) regardless of grid scale. The need for such a convective scheme has increased in recent years as more global weather and climate models have adopted variable resolution meshes that are often extended into the range of resolving convection in selected locations.« less

Thermal signature identification system (TheSIS): a spread spectrum temperature cycling method

NASA Astrophysics Data System (ADS)

Merritt, Scott

2015-03-01

NASA GSFC's Thermal Signature Identification System (TheSIS) 1) measures the high order dynamic responses of optoelectronic components to direct sequence spread-spectrum temperature cycling, 2) estimates the parameters of multiple autoregressive moving average (ARMA) or other models the of the responses, 3) and selects the most appropriate model using the Akaike Information Criterion (AIC). Using the AIC-tested model and parameter vectors from TheSIS, one can 1) select high-performing components on a multivariate basis, i.e., with multivariate Figures of Merit (FOMs), 2) detect subtle reversible shifts in performance, and 3) investigate irreversible changes in component or subsystem performance, e.g. aging. We show examples of the TheSIS methodology for passive and active components and systems, e.g. fiber Bragg gratings (FBGs) and DFB lasers with coupled temperature control loops, respectively.

QSAR-like models: a potential tool for the selection of PhACs and EDCs for monitoring purposes in drinking water treatment systems--a review.

PubMed

Delgado, Luis F; Charles, Philippe; Glucina, Karl; Morlay, Catherine

2012-12-01

Recent studies have demonstrated the presence of trace-level pharmaceutically active compounds (PhACs) and endocrine disrupting compounds (EDCs) in a number of finished drinking waters (DWs). Since there is sparse knowledge currently available on the potential effects on human health associated with the chronic exposure to trace levels of these Emerging Contaminants (ECs) through routes such as DW, it is suggested that the most appropriate criterion is a treatment criterion in order to prioritize ECs to be monitored during DW preparation. Hence, only the few ECs showing the lowest removals towards a given DW Treatment (DWT) process would serve as indicators of the overall efficiency of this process and would be relevant for DW quality monitoring. In addition, models should be developed for estimating the removal of ECs in DWT processes, thereby overcoming the practical difficulties of experimentally assessing each compound. Therefore, the present review has two objectives: (1) to provide an overview of the recent scientific surveys on the occurrence of PhACs and EDCs in finished DWs; and (2) to propose the potential of Quantitative-Structure-Activity-Relationship-(QSAR)-like models to rank ECs found in environmental waters, including parent compounds, metabolites and transformation products, in order to select the most relevant compounds to be considered as indicators for monitoring purposes in DWT systems. Copyright © 2012 Elsevier Ltd. All rights reserved.

Bayesian model selection applied to artificial neural networks used for water resources modeling

NASA Astrophysics Data System (ADS)

Kingston, Greer B.; Maier, Holger R.; Lambert, Martin F.

2008-04-01

Artificial neural networks (ANNs) have proven to be extremely valuable tools in the field of water resources engineering. However, one of the most difficult tasks in developing an ANN is determining the optimum level of complexity required to model a given problem, as there is no formal systematic model selection method. This paper presents a Bayesian model selection (BMS) method for ANNs that provides an objective approach for comparing models of varying complexity in order to select the most appropriate ANN structure. The approach uses Markov Chain Monte Carlo posterior simulations to estimate the evidence in favor of competing models and, in this study, three known methods for doing this are compared in terms of their suitability for being incorporated into the proposed BMS framework for ANNs. However, it is acknowledged that it can be particularly difficult to accurately estimate the evidence of ANN models. Therefore, the proposed BMS approach for ANNs incorporates a further check of the evidence results by inspecting the marginal posterior distributions of the hidden-to-output layer weights, which unambiguously indicate any redundancies in the hidden layer nodes. The fact that this check is available is one of the greatest advantages of the proposed approach over conventional model selection methods, which do not provide such a test and instead rely on the modeler's subjective choice of selection criterion. The advantages of a total Bayesian approach to ANN development, including training and model selection, are demonstrated on two synthetic and one real world water resources case study.

Model-based estimates of long-term persistence of induced HPV antibodies: a flexible subject-specific approach.

PubMed

Aregay, Mehreteab; Shkedy, Ziv; Molenberghs, Geert; David, Marie-Pierre; Tibaldi, Fabián

2013-01-01

In infectious diseases, it is important to predict the long-term persistence of vaccine-induced antibodies and to estimate the time points where the individual titers are below the threshold value for protection. This article focuses on HPV-16/18, and uses a so-called fractional-polynomial model to this effect, derived in a data-driven fashion. Initially, model selection was done from among the second- and first-order fractional polynomials on the one hand and from the linear mixed model on the other. According to a functional selection procedure, the first-order fractional polynomial was selected. Apart from the fractional polynomial model, we also fitted a power-law model, which is a special case of the fractional polynomial model. Both models were compared using Akaike's information criterion. Over the observation period, the fractional polynomials fitted the data better than the power-law model; this, of course, does not imply that it fits best over the long run, and hence, caution ought to be used when prediction is of interest. Therefore, we point out that the persistence of the anti-HPV responses induced by these vaccines can only be ascertained empirically by long-term follow-up analysis.

Relationships between Classroom Schedule Types and Performance on the Algebra I Criterion-Referenced Test

ERIC Educational Resources Information Center

Murray, Gregory V.; Moyer-Packenham, Patricia S.

2014-01-01

One option for length of individual mathematics class periods is the schedule type selected for Algebra I classes. This study examined the relationship between student achievement, as indicated by Algebra I Criterion-Referenced Test scores, and the schedule type for Algebra I classes. Data obtained from the Utah State Office of Education included…

Factors Affecting the Identification of Research Problems in Educational Administration Studies

ERIC Educational Resources Information Center

Yalçin, Mikail; Bektas, Fatih; Öztekin, Özge; Karadag, Engin

2016-01-01

The purpose of this study is to reveal the factors that affect the identification of research problems in educational administration studies. The study was designed using the case study method. Criterion sampling was used to determine the work group; the criterion used to select the participants was that of having a study in the field of…

A criterion for maximum resin flow in composite materials curing process

NASA Astrophysics Data System (ADS)

Lee, Woo I.; Um, Moon-Kwang

1993-06-01

On the basis of Springer's resin flow model, a criterion for maximum resin flow in autoclave curing is proposed. Validity of the criterion was proved for two resin systems (Fiberite 976 and Hercules 3501-6 epoxy resin). The parameter required for the criterion can be easily estimated from the measured resin viscosity data. The proposed criterion can be used in establishing the proper cure cycle to ensure maximum resin flow and, thus, the maximum compaction.

A pattern of contractor selection for oil and gas industries in a safety approach using ANP-DEMATEL in a Grey environment.

PubMed

Gharedaghi, Gholamreza; Omidvari, Manouchehr

2018-01-11

Contractor selection is one of the major concerns of industry managers such as those in the oil industry. The objective of this study was to determine a contractor selection pattern for oil and gas industries in a safety approach. Assessment of contractors based on specific criteria and ultimately selecting an eligible contractor preserves the organizational resources. Due to the safety risks involved in the oil industry, one of the major criteria of contractor selection considered by managers today is safety. The results indicated that the most important safety criterion of contractor selection was safety records and safety investments. This represented the industry's risks and the impact of safety training and investment on the performance of other sectors and the overall organization. The output of this model could be useful in the safety risk assessment process in the oil industry and other industries.

Causal Inference for Cross-Modal Action Selection: A Computational Study in a Decision Making Framework.

PubMed

Daemi, Mehdi; Harris, Laurence R; Crawford, J Douglas

2016-01-01

Animals try to make sense of sensory information from multiple modalities by categorizing them into perceptions of individual or multiple external objects or internal concepts. For example, the brain constructs sensory, spatial representations of the locations of visual and auditory stimuli in the visual and auditory cortices based on retinal and cochlear stimulations. Currently, it is not known how the brain compares the temporal and spatial features of these sensory representations to decide whether they originate from the same or separate sources in space. Here, we propose a computational model of how the brain might solve such a task. We reduce the visual and auditory information to time-varying, finite-dimensional signals. We introduce controlled, leaky integrators as working memory that retains the sensory information for the limited time-course of task implementation. We propose our model within an evidence-based, decision-making framework, where the alternative plan units are saliency maps of space. A spatiotemporal similarity measure, computed directly from the unimodal signals, is suggested as the criterion to infer common or separate causes. We provide simulations that (1) validate our model against behavioral, experimental results in tasks where the participants were asked to report common or separate causes for cross-modal stimuli presented with arbitrary spatial and temporal disparities. (2) Predict the behavior in novel experiments where stimuli have different combinations of spatial, temporal, and reliability features. (3) Illustrate the dynamics of the proposed internal system. These results confirm our spatiotemporal similarity measure as a viable criterion for causal inference, and our decision-making framework as a viable mechanism for target selection, which may be used by the brain in cross-modal situations. Further, we suggest that a similar approach can be extended to other cognitive problems where working memory is a limiting factor, such as target selection among higher numbers of stimuli and selections among other modality combinations.

Selected mode of dendritic growth with n-fold symmetry in the presence of a forced flow

NASA Astrophysics Data System (ADS)

Alexandrov, D. V.; Galenko, P. K.

2017-07-01

The effect of n-fold crystal symmetry is investigated for a two-dimensional stable dendritic growth in the presence of a forced convective flow. We consider dendritic growth in a one-component undercooled liquid. The theory is developed for the parabolic solid-liquid surface of dendrite growing at arbitrary growth Péclet numbers keeping in mind small anisotropies of surface energy and growth kinetics. The selection criterion determining the stable growth velocity of the dendritic tip and its stable tip diameter is found on the basis of solvability analysis. The obtained criterion includes previously developed theories of thermally and kinetically controlled dendritic growth with convection for the case of four-fold crystal symmetry. The obtained nonlinear system of equations (representing the selection criterion and undercooling balance) for the determination of dendrite tip velocity and dendrite tip diameter is analytically solved in a parametric form. These exact solutions clearly demonstrate a transition between thermally and kinetically controlled growth regimes. In addition, we show that the dendrites with larger crystal symmetry grow faster than those with smaller symmetry.

Quantitative model validation of manipulative robot systems

NASA Astrophysics Data System (ADS)

Kartowisastro, Iman Herwidiana

This thesis is concerned with applying the distortion quantitative validation technique to a robot manipulative system with revolute joints. Using the distortion technique to validate a model quantitatively, the model parameter uncertainties are taken into account in assessing the faithfulness of the model and this approach is relatively more objective than the commonly visual comparison method. The industrial robot is represented by the TQ MA2000 robot arm. Details of the mathematical derivation of the distortion technique are given which explains the required distortion of the constant parameters within the model and the assessment of model adequacy. Due to the complexity of a robot model, only the first three degrees of freedom are considered where all links are assumed rigid. The modelling involves the Newton-Euler approach to obtain the dynamics model, and the Denavit-Hartenberg convention is used throughout the work. The conventional feedback control system is used in developing the model. The system behavior to parameter changes is investigated as some parameters are redundant. This work is important so that the most important parameters to be distorted can be selected and this leads to a new term called the fundamental parameters. The transfer function approach has been chosen to validate an industrial robot quantitatively against the measured data due to its practicality. Initially, the assessment of the model fidelity criterion indicated that the model was not capable of explaining the transient record in term of the model parameter uncertainties. Further investigations led to significant improvements of the model and better understanding of the model properties. After several improvements in the model, the fidelity criterion obtained was almost satisfied. Although the fidelity criterion is slightly less than unity, it has been shown that the distortion technique can be applied in a robot manipulative system. Using the validated model, the importance of friction terms in the model was highlighted with the aid of the partition control technique. It was also shown that the conventional feedback control scheme was insufficient for a robot manipulative system due to high nonlinearity which was inherent in the robot manipulator.

Guidelines and Parameter Selection for the Simulation of Progressive Delamination

NASA Technical Reports Server (NTRS)

Song, Kyongchan; Davila, Carlos G.; Rose, Cheryl A.

2008-01-01

Turon s methodology for determining optimal analysis parameters for the simulation of progressive delamination is reviewed. Recommended procedures for determining analysis parameters for efficient delamination growth predictions using the Abaqus/Standard cohesive element and relatively coarse meshes are provided for single and mixed-mode loading. The Abaqus cohesive element, COH3D8, and a user-defined cohesive element are used to develop finite element models of the double cantilever beam specimen, the end-notched flexure specimen, and the mixed-mode bending specimen to simulate progressive delamination growth in Mode I, Mode II, and mixed-mode fracture, respectively. The predicted responses are compared with their analytical solutions. The results show that for single-mode fracture, the predicted responses obtained with the Abaqus cohesive element correlate well with the analytical solutions. For mixed-mode fracture, it was found that the response predicted using COH3D8 elements depends on the damage evolution criterion that is used. The energy-based criterion overpredicts the peak loads and load-deflection response. The results predicted using a tabulated form of the BK criterion correlate well with the analytical solution and with the results predicted with the user-written element.

Criterion-Referenced Testing: A Critical Analysis of Selected Models

DTIC Science & Technology

1978-08-01

158025 .159372 4 (all .5 .5 0 0 .5 .5 fai l) a, bme probability that a master will be misclassified when the cutoff score is set at 2 correct equals...used the 45-item spiral - omnibus intelligence test for screening applicants to the Australian Army or Royal Australian Navy. Samples of 608 recruit...applicants to the Citizen Military Force (CM?) and 874 recruit applicants to the Royal Australian Navy were studied. Twelve items were deleted for zero

Vortex Advisory System. Volume I. Effectiveness for Selected Airports.

DTIC Science & Technology

1980-05-01

analysis of tens of thousands of vortex tracks. Wind velocity was found to be the primary determinant of vortex behavior. The VAS uses wind-velocity...and the correlation of vortex be- havior with the ambient winds. Analysis showed that a wind-rose criterion could be used to determine when interarrival...Washington DC. 2. Hallock, J.N., " Vortex Advisory System Safety Analysis , Vol. I: Analytical Model ," FAA-RD-78-68,1, Sep. 1978, DOT/ Transportation

Boosting for detection of gene-environment interactions.

PubMed

Pashova, H; LeBlanc, M; Kooperberg, C

2013-01-30

In genetic association studies, it is typically thought that genetic variants and environmental variables jointly will explain more of the inheritance of a phenotype than either of these two components separately. Traditional methods to identify gene-environment interactions typically consider only one measured environmental variable at a time. However, in practice, multiple environmental factors may each be imprecise surrogates for the underlying physiological process that actually interacts with the genetic factors. In this paper, we develop a variant of L(2) boosting that is specifically designed to identify combinations of environmental variables that jointly modify the effect of a gene on a phenotype. Because the effect modifiers might have a small signal compared with the main effects, working in a space that is orthogonal to the main predictors allows us to focus on the interaction space. In a simulation study that investigates some plausible underlying model assumptions, our method outperforms the least absolute shrinkage and selection and Akaike Information Criterion and Bayesian Information Criterion model selection procedures as having the lowest test error. In an example for the Women's Health Initiative-Population Architecture using Genomics and Epidemiology study, the dedicated boosting method was able to pick out two single-nucleotide polymorphisms for which effect modification appears present. The performance was evaluated on an independent test set, and the results are promising. Copyright © 2012 John Wiley & Sons, Ltd.

Evaluation of optimal control type models for the human gunner in an Anti-Aircraft Artillery (AAA) system

NASA Technical Reports Server (NTRS)

Phatak, A. V.; Kessler, K. M.

1975-01-01

The selection of the structure of optimal control type models for the human gunner in an anti aircraft artillery system is considered. Several structures within the LQG framework may be formulated. Two basic types are considered: (1) kth derivative controllers; and (2) proportional integral derivative (P-I-D) controllers. It is shown that a suitable criterion for model structure determination can be based on the ensemble statistics of the tracking error. In the case when the ensemble tracking steady state error is zero, it is suggested that a P-I-D controller formulation be used in preference to the kth derivative controller.

Train axle bearing fault detection using a feature selection scheme based multi-scale morphological filter

NASA Astrophysics Data System (ADS)

Li, Yifan; Liang, Xihui; Lin, Jianhui; Chen, Yuejian; Liu, Jianxin

2018-02-01

This paper presents a novel signal processing scheme, feature selection based multi-scale morphological filter (MMF), for train axle bearing fault detection. In this scheme, more than 30 feature indicators of vibration signals are calculated for axle bearings with different conditions and the features which can reflect fault characteristics more effectively and representatively are selected using the max-relevance and min-redundancy principle. Then, a filtering scale selection approach for MMF based on feature selection and grey relational analysis is proposed. The feature selection based MMF method is tested on diagnosis of artificially created damages of rolling bearings of railway trains. Experimental results show that the proposed method has a superior performance in extracting fault features of defective train axle bearings. In addition, comparisons are performed with the kurtosis criterion based MMF and the spectral kurtosis criterion based MMF. The proposed feature selection based MMF method outperforms these two methods in detection of train axle bearing faults.

Ensemble classification of individual Pinus crowns from multispectral satellite imagery and airborne LiDAR

NASA Astrophysics Data System (ADS)

Kukunda, Collins B.; Duque-Lazo, Joaquín; González-Ferreiro, Eduardo; Thaden, Hauke; Kleinn, Christoph

2018-03-01

Distinguishing tree species is relevant in many contexts of remote sensing assisted forest inventory. Accurate tree species maps support management and conservation planning, pest and disease control and biomass estimation. This study evaluated the performance of applying ensemble techniques with the goal of automatically distinguishing Pinus sylvestris L. and Pinus uncinata Mill. Ex Mirb within a 1.3 km2 mountainous area in Barcelonnette (France). Three modelling schemes were examined, based on: (1) high-density LiDAR data (160 returns m-2), (2) Worldview-2 multispectral imagery, and (3) Worldview-2 and LiDAR in combination. Variables related to the crown structure and height of individual trees were extracted from the normalized LiDAR point cloud at individual-tree level, after performing individual tree crown (ITC) delineation. Vegetation indices and the Haralick texture indices were derived from Worldview-2 images and served as independent spectral variables. Selection of the best predictor subset was done after a comparison of three variable selection procedures: (1) Random Forests with cross validation (AUCRFcv), (2) Akaike Information Criterion (AIC) and (3) Bayesian Information Criterion (BIC). To classify the species, 9 regression techniques were combined using ensemble models. Predictions were evaluated using cross validation and an independent dataset. Integration of datasets and models improved individual tree species classification (True Skills Statistic, TSS; from 0.67 to 0.81) over individual techniques and maintained strong predictive power (Relative Operating Characteristic, ROC = 0.91). Assemblage of regression models and integration of the datasets provided more reliable species distribution maps and associated tree-scale mapping uncertainties. Our study highlights the potential of model and data assemblage at improving species classifications needed in present-day forest planning and management.

Can scrotal circumference-based selection discard bulls with good productive and reproductive potential?

PubMed Central

Villadiego, Faider Alberto Castaño; Camilo, Breno Soares; León, Victor Gomez; Peixoto, Thiago; Díaz, Edgar; Okano, Denise; Maitan, Paula; Lima, Daniel; Guimarães, Simone Facioni; Siqueira, Jeanne Broch; Pinho, Rogério

2018-01-01

Nonlinear mixed models were used to describe longitudinal scrotal circumference (SC) measurements of Nellore bulls. Models comparisons were based on Akaike’s information criterion, Bayesian information criterion, error sum of squares, adjusted R2 and percentage of convergence. Sequentially, the best model was used to compare the SC growth curve in bulls divergently classified according to SC at 18–21 months of age. For this, bulls were classified into five groups: SC < 28cm; 28cm ≤ SC < 30cm, 30cm ≤ SC < 32cm, 32cm ≤ SC < 34cm and SC ≥ 34cm. Michaelis-Menten model showed the best fit according to the mentioned criteria. In this model, β1 is the asymptotic SC value and β2 represents the time to half-final growth and may be related to sexual precocity. Parameters of the individual estimated growth curves were used to create a new dataset to evaluate the effect of the classification, farms, and year of birth on β1 and β2 parameters. Bulls of the largest SC group presented a larger predicted SC along all analyzed periods; nevertheless, smaller SC group showed predicted SC similar to intermediate SC groups (28cm ≤ SC < 32cm), around 1200 days of age. In this context, bulls classified as improper for reproduction at 18–21 months old can reach a similar condition to those considered as good condition. In terms of classification at 18–21 months, asymptotic SC was similar among groups, farms and years; however, β2 differed among groups indicating that differences in growth curves are related to sexual precocity. In summary, it seems that selection based on SC at too early ages may lead to discard bulls with suitable reproductive potential. PMID:29494597

Numerical and Experimental Validation of a New Damage Initiation Criterion

NASA Astrophysics Data System (ADS)

Sadhinoch, M.; Atzema, E. H.; Perdahcioglu, E. S.; van den Boogaard, A. H.

2017-09-01

Most commercial finite element software packages, like Abaqus, have a built-in coupled damage model where a damage evolution needs to be defined in terms of a single fracture energy value for all stress states. The Johnson-Cook criterion has been modified to be Lode parameter dependent and this Modified Johnson-Cook (MJC) criterion is used as a Damage Initiation Surface (DIS) in combination with the built-in Abaqus ductile damage model. An exponential damage evolution law has been used with a single fracture energy value. Ultimately, the simulated force-displacement curves are compared with experiments to validate the MJC criterion. 7 out of 9 fracture experiments were predicted accurately. The limitations and accuracy of the failure predictions of the newly developed damage initiation criterion will be discussed shortly.

Time series ARIMA models for daily price of palm oil

NASA Astrophysics Data System (ADS)

Ariff, Noratiqah Mohd; Zamhawari, Nor Hashimah; Bakar, Mohd Aftar Abu

2015-02-01

Palm oil is deemed as one of the most important commodity that forms the economic backbone of Malaysia. Modeling and forecasting the daily price of palm oil is of great interest for Malaysia's economic growth. In this study, time series ARIMA models are used to fit the daily price of palm oil. The Akaike Infromation Criterion (AIC), Akaike Infromation Criterion with a correction for finite sample sizes (AICc) and Bayesian Information Criterion (BIC) are used to compare between different ARIMA models being considered. It is found that ARIMA(1,2,1) model is suitable for daily price of crude palm oil in Malaysia for the year 2010 to 2012.

Effect of Items Direction (Positive or Negative) on the Factorial Construction and Criterion Related Validity in Likert Scale

ERIC Educational Resources Information Center

Naji Qasem, Mamun Ali; Ahmad Gul, Showkeen Bilal

2014-01-01

The study was conducted to know the effect of items direction (positive or negative) on the factorial construction and criterion related validity in Likert scale. The descriptive survey research method was used for the study and the sample consisted of 510 undergraduate students selected by used random sampling technique. A scale developed by…

Using Norm-Referenced Data to Set Standards for a Minimum Competency Program in the State of South Carolina.

ERIC Educational Resources Information Center

Garcia-Quintana, Roan A.; Mappus, M. Lynne

1980-01-01

Norm referenced data were utilized for determining the mastery cutoff score on a criterion referenced test. Once a cutoff score on the norm referenced measure is selected, the cutoff score on the criterion referenced measure becomes that score which maximizes proportion of consistent classifications and proportion of improvement beyond change. (CP)

Growth models of Rhizophora mangle L. seedlings in tropical southwestern Atlantic

NASA Astrophysics Data System (ADS)

Lima, Karen Otoni de Oliveira; Tognella, Mônica Maria Pereira; Cunha, Simone Rabelo; Andrade, Humber Agrelli de

2018-07-01

The present study selected and compared regression models that best describe the growth curves of Rhizophora mangle seedlings based on the height (cm) and time (days) variables. The Linear, Exponential, Power Law, Monomolecular, Logistic, and Gompertz models were adjusted with non-linear formulations and minimization of the sum of the squares of the residues. The Akaike Information Criterion was used to select the best model for each seedling. After this selection, the determination coefficient, which evaluates how well a model describes height variation as a time function, was inspected. Differing from the classic population ecology studies, the Monomolecular, Three-parameter Logistic, and Gompertz models presented the best performance in describing growth, suggesting they are the most adequate options for long-term studies. The different growth curves reflect the complexity of stem growth at the seedling stage for R. mangle. The analysis of the joint distribution of the parameters initial height, growth rate, and, asymptotic size allowed the study of the species ecological attributes and to observe its intraspecific variability in each model. Our results provide a basis for interpretation of the dynamics of seedlings growth during their establishment in a mature forest, as well as its regeneration processes.

Probability density function characterization for aggregated large-scale wind power based on Weibull mixtures

DOE PAGES

Gomez-Lazaro, Emilio; Bueso, Maria C.; Kessler, Mathieu; ...

2016-02-02

Here, the Weibull probability distribution has been widely applied to characterize wind speeds for wind energy resources. Wind power generation modeling is different, however, due in particular to power curve limitations, wind turbine control methods, and transmission system operation requirements. These differences are even greater for aggregated wind power generation in power systems with high wind penetration. Consequently, models based on one-Weibull component can provide poor characterizations for aggregated wind power generation. With this aim, the present paper focuses on discussing Weibull mixtures to characterize the probability density function (PDF) for aggregated wind power generation. PDFs of wind power datamore » are firstly classified attending to hourly and seasonal patterns. The selection of the number of components in the mixture is analyzed through two well-known different criteria: the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). Finally, the optimal number of Weibull components for maximum likelihood is explored for the defined patterns, including the estimated weight, scale, and shape parameters. Results show that multi-Weibull models are more suitable to characterize aggregated wind power data due to the impact of distributed generation, variety of wind speed values and wind power curtailment.« less

Chemical library subset selection algorithms: a unified derivation using spatial statistics.

PubMed

Hamprecht, Fred A; Thiel, Walter; van Gunsteren, Wilfred F

2002-01-01

If similar compounds have similar activity, rational subset selection becomes superior to random selection in screening for pharmacological lead discovery programs. Traditional approaches to this experimental design problem fall into two classes: (i) a linear or quadratic response function is assumed (ii) some space filling criterion is optimized. The assumptions underlying the first approach are clear but not always defendable; the second approach yields more intuitive designs but lacks a clear theoretical foundation. We model activity in a bioassay as realization of a stochastic process and use the best linear unbiased estimator to construct spatial sampling designs that optimize the integrated mean square prediction error, the maximum mean square prediction error, or the entropy. We argue that our approach constitutes a unifying framework encompassing most proposed techniques as limiting cases and sheds light on their underlying assumptions. In particular, vector quantization is obtained, in dimensions up to eight, in the limiting case of very smooth response surfaces for the integrated mean square error criterion. Closest packing is obtained for very rough surfaces under the integrated mean square error and entropy criteria. We suggest to use either the integrated mean square prediction error or the entropy as optimization criteria rather than approximations thereof and propose a scheme for direct iterative minimization of the integrated mean square prediction error. Finally, we discuss how the quality of chemical descriptors manifests itself and clarify the assumptions underlying the selection of diverse or representative subsets.

Controlling the Growth of Future LEO Debris Populations with Active Debris Removal

NASA Technical Reports Server (NTRS)

Liou, J.-C.; Johnson, N. L.; Hill, N. M.

2008-01-01

Active debris removal (ADR) was suggested as a potential means to remediate the low Earth orbit (LEO) debris environment as early as the 1980s. The reasons ADR has not become practical are due to its technical difficulties and the high cost associated with the approach. However, as the LEO debris populations continue to increase, ADR may be the only option to preserve the near-Earth environment for future generations. An initial study was completed in 2007 to demonstrate that a simple ADR target selection criterion could be developed to reduce the future debris population growth. The present paper summarizes a comprehensive study based on more realistic simulation scenarios, including fragments generated from the 2007 Fengyun-1C event, mitigation measures, and other target selection options. The simulations were based on the NASA long-term orbital debris projection model, LEGEND. A scenario, where at the end of mission lifetimes, spacecraft and upper stages were moved to 25-year decay orbits, was adopted as the baseline environment for comparison. Different annual removal rates and different ADR target selection criteria were tested, and the resulting 200-year future environment projections were compared with the baseline scenario. Results of this parametric study indicate that (1) an effective removal strategy can be developed based on the mass and collision probability of each object as the selection criterion, and (2) the LEO environment can be stabilized in the next 200 years with an ADR removal rate of five objects per year.

Predicting operator workload during system design

NASA Technical Reports Server (NTRS)

Aldrich, Theodore B.; Szabo, Sandra M.

1988-01-01

A workload prediction methodology was developed in response to the need to measure workloads associated with operation of advanced aircraft. The application of the methodology will involve: (1) conducting mission/task analyses of critical mission segments and assigning estimates of workload for the sensory, cognitive, and psychomotor workload components of each task identified; (2) developing computer-based workload prediction models using the task analysis data; and (3) exercising the computer models to produce predictions of crew workload under varying automation and/or crew configurations. Critical issues include reliability and validity of workload predictors and selection of appropriate criterion measures.

Properties of DRGs, LBGs, and BzK Galaxies in the GOODS South Field

NASA Astrophysics Data System (ADS)

Grazian, A.; Salimbeni, S.; Pentericci, L.; Fontana, A.; Santini, P.; Giallongo, E.; de Santis, C.; Gallozzi, S.; Nonino, M.; Cristiani, S.; Vanzella, E.

2007-12-01

We use the GOODS-MUSIC catalog with multi-wavelength coverage extending from the U band to the Spitzer 8 μm band, and spectroscopic or accurate photometric redshifts to select samples of BM/BX/LBGs, DRGs, and BzK galaxies. We discuss the overlap and the limitations of these selection criteria, which can be overcome with a criterion based on physical parameters (age and star formation timescale). We show that the BzK-PE criterion is not optimal for selecting early type galaxies at the faint end. We also find that LBGs and DRGs contribute almost equally to the global Stellar Mass Density (SMD) at z≥ 2 and in general that star forming galaxies form a substantial fraction of the universal SMD.

[GSH fermentation process modeling using entropy-criterion based RBF neural network model].

PubMed

Tan, Zuoping; Wang, Shitong; Deng, Zhaohong; Du, Guocheng

2008-05-01

The prediction accuracy and generalization of GSH fermentation process modeling are often deteriorated by noise existing in the corresponding experimental data. In order to avoid this problem, we present a novel RBF neural network modeling approach based on entropy criterion. It considers the whole distribution structure of the training data set in the parameter learning process compared with the traditional MSE-criterion based parameter learning, and thus effectively avoids the weak generalization and over-learning. Then the proposed approach is applied to the GSH fermentation process modeling. Our results demonstrate that this proposed method has better prediction accuracy, generalization and robustness such that it offers a potential application merit for the GSH fermentation process modeling.

Uncertainty, imprecision, and the precautionary principle in climate change assessment.

PubMed

Borsuk, M E; Tomassini, L

2005-01-01

Statistical decision theory can provide useful support for climate change decisions made under conditions of uncertainty. However, the probability distributions used to calculate expected costs in decision theory are themselves subject to uncertainty, disagreement, or ambiguity in their specification. This imprecision can be described using sets of probability measures, from which upper and lower bounds on expectations can be calculated. However, many representations, or classes, of probability measures are possible. We describe six of the more useful classes and demonstrate how each may be used to represent climate change uncertainties. When expected costs are specified by bounds, rather than precise values, the conventional decision criterion of minimum expected cost is insufficient to reach a unique decision. Alternative criteria are required, and the criterion of minimum upper expected cost may be desirable because it is consistent with the precautionary principle. Using simple climate and economics models as an example, we determine the carbon dioxide emissions levels that have minimum upper expected cost for each of the selected classes. There can be wide differences in these emissions levels and their associated costs, emphasizing the need for care when selecting an appropriate class.

[What determines the participation in stepwise occupational reintegration on behalf of the German pension insurance? Results of the "SOR cohort study"].

PubMed

Bürger, W; Streibelt, M

2015-02-01

Stepwise Occupational Reintegration (SOR) measures are of growing importance for the German statutory pension insurance. There is moderate evidence that patients with a poor prognosis in terms of a successful return to work, profit most from SOR measures. However, it is not clear to what extend these information are utilized when recommending SOR to a patient. A questionnaire was sent to 40406 persons (up to 59 years old, excluding rehabilitation after hospital stay) before admission to a medical rehabilitation service. The survey data were matched with data from the discharge report and information on the participation in a SOR measure. Initially, a single criterion was defined which describes the need of SOR measures. This criterion is based on 3 different items: patients with at least 12 weeks sickness absence, (a) a SIBAR score>7 and/or (b) a perceived need of SOR.The main aspect of our analyses was to describe the association between the SOR need-criterion and the participation in SOR measures as well as between the predictors of SOR participation when fulfilling the SOR need-criterion. The analyses were based on a multiple logistic regression model. For 16408 patients full data were available. The formal prerequisites for SOR were given for 33% of the sample, out of which 32% received a SOR after rehabilitation and 43% fulfilled the SOR needs criterion. A negative relationship between these 2 categories was observed (phi=-0.08, p<0.01). For patients that fulfilled the need-criterion the probability for participating in SOR decreased by 22% (RR=0.78). The probability of SOR participation increased with a decreasing SIBAR score (OR=0.56) and in patients who showed more confidence in being able be return to work. Participation in SOR measures cannot be predicted by the empirically defined SOR need-criterion: the probability even decreased when fulfilling the criterion. Furthermore, the results of a multivariate analysis show a positive selection of the patients who participate in SOR measures. Our results point strongly to the need of an indication guideline for physicians in rehabilitation centres. Further research addressing the success of SOR measures have to show whether the information used in this case can serve as a base for such a guideline. © Georg Thieme Verlag KG Stuttgart · New York.

Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle.

PubMed

Pereira, R J; Bignardi, A B; El Faro, L; Verneque, R S; Vercesi Filho, A E; Albuquerque, L G

2013-01-01

Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Assessing potential effects of highway runoff on receiving-water quality at selected sites in Oregon with the Stochastic Empirical Loading and Dilution Model (SELDM)

USGS Publications Warehouse

Risley, John C.; Granato, Gregory E.

2014-01-01

6. An analysis of the use of grab sampling and nonstochastic upstream modeling methods was done to evaluate the potential effects on modeling outcomes. Additional analyses using surrogate water-quality datasets for the upstream basin and highway catchment were provided for six Oregon study sites to illustrate the risk-based information that SELDM will produce. These analyses show that the potential effects of highway runoff on receiving-water quality downstream of the outfall depends on the ratio of drainage areas (dilution), the quality of the receiving water upstream of the highway, and the concentration of the criteria of the constituent of interest. These analyses also show that the probability of exceeding a water-quality criterion may depend on the input statistics used, thus careful selection of representative values is important.

Technical issues affecting the implementation of US Environmental Protection Agency's proposed fish tissue-based aquatic criterion for selenium.

PubMed

Lemly, A Dennis; Skorupa, Joseph P

2007-10-01

The US Environmental Protection Agency is developing a national water quality criterion for selenium that is based on concentrations of the element in fish tissue. Although this approach offers advantages over the current water-based regulations, it also presents new challenges with respect to implementation. A comprehensive protocol that answers the "what, where, and when" is essential with the new tissue-based approach in order to ensure proper acquisition of data that apply to the criterion. Dischargers will need to understand selenium transport, cycling, and bioaccumulation in order to effectively monitor for the criterion and, if necessary, develop site-specific standards. This paper discusses 11 key issues that affect the implementation of a tissue-based criterion, ranging from the selection of fish species to the importance of hydrological units in the sampling design. It also outlines a strategy that incorporates both water column and tissue-based approaches. A national generic safety-net water criterion could be combined with a fish tissue-based criterion for site-specific implementation. For the majority of waters nationwide, National Pollution Discharge Elimination System permitting and other activities associated with the Clean Water Act could continue without the increased expense of sampling and interpreting biological materials. Dischargers would do biotic sampling intermittently (not a routine monitoring burden) on fish tissue relative to the fish tissue criterion. Only when the fish tissue criterion is exceeded would a full site-specific analysis including development of intermedia translation factors be necessary.

Does the Committee Peer Review Select the Best Applicants for Funding? An Investigation of the Selection Process for Two European Molecular Biology Organization Programmes

PubMed Central

Bornmann, Lutz; Wallon, Gerlind; Ledin, Anna

2008-01-01

Does peer review fulfill its declared objective of identifying the best science and the best scientists? In order to answer this question we analyzed the Long-Term Fellowship and the Young Investigator programmes of the European Molecular Biology Organization. Both programmes aim to identify and support the best post doctoral fellows and young group leaders in the life sciences. We checked the association between the selection decisions and the scientific performance of the applicants. Our study involved publication and citation data for 668 applicants to the Long-Term Fellowship programme from the year 1998 (130 approved, 538 rejected) and 297 applicants to the Young Investigator programme (39 approved and 258 rejected applicants) from the years 2001 and 2002. If quantity and impact of research publications are used as a criterion for scientific achievement, the results of (zero-truncated) negative binomial models show that the peer review process indeed selects scientists who perform on a higher level than the rejected ones subsequent to application. We determined the extent of errors due to over-estimation (type I errors) and under-estimation (type 2 errors) of future scientific performance. Our statistical analyses point out that between 26% and 48% of the decisions made to award or reject an application show one of both error types. Even though for a part of the applicants, the selection committee did not correctly estimate the applicant's future performance, the results show a statistically significant association between selection decisions and the applicants' scientific achievements, if quantity and impact of research publications are used as a criterion for scientific achievement. PMID:18941530

Red-shouldered hawk nesting habitat preference in south Texas

USGS Publications Warehouse

Strobel, Bradley N.; Boal, Clint W.

2010-01-01

We examined nesting habitat preference by red-shouldered hawks Buteo lineatus using conditional logistic regression on characteristics measured at 27 occupied nest sites and 68 unused sites in 2005–2009 in south Texas. We measured vegetation characteristics of individual trees (nest trees and unused trees) and corresponding 0.04-ha plots. We evaluated the importance of tree and plot characteristics to nesting habitat selection by comparing a priori tree-specific and plot-specific models using Akaike's information criterion. Models with only plot variables carried 14% more weight than models with only center tree variables. The model-averaged odds ratios indicated red-shouldered hawks selected to nest in taller trees and in areas with higher average diameter at breast height than randomly available within the forest stand. Relative to randomly selected areas, each 1-m increase in nest tree height and 1-cm increase in the plot average diameter at breast height increased the probability of selection by 85% and 10%, respectively. Our results indicate that red-shouldered hawks select nesting habitat based on vegetation characteristics of individual trees as well as the 0.04-ha area surrounding the tree. Our results indicate forest management practices resulting in tall forest stands with large average diameter at breast height would benefit red-shouldered hawks in south Texas.

A new methodology based on sensitivity analysis to simplify the recalibration of functional-structural plant models in new conditions.

PubMed

Mathieu, Amélie; Vidal, Tiphaine; Jullien, Alexandra; Wu, QiongLi; Chambon, Camille; Bayol, Benoit; Cournède, Paul-Henry

2018-06-19

Functional-structural plant models (FSPMs) describe explicitly the interactions between plants and their environment at organ to plant scale. However, the high level of description of the structure or model mechanisms makes this type of model very complex and hard to calibrate. A two-step methodology to facilitate the calibration process is proposed here. First, a global sensitivity analysis method was applied to the calibration loss function. It provided first-order and total-order sensitivity indexes that allow parameters to be ranked by importance in order to select the most influential ones. Second, the Akaike information criterion (AIC) was used to quantify the model's quality of fit after calibration with different combinations of selected parameters. The model with the lowest AIC gives the best combination of parameters to select. This methodology was validated by calibrating the model on an independent data set (same cultivar, another year) with the parameters selected in the second step. All the parameters were set to their nominal value; only the most influential ones were re-estimated. Sensitivity analysis applied to the calibration loss function is a relevant method to underline the most significant parameters in the estimation process. For the studied winter oilseed rape model, 11 out of 26 estimated parameters were selected. Then, the model could be recalibrated for a different data set by re-estimating only three parameters selected with the model selection method. Fitting only a small number of parameters dramatically increases the efficiency of recalibration, increases the robustness of the model and helps identify the principal sources of variation in varying environmental conditions. This innovative method still needs to be more widely validated but already gives interesting avenues to improve the calibration of FSPMs.

Accounting for uncertainty in health economic decision models by using model averaging.

PubMed

Jackson, Christopher H; Thompson, Simon G; Sharples, Linda D

2009-04-01

Health economic decision models are subject to considerable uncertainty, much of which arises from choices between several plausible model structures, e.g. choices of covariates in a regression model. Such structural uncertainty is rarely accounted for formally in decision models but can be addressed by model averaging. We discuss the most common methods of averaging models and the principles underlying them. We apply them to a comparison of two surgical techniques for repairing abdominal aortic aneurysms. In model averaging, competing models are usually either weighted by using an asymptotically consistent model assessment criterion, such as the Bayesian information criterion, or a measure of predictive ability, such as Akaike's information criterion. We argue that the predictive approach is more suitable when modelling the complex underlying processes of interest in health economics, such as individual disease progression and response to treatment.

A Clue to the Extent of Convective Mixing Inside Massive Stars: The Surface Hydrogen Abundances of Luminous Blue Variables and Hydrogen-Poor Wolf-Rayet Stars

NASA Technical Reports Server (NTRS)

Stothers, Richard B.; Chin, Chao-wen

1999-01-01

Interior layers of stars that have been exposed by surface mass loss reveal aspects of their chemical and convective histories that are otherwise inaccessible to observation. It must be significant that the surface hydrogen abundances of luminous blue variables (LBVs) show a remarkable uniformity, specifically X(sub surf) = 0.3 - 0.4, while those of hydrogen-poor Wolf-Rayet (WN) stars fall, almost without exception, below these values, ranging down to X(sub surf) = 0. According to our stellar model calculations, most LBVs are post-red-supergiant objects in a late blue phase of dynamical instability, and most hydrogen-poor WN stars are their immediate descendants. If this is so, stellar models constructed with the Schwarzschild (temperature-gradient) criterion for convection account well for the observed hydrogen abundances, whereas models built with the Ledoux (density-gradient) criterion fail. At the brightest luminosities, the observed hydrogen abundances of LBVs are too large to be explained by any of our highly evolved stellar models, but these LBVs may occupy transient blue loops that exist during an earlier phase of dynamical instability when the star first becomes a yellow supergiant. Independent evidence concerning the criterion for convection, which is based mostly on traditional color distributions of less massive supergiants on the Hertzsprung-Russell diagram, tends to favor the Ledoux criterion. It is quite possible that the true criterion for convection changes over from something like the Ledoux criterion to something like the Schwarzschild criterion as the stellar mass increases.

On the theory of compliant wall drag reduction in turbulent boundary layers

NASA Technical Reports Server (NTRS)

Ash, R. L.

1974-01-01

A theoretical model has been developed which can explain how the motion of a compliant wall reduces turbulent skin friction drag. Available experimental evidence at low speeds has been used to infer that a compliant surface selectively removes energy from the upper frequency range of the energy containing eddies and through resulting surface motions can produce locally negative Reynolds stresses at the wall. The theory establishes a preliminary amplitude and frequency criterion as the basis for designing effective drag reducing compliant surfaces.

Implementation of model predictive control for resistive wall mode stabilization on EXTRAP T2R

NASA Astrophysics Data System (ADS)

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

2015-10-01

A model predictive control (MPC) method for stabilization of the resistive wall mode (RWM) in the EXTRAP T2R reversed-field pinch is presented. The system identification technique is used to obtain a linearized empirical model of EXTRAP T2R. MPC employs the model for prediction and computes optimal control inputs that satisfy performance criterion. The use of a linearized form of the model allows for compact formulation of MPC, implemented on a millisecond timescale, that can be used for real-time control. The design allows the user to arbitrarily suppress any selected Fourier mode. The experimental results from EXTRAP T2R show that the designed and implemented MPC successfully stabilizes the RWM.

The Causal Meaning of Genomic Predictors and How It Affects Construction and Comparison of Genome-Enabled Selection Models

PubMed Central

Valente, Bruno D.; Morota, Gota; Peñagaricano, Francisco; Gianola, Daniel; Weigel, Kent; Rosa, Guilherme J. M.

2015-01-01

The term “effect” in additive genetic effect suggests a causal meaning. However, inferences of such quantities for selection purposes are typically viewed and conducted as a prediction task. Predictive ability as tested by cross-validation is currently the most acceptable criterion for comparing models and evaluating new methodologies. Nevertheless, it does not directly indicate if predictors reflect causal effects. Such evaluations would require causal inference methods that are not typical in genomic prediction for selection. This suggests that the usual approach to infer genetic effects contradicts the label of the quantity inferred. Here we investigate if genomic predictors for selection should be treated as standard predictors or if they must reflect a causal effect to be useful, requiring causal inference methods. Conducting the analysis as a prediction or as a causal inference task affects, for example, how covariates of the regression model are chosen, which may heavily affect the magnitude of genomic predictors and therefore selection decisions. We demonstrate that selection requires learning causal genetic effects. However, genomic predictors from some models might capture noncausal signal, providing good predictive ability but poorly representing true genetic effects. Simulated examples are used to show that aiming for predictive ability may lead to poor modeling decisions, while causal inference approaches may guide the construction of regression models that better infer the target genetic effect even when they underperform in cross-validation tests. In conclusion, genomic selection models should be constructed to aim primarily for identifiability of causal genetic effects, not for predictive ability. PMID:25908318

A mathematical programming method for formulating a fuzzy regression model based on distance criterion.

PubMed

Chen, Liang-Hsuan; Hsueh, Chan-Ching

2007-06-01

Fuzzy regression models are useful to investigate the relationship between explanatory and response variables with fuzzy observations. Different from previous studies, this correspondence proposes a mathematical programming method to construct a fuzzy regression model based on a distance criterion. The objective of the mathematical programming is to minimize the sum of distances between the estimated and observed responses on the X axis, such that the fuzzy regression model constructed has the minimal total estimation error in distance. Only several alpha-cuts of fuzzy observations are needed as inputs to the mathematical programming model; therefore, the applications are not restricted to triangular fuzzy numbers. Three examples, adopted in the previous studies, and a larger example, modified from the crisp case, are used to illustrate the performance of the proposed approach. The results indicate that the proposed model has better performance than those in the previous studies based on either distance criterion or Kim and Bishu's criterion. In addition, the efficiency and effectiveness for solving the larger example by the proposed model are also satisfactory.

Large Area Crop Inventory Experiment (LACIE). YES phase 1 yield feasibility report

NASA Technical Reports Server (NTRS)

1977-01-01

The author has identified the following significant results. Each state model was separately evaluated to determine if a projected performance to the country level would satisfy a 90/90 criterion. All state models, except the North Dakota and Kansas models, satisfied that criterion both for district estimates aggregated to the state level and for state estimates directly from the models. In addition to the tests of the 90/90 criterion, the models were examined for their ability to adequately respond to fluctuations in weather. This portion of the analysis was based on a subjective interpretation of values of certain description statistics. As a result, 10 of the 12 models were judged to respond inadequately to variation in weather-related variables.

New criteria for isotropic and textured metals

NASA Astrophysics Data System (ADS)

Cazacu, Oana

2018-05-01

In this paper a isotropic criterion expressed in terms of both invariants of the stress deviator, J2 and J3 is proposed. This criterion involves a unique parameter, α, which depends only on the ratio between the yield stresses in uniaxial tension and pure shear. If this parameter is zero, the von Mises yield criterion is recovered; if a is positive the yield surface is interior to the von Mises yield surface whereas when a is negative, the new yield surface is exterior to it. Comparison with polycrystalline calculations using Taylor-Bishop-Hill model [1] for randomly oriented face-centered (FCC) polycrystalline metallic materials show that this new criterion captures well the numerical yield points. Furthermore, the criterion reproduces well yielding under combined tension-shear loadings for a variety of isotropic materials. An extension of this isotropic yield criterion such as to account for orthotropy in yielding is developed using the generalized invariants approach of Cazacu and Barlat [2]. This new orthotropic criterion is general and applicable to three-dimensional stress states. The procedure for the identification of the material parameters is outlined. Illustration of the predictive capabilities of the new orthotropic is demonstrated through comparison between the model predictions and data on aluminum sheet samples.

Analyzing Genome-Wide Association Studies with an FDR Controlling Modification of the Bayesian Information Criterion

PubMed Central

Dolejsi, Erich; Bodenstorfer, Bernhard; Frommlet, Florian

2014-01-01

The prevailing method of analyzing GWAS data is still to test each marker individually, although from a statistical point of view it is quite obvious that in case of complex traits such single marker tests are not ideal. Recently several model selection approaches for GWAS have been suggested, most of them based on LASSO-type procedures. Here we will discuss an alternative model selection approach which is based on a modification of the Bayesian Information Criterion (mBIC2) which was previously shown to have certain asymptotic optimality properties in terms of minimizing the misclassification error. Heuristic search strategies are introduced which attempt to find the model which minimizes mBIC2, and which are efficient enough to allow the analysis of GWAS data. Our approach is implemented in a software package called MOSGWA. Its performance in case control GWAS is compared with the two algorithms HLASSO and d-GWASelect, as well as with single marker tests, where we performed a simulation study based on real SNP data from the POPRES sample. Our results show that MOSGWA performs slightly better than HLASSO, where specifically for more complex models MOSGWA is more powerful with only a slight increase in Type I error. On the other hand according to our simulations GWASelect does not at all control the type I error when used to automatically determine the number of important SNPs. We also reanalyze the GWAS data from the Wellcome Trust Case-Control Consortium and compare the findings of the different procedures, where MOSGWA detects for complex diseases a number of interesting SNPs which are not found by other methods. PMID:25061809

Diel habitat selection of largemouth bass following woody structure installation in Table Rock Lake, Missouri

USGS Publications Warehouse

Harris, J.M.; Paukert, Craig P.; Bush, S.C.; Allen, M.J.; Siepker, Michael

2018-01-01

Largemouth bass Micropterus salmoides (Lacepède) use of installed habitat structure was evaluated in a large Midwestern USA reservoir to determine whether or not these structures were used in similar proportion to natural habitats. Seventy largemouth bass (>380 mm total length) were surgically implanted with radio transmitters and a subset was relocated monthly during day and night for one year. The top habitat selection models (based on Akaike's information criterion) suggest largemouth bass select 2–4 m depths during night and 4–7 m during day, whereas littoral structure selection was similar across diel periods. Largemouth bass selected boat docks at twice the rate of other structures. Installed woody structure was selected at similar rates to naturally occurring complex woody structure, whereas both were selected at a higher rate than simple woody structure. The results suggest the addition of woody structure may concentrate largemouth bass and mitigate the loss of woody habitat in a large reservoir.

Two criteria for the selection of assembly plans - Maximizing the flexibility of sequencing the assembly tasks and minimizing the assembly time through parallel execution of assembly tasks

NASA Technical Reports Server (NTRS)

Homem De Mello, Luiz S.; Sanderson, Arthur C.

1991-01-01

The authors introduce two criteria for the evaluation and selection of assembly plans. The first criterion is to maximize the number of different sequences in which the assembly tasks can be executed. The second criterion is to minimize the total assembly time through simultaneous execution of assembly tasks. An algorithm that performs a heuristic search for the best assembly plan over the AND/OR graph representation of assembly plans is discussed. Admissible heuristics for each of the two criteria introduced are presented. Some implementation issues that affect the computational efficiency are addressed.

Thermal induced flow oscillations in heat exchangers for supercritical fluids

NASA Technical Reports Server (NTRS)

Friedly, J. C.; Manganaro, J. L.; Krueger, P. G.

1972-01-01

Analytical model has been developed to predict possible unstable behavior in supercritical heat exchangers. From complete model, greatly simplified stability criterion is derived. As result of this criterion, stability of heat exchanger system can be predicted in advance.

Does the choice of nucleotide substitution models matter topologically?

PubMed

Hoff, Michael; Orf, Stefan; Riehm, Benedikt; Darriba, Diego; Stamatakis, Alexandros

2016-03-24

In the context of a master level programming practical at the computer science department of the Karlsruhe Institute of Technology, we developed and make available an open-source code for testing all 203 possible nucleotide substitution models in the Maximum Likelihood (ML) setting under the common Akaike, corrected Akaike, and Bayesian information criteria. We address the question if model selection matters topologically, that is, if conducting ML inferences under the optimal, instead of a standard General Time Reversible model, yields different tree topologies. We also assess, to which degree models selected and trees inferred under the three standard criteria (AIC, AICc, BIC) differ. Finally, we assess if the definition of the sample size (#sites versus #sites × #taxa) yields different models and, as a consequence, different tree topologies. We find that, all three factors (by order of impact: nucleotide model selection, information criterion used, sample size definition) can yield topologically substantially different final tree topologies (topological difference exceeding 10 %) for approximately 5 % of the tree inferences conducted on the 39 empirical datasets used in our study. We find that, using the best-fit nucleotide substitution model may change the final ML tree topology compared to an inference under a default GTR model. The effect is less pronounced when comparing distinct information criteria. Nonetheless, in some cases we did obtain substantial topological differences.

Decision support system of e-book provider selection for library using Simple Additive Weighting

NASA Astrophysics Data System (ADS)

Ciptayani, P. I.; Dewi, K. C.

2018-01-01

Each library has its own criteria and differences in the importance of each criterion in choosing an e-book provider for them. The large number of providers and the different importance levels of each criterion make the problem of determining the e-book provider to be complex and take a considerable time in decision making. The aim of this study was to implement Decision support system (DSS) to assist the library in selecting the best e-book provider based on their preferences. The way of DSS works is by comparing the importance of each criterion and the condition of each alternative decision. SAW is one of DSS method that is quite simple, fast and widely used. This study used 9 criteria and 18 provider to demonstrate how SAW work in this study. With the DSS, then the decision-making time can be shortened and the calculation results can be more accurate than manual calculations.

Accounting for uncertainty in health economic decision models by using model averaging

PubMed Central

Jackson, Christopher H; Thompson, Simon G; Sharples, Linda D

2009-01-01

Health economic decision models are subject to considerable uncertainty, much of which arises from choices between several plausible model structures, e.g. choices of covariates in a regression model. Such structural uncertainty is rarely accounted for formally in decision models but can be addressed by model averaging. We discuss the most common methods of averaging models and the principles underlying them. We apply them to a comparison of two surgical techniques for repairing abdominal aortic aneurysms. In model averaging, competing models are usually either weighted by using an asymptotically consistent model assessment criterion, such as the Bayesian information criterion, or a measure of predictive ability, such as Akaike's information criterion. We argue that the predictive approach is more suitable when modelling the complex underlying processes of interest in health economics, such as individual disease progression and response to treatment. PMID:19381329

Transformation and model choice for RNA-seq co-expression analysis.

PubMed

Rau, Andrea; Maugis-Rabusseau, Cathy

2018-05-01

Although a large number of clustering algorithms have been proposed to identify groups of co-expressed genes from microarray data, the question of if and how such methods may be applied to RNA sequencing (RNA-seq) data remains unaddressed. In this work, we investigate the use of data transformations in conjunction with Gaussian mixture models for RNA-seq co-expression analyses, as well as a penalized model selection criterion to select both an appropriate transformation and number of clusters present in the data. This approach has the advantage of accounting for per-cluster correlation structures among samples, which can be strong in RNA-seq data. In addition, it provides a rigorous statistical framework for parameter estimation, an objective assessment of data transformations and number of clusters and the possibility of performing diagnostic checks on the quality and homogeneity of the identified clusters. We analyze four varied RNA-seq data sets to illustrate the use of transformations and model selection in conjunction with Gaussian mixture models. Finally, we propose a Bioconductor package coseq (co-expression of RNA-seq data) to facilitate implementation and visualization of the recommended RNA-seq co-expression analyses.

A flexible model for correlated medical costs, with application to medical expenditure panel survey data.

PubMed

Chen, Jinsong; Liu, Lei; Shih, Ya-Chen T; Zhang, Daowen; Severini, Thomas A

2016-03-15

We propose a flexible model for correlated medical cost data with several appealing features. First, the mean function is partially linear. Second, the distributional form for the response is not specified. Third, the covariance structure of correlated medical costs has a semiparametric form. We use extended generalized estimating equations to simultaneously estimate all parameters of interest. B-splines are used to estimate unknown functions, and a modification to Akaike information criterion is proposed for selecting knots in spline bases. We apply the model to correlated medical costs in the Medical Expenditure Panel Survey dataset. Simulation studies are conducted to assess the performance of our method. Copyright © 2015 John Wiley & Sons, Ltd.

Strength Evaluation and Failure Prediction of Short Carbon Fiber Reinforced Nylon Spur Gears by Finite Element Modeling

NASA Astrophysics Data System (ADS)

Hu, Zhong; Hossan, Mohammad Robiul

2013-06-01

In this paper, short carbon fiber reinforced nylon spur gear pairs, and steel and unreinforced nylon spur gear pairs have been selected for study and comparison. A 3D finite element model was developed to simulate the multi-axial stress-strain behaviors of the gear tooth. Failure prediction has been conducted based on the different failure criteria, including Tsai-Wu criterion. The tooth roots, where has stress concentration and the potential for failure, have been carefully investigated. The modeling results show that the short carbon fiber reinforced nylon gear fabricated by properly controlled injection molding processes can provide higher strength and better performance.

Evaluation and clinical significance of the stomach age model for evaluating aging of the stomach-a multicenter study in China

PubMed Central

2014-01-01

Background A higher prevalence of chronic atrophic gastritis (CAG) occurs in younger adults in Asia. We used Stomach Age to examine the different mechanisms of CAG between younger adults and elderly individuals, and established a simple model of cancer risk that can be applied to CAG surveillance. Methods Stomach Age was determined by FISH examination of telomere length in stomach biopsies. Δψm was also determined by flow cytometry. Sixty volunteers were used to confirm the linear relationship between telomere length and age while 120 subjects were used to build a mathematical model by a multivariate analysis. Overall, 146 subjects were used to evaluate the validity of the model, and 1,007 subjects were used to evaluate the relationship between prognosis and Δage (calculated from the mathematical model). ROC curves were used to evaluate the relationship between prognosis and Δage and to determine the cut-off point for Δage. Results We established that a tight linear relationship between the telomere length and the age. The telomere length was obvious different between patients with and without CAG even in the same age. Δψm decreased in individuals whose Stomach Age was greater than real age, especially in younger adults. A mathematical model of Stomach Age (real age + Δage) was successfully constructed which was easy to apply in clinical work. A higher Δage was correlated with a worse outcome. The criterion of Δage >3.11 should be considered as the cut-off to select the subgroup of patients who require endoscopic surveillance. Conclusion Variation in Stomach Age between individuals of the same biological age was confirmed. Attention should be paid to those with a greater Stomach Age, especially in younger adults. The Δage in the Simple Model can be used as a criterion to select CAG patients for gastric cancer surveillance. PMID:25057261

[Silvicultural treatments and their selection effects].

PubMed

Vincent, G

1973-01-01

Selection can be defined in terms of its observable consequences as the non random differential reproduction of genotypes (Lerner 1958). In the forest stands we are selecting during the improvements-fellings and reproduction treatments the individuals surpassing in growth or in production of first-class timber. However the silvicultural treatments taken in forest stands guarantee a permanent increase of forest production only in such cases, if they have been taken with respect to the principles of directional (dynamic) selection. These principles require that the trees determined for further growing and for forest regeneration are selected by their hereditary properties, i.e. by their genotypes.For making this selection feasible, our study deals with the genetic parameters and gives some examples of the application of the response, the selection differential, the heritability in the narrow and in the broad sense, as well as of the genetic and genotypic gain. On the strength of this parameter we have the possibility to estimate the economic success of several silvicultural treatments in forest stands.The mentioned examples demonstrate that the selection measures of a higher intensity will be manifested in a higher selection differential, in a higher genetic and genotypic gain and that the mentioned measures show more distinct effects in the variable populations - in natural forest - than in the population characteristic by a smaller variability, e.g. in many uniform artificially established stands.The examples of influences of different selection on the genotypes composition of population prove that genetics instructs us to differentiate the different genotypes of the same species and gives us at the same time a new criterions for evaluating selectional treatments. These criterions from economic point of view is necessary to consider in silviculture as advantageous even for the reason that we can judge from these criterions the genetical composition of forest stands in the following generation, it means, within the scope of time for more than a human age.

TESTING NONSTANDARD COSMOLOGICAL MODELS WITH SNLS3 SUPERNOVA DATA AND OTHER COSMOLOGICAL PROBES

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

Li Zhengxiang; Yu Hongwei; Wu Puxun, E-mail: hwyu@hunnu.edu.cn

2012-01-10

We investigate the implications for some nonstandard cosmological models using data from the first three years of the Supernova Legacy Survey (SNLS3), assuming a spatially flat universe. A comparison between the constraints from the SNLS3 and those from other SN Ia samples, such as the ESSENCE, Union2, SDSS-II, and Constitution samples, is given and the effects of different light-curve fitters are considered. We find that analyzing SNe Ia with SALT2 or SALT or SiFTO can give consistent results and the tensions between different data sets and different light-curve fitters are obvious for fewer-free-parameters models. At the same time, we alsomore » study the constraints from SNLS3 along with data from the cosmic microwave background and the baryonic acoustic oscillations (CMB/BAO), and the latest Hubble parameter versus redshift (H(z)). Using model selection criteria such as {chi}{sup 2}/dof, goodness of fit, Akaike information criterion, and Bayesian information criterion, we find that, among all the cosmological models considered here ({Lambda}CDM, constant w, varying w, Dvali-Gabadadze-Porrati (DGP), modified polytropic Cardassian, and the generalized Chaplygin gas), the flat DGP is favored by SNLS3 alone. However, when additional CMB/BAO or H(z) constraints are included, this is no longer the case, and the flat {Lambda}CDM becomes preferred.« less

Ellipticity angle of electromagnetic signals and its use for non-energetic detection optimal by the Neumann-Pearson criterion

NASA Astrophysics Data System (ADS)

Gromov, V. A.; Sharygin, G. S.; Mironov, M. V.

2012-08-01

An interval method of radar signal detection and selection based on non-energetic polarization parameter - the ellipticity angle - is suggested. The examined method is optimal by the Neumann-Pearson criterion. The probability of correct detection for a preset probability of false alarm is calculated for different signal/noise ratios. Recommendations for optimization of the given method are provided.

Selection of effective cocrystals former for dissolution rate improvement of active pharmaceutical ingredients based on lipoaffinity index.

PubMed

Cysewski, Piotr; Przybyłek, Maciej

2017-09-30

New theoretical screening procedure was proposed for appropriate selection of potential cocrystal formers possessing the ability of enhancing dissolution rates of drugs. The procedure relies on the training set comprising 102 positive and 17 negative cases of cocrystals found in the literature. Despite the fact that the only available data were of qualitative character, performed statistical analysis using binary classification allowed to formulate quantitative criterions. Among considered 3679 molecular descriptors the relative value of lipoaffinity index, expressed as the difference between values calculated for active compound and excipient, has been found as the most appropriate measure suited for discrimination of positive and negative cases. Assuming 5% precision, the applied classification criterion led to inclusion of 70% positive cases in the final prediction. Since lipoaffinity index is a molecular descriptor computed using only 2D information about a chemical structure, its estimation is straightforward and computationally inexpensive. The inclusion of an additional criterion quantifying the cocrystallization probability leads to the following conjunction criterions H mix <-0.18 and ΔLA>3.61, allowing for identification of dissolution rate enhancers. The screening procedure was applied for finding the most promising coformers of such drugs as Iloperidone, Ritonavir, Carbamazepine and Enthenzamide. Copyright © 2017 Elsevier B.V. All rights reserved.

Formation of integrated structural units using the systematic and integrated method when implementing high-rise construction projects

NASA Astrophysics Data System (ADS)

Abramov, Ivan

2018-03-01

Development of design documentation for a future construction project gives rise to a number of issues with the main one being selection of manpower for structural units of the project's overall implementation system. Well planned and competently staffed integrated structural construction units will help achieve a high level of reliability and labor productivity and avoid negative (extraordinary) situations during the construction period eventually ensuring improved project performance. Research priorities include the development of theoretical recommendations for enhancing reliability of a structural unit staffed as an integrated construction crew. The author focuses on identification of destabilizing factors affecting formation of an integrated construction crew; assessment of these destabilizing factors; based on the developed mathematical model, highlighting the impact of these factors on the integration criterion with subsequent identification of an efficiency and reliability criterion for the structural unit in general. The purpose of this article is to develop theoretical recommendations and scientific and methodological provisions of an organizational and technological nature in order to identify a reliability criterion for a structural unit based on manpower integration and productivity criteria. With this purpose in mind, complex scientific tasks have been defined requiring special research, development of corresponding provisions and recommendations based on the system analysis findings presented herein.

Modeling cumulative dose and exposure duration provided insights regarding the associations between benzodiazepines and injuries.

PubMed

Abrahamowicz, Michal; Bartlett, Gillian; Tamblyn, Robyn; du Berger, Roxane

2006-04-01

Accurate assessment of medication impact requires modeling cumulative effects of exposure duration and dose; however, postmarketing studies usually represent medication exposure by baseline or current use only. We propose new methods for modeling various aspects of medication use history and employment of them to assess the adverse effects of selected benzodiazepines. Time-dependent measures of cumulative dose or duration of use, with weighting of past exposures by recency, were proposed. These measures were then included in alternative versions of the multivariable Cox model to analyze the risk of fall related injuries among the elderly new users of three benzodiazepines (nitrazepam, temazepam, and flurazepam) in Quebec. Akaike's information criterion (AIC) was used to select the most predictive model for a given benzodiazepine. The best-fitting model included a combination of cumulative duration and current dose for temazepam, and cumulative dose for flurazepam and nitrazepam, with different weighting functions. The window of clinically relevant exposure was shorter for flurazepam than for the two other products. Careful modeling of the medication exposure history may enhance our understanding of the mechanisms underlying their adverse effects.

Bivariate copula in fitting rainfall data

NASA Astrophysics Data System (ADS)

Yee, Kong Ching; Suhaila, Jamaludin; Yusof, Fadhilah; Mean, Foo Hui

2014-07-01

The usage of copula to determine the joint distribution between two variables is widely used in various areas. The joint distribution of rainfall characteristic obtained using the copula model is more ideal than the standard bivariate modelling where copula is belief to have overcome some limitation. Six copula models will be applied to obtain the most suitable bivariate distribution between two rain gauge stations. The copula models are Ali-Mikhail-Haq (AMH), Clayton, Frank, Galambos, Gumbel-Hoogaurd (GH) and Plackett. The rainfall data used in the study is selected from rain gauge stations which are located in the southern part of Peninsular Malaysia, during the period from 1980 to 2011. The goodness-of-fit test in this study is based on the Akaike information criterion (AIC).

Modelling of salad plants growth and physiological status in vitamin space greenhouse during lighting regime optimization

NASA Astrophysics Data System (ADS)

Konovalova, Irina; Berkovich, Yuliy A.; Smolyanina, Svetlana; Erokhin, Alexei; Yakovleva, Olga; Lapach, Sergij; Radchenko, Stanislav; Znamenskii, Artem; Tarakanov, Ivan

2016-07-01

The efficiency of the photoautotrophic element as part of bio-engineering life-support systems is determined substantially by lighting regime. The artificial light regime optimization complexity results from the wide range of plant physiological functions controlled by light: trophic, informative, biosynthetical, etc. An average photosynthetic photon flux density (PPFD), light spectral composition and pulsed light effects on the crop growth and plant physiological status were studied in the multivariate experiment, including 16 independent experiments in 3 replicates. Chinese cabbage plants (Brassica chinensis L.), cultivar Vesnianka, were grown during 24 days in a climatic chamber under white and red light-emitting diodes (LEDs): photoperiod 24 h, PPFD from 260 to 500 µM/(m ^{2}*s), red light share in the spectrum varying from 33% to 73%, pulsed (pulse period from 30 to 501 µs) and non-pulsed lighting. The regressions of plant photosynthetic and biochemical indexes as well as the crop specific productivity in response to the selected parameters of lighting regime were calculated. Developed models of crop net photosynthesis and dark respiration revealed the most intense gas exchange area corresponding to PPFD level 450 - 500 µM/(m ^{2}*s) with red light share in the spectrum about 60% and the pulse length 30 µs with a pulse period from 300 to 400 µs. Shoot dry weight increased monotonically in response to the increasing PPFD and changed depending on the pulse period under stabilized PPFD level. An increase in ascorbic acid content in the shoot biomass was revealed when increasing red light share in spectrum from 33% to 73%. The lighting regime optimization criterion (Q) was designed for the vitamin space greenhouse as the maximum of a crop yield square on its ascorbic acid concentration, divided by the light energy consumption. The regression model of optimization criterion was constructed based on the experimental data. The analysis of the model made it possible to determine the optimal lighting regime for the space greenhouse: PPFD level about 430 µ&M/(m ^{2}*s), red light share in the spectrum around 73%, non-pulsed lighting. At the same PPFD, Q-criterion value for the selected lighting regime was 1.5 times higher than under white LEDs, and slightly (about 15%) lower than under high-pressure sodium lamp light.

Analyses related to the development of DSM-5 criteria for substance use related disorders: 1. Toward amphetamine, cocaine and prescription drug use disorder continua using Item Response Theory.

PubMed

Saha, Tulshi D; Compton, Wilson M; Chou, S Patricia; Smith, Sharon; Ruan, W June; Huang, Boji; Pickering, Roger P; Grant, Bridget F

2012-04-01

Prior research has demonstrated the dimensionality of alcohol, nicotine and cannabis use disorders criteria. The purpose of this study was to examine the unidimensionality of DSM-IV cocaine, amphetamine and prescription drug abuse and dependence criteria and to determine the impact of elimination of the legal problems criterion on the information value of the aggregate criteria. Factor analyses and Item Response Theory (IRT) analyses were used to explore the unidimensionality and psychometric properties of the illicit drug use criteria using a large representative sample of the U.S. population. All illicit drug abuse and dependence criteria formed unidimensional latent traits. For amphetamines, cocaine, sedatives, tranquilizers and opioids, IRT models fit better for models without legal problems criterion than models with legal problems criterion and there were no differences in the information value of the IRT models with and without the legal problems criterion, supporting the elimination of that criterion. Consistent with findings for alcohol, nicotine and cannabis, amphetamine, cocaine, sedative, tranquilizer and opioid abuse and dependence criteria reflect underlying unitary dimensions of severity. The legal problems criterion associated with each of these substance use disorders can be eliminated with no loss in informational value and an advantage of parsimony. Taken together, these findings support the changes to substance use disorder diagnoses recommended by the American Psychiatric Association's DSM-5 Substance and Related Disorders Workgroup. Published by Elsevier Ireland Ltd.

Decision Criterion Dynamics in Animals Performing an Auditory Detection Task

PubMed Central

Mill, Robert W.; Alves-Pinto, Ana; Sumner, Christian J.

2014-01-01

Classical signal detection theory attributes bias in perceptual decisions to a threshold criterion, against which sensory excitation is compared. The optimal criterion setting depends on the signal level, which may vary over time, and about which the subject is naïve. Consequently, the subject must optimise its threshold by responding appropriately to feedback. Here a series of experiments was conducted, and a computational model applied, to determine how the decision bias of the ferret in an auditory signal detection task tracks changes in the stimulus level. The time scales of criterion dynamics were investigated by means of a yes-no signal-in-noise detection task, in which trials were grouped into blocks that alternately contained easy- and hard-to-detect signals. The responses of the ferrets implied both long- and short-term criterion dynamics. The animals exhibited a bias in favour of responding “yes” during blocks of harder trials, and vice versa. Moreover, the outcome of each single trial had a strong influence on the decision at the next trial. We demonstrate that the single-trial and block-level changes in bias are a manifestation of the same criterion update policy by fitting a model, in which the criterion is shifted by fixed amounts according to the outcome of the previous trial and decays strongly towards a resting value. The apparent block-level stabilisation of bias arises as the probabilities of outcomes and shifts on single trials mutually interact to establish equilibrium. To gain an intuition into how stable criterion distributions arise from specific parameter sets we develop a Markov model which accounts for the dynamic effects of criterion shifts. Our approach provides a framework for investigating the dynamics of decisions at different timescales in other species (e.g., humans) and in other psychological domains (e.g., vision, memory). PMID:25485733

Upper Gastrointestinal Hemorrhage: Development of the Severity Score.

PubMed

Chaikitamnuaychok, Rangson; Patumanond, Jayanton

2012-12-01

Emergency endoscopy for every patient with upper gastrointestinal hemorrhage is not possible in many medical centers. Simple guidelines to select patients for emergency endoscopy are lacking. The aim of the present report is to develop a simple scoring system to classify upper gastrointestinal hemorrhage (UGIH) severity based on patient clinical profiles at the emergency departments. Retrospective data of patients with UGIH in a university affiliated hospital were analyzed. Patients were criterion-classified into 3 severity levels: mild, moderate and severe. Clinical and laboratory information were compared among the 3 groups. Significant parameters were selected as indicators of severity. Coefficients of significant multivariable parameters were transformed into item scores, which added up as individual severity scores. The scores were used to classify patients into 3 urgency levels: non-urgent, urgent and emergent groups. Score-classification and criterion-classification were compared. Significant parameters in the model were age ≥ 60 years, pulse rate ≥ 100/min, systolic blood pressure < 100 mmHg, hemoglobin < 10 g/dL, blood urea nitrogen ≥ 35 mg/dL, presence of cirrhosis and hepatic failure. The score ranged from 0 to 27, and classifying patients into 3 urgency groups: non-urgent (score < 4, n = 215, 21.2%), urgent (score 4 - 16, n = 677, 66.9%) and emergent (score > 16, n = 121, 11.9%). The score correctly classified 81.4% of the patients into their original (criterion-classified) severity groups. Under-estimation (7.5%) and over-estimation (11.1%) were clinically acceptable. Our UGIH severity scoring system classified patients into 3 urgency groups: non-urgent, urgent and emergent, with clinically acceptable small number of under- and over-estimations. Its discriminative ability and precision should be validated before adopting into clinical practice.

Construction of edge cracks pre-criterion model based on hot rolling experiment and simulation of AZ31 magnesium alloy

NASA Astrophysics Data System (ADS)

Ning, Fangkun; Jia, Weitao; Hou, Jian; Chen, Xingrui; Le, Qichi

2018-05-01

Various fracture criteria, especially Johnson and Cook (J-C) model and (normalized) Cockcroft and Latham (C-L) criterion were contrasted and discussed. Based on normalized C-L criterion, adopted in this paper, FE simulation was carried out and hot rolling experiments under temperature range of 200 °C–350 °C, rolling reduction rate of 25%–40% and rolling speed from 7–21 r/min was implemented. The microstructure was observed by optical microscope and damage values of simulation results were contrasted with the length of cracks on diverse parameters. The results show that the plate generated less edge cracks and the microstructure emerged slight shear bands and fine dynamic recrystallization grains rolled at 350 °C, 40% reduction and 14 r/min. The edge cracks pre-criterion model was obtained combined with Zener-Hollomon equation and deformation activation energy.

Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion

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

He, Xu; Tuo, Rui; Jeff Wu, C. F.

Computer experiments based on mathematical models are powerful tools for understanding physical processes. This article addresses the problem of kriging-based optimization for deterministic computer experiments with tunable accuracy. Our approach is to use multi- delity computer experiments with increasing accuracy levels and a nonstationary Gaussian process model. We propose an optimization scheme that sequentially adds new computer runs by following two criteria. The first criterion, called EQI, scores candidate inputs with given level of accuracy, and the second criterion, called EQIE, scores candidate combinations of inputs and accuracy. Here, from simulation results and a real example using finite element analysis,more » our method out-performs the expected improvement (EI) criterion which works for single-accuracy experiments.« less

An Improvement of the Anisotropy and Formability Predictions of Aluminum Alloy Sheets

NASA Astrophysics Data System (ADS)

Banabic, D.; Comsa, D. S.; Jurco, P.; Wagner, S.; Vos, M.

2004-06-01

The paper presents an yield criterion for orthotropic sheet metals and its implementation in a theoretical model in order to calculate the Forming Limit Curves. The proposed yield criterion has been validated for two aluminum alloys: AA3103-0 and AA5182-0, respectively. The biaxial tensile test of cross specimens has been used for the determination of the experimental yield locus. The new yield criterion has been implemented in the Marciniak-Kuczynski model for the calculus of limit strains. The calculated Forming Limit Curves have been compared with the experimental ones, determined by frictionless test: bulge test, plane strain test and uniaxial tensile test. The predicted Forming Limit Curves using the new yield criterion are in good agreement with the experimental ones.

Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion

DOE PAGES

He, Xu; Tuo, Rui; Jeff Wu, C. F.

2017-01-31

Computer experiments based on mathematical models are powerful tools for understanding physical processes. This article addresses the problem of kriging-based optimization for deterministic computer experiments with tunable accuracy. Our approach is to use multi- delity computer experiments with increasing accuracy levels and a nonstationary Gaussian process model. We propose an optimization scheme that sequentially adds new computer runs by following two criteria. The first criterion, called EQI, scores candidate inputs with given level of accuracy, and the second criterion, called EQIE, scores candidate combinations of inputs and accuracy. Here, from simulation results and a real example using finite element analysis,more » our method out-performs the expected improvement (EI) criterion which works for single-accuracy experiments.« less

Bootstrap-after-bootstrap model averaging for reducing model uncertainty in model selection for air pollution mortality studies.

PubMed

Roberts, Steven; Martin, Michael A

2010-01-01

Concerns have been raised about findings of associations between particulate matter (PM) air pollution and mortality that have been based on a single "best" model arising from a model selection procedure, because such a strategy may ignore model uncertainty inherently involved in searching through a set of candidate models to find the best model. Model averaging has been proposed as a method of allowing for model uncertainty in this context. To propose an extension (double BOOT) to a previously described bootstrap model-averaging procedure (BOOT) for use in time series studies of the association between PM and mortality. We compared double BOOT and BOOT with Bayesian model averaging (BMA) and a standard method of model selection [standard Akaike's information criterion (AIC)]. Actual time series data from the United States are used to conduct a simulation study to compare and contrast the performance of double BOOT, BOOT, BMA, and standard AIC. Double BOOT produced estimates of the effect of PM on mortality that have had smaller root mean squared error than did those produced by BOOT, BMA, and standard AIC. This performance boost resulted from estimates produced by double BOOT having smaller variance than those produced by BOOT and BMA. Double BOOT is a viable alternative to BOOT and BMA for producing estimates of the mortality effect of PM.

Interactive Reliability Model for Whisker-toughened Ceramics

NASA Technical Reports Server (NTRS)

Palko, Joseph L.

1993-01-01

Wider use of ceramic matrix composites (CMC) will require the development of advanced structural analysis technologies. The use of an interactive model to predict the time-independent reliability of a component subjected to multiaxial loads is discussed. The deterministic, three-parameter Willam-Warnke failure criterion serves as the theoretical basis for the reliability model. The strength parameters defining the model are assumed to be random variables, thereby transforming the deterministic failure criterion into a probabilistic criterion. The ability of the model to account for multiaxial stress states with the same unified theory is an improvement over existing models. The new model was coupled with a public-domain finite element program through an integrated design program. This allows a design engineer to predict the probability of failure of a component. A simple structural problem is analyzed using the new model, and the results are compared to existing models.

Testing alternative ground water models using cross-validation and other methods

USGS Publications Warehouse

Foglia, L.; Mehl, S.W.; Hill, M.C.; Perona, P.; Burlando, P.

2007-01-01

Many methods can be used to test alternative ground water models. Of concern in this work are methods able to (1) rank alternative models (also called model discrimination) and (2) identify observations important to parameter estimates and predictions (equivalent to the purpose served by some types of sensitivity analysis). Some of the measures investigated are computationally efficient; others are computationally demanding. The latter are generally needed to account for model nonlinearity. The efficient model discrimination methods investigated include the information criteria: the corrected Akaike information criterion, Bayesian information criterion, and generalized cross-validation. The efficient sensitivity analysis measures used are dimensionless scaled sensitivity (DSS), composite scaled sensitivity, and parameter correlation coefficient (PCC); the other statistics are DFBETAS, Cook's D, and observation-prediction statistic. Acronyms are explained in the introduction. Cross-validation (CV) is a computationally intensive nonlinear method that is used for both model discrimination and sensitivity analysis. The methods are tested using up to five alternative parsimoniously constructed models of the ground water system of the Maggia Valley in southern Switzerland. The alternative models differ in their representation of hydraulic conductivity. A new method for graphically representing CV and sensitivity analysis results for complex models is presented and used to evaluate the utility of the efficient statistics. The results indicate that for model selection, the information criteria produce similar results at much smaller computational cost than CV. For identifying important observations, the only obviously inferior linear measure is DSS; the poor performance was expected because DSS does not include the effects of parameter correlation and PCC reveals large parameter correlations. ?? 2007 National Ground Water Association.

Refining Stimulus Parameters in Assessing Infant Speech Perception Using Visual Reinforcement Infant Speech Discrimination: Sensation Level.

PubMed

Uhler, Kristin M; Baca, Rosalinda; Dudas, Emily; Fredrickson, Tammy

2015-01-01

Speech perception measures have long been considered an integral piece of the audiological assessment battery. Currently, a prelinguistic, standardized measure of speech perception is missing in the clinical assessment battery for infants and young toddlers. Such a measure would allow systematic assessment of speech perception abilities of infants as well as the potential to investigate the impact early identification of hearing loss and early fitting of amplification have on the auditory pathways. To investigate the impact of sensation level (SL) on the ability of infants with normal hearing (NH) to discriminate /a-i/ and /ba-da/ and to determine if performance on the two contrasts are significantly different in predicting the discrimination criterion. The design was based on a survival analysis model for event occurrence and a repeated measures logistic model for binary outcomes. The outcome for survival analysis was the minimum SL for criterion and the outcome for the logistic regression model was the presence/absence of achieving the criterion. Criterion achievement was designated when an infant's proportion correct score was >0.75 on the discrimination performance task. Twenty-two infants with NH sensitivity participated in this study. There were 9 males and 13 females, aged 6-14 mo. Testing took place over two to three sessions. The first session consisted of a hearing test, threshold assessment of the two speech sounds (/a/ and /i/), and if time and attention allowed, visual reinforcement infant speech discrimination (VRISD). The second session consisted of VRISD assessment for the two test contrasts (/a-i/ and /ba-da/). The presentation level started at 50 dBA. If the infant was unable to successfully achieve criterion (>0.75) at 50 dBA, the presentation level was increased to 70 dBA followed by 60 dBA. Data examination included an event analysis, which provided the probability of criterion distribution across SL. The second stage of the analysis was a repeated measures logistic regression where SL and contrast were used to predict the likelihood of speech discrimination criterion. Infants were able to reach criterion for the /a-i/ contrast at statistically lower SLs when compared to /ba-da/. There were six infants who never reached criterion for /ba-da/ and one never reached criterion for /a-i/. The conditional probability of not reaching criterion by 70 dB SL was 0% for /a-i/ and 21% for /ba-da/. The predictive logistic regression model showed that children were more likely to discriminate the /a-i/ even when controlling for SL. Nearly all normal-hearing infants can demonstrate discrimination criterion of a vowel contrast at 60 dB SL, while a level of ≥70 dB SL may be needed to allow all infants to demonstrate discrimination criterion of a difficult consonant contrast. American Academy of Audiology.

Method Development for Clinical Comprehensive Evaluation of Pediatric Drugs Based on Multi-Criteria Decision Analysis: Application to Inhaled Corticosteroids for Children with Asthma.

PubMed

Yu, Yuncui; Jia, Lulu; Meng, Yao; Hu, Lihua; Liu, Yiwei; Nie, Xiaolu; Zhang, Meng; Zhang, Xuan; Han, Sheng; Peng, Xiaoxia; Wang, Xiaoling

2018-04-01

Establishing a comprehensive clinical evaluation system is critical in enacting national drug policy and promoting rational drug use. In China, the 'Clinical Comprehensive Evaluation System for Pediatric Drugs' (CCES-P) project, which aims to compare drugs based on clinical efficacy and cost effectiveness to help decision makers, was recently proposed; therefore, a systematic and objective method is required to guide the process. An evidence-based multi-criteria decision analysis model that involved an analytic hierarchy process (AHP) was developed, consisting of nine steps: (1) select the drugs to be reviewed; (2) establish the evaluation criterion system; (3) determine the criterion weight based on the AHP; (4) construct the evidence body for each drug under evaluation; (5) select comparative measures and calculate the original utility score; (6) place a common utility scale and calculate the standardized utility score; (7) calculate the comprehensive utility score; (8) rank the drugs; and (9) perform a sensitivity analysis. The model was applied to the evaluation of three different inhaled corticosteroids (ICSs) used for asthma management in children (a total of 16 drugs with different dosage forms and strengths or different manufacturers). By applying the drug analysis model, the 16 ICSs under review were successfully scored and evaluated. Budesonide suspension for inhalation (drug ID number: 7) ranked the highest, with comprehensive utility score of 80.23, followed by fluticasone propionate inhaled aerosol (drug ID number: 16), with a score of 79.59, and budesonide inhalation powder (drug ID number: 6), with a score of 78.98. In the sensitivity analysis, the ranking of the top five and lowest five drugs remains unchanged, suggesting this model is generally robust. An evidence-based drug evaluation model based on AHP was successfully developed. The model incorporates sufficient utility and flexibility for aiding the decision-making process, and can be a useful tool for the CCES-P.

Bayesian image reconstruction - The pixon and optimal image modeling

NASA Technical Reports Server (NTRS)

Pina, R. K.; Puetter, R. C.

1993-01-01

In this paper we describe the optimal image model, maximum residual likelihood method (OptMRL) for image reconstruction. OptMRL is a Bayesian image reconstruction technique for removing point-spread function blurring. OptMRL uses both a goodness-of-fit criterion (GOF) and an 'image prior', i.e., a function which quantifies the a priori probability of the image. Unlike standard maximum entropy methods, which typically reconstruct the image on the data pixel grid, OptMRL varies the image model in order to find the optimal functional basis with which to represent the image. We show how an optimal basis for image representation can be selected and in doing so, develop the concept of the 'pixon' which is a generalized image cell from which this basis is constructed. By allowing both the image and the image representation to be variable, the OptMRL method greatly increases the volume of solution space over which the image is optimized. Hence the likelihood of the final reconstructed image is greatly increased. For the goodness-of-fit criterion, OptMRL uses the maximum residual likelihood probability distribution introduced previously by Pina and Puetter (1992). This GOF probability distribution, which is based on the spatial autocorrelation of the residuals, has the advantage that it ensures spatially uncorrelated image reconstruction residuals.

Earing Prediction in Cup Drawing using the BBC2008 Yield Criterion

NASA Astrophysics Data System (ADS)

Vrh, Marko; Halilovič, Miroslav; Starman, Bojan; Štok, Boris; Comsa, Dan-Sorin; Banabic, Dorel

2011-08-01

The paper deals with constitutive modelling of highly anisotropic sheet metals. It presents FEM based earing predictions in cup drawing simulation of highly anisotropic aluminium alloys where more than four ears occur. For that purpose the BBC2008 yield criterion, which is a plane-stress yield criterion formulated in the form of a finite series, is used. Thus defined criterion can be expanded to retain more or less terms, depending on the amount of given experimental data. In order to use the model in sheet metal forming simulations we have implemented it in a general purpose finite element code ABAQUS/Explicit via VUMAT subroutine, considering alternatively eight or sixteen parameters (8p and 16p version). For the integration of the constitutive model the explicit NICE (Next Increment Corrects Error) integration scheme has been used. Due to the scheme effectiveness the CPU time consumption for a simulation is comparable to the time consumption of built-in constitutive models. Two aluminium alloys, namely AA5042-H2 and AA2090-T3, have been used for a validation of the model. For both alloys the parameters of the BBC2008 model have been identified with a developed numerical procedure, based on a minimization of the developed cost function. For both materials, the predictions of the BBC2008 model prove to be in very good agreement with the experimental results. The flexibility and the accuracy of the model together with the identification and integration procedure guarantee the applicability of the BBC2008 yield criterion in industrial applications.

An Evaluation of Available Models for Estimating the Reliability and Validity of Criterion Referenced Measures.

ERIC Educational Resources Information Center

Oakland, Thomas

New strategies for evaluation criterion referenced measures (CRM) are discussed. These strategies examine the following issues: (1) the use of normed referenced measures (NRM) as CRM and then estimating the reliability and validity of such measures in terms of variance from an arbitrarily specified criterion score, (2) estimation of the…

76 FR 21985 - Notice of Final Priorities, Requirements, Definitions, and Selection Criteria

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-19

... only after a research base has been established to support the use of the assessments for such purposes..., research-based assessment practices. Discussion: We agree that the selection criteria should address the... selection criterion, which addresses methods of scoring, to allow for self-scoring of student performance on...

Orbit IMU alinement interpretation of onboard display data

NASA Technical Reports Server (NTRS)

Corson, R.

1978-01-01

The space shuttle inertial measurement unit (IMU) alinement algorith was examined to determine the most important alinement starpair selection criterion. Three crew displayed parameters were considered: (1) the results of the separation angle difference (SAD) check for each starpair; (2) the separation angle of each starpair; and (3) the age of each star measurement. It was determined that the SAD for each pair cannot be used to predict the IMu alinement accuracy. If the age of each star measurement is less than approximately 30 minutes, time is a relatively unimportant factor and the most important alinement pair selection criterion is the starpair separation angle. Therefore, when there are three available alinement starpairs and all measurements were taken within the last 30 minutes, the pair with the separation angle closest to 90 degrees should be selected for IMU alinement.

Using histograms to introduce randomization in the generation of ensembles of decision trees

DOEpatents

Kamath, Chandrika; Cantu-Paz, Erick; Littau, David

2005-02-22

A system for decision tree ensembles that includes a module to read the data, a module to create a histogram, a module to evaluate a potential split according to some criterion using the histogram, a module to select a split point randomly in an interval around the best split, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method includes the steps of reading the data; creating a histogram; evaluating a potential split according to some criterion using the histogram, selecting a split point randomly in an interval around the best split, splitting the data, and combining multiple decision trees in ensembles.

Adaptive Resource Utilization Prediction System for Infrastructure as a Service Cloud.

PubMed

Zia Ullah, Qazi; Hassan, Shahzad; Khan, Gul Muhammad

2017-01-01

Infrastructure as a Service (IaaS) cloud provides resources as a service from a pool of compute, network, and storage resources. Cloud providers can manage their resource usage by knowing future usage demand from the current and past usage patterns of resources. Resource usage prediction is of great importance for dynamic scaling of cloud resources to achieve efficiency in terms of cost and energy consumption while keeping quality of service. The purpose of this paper is to present a real-time resource usage prediction system. The system takes real-time utilization of resources and feeds utilization values into several buffers based on the type of resources and time span size. Buffers are read by R language based statistical system. These buffers' data are checked to determine whether their data follows Gaussian distribution or not. In case of following Gaussian distribution, Autoregressive Integrated Moving Average (ARIMA) is applied; otherwise Autoregressive Neural Network (AR-NN) is applied. In ARIMA process, a model is selected based on minimum Akaike Information Criterion (AIC) values. Similarly, in AR-NN process, a network with the lowest Network Information Criterion (NIC) value is selected. We have evaluated our system with real traces of CPU utilization of an IaaS cloud of one hundred and twenty servers.

Adaptive Resource Utilization Prediction System for Infrastructure as a Service Cloud

PubMed Central

Hassan, Shahzad; Khan, Gul Muhammad

2017-01-01

Infrastructure as a Service (IaaS) cloud provides resources as a service from a pool of compute, network, and storage resources. Cloud providers can manage their resource usage by knowing future usage demand from the current and past usage patterns of resources. Resource usage prediction is of great importance for dynamic scaling of cloud resources to achieve efficiency in terms of cost and energy consumption while keeping quality of service. The purpose of this paper is to present a real-time resource usage prediction system. The system takes real-time utilization of resources and feeds utilization values into several buffers based on the type of resources and time span size. Buffers are read by R language based statistical system. These buffers' data are checked to determine whether their data follows Gaussian distribution or not. In case of following Gaussian distribution, Autoregressive Integrated Moving Average (ARIMA) is applied; otherwise Autoregressive Neural Network (AR-NN) is applied. In ARIMA process, a model is selected based on minimum Akaike Information Criterion (AIC) values. Similarly, in AR-NN process, a network with the lowest Network Information Criterion (NIC) value is selected. We have evaluated our system with real traces of CPU utilization of an IaaS cloud of one hundred and twenty servers. PMID:28811819

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities.

PubMed

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities

NASA Astrophysics Data System (ADS)

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

Characterizing the functional MRI response using Tikhonov regularization.

PubMed

Vakorin, Vasily A; Borowsky, Ron; Sarty, Gordon E

2007-09-20

The problem of evaluating an averaged functional magnetic resonance imaging (fMRI) response for repeated block design experiments was considered within a semiparametric regression model with autocorrelated residuals. We applied functional data analysis (FDA) techniques that use a least-squares fitting of B-spline expansions with Tikhonov regularization. To deal with the noise autocorrelation, we proposed a regularization parameter selection method based on the idea of combining temporal smoothing with residual whitening. A criterion based on a generalized chi(2)-test of the residuals for white noise was compared with a generalized cross-validation scheme. We evaluated and compared the performance of the two criteria, based on their effect on the quality of the fMRI response. We found that the regularization parameter can be tuned to improve the noise autocorrelation structure, but the whitening criterion provides too much smoothing when compared with the cross-validation criterion. The ultimate goal of the proposed smoothing techniques is to facilitate the extraction of temporal features in the hemodynamic response for further analysis. In particular, these FDA methods allow us to compute derivatives and integrals of the fMRI signal so that fMRI data may be correlated with behavioral and physiological models. For example, positive and negative hemodynamic responses may be easily and robustly identified on the basis of the first derivative at an early time point in the response. Ultimately, these methods allow us to verify previously reported correlations between the hemodynamic response and the behavioral measures of accuracy and reaction time, showing the potential to recover new information from fMRI data. 2007 John Wiley & Sons, Ltd

Evaluation of Validity and Reliability for Hierarchical Scales Using Latent Variable Modeling

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2012-01-01

A latent variable modeling method is outlined, which accomplishes estimation of criterion validity and reliability for a multicomponent measuring instrument with hierarchical structure. The approach provides point and interval estimates for the scale criterion validity and reliability coefficients, and can also be used for testing composite or…

Prediction of Burst Pressure in Multistage Tube Hydroforming of Aerospace Alloys.

PubMed

Saboori, M; Gholipour, J; Champliaud, H; Wanjara, P; Gakwaya, A; Savoie, J

2016-08-01

Bursting, an irreversible failure in tube hydroforming (THF), results mainly from the local plastic instabilities that occur when the biaxial stresses imparted during the process exceed the forming limit strains of the material. To predict the burst pressure, Oyan's and Brozzo's decoupled ductile fracture criteria (DFC) were implemented as user material models in a dynamic nonlinear commercial 3D finite-element (FE) software, ls-dyna. THF of a round to V-shape was selected as a generic representative of an aerospace component for the FE simulations and experimental trials. To validate the simulation results, THF experiments up to bursting were carried out using Inconel 718 (IN 718) tubes with a thickness of 0.9 mm to measure the internal pressures during the process. When comparing the experimental and simulation results, the burst pressure predicated based on Oyane's decoupled damage criterion was found to agree better with the measured data for IN 718 than Brozzo's fracture criterion.

Continuous-time mean-variance portfolio selection with value-at-risk and no-shorting constraints

NASA Astrophysics Data System (ADS)

Yan, Wei

2012-01-01

An investment problem is considered with dynamic mean-variance(M-V) portfolio criterion under discontinuous prices which follow jump-diffusion processes according to the actual prices of stocks and the normality and stability of the financial market. The short-selling of stocks is prohibited in this mathematical model. Then, the corresponding stochastic Hamilton-Jacobi-Bellman(HJB) equation of the problem is presented and the solution of the stochastic HJB equation based on the theory of stochastic LQ control and viscosity solution is obtained. The efficient frontier and optimal strategies of the original dynamic M-V portfolio selection problem are also provided. And then, the effects on efficient frontier under the value-at-risk constraint are illustrated. Finally, an example illustrating the discontinuous prices based on M-V portfolio selection is presented.

Decision analysis applied to the purchase of frozen premixed intravenous admixtures.

PubMed

Witte, K W; Eck, T A; Vogel, D P

1985-04-01

A structured decision-analysis model was used to evaluate frozen premixed cefazolin admixtures. Decision analysis is a process of stating the desired outcome, establishing and weighting evaluation criteria, identifying options for reaching the outcome, evaluating and numerically ranking each option for each criterion, multiplying the ranking by the weight for each criterion, and calculating total points for each option. It was used to compare objectively frozen premixed cefazolin admixtures with batch reconstitution from vials and reconstitution of lyophilized, ready-to-mix containers. In this institution the model numerically demonstrated a distinct preference for the premixed frozen admixture over these other alternatives. A comparison of these results with the total cost impact of each option resulted in a decision to purchase the frozen premixed solution. The advantages of the frozen premixed solution that contributed most to this decision were decreased waste and personnel time. The latter was especially important since it allowed for the reallocation of personnel resources to other potentially cost-reducing clinical functions. Decision analysis proved to be an effective tool for formalizing the process of selecting among various alternatives to reach a desired outcome in this hospital pharmacy.

Assessing the factor structure of posttraumatic stress disorder symptoms in war-exposed youths with and without Criterion A2 endorsement.

PubMed

Armour, Cherie; Layne, Christopher M; Naifeh, James A; Shevlin, Mark; Duraković-Belko, Elvira; Djapo, Nermin; Pynoos, Robert S; Elhai, Jon D

2011-01-01

Posttraumatic stress disorder's (PTSD) tripartite factor structure proposed by the DSM-IV is rarely empirically supported. Other four-factor models (King et al., 1998; Simms et al., 2002) have proven to better account for PTSD's latent structure; however, results regarding model superiority are conflicting. The current study assessed whether endorsement of PTSD's Criterion A2 would impact on the factorial invariance of the King et al. (1998) model. Participants were 1572 war-exposed Bosnian secondary students who were assessed two years following the 1992-1995 Bosnian conflict. The sample was grouped by those endorsing both parts of the DSM-IV Criterion A (A2 Group) and those endorsing only A1 (Non-A2 Group). The factorial invariance of the King et al. (1998) model was not supported between the A2 vs. Non-A2 Groups; rather, the groups significantly differed on all model parameters. The impact of removing A2 on the factor structure of King et al. (1998) PTSD model is discussed in light of the proposed removal of Criterion A2 for the DSM-V. Copyright © 2010 Elsevier Ltd. All rights reserved.

Analysing the accuracy of machine learning techniques to develop an integrated influent time series model: case study of a sewage treatment plant, Malaysia.

PubMed

Ansari, Mozafar; Othman, Faridah; Abunama, Taher; El-Shafie, Ahmed

2018-04-01

The function of a sewage treatment plant is to treat the sewage to acceptable standards before being discharged into the receiving waters. To design and operate such plants, it is necessary to measure and predict the influent flow rate. In this research, the influent flow rate of a sewage treatment plant (STP) was modelled and predicted by autoregressive integrated moving average (ARIMA), nonlinear autoregressive network (NAR) and support vector machine (SVM) regression time series algorithms. To evaluate the models' accuracy, the root mean square error (RMSE) and coefficient of determination (R 2 ) were calculated as initial assessment measures, while relative error (RE), peak flow criterion (PFC) and low flow criterion (LFC) were calculated as final evaluation measures to demonstrate the detailed accuracy of the selected models. An integrated model was developed based on the individual models' prediction ability for low, average and peak flow. An initial assessment of the results showed that the ARIMA model was the least accurate and the NAR model was the most accurate. The RE results also prove that the SVM model's frequency of errors above 10% or below - 10% was greater than the NAR model's. The influent was also forecasted up to 44 weeks ahead by both models. The graphical results indicate that the NAR model made better predictions than the SVM model. The final evaluation of NAR and SVM demonstrated that SVM made better predictions at peak flow and NAR fit well for low and average inflow ranges. The integrated model developed includes the NAR model for low and average influent and the SVM model for peak inflow.

Process dominance analysis for fate modeling of flubendazole and fenbendazole in liquid manure and manured soil.

PubMed

Moenickes, Sylvia; Höltge, Sibylla; Kreuzig, Robert; Richter, Otto

2011-12-01

Fate monitoring data on anaerobic transformation of the benzimidazole anthelmintics flubendazole (FLU) and fenbendazole (FEN) in liquid pig manure and aerobic transformation and sorption in soil and manured soil under laboratory conditions were used for corresponding fate modeling. Processes considered were reversible and irreversible sequestration, mineralization, and metabolization, from which a set of up to 50 different models, both nested and concurrent, was assembled. Five selection criteria served for model selection after parameter fitting: the coefficient of determination, modeling efficiency, a likelihood ratio test, an information criterion, and a determinability measure. From the set of models selected, processes were classified as essential or sufficient. This strategy to identify process dominance was corroborated through application to data from analogous experiments for sulfadiazine and a comparison with established fate models for this substance. For both, FLU and FEN, model selection performance was fine, including indication of weak data support where observed. For FLU reversible and irreversible sequestration in a nonextractable fraction was determined. In particular, both the extractable and the nonextractable fraction were equally sufficient sources for irreversible sequestration. For FEN generally reversible formation of the extractable sulfoxide metabolite and reversible sequestration of both the parent and the metabolite were dominant. Similar to FLU, irreversible sequestration in the nonextractable fraction was determined for which both the extractable or the nonextractable fraction were equally sufficient sources. Formation of the sulfone metabolite was determined as irreversible, originating from the first metabolite. Copyright © 2011 Elsevier B.V. All rights reserved.

Improved Multi-Axial, Temperature and Time Dependent (MATT) Failure Model

NASA Technical Reports Server (NTRS)

Richardson, D. E.; Anderson, G. L.; Macon, D. J.

2002-01-01

An extensive effort has recently been completed by the Space Shuttle's Reusable Solid Rocket Motor (RSRM) nozzle program to completely characterize the effects of multi-axial loading, temperature and time on the failure characteristics of three filled epoxy adhesives (TIGA 321, EA913NA, EA946). As part of this effort, a single general failure criterion was developed that accounted for these effects simultaneously. This model was named the Multi- Axial, Temperature, and Time Dependent or MATT failure criterion. Due to the intricate nature of the failure criterion, some parameters were required to be calculated using complex equations or numerical methods. This paper documents some simple but accurate modifications to the failure criterion to allow for calculations of failure conditions without complex equations or numerical techniques.

A generic bio-economic farm model for environmental and economic assessment of agricultural systems.

PubMed

Janssen, Sander; Louhichi, Kamel; Kanellopoulos, Argyris; Zander, Peter; Flichman, Guillermo; Hengsdijk, Huib; Meuter, Eelco; Andersen, Erling; Belhouchette, Hatem; Blanco, Maria; Borkowski, Nina; Heckelei, Thomas; Hecker, Martin; Li, Hongtao; Oude Lansink, Alfons; Stokstad, Grete; Thorne, Peter; van Keulen, Herman; van Ittersum, Martin K

2010-12-01

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models.

A Generic Bio-Economic Farm Model for Environmental and Economic Assessment of Agricultural Systems

PubMed Central

Louhichi, Kamel; Kanellopoulos, Argyris; Zander, Peter; Flichman, Guillermo; Hengsdijk, Huib; Meuter, Eelco; Andersen, Erling; Belhouchette, Hatem; Blanco, Maria; Borkowski, Nina; Heckelei, Thomas; Hecker, Martin; Li, Hongtao; Oude Lansink, Alfons; Stokstad, Grete; Thorne, Peter; van Keulen, Herman; van Ittersum, Martin K.

2010-01-01

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models. PMID:21113782

Downscaling reanalysis data to high-resolution variables above a glacier surface (Cordillera Blanca, Peru)

NASA Astrophysics Data System (ADS)

Hofer, Marlis; Mölg, Thomas; Marzeion, Ben; Kaser, Georg

2010-05-01

Recently initiated observation networks in the Cordillera Blanca provide temporally high-resolution, yet short-term atmospheric data. The aim of this study is to extend the existing time series into the past. We present an empirical-statistical downscaling (ESD) model that links 6-hourly NCEP/NCAR reanalysis data to the local target variables, measured at the tropical glacier Artesonraju (Northern Cordillera Blanca). The approach is particular in the context of ESD for two reasons. First, the observational time series for model calibration are short (only about two years). Second, unlike most ESD studies in climate research, we focus on variables at a high temporal resolution (i.e., six-hourly values). Our target variables are two important drivers in the surface energy balance of tropical glaciers; air temperature and specific humidity. The selection of predictor fields from the reanalysis data is based on regression analyses and climatologic considerations. The ESD modelling procedure includes combined empirical orthogonal function and multiple regression analyses. Principal component screening is based on cross-validation using the Akaike Information Criterion as model selection criterion. Double cross-validation is applied for model evaluation. Potential autocorrelation in the time series is considered by defining the block length in the resampling procedure. Apart from the selection of predictor fields, the modelling procedure is automated and does not include subjective choices. We assess the ESD model sensitivity to the predictor choice by using both single- and mixed-field predictors of the variables air temperature (1000 hPa), specific humidity (1000 hPa), and zonal wind speed (500 hPa). The chosen downscaling domain ranges from 80 to 50 degrees west and from 0 to 20 degrees south. Statistical transfer functions are derived individually for different months and times of day (month/hour-models). The forecast skill of the month/hour-models largely depends on month and time of day, ranging from 0 to 0.8, but the mixed-field predictors generally perform better than the single-field predictors. At all time scales, the ESD model shows added value against two simple reference models; (i) the direct use of reanalysis grid point values, and (ii) mean diurnal and seasonal cycles over the calibration period. The ESD model forecast 1960 to 2008 clearly reflects interannual variability related to the El Niño/Southern Oscillation, but is sensitive to the chosen predictor type. So far, we have not assessed the performance of NCEP/NCAR reanalysis data against other reanalysis products. The developed ESD model is computationally cheap and applicable wherever measurements are available for model calibration.

Dynamic Portfolio Strategy Using Clustering Approach

PubMed Central

Lu, Ya-Nan; Li, Sai-Ping; Jiang, Xiong-Fei; Zhong, Li-Xin; Qiu, Tian

2017-01-01

The problem of portfolio optimization is one of the most important issues in asset management. We here propose a new dynamic portfolio strategy based on the time-varying structures of MST networks in Chinese stock markets, where the market condition is further considered when using the optimal portfolios for investment. A portfolio strategy comprises two stages: First, select the portfolios by choosing central and peripheral stocks in the selection horizon using five topological parameters, namely degree, betweenness centrality, distance on degree criterion, distance on correlation criterion and distance on distance criterion. Second, use the portfolios for investment in the investment horizon. The optimal portfolio is chosen by comparing central and peripheral portfolios under different combinations of market conditions in the selection and investment horizons. Market conditions in our paper are identified by the ratios of the number of trading days with rising index to the total number of trading days, or the sum of the amplitudes of the trading days with rising index to the sum of the amplitudes of the total trading days. We find that central portfolios outperform peripheral portfolios when the market is under a drawup condition, or when the market is stable or drawup in the selection horizon and is under a stable condition in the investment horizon. We also find that peripheral portfolios gain more than central portfolios when the market is stable in the selection horizon and is drawdown in the investment horizon. Empirical tests are carried out based on the optimal portfolio strategy. Among all possible optimal portfolio strategies based on different parameters to select portfolios and different criteria to identify market conditions, 65% of our optimal portfolio strategies outperform the random strategy for the Shanghai A-Share market while the proportion is 70% for the Shenzhen A-Share market. PMID:28129333

Dynamic Portfolio Strategy Using Clustering Approach.

PubMed

Ren, Fei; Lu, Ya-Nan; Li, Sai-Ping; Jiang, Xiong-Fei; Zhong, Li-Xin; Qiu, Tian

2017-01-01

The problem of portfolio optimization is one of the most important issues in asset management. We here propose a new dynamic portfolio strategy based on the time-varying structures of MST networks in Chinese stock markets, where the market condition is further considered when using the optimal portfolios for investment. A portfolio strategy comprises two stages: First, select the portfolios by choosing central and peripheral stocks in the selection horizon using five topological parameters, namely degree, betweenness centrality, distance on degree criterion, distance on correlation criterion and distance on distance criterion. Second, use the portfolios for investment in the investment horizon. The optimal portfolio is chosen by comparing central and peripheral portfolios under different combinations of market conditions in the selection and investment horizons. Market conditions in our paper are identified by the ratios of the number of trading days with rising index to the total number of trading days, or the sum of the amplitudes of the trading days with rising index to the sum of the amplitudes of the total trading days. We find that central portfolios outperform peripheral portfolios when the market is under a drawup condition, or when the market is stable or drawup in the selection horizon and is under a stable condition in the investment horizon. We also find that peripheral portfolios gain more than central portfolios when the market is stable in the selection horizon and is drawdown in the investment horizon. Empirical tests are carried out based on the optimal portfolio strategy. Among all possible optimal portfolio strategies based on different parameters to select portfolios and different criteria to identify market conditions, 65% of our optimal portfolio strategies outperform the random strategy for the Shanghai A-Share market while the proportion is 70% for the Shenzhen A-Share market.

Model selection on solid ground: Rigorous comparison of nine ways to evaluate Bayesian model evidence

PubMed Central

Schöniger, Anneli; Wöhling, Thomas; Samaniego, Luis; Nowak, Wolfgang

2014-01-01

Bayesian model selection or averaging objectively ranks a number of plausible, competing conceptual models based on Bayes' theorem. It implicitly performs an optimal trade-off between performance in fitting available data and minimum model complexity. The procedure requires determining Bayesian model evidence (BME), which is the likelihood of the observed data integrated over each model's parameter space. The computation of this integral is highly challenging because it is as high-dimensional as the number of model parameters. Three classes of techniques to compute BME are available, each with its own challenges and limitations: (1) Exact and fast analytical solutions are limited by strong assumptions. (2) Numerical evaluation quickly becomes unfeasible for expensive models. (3) Approximations known as information criteria (ICs) such as the AIC, BIC, or KIC (Akaike, Bayesian, or Kashyap information criterion, respectively) yield contradicting results with regard to model ranking. Our study features a theory-based intercomparison of these techniques. We further assess their accuracy in a simplistic synthetic example where for some scenarios an exact analytical solution exists. In more challenging scenarios, we use a brute-force Monte Carlo integration method as reference. We continue this analysis with a real-world application of hydrological model selection. This is a first-time benchmarking of the various methods for BME evaluation against true solutions. Results show that BME values from ICs are often heavily biased and that the choice of approximation method substantially influences the accuracy of model ranking. For reliable model selection, bias-free numerical methods should be preferred over ICs whenever computationally feasible. PMID:25745272

A new tracer‐density criterion for heterogeneous porous media

USGS Publications Warehouse

Barth, Gilbert R.; Illangasekare, Tissa H.; Hill, Mary C.; Rajaram, Harihar

2001-01-01

Tracer experiments provide information about aquifer material properties vital for accurate site characterization. Unfortunately, density‐induced sinking can distort tracer movement, leading to an inaccurate assessment of material properties. Yet existing criteria for selecting appropriate tracer concentrations are based on analysis of homogeneous media instead of media with heterogeneities typical of field sites. This work introduces a hydraulic‐gradient correction for heterogeneous media and applies it to a criterion previously used to indicate density‐induced instabilities in homogeneous media. The modified criterion was tested using a series of two‐dimensional heterogeneous intermediate‐scale tracer experiments and data from several detailed field tracer tests. The intermediate‐scale experimental facility (10.0×1.2×0.06 m) included both homogeneous and heterogeneous (σln k2 = 1.22) zones. The field tracer tests were less heterogeneous (0.24 < σln k2 < 0.37), but measurements were sufficient to detect density‐induced sinking. Evaluation of the modified criterion using the experiments and field tests demonstrates that the new criterion appears to account for the change in density‐induced sinking due to heterogeneity. The criterion demonstrates the importance of accounting for heterogeneity to predict density‐induced sinking and differences in the onset of density‐induced sinking in two‐ and three‐dimensional systems.

A study on the use and modeling of geographical information system for combating forest crimes: an assessment of crimes in the eastern Mediterranean forests.

PubMed

Pak, Mehmet; Gülci, Sercan; Okumuş, Arif

2018-01-06

This study focuses on the geo-statistical assessment of spatial estimation models in forest crimes. Used widely in the assessment of crime and crime-dependent variables, geographic information system (GIS) helps the detection of forest crimes in rural regions. In this study, forest crimes (forest encroachment, illegal use, illegal timber logging, etc.) are assessed holistically and modeling was performed with ten different independent variables in GIS environment. The research areas are three Forest Enterprise Chiefs (Baskonus, Cinarpinar, and Hartlap) affiliated to Kahramanmaras Forest Regional Directorate in Kahramanmaras. An estimation model was designed using ordinary least squares (OLS) and geographically weighted regression (GWR) methods, which are often used in spatial association. Three different models were proposed in order to increase the accuracy of the estimation model. The use of variables with a variance inflation factor (VIF) value of lower than 7.5 in Model I and lower than 4 in Model II and dependent variables with significant robust probability values in Model III are associated with forest crimes. Afterwards, the model with the lowest corrected Akaike Information Criterion (AIC c ), and the highest R 2 value was selected as the comparison criterion. Consequently, Model III proved to be more accurate compared to other models. For Model III, while AIC c was 328,491 and R 2 was 0.634 for OLS-3 model, AIC c was 318,489 and R 2 was 0.741 for GWR-3 model. In this respect, the uses of GIS for combating forest crimes provide different scenarios and tangible information that will help take political and strategic measures.

AIC and the challenge of complexity: A case study from ecology.

PubMed

Moll, Remington J; Steel, Daniel; Montgomery, Robert A

2016-12-01

Philosophers and scientists alike have suggested Akaike's Information Criterion (AIC), and other similar model selection methods, show predictive accuracy justifies a preference for simplicity in model selection. This epistemic justification of simplicity is limited by an assumption of AIC which requires that the same probability distribution must generate the data used to fit the model and the data about which predictions are made. This limitation has been previously noted but appears to often go unnoticed by philosophers and scientists and has not been analyzed in relation to complexity. If predictions are about future observations, we argue that this assumption is unlikely to hold for models of complex phenomena. That in turn creates a practical limitation for simplicity's AIC-based justification because scientists modeling such phenomena are often interested in predicting the future. We support our argument with an ecological case study concerning the reintroduction of wolves into Yellowstone National Park, U.S.A. We suggest that AIC might still lend epistemic support for simplicity by leading to better explanations of complex phenomena. Copyright © 2016 Elsevier Ltd. All rights reserved.

Assessment of NDE reliability data

NASA Technical Reports Server (NTRS)

Yee, B. G. W.; Couchman, J. C.; Chang, F. H.; Packman, D. F.

1975-01-01

Twenty sets of relevant nondestructive test (NDT) reliability data were identified, collected, compiled, and categorized. A criterion for the selection of data for statistical analysis considerations was formulated, and a model to grade the quality and validity of the data sets was developed. Data input formats, which record the pertinent parameters of the defect/specimen and inspection procedures, were formulated for each NDE method. A comprehensive computer program was written and debugged to calculate the probability of flaw detection at several confidence limits by the binomial distribution. This program also selects the desired data sets for pooling and tests the statistical pooling criteria before calculating the composite detection reliability. An example of the calculated reliability of crack detection in bolt holes by an automatic eddy current method is presented.

A neural network model of foraging decisions made under predation risk.

PubMed

Coleman, Scott L; Brown, Vincent R; Levine, Daniel S; Mellgren, Roger L

2005-12-01

This article develops the cognitive-emotional forager (CEF) model, a novel application of a neural network to dynamical processes in foraging behavior. The CEF is based on a neural network known as the gated dipole, introduced by Grossberg, which is capable of representing short-term affective reactions in a manner similar to Solomon and Corbit's (1974) opponent process theory. The model incorporates a trade-off between approach toward food and avoidance of predation under varying levels of motivation induced by hunger. The results of simulations in a simple patch selection paradigm, using a lifetime fitness criterion for comparison, indicate that the CEF model is capable of nearly optimal foraging and outperforms a run-of-luck rule-of-thumb model. Models such as the one presented here can illuminate the underlying cognitive and motivational components of animal decision making.

Trait-specific long-term consequences of genomic selection in beef cattle.

PubMed

de Rezende Neves, Haroldo Henrique; Carvalheiro, Roberto; de Queiroz, Sandra Aidar

2018-02-01

Simulation studies allow addressing consequences of selection schemes, helping to identify effective strategies to enable genetic gain and maintain genetic diversity. The aim of this study was to evaluate the long-term impact of genomic selection (GS) in genetic progress and genetic diversity of beef cattle. Forward-in-time simulation generated a population with pattern of linkage disequilibrium close to that previously reported for real beef cattle populations. Different scenarios of GS and traditional pedigree-based BLUP (PBLUP) selection were simulated for 15 generations, mimicking selection for female reproduction and meat quality. For GS scenarios, an alternative selection criterion was simulated (wGBLUP), intended to enhance long-term gains by attributing more weight to favorable alleles with low frequency. GS allowed genetic progress up to 40% greater than PBLUP, for female reproduction and meat quality. The alternative criterion wGBLUP did not increase long-term response, although allowed reducing inbreeding rates and loss of favorable alleles. The results suggest that GS outperforms PBLUP when the selected trait is under less polygenic background and that attributing more weight to low-frequency favorable alleles can reduce inbreeding rates and loss of favorable alleles in GS.

[Employees in high-reliability organizations: systematic selection of personnel as a final criterion].

PubMed

Oubaid, V; Anheuser, P

2014-05-01

Employees represent an important safety factor in high-reliability organizations. The combination of clear organizational structures, a nonpunitive safety culture, and psychological personnel selection guarantee a high level of safety. The cockpit personnel selection process of a major German airline is presented in order to demonstrate a possible transferability into medicine and urology.

Evaluation of Weighted Scale Reliability and Criterion Validity: A Latent Variable Modeling Approach

ERIC Educational Resources Information Center

Raykov, Tenko

2007-01-01

A method is outlined for evaluating the reliability and criterion validity of weighted scales based on sets of unidimensional measures. The approach is developed within the framework of latent variable modeling methodology and is useful for point and interval estimation of these measurement quality coefficients in counseling and education…

An enhanced version of a bone-remodelling model based on the continuum damage mechanics theory.

PubMed

Mengoni, M; Ponthot, J P

2015-01-01

The purpose of this work was to propose an enhancement of Doblaré and García's internal bone remodelling model based on the continuum damage mechanics (CDM) theory. In their paper, they stated that the evolution of the internal variables of the bone microstructure, and its incidence on the modification of the elastic constitutive parameters, may be formulated following the principles of CDM, although no actual damage was considered. The resorption and apposition criteria (similar to the damage criterion) were expressed in terms of a mechanical stimulus. However, the resorption criterion is lacking a dimensional consistency with the remodelling rate. We propose here an enhancement to this resorption criterion, insuring the dimensional consistency while retaining the physical properties of the original remodelling model. We then analyse the change in the resorption criterion hypersurface in the stress space for a two-dimensional (2D) analysis. We finally apply the new formulation to analyse the structural evolution of a 2D femur. This analysis gives results consistent with the original model but with a faster and more stable convergence rate.

Analysis of Criteria Influencing Contractor Selection Using TOPSIS Method

NASA Astrophysics Data System (ADS)

Alptekin, Orkun; Alptekin, Nesrin

2017-10-01

Selection of the most suitable contractor is an important process in public construction projects. This process is a major decision which may influence the progress and success of a construction project. Improper selection of contractors may lead to problems such as bad quality of work and delay in project duration. Especially in the construction projects of public buildings, the proper choice of contractor is beneficial to the public institution. Public procurement processes have different characteristics in respect to dissimilarities in political, social and economic features of every country. In Turkey, Turkish Public Procurement Law PPL 4734 is the main regulatory law for the procurement of the public buildings. According to the PPL 4734, public construction administrators have to contract with the lowest bidder who has the minimum requirements according to the criteria in prequalification process. Public administrators are not sufficient for selection of the proper contractor because of the restrictive provisions of the PPL 4734. The lowest bid method does not enable public construction administrators to select the most qualified contractor and they have realised the fact that the selection of a contractor based on lowest bid alone is inadequate and may lead to the failure of the project in terms of time delay Eand poor quality standards. In order to evaluate the overall efficiency of a project, it is necessary to identify selection criteria. This study aims to focus on identify importance of other criteria besides lowest bid criterion in contractor selection process of PPL 4734. In this study, a survey was conducted to staff of Department of Construction Works of Eskisehir Osmangazi University. According to TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution) for analysis results, termination of construction work in previous tenders is the most important criterion of 12 determined criteria. The lowest bid criterion is ranked in rank 5.

How the mind shapes action: Offline contexts modulate involuntary episodic retrieval.

PubMed

Frings, Christian; Koch, Iring; Moeller, Birte

2017-11-01

Involuntary retrieval of previous stimulus-response episodes is a centerpiece of many theories of priming, episodic binding, and action control. Typically it is assumed that by repeating a stimulus from trial n-1 to trial n, involuntary retrieval is triggered in a nearly automatic fashion, facilitating (or interfering with) the to-be-executed action. Here we argue that changes in the offline context weaken the involuntary retrieval of previous episodes (the offline context is defined to be the information presented before or after the focal stimulus). In four conditions differing in cue modality and target modality, retrieval was diminished if participants changed the target selection criterion (as indicated by a cue presented before the selection took place) while they still performed the same task. Thus, solely through changes in the offline context (cue or selection criterion), involuntary retrieval can be weakened in an effective way.

Physical mechanism and numerical simulation of the inception of the lightning upward leader

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

Li Qingmin; Lu Xinchang; Shi Wei

2012-12-15

The upward leader is a key physical process of the leader progression model of lightning shielding. The inception mechanism and criterion of the upward leader need further understanding and clarification. Based on leader discharge theory, this paper proposes the critical electric field intensity of the stable upward leader (CEFISUL) and characterizes it by the valve electric field intensity on the conductor surface, E{sub L}, which is the basis of a new inception criterion for the upward leader. Through numerical simulation under various physical conditions, we verified that E{sub L} is mainly related to the conductor radius, and data fitting yieldsmore » the mathematical expression of E{sub L}. We further establish a computational model for lightning shielding performance of the transmission lines based on the proposed CEFISUL criterion, which reproduces the shielding failure rate of typical UHV transmission lines. The model-based calculation results agree well with the statistical data from on-site operations, which show the effectiveness and validity of the CEFISUL criterion.« less

The impact of model prediction error in designing geodetic networks for crustal deformation applications

NASA Astrophysics Data System (ADS)

Murray, J. R.

2017-12-01

Earth surface displacements measured at Global Navigation Satellite System (GNSS) sites record crustal deformation due, for example, to slip on faults underground. A primary objective in designing geodetic networks to study crustal deformation is to maximize the ability to recover parameters of interest like fault slip. Given Green's functions (GFs) relating observed displacement to motion on buried dislocations representing a fault, one can use various methods to estimate spatially variable slip. However, assumptions embodied in the GFs, e.g., use of a simplified elastic structure, introduce spatially correlated model prediction errors (MPE) not reflected in measurement uncertainties (Duputel et al., 2014). In theory, selection algorithms should incorporate inter-site correlations to identify measurement locations that give unique information. I assess the impact of MPE on site selection by expanding existing methods (Klein et al., 2017; Reeves and Zhe, 1999) to incorporate this effect. Reeves and Zhe's algorithm sequentially adds or removes a predetermined number of data according to a criterion that minimizes the sum of squared errors (SSE) on parameter estimates. Adapting this method to GNSS network design, Klein et al. select new sites that maximize model resolution, using trade-off curves to determine when additional resolution gain is small. Their analysis uses uncorrelated data errors and GFs for a uniform elastic half space. I compare results using GFs for spatially variable strike slip on a discretized dislocation in a uniform elastic half space, a layered elastic half space, and a layered half space with inclusion of MPE. I define an objective criterion to terminate the algorithm once the next site removal would increase SSE more than the expected incremental SSE increase if all sites had equal impact. Using a grid of candidate sites with 8 km spacing, I find the relative value of the selected sites (defined by the percent increase in SSE that further removal of each site would cause) is more uniform when MPE is included. However, the number and distribution of selected sites depends primarily on site location relative to the fault. For this test case, inclusion of MPE has minimal practical impact; I will investigate whether these findings hold for more densely spaced candidate grids and dipping faults.

Crucial nesting habitat for gunnison sage-grouse: A spatially explicit hierarchical approach

USGS Publications Warehouse

Aldridge, Cameron L.; Saher, D.J.; Childers, T.M.; Stahlnecker, K.E.; Bowen, Z.H.

2012-01-01

Gunnison sage-grouse (Centrocercus minimus) is a species of special concern and is currently considered a candidate species under Endangered Species Act. Careful management is therefore required to ensure that suitable habitat is maintained, particularly because much of the species' current distribution is faced with exurban development pressures. We assessed hierarchical nest site selection patterns of Gunnison sage-grouse inhabiting the western portion of the Gunnison Basin, Colorado, USA, at multiple spatial scales, using logistic regression-based resource selection functions. Models were selected using Akaike Information Criterion corrected for small sample sizes (AIC c) and predictive surfaces were generated using model averaged relative probabilities. Landscape-scale factors that had the most influence on nest site selection included the proportion of sagebrush cover >5%, mean productivity, and density of 2 wheel-drive roads. The landscape-scale predictive surface captured 97% of known Gunnison sage-grouse nests within the top 5 of 10 prediction bins, implicating 57% of the basin as crucial nesting habitat. Crucial habitat identified by the landscape model was used to define the extent for patch-scale modeling efforts. Patch-scale variables that had the greatest influence on nest site selection were the proportion of big sagebrush cover >10%, distance to residential development, distance to high volume paved roads, and mean productivity. This model accurately predicted independent nest locations. The unique hierarchical structure of our models more accurately captures the nested nature of habitat selection, and allowed for increased discrimination within larger landscapes of suitable habitat. We extrapolated the landscape-scale model to the entire Gunnison Basin because of conservation concerns for this species. We believe this predictive surface is a valuable tool which can be incorporated into land use and conservation planning as well the assessment of future land-use scenarios. ?? 2011 The Wildlife Society.

D-optimal experimental designs to test for departure from additivity in a fixed-ratio mixture ray.

PubMed

Coffey, Todd; Gennings, Chris; Simmons, Jane Ellen; Herr, David W

2005-12-01

Traditional factorial designs for evaluating interactions among chemicals in a mixture may be prohibitive when the number of chemicals is large. Using a mixture of chemicals with a fixed ratio (mixture ray) results in an economical design that allows estimation of additivity or nonadditive interaction for a mixture of interest. This methodology is extended easily to a mixture with a large number of chemicals. Optimal experimental conditions can be chosen that result in increased power to detect departures from additivity. Although these designs are used widely for linear models, optimal designs for nonlinear threshold models are less well known. In the present work, the use of D-optimal designs is demonstrated for nonlinear threshold models applied to a fixed-ratio mixture ray. For a fixed sample size, this design criterion selects the experimental doses and number of subjects per dose level that result in minimum variance of the model parameters and thus increased power to detect departures from additivity. An optimal design is illustrated for a 2:1 ratio (chlorpyrifos:carbaryl) mixture experiment. For this example, and in general, the optimal designs for the nonlinear threshold model depend on prior specification of the slope and dose threshold parameters. Use of a D-optimal criterion produces experimental designs with increased power, whereas standard nonoptimal designs with equally spaced dose groups may result in low power if the active range or threshold is missed.

Investigation of Two Models to Set and Evaluate Quality Targets for HbA1c: Biological Variation and Sigma-metrics

PubMed Central

Weykamp, Cas; John, Garry; Gillery, Philippe; English, Emma; Ji, Linong; Lenters-Westra, Erna; Little, Randie R.; Roglic, Gojka; Sacks, David B.; Takei, Izumi

2016-01-01

Background A major objective of the IFCC Task Force on implementation of HbA1c standardization is to develop a model to define quality targets for HbA1c. Methods Two generic models, the Biological Variation and Sigma-metrics model, are investigated. Variables in the models were selected for HbA1c and data of EQA/PT programs were used to evaluate the suitability of the models to set and evaluate quality targets within and between laboratories. Results In the biological variation model 48% of individual laboratories and none of the 26 instrument groups met the minimum performance criterion. In the Sigma-metrics model, with a total allowable error (TAE) set at 5 mmol/mol (0.46% NGSP) 77% of the individual laboratories and 12 of 26 instrument groups met the 2 sigma criterion. Conclusion The Biological Variation and Sigma-metrics model were demonstrated to be suitable for setting and evaluating quality targets within and between laboratories. The Sigma-metrics model is more flexible as both the TAE and the risk of failure can be adjusted to requirements related to e.g. use for diagnosis/monitoring or requirements of (inter)national authorities. With the aim of reaching international consensus on advice regarding quality targets for HbA1c, the Task Force suggests the Sigma-metrics model as the model of choice with default values of 5 mmol/mol (0.46%) for TAE, and risk levels of 2 and 4 sigma for routine laboratories and laboratories performing clinical trials, respectively. These goals should serve as a starting point for discussion with international stakeholders in the field of diabetes. PMID:25737535

Optimization of Thermal Object Nonlinear Control Systems by Energy Efficiency Criterion.

NASA Astrophysics Data System (ADS)

Velichkin, Vladimir A.; Zavyalov, Vladimir A.

2018-03-01

This article presents the results of thermal object functioning control analysis (heat exchanger, dryer, heat treatment chamber, etc.). The results were used to determine a mathematical model of the generalized thermal control object. The appropriate optimality criterion was chosen to make the control more energy-efficient. The mathematical programming task was formulated based on the chosen optimality criterion, control object mathematical model and technological constraints. The “maximum energy efficiency” criterion helped avoid solving a system of nonlinear differential equations and solve the formulated problem of mathematical programming in an analytical way. It should be noted that in the case under review the search for optimal control and optimal trajectory reduces to solving an algebraic system of equations. In addition, it is shown that the optimal trajectory does not depend on the dynamic characteristics of the control object.

29 CFR 1630.10 - Qualification standards, tests, and other selection criteria.

Code of Federal Regulations, 2011 CFR

2011-07-01

... business necessity. (b) Qualification standards and tests related to uncorrected vision. Notwithstanding..., or other selection criteria based on an individual's uncorrected vision unless the standard, test, or... application of a qualification standard, test, or other criterion based on uncorrected vision need not be a...

Statistically Based Approach to Broadband Liner Design and Assessment

NASA Technical Reports Server (NTRS)

Jones, Michael G. (Inventor); Nark, Douglas M. (Inventor)

2016-01-01

A broadband liner design optimization includes utilizing in-duct attenuation predictions with a statistical fan source model to obtain optimum impedance spectra over a number of flow conditions for one or more liner locations in a bypass duct. The predicted optimum impedance information is then used with acoustic liner modeling tools to design liners having impedance spectra that most closely match the predicted optimum values. Design selection is based on an acceptance criterion that provides the ability to apply increasing weighting to specific frequencies and/or operating conditions. One or more broadband design approaches are utilized to produce a broadband liner that targets a full range of frequencies and operating conditions.

Predictability of Bristol Bay, Alaska, sockeye salmon returns one to four years in the future

USGS Publications Warehouse

Adkison, Milo D.; Peterson, R.M.

2000-01-01

Historically, forecast error for returns of sockeye salmon Oncorhynchus nerka to Bristol Bay, Alaska, has been large. Using cross-validation forecast error as our criterion, we selected forecast models for each of the nine principal Bristol Bay drainages. Competing forecast models included stock-recruitment relationships, environmental variables, prior returns of siblings, or combinations of these predictors. For most stocks, we found prior returns of siblings to be the best single predictor of returns; however, forecast accuracy was low even when multiple predictors were considered. For a typical drainage, an 80% confidence interval ranged from one half to double the point forecast. These confidence intervals appeared to be appropriately wide.

Service-Oriented Node Scheduling Scheme for Wireless Sensor Networks Using Markov Random Field Model

PubMed Central

Cheng, Hongju; Su, Zhihuang; Lloret, Jaime; Chen, Guolong

2014-01-01

Future wireless sensor networks are expected to provide various sensing services and energy efficiency is one of the most important criterions. The node scheduling strategy aims to increase network lifetime by selecting a set of sensor nodes to provide the required sensing services in a periodic manner. In this paper, we are concerned with the service-oriented node scheduling problem to provide multiple sensing services while maximizing the network lifetime. We firstly introduce how to model the data correlation for different services by using Markov Random Field (MRF) model. Secondly, we formulate the service-oriented node scheduling issue into three different problems, namely, the multi-service data denoising problem which aims at minimizing the noise level of sensed data, the representative node selection problem concerning with selecting a number of active nodes while determining the services they provide, and the multi-service node scheduling problem which aims at maximizing the network lifetime. Thirdly, we propose a Multi-service Data Denoising (MDD) algorithm, a novel multi-service Representative node Selection and service Determination (RSD) algorithm, and a novel MRF-based Multi-service Node Scheduling (MMNS) scheme to solve the above three problems respectively. Finally, extensive experiments demonstrate that the proposed scheme efficiently extends the network lifetime. PMID:25384005

Comparing the Construct and Criterion-Related Validity of Ability-Based and Mixed-Model Measures of Emotional Intelligence

ERIC Educational Resources Information Center

Livingstone, Holly A.; Day, Arla L.

2005-01-01

Despite the popularity of the concept of emotional intelligence(EI), there is much controversy around its definition, measurement, and validity. Therefore, the authors examined the construct and criterion-related validity of an ability-based EI measure (Mayer Salovey Caruso Emotional Intelligence Test [MSCEIT]) and a mixed-model EI measure…

Empirical agreement in model validation.

PubMed

Jebeile, Julie; Barberousse, Anouk

2016-04-01

Empirical agreement is often used as an important criterion when assessing the validity of scientific models. However, it is by no means a sufficient criterion as a model can be so adjusted as to fit available data even though it is based on hypotheses whose plausibility is known to be questionable. Our aim in this paper is to investigate into the uses of empirical agreement within the process of model validation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparative evaluation of human heat stress indices on selected hospital admissions in Sydney, Australia.

PubMed

Goldie, James; Alexander, Lisa; Lewis, Sophie C; Sherwood, Steven

2017-08-01

To find appropriate regression model specifications for counts of the daily hospital admissions of a Sydney cohort and determine which human heat stress indices best improve the models' fit. We built parent models of eight daily counts of admission records using weather station observations, census population estimates and public holiday data. We added heat stress indices; models with lower Akaike Information Criterion scores were judged a better fit. Five of the eight parent models demonstrated adequate fit. Daily maximum Simplified Wet Bulb Globe Temperature (sWBGT) consistently improved fit more than most other indices; temperature and heatwave indices also modelled some health outcomes well. Humidity and heat-humidity indices better fit counts of patients who died following admission. Maximum sWBGT is an ideal measure of heat stress for these types of Sydney hospital admissions. Simple temperature indices are a good fallback where a narrower range of conditions is investigated. Implications for public health: This study confirms the importance of selecting appropriate heat stress indices for modelling. Epidemiologists projecting Sydney hospital admissions should use maximum sWBGT as a common measure of heat stress. Health organisations interested in short-range forecasting may prefer simple temperature indices. © 2017 The Authors.

Precoded spatial multiplexing MIMO system with spatial component interleaver.

PubMed

Gao, Xiang; Wu, Zhanji

In this paper, the performance of precoded bit-interleaved coded modulation (BICM) spatial multiplexing multiple-input multiple-output (MIMO) system with spatial component interleaver is investigated. For the ideal precoded spatial multiplexing MIMO system with spatial component interleaver based on singular value decomposition (SVD) of the MIMO channel, the average pairwise error probability (PEP) of coded bits is derived. Based on the PEP analysis, the optimum spatial Q-component interleaver design criterion is provided to achieve the minimum error probability. For the limited feedback precoded proposed scheme with linear zero forcing (ZF) receiver, in order to minimize a bound on the average probability of a symbol vector error, a novel effective signal-to-noise ratio (SNR)-based precoding matrix selection criterion and a simplified criterion are proposed. Based on the average mutual information (AMI)-maximization criterion, the optimal constellation rotation angles are investigated. Simulation results indicate that the optimized spatial multiplexing MIMO system with spatial component interleaver can achieve significant performance advantages compared to the conventional spatial multiplexing MIMO system.

Investigation of limit state criteria for amorphous metals

NASA Astrophysics Data System (ADS)

Comanici, A. M.; Sandovici, A.; Barsanescu, P. D.

2016-08-01

The name of amorphous metals is assigned to metals that have a non-crystalline structure, but they are also very similar to glass if we look into their properties. A very distinguished feature is the fact that amorphous metals, also known as metallic glasses, show a good electrical conductivity. The extension of the limit state criteria for different materials makes this type of alloy a choice to validate the new criterions. Using a new criterion developed for biaxial and triaxial state of stress, the results are investigated in order to determine the applicability of the mathematical model for these amorphous metals. Especially for brittle materials, it is extremely important to find suitable fracture criterion. Mohr-Coulomb criterion, which is permitting a linear failure envelope, is often used for very brittle materials. But for metallic glasses this criterion is not consistent with the experimental determinations. For metallic glasses, and other high-strength materials, Rui Tao Qu and Zhe Feng Zhang proposed a failure envelope modeling with an ellipse in σ-τ coordinates. In this paper this model is being developed for principal stresses space. It is also proposed a method for transforming σ-τ coordinates in principal stresses coordinates and the theoretical results are consistent with the experimental ones.

Optimal Tikhonov regularization for DEER spectroscopy

NASA Astrophysics Data System (ADS)

Edwards, Thomas H.; Stoll, Stefan

2018-03-01

Tikhonov regularization is the most commonly used method for extracting distance distributions from experimental double electron-electron resonance (DEER) spectroscopy data. This method requires the selection of a regularization parameter, α , and a regularization operator, L. We analyze the performance of a large set of α selection methods and several regularization operators, using a test set of over half a million synthetic noisy DEER traces. These are generated from distance distributions obtained from in silico double labeling of a protein crystal structure of T4 lysozyme with the spin label MTSSL. We compare the methods and operators based on their ability to recover the model distance distributions from the noisy time traces. The results indicate that several α selection methods perform quite well, among them the Akaike information criterion and the generalized cross validation method with either the first- or second-derivative operator. They perform significantly better than currently utilized L-curve methods.

QSRR using evolved artificial neural network for 52 common pharmaceuticals and drugs of abuse in hair from UPLC-TOF-MS.

PubMed

Noorizadeh, Hadi; Farmany, Abbas; Narimani, Hojat; Noorizadeh, Mehrab

2013-05-01

A quantitative structure-retention relationship (QSRR) study based on an artificial neural network (ANN) was carried out for the prediction of the ultra-performance liquid chromatography-Time-of-Flight mass spectrometry (UPLC-TOF-MS) retention time (RT) of a set of 52 pharmaceuticals and drugs of abuse in hair. The genetic algorithm was used as a variable selection tool. A partial least squares (PLS) method was used to select the best descriptors which were used as input neurons in neural network model. For choosing the best predictive model from among comparable models, square correlation coefficient R(2) for the whole set calculated based on leave-group-out predicted values of the training set and model-derived predicted values for the test set compounds is suggested to be a good criterion. Finally, to improve the results, structure-retention relationships were followed by a non-linear approach using artificial neural networks and consequently better results were obtained. This also demonstrates the advantages of ANN. Copyright © 2011 John Wiley & Sons, Ltd.

Research Supervisors' Perceptions of Effective Practices for Selecting Successful Research Candidates

ERIC Educational Resources Information Center

Blunt, R. J. S.

2009-01-01

This investigation elicited the perceptions of thirteen of the most successful research supervisors from one university, with a view to identifying their approaches to selecting research candidates. The supervisors were identified by the university's research office using the single criterion of having the largest number of completed research…

Plasma polar lipid profiles of channel catfish with different growth rates

USDA-ARS?s Scientific Manuscript database

Increased growth in channel catfish is an economically important trait and has been used as a criterion for the selection and development of brood fish. Selection of channel catfish toward increased growth usually results in the accumulation of large amounts of fats in their abdomen rather than incr...

App Development Paradigms for Instructional Developers

ERIC Educational Resources Information Center

Luterbach, Kenneth J.; Hubbell, Kenneth R.

2015-01-01

To create instructional apps for desktop, laptop and mobile devices, developers must select a development tool. Tool selection is critical and complicated by the large number and variety of app development tools. One important criterion to consider is the type of development environment, which may primarily be visual or symbolic. Those distinct…

Mesh size selectivity of the gillnet in East China Sea

NASA Astrophysics Data System (ADS)

Li, L. Z.; Tang, J. H.; Xiong, Y.; Huang, H. L.; Wu, L.; Shi, J. J.; Gao, Y. S.; Wu, F. Q.

2017-07-01

A production test using several gillnets with various mesh sizes was carried out to discover the selectivity of gillnets in the East China Sea. The result showed that the composition of the catch species was synthetically affected by panel height and mesh size. The bycatch species of the 10-m nets were more than those of the 6-m nets. For target species, the effect of panel height on juvenile fish was ambiguous, but the number of juvenile fish declined quickly with the increase in mesh size. According to model deviance (D) and Akaike’s information criterion, the bi-normal model provided the best fit for small yellow croaker (Larimichthy polyactis), and the relative retention was 0.2 and 1, respectively. For Chelidonichthys spinosus, the log-normal was the best model; the right tilt of the selectivity curve was obvious and well coincided with the original data. The contact population of small yellow croaker showed a bi-normal distribution, and body lengths ranged from 95 to 215 mm. The contact population of C. spinosus showed a normal distribution, and the body lengths ranged from 95 to 205 mm. These results can provide references for coastal fishery management.

A forecasting model for dengue incidence in the District of Gampaha, Sri Lanka.

PubMed

Withanage, Gayan P; Viswakula, Sameera D; Nilmini Silva Gunawardena, Y I; Hapugoda, Menaka D

2018-04-24

Dengue is one of the major health problems in Sri Lanka causing an enormous social and economic burden to the country. An accurate early warning system can enhance the efficiency of preventive measures. The aim of the study was to develop and validate a simple accurate forecasting model for the District of Gampaha, Sri Lanka. Three time-series regression models were developed using monthly rainfall, rainy days, temperature, humidity, wind speed and retrospective dengue incidences over the period January 2012 to November 2015 for the District of Gampaha, Sri Lanka. Various lag times were analyzed to identify optimum forecasting periods including interactions of multiple lags. The models were validated using epidemiological data from December 2015 to November 2017. Prepared models were compared based on Akaike's information criterion, Bayesian information criterion and residual analysis. The selected model forecasted correctly with mean absolute errors of 0.07 and 0.22, and root mean squared errors of 0.09 and 0.28, for training and validation periods, respectively. There were no dengue epidemics observed in the district during the training period and nine outbreaks occurred during the forecasting period. The proposed model captured five outbreaks and correctly rejected 14 within the testing period of 24 months. The Pierce skill score of the model was 0.49, with a receiver operating characteristic of 86% and 92% sensitivity. The developed weather based forecasting model allows warnings of impending dengue outbreaks and epidemics in advance of one month with high accuracy. Depending upon climatic factors, the previous month's dengue cases had a significant effect on the dengue incidences of the current month. The simple, precise and understandable forecasting model developed could be used to manage limited public health resources effectively for patient management, vector surveillance and intervention programmes in the district.

Application of time series analysis in modelling and forecasting emergency department visits in a medical centre in Southern Taiwan

PubMed Central

Juang, Wang-Chuan; Huang, Sin-Jhih; Huang, Fong-Dee; Cheng, Pei-Wen; Wann, Shue-Ren

2017-01-01

Objective Emergency department (ED) overcrowding is acknowledged as an increasingly important issue worldwide. Hospital managers are increasingly paying attention to ED crowding in order to provide higher quality medical services to patients. One of the crucial elements for a good management strategy is demand forecasting. Our study sought to construct an adequate model and to forecast monthly ED visits. Methods We retrospectively gathered monthly ED visits from January 2009 to December 2016 to carry out a time series autoregressive integrated moving average (ARIMA) analysis. Initial development of the model was based on past ED visits from 2009 to 2016. A best-fit model was further employed to forecast the monthly data of ED visits for the next year (2016). Finally, we evaluated the predicted accuracy of the identified model with the mean absolute percentage error (MAPE). The software packages SAS/ETS V.9.4 and Office Excel 2016 were used for all statistical analyses. Results A series of statistical tests showed that six models, including ARIMA (0, 0, 1), ARIMA (1, 0, 0), ARIMA (1, 0, 1), ARIMA (2, 0, 1), ARIMA (3, 0, 1) and ARIMA (5, 0, 1), were candidate models. The model that gave the minimum Akaike information criterion and Schwartz Bayesian criterion and followed the assumptions of residual independence was selected as the adequate model. Finally, a suitable ARIMA (0, 0, 1) structure, yielding a MAPE of 8.91%, was identified and obtained as Visitt=7111.161+(at+0.37462 at−1). Conclusion The ARIMA (0, 0, 1) model can be considered adequate for predicting future ED visits, and its forecast results can be used to aid decision-making processes. PMID:29196487

Genome-wide heterogeneity of nucleotide substitution model fit.

PubMed

Arbiza, Leonardo; Patricio, Mateus; Dopazo, Hernán; Posada, David

2011-01-01

At a genomic scale, the patterns that have shaped molecular evolution are believed to be largely heterogeneous. Consequently, comparative analyses should use appropriate probabilistic substitution models that capture the main features under which different genomic regions have evolved. While efforts have concentrated in the development and understanding of model selection techniques, no descriptions of overall relative substitution model fit at the genome level have been reported. Here, we provide a characterization of best-fit substitution models across three genomic data sets including coding regions from mammals, vertebrates, and Drosophila (24,000 alignments). According to the Akaike Information Criterion (AIC), 82 of 88 models considered were selected as best-fit models at least in one occasion, although with very different frequencies. Most parameter estimates also varied broadly among genes. Patterns found for vertebrates and Drosophila were quite similar and often more complex than those found in mammals. Phylogenetic trees derived from models in the 95% confidence interval set showed much less variance and were significantly closer to the tree estimated under the best-fit model than trees derived from models outside this interval. Although alternative criteria selected simpler models than the AIC, they suggested similar patterns. All together our results show that at a genomic scale, different gene alignments for the same set of taxa are best explained by a large variety of different substitution models and that model choice has implications on different parameter estimates including the inferred phylogenetic trees. After taking into account the differences related to sample size, our results suggest a noticeable diversity in the underlying evolutionary process. All together, we conclude that the use of model selection techniques is important to obtain consistent phylogenetic estimates from real data at a genomic scale.

Assessing the general health of diagnostic orphans using the Short Form Health Survey (SF-12v2): a latent variable modelling approach.

PubMed

McBride, Orla; Adamson, Gary; Bunting, Brendan P; McCann, Siobhan

2009-01-01

Research has demonstrated that diagnostic orphans (i.e. individuals who experience only one to two criteria of DSM-IV alcohol dependence) can encounter significant health problems. Using the SF-12v2, this study examined the general health functioning of alcohol users, and in particular, diagnostic orphans. Current drinkers (n = 26,913) in the National Epidemiologic Survey on Alcohol and Related Conditions were categorized into five diagnosis groups: no alcohol use disorder (no-AUD), one-criterion orphans, two-criterion orphans, alcohol abuse and alcohol dependence. Latent variable modelling was used to assess the associations between the physical and mental health factors of the SF-12v2 and the diagnosis groups and a variety of background variables. In terms of mental health, one-criterion orphans had significantly better health than two-criterion orphans and the dependence group, but poorer health than the no-AUD group. No significant differences were evident between the one-criterion orphan group and the alcohol abuse group. One-criterion orphans had significantly poorer physical health when compared to the no-AUD group. One- and two-criterion orphans did not differ in relation to physical health. Consistent with previous research, diagnostic orphans in the current study appear to have experienced clinically relevant symptoms of alcohol dependence. The current findings suggest that diagnostic orphans may form part of an alcohol use disorders spectrum severity.

A comparison of the criterion validity of popular measures of narcissism and narcissistic personality disorder via the use of expert ratings.

PubMed

Miller, Joshua D; McCain, Jessica; Lynam, Donald R; Few, Lauren R; Gentile, Brittany; MacKillop, James; Campbell, W Keith

2014-09-01

The growing interest in the study of narcissism has resulted in the development of a number of assessment instruments that manifest only modest to moderate convergence. The present studies adjudicate among these measures with regard to criterion validity. In the 1st study, we compared multiple narcissism measures to expert consensus ratings of the personality traits associated with narcissistic personality disorder (NPD; Study 1; N = 98 community participants receiving psychological/psychiatric treatment) according to the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM-IV-TR; American Psychiatric Association, 2000) using 5-factor model traits as well as the traits associated with the pathological trait model according to the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; American Psychiatric Association, 2013). In Study 2 (N = 274 undergraduates), we tested the criterion validity of an even larger set of narcissism instruments by examining their relations with measures of general and pathological personality, as well as psychopathology, and compared the resultant correlations to the correlations expected by experts for measures of grandiose and vulnerable narcissism. Across studies, the grandiose dimensions from the Five-Factor Narcissism Inventory (FFNI; Glover, Miller, Lynam, Crego, & Widiger, 2012) and the Narcissistic Personality Inventory (Raskin & Terry, 1988) provided the strongest match to expert ratings of DSM-IV-TR NPD and grandiose narcissism, whereas the vulnerable dimensions of the FFNI and the Pathological Narcissism Inventory (Pincus et al., 2009), as well as the Hypersensitive Narcissism Scale (Hendin & Cheek, 1997), provided the best match to expert ratings of vulnerable narcissism. These results should help guide researchers toward the selection of narcissism instruments that are most well suited to capturing different aspects of narcissism. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Modelling the graphite fracture mechanisms

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

Jacquemoud, C.; Marie, S.; Nedelec, M.

2012-07-01

In order to define a design criterion for graphite components, it is important to identify the physical phenomena responsible for the graphite fracture, to include them in a more effective modelling. In a first step, a large panel of experiments have been realised in order to build up an important database; results of tensile tests, 3 and 4 point bending tests on smooth and notched specimens have been analysed and have demonstrated an important geometry related effects on the behavior up to fracture. Then, first simulations with an elastic or an elastoplastic bilinear constitutive law have not made it possiblemore » to simulate the experimental fracture stress variations with the specimen geometry, the fracture mechanisms of the graphite being at the microstructural scale. That is the reason why a specific F.E. model of the graphite structure has been developed in which every graphite grain has been meshed independently, the crack initiation along the basal plane of the particles as well as the crack propagation and coalescence have been modelled too. This specific model has been used to test two different approaches for fracture initiation: a critical stress criterion and two criteria of fracture mechanic type. They are all based on crystallographic considerations as a global critical stress criterion gave unsatisfactory results. The criteria of fracture mechanic type being extremely unstable and unable to represent the graphite global behaviour up to the final collapse, the critical stress criterion has been preferred to predict the results of the large range of available experiments, on both smooth and notched specimens. In so doing, the experimental observations have been correctly simulated: the geometry related effects on the experimental fracture stress dispersion, the specimen volume effects on the macroscopic fracture stress and the crack propagation at a constant stress intensity factor. In addition, the parameters of the criterion have been related to experimental observations: the local crack initiation stress of 8 MPa corresponds to the non-linearity apparition on the global behavior observed experimentally and the the maximal critical stress defined for the particle of 30 MPa is equivalent to the fracture stress of notched specimens. This innovative combination of crack modelling and a local crystallographic critical stress criterion made it possible to understand that cleavage initiation and propagation in the graphite microstructure was driven by a mean critical stress criterion. (authors)« less

40 CFR 35.6555 - Competition.

Code of Federal Regulations, 2012 CFR

2012-07-01

... engineering (A/E) services, the recipient may use geographic location as a selection criterion, provided that... bids or proposals. The recipient must publish the public notice in professional journals, newspapers...

40 CFR 35.6555 - Competition.

Code of Federal Regulations, 2013 CFR

2013-07-01

... engineering (A/E) services, the recipient may use geographic location as a selection criterion, provided that... bids or proposals. The recipient must publish the public notice in professional journals, newspapers...

40 CFR 35.6555 - Competition.

Code of Federal Regulations, 2014 CFR

2014-07-01

... engineering (A/E) services, the recipient may use geographic location as a selection criterion, provided that... bids or proposals. The recipient must publish the public notice in professional journals, newspapers...

A K-BKZ Formulation for Soft-Tissue Viscoelasticity

NASA Technical Reports Server (NTRS)

Freed, Alan D.; Diethelm, Kai

2005-01-01

A viscoelastic model of the K-BKZ (Kaye 1962; Bernstein et al. 1963) type is developed for isotropic biological tissues, and applied to the fat pad of the human heel. To facilitate this pursuit, a class of elastic solids is introduced through a novel strain-energy function whose elements possess strong ellipticity, and therefore lead to stable material models. The standard fractional-order viscoelastic (FOV) solid is used to arrive at the overall elastic/viscoelastic structure of the model, while the elastic potential via the K-BKZ hypothesis is used to arrive at the tensorial structure of the model. Candidate sets of functions are proposed for the elastic and viscoelastic material functions present in the model, including a regularized fractional derivative that was determined to be the best. The Akaike information criterion (AIC) is advocated for performing multi-model inference, enabling an objective selection of the best material function from within a candidate set.

Fractional calculus in biomechanics: a 3D viscoelastic model using regularized fractional derivative kernels with application to the human calcaneal fat pad.

PubMed

Freed, A D; Diethelm, K

2006-11-01

A viscoelastic model of the K-BKZ (Kaye, Technical Report 134, College of Aeronautics, Cranfield 1962; Bernstein et al., Trans Soc Rheol 7: 391-410, 1963) type is developed for isotropic biological tissues and applied to the fat pad of the human heel. To facilitate this pursuit, a class of elastic solids is introduced through a novel strain-energy function whose elements possess strong ellipticity, and therefore lead to stable material models. This elastic potential - via the K-BKZ hypothesis - also produces the tensorial structure of the viscoelastic model. Candidate sets of functions are proposed for the elastic and viscoelastic material functions present in the model, including two functions whose origins lie in the fractional calculus. The Akaike information criterion is used to perform multi-model inference, enabling an objective selection to be made as to the best material function from within a candidate set.

The Benslimane's Artistic Model for Leg Beauty.

PubMed

Benslimane, Fahd

2012-08-01

In 2000, the author started observing legs considered to be attractive. The goal was to have an ideal aesthetic model and compare the disparity between this model and a patient's reality. This could prove helpful during leg sculpturing to get closer to this ideal. Postoperatively, the result could then be compared to the ideal curves of the model legs and any remaining deviations from the ideal curves could be pointed out and eventually corrected in a second session. The lack of anthropometric studies of legs from the knee to the ankle led the author to select and study attractive legs to find out the common denominators of their beauty. The study consisted in analyzing the features that make legs look attractive. The legs of models in magazines were scanned and inserted into a PowerPoint program. The legs of live models, Barbie dolls, and athletes were photographed. Artistic drawings by Leonardo da Vinci were reviewed and Greek sculptures studied. Sculptures from the National Archaeological Museum of Athens were photographed and included in the PowerPoint program. This study shows that the first criterion for beautiful legs is the straightness of the leg column. Not a single attractive leg was found to deviate from the vertical, and each was in absolute continuity with the thigh. The second criterion is the similarity of curve distribution and progression from knee to ankle. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors at www.springer.com/00266.

Analysis of significant factors for dengue fever incidence prediction.

PubMed

Siriyasatien, Padet; Phumee, Atchara; Ongruk, Phatsavee; Jampachaisri, Katechan; Kesorn, Kraisak

2016-04-16

Many popular dengue forecasting techniques have been used by several researchers to extrapolate dengue incidence rates, including the K-H model, support vector machines (SVM), and artificial neural networks (ANN). The time series analysis methodology, particularly ARIMA and SARIMA, has been increasingly applied to the field of epidemiological research for dengue fever, dengue hemorrhagic fever, and other infectious diseases. The main drawback of these methods is that they do not consider other variables that are associated with the dependent variable. Additionally, new factors correlated to the disease are needed to enhance the prediction accuracy of the model when it is applied to areas of similar climates, where weather factors such as temperature, total rainfall, and humidity are not substantially different. Such drawbacks may consequently lower the predictive power for the outbreak. The predictive power of the forecasting model-assessed by Akaike's information criterion (AIC), Bayesian information criterion (BIC), and the mean absolute percentage error (MAPE)-is improved by including the new parameters for dengue outbreak prediction. This study's selected model outperforms all three other competing models with the lowest AIC, the lowest BIC, and a small MAPE value. The exclusive use of climate factors from similar locations decreases a model's prediction power. The multivariate Poisson regression, however, effectively forecasts even when climate variables are slightly different. Female mosquitoes and seasons were strongly correlated with dengue cases. Therefore, the dengue incidence trends provided by this model will assist the optimization of dengue prevention. The present work demonstrates the important roles of female mosquito infection rates from the previous season and climate factors (represented as seasons) in dengue outbreaks. Incorporating these two factors in the model significantly improves the predictive power of dengue hemorrhagic fever forecasting models, as confirmed by AIC, BIC, and MAPE.

The Information a Test Provides on an Ability Parameter. Research Report. ETS RR-07-18

ERIC Educational Resources Information Center

Haberman, Shelby J.

2007-01-01

In item-response theory, if a latent-structure model has an ability variable, then elementary information theory may be employed to provide a criterion for evaluation of the information the test provides concerning ability. This criterion may be considered even in cases in which the latent-structure model is not valid, although interpretation of…

Assessing the relative importance of parameter and forcing uncertainty and their interactions in conceptual hydrological model simulations

NASA Astrophysics Data System (ADS)

Mockler, E. M.; Chun, K. P.; Sapriza-Azuri, G.; Bruen, M.; Wheater, H. S.

2016-11-01

Predictions of river flow dynamics provide vital information for many aspects of water management including water resource planning, climate adaptation, and flood and drought assessments. Many of the subjective choices that modellers make including model and criteria selection can have a significant impact on the magnitude and distribution of the output uncertainty. Hydrological modellers are tasked with understanding and minimising the uncertainty surrounding streamflow predictions before communicating the overall uncertainty to decision makers. Parameter uncertainty in conceptual rainfall-runoff models has been widely investigated, and model structural uncertainty and forcing data have been receiving increasing attention. This study aimed to assess uncertainties in streamflow predictions due to forcing data and the identification of behavioural parameter sets in 31 Irish catchments. By combining stochastic rainfall ensembles and multiple parameter sets for three conceptual rainfall-runoff models, an analysis of variance model was used to decompose the total uncertainty in streamflow simulations into contributions from (i) forcing data, (ii) identification of model parameters and (iii) interactions between the two. The analysis illustrates that, for our subjective choices, hydrological model selection had a greater contribution to overall uncertainty, while performance criteria selection influenced the relative intra-annual uncertainties in streamflow predictions. Uncertainties in streamflow predictions due to the method of determining parameters were relatively lower for wetter catchments, and more evenly distributed throughout the year when the Nash-Sutcliffe Efficiency of logarithmic values of flow (lnNSE) was the evaluation criterion.

On the problem of data assimilation by means of synchronization

NASA Astrophysics Data System (ADS)

Szendro, Ivan G.; RodríGuez, Miguel A.; López, Juan M.

2009-10-01

The potential use of synchronization as a method for data assimilation is investigated in a Lorenz96 model. Data representing the reality are obtained from a Lorenz96 model with added noise. We study the assimilation scheme by means of synchronization for different noise intensities. We use a novel plot representation of the synchronization error in a phase diagram consisting of two variables: the amplitude and the width of the error after a suitable logarithmic transformation (the so-called mean-variance of logarithms diagram). Our main result concerns the existence of an "optimal" coupling for which the synchronization is maximal. We finally show how this allows us to quantify the degree of assimilation, providing a criterion for the selection of optimal couplings and validity of models.

Source spectra of the first four Source Physics Experiments (SPE) explosions from the frequency-domain moment-tensor inversion

DOE PAGES

Yang, Xiaoning

2016-08-01

In this study, I used seismic waveforms recorded within 2 km from the epicenter of the first four Source Physics Experiments (SPE) explosions to invert for the moment-tensor spectra of these explosions. I employed a one-dimensional (1D) Earth model for Green's function calculations. The model was developed from P- and R g-wave travel times and amplitudes. I selected data for the inversion based on the criterion that they had consistent travel times and amplitude behavior as those predicted by the 1D model. Due to limited azimuthal coverage of the sources and the mostly vertical-component-only nature of the dataset, only long-period,more » volumetric components of the moment-tensor spectra were well constrained.« less

Indonesian teacher engagement index: a rasch model analysis

NASA Astrophysics Data System (ADS)

Sasmoko; Abbas, B. S.; Indrianti, Y.; Widhoyoko, S. A.

2018-01-01

The research aimed to calibrate Indonesian Teacher Engagement Index (ITEI) using instrument with RASCH MODEL. The respondents were 672 teachers of elementary, junior high, high school and vocational school. The number of items planned was 165 items with the initial reliability of 0.98. The ITEI scale uses Likert Scale (1 to 4) which was converted from ordinal scale to Equal Interval Scale. RASCH MODEL analysis was done by selecting based on Outfit Mean Square (MNSQ) between 0.5-1.5 as a good item, and measuring Point Measure Correlation (Pt Mean Corr) with the criterion of 0.4-0.85. Moderate Outfit Z-Standard (ZSTD) was ignored because the sample was >500. Conclusions: ITEI is valid with 30 items and reliability of 0.97, and less engage teachers significantly at α <0.05.

A viscoplastic study of crack-tip deformation and crack growth in a nickel-based superalloy at elevated temperature

NASA Astrophysics Data System (ADS)

Zhao, L. G.; Tong, J.

Viscoplastic crack-tip deformation behaviour in a nickel-based superalloy at elevated temperature has been studied for both stationary and growing cracks in a compact tension (CT) specimen using the finite element method. The material behaviour was described by a unified viscoplastic constitutive model with non-linear kinematic and isotropic hardening rules, and implemented in the finite element software ABAQUS via a user-defined material subroutine (UMAT). Finite element analyses for stationary cracks showed distinctive strain ratchetting behaviour near the crack tip at selected load ratios, leading to progressive accumulation of tensile strain normal to the crack-growth plane. Results also showed that low frequencies and superimposed hold periods at peak loads significantly enhanced strain accumulation at crack tip. Finite element simulation of crack growth was carried out under a constant Δ K-controlled loading condition, again ratchetting was observed ahead of the crack tip, similar to that for stationary cracks. A crack-growth criterion based on strain accumulation is proposed where a crack is assumed to grow when the accumulated strain ahead of the crack tip reaches a critical value over a characteristic distance. The criterion has been utilized in the prediction of crack-growth rates in a CT specimen at selected loading ranges, frequencies and dwell periods, and the predictions were compared with the experimental results.

Endoscopic versus Percutaneous Biliary Drainage in Palliation of Advanced Malignant Hilar Obstruction: A Meta-Analysis and Systematic Review

PubMed Central

Dharmapuri, Sirish; Duvvuri, Abhiram; Dharmapuri, Sowmya; Boddireddy, Raghuveer; Moole, Vishnu; Yedama, Prathyusha; Bondalapati, Naveen; Uppu, Achuta

2016-01-01

Background. Palliation in advanced unresectable hilar malignancies can be achieved by endoscopic (EBD) or percutaneous transhepatic biliary drainage (PTBD). It is unclear if one approach is superior to the other in this group of patients. Aims. Compare clinical outcomes of EBD versus PTBD. Methods. (i) Study Selection Criterion. Studies using PTBD and EBD for palliation of advanced unresectable hilar malignancies. (ii) Data Collection and Extraction. Articles were searched in Medline, PubMed, and Ovid journals. (iii) Statistical Method. Fixed and random effects models were used to calculate the pooled proportions. Results. Initial search identified 786 reference articles, in which 62 articles were selected and reviewed. Data was extracted from nine studies (N = 546) that met the inclusion criterion. The pooled odds ratio for successful biliary drainage in PTBD versus EBD was 2.53 (95% CI = 1.57 to 4.08). Odds ratio for overall adverse effects in PTBD versus EBD groups was 0.81 (95% CI = 0.52 to 1.26). Odds ratio for 30-day mortality rate in PTBD group versus EBD group was 0.84 (95% CI = 0.37 to 1.91). Conclusions. In patients with advanced unresectable hilar malignancies, palliation with PTBD seems to be superior to EBD. PTBD is comparable to EBD in regard to overall adverse effects and 30-day mortality. PMID:27648439

Endometrial cancer risk prediction including serum-based biomarkers: results from the EPIC cohort.

PubMed

Fortner, Renée T; Hüsing, Anika; Kühn, Tilman; Konar, Meric; Overvad, Kim; Tjønneland, Anne; Hansen, Louise; Boutron-Ruault, Marie-Christine; Severi, Gianluca; Fournier, Agnès; Boeing, Heiner; Trichopoulou, Antonia; Benetou, Vasiliki; Orfanos, Philippos; Masala, Giovanna; Agnoli, Claudia; Mattiello, Amalia; Tumino, Rosario; Sacerdote, Carlotta; Bueno-de-Mesquita, H B As; Peeters, Petra H M; Weiderpass, Elisabete; Gram, Inger T; Gavrilyuk, Oxana; Quirós, J Ramón; Maria Huerta, José; Ardanaz, Eva; Larrañaga, Nerea; Lujan-Barroso, Leila; Sánchez-Cantalejo, Emilio; Butt, Salma Tunå; Borgquist, Signe; Idahl, Annika; Lundin, Eva; Khaw, Kay-Tee; Allen, Naomi E; Rinaldi, Sabina; Dossus, Laure; Gunter, Marc; Merritt, Melissa A; Tzoulaki, Ioanna; Riboli, Elio; Kaaks, Rudolf

2017-03-15

Endometrial cancer risk prediction models including lifestyle, anthropometric and reproductive factors have limited discrimination. Adding biomarker data to these models may improve predictive capacity; to our knowledge, this has not been investigated for endometrial cancer. Using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we investigated the improvement in discrimination gained by adding serum biomarker concentrations to risk estimates derived from an existing risk prediction model based on epidemiologic factors. Serum concentrations of sex steroid hormones, metabolic markers, growth factors, adipokines and cytokines were evaluated in a step-wise backward selection process; biomarkers were retained at p < 0.157 indicating improvement in the Akaike information criterion (AIC). Improvement in discrimination was assessed using the C-statistic for all biomarkers alone, and change in C-statistic from addition of biomarkers to preexisting absolute risk estimates. We used internal validation with bootstrapping (1000-fold) to adjust for over-fitting. Adiponectin, estrone, interleukin-1 receptor antagonist, tumor necrosis factor-alpha and triglycerides were selected into the model. After accounting for over-fitting, discrimination was improved by 2.0 percentage points when all evaluated biomarkers were included and 1.7 percentage points in the model including the selected biomarkers. Models including etiologic markers on independent pathways and genetic markers may further improve discrimination. © 2016 UICC.

Innovative high-performance liquid chromatography method development for the screening of 19 antimalarial drugs based on a generic approach, using design of experiments, independent component analysis and design space.

PubMed

Debrus, B; Lebrun, P; Kindenge, J Mbinze; Lecomte, F; Ceccato, A; Caliaro, G; Mbay, J Mavar Tayey; Boulanger, B; Marini, R D; Rozet, E; Hubert, Ph

2011-08-05

An innovative methodology based on design of experiments (DoE), independent component analysis (ICA) and design space (DS) was developed in previous works and was tested out with a mixture of 19 antimalarial drugs. This global LC method development methodology (i.e. DoE-ICA-DS) was used to optimize the separation of 19 antimalarial drugs to obtain a screening method. DoE-ICA-DS methodology is fully compliant with the current trend of quality by design. DoE was used to define the set of experiments to model the retention times at the beginning, the apex and the end of each peak. Furthermore, ICA was used to numerically separate coeluting peaks and estimate their unbiased retention times. Gradient time, temperature and pH were selected as the factors of a full factorial design. These retention times were modelled by stepwise multiple linear regressions. A recently introduced critical quality attribute, namely the separation criterion (S), was also used to assess the quality of separations rather than using the resolution. Furthermore, the resulting mathematical models were also studied from a chromatographic point of view to understand and investigate the chromatographic behaviour of each compound. Good adequacies were found between the mathematical models and the expected chromatographic behaviours predicted by chromatographic theory. Finally, focusing at quality risk management, the DS was computed as the multidimensional subspace where the probability for the separation criterion to lie in acceptance limits was higher than a defined quality level. The DS was computed propagating the prediction error from the modelled responses to the quality criterion using Monte Carlo simulations. DoE-ICA-DS allowed encountering optimal operating conditions to obtain a robust screening method for the 19 considered antimalarial drugs in the framework of the fight against counterfeit medicines. Moreover and only on the basis of the same data set, a dedicated method for the determination of three antimalarial compounds in a pharmaceutical formulation was optimized to demonstrate both the efficiency and flexibility of the methodology proposed in the present study. Copyright © 2011 Elsevier B.V. All rights reserved.

Kinematic Modeling of the 2011, Mw7.1 Van, Eastern Turkey Earthquake Using Teleseismic, Regional and GPS Data

NASA Astrophysics Data System (ADS)

Konca, A.

2013-12-01

A kinematic model for the Mw7.1 2011 Van Earthquake was obtained using regional, teleseismic and GPS data. One issue regarding regional data is that 1D Green's functions may not be appropriate due to complications in the upper mantle and crust that affects the Pnl waveforms. In order to resolve whether the 1D Green's function is appropriate, an aftershock of the main event was also modeled, which is then used as a criterion in the selection of the regional stations. The GPS data itself is not sufficient to obtain a slip model, but helps constrain the slip distribution. The slip distribution is up-dip and bilateral with more slip toward west, where the maximum slip reaches 4 meters. The rupture velocity is about 1.5 km/s.

Ensemble-Based Parameter Estimation in a Coupled GCM Using the Adaptive Spatial Average Method

DOE PAGES

Liu, Y.; Liu, Z.; Zhang, S.; ...

2014-05-29

Ensemble-based parameter estimation for a climate model is emerging as an important topic in climate research. And for a complex system such as a coupled ocean–atmosphere general circulation model, the sensitivity and response of a model variable to a model parameter could vary spatially and temporally. An adaptive spatial average (ASA) algorithm is proposed to increase the efficiency of parameter estimation. Refined from a previous spatial average method, the ASA uses the ensemble spread as the criterion for selecting “good” values from the spatially varying posterior estimated parameter values; these good values are then averaged to give the final globalmore » uniform posterior parameter. In comparison with existing methods, the ASA parameter estimation has a superior performance: faster convergence and enhanced signal-to-noise ratio.« less

Digital Materials - Evaluation of the Possibilities of using Selected Hyperelastic Models to Describe Constitutive Relations

NASA Astrophysics Data System (ADS)

Mańkowski, J.; Lipnicki, J.

2017-08-01

The authors tried to identify the parameters of numerical models of digital materials, which are a kind of composite resulting from the manufacture of the product in 3D printers. With the arrangement of several heads of the printer, the new material can result from mixing of materials with radically different properties, during the process of producing single layer of the product. The new material has properties dependent on the base materials properties and their proportions. Digital materials tensile characteristics are often non-linear and qualify to be described by hyperelastic materials models. The identification was conducted based on the results of tensile tests models, its various degrees coefficients of the polynomials to various degrees coefficients of the polynomials. The Drucker's stability criterion was also examined. Fourteen different materials were analyzed.

Data-Driven Learning of Q-Matrix

PubMed Central

Liu, Jingchen; Xu, Gongjun; Ying, Zhiliang

2013-01-01

The recent surge of interests in cognitive assessment has led to developments of novel statistical models for diagnostic classification. Central to many such models is the well-known Q-matrix, which specifies the item–attribute relationships. This article proposes a data-driven approach to identification of the Q-matrix and estimation of related model parameters. A key ingredient is a flexible T-matrix that relates the Q-matrix to response patterns. The flexibility of the T-matrix allows the construction of a natural criterion function as well as a computationally amenable algorithm. Simulations results are presented to demonstrate usefulness and applicability of the proposed method. Extension to handling of the Q-matrix with partial information is presented. The proposed method also provides a platform on which important statistical issues, such as hypothesis testing and model selection, may be formally addressed. PMID:23926363

Physical approach to price momentum and its application to momentum strategy

NASA Astrophysics Data System (ADS)

Choi, Jaehyung

2014-12-01

We introduce various quantitative and mathematical definitions for price momentum of financial instruments. The price momentum is quantified with velocity and mass concepts originated from the momentum in physics. By using the physical momentum of price as a selection criterion, the weekly contrarian strategies are implemented in South Korea KOSPI 200 and US S&P 500 universes. The alternative strategies constructed by the physical momentum achieve the better expected returns and reward-risk measures than those of the traditional contrarian strategy in weekly scale. The portfolio performance is not understood by the Fama-French three-factor model.

Thermo-solutal growth of an anisotropic dendrite with six-fold symmetry

NASA Astrophysics Data System (ADS)

Alexandrov, D. V.; Galenko, P. K.

2018-03-01

A stable growth of dendritic crystal with the six-fold crystalline anisotropy is analyzed in a binary nonisothermal mixture. A selection criterion representing a relationship between the dendrite tip velocity and its tip diameter is derived on the basis of morphological stability analysis and solvability theory. A complete set of nonlinear equations, consisting of the selection criterion and undercooling balance condition, which determines implicit dependencies of the dendrite tip velocity and tip diameter as functions of the total undercooling, is formulated. Exact analytical solutions of these nonlinear equations are found in a parametric form. Asymptotic solutions describing the crystal growth at small Péclet numbers are determined. Theoretical predictions are compared with experimental data obtained for ice dendrites growing in binary water-ethylenglycol solutions as well as in pure water.

A comparison study of two different control criteria for the real-time management of urban groundwater works.

PubMed

Bauser, G; Hendricks Franssen, Harrie-Jan; Stauffer, Fritz; Kaiser, Hans-Peter; Kuhlmann, U; Kinzelbach, W

2012-08-30

We present the comparison of two control criteria for the real-time management of a water well field. The criteria were used to simulate the operation of the Hardhof well field in the city of Zurich, Switzerland. This well field is threatened by diffuse pollution in the subsurface of the surrounding city area. The risk of attracting pollutants is higher if the pumping rates in four horizontal wells are increased, and can be reduced by increasing artificial recharge in several recharge basins and infiltration wells or by modifying the artificial recharge distribution. A three-dimensional finite elements flow model was built for the Hardhof site. The first control criterion used hydraulic head differences (Δh-criterion) to control the management of the well field and the second criterion used a path line method (%s-criterion) to control the percentage of inflowing water from the city area. Both control methods adapt the allocation of artificial recharge (AR) for given pumping rates in time. The simulation results show that (1) historical management decisions were less effective compared to the optimal control according to the two different criteria and (2) the distribution of artificial recharge calculated with the two control criteria also differ from each other with the %s-criterion giving better results compared to the Δh-criterion. The recharge management with the %s-criterion requires a smaller amount of water to be recharged. The ratio between average artificial recharge and average abstraction is 1.7 for the Δh-criterion and 1.5 for the %s-criterion. Both criteria were tested online. The methodologies were extended to a real-time control method using the Ensemble Kalman Filter method for assimilating 87 online available groundwater head measurements to update the model in real-time. The results of the operational implementation are also satisfying in regard of a reduced risk of well contamination. Copyright © 2012 Elsevier Ltd. All rights reserved.

Failure prediction of thin beryllium sheets used in spacecraft structures

NASA Technical Reports Server (NTRS)

Roschke, Paul N.; Mascorro, Edward; Papados, Photios; Serna, Oscar R.

1991-01-01

The primary objective of this study is to develop a method for prediction of failure of thin beryllium sheets that undergo complex states of stress. Major components of the research include experimental evaluation of strength parameters for cross-rolled beryllium sheet, application of the Tsai-Wu failure criterion to plate bending problems, development of a high order failure criterion, application of the new criterion to a variety of structures, and incorporation of both failure criteria into a finite element code. A Tsai-Wu failure model for SR-200 sheet material is developed from available tensile data, experiments carried out by NASA on two circular plates, and compression and off-axis experiments performed in this study. The failure surface obtained from the resulting criterion forms an ellipsoid. By supplementing experimental data used in the the two-dimensional criterion and modifying previously suggested failure criteria, a multi-dimensional failure surface is proposed for thin beryllium structures. The new criterion for orthotropic material is represented by a failure surface in six-dimensional stress space. In order to determine coefficients of the governing equation, a number of uniaxial, biaxial, and triaxial experiments are required. Details of these experiments and a complementary ultrasonic investigation are described in detail. Finally, validity of the criterion and newly determined mechanical properties is established through experiments on structures composed of SR200 sheet material. These experiments include a plate-plug arrangement under a complex state of stress and a series of plates with an out-of-plane central point load. Both criteria have been incorporated into a general purpose finite element analysis code. Numerical simulation incrementally applied loads to a structural component that is being designed and checks each nodal point in the model for exceedance of a failure criterion. If stresses at all locations do not exceed the failure criterion, the load is increased and the process is repeated. Failure results for the plate-plug and clamped plate tests are accurate to within 2 percent.

A complete graphical criterion for the adjustment formula in mediation analysis.

PubMed

Shpitser, Ilya; VanderWeele, Tyler J

2011-03-04

Various assumptions have been used in the literature to identify natural direct and indirect effects in mediation analysis. These effects are of interest because they allow for effect decomposition of a total effect into a direct and indirect effect even in the presence of interactions or non-linear models. In this paper, we consider the relation and interpretation of various identification assumptions in terms of causal diagrams interpreted as a set of non-parametric structural equations. We show that for such causal diagrams, two sets of assumptions for identification that have been described in the literature are in fact equivalent in the sense that if either set of assumptions holds for all models inducing a particular causal diagram, then the other set of assumptions will also hold for all models inducing that diagram. We moreover build on prior work concerning a complete graphical identification criterion for covariate adjustment for total effects to provide a complete graphical criterion for using covariate adjustment to identify natural direct and indirect effects. Finally, we show that this criterion is equivalent to the two sets of independence assumptions used previously for mediation analysis.

Selection Methods for Undergraduate Admissions in Australia. Does the Australian Predominate Entry Scheme the Australian Tertiary Admissions Rank (ATAR) Have a Future?

ERIC Educational Resources Information Center

Blyth, Kathryn

2014-01-01

This article considers the Australian entry score system, the Australian Tertiary Admissions Rank (ATAR), and its usage as a selection mechanism for undergraduate places in Australian higher education institutions and asks whether its role as the main selection criterion will continue with the introduction of demand driven funding in 2012.…

Examining recognition criterion rigidity during testing using a biased feedback technique: Evidence for adaptive criterion learning

PubMed Central

Han, Sanghoon; Dobbins, Ian G.

2009-01-01

Recognition models often assume that subjects use specific evidence values (decision criteria) to adaptively parse continuous memory evidence into response categories (e.g., “old” or “new”). Although explicit pre-test instructions influence criterion placement, these criteria appear extremely resistant to change once testing begins. We tested criterion sensitivity to local feedback using a novel, biased feedback technique designed to tacitly encourage certain errors by indicating they were correct choices. Experiment 1 demonstrated that fully correct feedback had little effect on criterion placement, whereas biased feedback during Experiments 2 and 3 yielded prominent, durable, and adaptive criterion shifts, with observers reporting they were unaware of the manipulation in Experiment 3. These data suggest recognition criteria can be easily modified during testing through a form of feedback learning that operates independent of stimulus characteristics and observer awareness of the nature of the manipulation. This mechanism may be fundamentally different than criterion shifts following explicit instructions and warnings, or shifts linked to manipulations of stimulus characteristics combined with feedback highlighting those manipulations. PMID:18604954

An Intelligent Ensemble Neural Network Model for Wind Speed Prediction in Renewable Energy Systems.

PubMed

Ranganayaki, V; Deepa, S N

2016-01-01

Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural network models which includes multilayer perceptron (MLP), multilayer adaptive linear neuron (Madaline), back propagation neural network (BPN), and probabilistic neural network (PNN) so as to obtain better accuracy in wind speed prediction with minimum error. The random selection of hidden neurons numbers in artificial neural network results in overfitting or underfitting problem. This paper aims to avoid the occurrence of overfitting and underfitting problems. The selection of number of hidden neurons is done in this paper employing 102 criteria; these evolved criteria are verified by the computed various error values. The proposed criteria for fixing hidden neurons are validated employing the convergence theorem. The proposed intelligent ensemble neural model is applied for wind speed prediction application considering the real time wind data collected from the nearby locations. The obtained simulation results substantiate that the proposed ensemble model reduces the error value to minimum and enhances the accuracy. The computed results prove the effectiveness of the proposed ensemble neural network (ENN) model with respect to the considered error factors in comparison with that of the earlier models available in the literature.

An Intelligent Ensemble Neural Network Model for Wind Speed Prediction in Renewable Energy Systems

PubMed Central

Ranganayaki, V.; Deepa, S. N.

2016-01-01

Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural network models which includes multilayer perceptron (MLP), multilayer adaptive linear neuron (Madaline), back propagation neural network (BPN), and probabilistic neural network (PNN) so as to obtain better accuracy in wind speed prediction with minimum error. The random selection of hidden neurons numbers in artificial neural network results in overfitting or underfitting problem. This paper aims to avoid the occurrence of overfitting and underfitting problems. The selection of number of hidden neurons is done in this paper employing 102 criteria; these evolved criteria are verified by the computed various error values. The proposed criteria for fixing hidden neurons are validated employing the convergence theorem. The proposed intelligent ensemble neural model is applied for wind speed prediction application considering the real time wind data collected from the nearby locations. The obtained simulation results substantiate that the proposed ensemble model reduces the error value to minimum and enhances the accuracy. The computed results prove the effectiveness of the proposed ensemble neural network (ENN) model with respect to the considered error factors in comparison with that of the earlier models available in the literature. PMID:27034973

How Well Can We Detect Lineage-Specific Diversification-Rate Shifts? A Simulation Study of Sequential AIC Methods.

PubMed

May, Michael R; Moore, Brian R

2016-11-01

Evolutionary biologists have long been fascinated by the extreme differences in species numbers across branches of the Tree of Life. This has motivated the development of statistical methods for detecting shifts in the rate of lineage diversification across the branches of phylogenic trees. One of the most frequently used methods, MEDUSA, explores a set of diversification-rate models, where each model assigns branches of the phylogeny to a set of diversification-rate categories. Each model is first fit to the data, and the Akaike information criterion (AIC) is then used to identify the optimal diversification model. Surprisingly, the statistical behavior of this popular method is uncharacterized, which is a concern in light of: (1) the poor performance of the AIC as a means of choosing among models in other phylogenetic contexts; (2) the ad hoc algorithm used to visit diversification models, and; (3) errors that we reveal in the likelihood function used to fit diversification models to the phylogenetic data. Here, we perform an extensive simulation study demonstrating that MEDUSA (1) has a high false-discovery rate (on average, spurious diversification-rate shifts are identified [Formula: see text] of the time), and (2) provides biased estimates of diversification-rate parameters. Understanding the statistical behavior of MEDUSA is critical both to empirical researchers-in order to clarify whether these methods can make reliable inferences from empirical datasets-and to theoretical biologists-in order to clarify the specific problems that need to be solved in order to develop more reliable approaches for detecting shifts in the rate of lineage diversification. [Akaike information criterion; extinction; lineage-specific diversification rates; phylogenetic model selection; speciation.]. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

How Well Can We Detect Lineage-Specific Diversification-Rate Shifts? A Simulation Study of Sequential AIC Methods

PubMed Central

May, Michael R.; Moore, Brian R.

2016-01-01

Evolutionary biologists have long been fascinated by the extreme differences in species numbers across branches of the Tree of Life. This has motivated the development of statistical methods for detecting shifts in the rate of lineage diversification across the branches of phylogenic trees. One of the most frequently used methods, MEDUSA, explores a set of diversification-rate models, where each model assigns branches of the phylogeny to a set of diversification-rate categories. Each model is first fit to the data, and the Akaike information criterion (AIC) is then used to identify the optimal diversification model. Surprisingly, the statistical behavior of this popular method is uncharacterized, which is a concern in light of: (1) the poor performance of the AIC as a means of choosing among models in other phylogenetic contexts; (2) the ad hoc algorithm used to visit diversification models, and; (3) errors that we reveal in the likelihood function used to fit diversification models to the phylogenetic data. Here, we perform an extensive simulation study demonstrating that MEDUSA (1) has a high false-discovery rate (on average, spurious diversification-rate shifts are identified ≈30% of the time), and (2) provides biased estimates of diversification-rate parameters. Understanding the statistical behavior of MEDUSA is critical both to empirical researchers—in order to clarify whether these methods can make reliable inferences from empirical datasets—and to theoretical biologists—in order to clarify the specific problems that need to be solved in order to develop more reliable approaches for detecting shifts in the rate of lineage diversification. [Akaike information criterion; extinction; lineage-specific diversification rates; phylogenetic model selection; speciation.] PMID:27037081

Vehicle lift-off modelling and a new rollover detection criterion

NASA Astrophysics Data System (ADS)

Mashadi, Behrooz; Mostaghimi, Hamid

2017-05-01

The modelling and development of a general criterion for the prediction of rollover threshold is the main purpose of this work. Vehicle dynamics models after the wheels lift-off and when the vehicle moves on the two wheels are derived and the governing equations are used to develop the rollover threshold. These models include the properties of the suspension and steering systems. In order to study the stability of motion, the steady-state solutions of the equations of motion are carried out. Based on the stability analyses, a new relation is obtained for the rollover threshold in terms of measurable response parameters. The presented criterion predicts the best time for the prevention of the vehicle rollover by applying a correcting moment. It is shown that the introduced threshold of vehicle rollover is a proper state of vehicle motion that is best for stabilising the vehicle with a low energy requirement.

Prediction of the Dynamic Yield Strength of Metals Using Two Structural-Temporal Parameters

NASA Astrophysics Data System (ADS)

Selyutina, N. S.; Petrov, Yu. V.

2018-02-01

The behavior of the yield strength of steel and a number of aluminum alloys is investigated in a wide range of strain rates, based on the incubation time criterion of yield and the empirical models of Johnson-Cook and Cowper-Symonds. In this paper, expressions for the parameters of the empirical models are derived through the characteristics of the incubation time criterion; a satisfactory agreement of these data and experimental results is obtained. The parameters of the empirical models can depend on some strain rate. The independence of the characteristics of the incubation time criterion of yield from the loading history and their connection with the structural and temporal features of the plastic deformation process give advantage of the approach based on the concept of incubation time with respect to empirical models and an effective and convenient equation for determining the yield strength in a wider range of strain rates.

48 CFR 36.602-1 - Selection criteria.

Code of Federal Regulations, 2011 CFR

2011-10-01

...; provided, that application of this criterion leaves an appropriate number of qualified firms, given the...) Unique situations exist involving prestige projects, such as the design of memorials and structures of...

48 CFR 36.602-1 - Selection criteria.

Code of Federal Regulations, 2013 CFR

2013-10-01

...; provided, that application of this criterion leaves an appropriate number of qualified firms, given the...) Unique situations exist involving prestige projects, such as the design of memorials and structures of...

48 CFR 36.602-1 - Selection criteria.

Code of Federal Regulations, 2012 CFR

2012-10-01

...; provided, that application of this criterion leaves an appropriate number of qualified firms, given the...) Unique situations exist involving prestige projects, such as the design of memorials and structures of...

48 CFR 36.602-1 - Selection criteria.

Code of Federal Regulations, 2014 CFR

2014-10-01

...; provided, that application of this criterion leaves an appropriate number of qualified firms, given the...) Unique situations exist involving prestige projects, such as the design of memorials and structures of...

Application of color mixing for safety and quality inspection of agricultural products

NASA Astrophysics Data System (ADS)

Ding, Fujian; Chen, Yud-Ren; Chao, Kuanglin

2005-11-01

In this paper, color-mixing applications for food safety and quality was studied, including two-color mixing and three-color mixing. It was shown that the chromaticness of the visual signal resulting from two- or three-color mixing is directly related to the band ratio of light intensity at the two or three selected wavebands. An optical visual device using color mixing to implement the band ratio criterion was presented. Inspection through human vision assisted by an optical device that implements the band ratio criterion would offer flexibility and significant cost savings as compared to inspection with a multispectral machine vision system that implements the same criterion. Example applications of this optical color mixing technique were given for the inspection of chicken carcasses with various diseases and for the detection of chilling injury in cucumbers. Simulation results showed that discrimination by chromaticness that has a direct relation with band ratio can work very well with proper selection of the two or three narrow wavebands. This novel color mixing technique for visual inspection can be implemented on visual devices for a variety of applications, ranging from target detection to food safety inspection.

An Efficiency Balanced Information Criterion for Item Selection in Computerized Adaptive Testing

ERIC Educational Resources Information Center

Han, Kyung T.

2012-01-01

Successful administration of computerized adaptive testing (CAT) programs in educational settings requires that test security and item exposure control issues be taken seriously. Developing an item selection algorithm that strikes the right balance between test precision and level of item pool utilization is the key to successful implementation…

Calculus: Readings from the "Mathematics Teacher."

ERIC Educational Resources Information Center

Grinstein, Louise S., Ed.; Michaels, Brenda, Ed.

Many of the suggestions that calculus instructors have published as articles from 1908 through 1973 are included in this book of readings. The main criterion for selecting an item was whether it would be helpful to teachers and students; therefore, those which dealt exclusively with curricular structure were not included. The selected articles are…

Can local adaptation research in plants inform selection of native plant materials? An analysis of experimental methodologies

USDA-ARS?s Scientific Manuscript database

Local adaptation research in plants: limitations to synthetic understanding Local adaptation is used as a criterion to select plant materials that will display high fitness in new environments. A large body of research has explored local adaptation in plants, however, to what extent findings can inf...

Teaching Viewed through Student Performance and Selected Effectiveness Factors.

ERIC Educational Resources Information Center

Papandreou, Andreas P.

The degree of influence of selected factors upon effective teaching is investigated, as perceived by students through the criterion of their academic performance. A 2-part questionnaire was developed and presented to 528 graduating high school students in Cyprus in 1994-95. Part 1 consisted of four questions on student gender, academic…

34 CFR 388.20 - What additional selection criterion is used under this program?

Code of Federal Regulations, 2013 CFR

2013-07-01

... State unit in-service training plan responds to needs identified in their training needs assessment and... employment outcomes; and (iv) The State has conducted a needs assessment of the in-service training needs for... Secretary uses the following additional selection criteria to evaluate an application: (a) Evidence of need...

34 CFR 388.20 - What additional selection criterion is used under this program?

Code of Federal Regulations, 2011 CFR

2011-07-01

... State unit in-service training plan responds to needs identified in their training needs assessment and... employment outcomes; and (iv) The State has conducted a needs assessment of the in-service training needs for... Secretary uses the following additional selection criteria to evaluate an application: (a) Evidence of need...

34 CFR 388.20 - What additional selection criterion is used under this program?

Code of Federal Regulations, 2014 CFR

2014-07-01

... State unit in-service training plan responds to needs identified in their training needs assessment and... employment outcomes; and (iv) The State has conducted a needs assessment of the in-service training needs for... Secretary uses the following additional selection criteria to evaluate an application: (a) Evidence of need...

34 CFR 388.20 - What additional selection criterion is used under this program?

Code of Federal Regulations, 2010 CFR

2010-07-01

... State unit in-service training plan responds to needs identified in their training needs assessment and... employment outcomes; and (iv) The State has conducted a needs assessment of the in-service training needs for... Secretary uses the following additional selection criteria to evaluate an application: (a) Evidence of need...

34 CFR 388.20 - What additional selection criterion is used under this program?

Code of Federal Regulations, 2012 CFR

2012-07-01

... State unit in-service training plan responds to needs identified in their training needs assessment and... employment outcomes; and (iv) The State has conducted a needs assessment of the in-service training needs for... Secretary uses the following additional selection criteria to evaluate an application: (a) Evidence of need...

Assessment of Pathological Traits in DSM-5 Personality Disorders by the DAPP-BQ: How Do These Traits Relate to the Six Personality Disorder Types of the Alternative Model?

PubMed

Berghuis, Han; Ingenhoven, Theo J M; van der Heijden, Paul T; Rossi, Gina M P; Schotte, Chris K W

2017-11-09

The six personality disorder (PD) types in DSM-5 section III are intended to resemble their DSM-IV/DSM-5 section II PD counterparts, but are now described by the level of personality functioning (criterion A) and an assigned trait profile (criterion B). However, concerns have been raised about the validity of these PD types. The present study examined the continuity between the DSM-IV/DSM-5 section II PDs and the corresponding trait profiles of the six DSM-5 section III PDs in a sample of 350 Dutch psychiatric patients. Facets of the Dimensional Assessment of Personality Pathology-Basic Questionnaire (DAPP-BQ) were presumed as representations (proxies) of the DSM-5 section III traits. Correlational patterns between the DAPP-BQ and the six PDs were consistent with previous research between DAPP-BQ and DSM-IV PDs. Moreover, DAPP-BQ proxies were able to predict the six selected PDs. However, the assigned trait profile for each PD didn't fully match the corresponding PD.

Finite Element Vibration Modeling and Experimental Validation for an Aircraft Engine Casing

NASA Astrophysics Data System (ADS)

Rabbitt, Christopher

This thesis presents a procedure for the development and validation of a theoretical vibration model, applies this procedure to a pair of aircraft engine casings, and compares select parameters from experimental testing of those casings to those from a theoretical model using the Modal Assurance Criterion (MAC) and linear regression coefficients. A novel method of determining the optimal MAC between axisymmetric results is developed and employed. It is concluded that the dynamic finite element models developed as part of this research are fully capable of modelling the modal parameters within the frequency range of interest. Confidence intervals calculated in this research for correlation coefficients provide important information regarding the reliability of predictions, and it is recommended that these intervals be calculated for all comparable coefficients. The procedure outlined for aligning mode shapes around an axis of symmetry proved useful, and the results are promising for the development of further optimization techniques.

The Effects of Georgia's Choice Curricular Reform Model on Third Grade Science Scores on the Georgia Criterion Referenced Competency Test

ERIC Educational Resources Information Center

Phemister, Art W.

2010-01-01

The purpose of this study was to evaluate the effectiveness of the Georgia's Choice reading curriculum on third grade science scores on the Georgia Criterion Referenced Competency Test from 2002 to 2008. In assessing the effectiveness of the Georgia's Choice curriculum model this causal comparative study examined the 105 elementary schools that…

Modeling of cw OIL energy performance based on similarity criteria

NASA Astrophysics Data System (ADS)

Mezhenin, Andrey V.; Pichugin, Sergey Y.; Azyazov, Valeriy N.

2012-01-01

A simplified two-level generation model predicts that power extraction from an cw oxygen-iodine laser (OIL) with stable resonator depends on three similarity criteria. Criterion τd is the ratio of the residence time of active medium in the resonator to the O2(1Δ) reduction time at the infinitely large intraresonator intensity. Criterion Π is small-signal gain to the threshold ratio. Criterion Λ is the relaxation to excitation rate ratio for the electronically excited iodine atoms I(2P1/2). Effective power extraction from a cw OIL is achieved when the values of the similarity criteria are located in the intervals: τd=5-8, Π=3-8 and Λ<=0.01.

Dimensionality of Hallucinogen and Inhalant/Solvent Abuse and Dependence Criteria: Implications for the Diagnostic and Statistical Manual of Mental Disorders – Fifth Edition

PubMed Central

Kerridge, Bradley T.; Saha, Tulshi D.; Smith, Sharon; Chou, Patricia S.; Pickering, Roger P.; Huang, Boji; Ruan, June W.; Pulay, Attila J.

2012-01-01

Background Prior research has demonstrated the dimensionality of Diagnostic and Statistical Manual of Mental Disorders - Fourth Edition (DSM-IV) alcohol, nicotine, cannabis, cocaine and amphetamine abuse and dependence criteria. The purpose of this study was to examine the dimensionality of hallucinogen and inhalant/solvent abuse and dependence criteria. In addition, we assessed the impact of elimination of the legal problems abuse criterion on the information value of the aggregate abuse and dependence criteria, another proposed change for DSM- IV currently lacking empirical justification. Methods Factor analyses and item response theory (IRT) analyses were used to explore the unidimisionality and psychometric properties of hallucinogen and inhalant/solvent abuse and dependence criteria using a large representative sample of the United States (U.S.) general population. Results Hallucinogen and inhalant/solvent abuse and dependence criteria formed unidimensional latent traits. For both substances, IRT models without the legal problems abuse criterion demonstrated better fit than the corresponding model with the legal problem abuse criterion. Further, there were no differences in the information value of the IRT models with and without the legal problems abuse criterion, supporting the elimination of that criterion. No bias in the new diagnoses was observed by sex, age and race-ethnicity. Conclusion Consistent with findings for alcohol, nicotine, cannabis, cocaine and amphetamine abuse and dependence criteria, hallucinogen and inhalant/solvent criteria reflect underlying dimensions of severity. The legal problems criterion associated with each of these substance use disorders can be eliminated with no loss in informational value and an advantage of parsimony. Taken together, these findings support the changes to substance use disorder diagnoses recommended by the DSM-V Substance and Related Disorders Workgroup, that is, combining DSM-IV abuse and dependence criteria and eliminating the legal problems abuse criterion. PMID:21621334

Dimensionality of hallucinogen and inhalant/solvent abuse and dependence criteria: implications for the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition.

PubMed

Kerridge, Bradley T; Saha, Tulshi D; Smith, Sharon; Chou, Patricia S; Pickering, Roger P; Huang, Boji; Ruan, June W; Pulay, Attila J

2011-09-01

Prior research has demonstrated the dimensionality of Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition (DSM-IV) alcohol, nicotine, cannabis, cocaine and amphetamine abuse and dependence criteria. The purpose of this study was to examine the dimensionality of hallucinogen and inhalant/solvent abuse and dependence criteria. In addition, we assessed the impact of elimination of the legal problems abuse criterion on the information value of the aggregate abuse and dependence criteria, another proposed change for DSM-IV currently lacking empirical justification. Factor analyses and item response theory (IRT) analyses were used to explore the unidimisionality and psychometric properties of hallucinogen and inhalant/solvent abuse and dependence criteria using a large representative sample of the United States (U.S.) general population. Hallucinogen and inhalant/solvent abuse and dependence criteria formed unidimensional latent traits. For both substances, IRT models without the legal problems abuse criterion demonstrated better fit than the corresponding model with the legal problem abuse criterion. Further, there were no differences in the information value of the IRT models with and without the legal problems abuse criterion, supporting the elimination of that criterion. No bias in the new diagnoses was observed by sex, age and race-ethnicity. Consistent with findings for alcohol, nicotine, cannabis, cocaine and amphetamine abuse and dependence criteria, hallucinogen and inhalant/solvent criteria reflect underlying dimensions of severity. The legal problems criterion associated with each of these substance use disorders can be eliminated with no loss in informational value and an advantage of parsimony. Taken together, these findings support the changes to substance use disorder diagnoses recommended by the DSM-V Substance and Related Disorders Workgroup, that is, combining DSM-IV abuse and dependence criteria and eliminating the legal problems abuse criterion. Published by Elsevier Ltd.

Universal first-order reliability concept applied to semistatic structures

NASA Technical Reports Server (NTRS)

Verderaime, V.

1994-01-01

A reliability design concept was developed for semistatic structures which combines the prevailing deterministic method with the first-order reliability method. The proposed method surmounts deterministic deficiencies in providing uniformly reliable structures and improved safety audits. It supports risk analyses and reliability selection criterion. The method provides a reliability design factor derived from the reliability criterion which is analogous to the current safety factor for sizing structures and verifying reliability response. The universal first-order reliability method should also be applicable for air and surface vehicles semistatic structures.

An orbital localization criterion based on the theory of "fuzzy" atoms.

PubMed

Alcoba, Diego R; Lain, Luis; Torre, Alicia; Bochicchio, Roberto C

2006-04-15

This work proposes a new procedure for localizing molecular and natural orbitals. The localization criterion presented here is based on the partitioning of the overlap matrix into atomic contributions within the theory of "fuzzy" atoms. Our approach has several advantages over other schemes: it is computationally inexpensive, preserves the sigma/pi-separability in planar systems and provides a straightforward interpretation of the resulting orbitals in terms of their localization indices and atomic occupancies. The corresponding algorithm has been implemented and its efficiency tested on selected molecular systems. (c) 2006 Wiley Periodicals, Inc.

Universal first-order reliability concept applied to semistatic structures

NASA Astrophysics Data System (ADS)

Verderaime, V.

1994-07-01

A reliability design concept was developed for semistatic structures which combines the prevailing deterministic method with the first-order reliability method. The proposed method surmounts deterministic deficiencies in providing uniformly reliable structures and improved safety audits. It supports risk analyses and reliability selection criterion. The method provides a reliability design factor derived from the reliability criterion which is analogous to the current safety factor for sizing structures and verifying reliability response. The universal first-order reliability method should also be applicable for air and surface vehicles semistatic structures.

Water-sediment controversy in setting environmental standards for selenium

USGS Publications Warehouse

Hamilton, Steven J.; Lemly, A. Dennis

1999-01-01

A substantial amount of laboratory and field research on selenium effects to biota has been accomplished since the national water quality criterion was published for selenium in 1987. Many articles have documented adverse effects on biota at concentrations below the current chronic criterion of 5 μg/L. This commentary will present information to support a national water quality criterion for selenium of 2 μg/L, based on a wide array of support from federal, state, university, and international sources. Recently, two articles have argued for a sediment-based criterion and presented a model for deriving site-specific criteria. In one example, they calculate a criterion of 31 μg/L for a stream with a low sediment selenium toxicity threshold and low site-specific sediment total organic carbon content, which is substantially higher than the national criterion of 5 μg/L. Their basic premise for proposing a sediment-based method has been critically reviewed and problems in their approach are discussed.

Optimal assignment of workers to supporting services in a hospital

NASA Astrophysics Data System (ADS)

Sawik, Bartosz; Mikulik, Jerzy

2008-01-01

Supporting services play an important role in health care institutions such as hospitals. This paper presents an application of operations research model for optimal allocation of workers among supporting services in a public hospital. The services include logistics, inventory management, financial management, operations management, medical analysis, etc. The optimality criterion of the problem is to minimize operations costs of supporting services subject to some specific constraints. The constraints represent specific conditions for resource allocation in a hospital. The overall problem is formulated as an integer program in the literature known as the assignment problem, where the decision variables represent the assignment of people to various jobs. The results of some computational experiments modeled on a real data from a selected Polish hospital are reported.

Microgravity Investigation of Capillary Driven Imbibition

NASA Astrophysics Data System (ADS)

Dushin, V. R.; Nikitin, V. F.; Smirnov, N. N.; Skryleva, E. I.; Tyurenkova, V. V.

2018-05-01

The goal of the present paper is to investigate the capillary driven filtration in porous media under microgravity conditions. New mathematical model that allows taking into account the blurring of the front due to the instability of the displacement that is developing at the front is proposed. The constants in the mathematical model were selected on the basis of the experimental data on imbibition into unsaturated porous media under microgravity conditions. The flow under the action of a combination of capillary forces and a constant pressure drop or a constant flux is considered. The effect of capillary forces and the type of wettability of the medium on the displacement process is studied. A criterion in which case the capillary effects are insignificant and can be neglected is established.

Thermal Signature Identification System (TheSIS)

NASA Technical Reports Server (NTRS)

Merritt, Scott; Bean, Brian

2015-01-01

We characterize both nonlinear and high order linear responses of fiber-optic and optoelectronic components using spread spectrum temperature cycling methods. This Thermal Signature Identification System (TheSIS) provides much more detail than conventional narrowband or quasi-static temperature profiling methods. This detail allows us to match components more thoroughly, detect subtle reversible shifts in performance, and investigate the cause of instabilities or irreversible changes. In particular, we create parameterized models of athermal fiber Bragg gratings (FBGs), delay line interferometers (DLIs), and distributed feedback (DFB) lasers, then subject the alternative models to selection via the Akaike Information Criterion (AIC). Detailed pairing of components, e.g. FBGs, is accomplished by means of weighted distance metrics or norms, rather than on the basis of a single parameter, such as center wavelength.

Fruit Phenolic Profiling: A New Selection Criterion in Olive Breeding Programs

PubMed Central

Pérez, Ana G.; León, Lorenzo; Sanz, Carlos; de la Rosa, Raúl

2018-01-01

Olive growing is mainly based on traditional varieties selected by the growers across the centuries. The few attempts so far reported to obtain new varieties by systematic breeding have been mainly focused on improving the olive adaptation to different growing systems, the productivity and the oil content. However, the improvement of oil quality has rarely been considered as selection criterion and only in the latter stages of the breeding programs. Due to their health promoting and organoleptic properties, phenolic compounds are one of the most important quality markers for Virgin olive oil (VOO) although they are not commonly used as quality traits in olive breeding programs. This is mainly due to the difficulties for evaluating oil phenolic composition in large number of samples and the limited knowledge on the genetic and environmental factors that may influence phenolic composition. In the present work, we propose a high throughput methodology to include the phenolic composition as a selection criterion in olive breeding programs. For that purpose, the phenolic profile has been determined in fruits and oils of several breeding selections and two varieties (“Picual” and “Arbequina”) used as control. The effect of three different environments, typical for olive growing in Andalusia, Southern Spain, was also evaluated. A high genetic effect was observed on both fruit and oil phenolic profile. In particular, the breeding selection UCI2-68 showed an optimum phenolic profile, which sums up to a good agronomic performance previously reported. A high correlation was found between fruit and oil total phenolic content as well as some individual phenols from the two different matrices. The environmental effect on phenolic compounds was also significant in both fruit and oil, although the low genotype × environment interaction allowed similar ranking of genotypes on the different environments. In summary, the high genotypic variance and the simplified procedure of the proposed methodology for fruit phenol evaluation seems to be convenient for breeding programs aiming at obtaining new cultivars with improved phenolic profile. PMID:29535752

Fruit Phenolic Profiling: A New Selection Criterion in Olive Breeding Programs.

PubMed

Pérez, Ana G; León, Lorenzo; Sanz, Carlos; de la Rosa, Raúl

2018-01-01

Olive growing is mainly based on traditional varieties selected by the growers across the centuries. The few attempts so far reported to obtain new varieties by systematic breeding have been mainly focused on improving the olive adaptation to different growing systems, the productivity and the oil content. However, the improvement of oil quality has rarely been considered as selection criterion and only in the latter stages of the breeding programs. Due to their health promoting and organoleptic properties, phenolic compounds are one of the most important quality markers for Virgin olive oil (VOO) although they are not commonly used as quality traits in olive breeding programs. This is mainly due to the difficulties for evaluating oil phenolic composition in large number of samples and the limited knowledge on the genetic and environmental factors that may influence phenolic composition. In the present work, we propose a high throughput methodology to include the phenolic composition as a selection criterion in olive breeding programs. For that purpose, the phenolic profile has been determined in fruits and oils of several breeding selections and two varieties ("Picual" and "Arbequina") used as control. The effect of three different environments, typical for olive growing in Andalusia, Southern Spain, was also evaluated. A high genetic effect was observed on both fruit and oil phenolic profile. In particular, the breeding selection UCI2-68 showed an optimum phenolic profile, which sums up to a good agronomic performance previously reported. A high correlation was found between fruit and oil total phenolic content as well as some individual phenols from the two different matrices. The environmental effect on phenolic compounds was also significant in both fruit and oil, although the low genotype × environment interaction allowed similar ranking of genotypes on the different environments. In summary, the high genotypic variance and the simplified procedure of the proposed methodology for fruit phenol evaluation seems to be convenient for breeding programs aiming at obtaining new cultivars with improved phenolic profile.

Time series models for prediction the total and dissolved heavy metals concentration in road runoff and soil solution of roadside embankments

NASA Astrophysics Data System (ADS)

Aljoumani, Basem; Kluge, Björn; sanchez, Josep; Wessolek, Gerd

2017-04-01

Highways and main roads are potential sources of contamination for the surrounding environment. High traffic rates result in elevated heavy metal concentrations in road runoff, soil and water seepage, which has attracted much attention in the recent past. Prediction of heavy metals transfer near the roadside into deeper soil layers are very important to prevent the groundwater pollution. This study was carried out on data of a number of lysimeters which were installed along the A115 highway (Germany) with a mean daily traffic of 90.000 vehicles per day. Three polyethylene (PE) lysimeters were installed at the A115 highway. They have the following dimensions: length 150 cm, width 100 cm, height 60 cm. The lysimeters were filled with different soil materials, which were recently used for embankment construction in Germany. With the obtained data, we will develop a time series analysis model to predict total and dissolved metal concentration in road runoff and in soil solution of the roadside embankments. The time series consisted of monthly measurements of heavy metals and was transformed to a stationary situation. Subsequently, the transformed data will be used to conduct analyses in the time domain in order to obtain the parameters of a seasonal autoregressive integrated moving average (ARIMA) model. Four phase approaches for identifying and fitting ARIMA models will be used: identification, parameter estimation, diagnostic checking, and forecasting. An automatic selection criterion, such as the Akaike information criterion, will use to enhance this flexible approach to model building

Relating DSM-5 section III personality traits to section II personality disorder diagnoses.

PubMed

Morey, L C; Benson, K T; Skodol, A E

2016-02-01

The DSM-5 Personality and Personality Disorders Work Group formulated a hybrid dimensional/categorical model that represented personality disorders as combinations of core impairments in personality functioning with specific configurations of problematic personality traits. Specific clusters of traits were selected to serve as indicators for six DSM categorical diagnoses to be retained in this system - antisocial, avoidant, borderline, narcissistic, obsessive-compulsive and schizotypal personality disorders. The goal of the current study was to describe the empirical relationships between the DSM-5 section III pathological traits and DSM-IV/DSM-5 section II personality disorder diagnoses. Data were obtained from a sample of 337 clinicians, each of whom rated one of his or her patients on all aspects of the DSM-IV and DSM-5 proposed alternative model. Regression models were constructed to examine trait-disorder relationships, and the incremental validity of core personality dysfunctions (i.e. criterion A features for each disorder) was examined in combination with the specified trait clusters. Findings suggested that the trait assignments specified by the Work Group tended to be substantially associated with corresponding DSM-IV concepts, and the criterion A features provided additional diagnostic information in all but one instance. Although the DSM-5 section III alternative model provided a substantially different taxonomic structure for personality disorders, the associations between this new approach and the traditional personality disorder concepts in DSM-5 section II make it possible to render traditional personality disorder concepts using alternative model traits in combination with core impairments in personality functioning.

Selecting AGN through Variability in SN Datasets

NASA Astrophysics Data System (ADS)

Boutsia, K.; Leibundgut, B.; Trevese, D.; Vagnetti, F.

2010-07-01

Variability is a main property of Active Galactic Nuclei (AGN) and it was adopted as a selection criterion using multi epoch surveys conducted for the detection of supernovae (SNe). We have used two SN datasets. First we selected the AXAF field of the STRESS project, centered in the Chandra Deep Field South where, besides the deep X-ray surveys also various optical catalogs exist. Our method yielded 132 variable AGN candidates. We then extended our method including the dataset of the ESSENCE project that has been active for 6 years, producing high quality light curves in the R and I bands. We obtained a sample of ˜4800 variable sources, down to R=22, in the whole 12 deg2 ESSENCE field. Among them, a subsample of ˜500 high priority AGN candidates was created using as secondary criterion the shape of the structure function. In a pilot spectroscopic run we have confirmed the AGN nature for nearly all of our candidates.

Why noise is useful in functional and neural mechanisms of interval timing?

PubMed Central

2013-01-01

Background The ability to estimate durations in the seconds-to-minutes range - interval timing - is essential for survival, adaptation and its impairment leads to severe cognitive and/or motor dysfunctions. The response rate near a memorized duration has a Gaussian shape centered on the to-be-timed interval (criterion time). The width of the Gaussian-like distribution of responses increases linearly with the criterion time, i.e., interval timing obeys the scalar property. Results We presented analytical and numerical results based on the striatal beat frequency (SBF) model showing that parameter variability (noise) mimics behavioral data. A key functional block of the SBF model is the set of oscillators that provide the time base for the entire timing network. The implementation of the oscillators block as simplified phase (cosine) oscillators has the additional advantage that is analytically tractable. We also checked numerically that the scalar property emerges in the presence of memory variability by using biophysically realistic Morris-Lecar oscillators. First, we predicted analytically and tested numerically that in a noise-free SBF model the output function could be approximated by a Gaussian. However, in a noise-free SBF model the width of the Gaussian envelope is independent of the criterion time, which violates the scalar property. We showed analytically and verified numerically that small fluctuations of the memorized criterion time leads to scalar property of interval timing. Conclusions Noise is ubiquitous in the form of small fluctuations of intrinsic frequencies of the neural oscillators, the errors in recording/retrieving stored information related to criterion time, fluctuation in neurotransmitters’ concentration, etc. Our model suggests that the biological noise plays an essential functional role in the SBF interval timing. PMID:23924391

AMD-stability in the presence of first-order mean motion resonances

NASA Astrophysics Data System (ADS)

Petit, A. C.; Laskar, J.; Boué, G.

2017-11-01

The angular momentum deficit (AMD)-stability criterion allows to discriminate between a priori stable planetary systems and systems for which the stability is not granted and needs further investigations. AMD-stability is based on the conservation of the AMD in the averaged system at all orders of averaging. While the AMD criterion is rigorous, the conservation of the AMD is only granted in absence of mean-motion resonances (MMR). Here we extend the AMD-stability criterion to take into account mean-motion resonances, and more specifically the overlap of first-order MMR. If the MMR islands overlap, the system will experience generalized chaos leading to instability. The Hamiltonian of two massive planets on coplanar quasi-circular orbits can be reduced to an integrable one degree of freedom problem for period ratios close to a first-order MMR. We use the reduced Hamiltonian to derive a new overlap criterion for first-order MMR. This stability criterion unifies the previous criteria proposed in the literature and admits the criteria obtained for initially circular and eccentric orbits as limit cases. We then improve the definition of AMD-stability to take into account the short term chaos generated by MMR overlap. We analyze the outcome of this improved definition of AMD-stability on selected multi-planet systems from the Extrasolar Planets Encyclopædia.

Is First-Order Vector Autoregressive Model Optimal for fMRI Data?

PubMed

Ting, Chee-Ming; Seghouane, Abd-Krim; Khalid, Muhammad Usman; Salleh, Sh-Hussain

2015-09-01

We consider the problem of selecting the optimal orders of vector autoregressive (VAR) models for fMRI data. Many previous studies used model order of one and ignored that it may vary considerably across data sets depending on different data dimensions, subjects, tasks, and experimental designs. In addition, the classical information criteria (IC) used (e.g., the Akaike IC (AIC)) are biased and inappropriate for the high-dimensional fMRI data typically with a small sample size. We examine the mixed results on the optimal VAR orders for fMRI, especially the validity of the order-one hypothesis, by a comprehensive evaluation using different model selection criteria over three typical data types--a resting state, an event-related design, and a block design data set--with varying time series dimensions obtained from distinct functional brain networks. We use a more balanced criterion, Kullback's IC (KIC) based on Kullback's symmetric divergence combining two directed divergences. We also consider the bias-corrected versions (AICc and KICc) to improve VAR model selection in small samples. Simulation results show better small-sample selection performance of the proposed criteria over the classical ones. Both bias-corrected ICs provide more accurate and consistent model order choices than their biased counterparts, which suffer from overfitting, with KICc performing the best. Results on real data show that orders greater than one were selected by all criteria across all data sets for the small to moderate dimensions, particularly from small, specific networks such as the resting-state default mode network and the task-related motor networks, whereas low orders close to one but not necessarily one were chosen for the large dimensions of full-brain networks.

Forecasting mortality of road traffic injuries in China using seasonal autoregressive integrated moving average model.

PubMed

Zhang, Xujun; Pang, Yuanyuan; Cui, Mengjing; Stallones, Lorann; Xiang, Huiyun

2015-02-01

Road traffic injuries have become a major public health problem in China. This study aimed to develop statistical models for predicting road traffic deaths and to analyze seasonality of deaths in China. A seasonal autoregressive integrated moving average (SARIMA) model was used to fit the data from 2000 to 2011. Akaike Information Criterion, Bayesian Information Criterion, and mean absolute percentage error were used to evaluate the constructed models. Autocorrelation function and partial autocorrelation function of residuals and Ljung-Box test were used to compare the goodness-of-fit between the different models. The SARIMA model was used to forecast monthly road traffic deaths in 2012. The seasonal pattern of road traffic mortality data was statistically significant in China. SARIMA (1, 1, 1) (0, 1, 1)12 model was the best fitting model among various candidate models; the Akaike Information Criterion, Bayesian Information Criterion, and mean absolute percentage error were -483.679, -475.053, and 4.937, respectively. Goodness-of-fit testing showed nonautocorrelations in the residuals of the model (Ljung-Box test, Q = 4.86, P = .993). The fitted deaths using the SARIMA (1, 1, 1) (0, 1, 1)12 model for years 2000 to 2011 closely followed the observed number of road traffic deaths for the same years. The predicted and observed deaths were also very close for 2012. This study suggests that accurate forecasting of road traffic death incidence is possible using SARIMA model. The SARIMA model applied to historical road traffic deaths data could provide important evidence of burden of road traffic injuries in China. Copyright © 2015 Elsevier Inc. All rights reserved.

Assessment and Selection of Competing Models for Zero-Inflated Microbiome Data

PubMed Central

Xu, Lizhen; Paterson, Andrew D.; Turpin, Williams; Xu, Wei

2015-01-01

Typical data in a microbiome study consist of the operational taxonomic unit (OTU) counts that have the characteristic of excess zeros, which are often ignored by investigators. In this paper, we compare the performance of different competing methods to model data with zero inflated features through extensive simulations and application to a microbiome study. These methods include standard parametric and non-parametric models, hurdle models, and zero inflated models. We examine varying degrees of zero inflation, with or without dispersion in the count component, as well as different magnitude and direction of the covariate effect on structural zeros and the count components. We focus on the assessment of type I error, power to detect the overall covariate effect, measures of model fit, and bias and effectiveness of parameter estimations. We also evaluate the abilities of model selection strategies using Akaike information criterion (AIC) or Vuong test to identify the correct model. The simulation studies show that hurdle and zero inflated models have well controlled type I errors, higher power, better goodness of fit measures, and are more accurate and efficient in the parameter estimation. Besides that, the hurdle models have similar goodness of fit and parameter estimation for the count component as their corresponding zero inflated models. However, the estimation and interpretation of the parameters for the zero components differs, and hurdle models are more stable when structural zeros are absent. We then discuss the model selection strategy for zero inflated data and implement it in a gut microbiome study of > 400 independent subjects. PMID:26148172

Assessment and Selection of Competing Models for Zero-Inflated Microbiome Data.

PubMed

Xu, Lizhen; Paterson, Andrew D; Turpin, Williams; Xu, Wei

2015-01-01

Typical data in a microbiome study consist of the operational taxonomic unit (OTU) counts that have the characteristic of excess zeros, which are often ignored by investigators. In this paper, we compare the performance of different competing methods to model data with zero inflated features through extensive simulations and application to a microbiome study. These methods include standard parametric and non-parametric models, hurdle models, and zero inflated models. We examine varying degrees of zero inflation, with or without dispersion in the count component, as well as different magnitude and direction of the covariate effect on structural zeros and the count components. We focus on the assessment of type I error, power to detect the overall covariate effect, measures of model fit, and bias and effectiveness of parameter estimations. We also evaluate the abilities of model selection strategies using Akaike information criterion (AIC) or Vuong test to identify the correct model. The simulation studies show that hurdle and zero inflated models have well controlled type I errors, higher power, better goodness of fit measures, and are more accurate and efficient in the parameter estimation. Besides that, the hurdle models have similar goodness of fit and parameter estimation for the count component as their corresponding zero inflated models. However, the estimation and interpretation of the parameters for the zero components differs, and hurdle models are more stable when structural zeros are absent. We then discuss the model selection strategy for zero inflated data and implement it in a gut microbiome study of > 400 independent subjects.

Modeling of weak blast wave propagation in the lung.

PubMed

D'yachenko, A I; Manyuhina, O V

2006-01-01

Blast injuries of the lung are the most life-threatening after an explosion. The choice of physical parameters responsible for trauma is important to understand its mechanism. We developed a one-dimensional linear model of an elastic wave propagation in foam-like pulmonary parenchyma to identify the possible cause of edema due to the impact load. The model demonstrates different injury localizations for free and rigid boundary conditions. The following parameters were considered: strain, velocity, pressure in the medium and stresses in structural elements, energy dissipation, parameter of viscous criterion. Maximum underpressure is the most suitable wave parameter to be the criterion for edema formation in a rabbit lung. We supposed that observed scattering of experimental data on edema severity is induced by the physiological variety of rabbit lungs. The criterion and the model explain this scattering. The model outlines the demands for experimental data to make an unambiguous choice of physical parameters responsible for lung trauma due to impact load.

Socio-economic status and problem alcohol use: the positive relationship between income and the DSM-IV alcohol abuse diagnosis.

PubMed

Keyes, Katherine M; Hasin, Deborah S

2008-07-01

Epidemiological evidence indicates a positive relationship between income and the prevalence of alcohol abuse in the general population, but an inverse relationship between income and alcohol dependence. Among those with a diagnosis of alcohol abuse, the most prevalent criterion is hazardous use, which commonly requires sufficient resources to own or access a car. The present study investigated whether the association between income and the prevalence of current alcohol abuse is accounted for by the hazardous use criterion; specifically, the drinking and driving symptoms of the hazardous use criterion. Face-to-face survey conducted in the 2001-02 National Epidemiologic Survey on Alcohol and Related Conditions, interviewed with the Alcohol Use Disorders and Associated Disabilities Interview 4th edition (AUDADIS-IV). The United States and District of Columbia, including Alaska and Hawaii. Household and group-quarters residents aged >18 years. Life-time dependence cases were excluded (n = 4781). Income was defined as past-year personal income. Outcomes were specific alcohol abuse criteria and symptom questions. Logistic regressions were performed controlling for demographics. The relationship between alcohol abuse severity indicators and income was modeled using polytomous regression. Findings Among the alcohol abuse criteria, hazardous use is the most prevalent and the only criterion to have a significant positive relationship with income (F = 20.3, df = 3, P < 0.0001). Among the hazardous use symptoms, driving after drinking (F = 13.0, df = 3, P < 0.0001) and driving while drinking (F = 9.2, df = 3, P < 0.0001) were related positively to income. Because hazardous use is the most commonly endorsed criterion of alcohol abuse, the link with income raises questions about whether the current alcohol abuse diagnosis can capture the full range of alcohol abusers in every socio-economic class. While many psychiatric disorders exhibit an inverse relationship with socio-economic status, a selection bias may cause the alcohol abuse diagnosis to have an artificially positive relationship with income due to the necessity for access to a vehicle to be diagnosed.

A two-phased fuzzy decision making procedure for IT supplier selection

NASA Astrophysics Data System (ADS)

Shohaimay, Fairuz; Ramli, Nazirah; Mohamed, Siti Rosiah; Mohd, Ainun Hafizah

2013-09-01

In many studies on fuzzy decision making, linguistic terms are usually represented by corresponding fixed triangular or trapezoidal fuzzy numbers. However, the fixed fuzzy numbers used in decision making process may not explain the actual respondents' opinions. Hence, a two-phased fuzzy decision making procedure is proposed. First, triangular fuzzy numbers were built based on respondents' opinions on the appropriate range (0-100) for each seven-scale linguistic terms. Then, the fuzzy numbers were integrated into fuzzy decision making model. The applicability of the proposed method is demonstrated in a case study of supplier selection in Information Technology (IT) department. The results produced via the developed fuzzy numbers were consistent with the results obtained using fixed fuzzy numbers. However, with different set of fuzzy numbers based on respondents, there is a difference in the ranking of suppliers based on criterion X1 (background of supplier). Hopefully the proposed model which incorporates fuzzy numbers based on respondents will provide a more significant meaning towards future decision making.

A Critical Evaluation of Waste Incineration Plants in Wuhan (China) Based on Site Selection, Environmental Influence, Public Health and Public Participation

PubMed Central

Hu, Hui; Li, Xiang; Nguyen, Anh Dung; Kavan, Philip

2015-01-01

With the rapid development of the waste incineration industry in China, top priority has been given to the problem of pollution caused by waste incineration. This study is the first attempt to assess all the waste incineration plants in Wuhan, the only national key city in central China, in terms of environmental impact, site selection, public health and public participation. By using a multi-criterion assessment model for economic, social, public health and environmental effects, this study indicates these incineration plants are established without much consideration of the local residents’ health and environment. A location analysis is also applied and some influences of waste incineration plants are illustrated. This study further introduces a signaling game model to prove that public participation is a necessary condition for improving the environmental impact assessment and increasing total welfare of different interest groups in China. This study finally offers some corresponding recommendations for improving the environmental impact assessments of waste incineration projects. PMID:26184242

A Critical Evaluation of Waste Incineration Plants in Wuhan (China) Based on Site Selection, Environmental Influence, Public Health and Public Participation.

PubMed

Hu, Hui; Li, Xiang; Nguyen, Anh Dung; Kavan, Philip

2015-07-08

With the rapid development of the waste incineration industry in China, top priority has been given to the problem of pollution caused by waste incineration. This study is the first attempt to assess all the waste incineration plants in Wuhan, the only national key city in central China, in terms of environmental impact, site selection, public health and public participation. By using a multi-criterion assessment model for economic, social, public health and environmental effects, this study indicates these incineration plants are established without much consideration of the local residents' health and environment. A location analysis is also applied and some influences of waste incineration plants are illustrated. This study further introduces a signaling game model to prove that public participation is a necessary condition for improving the environmental impact assessment and increasing total welfare of different interest groups in China. This study finally offers some corresponding recommendations for improving the environmental impact assessments of waste incineration projects.

Numerical validation of selected computer programs in nonlinear analysis of steel frame exposed to fire

NASA Astrophysics Data System (ADS)

Maślak, Mariusz; Pazdanowski, Michał; Woźniczka, Piotr

2018-01-01

Validation of fire resistance for the same steel frame bearing structure is performed here using three different numerical models, i.e. a bar one prepared in the SAFIR environment, and two 3D models developed within the framework of Autodesk Simulation Mechanical (ASM) and an alternative one developed in the environment of the Abaqus code. The results of the computer simulations performed are compared with the experimental results obtained previously, in a laboratory fire test, on a structure having the same characteristics and subjected to the same heating regimen. Comparison of the experimental and numerically determined displacement evolution paths for selected nodes of the considered frame during the simulated fire exposure constitutes the basic criterion applied to evaluate the validity of the numerical results obtained. The experimental and numerically determined estimates of critical temperature specific to the considered frame and related to the limit state of bearing capacity in fire have been verified as well.

Time Series Analysis and Forecasting of Wastewater Inflow into Bandar Tun Razak Sewage Treatment Plant in Selangor, Malaysia

NASA Astrophysics Data System (ADS)

Abunama, Taher; Othman, Faridah

2017-06-01

Analysing the fluctuations of wastewater inflow rates in sewage treatment plants (STPs) is essential to guarantee a sufficient treatment of wastewater before discharging it to the environment. The main objectives of this study are to statistically analyze and forecast the wastewater inflow rates into the Bandar Tun Razak STP in Kuala Lumpur, Malaysia. A time series analysis of three years’ weekly influent data (156weeks) has been conducted using the Auto-Regressive Integrated Moving Average (ARIMA) model. Various combinations of ARIMA orders (p, d, q) have been tried to select the most fitted model, which was utilized to forecast the wastewater inflow rates. The linear regression analysis was applied to testify the correlation between the observed and predicted influents. ARIMA (3, 1, 3) model was selected with the highest significance R-square and lowest normalized Bayesian Information Criterion (BIC) value, and accordingly the wastewater inflow rates were forecasted to additional 52weeks. The linear regression analysis between the observed and predicted values of the wastewater inflow rates showed a positive linear correlation with a coefficient of 0.831.

A multiloop generalization of the circle criterion for stability margin analysis

NASA Technical Reports Server (NTRS)

Safonov, M. G.; Athans, M.

1979-01-01

In order to provide a theoretical tool suited for characterizing the stability margins of multiloop feedback systems, multiloop input-output stability results generalizing the circle stability criterion are considered. Generalized conic sectors with 'centers' and 'radii' determined by linear dynamical operators are employed to specify the stability margins as a frequency dependent convex set of modeling errors (including nonlinearities, gain variations and phase variations) which the system must be able to tolerate in each feedback loop without instability. The resulting stability criterion gives sufficient conditions for closed loop stability in the presence of frequency dependent modeling errors, even when the modeling errors occur simultaneously in all loops. The stability conditions yield an easily interpreted scalar measure of the amount by which a multiloop system exceeds, or falls short of, its stability margin specifications.

36 CFR 18.7 - How are lease proposals solicited and selected if the Director issues a Request for Bids?

Code of Federal Regulations, 2010 CFR

2010-07-01

... solicited and selected if the Director issues a Request for Bids? 18.7 Section 18.7 Parks, Forests, and... § 18.7 How are lease proposals solicited and selected if the Director issues a Request for Bids? (a) If the amount of the rent is the only criterion for award of a lease, the Director may solicit bids...

MID-INFRARED SELECTION OF ACTIVE GALACTIC NUCLEI WITH THE WIDE-FIELD INFRARED SURVEY EXPLORER. I. CHARACTERIZING WISE-SELECTED ACTIVE GALACTIC NUCLEI IN COSMOS

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

Stern, Daniel; Assef, Roberto J.; Eisenhardt, Peter

2012-07-01

The Wide-field Infrared Survey Explorer (WISE) is an extremely capable and efficient black hole finder. We present a simple mid-infrared color criterion, W1 - W2 {>=} 0.8 (i.e., [3.4]-[4.6] {>=}0.8, Vega), which identifies 61.9 {+-} 5.4 active galactic nucleus (AGN) candidates per deg{sup 2} to a depth of W2 {approx} 15.0. This implies a much larger census of luminous AGNs than found by typical wide-area surveys, attributable to the fact that mid-infrared selection identifies both unobscured (type 1) and obscured (type 2) AGNs. Optical and soft X-ray surveys alone are highly biased toward only unobscured AGNs, while this simple WISEmore » selection likely identifies even heavily obscured, Compton-thick AGNs. Using deep, public data in the COSMOS field, we explore the properties of WISE-selected AGN candidates. At the mid-infrared depth considered, 160 {mu}Jy at 4.6 {mu}m, this simple criterion identifies 78% of Spitzer mid-infrared AGN candidates according to the criteria of Stern et al. and the reliability is 95%. We explore the demographics, multiwavelength properties and redshift distribution of WISE-selected AGN candidates in the COSMOS field.« less

When is hub gene selection better than standard meta-analysis?

PubMed

Langfelder, Peter; Mischel, Paul S; Horvath, Steve

2013-01-01

Since hub nodes have been found to play important roles in many networks, highly connected hub genes are expected to play an important role in biology as well. However, the empirical evidence remains ambiguous. An open question is whether (or when) hub gene selection leads to more meaningful gene lists than a standard statistical analysis based on significance testing when analyzing genomic data sets (e.g., gene expression or DNA methylation data). Here we address this question for the special case when multiple genomic data sets are available. This is of great practical importance since for many research questions multiple data sets are publicly available. In this case, the data analyst can decide between a standard statistical approach (e.g., based on meta-analysis) and a co-expression network analysis approach that selects intramodular hubs in consensus modules. We assess the performance of these two types of approaches according to two criteria. The first criterion evaluates the biological insights gained and is relevant in basic research. The second criterion evaluates the validation success (reproducibility) in independent data sets and often applies in clinical diagnostic or prognostic applications. We compare meta-analysis with consensus network analysis based on weighted correlation network analysis (WGCNA) in three comprehensive and unbiased empirical studies: (1) Finding genes predictive of lung cancer survival, (2) finding methylation markers related to age, and (3) finding mouse genes related to total cholesterol. The results demonstrate that intramodular hub gene status with respect to consensus modules is more useful than a meta-analysis p-value when identifying biologically meaningful gene lists (reflecting criterion 1). However, standard meta-analysis methods perform as good as (if not better than) a consensus network approach in terms of validation success (criterion 2). The article also reports a comparison of meta-analysis techniques applied to gene expression data and presents novel R functions for carrying out consensus network analysis, network based screening, and meta analysis.

Construction of Lagrangians and Hamiltonians from the Equation of Motion

ERIC Educational Resources Information Center

Yan, C. C.

1978-01-01

Demonstrates that infinitely many Lagrangians and Hamiltonians can be constructed from a given equation of motion. Points out the lack of an established criterion for making a proper selection. (Author/GA)

Vortex Advisory System Safety Analysis : Volume 1. Analytical Model

DOT National Transportation Integrated Search

1978-09-01

The Vortex Advisory System (VAS) is based on wind criterion--when the wind near the runway end is outside of the criterion, all interarrival Instrument Flight Rules (IFR) aircraft separations can be set at 3 nautical miles. Five years of wind data ha...

Inviscid criterion for decomposing scales

NASA Astrophysics Data System (ADS)

Zhao, Dongxiao; Aluie, Hussein

2018-05-01

The proper scale decomposition in flows with significant density variations is not as straightforward as in incompressible flows, with many possible ways to define a "length scale." A choice can be made according to the so-called inviscid criterion [Aluie, Physica D 24, 54 (2013), 10.1016/j.physd.2012.12.009]. It is a kinematic requirement that a scale decomposition yield negligible viscous effects at large enough length scales. It has been proved [Aluie, Physica D 24, 54 (2013), 10.1016/j.physd.2012.12.009] recently that a Favre decomposition satisfies the inviscid criterion, which is necessary to unravel inertial-range dynamics and the cascade. Here we present numerical demonstrations of those results. We also show that two other commonly used decompositions can violate the inviscid criterion and, therefore, are not suitable to study inertial-range dynamics in variable-density and compressible turbulence. Our results have practical modeling implication in showing that viscous terms in Large Eddy Simulations do not need to be modeled and can be neglected.

Comparison of Nurse Staffing Measurements in Staffing-Outcomes Research.

PubMed

Park, Shin Hye; Blegen, Mary A; Spetz, Joanne; Chapman, Susan A; De Groot, Holly A

2015-01-01

Investigators have used a variety of operational definitions of nursing hours of care in measuring nurse staffing for health services research. However, little is known about which approach is best for nurse staffing measurement. To examine whether various nursing hours measures yield different model estimations when predicting patient outcomes and to determine the best method to measure nurse staffing based on the model estimations. We analyzed data from the University HealthSystem Consortium for 2005. The sample comprised 208 hospital-quarter observations from 54 hospitals, representing information on 971 adult-care units and about 1 million inpatient discharges. We compared regression models using different combinations of staffing measures based on productive/nonproductive and direct-care/indirect-care hours. Akaike Information Criterion and Bayesian Information Criterion were used in the assessment of staffing measure performance. The models that included the staffing measure calculated from productive hours by direct-care providers were best, in general. However, the Akaike Information Criterion and Bayesian Information Criterion differences between models were small, indicating that distinguishing nonproductive and indirect-care hours from productive direct-care hours does not substantially affect the approximation of the relationship between nurse staffing and patient outcomes. This study is the first to explicitly evaluate various measures of nurse staffing. Productive hours by direct-care providers are the strongest measure related to patient outcomes and thus should be preferred in research on nurse staffing and patient outcomes.

A Comparison of Three Approaches to Correct for Direct and Indirect Range Restrictions: A Simulation Study

ERIC Educational Resources Information Center

Pfaffel, Andreas; Schober, Barbara; Spiel, Christiane

2016-01-01

A common methodological problem in the evaluation of the predictive validity of selection methods, e.g. in educational and employment selection, is that the correlation between predictor and criterion is biased. Thorndike's (1949) formulas are commonly used to correct for this biased correlation. An alternative approach is to view the selection…

Diameter Growth of Selected Bottomland Hardwoods as Affected by Species and Site

Treesearch

Charles B. Briscoe

1955-01-01

As management is intensified in bottomland forests, efforts will be made to control species composition. One criterion for the selection of species to favor is growth rate, about which relatively little is known for bottomland species. This study was made to compare the relative growth rates of certain bottomland hardwood species in southern Louisiana.

Optimizing the Use of Response Times for Item Selection in Computerized Adaptive Testing

ERIC Educational Resources Information Center

Choe, Edison M.; Kern, Justin L.; Chang, Hua-Hua

2018-01-01

Despite common operationalization, measurement efficiency of computerized adaptive testing should not only be assessed in terms of the number of items administered but also the time it takes to complete the test. To this end, a recent study introduced a novel item selection criterion that maximizes Fisher information per unit of expected response…

Constructing exact perturbations of the standard cosmological models

NASA Astrophysics Data System (ADS)

Sopuerta, Carlos F.

1999-11-01

In this paper we show a procedure to construct cosmological models which, according to a covariant criterion, can be seen as exact (nonlinear) perturbations of the standard Friedmann-Lemaı⁁tre-Robertson-Walker (FLRW) cosmological models. The special properties of this procedure will allow us to select some of the characteristics of the models and also to study in depth their main geometrical and physical features. In particular, the models are conformally stationary, which means that they are compatible with the existence of isotropic radiation, and the observers that would measure this isotropy are rotating. Moreover, these models have two arbitrary functions (one of them is a complex function) which control their main properties, and in general they do not have any isometry. We study two examples, focusing on the case when the underlying FLRW models are flat dust models. In these examples we compare our results with those of the linearized theory of perturbations about a FLRW background.

Turbulence Model Selection for Low Reynolds Number Flows

PubMed Central

2016-01-01

One of the major flow phenomena associated with low Reynolds number flow is the formation of separation bubbles on an airfoil’s surface. NACA4415 airfoil is commonly used in wind turbines and UAV applications. The stall characteristics are gradual compared to thin airfoils. The primary criterion set for this work is the capture of laminar separation bubble. Flow is simulated for a Reynolds number of 120,000. The numerical analysis carried out shows the advantages and disadvantages of a few turbulence models. The turbulence models tested were: one equation Spallart Allmars (S-A), two equation SST K-ω, three equation Intermittency (γ) SST, k-kl-ω and finally, the four equation transition γ-Reθ SST. However, the variation in flow physics differs between these turbulence models. Procedure to establish the accuracy of the simulation, in accord with previous experimental results, has been discussed in detail. PMID:27104354

Turbulence Model Selection for Low Reynolds Number Flows.

PubMed

Aftab, S M A; Mohd Rafie, A S; Razak, N A; Ahmad, K A

2016-01-01

One of the major flow phenomena associated with low Reynolds number flow is the formation of separation bubbles on an airfoil's surface. NACA4415 airfoil is commonly used in wind turbines and UAV applications. The stall characteristics are gradual compared to thin airfoils. The primary criterion set for this work is the capture of laminar separation bubble. Flow is simulated for a Reynolds number of 120,000. The numerical analysis carried out shows the advantages and disadvantages of a few turbulence models. The turbulence models tested were: one equation Spallart Allmars (S-A), two equation SST K-ω, three equation Intermittency (γ) SST, k-kl-ω and finally, the four equation transition γ-Reθ SST. However, the variation in flow physics differs between these turbulence models. Procedure to establish the accuracy of the simulation, in accord with previous experimental results, has been discussed in detail.

Analysis of Composite Panel-Stiffener Debonding Using a Shell/3D Modeling Technique

NASA Technical Reports Server (NTRS)

Krueger, Ronald; Minguet, Pierre J.

2006-01-01

Interlaminar fracture mechanics has proven useful for characterizing the onset of delaminations in composites and has been used with limited success primarily to investigate onset in fracture toughness specimens and laboratory size coupon type specimens. Future acceptance of the methodology by industry and certification authorities however, requires the successful demonstration of the methodology on structural level. For this purpose a panel was selected that was reinforced with stringers. Shear loading cases the panel to buckle and the resulting out-of-plane deformations initiate skin/stringer separation at the location of an embedded defect. For finite element analysis, the panel and surrounding load fixture were modeled with shell element. A small section of the stringer foot and the panel in the vicinity of the embedded defect were modeled with a local 3D solid model. A failure index was calculated by correlating computed mixed-mode failure criterion of the graphite/epoxy material.

Locomotor activity, core body temperature, and circadian rhythms in mice selected for high or low heat loss.

PubMed

Mousel, M R; Stroup, W W; Nielsen, M K

2001-04-01

Daily locomotor activity, core body temperature, and their circadian rhythms were measured in lines of mice selected for high (MH) or low (ML) heat loss and unselected controls (MC). Lines were created by selecting for 16 generations in each of three replicates. Collection of locomotor activity and core temperature data spanned Generations 20 and 21 for a total of 352 mice. Physical activity and core body temperature data were accumulated using implanted transmitters and continuous automated collection. Measurement for each animal was for 3 d. Activity was recorded for each half hour and then averaged for the day; temperature was averaged daily; circadian rhythm was expressed in 12-h (light vs dark) or 6-h periods as well as by fitting cyclic models. Activity means were transformed to log base 2 to lessen heterogeneity of variance within lines. Heat loss for a 15-h period beginning at 1630 and feed intake for 7 d were measured on 74 additional mice in order to estimate the relationship between locomotor activity and heat loss or feed intake. Selection lines were different (P < 0.01) for both locomotor activity and core body temperature. Differences were due to selection (MH-ML, P < 0.01), and there was no evidence of asymmetry of response (P > 0.38). Retransformed from log base 2 to the scale of measurement, mean activity counts were 308, 210, and 150 for MH, MC, and ML, respectively. Mean core temperatures were 37.2, 36.9, and 36.7 degrees C for MH, MC, and ML (P < 0.01), respectively. Females had greater physical activity (P < 0.01) and body temperature (P < 0.01) than males. There was no evidence of a sex x selection criterion interaction for either activity or temperature (P > 0.20). Overall phenotypic correlation between body temperature and log base 2 activity was 0.43 (P < 0.01). Periods during the day were different for both 12- and 6-h analyses (P < 0.01), but there were no period x selection criterion interactions (P > 0.1) for physical activity or body temperature. More sensitive cyclic models revealed significant (P < 0.01) 24-, 12-, 8-, and 6-h cycles that differed (P < 0.01) among lines. Estimated differences between MH and ML mice in feed intake and heat loss due to locomotor activity were 36 and 11.5%, respectively. Variation in activity thus contributed to variation in feed intake.

Assessment of NDE Reliability Data

NASA Technical Reports Server (NTRS)

Yee, B. G. W.; Chang, F. H.; Couchman, J. C.; Lemon, G. H.; Packman, P. F.

1976-01-01

Twenty sets of relevant Nondestructive Evaluation (NDE) reliability data have been identified, collected, compiled, and categorized. A criterion for the selection of data for statistical analysis considerations has been formulated. A model to grade the quality and validity of the data sets has been developed. Data input formats, which record the pertinent parameters of the defect/specimen and inspection procedures, have been formulated for each NDE method. A comprehensive computer program has been written to calculate the probability of flaw detection at several confidence levels by the binomial distribution. This program also selects the desired data sets for pooling and tests the statistical pooling criteria before calculating the composite detection reliability. Probability of detection curves at 95 and 50 percent confidence levels have been plotted for individual sets of relevant data as well as for several sets of merged data with common sets of NDE parameters.

Modeling of direct wafer bonding: Effect of wafer bow and etch patterns

NASA Astrophysics Data System (ADS)

Turner, K. T.; Spearing, S. M.

2002-12-01

Direct wafer bonding is an important technology for the manufacture of silicon-on-insulator substrates and microelectromechanical systems. As devices become more complex and require the bonding of multiple patterned wafers, there is a need to understand the mechanics of the bonding process. A general bonding criterion based on the competition between the strain energy accumulated in the wafers and the surface energy that is dissipated as the bond front advances is developed. The bonding criterion is used to examine the case of bonding bowed wafers. An analytical expression for the strain energy accumulation rate, which is the quantity that controls bonding, and the final curvature of a bonded stack is developed. It is demonstrated that the thickness of the wafers plays a large role and bonding success is independent of wafer diameter. The analytical results are verified through a finite element model and a general method for implementing the bonding criterion numerically is presented. The bonding criterion developed permits the effect of etched features to be assessed. Shallow etched patterns are shown to make bonding more difficult, while it is demonstrated that deep etched features can facilitate bonding. Model results and their process design implications are discussed in detail.

Dilatancy Criteria for Salt Cavern Design: A Comparison Between Stress- and Strain-Based Approaches

NASA Astrophysics Data System (ADS)

Labaune, P.; Rouabhi, A.; Tijani, M.; Blanco-Martín, L.; You, T.

2018-02-01

This paper presents a new approach for salt cavern design, based on the use of the onset of dilatancy as a design threshold. In the proposed approach, a rheological model that includes dilatancy at the constitutive level is developed, and a strain-based dilatancy criterion is defined. As compared to classical design methods that consist in simulating cavern behavior through creep laws (fitted on long-term tests) and then using a criterion (derived from short-terms tests or experience) to determine the stability of the excavation, the proposed approach is consistent both with short- and long-term conditions. The new strain-based dilatancy criterion is compared to a stress-based dilatancy criterion through numerical simulations of salt caverns under cyclic loading conditions. The dilatancy zones predicted by the strain-based criterion are larger than the ones predicted by the stress-based criteria, which is conservative yet constructive for design purposes.

An advanced constitutive model in the sheet metal forming simulation: the Teodosiu microstructural model and the Cazacu Barlat yield criterion

NASA Astrophysics Data System (ADS)

Alves, J. L.; Oliveira, M. C.; Menezes, L. F.

2004-06-01

Two constitutive models used to describe the plastic behavior of sheet metals in the numerical simulation of sheet metal forming process are studied: a recently proposed advanced constitutive model based on the Teodosiu microstructural model and the Cazacu Barlat yield criterion is compared with a more classical one, based on the Swift law and the Hill 1948 yield criterion. These constitutive models are implemented into DD3IMP, a finite element home code specifically developed to simulate sheet metal forming processes, which generically is a 3-D elastoplastic finite element code with an updated Lagrangian formulation, following a fully implicit time integration scheme, large elastoplastic strains and rotations. Solid finite elements and parametric surfaces are used to model the blank sheet and tool surfaces, respectively. Some details of the numerical implementation of the constitutive models are given. Finally, the theory is illustrated with the numerical simulation of the deep drawing of a cylindrical cup. The results show that the proposed advanced constitutive model predicts with more exactness the final shape (medium height and ears profile) of the formed part, as one can conclude from the comparison with the experimental results.

Role of optimization criterion in static asymmetric analysis of lumbar spine load.

PubMed

Daniel, Matej

2011-10-01

A common method for load estimation in biomechanics is the inverse dynamics optimization, where the muscle activation pattern is found by minimizing or maximizing the optimization criterion. It has been shown that various optimization criteria predict remarkably similar muscle activation pattern and intra-articular contact forces during leg motion. The aim of this paper is to study the effect of the choice of optimization criterion on L4/L5 loading during static asymmetric loading. Upright standing with weight in one stretched arm was taken as a representative position. Musculoskeletal model of lumbar spine model was created from CT images of Visible Human Project. Several criteria were tested based on the minimization of muscle forces, muscle stresses, and spinal load. All criteria provide the same level of lumbar spine loading (difference is below 25%), except the criterion of minimum lumbar shear force which predicts unrealistically high spinal load and should not be considered further. Estimated spinal load and predicted muscle force activation pattern are in accordance with the intradiscal pressure measurements and EMG measurements. The L4/L5 spine loads 1312 N, 1674 N, and 1993 N were predicted for mass of weight in hand 2, 5, and 8 kg, respectively using criterion of mininum muscle stress cubed. As the optimization criteria do not considerably affect the spinal load, their choice is not critical in further clinical or ergonomic studies and computationally simpler criterion can be used.

Dental caries clusters among adolescents.

PubMed

Warren, John J; Van Buren, John M; Levy, Steven M; Marshall, Teresa A; Cavanaugh, Joseph E; Curtis, Alexandra M; Kolker, Justine L; Weber-Gasparoni, Karin

2017-12-01

There have been very few longitudinal studies of dental caries in adolescents, and little study of the caries risk factors in this age group. The purpose of this study was to describe different caries trajectories and associated risk factors among members of the Iowa Fluoride Study (IFS) cohort. The IFS recruited a birth cohort from 1992 to 1995, and has gathered dietary, fluoride and behavioural data at least twice yearly since recruitment. Examinations for dental caries were completed when participants were ages 5, 9, 13 and 17 years. For this study, only participants with decayed and filled surface (DFS) caries data at ages 9, 13 and 17 were included (N=396). The individual DFS counts at age 13 and the DFS increment from 13 to 17 were used to identify distinct caries trajectories using Ward's hierarchical clustering algorithm. A number of multinomial logistic regression models were developed to predict trajectory membership, using longitudinal dietary, fluoride and demographic/behavioural data from 9 to 17 years. Model selection was based on the akaike information criterion (AIC). Several different trajectory schemes were considered, and a three-trajectory scheme-no DFS at age 17 (n=142), low DFS (n=145) and high DFS (n=109)-was chosen to balance sample sizes and interpretability. The model selection process resulted in use of an arithmetic average for dietary variables across the period from 9 to 17 years. The multinomial logistic regression model with the best fit included the variables maternal education level, 100% juice consumption, brushing frequency and sex. Other favoured models also included water and milk consumption and home water fluoride concentration. The high caries cluster was most consistently associated with lower maternal education level, lower 100% juice consumption, lower brushing frequency and being female. The use of a clustering algorithm and use of Akaike's Information Criterion (AIC) to determine the best representation of the data were useful means in presenting longitudinal caries data. Findings suggest that high caries incidence in adolescence is associated with lower maternal educational level, less frequent tooth brushing, lower 100% juice consumption and being female. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A bi-objective model for optimizing replacement time of age and block policies with consideration of spare parts’ availability

NASA Astrophysics Data System (ADS)

Alsyouf, Imad

2018-05-01

Reliability and availability of critical systems play an important role in achieving the stated objectives of engineering assets. Preventive replacement time affects the reliability of the components, thus the number of system failures encountered and its downtime expenses. On the other hand, spare parts inventory level is a very critical factor that affects the availability of the system. Usually, the decision maker has many conflicting objectives that should be considered simultaneously for the selection of the optimal maintenance policy. The purpose of this research was to develop a bi-objective model that will be used to determine the preventive replacement time for three maintenance policies (age, block good as new, block bad as old) with consideration of spare parts’ availability. It was suggested to use a weighted comprehensive criterion method with two objectives, i.e. cost and availability. The model was tested with a typical numerical example. The results of the model demonstrated its effectiveness in enabling the decision maker to select the optimal maintenance policy under different scenarios and taking into account preferences with respect to contradicting objectives such as cost and availability.

Selecting the optimum number of partial least squares components for the calibration of attenuated total reflectance-mid-infrared spectra of undesigned kerosene samples.

PubMed

Gómez-Carracedo, M P; Andrade, J M; Rutledge, D N; Faber, N M

2007-03-07

Selecting the correct dimensionality is critical for obtaining partial least squares (PLS) regression models with good predictive ability. Although calibration and validation sets are best established using experimental designs, industrial laboratories cannot afford such an approach. Typically, samples are collected in an (formally) undesigned way, spread over time and their measurements are included in routine measurement processes. This makes it hard to evaluate PLS model dimensionality. In this paper, classical criteria (leave-one-out cross-validation and adjusted Wold's criterion) are compared to recently proposed alternatives (smoothed PLS-PoLiSh and a randomization test) to seek out the optimum dimensionality of PLS models. Kerosene (jet fuel) samples were measured by attenuated total reflectance-mid-IR spectrometry and their spectra where used to predict eight important properties determined using reference methods that are time-consuming and prone to analytical errors. The alternative methods were shown to give reliable dimensionality predictions when compared to external validation. By contrast, the simpler methods seemed to be largely affected by the largest changes in the modeling capabilities of the first components.

Variable Selection with Prior Information for Generalized Linear Models via the Prior LASSO Method.

PubMed

Jiang, Yuan; He, Yunxiao; Zhang, Heping

LASSO is a popular statistical tool often used in conjunction with generalized linear models that can simultaneously select variables and estimate parameters. When there are many variables of interest, as in current biological and biomedical studies, the power of LASSO can be limited. Fortunately, so much biological and biomedical data have been collected and they may contain useful information about the importance of certain variables. This paper proposes an extension of LASSO, namely, prior LASSO (pLASSO), to incorporate that prior information into penalized generalized linear models. The goal is achieved by adding in the LASSO criterion function an additional measure of the discrepancy between the prior information and the model. For linear regression, the whole solution path of the pLASSO estimator can be found with a procedure similar to the Least Angle Regression (LARS). Asymptotic theories and simulation results show that pLASSO provides significant improvement over LASSO when the prior information is relatively accurate. When the prior information is less reliable, pLASSO shows great robustness to the misspecification. We illustrate the application of pLASSO using a real data set from a genome-wide association study.

Technical Guidance for Conducting ASVAB Validation/Standards Studies in the U.S. Navy

DTIC Science & Technology

2015-02-01

the criterion), we can compute the variance of X in the unrestricted group, 2xS , and in the restricted (selected) group, 2 xs . 3 In contrast, we...well as the selected group, 2 xs . We also know the variance of Y in the selected group, 2ys , and the correlation of X and Y in the selected...and AS. Five levels of selection ratio (1.0, .8, .6, .4, and .2) and eight sample sizes (50, 75, 100, 150, 225, 350 , 500, and 800) were considered

Estimation of submarine mass failure probability from a sequence of deposits with age dates

USGS Publications Warehouse

Geist, Eric L.; Chaytor, Jason D.; Parsons, Thomas E.; ten Brink, Uri S.

2013-01-01

The empirical probability of submarine mass failure is quantified from a sequence of dated mass-transport deposits. Several different techniques are described to estimate the parameters for a suite of candidate probability models. The techniques, previously developed for analyzing paleoseismic data, include maximum likelihood and Type II (Bayesian) maximum likelihood methods derived from renewal process theory and Monte Carlo methods. The estimated mean return time from these methods, unlike estimates from a simple arithmetic mean of the center age dates and standard likelihood methods, includes the effects of age-dating uncertainty and of open time intervals before the first and after the last event. The likelihood techniques are evaluated using Akaike’s Information Criterion (AIC) and Akaike’s Bayesian Information Criterion (ABIC) to select the optimal model. The techniques are applied to mass transport deposits recorded in two Integrated Ocean Drilling Program (IODP) drill sites located in the Ursa Basin, northern Gulf of Mexico. Dates of the deposits were constrained by regional bio- and magnetostratigraphy from a previous study. Results of the analysis indicate that submarine mass failures in this location occur primarily according to a Poisson process in which failures are independent and return times follow an exponential distribution. However, some of the model results suggest that submarine mass failures may occur quasiperiodically at one of the sites (U1324). The suite of techniques described in this study provides quantitative probability estimates of submarine mass failure occurrence, for any number of deposits and age uncertainty distributions.

Clinical and pathological tools for identifying microsatellite instability in colorectal cancer

PubMed Central

Krivokapić, Zoran; Marković, Srdjan; Antić, Jadranka; Dimitrijević, Ivan; Bojić, Daniela; Svorcan, Petar; Jojić, Njegica; Damjanović, Svetozar

2012-01-01

Aim To assess practical accuracy of revised Bethesda criteria (BGrev), pathological predictive model (MsPath), and histopathological parameters for detection of high-frequency of microsatellite instability (MSI-H) phenotype in patients with colorectal carcinoma (CRC). Method Tumors from 150 patients with CRC were analyzed for MSI using a fluorescence-based pentaplex polymerase chain reaction technique. For all patients, we evaluated age, sex, family history of cancer, localization, tumor differentiation, mucin production, lymphocytic infiltration (TIL), and Union for International Cancer Control stage. Patients were classified according to the BGrev, and the groups were compared. The utility of the BGrev, MsPath, and clinical and histopathological parameters for predicting microsatellite tumor status were assessed by univariate logistic regression analysis and by calculating the sensitivity, specificity, and positive (PPV) and negative (NPV) predictive values. Results Fifteen out of 45 patients who met and 4 of 105 patients who did not meet the BGrev criteria had MSI-H CRC. Sensitivity, specificity, PPV, and NPV for BGrev were 78.9%, 77%, 30%, and 70%, respectively. MSI histology (the third BGrev criterion without age limit) was as sensitive as BGrev, but more specific. MsPath model was more sensitive than BGrev (86%), with similar specificity. Any BGrev criterion fulfillment, mucinous differentiation, and right-sided CRC were singled out as independent factors to identify MSI-H colorectal cancer. Conclusion The BGrev, MsPath model, and MSI histology are useful tools for selecting patients for MSI testing. PMID:22911525

Comparison of Linear and Non-linear Regression Analysis to Determine Pulmonary Pressure in Hyperthyroidism.

PubMed

Scarneciu, Camelia C; Sangeorzan, Livia; Rus, Horatiu; Scarneciu, Vlad D; Varciu, Mihai S; Andreescu, Oana; Scarneciu, Ioan

2017-01-01

This study aimed at assessing the incidence of pulmonary hypertension (PH) at newly diagnosed hyperthyroid patients and at finding a simple model showing the complex functional relation between pulmonary hypertension in hyperthyroidism and the factors causing it. The 53 hyperthyroid patients (H-group) were evaluated mainly by using an echocardiographical method and compared with 35 euthyroid (E-group) and 25 healthy people (C-group). In order to identify the factors causing pulmonary hypertension the statistical method of comparing the values of arithmetical means is used. The functional relation between the two random variables (PAPs and each of the factors determining it within our research study) can be expressed by linear or non-linear function. By applying the linear regression method described by a first-degree equation the line of regression (linear model) has been determined; by applying the non-linear regression method described by a second degree equation, a parabola-type curve of regression (non-linear or polynomial model) has been determined. We made the comparison and the validation of these two models by calculating the determination coefficient (criterion 1), the comparison of residuals (criterion 2), application of AIC criterion (criterion 3) and use of F-test (criterion 4). From the H-group, 47% have pulmonary hypertension completely reversible when obtaining euthyroidism. The factors causing pulmonary hypertension were identified: previously known- level of free thyroxin, pulmonary vascular resistance, cardiac output; new factors identified in this study- pretreatment period, age, systolic blood pressure. According to the four criteria and to the clinical judgment, we consider that the polynomial model (graphically parabola- type) is better than the linear one. The better model showing the functional relation between the pulmonary hypertension in hyperthyroidism and the factors identified in this study is given by a polynomial equation of second degree where the parabola is its graphical representation.

A study of finite mixture model: Bayesian approach on financial time series data

NASA Astrophysics Data System (ADS)

Phoong, Seuk-Yen; Ismail, Mohd Tahir

2014-07-01

Recently, statistician have emphasized on the fitting finite mixture model by using Bayesian method. Finite mixture model is a mixture of distributions in modeling a statistical distribution meanwhile Bayesian method is a statistical method that use to fit the mixture model. Bayesian method is being used widely because it has asymptotic properties which provide remarkable result. In addition, Bayesian method also shows consistency characteristic which means the parameter estimates are close to the predictive distributions. In the present paper, the number of components for mixture model is studied by using Bayesian Information Criterion. Identify the number of component is important because it may lead to an invalid result. Later, the Bayesian method is utilized to fit the k-component mixture model in order to explore the relationship between rubber price and stock market price for Malaysia, Thailand, Philippines and Indonesia. Lastly, the results showed that there is a negative effect among rubber price and stock market price for all selected countries.

Improving the Selection, Classification, and Utilization of Army Enlisted Personnel: Technical Appendix to the Annual Report

DTIC Science & Technology

1983-10-01

03.1 I20 -06 -20 -26 79.0 SfC sic SCaflayepm VS -09 -27 33 -13 -23 -16 .14 3 .ŝ of 2 2? 09 40-40 .09 -17 -28 .00 .10 -it .’ -20 72 073 040.Uu.s jsos...difference between the chi-squares for these *two models (pattern invariance vs . loading invariance) was computed to be 63.83 with 30 degrees of freedom...paragraphs in order to master or pass the objective or to receive a "GO." Typical criterion-referenced scores are number of objectives A" passed, GO vs . NO

Selection criteria for the integrated model of plastic surgery residency.

PubMed

LaGrasso, Jeffrey R; Kennedy, Debbie A; Hoehn, James G; Ashruf, Salmon; Przybyla, Adrian M

2008-03-01

The purpose of this study was to identify those qualities and characteristics of fourth-year medical students applying for the Integrated Model of Plastic Surgery residency training that will make a successful plastic surgery resident. A three-part questionnaire was distributed to the training program directors of the 20 Integrated Model of Plastic Surgery programs accredited by the Residency Review Committee for Plastic Surgery by the Accreditation Council on Graduate Medical Education. The first section focused on 19 objective characteristics that directors use to evaluate applicants (e.g., Alpha Omega Alpha Honor Society membership, United States Medical Licensing Examination scores). The second section consisted of 20 subjective characteristics commonly used to evaluate applicants during the interview process. The third section consisted of reasons why, if any, residents failed to successfully complete the training program. Fifteen of the 20 program directors responded to the questionnaire. The results showed that they considered membership in the Alpha Omega Alpha Honor Society to be the most important objective criterion, followed by publications in peer-reviewed journals and letters of recommendation from plastic surgeons known to the director. Leadership capabilities were considered the most important subjective criterion, followed by maturity and interest in academics. Reasons residents failed to complete the training program included illness or death, academic inadequacies, and family demands. The authors conclude that applicants who have achieved high academic honors and demonstrate leadership ability with interest in academics were viewed most likely to succeed as plastic surgery residents by program directors of Integrated Model of Plastic Surgery residencies.

3DFEMWATER/3DLEWASTE: NUMERICAL CODES FOR DELINEATING WELLHEAD PROTECTION AREAS IN AGRICULTURAL REGIONS BASED ON THE ASSIMILATIVE CAPACITY CRITERION

EPA Science Inventory

Two related numerical codes, 3DFEMWATER and 3DLEWASTE, are presented sed to delineate wellhead protection areas in agricultural regions using the assimilative capacity criterion. DFEMWATER (Three-dimensional Finite Element Model of Water Flow Through Saturated-Unsaturated Media) ...

Aging: Sensitivity versus Criterion in Taste Perception.

ERIC Educational Resources Information Center

Kushnir, T.; Shapira, N.

1983-01-01

Employed the signal-detection paradigm as a model for investigating age-related biological versus cognitive effects on perceptual behavior. Old and young subjects reported the presence or absence of sugar in threshold level solutions and tap water. Older subjects displayed a higher detection threshold and obtained a stricter criterion of decision.…

Toppling Trains.

ERIC Educational Resources Information Center

Parry, Malcolm

1998-01-01

Explains a novel way of approaching centripetal force: theory is used to predict an orbital period at which a toy train will topple from a circular track. The demonstration has elements of prediction (a criterion for a good model) and suspense (a criterion for a good demonstration). The demonstration proved useful in undergraduate physics and…

Discriminant Validity Assessment: Use of Fornell & Larcker criterion versus HTMT Criterion

NASA Astrophysics Data System (ADS)

Hamid, M. R. Ab; Sami, W.; Mohmad Sidek, M. H.

2017-09-01

Assessment of discriminant validity is a must in any research that involves latent variables for the prevention of multicollinearity issues. Fornell and Larcker criterion is the most widely used method for this purpose. However, a new method has emerged for establishing the discriminant validity assessment through heterotrait-monotrait (HTMT) ratio of correlations method. Therefore, this article presents the results of discriminant validity assessment using these methods. Data from previous study was used that involved 429 respondents for empirical validation of value-based excellence model in higher education institutions (HEI) in Malaysia. From the analysis, the convergent, divergent and discriminant validity were established and admissible using Fornell and Larcker criterion. However, the discriminant validity is an issue when employing the HTMT criterion. This shows that the latent variables under study faced the issue of multicollinearity and should be looked into for further details. This also implied that the HTMT criterion is a stringent measure that could detect the possible indiscriminant among the latent variables. In conclusion, the instrument which consisted of six latent variables was still lacking in terms of discriminant validity and should be explored further.

Age-Neutrality of a Brief Assessment of the Section III Alternative Model for Personality Disorders in Older Adults.

PubMed

Debast, Inge; Rossi, Gina; van Alphen, S P J

2018-04-01

The alternative model for personality disorders in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders ( DSM-5) is considered an important step toward a possibly better conceptualization of personality pathology in older adulthood, by the introduction of levels of personality functioning (Criterion A) and trait dimensions (Criterion B). Our main aim was to examine age-neutrality of the Short Form of the Severity Indices of Personality Problems (SIPP-SF; Criterion A) and Personality Inventory for DSM-5-Brief Form (PID-5-BF; Criterion B). Differential item functioning (DIF) analyses and more specifically the impact on scale level through differential test functioning (DTF) analyses made clear that the SIPP-SF was more age-neutral (6% DIF, only one of four domains showed DTF) than the PID-5-BF (25% DIF, all four tested domains had DTF) in a community sample of older and younger adults. Age differences in convergent validity also point in the direction of differences in underlying constructs. Concurrent and criterion validity in geriatric psychiatry inpatients suggest that both the SIPP-SF scales measuring levels of personality functioning (especially self-functioning) and the PID-5-BF might be useful screening measures in older adults despite age-neutrality not being confirmed.

An application of model-fitting procedures for marginal structural models.

PubMed

Mortimer, Kathleen M; Neugebauer, Romain; van der Laan, Mark; Tager, Ira B

2005-08-15

Marginal structural models (MSMs) are being used more frequently to obtain causal effect estimates in observational studies. Although the principal estimator of MSM coefficients has been the inverse probability of treatment weight (IPTW) estimator, there are few published examples that illustrate how to apply IPTW or discuss the impact of model selection on effect estimates. The authors applied IPTW estimation of an MSM to observational data from the Fresno Asthmatic Children's Environment Study (2000-2002) to evaluate the effect of asthma rescue medication use on pulmonary function and compared their results with those obtained through traditional regression methods. Akaike's Information Criterion and cross-validation methods were used to fit the MSM. In this paper, the influence of model selection and evaluation of key assumptions such as the experimental treatment assignment assumption are discussed in detail. Traditional analyses suggested that medication use was not associated with an improvement in pulmonary function--a finding that is counterintuitive and probably due to confounding by symptoms and asthma severity. The final MSM estimated that medication use was causally related to a 7% improvement in pulmonary function. The authors present examples that should encourage investigators who use IPTW estimation to undertake and discuss the impact of model-fitting procedures to justify the choice of the final weights.

Corrections to the Eckhaus' stability criterion for one-dimensional stationary structures

NASA Astrophysics Data System (ADS)

Malomed, B. A.; Staroselsky, I. E.; Konstantinov, A. B.

1989-01-01

Two amendments to the well-known Eckhaus' stability criterion for small-amplitude non-linear structures generated by weak instability of a spatially uniform state of a non-equilibrium one-dimensional system against small perturbations with finite wavelengths are obtained. Firstly, we evaluate small corrections to the main Eckhaus' term which, on the contrary so that term, do not have a universal form. Comparison of those non-universal corrections with experimental or numerical results gives a possibility to select a more relevant form of an effective nonlinear evolution equation. In particular, the comparison with such results for convective rolls and Taylor vortices gives arguments in favor of the Swift-Hohenberg equation. Secondly, we derive an analog of the Eckhaus criterion for systems degenerate in the sense that in an expansion of their non-linear parts in powers of dynamical variables, the second and third degree terms are absent.

A heuristic multi-criteria classification approach incorporating data quality information for choropleth mapping

PubMed Central

Sun, Min; Wong, David; Kronenfeld, Barry

2016-01-01

Despite conceptual and technology advancements in cartography over the decades, choropleth map design and classification fail to address a fundamental issue: estimates that are statistically indifferent may be assigned to different classes on maps or vice versa. Recently, the class separability concept was introduced as a map classification criterion to evaluate the likelihood that estimates in two classes are statistical different. Unfortunately, choropleth maps created according to the separability criterion usually have highly unbalanced classes. To produce reasonably separable but more balanced classes, we propose a heuristic classification approach to consider not just the class separability criterion but also other classification criteria such as evenness and intra-class variability. A geovisual-analytic package was developed to support the heuristic mapping process to evaluate the trade-off between relevant criteria and to select the most preferable classification. Class break values can be adjusted to improve the performance of a classification. PMID:28286426

Correlates of the MMPI-2-RF in a college setting.

PubMed

Forbey, Johnathan D; Lee, Tayla T C; Handel, Richard W

2010-12-01

The current study examined empirical correlates of scores on Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF; A. Tellegen & Y. S. Ben-Porath, 2008; Y. S. Ben-Porath & A. Tellegen, 2008) scales in a college setting. The MMPI-2-RF and six criterion measures (assessing anger, assertiveness, sex roles, cognitive failures, social avoidance, and social fear) were administered to 846 college students (nmen = 264, nwomen = 582) to examine the convergent and discriminant validity of scores on the MMPI-2-RF Specific Problems and Interest scales. Results demonstrated evidence of generally good convergent score validity for the selected MMPI-2-RF scales, reflected in large effect size correlations with criterion measure scores. Further, MMPI-2-RF scale scores demonstrated adequate discriminant validity, reflected in relatively low comparative median correlations between scores on MMPI-2-RF substantive scale sets and criterion measures. Limitations and future directions are discussed.

Older Adults' Online Dating Profiles and Successful Aging.

PubMed

Wada, Mineko; Mortenson, William Bennett; Hurd Clarke, Laura

2016-12-01

This study examined how relevant Rowe and Kahn's three criteria of successful aging were to older adults' self-portrayals in online dating profiles: low probability of disease and disability, high functioning, and active life engagement. In this cross-sectional study, 320 online dating profiles of older adults were randomly selected and coded based on the criteria. Logistic regression analyses determined whether age, gender, and race/ethnicity predicted self-presentation. Few profiles were indicative of successful aging due to the low prevalence of the first two criteria; the third criterion, however, was identified in many profiles. Native Americans were significantly less likely than other ethnic groups to highlight the first two criteria. Younger age predicted presenting the first criterion. Women's presentation of the third criterion remained significantly high with age. The findings suggest that the criteria may be unimportant to older adults when seeking partners, or they may reflect the exclusivity of this construct.

Reproductive medicine: the ethical issues in the twenty-first century.

PubMed

Campbell, Alastair V

2002-02-01

Reproductive medicine has developed to such an extent that numerous moral questions arise about the boundaries of applications of new reproductive technology. It is possible to imagine a future in which 'designer babies' are created and in which cloning, sex selection and male pregnancy become the instruments of individual desire or social policy. In this article, the concept of 'natural' is explored but rejected as an insufficient moral criterion for deciding these complex questions. A case is made for the criterion of welfare of the child and for the concept of the child as gift rather than product.

Nearest neighbor density ratio estimation for large-scale applications in astronomy

NASA Astrophysics Data System (ADS)

Kremer, J.; Gieseke, F.; Steenstrup Pedersen, K.; Igel, C.

2015-09-01

In astronomical applications of machine learning, the distribution of objects used for building a model is often different from the distribution of the objects the model is later applied to. This is known as sample selection bias, which is a major challenge for statistical inference as one can no longer assume that the labeled training data are representative. To address this issue, one can re-weight the labeled training patterns to match the distribution of unlabeled data that are available already in the training phase. There are many examples in practice where this strategy yielded good results, but estimating the weights reliably from a finite sample is challenging. We consider an efficient nearest neighbor density ratio estimator that can exploit large samples to increase the accuracy of the weight estimates. To solve the problem of choosing the right neighborhood size, we propose to use cross-validation on a model selection criterion that is unbiased under covariate shift. The resulting algorithm is our method of choice for density ratio estimation when the feature space dimensionality is small and sample sizes are large. The approach is simple and, because of the model selection, robust. We empirically find that it is on a par with established kernel-based methods on relatively small regression benchmark datasets. However, when applied to large-scale photometric redshift estimation, our approach outperforms the state-of-the-art.

A model of the human supervisor

NASA Technical Reports Server (NTRS)

Kok, J. J.; Vanwijk, R. A.

1977-01-01

A general model of the human supervisor's behavior is given. Submechanisms of the model include: the observer/reconstructor; decision-making; and controller. A set of hypothesis is postulated for the relations between the task variables and the parameters of the different submechanisms of the model. Verification of the model hypotheses is considered using variations in the task variables. An approach is suggested for the identification of the model parameters which makes use of a multidimensional error criterion. Each of the elements of this multidimensional criterion corresponds to a certain aspect of the supervisor's behavior, and is directly related to a particular part of the model and its parameters. This approach offers good possibilities for an efficient parameter adjustment procedure.

A hybrid gene selection approach for microarray data classification using cellular learning automata and ant colony optimization.

PubMed

Vafaee Sharbaf, Fatemeh; Mosafer, Sara; Moattar, Mohammad Hossein

2016-06-01

This paper proposes an approach for gene selection in microarray data. The proposed approach consists of a primary filter approach using Fisher criterion which reduces the initial genes and hence the search space and time complexity. Then, a wrapper approach which is based on cellular learning automata (CLA) optimized with ant colony method (ACO) is used to find the set of features which improve the classification accuracy. CLA is applied due to its capability to learn and model complicated relationships. The selected features from the last phase are evaluated using ROC curve and the most effective while smallest feature subset is determined. The classifiers which are evaluated in the proposed framework are K-nearest neighbor; support vector machine and naïve Bayes. The proposed approach is evaluated on 4 microarray datasets. The evaluations confirm that the proposed approach can find the smallest subset of genes while approaching the maximum accuracy. Copyright © 2016 Elsevier Inc. All rights reserved.

Evolution of Boolean networks under selection for a robust response to external inputs yields an extensive neutral space

NASA Astrophysics Data System (ADS)

Szejka, Agnes; Drossel, Barbara

2010-02-01

We study the evolution of Boolean networks as model systems for gene regulation. Inspired by biological networks, we select simultaneously for robust attractors and for the ability to respond to external inputs by changing the attractor. Mutations change the connections between the nodes and the update functions. In order to investigate the influence of the type of update functions, we perform our simulations with canalizing as well as with threshold functions. We compare the properties of the fitness landscapes that result for different versions of the selection criterion and the update functions. We find that for all studied cases the fitness landscape has a plateau with maximum fitness resulting in the fact that structurally very different networks are able to fulfill the same task and are connected by neutral paths in network (“genotype”) space. We find furthermore a connection between the attractor length and the mutational robustness, and an extremely long memory of the initial evolutionary stage.

Thermo-solutal and kinetic modes of stable dendritic growth with different symmetries of crystalline anisotropy in the presence of convection

NASA Astrophysics Data System (ADS)

Alexandrov, Dmitri V.; Galenko, Peter K.; Toropova, Lyubov V.

2018-01-01

Motivated by important applications in materials science and geophysics, we consider the steady-state growth of anisotropic needle-like dendrites in undercooled binary mixtures with a forced convective flow. We analyse the stable mode of dendritic evolution in the case of small anisotropies of growth kinetics and surface energy for arbitrary Péclet numbers and n-fold symmetry of dendritic crystals. On the basis of solvability and stability theories, we formulate a selection criterion giving a stable combination between dendrite tip diameter and tip velocity. A set of nonlinear equations consisting of the solvability criterion and undercooling balance is solved analytically for the tip velocity V and tip diameter ρ of dendrites with n-fold symmetry in the absence of convective flow. The case of convective heat and mass transfer mechanisms in a binary mixture occurring as a result of intensive flows in the liquid phase is detailed. A selection criterion that describes such solidification conditions is derived. The theory under consideration comprises previously considered theoretical approaches and results as limiting cases. This article is part of the theme issue `From atomistic interfaces to dendritic patterns'. This article is part of the theme issue `From atomistic interfaces to dendritic patterns'.

Three-color mixing for classifying agricultural products for safety and quality

NASA Astrophysics Data System (ADS)

Ding, Fujian; Chen, Yud-Ren; Chao, Kuanglin; Kim, Moon S.

2006-05-01

A three-color mixing application for food safety inspection is presented. It is shown that the chromaticness of the visual signal resulting from the three-color mixing achieved through our device is directly related to the three-band ratio of light intensity at three selected wavebands. An optical visual device using three-color mixing to implement the three-band ratio criterion is presented. Inspection through human vision assisted by an optical device that implements the three-band ratio criterion would offer flexibility and significant cost savings as compared to inspection with a multispectral machine vision system that implements the same criterion. Example applications of this optical three-color mixing technique are given for the inspection of chicken carcasses with various diseases and for apples with fecal contamination. With proper selection of the three narrow wavebands, discrimination by chromaticness that has a direct relation with the three-band ratio can work very well. In particular, compared with the previously presented two-color mixing application, the conditions of chicken carcasses were more easily identified using the three-color mixing application. The novel three-color mixing technique for visual inspection can be implemented on visual devices for a variety of applications, ranging from target detection to food safety inspection.

Learning redundant motor tasks with and without overlapping dimensions: facilitation and interference effects.

PubMed

Ranganathan, Rajiv; Wieser, Jon; Mosier, Kristine M; Mussa-Ivaldi, Ferdinando A; Scheidt, Robert A

2014-06-11

Prior learning of a motor skill creates motor memories that can facilitate or interfere with learning of new, but related, motor skills. One hypothesis of motor learning posits that for a sensorimotor task with redundant degrees of freedom, the nervous system learns the geometric structure of the task and improves performance by selectively operating within that task space. We tested this hypothesis by examining if transfer of learning between two tasks depends on shared dimensionality between their respective task spaces. Human participants wore a data glove and learned to manipulate a computer cursor by moving their fingers. Separate groups of participants learned two tasks: a prior task that was unique to each group and a criterion task that was common to all groups. We manipulated the mapping between finger motions and cursor positions in the prior task to define task spaces that either shared or did not share the task space dimensions (x-y axes) of the criterion task. We found that if the prior task shared task dimensions with the criterion task, there was an initial facilitation in criterion task performance. However, if the prior task did not share task dimensions with the criterion task, there was prolonged interference in learning the criterion task due to participants finding inefficient task solutions. These results show that the nervous system learns the task space through practice, and that the degree of shared task space dimensionality influences the extent to which prior experience transfers to subsequent learning of related motor skills. Copyright © 2014 the authors 0270-6474/14/348289-11$15.00/0.

Is It Reliable to Take the Molecular Docking Top Scoring Position as the Best Solution without Considering Available Structural Data?

PubMed

Ramírez, David; Caballero, Julio

2018-04-28

Molecular docking is the most frequently used computational method for studying the interactions between organic molecules and biological macromolecules. In this context, docking allows predicting the preferred pose of a ligand inside a receptor binding site. However, the selection of the “best” solution is not a trivial task, despite the widely accepted selection criterion that the best pose corresponds to the best energy score. Here, several rigid-target docking methods were evaluated on the same dataset with respect to their ability to reproduce crystallographic binding orientations, to test if the best energy score is a reliable criterion for selecting the best solution. For this, two experiments were performed: (A) to reconstruct the ligand-receptor complex by performing docking of the ligand in its own crystal structure receptor (defined as self-docking), and (B) to reconstruct the ligand-receptor complex by performing docking of the ligand in a crystal structure receptor that contains other ligand (defined as cross-docking). Root-mean square deviation (RMSD) was used to evaluate how different the obtained docking orientation is from the corresponding co-crystallized pose of the same ligand molecule. We found that docking score function is capable of predicting crystallographic binding orientations, but the best ranked solution according to the docking energy is not always the pose that reproduces the experimental binding orientation. This happened when self-docking was achieved, but it was critical in cross-docking. Taking into account that docking is typically used with predictive purposes, during cross-docking experiments, our results indicate that the best energy score is not a reliable criterion to select the best solution in common docking applications. It is strongly recommended to choose the best docking solution according to the scoring function along with additional structural criteria described for analogue ligands to assure the selection of a correct docking solution.

Potential Singularity for a Family of Models of the Axisymmetric Incompressible Flow

NASA Astrophysics Data System (ADS)

Hou, Thomas Y.; Jin, Tianling; Liu, Pengfei

2017-03-01

We study a family of 3D models for the incompressible axisymmetric Euler and Navier-Stokes equations. The models are derived by changing the strength of the convection terms in the equations written using a set of transformed variables. The models share several regularity results with the Euler and Navier-Stokes equations, including an energy identity, the conservation of a modified circulation quantity, the BKM criterion and the Prodi-Serrin criterion. The inviscid models with weak convection are numerically observed to develop stable self-similar singularity with the singular region traveling along the symmetric axis, and such singularity scenario does not seem to persist for strong convection.

Zipper model for the melting of thin films

NASA Astrophysics Data System (ADS)

Abdullah, Mikrajuddin; Khairunnisa, Shafira; Akbar, Fathan

2016-01-01

We propose an alternative model to Lindemann’s criterion for melting that explains the melting of thin films on the basis of a molecular zipper-like mechanism. Using this model, a unique criterion for melting is obtained. We compared the results of the proposed model with experimental data of melting points and heat of fusion for many materials and obtained interesting results. The interesting thing reported here is how complex physics problems can sometimes be modeled with simple objects around us that seemed to have no correlation. This kind of approach is sometimes very important in physics education and should always be taught to undergraduate or graduate students.

Continuous-time safety-first portfolio selection with jump-diffusion processes

NASA Astrophysics Data System (ADS)

Yan, Wei

2012-04-01

This article is concerned with continuous-time portfolio selection based on a safety-first criterion under discontinuous price processes (jump-diffusion processes). The solution of the corresponding Hamilton-Jacobi-Bellman equation of the problem is demonstrated. The analytical solutions are presented when there does not exist any riskless asset. Moreover, the problem is also discussed while there exists one riskless asset.

Portrayal of Life Form in Selected Biographies for Children Eight to Twelve Years of Age.

ERIC Educational Resources Information Center

Koch, Shirley Lois

This study describes and analyzes, in a critical literary manner, selected biographies for children eight to twelve years of age. Biographies of Jane Addams, Cesar Chavez, Mohandas Gandhi, Toyohiko Kagawa, Martin Luther King, Jr., and Albert Schweitzer are viewed from the perspective of a literary criterion based on the principles of design to…

South Carolina Elementary Teachers' Perceptions of Principals' Transformational Leadership in Academically Recognized and Other, High Poverty Schools

ERIC Educational Resources Information Center

Lewis, Julian Carlton

2012-01-01

This study investigated selected elementary school teachers' perceptions of principals' leadership. Ten South Carolina schools were selected based on the criterion of 50% or higher poverty index. Five schools included the feature of recognition by the state for academic success for one year or more over the 2003-2006 timeframe. One hundred three…

The genetic and economic effect of preliminary culling in the seedling orchard

Treesearch

Don E. Riemenschneider

1977-01-01

The genetic and economic effects of two stages of truncation selection in a white spruce seedling orchard were investigated by computer simulation. Genetic effects were computed by assuming a bivariate distribution of juvenile and mature traits and volume was used as the selection criterion. Seed production was assumed to rise in a linear fashion to maturity and then...

Evaluation of a Progressive Failure Analysis Methodology for Laminated Composite Structures

NASA Technical Reports Server (NTRS)

Sleight, David W.; Knight, Norman F., Jr.; Wang, John T.

1997-01-01

A progressive failure analysis methodology has been developed for predicting the nonlinear response and failure of laminated composite structures. The progressive failure analysis uses C plate and shell elements based on classical lamination theory to calculate the in-plane stresses. Several failure criteria, including the maximum strain criterion, Hashin's criterion, and Christensen's criterion, are used to predict the failure mechanisms. The progressive failure analysis model is implemented into a general purpose finite element code and can predict the damage and response of laminated composite structures from initial loading to final failure.

A Novel Non-Invasive Selection Criterion for the Preservation of Primitive Dutch Konik Horses

PubMed Central

May-Davis, Sharon; Shorter, Kathleen; Vermeulen, Zefanja; Butler, Raquel; Koekkoek, Marianne

2018-01-01

The Dutch Konik is valued from a genetic conservation perspective and also for its role in preservation of natural landscapes. The primary management objective for the captive breeding of this primitive horse is to maintain its genetic purity, whilst also maintaining the nature reserves on which they graze. Breeding selection has traditionally been based on phenotypic characteristics consistent with the breed description, and the selection of animals for removal from the breeding program is problematic at times due to high uniformity within the breed, particularly in height at the wither, colour (mouse to grey dun) and presence of primitive markings. With the objective of identifying an additional non-invasive selection criterion with potential uniqueness to the Dutch Konik, this study investigates the anatomic parameters of the distal equine limb, with a specific focus on the relative lengths of the individual splint bones. Post-mortem dissections performed on distal limbs of Dutch Konik (n = 47) and modern domesticated horses (n = 120) revealed significant differences in relation to the length and symmetry of the 2nd and 4th Metacarpals and Metatarsals. Distal limb characteristics with apparent uniqueness to the Dutch Konik are described which could be an important tool in the selection and preservation of the breed. PMID:29389896

A Novel Non-Invasive Selection Criterion for the Preservation of Primitive Dutch Konik Horses.

PubMed

May-Davis, Sharon; Brown, Wendy Y; Shorter, Kathleen; Vermeulen, Zefanja; Butler, Raquel; Koekkoek, Marianne

2018-02-01

The Dutch Konik is valued from a genetic conservation perspective and also for its role in preservation of natural landscapes. The primary management objective for the captive breeding of this primitive horse is to maintain its genetic purity, whilst also maintaining the nature reserves on which they graze. Breeding selection has traditionally been based on phenotypic characteristics consistent with the breed description, and the selection of animals for removal from the breeding program is problematic at times due to high uniformity within the breed, particularly in height at the wither, colour (mouse to grey dun) and presence of primitive markings. With the objective of identifying an additional non-invasive selection criterion with potential uniqueness to the Dutch Konik, this study investigates the anatomic parameters of the distal equine limb, with a specific focus on the relative lengths of the individual splint bones. Post-mortem dissections performed on distal limbs of Dutch Konik ( n = 47) and modern domesticated horses ( n = 120) revealed significant differences in relation to the length and symmetry of the 2nd and 4th Metacarpals and Metatarsals. Distal limb characteristics with apparent uniqueness to the Dutch Konik are described which could be an important tool in the selection and preservation of the breed.

A method for tailoring the information content of a software process model

NASA Technical Reports Server (NTRS)

Perkins, Sharon; Arend, Mark B.

1990-01-01

The framework is defined for a general method for selecting a necessary and sufficient subset of a general software life cycle's information products, to support new software development process. Procedures for characterizing problem domains in general and mapping to a tailored set of life cycle processes and products is presented. An overview of the method is shown using the following steps: (1) During the problem concept definition phase, perform standardized interviews and dialogs between developer and user, and between user and customer; (2) Generate a quality needs profile of the software to be developed, based on information gathered in step 1; (3) Translate the quality needs profile into a profile of quality criteria that must be met by the software to satisfy the quality needs; (4) Map the quality criteria to set of accepted processes and products for achieving each criterion; (5) Select the information products which match or support the accepted processes and product of step 4; and (6) Select the design methodology which produces the information products selected in step 5.

A method for tailoring the information content of a software process model

NASA Technical Reports Server (NTRS)

Perkins, Sharon; Arend, Mark B.

1990-01-01

The framework is defined for a general method for selecting a necessary and sufficient subset of a general software life cycle's information products, to support new software development process. Procedures for characterizing problem domains in general and mapping to a tailored set of life cycle processes and products is presented. An overview of the method is shown using the following steps: (1) During the problem concept definition phase, perform standardized interviews and dialogs between developer and user, and between user and customer; (2) Generate a quality needs profile of the software to be developed, based on information gathered in step 1; (3) Translate the quality needs profile into a profile of quality criteria that must be met by the software to satisfy the quality needs; (4) Map the quality criteria to a set of accepted processes and products for achieving each criterion; (5) select the information products which match or support the accepted processes and product of step 4; and (6) Select the design methodology which produces the information products selected in step 5.

Gravity Field of Venus and Comparison with Earth

NASA Technical Reports Server (NTRS)

Bowin, C.

1985-01-01

The acceleration (gravity) anomaly estimates by spacecraft tracking, determined from Doppler residuals, are components of the gravity field directed along the spacecraft Earth line of sight (LOS). These data constitute a set of vector components of a planet's gravity field, the specific component depending upon where the Earth happened to be at the time of each measurement, and they are at varying altitudes above the planet surface. From this data set the gravity field vector components were derived using the method of harmonic splines which imposes a smoothness criterion to select a gravity model compatible with the LOS data. Given the piecewise model it is now possible to upward and downward continue the field quantities desired with a few parameters unlike some other methods which must return to the full dataset for each desired calculation.

Application of optimal control principles to describe the supervisory control behavior of AAA crew members

NASA Technical Reports Server (NTRS)

Hale, C.; Valentino, G. J.

1982-01-01

Supervisory decision making and control behavior within a C(3) oriented, ground based weapon system is being studied. The program involves empirical investigation of the sequence of control strategies used during engagement of aircraft targets. An engagement is conceptually divided into several stages which include initial information processing activity, tracking, and ongoing adaptive control decisions. Following a brief description of model parameters, two experiments which served as initial investigation into the accuracy of assumptions regarding the importance of situation assessment in procedure selection are outlined. Preliminary analysis of the results upheld the validity of the assumptions regarding strategic information processing and cue-criterion relationship learning. These results indicate that this model structure should be useful in studies of supervisory decision behavior.

47 CFR 73.872 - Selection procedure for mutually exclusive LPFM applications.

Code of Federal Regulations, 2010 CFR

2010-10-01

... locally at least eight hours of programming per day. For purposes of this criterion, local origination is the production of programming, by the licensee, within ten miles of the coordinates of the proposed...

Assessing the Validity of Automated Webcrawlers as Data Collection Tools to Investigate Online Child Sexual Exploitation.

PubMed

Westlake, Bryce; Bouchard, Martin; Frank, Richard

2017-10-01

The distribution of child sexual exploitation (CE) material has been aided by the growth of the Internet. The graphic nature and prevalence of the material has made researching and combating difficult. Although used to study online CE distribution, automated data collection tools (e.g., webcrawlers) have yet to be shown effective at targeting only relevant data. Using CE-related image and keyword criteria, we compare networks starting from CE websites to those from similar non-CE sexuality websites and dissimilar sports websites. Our results provide evidence that (a) webcrawlers have the potential to provide valid CE data, if the appropriate criterion is selected; (b) CE distribution is still heavily image-based suggesting images as an effective criterion; (c) CE-seeded networks are more hub-based and differ from non-CE-seeded networks on several website characteristics. Recommendations for improvements to reliable criteria selection are discussed.

RLS Channel Estimation with Adaptive Forgetting Factor for DS-CDMA Frequency-Domain Equalization

NASA Astrophysics Data System (ADS)

Kojima, Yohei; Tomeba, Hiromichi; Takeda, Kazuaki; Adachi, Fumiyuki

Frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion can increase the downlink bit error rate (BER) performance of DS-CDMA beyond that possible with conventional rake combining in a frequency-selective fading channel. FDE requires accurate channel estimation. Recently, we proposed a pilot-assisted channel estimation (CE) based on the MMSE criterion. Using MMSE-CE, the channel estimation accuracy is almost insensitive to the pilot chip sequence, and a good BER performance is achieved. In this paper, we propose a channel estimation scheme using one-tap recursive least square (RLS) algorithm, where the forgetting factor is adapted to the changing channel condition by the least mean square (LMS)algorithm, for DS-CDMA with FDE. We evaluate the BER performance using RLS-CE with adaptive forgetting factor in a frequency-selective fast Rayleigh fading channel by computer simulation.

GPS baseline configuration design based on robustness analysis

NASA Astrophysics Data System (ADS)

Yetkin, M.; Berber, M.

2012-11-01

The robustness analysis results obtained from a Global Positioning System (GPS) network are dramatically influenced by the configurationof the observed baselines. The selection of optimal GPS baselines may allow for a cost effective survey campaign and a sufficiently robustnetwork. Furthermore, using the approach described in this paper, the required number of sessions, the baselines to be observed, and thesignificance levels for statistical testing and robustness analysis can be determined even before the GPS campaign starts. In this study, wepropose a robustness criterion for the optimal design of geodetic networks, and present a very simple and efficient algorithm based on thiscriterion for the selection of optimal GPS baselines. We also show the relationship between the number of sessions and the non-centralityparameter. Finally, a numerical example is given to verify the efficacy of the proposed approach.

A reliability and mass perspective of SP-100 Stirling cycle lunar-base powerplant designs

NASA Technical Reports Server (NTRS)

Bloomfield, Harvey S.

1991-01-01

The purpose was to obtain reliability and mass perspectives on selection of space power system conceptual designs based on SP-100 reactor and Stirling cycle power-generation subsystems. The approach taken was to: (1) develop a criterion for an acceptable overall reliability risk as a function of the expected range of emerging technology subsystem unit reliabilities; (2) conduct reliability and mass analyses for a diverse matrix of 800-kWe lunar-base design configurations employing single and multiple powerplants with both full and partial subsystem redundancy combinations; and (3) derive reliability and mass perspectives on selection of conceptual design configurations that meet an acceptable reliability criterion with the minimum system mass increase relative to reference powerplant design. The developed perspectives provided valuable insight into the considerations required to identify and characterize high-reliability and low-mass lunar-base powerplant conceptual design.

A non-destructive selection criterion for fibre content in jute : II. Regression approach.

PubMed

Arunachalam, V; Iyer, R D

1974-01-01

An experiment with ten populations of jute, comprising varieties and mutants of the two species Corchorus olitorius and C.capsularis was conducted at two different locations with the object of evolving an effective criterion for selecting superior single plants for fibre yield. At Delhi, variation existed only between varieties as a group and mutants as a group, while at Pusa variation also existed among the mutant populations of C. capsularis.A multiple regression approach was used to find the optimum combination of characters for prediction of fibre yield. A process of successive elimination of characters based on the coefficient of determination provided by individual regression equations was employed to arrive at the optimal set of characters for predicting fibre yield. It was found that plant height, basal and mid-diameters and basal and mid-dry fibre weights would provide such an optimal set.

Building a maintenance policy through a multi-criterion decision-making model

NASA Astrophysics Data System (ADS)

Faghihinia, Elahe; Mollaverdi, Naser

2012-08-01

A major competitive advantage of production and service systems is establishing a proper maintenance policy. Therefore, maintenance managers should make maintenance decisions that best fit their systems. Multi-criterion decision-making methods can take into account a number of aspects associated with the competitiveness factors of a system. This paper presents a multi-criterion decision-aided maintenance model with three criteria that have more influence on decision making: reliability, maintenance cost, and maintenance downtime. The Bayesian approach has been applied to confront maintenance failure data shortage. Therefore, the model seeks to make the best compromise between these three criteria and establish replacement intervals using Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE II), integrating the Bayesian approach with regard to the preference of the decision maker to the problem. Finally, using a numerical application, the model has been illustrated, and for a visual realization and an illustrative sensitivity analysis, PROMETHEE GAIA (the visual interactive module) has been used. Use of PROMETHEE II and PROMETHEE GAIA has been made with Decision Lab software. A sensitivity analysis has been made to verify the robustness of certain parameters of the model.

Experimental Design for Estimating Unknown Hydraulic Conductivity in a Confined Aquifer using a Genetic Algorithm and a Reduced Order Model

NASA Astrophysics Data System (ADS)

Ushijima, T.; Yeh, W.

2013-12-01

An optimal experimental design algorithm is developed to select locations for a network of observation wells that provides the maximum information about unknown hydraulic conductivity in a confined, anisotropic aquifer. The design employs a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. Because that the formulated problem is non-convex and contains integer variables (necessitating a combinatorial search), for a realistically-scaled model, the problem may be difficult, if not impossible, to solve through traditional mathematical programming techniques. Genetic Algorithms (GAs) are designed to search out the global optimum; however because a GA requires a large number of calls to a groundwater model, the formulated optimization problem may still be infeasible to solve. To overcome this, Proper Orthogonal Decomposition (POD) is applied to the groundwater model to reduce its dimension. The information matrix in the full model space can then be searched without solving the full model.

Development of an Empirical Model for Optimization of Machining Parameters to Minimize Power Consumption

NASA Astrophysics Data System (ADS)

Kant Garg, Girish; Garg, Suman; Sangwan, K. S.

2018-04-01

The manufacturing sector consumes huge energy demand and the machine tools used in this sector have very less energy efficiency. Selection of the optimum machining parameters for machine tools is significant for energy saving and for reduction of environmental emission. In this work an empirical model is developed to minimize the power consumption using response surface methodology. The experiments are performed on a lathe machine tool during the turning of AISI 6061 Aluminum with coated tungsten inserts. The relationship between the power consumption and machining parameters is adequately modeled. This model is used for formulation of minimum power consumption criterion as a function of optimal machining parameters using desirability function approach. The influence of machining parameters on the energy consumption has been found using the analysis of variance. The validation of the developed empirical model is proved using the confirmation experiments. The results indicate that the developed model is effective and has potential to be adopted by the industry for minimum power consumption of machine tools.

Galactic conformity measured in semi-analytic models

NASA Astrophysics Data System (ADS)

Lacerna, I.; Contreras, S.; González, R. E.; Padilla, N.; Gonzalez-Perez, V.

2018-03-01

We study the correlation between the specific star formation rate of central galaxies and neighbour galaxies, also known as `galactic conformity', out to 20 h^{-1} {Mpc} using three semi-analytic models (SAMs, one from L-GALAXIES and other two from GALFORM). The aim is to establish whether SAMs are able to show galactic conformity using different models and selection criteria. In all the models, when the selection of primary galaxies is based on an isolation criterion in real space, the mean fraction of quenched (Q) galaxies around Q primary galaxies is higher than that around star-forming primary galaxies of the same stellar mass. The overall signal of conformity decreases when we remove satellites selected as primary galaxies, but the effect is much stronger in GALFORM models compared with the L-GALAXIES model. We find this difference is partially explained by the fact that in GALFORM once a galaxy becomes a satellite remains as such, whereas satellites can become centrals at a later time in L-GALAXIES. The signal of conformity decreases down to 60 per cent in the L-GALAXIES model after removing central galaxies that were ejected from their host halo in the past. Galactic conformity is also influenced by primary galaxies at fixed stellar mass that reside in dark matter haloes of different masses. Finally, we explore a proxy of conformity between distinct haloes. In this case, the conformity is weak beyond ˜3 h^{-1} {Mpc} (<3 per cent in L-GALAXIES, <1-2 per cent in GALFORM models). Therefore, it seems difficult that conformity is directly related with a long-range effect.

[Can Psychometric Tests Predict Success in the Selection Interview for Medical School? A Cross-Sectional Study at One German Medical School].

PubMed

Kötter, T; Obst, K U; Brüheim, L; Eisemann, N; Voltmer, E; Katalinic, A

2017-07-01

Background The final exam grade is the main selection criterion for medical school application in Germany. For academic success, it seems to be a reliable predictor. Its use as the only selection criterion is, however, criticised. At some universities, personal interviews are part of the selection process. However, these are very time consuming and are of doubtful validity. The (additional) use of appropriate psychometric instruments could reduce the cost and increase the validity. This study investigates the extent to which psychometric instruments can predict the outcome of a personal selection interview. Methods This is a cross-sectional study on the correlation of the results of psychometric instruments with those of the personal selection interview as part of the application process. As the outcome, the score of the selection interview was used. The NEO - Five Factor Inventory, the Hospital Anxiety and Depression Scale (HADS) and the questionnaire to identify work-related behaviour and experience patterns (AVEM) were used as psychometric interviews. Results There was a statistically significant correlation with the results of the personal selection interview for the sum score of the depression scale from the HADS and the sum score for the dimension of life satisfaction of the AVEM. In addition, those participants who did not previously complete an application training achieved a better result in the selection interview. Conclusion The instruments used measure different aspects than the interviews and cannot replace them. It remains to be seen whether the selected parameters are able to predict academic success. © Georg Thieme Verlag KG Stuttgart · New York.

Selecting statistical model and optimum maintenance policy: a case study of hydraulic pump.

PubMed

Ruhi, S; Karim, M R

2016-01-01

Proper maintenance policy can play a vital role for effective investigation of product reliability. Every engineered object such as product, plant or infrastructure needs preventive and corrective maintenance. In this paper we look at a real case study. It deals with the maintenance of hydraulic pumps used in excavators by a mining company. We obtain the data that the owner had collected and carry out an analysis and building models for pump failures. The data consist of both failure and censored lifetimes of the hydraulic pump. Different competitive mixture models are applied to analyze a set of maintenance data of a hydraulic pump. Various characteristics of the mixture models, such as the cumulative distribution function, reliability function, mean time to failure, etc. are estimated to assess the reliability of the pump. Akaike Information Criterion, adjusted Anderson-Darling test statistic, Kolmogrov-Smirnov test statistic and root mean square error are considered to select the suitable models among a set of competitive models. The maximum likelihood estimation method via the EM algorithm is applied mainly for estimating the parameters of the models and reliability related quantities. In this study, it is found that a threefold mixture model (Weibull-Normal-Exponential) fits well for the hydraulic pump failures data set. This paper also illustrates how a suitable statistical model can be applied to estimate the optimum maintenance period at a minimum cost of a hydraulic pump.

Interface Pattern Selection Criterion for Cellular Structures in Directional Solidification

NASA Technical Reports Server (NTRS)

Trivedi, R.; Tewari, S. N.; Kurtze, D.

1999-01-01

The aim of this investigation is to establish key scientific concepts that govern the selection of cellular and dendritic patterns during the directional solidification of alloys. We shall first address scientific concepts that are crucial in the selection of interface patterns. Next, the results of ground-based experimental studies in the Al-4.0 wt % Cu system will be described. Both experimental studies and theoretical calculations will be presented to establish the need for microgravity experiments.