Searle, Shayle R
2012-01-01
This 1971 classic on linear models is once again available--as a Wiley Classics Library Edition. It features material that can be understood by any statistician who understands matrix algebra and basic statistical methods.
Castillo, J.A.; Ramirez, J.R.; Alonso, G. [ININ, 52045 Ocoyoacac, Estado de Mexico (Mexico)]. e-mail: jacm@nuclear.inin.mx
2003-07-01
The linear reactivity model allows the multicycle analysis in pressurized water reactors in a simple and quick way. In the case of the Boiling water reactors the void fraction it varies axially from 0% of voids in the inferior part of the fuel assemblies until approximately 70% of voids to the exit of the same ones. Due to this it is very important the determination of the average void fraction during different stages of the reactor operation to predict the burnt one appropriately of the same ones to inclination of the pattern of linear reactivity. In this work a pursuit is made of the profile of power for different steps of burnt of a typical operation cycle of a Boiling water reactor. Starting from these profiles it builds an algorithm that allows to determine the voids profile and this way to obtain the average value of the same one. The results are compared against those reported by the CM-PRESTO code that uses another method to carry out this calculation. Finally, the range in which is the average value of the void fraction during a typical cycle is determined and an estimate of the impact that it would have the use of this value in the prediction of the reactivity produced by the fuel assemblies is made. (Author)
Quadratic reactivity fuel cycle model
Lewins, J.D.
1985-11-01
For educational purposes it is highly desirable to provide simple yet realistic models for fuel cycle and fuel economy. In particular, a lumped model without recourse to detailed spatial calculations would be very helpful in providing the student with a proper understanding of the purposes of fuel cycle calculations. A teaching model for fuel cycle studies based on a lumped model assuming the summability of partial reactivities with a linear dependence of reactivity usefully illustrates fuel utilization concepts. The linear burnup model does not satisfactorily represent natural enrichment reactors. A better model, showing the trend of initial plutonium production before subsequent fuel burnup and fission product generation, is a quadratic fit. The study of M-batch cycles, reloading 1/Mth of the core at end of cycle, is now complicated by nonlinear equations. A complete account of the asymptotic cycle for any order of M-batch refueling can be given and compared with the linear model. A complete account of the transient cycle can be obtained readily in the two-batch model and this exact solution would be useful in verifying numerical marching models. It is convenient to treat the parabolic fit rho = 1 - tau/sup 2/ as a special case of the general quadratic fit rho = 1 - C/sub tau/ - (1 - C)tau/sup 2/ in suitably normalized reactivity and cycle time units. The parabolic results are given in this paper.
Faraway, Julian J
2014-01-01
A Hands-On Way to Learning Data AnalysisPart of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with R, Second Edition explains how to use linear models in physical science, engineering, social science, and business applications. The book incorporates several improvements that reflect how the world of R has greatly expanded since the publication of the first edition.New to the Second EditionReorganiz
Høskuldsson, Agnar
1996-01-01
Determination of the proper dimension of a given linear model is one of the most important tasks in the applied modeling work. We consider here eight criteria that can be used to determine the dimension of the model, or equivalently, the number of components to use in the model. Four...... the basic problems in determining the dimension of linear models. Then each of the eight measures are treated. The results are illustrated by examples....
Foundations of linear and generalized linear models
Agresti, Alan
2015-01-01
A valuable overview of the most important ideas and results in statistical analysis Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linear statistical models. The book presents a broad, in-depth overview of the most commonly used statistical models by discussing the theory underlying the models, R software applications, and examples with crafted models to elucidate key ideas and promote practical model building. The book begins by illustrating the fundamentals of linear models,
Reactive Scattering Wave Functions by Linear Combination of Arrangement Channels
邓从豪; 冯大诚; 蔡政亭
1994-01-01
The similarity and dissimilarity of reactive scattering wave functions and molecular orbitalby linear combination of atomic orbitals(LCAOMO)are examined.Based on the similarity a method is pro-posed to construct the reactive scattering wave functions by linear combination of arrangement channel wavefunctions(LCACSW).Based on the dissimilarity,it is shown that the combination coefficients can be deter-mined by solving s set of simultaneous algebraic equations.The elements of the reactive scattering matrix areshown to be related to the combination coefficients of open arrangement channels.The differential and totalreactive scattering cross-section derived by this method agrees completely with that derived by other meth-ods.
Monahan, John F
2008-01-01
Preface Examples of the General Linear Model Introduction One-Sample Problem Simple Linear Regression Multiple Regression One-Way ANOVA First Discussion The Two-Way Nested Model Two-Way Crossed Model Analysis of Covariance Autoregression Discussion The Linear Least Squares Problem The Normal Equations The Geometry of Least Squares Reparameterization Gram-Schmidt Orthonormalization Estimability and Least Squares Estimators Assumptions for the Linear Mean Model Confounding, Identifiability, and Estimability Estimability and Least Squares Estimators F
Campagnoli, Patrizia; Petris, Giovanni
2009-01-01
State space models have gained tremendous popularity in as disparate fields as engineering, economics, genetics and ecology. Introducing general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. It illustrates the fundamental steps needed to use dynamic linear models in practice, using R package.
Explorative methods in linear models
Høskuldsson, Agnar
2004-01-01
The author has developed the H-method of mathematical modeling that builds up the model by parts, where each part is optimized with respect to prediction. Besides providing with better predictions than traditional methods, these methods provide with graphic procedures for analyzing different feat...... features in data. These graphic methods extend the well-known methods and results of Principal Component Analysis to any linear model. Here the graphic procedures are applied to linear regression and Ridge Regression....
Explorative methods in linear models
Høskuldsson, Agnar
2004-01-01
The author has developed the H-method of mathematical modeling that builds up the model by parts, where each part is optimized with respect to prediction. Besides providing with better predictions than traditional methods, these methods provide with graphic procedures for analyzing different...... features in data. These graphic methods extend the well-known methods and results of Principal Component Analysis to any linear model. Here the graphic procedures are applied to linear regression and Ridge Regression....
Generalized, Linear, and Mixed Models
McCulloch, Charles E; Neuhaus, John M
2011-01-01
An accessible and self-contained introduction to statistical models-now in a modernized new editionGeneralized, Linear, and Mixed Models, Second Edition provides an up-to-date treatment of the essential techniques for developing and applying a wide variety of statistical models. The book presents thorough and unified coverage of the theory behind generalized, linear, and mixed models and highlights their similarities and differences in various construction, application, and computational aspects.A clear introduction to the basic ideas of fixed effects models, random effects models, and mixed m
Modeling and stability analysis of the nonlinear reactive sputtering process
György Katalin
2011-12-01
Full Text Available The model of the reactive sputtering process has been determined from the dynamic equilibrium of the reactive gas inside the chamber and the dynamic equilibrium of the sputtered metal atoms which form the compound with the reactive gas atoms on the surface of the substrate. The analytically obtained dynamical model is a system of nonlinear differential equations which can result in a histeresis-type input/output nonlinearity. The reactive sputtering process has been simulated by integrating these differential equations. Linearization has been applied for classical analysis of the sputtering process and control system design.
Sparse Linear Identifiable Multivariate Modeling
Henao, Ricardo; Winther, Ole
2011-01-01
In this paper we consider sparse and identifiable linear latent variable (factor) and linear Bayesian network models for parsimonious analysis of multivariate data. We propose a computationally efficient method for joint parameter and model inference, and model comparison. It consists of a fully...... Bayesian hierarchy for sparse models using slab and spike priors (two-component δ-function and continuous mixtures), non-Gaussian latent factors and a stochastic search over the ordering of the variables. The framework, which we call SLIM (Sparse Linear Identifiable Multivariate modeling), is validated...... and bench-marked on artificial and real biological data sets. SLIM is closest in spirit to LiNGAM (Shimizu et al., 2006), but differs substantially in inference, Bayesian network structure learning and model comparison. Experimentally, SLIM performs equally well or better than LiNGAM with comparable...
Decomposable log-linear models
Eriksen, Poul Svante
can be characterized by a structured set of conditional independencies between some variables given some other variables. We term the new model class decomposable log-linear models, which is illustrated to be a much richer class than decomposable graphical models.It covers a wide range of non...
Parameterized Linear Longitudinal Airship Model
Kulczycki, Eric; Elfes, Alberto; Bayard, David; Quadrelli, Marco; Johnson, Joseph
2010-01-01
A parameterized linear mathematical model of the longitudinal dynamics of an airship is undergoing development. This model is intended to be used in designing control systems for future airships that would operate in the atmospheres of Earth and remote planets. Heretofore, the development of linearized models of the longitudinal dynamics of airships has been costly in that it has been necessary to perform extensive flight testing and to use system-identification techniques to construct models that fit the flight-test data. The present model is a generic one that can be relatively easily specialized to approximate the dynamics of specific airships at specific operating points, without need for further system identification, and with significantly less flight testing. The approach taken in the present development is to merge the linearized dynamical equations of an airship with techniques for estimation of aircraft stability derivatives, and to thereby make it possible to construct a linearized dynamical model of the longitudinal dynamics of a specific airship from geometric and aerodynamic data pertaining to that airship. (It is also planned to develop a model of the lateral dynamics by use of the same methods.) All of the aerodynamic data needed to construct the model of a specific airship can be obtained from wind-tunnel testing and computational fluid dynamics
Inequality constrained normal linear models
Klugkist, I.G.
2005-01-01
This dissertation deals with normal linear models with inequality constraints among model parameters. It consists of an introduction and four chapters that are papers submitted for publication. The first chapter introduces the use of inequality constraints. Scientists often have one or more theories
Inferential Models for Linear Regression
Zuoyi Zhang
2011-09-01
Full Text Available Linear regression is arguably one of the most widely used statistical methods in applications. However, important problems, especially variable selection, remain a challenge for classical modes of inference. This paper develops a recently proposed framework of inferential models (IMs in the linear regression context. In general, an IM is able to produce meaningful probabilistic summaries of the statistical evidence for and against assertions about the unknown parameter of interest and, moreover, these summaries are shown to be properly calibrated in a frequentist sense. Here we demonstrate, using simple examples, that the IM framework is promising for linear regression analysis --- including model checking, variable selection, and prediction --- and for uncertain inference in general.
Linearized Bekenstein Varying Alpha Models
Pina-Avelino, P; Oliveira, J C
2004-01-01
We study the simplest class of Bekenstein-type, varying $\\alpha$ models, in which the two available free functions (potential and gauge kinetic function) are Taylor-expanded up to linear order. Any realistic model of this type reduces to a model in this class for a certain time interval around the present day. Nevertheless, we show that no such model is consistent with all existing observational results. We discuss possible implications of these findings, and in particular clarify the ambiguous statement (often found in the literature) that ``the Webb results are inconsistent with Oklo''.
Linearized Bekenstein varying α models
Avelino, P. P.; Martins, C. J.; Oliveira, J. C.
2004-10-01
We study the simplest class of Bekenstein-type, varying α models, in which the two available free functions (potential and gauge kinetic function) are Taylor-expanded up to linear order. Any realistic model of this type reduces to a model in this class for a certain time interval around the present day. Nevertheless, we show that no such model is consistent with all existing observational results. We discuss possible implications of these findings, and, in particular, clarify the ambiguous statement (often found in the literature) that “the Webb results are inconsistent with Oklo.”
Multicollinearity in hierarchical linear models.
Yu, Han; Jiang, Shanhe; Land, Kenneth C
2015-09-01
This study investigates an ill-posed problem (multicollinearity) in Hierarchical Linear Models from both the data and the model perspectives. We propose an intuitive, effective approach to diagnosing the presence of multicollinearity and its remedies in this class of models. A simulation study demonstrates the impacts of multicollinearity on coefficient estimates, associated standard errors, and variance components at various levels of multicollinearity for finite sample sizes typical in social science studies. We further investigate the role multicollinearity plays at each level for estimation of coefficient parameters in terms of shrinkage. Based on these analyses, we recommend a top-down method for assessing multicollinearity in HLMs that first examines the contextual predictors (Level-2 in a two-level model) and then the individual predictors (Level-1) and uses the results for data collection, research problem redefinition, model re-specification, variable selection and estimation of a final model.
Modelling Loudspeaker Non-Linearities
Agerkvist, Finn T.
2007-01-01
This paper investigates different techniques for modelling the non-linear parameters of the electrodynamic loudspeaker. The methods are tested not only for their accuracy within the range of original data, but also for the ability to work reasonable outside that range, and it is demonstrated...... that polynomial expansions are rather poor at this, whereas an inverse polynomial expansion or localized fitting functions such as the gaussian are better suited for modelling the Bl-factor and compliance. For the inductance the sigmoid function is shown to give very good results. Finally the time varying...
Multivariate covariance generalized linear models
Bonat, W. H.; Jørgensen, Bent
2016-01-01
We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models, designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link...... function combined with a matrix linear predictor involving known matrices. The method is motivated by three data examples that are not easily handled by existing methods. The first example concerns multivariate count data, the second involves response variables of mixed types, combined with repeated...... are fitted by using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of types of response variables and covariance structures, including multivariate extensions...
Matrix algebra for linear models
Gruber, Marvin H J
2013-01-01
Matrix methods have evolved from a tool for expressing statistical problems to an indispensable part of the development, understanding, and use of various types of complex statistical analyses. This evolution has made matrix methods a vital part of statistical education. Traditionally, matrix methods are taught in courses on everything from regression analysis to stochastic processes, thus creating a fractured view of the topic. Matrix Algebra for Linear Models offers readers a unique, unified view of matrix analysis theory (where and when necessary), methods, and their applications. Written f
Adaptive discontinuous Galerkin methods for non-linear reactive flows
Uzunca, Murat
2016-01-01
The focus of this monograph is the development of space-time adaptive methods to solve the convection/reaction dominated non-stationary semi-linear advection diffusion reaction (ADR) equations with internal/boundary layers in an accurate and efficient way. After introducing the ADR equations and discontinuous Galerkin discretization, robust residual-based a posteriori error estimators in space and time are derived. The elliptic reconstruction technique is then utilized to derive the a posteriori error bounds for the fully discrete system and to obtain optimal orders of convergence. As coupled surface and subsurface flow over large space and time scales is described by (ADR) equation the methods described in this book are of high importance in many areas of Geosciences including oil and gas recovery, groundwater contamination and sustainable use of groundwater resources, storing greenhouse gases or radioactive waste in the subsurface.
Modelling Reactive and Proactive Behaviour in Simulation
Majid, Mazlina Abdul; Aickelin, Uwe
2010-01-01
This research investigated the simulation model behaviour of a traditional and combined discrete event as well as agent based simulation models when modelling human reactive and proactive behaviour in human centric complex systems. A departmental store was chosen as human centric complex case study where the operation system of a fitting room in WomensWear department was investigated. We have looked at ways to determine the efficiency of new management policies for the fitting room operation through simulating the reactive and proactive behaviour of staff towards customers. Once development of the simulation models and their verification had been done, we carried out a validation experiment in the form of a sensitivity analysis. Subsequently, we executed a statistical analysis where the mixed reactive and proactive behaviour experimental results were compared with some reactive experimental results from previously published works. Generally, this case study discovered that simple proactive individual behaviou...
Modeling and simulation of reactive flows
Bortoli, De AL; Pereira, Felipe
2015-01-01
Modelling and Simulation of Reactive Flows presents information on modeling and how to numerically solve reactive flows. The book offers a distinctive approach that combines diffusion flames and geochemical flow problems, providing users with a comprehensive resource that bridges the gap for scientists, engineers, and the industry. Specifically, the book looks at the basic concepts related to reaction rates, chemical kinetics, and the development of reduced kinetic mechanisms. It considers the most common methods used in practical situations, along with equations for reactive flows, and va
Linear and non-linear perturbations in dark energy models
Escamilla-Rivera, Celia; Fabris, Julio C; Alcaniz, Jailson S
2016-01-01
In this work we discuss observational aspects of three time-dependent parameterisations of the dark energy equation of state $w(z)$. In order to determine the dynamics associated with these models, we calculate their background evolution and perturbations in a scalar field representation. After performing a complete treatment of linear perturbations, we also show that the non-linear contribution of the selected $w(z)$ parameterisations to the matter power spectra is almost the same for all scales, with no significant difference from the predictions of the standard $\\Lambda$CDM model.
Multivariate generalized linear mixed models using R
Berridge, Damon Mark
2011-01-01
Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data sets, enabling readers to answer increasingly complex research questions. The book applies the principles of modeling to longitudinal data from panel and related studies via the Sabre software package in R. A Unified Framework for a Broad Class of Models The authors first discuss members of the family of generalized linear models, gradually adding complexity to the modeling framework by incorporating random effects. After reviewing the generalized linear model notation, they illustrate a range of random effects models, including three-level, multivariate, endpoint, event history, and state dependence models. They estimate the multivariate generalized linear mixed models (MGLMMs) using either standard or adaptive Gaussian quadrature. The authors also compare two-level fixed and random effects linear models. The appendices contain additional information on quadrature, model...
Linear Logistic Test Modeling with R
Baghaei, Purya; Kubinger, Klaus D.
2015-01-01
The present paper gives a general introduction to the linear logistic test model (Fischer, 1973), an extension of the Rasch model with linear constraints on item parameters, along with eRm (an R package to estimate different types of Rasch models; Mair, Hatzinger, & Mair, 2014) functions to estimate the model and interpret its parameters. The…
Processing Approach of Non-linear Adjustment Models in the Space of Non-linear Models
LI Chaokui; ZHU Qing; SONG Chengfang
2003-01-01
This paper investigates the mathematic features of non-linear models and discusses the processing way of non-linear factors which contributes to the non-linearity of a nonlinear model. On the basis of the error definition, this paper puts forward a new adjustment criterion, SGPE.Last, this paper investigates the solution of a non-linear regression model in the non-linear model space and makes the comparison between the estimated values in non-linear model space and those in linear model space.
Comparing linear probability model coefficients across groups
Holm, Anders; Ejrnæs, Mette; Karlson, Kristian Bernt
2015-01-01
This article offers a formal identification analysis of the problem in comparing coefficients from linear probability models between groups. We show that differences in coefficients from these models can result not only from genuine differences in effects, but also from differences in one or more...... these limitations, and we suggest a restricted approach to using linear probability model coefficients in group comparisons....
Composite Linear Models | Division of Cancer Prevention
By Stuart G. Baker The composite linear models software is a matrix approach to compute maximum likelihood estimates and asymptotic standard errors for models for incomplete multinomial data. It implements the method described in Baker SG. Composite linear models for incomplete multinomial data. Statistics in Medicine 1994;13:609-622. The software includes a library of thirty examples from the literature. |
Bayes linear covariance matrix adjustment for multivariate dynamic linear models
Wilkinson, Darren J
2008-01-01
A methodology is developed for the adjustment of the covariance matrices underlying a multivariate constant time series dynamic linear model. The covariance matrices are embedded in a distribution-free inner-product space of matrix objects which facilitates such adjustment. This approach helps to make the analysis simple, tractable and robust. To illustrate the methods, a simple model is developed for a time series representing sales of certain brands of a product from a cash-and-carry depot. The covariance structure underlying the model is revised, and the benefits of this revision on first order inferences are then examined.
Comparing linear probability model coefficients across groups
Holm, Anders; Ejrnæs, Mette; Karlson, Kristian Bernt
2015-01-01
This article offers a formal identification analysis of the problem in comparing coefficients from linear probability models between groups. We show that differences in coefficients from these models can result not only from genuine differences in effects, but also from differences in one or more...... of the following three components: outcome truncation, scale parameters and distributional shape of the predictor variable. These results point to limitations in using linear probability model coefficients for group comparisons. We also provide Monte Carlo simulations and real examples to illustrate...... these limitations, and we suggest a restricted approach to using linear probability model coefficients in group comparisons....
Franco-Pérez, Marco; Ayers, Paul W; Gázquez, José L; Vela, Alberto
2015-12-28
We explore the local and nonlocal response functions of the grand canonical potential density functional at nonzero temperature. In analogy to the zero-temperature treatment, local (e.g., the average electron density and the local softness) and nonlocal (e.g., the softness kernel) intrinsic response functions are defined as partial derivatives of the grand canonical potential with respect to its thermodynamic variables (i.e., the chemical potential of the electron reservoir and the external potential generated by the atomic nuclei). To define the local and nonlocal response functions of the electron density (e.g., the Fukui function, the linear density response function, and the dual descriptor), we differentiate with respect to the average electron number and the external potential. The well-known mathematical relationships between the intrinsic response functions and the electron-density responses are generalized to nonzero temperature, and we prove that in the zero-temperature limit, our results recover well-known identities from the density functional theory of chemical reactivity. Specific working equations and numerical results are provided for the 3-state ensemble model.
Franco-Pérez, Marco, E-mail: francopj@mcmaster.ca, E-mail: ayers@mcmaster.ca, E-mail: jlgm@xanum.uam.mx, E-mail: avela@cinvestav.mx [Department of Chemistry and Chemical Biology, McMaster University, Hamilton, Ontario L8S 4M1 (Canada); Departamento de Química, Universidad Autónoma Metropolitana-Iztapalapa, Av. San Rafael Atlixco 186, México, D.F. 09340 (Mexico); Ayers, Paul W., E-mail: francopj@mcmaster.ca, E-mail: ayers@mcmaster.ca, E-mail: jlgm@xanum.uam.mx, E-mail: avela@cinvestav.mx [Department of Chemistry and Chemical Biology, McMaster University, Hamilton, Ontario L8S 4M1 (Canada); Gázquez, José L., E-mail: francopj@mcmaster.ca, E-mail: ayers@mcmaster.ca, E-mail: jlgm@xanum.uam.mx, E-mail: avela@cinvestav.mx [Departamento de Química, Universidad Autónoma Metropolitana-Iztapalapa, Av. San Rafael Atlixco 186, México, D.F. 09340 (Mexico); Vela, Alberto, E-mail: francopj@mcmaster.ca, E-mail: ayers@mcmaster.ca, E-mail: jlgm@xanum.uam.mx, E-mail: avela@cinvestav.mx [Departamento de Química, Centro de Investigación y de Estudios Avanzados (Cinvestav), Av. Instituto Politécnico Nacional 2508, México, D.F. 07360 (Mexico)
2015-12-28
We explore the local and nonlocal response functions of the grand canonical potential density functional at nonzero temperature. In analogy to the zero-temperature treatment, local (e.g., the average electron density and the local softness) and nonlocal (e.g., the softness kernel) intrinsic response functions are defined as partial derivatives of the grand canonical potential with respect to its thermodynamic variables (i.e., the chemical potential of the electron reservoir and the external potential generated by the atomic nuclei). To define the local and nonlocal response functions of the electron density (e.g., the Fukui function, the linear density response function, and the dual descriptor), we differentiate with respect to the average electron number and the external potential. The well-known mathematical relationships between the intrinsic response functions and the electron-density responses are generalized to nonzero temperature, and we prove that in the zero-temperature limit, our results recover well-known identities from the density functional theory of chemical reactivity. Specific working equations and numerical results are provided for the 3-state ensemble model.
Generalized Quadratic Linearization of Machine Models
Parvathy Ayalur Krishnamoorthy; Kamaraj Vijayarajan; Devanathan Rajagopalan
2011-01-01
In the exact linearization of involutive nonlinear system models, the issue of singularity needs to be addressed in practical applications. The approximate linearization technique due to Krener, based on Taylor series expansion, apart from being applicable to noninvolutive systems, allows the singularity issue to be circumvented. But approximate linearization, while removing terms up to certain order, also introduces terms of higher order than those removed into the system. To overcome th...
Sparse Linear Identifiable Multivariate Modeling
Henao, Ricardo; Winther, Ole
2011-01-01
and bench-marked on artificial and real biological data sets. SLIM is closest in spirit to LiNGAM (Shimizu et al., 2006), but differs substantially in inference, Bayesian network structure learning and model comparison. Experimentally, SLIM performs equally well or better than LiNGAM with comparable...
Non-linear finite element modeling
Mikkelsen, Lars Pilgaard
The note is written for courses in "Non-linear finite element method". The note has been used by the author teaching non-linear finite element modeling at Civil Engineering at Aalborg University, Computational Mechanics at Aalborg University Esbjerg, Structural Engineering at the University...... on the governing equations and methods of implementing....
Correlations and Non-Linear Probability Models
Breen, Richard; Holm, Anders; Karlson, Kristian Bernt
2014-01-01
the dependent variable of the latent variable model and its predictor variables. We show how this correlation can be derived from the parameters of non-linear probability models, develop tests for the statistical significance of the derived correlation, and illustrate its usefulness in two applications. Under......Although the parameters of logit and probit and other non-linear probability models are often explained and interpreted in relation to the regression coefficients of an underlying linear latent variable model, we argue that they may also be usefully interpreted in terms of the correlations between...... certain circumstances, which we explain, the derived correlation provides a way of overcoming the problems inherent in cross-sample comparisons of the parameters of non-linear probability models....
Linear mixed models in sensometrics
Kuznetsova, Alexandra
quality of decision making in Danish as well as international food companies and other companies using the same methods. The two open-source R packages lmerTest and SensMixed implement and support the methodological developments in the research papers as well as the ANOVA modelling part of the Consumer......Today’s companies and researchers gather large amounts of data of different kind. In consumer studies the objective is the collection of the data to better understand consumer acceptance of products. In such studies a number of persons (generally not trained) are selected in order to score products......, texture, sound - depending on the aim of a study. It is a common approach in both studies to consider persons coming from a larger population, which, from the statistical perspective, leads to the use of mixed effects models, where consumers/assessors enter as random effects (Lawless and Heymann, 1997...
Linear Logistic Test Modeling with R
Purya Baghaei
2014-01-01
Full Text Available The present paper gives a general introduction to the linear logistic test model (Fischer, 1973, an extension of the Rasch model with linear constraints on item parameters, along with eRm (an R package to estimate different types of Rasch models; Mair, Hatzinger, & Mair, 2014 functions to estimate the model and interpret its parameters. The applications of the model in test validation, hypothesis testing, cross-cultural studies of test bias, rule-based item generation, and investigating construct irrelevant factors which contribute to item difficulty are explained. The model is applied to an English as a foreign language reading comprehension test and the results are discussed.
Linear mixed models for longitudinal data
Molenberghs, Geert
2000-01-01
This paperback edition is a reprint of the 2000 edition. This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place. Several variations to the conventional linear mixed model are discussed (a heterogeity model, conditional linear mixed models). This book will be of interest to applied statisticians and biomedical researchers in industry, public health organizations, contract research organizations, and academia. The book is explanatory rather than mathematically rigorous. Most analyses were done with the MIXED procedure of the SAS software package, and many of its features are clearly elucidated. However, some other commerc...
Correlations and Non-Linear Probability Models
Breen, Richard; Holm, Anders; Karlson, Kristian Bernt
2014-01-01
Although the parameters of logit and probit and other non-linear probability models are often explained and interpreted in relation to the regression coefficients of an underlying linear latent variable model, we argue that they may also be usefully interpreted in terms of the correlations betwee...... certain circumstances, which we explain, the derived correlation provides a way of overcoming the problems inherent in cross-sample comparisons of the parameters of non-linear probability models.......Although the parameters of logit and probit and other non-linear probability models are often explained and interpreted in relation to the regression coefficients of an underlying linear latent variable model, we argue that they may also be usefully interpreted in terms of the correlations between...... the dependent variable of the latent variable model and its predictor variables. We show how this correlation can be derived from the parameters of non-linear probability models, develop tests for the statistical significance of the derived correlation, and illustrate its usefulness in two applications. Under...
When to Use Hierarchical Linear Modeling
Veronika Huta
2014-01-01
Previous publications on hierarchical linear modeling (HLM) have provided guidance on how to perform the analysis, yet there is relatively little information on two questions that arise even before analysis...
An introduction to hierarchical linear modeling
Woltman, Heather; Feldstain, Andrea; MacKay, J. Christine; Rocchi, Meredith
2012-01-01
This tutorial aims to introduce Hierarchical Linear Modeling (HLM). A simple explanation of HLM is provided that describes when to use this statistical technique and identifies key factors to consider before conducting this analysis...
Linear causal modeling with structural equations
Mulaik, Stanley A
2009-01-01
Emphasizing causation as a functional relationship between variables that describe objects, Linear Causal Modeling with Structural Equations integrates a general philosophical theory of causation with structural equation modeling (SEM) that concerns the special case of linear causal relations. In addition to describing how the functional relation concept may be generalized to treat probabilistic causation, the book reviews historical treatments of causation and explores recent developments in experimental psychology on studies of the perception of causation. It looks at how to perceive causal
Statistical Tests for Mixed Linear Models
Khuri, André I; Sinha, Bimal K
2011-01-01
An advanced discussion of linear models with mixed or random effects. In recent years a breakthrough has occurred in our ability to draw inferences from exact and optimum tests of variance component models, generating much research activity that relies on linear models with mixed and random effects. This volume covers the most important research of the past decade as well as the latest developments in hypothesis testing. It compiles all currently available results in the area of exact and optimum tests for variance component models and offers the only comprehensive treatment for these models a
Matrix Tricks for Linear Statistical Models
Puntanen, Simo; Styan, George PH
2011-01-01
In teaching linear statistical models to first-year graduate students or to final-year undergraduate students there is no way to proceed smoothly without matrices and related concepts of linear algebra; their use is really essential. Our experience is that making some particular matrix tricks very familiar to students can substantially increase their insight into linear statistical models (and also multivariate statistical analysis). In matrix algebra, there are handy, sometimes even very simple "tricks" which simplify and clarify the treatment of a problem - both for the student and
Testing linearity against nonlinear moving average models
de Gooijer, J.G.; Brännäs, K.; Teräsvirta, T.
1998-01-01
Lagrange multiplier (LM) test statistics are derived for testing a linear moving average model against an additive smooth transition moving average model. The latter model is introduced in the paper. The small sample performance of the proposed tests are evaluated in a Monte Carlo study and compared
Exact Solutions in Nonlocal Linear Models
Vernov, S. Yu.
2008-01-01
A general class of cosmological models driven by a nonlocal scalar field inspired by the string field theory is studied. Using the fact that the considering linear nonlocal model is equivalent to an infinite number of local models we have found an exact special solution of the nonlocal Friedmann equations. This solution describes a monotonically increasing Universe with the phantom dark energy.
Modeling target erosion during reactive sputtering
Strijckmans, K., E-mail: Koen.Strijckmans@ugent.be; Depla, D.
2015-03-15
Highlights: • The erosion of a target is simulated with the RSD2013 software during reactive magnetron sputtering. • The influence of redeposition on the target state and on the hysteresis is explained. • The racetrack formation along the hysteresis and as function of the redeposition is quantified. • Comparison of the racetrack and the sputter profile shows clear differences. - Abstract: The influence of the reactive sputter conditions on the racetrack and the sputter profile for an Al/O{sub 2} DC reactive sputter system is studied by modeling. The role of redeposition, i.e. the deposition of sputtered material back on the target, is therefore taken into account. The used model RSD2013 is capable of simulating the effect of redeposition on the target condition in a spatial resolved way. Comparison between including and excluding redeposition in the RSD2013 model shows that the in-depth oxidation profile of the target differs. Modeling shows that it is important to distinguish between the formed racetrack, i.e. the erosion depth profile, and the sputter profile. The latter defines the distribution of the sputtered atoms in the vacuum chamber. As the target condition defines the sputter yield, it does determine the racetrack and the sputter profile of the planar circular target. Both the shape of the racetrack and the sputter profile change as function of the redeposition fraction as well as function of the oxygen flow change. Clear asymmetries and narrowing are observed for the racetrack shape. Similar effects are noticed for the sputter profile but to a different extent. Based on this study, the often heard misconception that the racetrack shape defines the distribution of the sputtered atoms during reactive sputtering is proven to be wrong.
Global identifiability of linear structural equation models
Drton, Mathias; Sullivant, Seth
2010-01-01
Structural equation models are multivariate statistical models that are defined by specifying noisy functional relationships among random variables. We consider the classical case of linear relationships and additive Gaussian noise terms. We give a necessary and sufficient condition for global identifiability of the model in terms of a mixed graph encoding the linear structural equations and the correlation structure of the error terms. Global identifiability is understood to mean injectivity of the parametrization of the model and is fundamental in particular for applicability of standard statistical methodology.
Modeling digital switching circuits with linear algebra
Thornton, Mitchell A
2014-01-01
Modeling Digital Switching Circuits with Linear Algebra describes an approach for modeling digital information and circuitry that is an alternative to Boolean algebra. While the Boolean algebraic model has been wildly successful and is responsible for many advances in modern information technology, the approach described in this book offers new insight and different ways of solving problems. Modeling the bit as a vector instead of a scalar value in the set {0, 1} allows digital circuits to be characterized with transfer functions in the form of a linear transformation matrix. The use of transf
Identification and Modelling of Linear Dynamic Systems
Stanislav Kocur
2006-01-01
Full Text Available System identification and modelling are very important parts of system control theory. System control is only as good as good is created model of system. So this article deals with identification and modelling problems. There are simple classification and evolution of identification methods, and then the modelling problem is described. Rest of paper is devoted to two most known and used models of linear dynamic systems.
Nakan U
2016-09-01
Full Text Available Сopolymerization of N-isopropylacrylamide (NIPAAm with 2-hydroxyethyl acrylate (2-HEA carried out by solvent ethanol solution method, at 600C, using Azoisobutyronitrile (AIBN as an initiator. The hydrophilic copolymers were characterized by elemental analysis, DSC, TGA and turbidimetric method. The results showed thermal stability increase with increase of NIPAAm in the copolymers. It was found that copolymer solutions have lower critical solution temperature (by turbidimetric analysis. The reactivity ratios of monomers were determined using linear methods like Fineman-Ross and Kelen-Tudos. The reactivity ratios of r1 and r2 were found to be 0,86, 0,72 and 1,02, 1,04 respectively.
Disc instantons in linear sigma models
Govindarajan, Suresh E-mail: suresh@chaos.iitm.ernet.in; Jayaraman, T. E-mail: jayaram@imsc.ernet.in; Sarkar, Tapobrata E-mail: tapo@theory.tifr.res.in
2002-12-16
We construct a linear sigma model for open-strings ending on special Lagrangian cycles of a Calabi-Yau manifold. We illustrate the construction for the cases considered by Aganagic and Vafa (AV). This leads naturally to concrete models for the moduli space of open-string instantons. These instanton moduli spaces can be seen to be intimately related to certain auxiliary boundary toric varieties. By considering the relevant Gelfand-Kapranov-Zelevinsky (GKZ) differential equations of the boundary toric variety, we obtain the contributions to the world volume superpotential on the A-branes from open-string instantons. By using an ansatz due to Aganagic, Klemm and Vafa (AKV), we obtain the relevant change of variables from the linear sigma model to the non-linear sigma model variables--the open-string mirror map. Using this mirror map, we obtain results in agreement with those of AV and AKV for the counting of holomorphic disc instantons.
Faraway, Julian J
2005-01-01
Linear models are central to the practice of statistics and form the foundation of a vast range of statistical methodologies. Julian J. Faraway''s critically acclaimed Linear Models with R examined regression and analysis of variance, demonstrated the different methods available, and showed in which situations each one applies. Following in those footsteps, Extending the Linear Model with R surveys the techniques that grow from the regression model, presenting three extensions to that framework: generalized linear models (GLMs), mixed effect models, and nonparametric regression models. The author''s treatment is thoroughly modern and covers topics that include GLM diagnostics, generalized linear mixed models, trees, and even the use of neural networks in statistics. To demonstrate the interplay of theory and practice, throughout the book the author weaves the use of the R software environment to analyze the data of real examples, providing all of the R commands necessary to reproduce the analyses. All of the ...
Introduction to general and generalized linear models
Madsen, Henrik
2010-01-01
IntroductionExamples of types of data Motivating examples A first view on the modelsThe Likelihood PrincipleIntroduction Point estimation theory The likelihood function The score function The information matrix Alternative parameterizations of the likelihood The maximum likelihood estimate (MLE) Distribution of the ML estimator Generalized loss-function and deviance Quadratic approximation of the log-likelihood Likelihood ratio tests Successive testing in hypothesis chains Dealing with nuisance parameters General Linear ModelsIntroduction The multivariate normal distribution General linear mod
An R companion to linear statistical models
Hay-Jahans, Christopher
2011-01-01
Focusing on user-developed programming, An R Companion to Linear Statistical Models serves two audiences: those who are familiar with the theory and applications of linear statistical models and wish to learn or enhance their skills in R; and those who are enrolled in an R-based course on regression and analysis of variance. For those who have never used R, the book begins with a self-contained introduction to R that lays the foundation for later chapters.This book includes extensive and carefully explained examples of how to write programs using the R programming language. These examples cove
Ruin Probability in Linear Time Series Model
ZHANG Lihong
2005-01-01
This paper analyzes a continuous time risk model with a linear model used to model the claim process. The time is discretized stochastically using the times when claims occur, using Doob's stopping time theorem and martingale inequalities to obtain expressions for the ruin probability as well as both exponential and non-exponential upper bounds for the ruin probability for an infinite time horizon. Numerical results are included to illustrate the accuracy of the non-exponential bound.
Are all Linear Paired Comparison Models Equivalent
1990-09-01
Previous authors (Jackson and Fleckenstein 1957, Mosteller 1958, Noether 1960) have found that different models of paired comparisons data lead to simi...ponential distribution with a location parameter (Mosteller 1958, Noether 1960). Formal statements describing the limiting behavior of the gamma...that are not convolu- tion type linear models (the uniform model considered by Smith (1956), Mosteller (1958), Noether (1960)) and other convolution
Estimation for the simple linear Boolean model
2006-01-01
We consider the simple linear Boolean model, a fundamental coverage process also known as the Markov/General/infinity queue. In the model, line segments of independent and identically distributed length are located at the points of a Poisson process. The segments may overlap, resulting in a pattern of "clumps"-regions of the line that are covered by one or more segments-alternating with uncovered regions or "spacings". Study and application of the model have been impeded by the difficult...
Orthogonal Nilpotent Superfields from Linear Models
Kallosh, Renata; Mosk, Benjamin; Murli, Divyanshu
2016-01-01
We derive supersymmetry/supergravity models with constrained orthogonal nilpotent superfields from the linear models in the formal limit when the masses of the sgoldstino, inflatino and sinflaton tend to infinity. The case when the sinflaton mass remains finite leads to a model with a `relaxed' constraint, where the sinflaton remains an independent field. Our procedure is equivalent to a requirement that some of the components of the curvature of the moduli space tend to infinity.
Managing Clustered Data Using Hierarchical Linear Modeling
Warne, Russell T.; Li, Yan; McKyer, E. Lisako J.; Condie, Rachel; Diep, Cassandra S.; Murano, Peter S.
2012-01-01
Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence…
Model reduction of linear conservative mechanical systems
Schaft, van der A.J.; Oeloff, J.E.
1990-01-01
An approach for model reduction of linear conservative or weakly damped mechanical systems is proposed. It is based on the balancing of an associated gradient system. It uses the joint knowledge of the system matrix and the input and output matrices of the Hamiltonian system. The key idea is to asso
Managing Clustered Data Using Hierarchical Linear Modeling
Warne, Russell T.; Li, Yan; McKyer, E. Lisako J.; Condie, Rachel; Diep, Cassandra S.; Murano, Peter S.
2012-01-01
Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence…
On Bayes linear unbiased estimation of estimable functions for the singular linear model
ZHANG Weiping; WEI Laisheng
2005-01-01
The unique Bayes linear unbiased estimator (Bayes LUE) of estimable functions is derived for the singular linear model. The superiority of Bayes LUE over ordinary best linear unbiased estimator is investigated under mean square error matrix (MSEM)criterion.
Non-linear Loudspeaker Unit Modelling
Pedersen, Bo Rohde; Agerkvist, Finn T.
2008-01-01
Simulations of a 6½-inch loudspeaker unit are performed and compared with a displacement measurement. The non-linear loudspeaker model is based on the major nonlinear functions and expanded with time-varying suspension behaviour and flux modulation. The results are presented with FFT plots of three...... frequencies and different displacement levels. The model errors are discussed and analysed including a test with loudspeaker unit where the diaphragm is removed....
Reactive transport modeling for Cs retention: from batch to field experiments
De Pourcq, K.; Ayora, C.; Carrera, J.; García-Gutiérrez, M.; Missana, T.; Mingarro, M.
2012-04-01
A Permeable Reactive Barrier has been designed to treat 137Cs polluted groundwater. In order to check both reactivity and permeability, laboratory batch and column tests combined with reactive transport modeling have been performed. The trapping mechanism is based on the sorption of cesium mainly on illite-containing clays. Batch experiments were conducted to obtain the partition coefficients (Kd) of different clay samples in solutions with different potassium concentration. A clear correlation of Kd values with potassium content was observed. The results were modeled with a cation-exchange model. The permeability of the reactive material is provided by the dispersion of the clay on a matrix of wooden shavings. Constant head tests allowed obtaining permeability values. Several column experiments with different flow rates were conducted to confirm the 137Cs retention under different conditions. A blind 1D reactive transport model based on the cation-exchange model was able to predict reasonably well the results of column experiments. The reactive transport model, validated with the column experiments, was used to investigate the performance and duration of 1m thick barrier under different scenarios (flow, clay proportion, 137Cs and K concentration). As expected, the sensitivity tests proved that the retention capacity of dissolved 137Cs in groundwater depends linearly on the amount of clay used in the filling material. As well, the operation time increases linearly when decreasing the flow rate. Finally, the concentration of potassium in inflow water has a remarkable and non-linear influence in the retention of 137Cs. Very high concentrations of potassium are the greatest threat and can lead to the unfeasibility of a permeable reactive barrier. Due to the Cs-K competition, the barrier is comparatively more efficient to treat high concentrations of 137Cs. Up to now, preliminary results from a field scale experiment have confirmed the reactivity and permeability
Linear Programming建模研讨%Modeling of Linear Programming
宋占奎; 於全收; 范光; 燕嬿; 胡杰军
2007-01-01
研究用图解法、simplexmethod和匈牙利法建立Linear Programming的数学模型并求得了最优解.结果表明:对仅有两个变量的Linear Programming,既可通过图解法求得最优解;也可用单纯形表简便地求得最优解;而对任务和人数不等的assignment problem,则用匈牙利法求最优解.
Multivariate Generalized Linear Mixed Models Using R
Berridge, Damon M
2011-01-01
To provide researchers with the ability to analyze large and complex data sets using robust models, this book presents a unified framework for a broad class of models that can be applied using a dedicated R package (Sabre). The first five chapters cover the analysis of multilevel models using univariate generalized linear mixed models (GLMMs). The next few chapters extend to multivariate GLMMs and the last chapters address more specialized topics, such as parallel computing for large-scale analyses. Each chapter includes many real-world examples implemented using Sabre as well as exercises and
Modelling female fertility traits in beef cattle using linear and non-linear models.
Naya, H; Peñagaricano, F; Urioste, J I
2017-06-01
Female fertility traits are key components of the profitability of beef cattle production. However, these traits are difficult and expensive to measure, particularly under extensive pastoral conditions, and consequently, fertility records are in general scarce and somehow incomplete. Moreover, fertility traits are usually dominated by the effects of herd-year environment, and it is generally assumed that relatively small margins are kept for genetic improvement. New ways of modelling genetic variation in these traits are needed. Inspired in the methodological developments made by Prof. Daniel Gianola and co-workers, we assayed linear (Gaussian), Poisson, probit (threshold), censored Poisson and censored Gaussian models to three different kinds of endpoints, namely calving success (CS), number of days from first calving (CD) and number of failed oestrus (FE). For models involving FE and CS, non-linear models overperformed their linear counterparts. For models derived from CD, linear versions displayed better adjustment than the non-linear counterparts. Non-linear models showed consistently higher estimates of heritability and repeatability in all cases (h(2 ) 0.23 and r > 0.24, for non-linear models). While additive and permanent environment effects showed highly favourable correlations between all models (>0.789), consistency in selecting the 10% best sires showed important differences, mainly amongst the considered endpoints (FE, CS and CD). In consequence, endpoints should be considered as modelling different underlying genetic effects, with linear models more appropriate to describe CD and non-linear models better for FE and CS. © 2017 Blackwell Verlag GmbH.
Neural Network for Combining Linear and Non-Linear Modelling of Dynamic Systems
Madsen, Per Printz
1994-01-01
The purpose of this paper is to develop a method to combine linear models with MLP networks. In other words to find a method to make a non-linear and multivariable model that performs at least as good as a linear model, when the training data lacks information.......The purpose of this paper is to develop a method to combine linear models with MLP networks. In other words to find a method to make a non-linear and multivariable model that performs at least as good as a linear model, when the training data lacks information....
Testing Parametric versus Semiparametric Modelling in Generalized Linear Models
Härdle, W.K.; Mammen, E.; Müller, M.D.
1996-01-01
We consider a generalized partially linear model E(Y|X,T) = G{X'b + m(T)} where G is a known function, b is an unknown parameter vector, and m is an unknown function.The paper introduces a test statistic which allows to decide between a parametric and a semiparametric model: (i) m is linear, i.e. m(
Using R In Generalized Linear Models
Mihaela Covrig
2015-09-01
Full Text Available This paper aims to approach the estimation of generalized linear models (GLM on the basis of the glm routine package in R. Particularly, regression models will be analyzed for those cases in which the explained variable follows a Poisson or a Negative Binomial distribution. The paper will briefly present the GLM methodology for count data, while the practical part will revolve around estimating and comparing models in which the response variable shows the number of claims in a portfolio of automobile insurance policies.
[From clinical judgment to linear regression model.
Palacios-Cruz, Lino; Pérez, Marcela; Rivas-Ruiz, Rodolfo; Talavera, Juan O
2013-01-01
When we think about mathematical models, such as linear regression model, we think that these terms are only used by those engaged in research, a notion that is far from the truth. Legendre described the first mathematical model in 1805, and Galton introduced the formal term in 1886. Linear regression is one of the most commonly used regression models in clinical practice. It is useful to predict or show the relationship between two or more variables as long as the dependent variable is quantitative and has normal distribution. Stated in another way, the regression is used to predict a measure based on the knowledge of at least one other variable. Linear regression has as it's first objective to determine the slope or inclination of the regression line: Y = a + bx, where "a" is the intercept or regression constant and it is equivalent to "Y" value when "X" equals 0 and "b" (also called slope) indicates the increase or decrease that occurs when the variable "x" increases or decreases in one unit. In the regression line, "b" is called regression coefficient. The coefficient of determination (R(2)) indicates the importance of independent variables in the outcome.
Synaptic dynamics: linear model and adaptation algorithm.
Yousefi, Ali; Dibazar, Alireza A; Berger, Theodore W
2014-08-01
In this research, temporal processing in brain neural circuitries is addressed by a dynamic model of synaptic connections in which the synapse model accounts for both pre- and post-synaptic processes determining its temporal dynamics and strength. Neurons, which are excited by the post-synaptic potentials of hundred of the synapses, build the computational engine capable of processing dynamic neural stimuli. Temporal dynamics in neural models with dynamic synapses will be analyzed, and learning algorithms for synaptic adaptation of neural networks with hundreds of synaptic connections are proposed. The paper starts by introducing a linear approximate model for the temporal dynamics of synaptic transmission. The proposed linear model substantially simplifies the analysis and training of spiking neural networks. Furthermore, it is capable of replicating the synaptic response of the non-linear facilitation-depression model with an accuracy better than 92.5%. In the second part of the paper, a supervised spike-in-spike-out learning rule for synaptic adaptation in dynamic synapse neural networks (DSNN) is proposed. The proposed learning rule is a biologically plausible process, and it is capable of simultaneously adjusting both pre- and post-synaptic components of individual synapses. The last section of the paper starts with presenting the rigorous analysis of the learning algorithm in a system identification task with hundreds of synaptic connections which confirms the learning algorithm's accuracy, repeatability and scalability. The DSNN is utilized to predict the spiking activity of cortical neurons and pattern recognition tasks. The DSNN model is demonstrated to be a generative model capable of producing different cortical neuron spiking patterns and CA1 Pyramidal neurons recordings. A single-layer DSNN classifier on a benchmark pattern recognition task outperforms a 2-Layer Neural Network and GMM classifiers while having fewer numbers of free parameters and
Rethinking the Lintnerian Linear Valuation Model
Shih-Cheng Lee
2014-09-01
Full Text Available This paper develops and tests a new valuation model. Callen and Morel (2000 apply the Lintner (1956 dividend model to the famous Ohlson (1995 valuation model and develop the Lintnerian linear accounting valuation model (henceforth, the CM model. However, Bauer and Bhattacharyya (2007 suggest that the Lintner dividend model does not fit firm dividend policy behaviour appropriately and decide to construct another dividend policy process. This study applies their dividend model to construct a new valuation model, which performs better than the original Ohlson and CM models empirically. Applying the Engle and Granger (1987 cointegration concepts, we examine the performance of the three models for the 1,564 firm-year panel data of US companies from 1973 to 2006. Our findings indicate that all tested variables are stationary after the first order difference process and that all three models exhibit long-run equilibrium relations among equity price and explanatory variables. However, our model has the highest cointegration ratio, which is almost 100 percent of sample firms. Hence, our model is more suitable to evaluate the equity value and provides improvement for the previous accounting valuation models.
Improved testing inference in mixed linear models
Melo, Tatiane F N; Cribari-Neto, Francisco; 10.1016/j.csda.2008.12.007
2011-01-01
Mixed linear models are commonly used in repeated measures studies. They account for the dependence amongst observations obtained from the same experimental unit. Oftentimes, the number of observations is small, and it is thus important to use inference strategies that incorporate small sample corrections. In this paper, we develop modified versions of the likelihood ratio test for fixed effects inference in mixed linear models. In particular, we derive a Bartlett correction to such a test and also to a test obtained from a modified profile likelihood function. Our results generalize those in Zucker et al. (Journal of the Royal Statistical Society B, 2000, 62, 827-838) by allowing the parameter of interest to be vector-valued. Additionally, our Bartlett corrections allow for random effects nonlinear covariance matrix structure. We report numerical evidence which shows that the proposed tests display superior finite sample behavior relative to the standard likelihood ratio test. An application is also presente...
Decomposed Implicit Models of Piecewise - Linear Networks
J. Brzobohaty
1992-05-01
Full Text Available The general matrix form of the implicit description of a piecewise-linear (PWL network and the symbolic block diagram of the corresponding circuit model are proposed. Their decomposed forms enable us to determine quite separately the existence of the individual breakpoints of the resultant PWL characteristic and their coordinates using independent network parameters. For the two-diode and three-diode cases all the attainable types of the PWL characteristic are introduced.
Data perturbation analysis of a linear model
无
2000-01-01
The linear model features were carefully studied in the cases of data perturbation and mean shift perturbation.Some important features were also proved mathematically. The results show that the mean shift perturbation is equivalentto the data perturbation, that is, adding a parameter to an observation equation means that this set of data is deleted fromthe data set. The estimate of this parameter is its predicted residual in fact
From spiking neuron models to linear-nonlinear models.
Srdjan Ostojic
Full Text Available Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF, exponential integrate-and-fire (EIF and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates.
B-737 Linear Autoland Simulink Model
Belcastro, Celeste (Technical Monitor); Hogge, Edward F.
2004-01-01
The Linear Autoland Simulink model was created to be a modular test environment for testing of control system components in commercial aircraft. The input variables, physical laws, and referenced frames used are summarized. The state space theory underlying the model is surveyed and the location of the control actuators described. The equations used to realize the Dryden gust model to simulate winds and gusts are derived. A description of the pseudo-random number generation method used in the wind gust model is included. The longitudinal autopilot, lateral autopilot, automatic throttle autopilot, engine model and automatic trim devices are considered as subsystems. The experience in converting the Airlabs FORTRAN aircraft control system simulation to a graphical simulation tool (Matlab/Simulink) is described.
Stochastic linear programming models, theory, and computation
Kall, Peter
2011-01-01
This new edition of Stochastic Linear Programming: Models, Theory and Computation has been brought completely up to date, either dealing with or at least referring to new material on models and methods, including DEA with stochastic outputs modeled via constraints on special risk functions (generalizing chance constraints, ICC’s and CVaR constraints), material on Sharpe-ratio, and Asset Liability Management models involving CVaR in a multi-stage setup. To facilitate use as a text, exercises are included throughout the book, and web access is provided to a student version of the authors’ SLP-IOR software. Additionally, the authors have updated the Guide to Available Software, and they have included newer algorithms and modeling systems for SLP. The book is thus suitable as a text for advanced courses in stochastic optimization, and as a reference to the field. From Reviews of the First Edition: "The book presents a comprehensive study of stochastic linear optimization problems and their applications. … T...
Exact linear modeling using Ore algebras
Schindelar, Kristina; Zerz, Eva
2010-01-01
Linear exact modeling is a problem coming from system identification: Given a set of observed trajectories, the goal is find a model (usually, a system of partial differential and/or difference equations) that explains the data as precisely as possible. The case of operators with constant coefficients is well studied and known in the systems theoretic literature, whereas the operators with varying coefficients were addressed only recently. This question can be tackled either using Gr\\"obner bases for modules over Ore algebras or by following the ideas from differential algebra and computing in commutative rings. In this paper, we present algorithmic methods to compute "most powerful unfalsified models" (MPUM) and their counterparts with variable coefficients (VMPUM) for polynomial and polynomial-exponential signals. We also study the structural properties of the resulting models, discuss computer algebraic techniques behind algorithms and provide several examples.
When to Use Hierarchical Linear Modeling
Veronika Huta
2014-04-01
Full Text Available Previous publications on hierarchical linear modeling (HLM have provided guidance on how to perform the analysis, yet there is relatively little information on two questions that arise even before analysis: Does HLM apply to ones data and research question? And if it does apply, how does one choose between HLM and other methods sometimes used in these circumstances, including multiple regression, repeated-measures or mixed ANOVA, and structural equation modeling or path analysis? The purpose of this tutorial is to briefly introduce HLM and then to review some of the considerations that are helpful in answering these questions, including the nature of the data, the model to be tested, and the information desired on the output. Some examples of how the same analysis could be performed in HLM, repeated-measures or mixed ANOVA, and structural equation modeling or path analysis are also provided. .
Impact of reactive settler models on simulated WWTP performance
Gernaey, Krist; Jeppsson, Ulf; Batstone, Damien J.
2006-01-01
Including a reactive settler model in a wastewater treatment plant model allows representation of the biological reactions taking place in the sludge blanket in the settler, something that is neglected in many simulation studies. The idea of including a reactive settler model is investigated for ...
Bayesian Discovery of Linear Acyclic Causal Models
Hoyer, Patrik O
2012-01-01
Methods for automated discovery of causal relationships from non-interventional data have received much attention recently. A widely used and well understood model family is given by linear acyclic causal models (recursive structural equation models). For Gaussian data both constraint-based methods (Spirtes et al., 1993; Pearl, 2000) (which output a single equivalence class) and Bayesian score-based methods (Geiger and Heckerman, 1994) (which assign relative scores to the equivalence classes) are available. On the contrary, all current methods able to utilize non-Gaussianity in the data (Shimizu et al., 2006; Hoyer et al., 2008) always return only a single graph or a single equivalence class, and so are fundamentally unable to express the degree of certainty attached to that output. In this paper we develop a Bayesian score-based approach able to take advantage of non-Gaussianity when estimating linear acyclic causal models, and we empirically demonstrate that, at least on very modest size networks, its accur...
Running vacuum cosmological models: linear scalar perturbations
Perico, E. L. D.; Tamayo, D. A.
2017-08-01
In cosmology, phenomenologically motivated expressions for running vacuum are commonly parameterized as linear functions typically denoted by Λ(H2) or Λ(R). Such models assume an equation of state for the vacuum given by bar PΛ = - bar rhoΛ, relating its background pressure bar PΛ with its mean energy density bar rhoΛ ≡ Λ/8πG. This equation of state suggests that the vacuum dynamics is due to an interaction with the matter content of the universe. Most of the approaches studying the observational impact of these models only consider the interaction between the vacuum and the transient dominant matter component of the universe. We extend such models by assuming that the running vacuum is the sum of independent contributions, namely bar rhoΛ = Σibar rhoΛi. Each Λ i vacuum component is associated and interacting with one of the i matter components in both the background and perturbation levels. We derive the evolution equations for the linear scalar vacuum and matter perturbations in those two scenarios, and identify the running vacuum imprints on the cosmic microwave background anisotropies as well as on the matter power spectrum. In the Λ(H2) scenario the vacuum is coupled with every matter component, whereas the Λ(R) description only leads to a coupling between vacuum and non-relativistic matter, producing different effects on the matter power spectrum.
CP Violation in the Linear Sigma Model
Mizher, Ana Júlia
2009-01-01
Motivated by the possibility of the formation of CP-odd domains in heavy ion collisions, we investigate the effects of CP violation on the chiral transition within the linear sigma model with two flavors of quarks. We also study how the CP-odd system is affected by the presence of a strong magnetic field, that is presumably generated in a non-central heavy ion collision. We find that both ingredients play an important role, influencing drastically the nature of the phase transition and the critical temperature.
CP Violation in the Linear Sigma Model
Mizher, Ana Júlia; Fraga, Eduardo S.
2008-01-01
Motivated by the possibility of the formation of CP-odd domains in heavy ion collisions, we investigate the effects of CP violation on the chiral transition within the linear sigma model with two flavors of quarks. We also study how the CP-odd system is affected by the presence of a strong magnetic field, that is presumably generated in a non-central heavy ion collision. We find that both ingredients play an important role, influencing drastically the nature of the phase transition and the cr...
CP Violation in the Linear Sigma Model
Mizher, Ana Julia; Fraga, Eduardo S. [Instituto de Fisica, Universidade Federal do Rio de Janeiro, Caixa Postal 68528, Rio de Janeiro, RJ 21941-972 (Brazil)
2009-04-01
Motivated by the possibility of the formation of CP-odd domains in heavy ion collisions, we investigate the effects of CP violation on the chiral transition within the linear sigma model with two flavors of quarks. We also study how the CP-odd system is affected by the presence of a strong magnetic field, that is presumably generated in a non-central heavy ion collision. We find that both ingredients play an important role, influencing drastically the nature of the phase transition and the critical temperature.
Linear Amplifier Model for Optomechanical Systems
Botter, Thierry; Brahms, Nathan; Schreppler, Sydney; Stamper-Kurn, Dan M
2011-01-01
We model optomechanical systems as linear optical amplifiers. This provides a unified treatment of diverse optomechanical phenomena. We emphasize, in particular, the relationship between ponderomotive squeezing and optomechanically induced transparency, two foci of current research. We characterize the amplifier response to quantum and deliberately applied fluctuations, both optical and mechanical. Further, we apply these results to establish quantum limits on external force sensing both on and off cavity resonance. We find that the maximum sensitivity attained on resonance constitutes an absolute upper limit, not surpassed when detuning off cavity resonance. The theory can be extended to a two-sided cavity with losses and limited detection efficiency.
Piecewise Linear Model-Based Image Enhancement
Fabrizio Russo
2004-09-01
Full Text Available A novel technique for the sharpening of noisy images is presented. The proposed enhancement system adopts a simple piecewise linear (PWL function in order to sharpen the image edges and to reduce the noise. Such effects can easily be controlled by varying two parameters only. The noise sensitivity of the operator is further decreased by means of an additional filtering step, which resorts to a nonlinear model too. Results of computer simulations show that the proposed sharpening system is simple and effective. The application of the method to contrast enhancement of color images is also discussed.
An introduction to hierarchical linear modeling
Heather Woltman
2012-02-01
Full Text Available This tutorial aims to introduce Hierarchical Linear Modeling (HLM. A simple explanation of HLM is provided that describes when to use this statistical technique and identifies key factors to consider before conducting this analysis. The first section of the tutorial defines HLM, clarifies its purpose, and states its advantages. The second section explains the mathematical theory, equations, and conditions underlying HLM. HLM hypothesis testing is performed in the third section. Finally, the fourth section provides a practical example of running HLM, with which readers can follow along. Throughout this tutorial, emphasis is placed on providing a straightforward overview of the basic principles of HLM.
Linear Parametric Model Checking of Timed Automata
Hune, Tohmas Seidelin; Romijn, Judi; Stoelinga, Mariëlle
2001-01-01
of a subclass of parametric timed automata (L/U automata), for which the emptiness problem is decidable, contrary to the full class where it is know to be undecidable. Also we present a number of lemmas enabling the verication eort to be reduced for L/U automata in some cases. We illustrate our approach......We present an extension of the model checker Uppaal capable of synthesize linear parameter constraints for the correctness of parametric timed automata. The symbolic representation of the (parametric) state-space is shown to be correct. A second contribution of this paper is the identication...
F-theory and linear sigma models
Bershadsky, M; Greene, Brian R; Johansen, A; Lazaroiu, C I
1998-01-01
We present an explicit method for translating between the linear sigma model and the spectral cover description of SU(r) stable bundles over an elliptically fibered Calabi-Yau manifold. We use this to investigate the 4-dimensional duality between (0,2) heterotic and F-theory compactifications. We indirectly find that much interesting heterotic information must be contained in the `spectral bundle' and in its dual description as a gauge theory on multiple F-theory 7-branes. A by-product of these efforts is a method for analyzing semistability and the splitting type of vector bundles over an elliptic curve given as the sheaf cohomology of a monad.
Ira Remsen, saccharin, and the linear model.
Warner, Deborah J
2008-03-01
While working in the chemistry laboratory at Johns Hopkins University, Constantin Fahlberg oxidized the 'ortho-sulfamide of benzoic acid' and, by chance, found the result to be incredibly sweet. Several years later, now working on his own, he termed this stuff saccharin, developed methods of making it in quantity, obtained patents on these methods, and went into production. As the industrial and scientific value of saccharin became apparent, Ira Remsen pointed out that the initial work had been done in his laboratory and at his suggestion. The ensuing argument, carried out in the courts of law and public opinion, illustrates the importance of the linear model to scientists who staked their identities on the model of disinterested research but who also craved credit for important practical results.
Impact of reactive settler models on simulated WWTP performance.
Gernaey, K V; Jeppsson, U; Batstone, D J; Ingildsen, P
2006-01-01
Including a reactive settler model in a wastewater treatment plant model allows representation of the biological reactions taking place in the sludge blanket in the settler, something that is neglected in many simulation studies. The idea of including a reactive settler model is investigated for an ASM1 case study. Simulations with a whole plant model including the non-reactive Takács settler model are used as a reference, and are compared to simulation results considering two reactive settler models. The first is a return sludge model block removing oxygen and a user-defined fraction of nitrate, combined with a non-reactive Takács settler. The second is a fully reactive ASM1 Takács settler model. Simulations with the ASM1 reactive settler model predicted a 15.3% and 7.4% improvement of the simulated N removal performance, for constant (steady-state) and dynamic influent conditions respectively. The oxygen/nitrate return sludge model block predicts a 10% improvement of N removal performance under dynamic conditions, and might be the better modelling option for ASM1 plants: it is computationally more efficient and it will not overrate the importance of decay processes in the settler.
Modeling hierarchical structures - Hierarchical Linear Modeling using MPlus
Jelonek, M
2006-01-01
The aim of this paper is to present the technique (and its linkage with physics) of overcoming problems connected to modeling social structures, which are typically hierarchical. Hierarchical Linear Models provide a conceptual and statistical mechanism for drawing conclusions regarding the influence of phenomena at different levels of analysis. In the social sciences it is used to analyze many problems such as educational, organizational or market dilemma. This paper introduces the logic of modeling hierarchical linear equations and estimation based on MPlus software. I present my own model to illustrate the impact of different factors on school acceptation level.
Upscaling heterogeneity in aquifer reactivity via exposure-time concept: forward model.
Seeboonruang, Uma; Ginn, Timothy R
2006-03-20
Reactive properties of aquifer solid phase materials play an important role in solute fate and transport in the natural subsurface on time scales ranging from years in contaminant remediation to millennia in dynamics of aqueous geochemistry. Quantitative tools for dealing with the impact of natural heterogeneity in solid phase reactivity on solute fate and transport are limited. Here we describe the use of a structural variable to keep track of solute flux exposure to reactive surfaces. With this approach, we develop a non-reactive tracer model that is useful for determining the signature of multi-scale reactive solid heterogeneity in terms of solute flux distributions at the field scale, given realizations of three-dimensional reactive site density fields. First, a governing Eulerian equation for the non-reactive tracer model is determined by an upscaling technique in which it is found that the exposure time of solution to reactive surface areas evolves via both a macroscopic velocity and a macroscopic dispersion in the artificial dimension of exposure time. Second, we focus on the Lagrangian approach in the context of a streamtube ensemble and demonstrate the use of the distribution of solute flux over the exposure time dimension in modeling two-dimensional transport of a solute undergoing simplified linear reversible reactions, in hypothetical conditions following prior laboratory experiments. The distribution of solute flux over exposure time in a given case is a signature of the impact of heterogeneous aquifer reactivity coupled with a particular physical heterogeneity, boundary conditions, and hydraulic gradient. Rigorous application of this approach in a simulation sense is limited here to linear kinetically controlled reactions.
Reactive burn models and ignition & growth concept
Menikoff, Ralph S [Los Alamos National Laboratory; Shaw, Milton S [Los Alamos National Laboratory
2010-01-01
Plastic-bonded explosives are heterogeneous materials. Experimentally, shock initiation is sensitive to small amounts of porosity, due to the formation of hot spots (small localized regions of high temperature). This leads to the Ignition and Growth concept, introduced by Lee and Tarver in 1980, as the basis for reactive burn models. A homogeneized burn rate needs to account for three mesoscale physical effects (i) the density of burnt hot spots, which depends on the lead shock strength; (ii) the growth of the burn fronts triggered by hot spots, which depends on the local deflagration speed; (iii) a geometric factor that accounts for the overlap of deflagration wavelets from adjacent hot spots. These effects can be combined and the burn model defined by specifying the reaction progress variable {lambda}(t) as a function of a dimensionless reaction length {tau}{sub hs}(t)/{ell}{sub hs}, rather than by xpecifying an explicit burn rate. The length scale {ell}{sub hs} is the average distance between hot spots, which is proportional to [N{sub hs}(P{sub s})]{sup -1/3}, where N{sub hs} is the number density of hot spots activated by the lead shock. The reaction length {tau}{sub hs}(t) = {line_integral}{sub 0}{sup t} D(P(t'))dt' is the distance the burn front propagates from a single hot spot, where D is the deflagration speed and t is the time since the shock arrival. A key implementation issue is how to determine the lead shock strength in conjunction with a shock capturing scheme. They have developed a robust algorithm for this purpose based on the Hugoniot jump condition for the energy. The algorithm utilizes the time dependence of density, pressure and energy within each cell. The method is independent of the numerical dissipation used for shock capturing. It is local and can be used in one or more space dimensions. The burn model has a small number of parameters which can be calibrated to fit velocity gauge data from shock initiation experiments.
Reactive burn models and ignition & growth concept
Shaw M.S.
2011-01-01
Full Text Available Plastic-bonded explosives are heterogeneous materials. Experimentally, shock initiation is sensitive to small amounts of porosity, due to the formation of hot spots (small localized regions of high temperature. This leads to the Ignition & Growth concept, introduced by LeeTarver in 1980, as the basis for reactive burn models. A homo- genized burn rate needs to account for three meso-scale physical effects: (i the density of active hot spots or burn centers; (ii the growth of the burn fronts triggered by the burn centers; (iii a geometric factor that accounts for the overlap of deflagration wavelets from adjacent burn centers. These effects can be combined and the burn model defined by specifying the reaction progress variable λ = g(s as a function of a dimensionless reaction length s(t = rbc/ℓbc, rather than by specifying an explicit burn rate. The length scale ℓbc(Ps = [Nbc(Ps]−1/3 is the average distance between burn centers, where Nbc is the number density of burn centers activated by the lead shock. The reaction length rbc(t = ∫t0 D(P(t′dt′ is the distance the burn front propagates from a single burn center, where D(P is the deflagration speed as a function of the local pressure and t is the time since the shock arrival. A key implementation issue is how to determine the lead shock strength in conjunction with a shock capturing scheme. We have developed a robust algorithm for this purpose based on the Hugoniot jump condition for the energy. The algorithm utilizes the time dependence of density, pressure and energy within each cell. The method is independent of the numerical dissipation used for shock capturing. It is local and can be used in one or more space dimensions. The burn model has a small number of parameters which can be calibrated to fit velocity gauge data from shock initiation experiments.
Linear models in the mathematics of uncertainty
Mordeson, John N; Clark, Terry D; Pham, Alex; Redmond, Michael A
2013-01-01
The purpose of this book is to present new mathematical techniques for modeling global issues. These mathematical techniques are used to determine linear equations between a dependent variable and one or more independent variables in cases where standard techniques such as linear regression are not suitable. In this book, we examine cases where the number of data points is small (effects of nuclear warfare), where the experiment is not repeatable (the breakup of the former Soviet Union), and where the data is derived from expert opinion (how conservative is a political party). In all these cases the data is difficult to measure and an assumption of randomness and/or statistical validity is questionable. We apply our methods to real world issues in international relations such as nuclear deterrence, smart power, and cooperative threat reduction. We next apply our methods to issues in comparative politics such as successful democratization, quality of life, economic freedom, political stability, and fail...
Marginal linearization method in modeling on fuzzy control systems
无
2003-01-01
Marginal linearization method in modeling on fuzzy control systems is proposed, which is to deal with the nonlinear model with variable coefficients. The method can turn a nonlinear model with variable coefficients into a linear model with variable coefficients in the way that the membership functions of the fuzzy sets in fuzzy partitions of the universes are changed from triangle waves into rectangle waves. However, the linearization models are incomplete in their forms because of their lacking some items. For solving this problem, joint approximation by using linear models is introduced. The simulation results show that marginal linearization models are of higher approximation precision than their original nonlinear models.
Reactive puff model SCICHEM: Model enhancements and performance studies
Chowdhury, B.; Karamchandani, P. K.; Sykes, R. I.; Henn, D. S.; Knipping, E.
2015-09-01
The SCICHEM model incorporates complete gas phase, aqueous and aerosol phase chemistry within a state-of-the-science Gaussian puff model SCIPUFF (Second-order Closure Integrated Puff). The model is a valuable tool that can be used to calculate the impacts of a single source or a small number of sources on downwind ozone and PM2.5. The model has flexible data requirements: it can be run with routine surface and upper air observations or with prognostic meteorological model outputs and source emissions are specified in a simple text format. This paper describes significant advances to the dispersion and chemistry components of the model in the latest release, SCICHEM 3.0. Some of the major advancements include modeling of skewed turbulence for convective boundary layer and updated chemistry schemes (CB05 gas phase chemical mechanism; AERO5 aerosol and aqueous modules). The results from SCICHEM 3.0 are compared with observations from a tracer study as well as aircraft measurements of reactive species in power plant plumes from two field studies. The results with the tracer experiment (Copenhagen study) show that the incorporation of skewed turbulence improves the calculation of tracer dispersion and transport. The comparisons with the Cumberland and Dolet Hills power plume measurements show good correlation between the observed and predicted concentrations of reactive gaseous species at most downwind distances from the source.
Investigation of kinetics model of dc reactive sputtering
朱圣龙; 王福会; 吴维叓
1996-01-01
A novel physical sputtering kinetics model for reactive sputtering is presented.Reactive gas gettering effects and interactions among the characteristic parameters have been taken into account in the model.The data derived from the model accorded fairly well with experimental results.The relationship between the values of initial oxide coverage on the target and the ready states was depicted in the model.This relationship gives reasons for the difference of the threshold of reactive gas fluxes (Q) from the metal sputtering region to the oxide sputtering region and in reverse direction.The discontinuities in oxide coverage on the target surface (θ) versus reactive gas fluxes (Q) are referred to as the effects of reactive gas partial pressure (p) upon the forming rates of oxide on the surfaces of target (V0).The diversity of the oxygen flux threshold results from the variance of the initial values of oxide coverage on target.
Non-Linear Sigma Model on Conifolds
Parthasarathy, R
2002-01-01
Explicit solutions to the conifold equations with complex dimension $n=3,4$ in terms of {\\it{complex coordinates (fields)}} are employed to construct the Ricci-flat K\\"{a}hler metrics on these manifolds. The K\\"{a}hler 2-forms are found to be closed. The complex realization of these conifold metrics are used in the construction of 2-dimensional non-linear sigma model with the conifolds as target spaces. The action for the sigma model is shown to be bounded from below. By a suitable choice of the 'integration constants', arising in the solution of Ricci flatness requirement, the metric and the equations of motion are found to be {\\it{non-singular}}. As the target space is Ricci flat, the perturbative 1-loop counter terms being absent, the model becomes topological. The inherent U(1) fibre over the base of the conifolds is shown to correspond to a gauge connection in the sigma model. The same procedure is employed to construct the metric for the resolved conifold, in terms of complex coordinates and the action ...
Interacting Dark Energy Models -- Scalar Linear Perturbations
Perico, E L D
2016-01-01
We extend the dark sector interacting models assuming the dark energy as the sum of independent contributions $\\rho_{\\Lambda} =\\sum_i\\rho_{\\Lambda i}$, associated with (and interacting with) each of the $i$ material species. We derive the linear scalar perturbations for two interacting dark energy scenarios, modeling its cosmic evolution and identifying their different imprints in the CMB and matter power spectrum. Our treatment was carried out for two phenomenological motivated expressions of the dark energy density, $\\rho_\\Lambda(H^2)$ and $\\rho_\\Lambda(R)$. The $\\rho_\\Lambda(H^2)$ description turned out to be a full interacting model, i.e., the dark energy interacts with everyone material species in the universe, whereas the $\\rho_\\Lambda(R)$ description only leads to interactions between dark energy and the non-relativistic matter components; which produces different imprints of the two models on the matter power spectrum. A comparison with the Planck 2015 data was made in order to constrain the free para...
F-theory and linear sigma models
Bershadsky, M.; Johansen, A. [Harvard Univ., Cambridge, MA (United States). Lyman Lab. of Physics; Chiang, T.M. [Newman Laboratory of Nuclear Studies, Cornell University, Ithaca, NY 14850 (United States); Greene, B.R.; Lazaroiu, C.I. [Departments of Physics and Mathematics, Columbia University, New York, NY 10027 (United States)
1998-09-07
We present an explicit method for translating between the linear sigma model and the spectral cover description of SU(r) stable bundles over an elliptically fibered Calabi-Yau manifold. We use this to investigate the four-dimensional duality between (0,2) heterotic and F-theory compactifications. We indirectly find that much interesting heterotic information must be contained in the `spectral bundle` and in its dual description as a gauge theory on multiple F-theory 7-branes. A by-product of these efforts is a method for analyzing semistability and the splitting type of vector bundles over an elliptic curve given as the sheaf cohomology of a monad. (orig.) 24 refs.
Distributed static linear Gaussian models using consensus.
Belanovic, Pavle; Valcarcel Macua, Sergio; Zazo, Santiago
2012-10-01
Algorithms for distributed agreement are a powerful means for formulating distributed versions of existing centralized algorithms. We present a toolkit for this task and show how it can be used systematically to design fully distributed algorithms for static linear Gaussian models, including principal component analysis, factor analysis, and probabilistic principal component analysis. These algorithms do not rely on a fusion center, require only low-volume local (1-hop neighborhood) communications, and are thus efficient, scalable, and robust. We show how they are also guaranteed to asymptotically converge to the same solution as the corresponding existing centralized algorithms. Finally, we illustrate the functioning of our algorithms on two examples, and examine the inherent cost-performance trade-off.
To Model Chemical Reactivity in Heterogeneous Emulsions, Think Homogeneous Microemulsions.
Bravo-Díaz, Carlos; Romsted, Laurence Stuart; Liu, Changyao; Losada-Barreiro, Sonia; Pastoriza-Gallego, Maria José; Gao, Xiang; Gu, Qing; Krishnan, Gunaseelan; Sánchez-Paz, Verónica; Zhang, Yongliang; Dar, Aijaz Ahmad
2015-08-25
Two important and unsolved problems in the food industry and also fundamental questions in colloid chemistry are how to measure molecular distributions, especially antioxidants (AOs), and how to model chemical reactivity, including AO efficiency in opaque emulsions. The key to understanding reactivity in organized surfactant media is that reaction mechanisms are consistent with a discrete structures-separate continuous regions duality. Aggregate structures in emulsions are determined by highly cooperative but weak organizing forces that allow reactants to diffuse at rates approaching their diffusion-controlled limit. Reactant distributions for slow thermal bimolecular reactions are in dynamic equilibrium, and their distributions are proportional to their relative solubilities in the oil, interfacial, and aqueous regions. Our chemical kinetic method is grounded in thermodynamics and combines a pseudophase model with methods for monitoring the reactions of AOs with a hydrophobic arenediazonium ion probe in opaque emulsions. We introduce (a) the logic and basic assumptions of the pseudophase model used to define the distributions of AOs among the oil, interfacial, and aqueous regions in microemulsions and emulsions and (b) the dye derivatization and linear sweep voltammetry methods for monitoring the rates of reaction in opaque emulsions. Our results show that this approach provides a unique, versatile, and robust method for obtaining quantitative estimates of AO partition coefficients or partition constants and distributions and interfacial rate constants in emulsions. The examples provided illustrate the effects of various emulsion properties on AO distributions such as oil hydrophobicity, emulsifier structure and HLB, temperature, droplet size, surfactant charge, and acidity on reactant distributions. Finally, we show that the chemical kinetic method provides a natural explanation for the cut-off effect, a maximum followed by a sharp reduction in AO efficiency with
The General Linear Model as Structural Equation Modeling
Graham, James M.
2008-01-01
Statistical procedures based on the general linear model (GLM) share much in common with one another, both conceptually and practically. The use of structural equation modeling path diagrams as tools for teaching the GLM as a body of connected statistical procedures is presented. A heuristic data set is used to demonstrate a variety of univariate…
Testing Linear Models for Ability Parameters in Item Response Models
Glas, Cees A.W.; Hendrawan, Irene
2005-01-01
Methods for testing hypotheses concerning the regression parameters in linear models for the latent person parameters in item response models are presented. Three tests are outlined: A likelihood ratio test, a Lagrange multiplier test and a Wald test. The tests are derived in a marginal maximum like
Modelling atmospheric OH-reactivity in a boreal forest ecosystem
Mogensen, D.; Smolander, S.; Sogachev, Andrey;
2011-01-01
We have modelled the total atmospheric OH-reactivity in a boreal forest and investigated the individual contributions from gas phase inorganic species, isoprene, monoterpenes, and methane along with other important VOCs. Daily and seasonal variation in OH-reactivity for the year 2008 was examined...... as well as the vertical OH-reactivity profile. We have used SOSA; a one dimensional vertical chemistry-transport model (Boy et al., 2011a) together with measurements from Hyytiala, SMEAR II station, Southern Finland, conducted in August 2008. Model simulations only account for similar to 30......-50% of the total measured OH sink, and in our opinion, the reason for missing OH-reactivity is due to unmeasured unknown BVOCs, and limitations in our knowledge of atmospheric chemistry including uncertainties in rate constants. Furthermore, we found that the OH-reactivity correlates with both organic...
Modelling atmospheric OH-reactivity in a boreal forest ecosystem
Mogensen, D.; Smolander, S.; Sogachev, Andrey;
2011-01-01
We have modelled the total atmospheric OH-reactivity in a boreal forest and investigated the individual contributions from gas phase inorganic species, isoprene, monoterpenes, and methane along with other important VOCs. Daily and seasonal variation in OH-reactivity for the year 2008 was examined...
Piecewise Linear-Linear Latent Growth Mixture Models with Unknown Knots
Kohli, Nidhi; Harring, Jeffrey R.; Hancock, Gregory R.
2013-01-01
Latent growth curve models with piecewise functions are flexible and useful analytic models for investigating individual behaviors that exhibit distinct phases of development in observed variables. As an extension of this framework, this study considers a piecewise linear-linear latent growth mixture model (LGMM) for describing segmented change of…
Thurstonian models for sensory discrimination tests as generalized linear models
Brockhoff, Per B.; Christensen, Rune Haubo Bojesen
2010-01-01
Sensory discrimination tests such as the triangle, duo-trio, 2-AFC and 3-AFC tests produce binary data and the Thurstonian decision rule links the underlying sensory difference 6 to the observed number of correct responses. In this paper it is shown how each of these four situations can be viewed...... as a so-called generalized linear model. The underlying sensory difference 6 becomes directly a parameter of the statistical model and the estimate d' and it's standard error becomes the "usual" output of the statistical analysis. The d' for the monadic A-NOT A method is shown to appear as a standard...... linear contrast in a generalized linear model using the probit link function. All methods developed in the paper are implemented in our free R-package sensR (http://www.cran.r-project.org/package=sensR/). This includes the basic power and sample size calculations for these four discrimination tests...
Pascale KULISA; Cédric DANO
2006-01-01
Three linear two-equation turbulence models k- ε, k- ω and k- 1 and a non-linear k- l model are used for aerodynamic and thermal turbine flow prediction. The pressure profile in the wake and the heat transfer coefficient on the blade are compared with experimental data. Good agreement is obtained with the linear k- l model. No significant modifications are observed with the non-linear model. The balance of transport equation terms in the blade wake is also presented. Linear and non-linear k- l models are evaluated to predict the threedimensional vortices characterising the turbine flows. The simulations show that the passage vortex is the main origin of the losses.
Hierarchical linear regression models for conditional quantiles
TIAN Maozai; CHEN Gemai
2006-01-01
The quantile regression has several useful features and therefore is gradually developing into a comprehensive approach to the statistical analysis of linear and nonlinear response models,but it cannot deal effectively with the data with a hierarchical structure.In practice,the existence of such data hierarchies is neither accidental nor ignorable,it is a common phenomenon.To ignore this hierarchical data structure risks overlooking the importance of group effects,and may also render many of the traditional statistical analysis techniques used for studying data relationships invalid.On the other hand,the hierarchical models take a hierarchical data structure into account and have also many applications in statistics,ranging from overdispersion to constructing min-max estimators.However,the hierarchical models are virtually the mean regression,therefore,they cannot be used to characterize the entire conditional distribution of a dependent variable given high-dimensional covariates.Furthermore,the estimated coefficient vector (marginal effects)is sensitive to an outlier observation on the dependent variable.In this article,a new approach,which is based on the Gauss-Seidel iteration and taking a full advantage of the quantile regression and hierarchical models,is developed.On the theoretical front,we also consider the asymptotic properties of the new method,obtaining the simple conditions for an n1/2-convergence and an asymptotic normality.We also illustrate the use of the technique with the real educational data which is hierarchical and how the results can be explained.
Non linear behaviour of cell tensegrity models
Alippi, A.; Bettucci, A.; Biagioni, A.; Conclusio, D.; D'Orazio, A.; Germano, M.; Passeri, D.
2012-05-01
Tensegrity models for the cytoskeleton structure of living cells is largely used nowadays for interpreting the biochemical response of living tissues to mechanical stresses. Microtubules, microfilaments and filaments are the microscopic cell counterparts of struts (microtubules) and cables (microfilaments and filaments) in the macroscopic world: the formers oppose to compression, the latters to tension, thus yielding an overall structure, light and highly deformable. Specific cell surface receptors, such as integrins, act as the coupling elements that transmit the outside mechanical stress state into the cell body. Reversible finite deformations of tensegrity structures have been widely demonstrated experimentally and in a number of living cell simulations. In the present paper, the bistability behaviour of two general models, the linear bar oscillator and the icosahedron, is studied, as they are both obtained from mathematical simulation, the former, and from larger scale experiments, the latter. The discontinuity in the frequency response of the oscillation amplitude and the lateral bending of the resonance curves are put in evidence, as it grows larger as the driving amplitude increases, respectively.
Models of reactive oxygen species in cancer
Lu, Weiqin; Ogasawara, Marcia A.; Huang, Peng
2007-01-01
Increased generation of reactive oxygen species (ROS) has been observed in cancer, degenerative diseases, and other pathological conditions. ROS can stimulate cell proliferation, promote genetic instability, and induce adaptive responses that enable cancer cells to maintain their malignant phenotypes. However, when cellular redox balance is severely disturbed, high levels of ROS may cause various damages leading to cell death. The studies of ROS effects on biological systems, their underlying...
Axioms and Models of Linear Logic
Hesselink, Wim H.
1990-01-01
Girard's recent system of linear logic is presented in a way that avoids the two-level structure of formulae and sequents, and that minimises the number of primitive function symbols. A deduction theorem is proved concerning the classical implication as embedded in linear logic. The Hilbert-style ax
Misaligned Image Integration With Local Linear Model.
Baba, Tatsuya; Matsuoka, Ryo; Shirai, Keiichiro; Okuda, Masahiro
2016-05-01
We present a new image integration technique for a flash and long-exposure image pair to capture a dark scene without incurring blurring or noisy artifacts. Most existing methods require well-aligned images for the integration, which is often a burdensome restriction in practical use. We address this issue by locally transferring the colors of the flash images using a small fraction of the corresponding pixels in the long-exposure images. We formulate the image integration as a convex optimization problem with the local linear model. The proposed method makes it possible to integrate the color of the long-exposure image with the detail of the flash image without causing any harmful effects to its contrast, where we do not need perfect alignment between the images by virtue of our new integration principle. We show that our method successfully outperforms the state of the art in the image integration and reference-based color transfer for challenging misaligned data sets.
Linearized Functional Minimization for Inverse Modeling
Wohlberg, Brendt [Los Alamos National Laboratory; Tartakovsky, Daniel M. [University of California, San Diego; Dentz, Marco [Institute of Environmental Assessment and Water Research, Barcelona, Spain
2012-06-21
Heterogeneous aquifers typically consist of multiple lithofacies, whose spatial arrangement significantly affects flow and transport. The estimation of these lithofacies is complicated by the scarcity of data and by the lack of a clear correlation between identifiable geologic indicators and attributes. We introduce a new inverse-modeling approach to estimate both the spatial extent of hydrofacies and their properties from sparse measurements of hydraulic conductivity and hydraulic head. Our approach is to minimize a functional defined on the vectors of values of hydraulic conductivity and hydraulic head fields defined on regular grids at a user-determined resolution. This functional is constructed to (i) enforce the relationship between conductivity and heads provided by the groundwater flow equation, (ii) penalize deviations of the reconstructed fields from measurements where they are available, and (iii) penalize reconstructed fields that are not piece-wise smooth. We develop an iterative solver for this functional that exploits a local linearization of the mapping from conductivity to head. This approach provides a computationally efficient algorithm that rapidly converges to a solution. A series of numerical experiments demonstrates the robustness of our approach.
Modeling a Linear Generator for Energy Harvesting Applications
2014-12-01
their potential uses. A flexible model of a linear generator created in MATLAB Simulink is presented. The model is a three-phase, 12-pole, non-salient...attention to linear generators and their potential uses. A flexible model of a linear generator created in MATLAB Simulink is presented. The model...Chapter III and the full MATLAB and Simulink code can be found in the Appendix. Several adaptations of the model have been created, with the results
A synchronous paradigm for modeling stable reactive systems
Winter, V.L.
1998-12-01
This paper describes a modeling technique for single-agent reactive systems, that is influenced by the modeling paradigm of Parnas as well as by the synchronous paradigms of LUSTRE and ESTEREL. In this paradigm, single-agent reactive systems are modeled in a universe having a discrete clock. This discretization of time greatly reduces the temporal complexity of the model. He believes that the advantage of this reduction in temporal complexity is that the resulting model is in many ways better suited to automated software construction and analysis techniques (e.g., deductive synthesis, transformation, and verification) than models that are based on continuous representations of time.
Modeling hierarchical structures - Hierarchical Linear Modeling using MPlus
Jelonek, Magdalena
2006-01-01
The aim of this paper is to present the technique (and its linkage with physics) of overcoming problems connected to modeling social structures, which are typically hierarchical. Hierarchical Linear Models provide a conceptual and statistical mechanism for drawing conclusions regarding the influence of phenomena at different levels of analysis. In the social sciences it is used to analyze many problems such as educational, organizational or market dilemma. This paper introduces the logic of m...
Modeling Biodegradation and Reactive Transport: Analytical and Numerical Models
Sun, Y; Glascoe, L
2005-06-09
The computational modeling of the biodegradation of contaminated groundwater systems accounting for biochemical reactions coupled to contaminant transport is a valuable tool for both the field engineer/planner with limited computational resources and the expert computational researcher less constrained by time and computer power. There exists several analytical and numerical computer models that have been and are being developed to cover the practical needs put forth by users to fulfill this spectrum of computational demands. Generally, analytical models provide rapid and convenient screening tools running on very limited computational power, while numerical models can provide more detailed information with consequent requirements of greater computational time and effort. While these analytical and numerical computer models can provide accurate and adequate information to produce defensible remediation strategies, decisions based on inadequate modeling output or on over-analysis can have costly and risky consequences. In this chapter we consider both analytical and numerical modeling approaches to biodegradation and reactive transport. Both approaches are discussed and analyzed in terms of achieving bioremediation goals, recognizing that there is always a tradeoff between computational cost and the resolution of simulated systems.
Analysis of linear trade models and relation to scale economies.
Gomory, R E; Baumol, W J
1997-09-01
We discuss linear Ricardo models with a range of parameters. We show that the exact boundary of the region of equilibria of these models is obtained by solving a simple integer programming problem. We show that there is also an exact correspondence between many of the equilibria resulting from families of linear models and the multiple equilibria of economies of scale models.
Thermal-hydraulic modeling of reactivity accidents in MTR reactors
Khater Hany
2006-01-01
Full Text Available This paper describes the development of a dynamic model for the thermal-hydraulic analysis of MTR research reactors during a reactivity insertion accident. The model is formulated for coupling reactor kinetics with feedback reactivity and reactor core thermal-hydraulics. To represent the reactor core, two types of channels are considered, average and hot channels. The developed computer program is compiled and executed on a personal computer, using the FORTRAN language. The model is validated by safety-related benchmark calculations for MTR-TYPE reactors of IAEA 10 MW generic reactor for both slow and fast reactivity insertion transients. A good agreement is shown between the present model and the benchmark calculations. Then, the model is used for simulating the uncontrolled withdrawal of a control rod of an ETRR-2 reactor in transient with over power scram trip. The model results for ETRR-2 are analyzed and discussed.
Model averaging for semiparametric additive partial linear models
无
2010-01-01
To improve the prediction accuracy of semiparametric additive partial linear models(APLM) and the coverage probability of confidence intervals of the parameters of interest,we explore a focused information criterion for model selection among ALPM after we estimate the nonparametric functions by the polynomial spline smoothing,and introduce a general model average estimator.The major advantage of the proposed procedures is that iterative backfitting implementation is avoided,which thus results in gains in computational simplicity.The resulting estimators are shown to be asymptotically normal.A simulation study and a real data analysis are presented for illustrations.
Admissibilities of linear estimator in a class of linear models with a multivariate t error variable
无
2010-01-01
This paper discusses admissibilities of estimators in a class of linear models,which include the following common models:the univariate and multivariate linear models,the growth curve model,the extended growth curve model,the seemingly unrelated regression equations,the variance components model,and so on.It is proved that admissible estimators of functions of the regression coefficient β in the class of linear models with multivariate t error terms,called as Model II,are also ones in the case that error terms have multivariate normal distribution under a strictly convex loss function or a matrix loss function.It is also proved under Model II that the usual estimators of β are admissible for p 2 with a quadratic loss function,and are admissible for any p with a matrix loss function,where p is the dimension of β.
Linear control theory for gene network modeling.
Shin, Yong-Jun; Bleris, Leonidas
2010-09-16
Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain) and linear state-space (time domain) can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.
Linear Factor Models and the Estimation of Expected Returns
Sarisoy, Cisil; de Goeij, Peter; Werker, Bas
2016-01-01
Linear factor models of asset pricing imply a linear relationship between expected returns of assets and exposures to one or more sources of risk. We show that exploiting this linear relationship leads to statistical gains of up to 31% in variances when estimating expected returns on individual asse
Andersen, Per Kragh; Klein, John P.; Rosthøj, Susanne
2003-01-01
Generalised estimating equation; Generalised linear model; Jackknife pseudo-value; Logistic regression; Markov Model; Multi-state model......Generalised estimating equation; Generalised linear model; Jackknife pseudo-value; Logistic regression; Markov Model; Multi-state model...
Chemical reactor modeling multiphase reactive flows
Jakobsen, Hugo A
2014-01-01
Chemical Reactor Modeling closes the gap between Chemical Reaction Engineering and Fluid Mechanics. The second edition consists of two volumes: Volume 1: Fundamentals. Volume 2: Chemical Engineering Applications In volume 1 most of the fundamental theory is presented. A few numerical model simulation application examples are given to elucidate the link between theory and applications. In volume 2 the chemical reactor equipment to be modeled are described. Several engineering models are introduced and discussed. A survey of the frequently used numerical methods, algorithms and schemes is provided. A few practical engineering applications of the modeling tools are presented and discussed. The working principles of several experimental techniques employed in order to get data for model validation are outlined. The monograph is based on lectures regularly taught in the fourth and fifth years graduate courses in transport phenomena and chemical reactor modeling, and in a post graduate course in modern reactor m...
Error Control of Iterative Linear Solvers for Integrated Groundwater Models
Dixon, Matthew; Brush, Charles; Chung, Francis; Dogrul, Emin; Kadir, Tariq
2010-01-01
An open problem that arises when using modern iterative linear solvers, such as the preconditioned conjugate gradient (PCG) method or Generalized Minimum RESidual method (GMRES) is how to choose the residual tolerance in the linear solver to be consistent with the tolerance on the solution error. This problem is especially acute for integrated groundwater models which are implicitly coupled to another model, such as surface water models, and resolve both multiple scales of flow and temporal interaction terms, giving rise to linear systems with variable scaling. This article uses the theory of 'forward error bound estimation' to show how rescaling the linear system affects the correspondence between the residual error in the preconditioned linear system and the solution error. Using examples of linear systems from models developed using the USGS GSFLOW package and the California State Department of Water Resources' Integrated Water Flow Model (IWFM), we observe that this error bound guides the choice of a prac...
Wahiddun Nisa
2016-05-01
Full Text Available In this paper non-linear model of the STATCOM is linearized and the following strategies have been adopted . Hence, a small signal model is adopted here. Here, the grid voltage lags the fundamental component of the STATCOM converter terminal voltage with a phase angle difference ' ' . Small signal modeling of the phase angle ' ' and modulation index ' m ' is also done. A single PI-controller for the reactive component current of the STATCOM has been designed. In this model, the DC-link capacitor voltage is held constant without using a separate controller. The STATCOM are designed using SVPWM technique. Through adjustment of the modulation index, fast modulation of the STATCOM reactive power output can be achieved due to high sensitivity of the same with respect to the output voltage of the STATCOM VSC. The model, with PI controllers has been simulated in MATLAB/SIMULINK environment with variation of the pre-charge voltage on the DClink capacitor with linear loads (inductive. Improvement of the power factor of the grid current is achieved for linear loads.
MODEL SELECTION FOR LOG-LINEAR MODELS OF CONTINGENCY TABLES
ZHAO Lincheng; ZHANG Hong
2003-01-01
In this paper, we propose an information-theoretic-criterion-based model selection procedure for log-linear model of contingency tables under multinomial sampling, and establish the strong consistency of the method under some mild conditions. An exponential bound of miss detection probability is also obtained. The selection procedure is modified so that it can be used in practice. Simulation shows that the modified method is valid. To avoid selecting the penalty coefficient in the information criteria, an alternative selection procedure is given.
Vuori, Kaarina; Strandén, Ismo; Sevón-Aimonen, Marja-Liisa; Mäntysaari, Esa A
2006-01-01
A method based on Taylor series expansion for estimation of location parameters and variance components of non-linear mixed effects models was considered. An attractive property of the method is the opportunity for an easily implemented algorithm. Estimation of non-linear mixed effects models can be done by common methods for linear mixed effects models, and thus existing programs can be used after small modifications. The applicability of this algorithm in animal breeding was studied with simulation using a Gompertz function growth model in pigs. Two growth data sets were analyzed: a full set containing observations from the entire growing period, and a truncated time trajectory set containing animals slaughtered prematurely, which is common in pig breeding. The results from the 50 simulation replicates with full data set indicate that the linearization approach was capable of estimating the original parameters satisfactorily. However, estimation of the parameters related to adult weight becomes unstable in the case of a truncated data set.
Hard-sphere kinetic models for inert and reactive mixtures
Polewczak, Jacek
2016-10-01
I consider stochastic variants of a simple reacting sphere (SRS) kinetic model (Xystris and Dahler 1978 J. Chem. Phys. 68 387-401, Qin and Dahler 1995 J. Chem. Phys. 103 725-50, Dahler and Qin 2003 J. Chem. Phys. 118 8396-404) for dense reacting mixtures. In contrast to the line-of-center models of chemical reactive models, in the SRS kinetic model, the microscopic reversibility (detailed balance) can be easily shown to be satisfied, and thus all mathematical aspects of the model can be fully justified. In the SRS model, the molecules behave as if they were single mass points with two internal states. Collisions may alter the internal states of the molecules, and this occurs when the kinetic energy associated with the reactive motion exceeds the activation energy. Reactive and non-reactive collision events are considered to be hard sphere-like. I consider a four component mixture A, B, A *, B *, in which the chemical reactions are of the type A+B\\rightleftharpoons {{A}\\ast}+{{B}\\ast} , with A * and B * being distinct species from A and B. This work extends the joined works with George Stell to the kinetic models of dense inert and reactive mixtures. The idea of introducing smearing-type effect in the collisional process results in a new class of stochastic kinetic models for both inert and reactive mixtures. In this paper the important new mathematical properties of such systems of kinetic equations are proven. The new results for stochastic revised Enskog system for inert mixtures are also provided.
Modeling of titration experiments by a reactive transport model
Ma Hongyun; Samper Javier; Xin Xin
2011-01-01
Acid mine drainage (AMD) is commonly treated by neutralization with alkaline substances. This treatment is supported by titration experiments that illustrate the buffering mechanisms and estimate the base neutralization capacity (BNC) of the AMD. Detailed explanation of titration curves requires modeling with a hydro-chemical model. In this study the titration curves of water samples from the drainage of the As Pontes mine and the corresponding dumps have been investigated and six buffers are selected by analyzing those curves. Titration curves have been simulated by a reactive transport model to discover the detailed buffering mechanisms. These simulations show seven regions involving different buffering mechanism. The BNC is primarily from buffers of dissolved Fe, Al and hydrogen sulfate. The BNC can be approximated by: BNC = 3(CFe + CAl) + 0.05Csulfate, where the units are mol/L. The BNC of the sample from the mine is 9.25 × 10-3 mol/L and that of the dumps sample is 1.28 × 10-2 mol/L.
An analytically linearized helicopter model with improved modeling accuracy
Jensen, Patrick T.; Curtiss, H. C., Jr.; Mckillip, Robert M., Jr.
1991-01-01
An analytically linearized model for helicopter flight response including rotor blade dynamics and dynamic inflow, that was recently developed, was studied with the objective of increasing the understanding, the ease of use, and the accuracy of the model. The mathematical model is described along with a description of the UH-60A Black Hawk helicopter and flight test used to validate the model. To aid in utilization of the model for sensitivity analysis, a new, faster, and more efficient implementation of the model was developed. It is shown that several errors in the mathematical modeling of the system caused a reduction in accuracy. These errors in rotor force resolution, trim force and moment calculation, and rotor inertia terms were corrected along with improvements to the programming style and documentation. Use of a trim input file to drive the model is examined. Trim file errors in blade twist, control input phase angle, coning and lag angles, main and tail rotor pitch, and uniform induced velocity, were corrected. Finally, through direct comparison of the original and corrected model responses to flight test data, the effect of the corrections on overall model output is shown.
General linear matrix model, Minkowski spacetime and the Standard Model
Belyea, Chris
2010-01-01
The Hermitian matrix model with general linear symmetry is argued to decouple into a finite unitary matrix model that contains metastable multidimensional lattice configurations and a fermion determinant. The simplest metastable state is a Hermitian Weyl kinetic operator of either handedness on a 3+1 D lattice with general nonlocal interactions. The Hermiticity produces 16 effective Weyl fermions by species doubling, 8 left- and 8 right-handed. These are identified with a Standard Model generation. Only local non-anomalous gauge fields within the soup of general fluctuations can survive at long distances, and the degrees of freedom for gauge fields of an $SU(8)_L X SU(8)_R$ GUT are present. Standard Model gauge symmetries associate with particular species symmetries, for example change of QCD color associates with permutation of doubling status amongst space directions. Vierbein gravity is probably also generated. While fundamental Higgs fields are not possible, low fermion current masses can arise from chira...
3D Object Recognition Based on Linear Lie Algebra Model
LI Fang-xing; WU Ping-dong; SUN Hua-fei; PENG Lin-yu
2009-01-01
A surface model called the fibre bundle model and a 3D object model based on linear Lie algebra model are proposed.Then an algorithm of 3D object recognition using the linear Lie algebra models is presented.It is a convenient recognition method for the objects which are symmetric about some axis.By using the presented algorithm,the representation matrices of the fibre or the base curve from only finite points of the linear Lie algebra model can be obtained.At last some recognition results of practicalities are given.
Linear latent variable models: the lava-package
Holst, Klaus Kähler; Budtz-Jørgensen, Esben
2013-01-01
An R package for specifying and estimating linear latent variable models is presented. The philosophy of the implementation is to separate the model specification from the actual data, which leads to a dynamic and easy way of modeling complex hierarchical structures. Several advanced features are...... interface covering a broad range of non-linear generalized structural equation models is described. The model and software are demonstrated in data of measurements of the serotonin transporter in the human brain....
Model Identification of Linear Parameter Varying Aircraft Systems
Fujimore, Atsushi; Ljung, Lennart
2007-01-01
This article presents a parameter estimation of continuous-time polytopic models for a linear parameter varying (LPV) system. The prediction error method of linear time invariant (LTI) models is modified for polytopic models. The modified prediction error method is applied to an LPV aircraft system whose varying parameter is the flight velocity and model parameters are the stability and control derivatives (SCDs). In an identification simulation, the polytopic model is more suitable for expre...
Quantitative Models and Analysis for Reactive Systems
Thrane, Claus
phones and websites. Acknowledging that now more than ever, systems come in contact with the physical world, we need to revise the way we construct models and verification algorithms, to take into account the behavior of systems in the presence of approximate, or quantitative information, provided...... by the environment in which they are embedded. This thesis studies the semantics and properties of a model-based framework for re- active systems, in which models and specifications are assumed to contain quantifiable information, such as references to time or energy. Our goal is to develop a theory of approximation......, by studying how small changes to our models affect the verification results. A key source of motivation for this work can be found in The Embedded Systems Design Challenge [HS06] posed by Thomas A. Henzinger and Joseph Sifakis. It contains a call for advances in the state-of-the-art of systems verification...
Mathematical Models of Tuberculosis Reactivation and Relapse
Robert Steven Wallis
2016-05-01
Full Text Available The natural history of human infection with Mycobacterium tuberculosis (Mtb is highly variable, as is the response to treatment of active tuberculosis. There is presently no direct means to identify individuals in whom Mtb infection has been eradicated, whether by a bactericidal immune response or sterilizing antimicrobial chemotherapy. Mathematical models can assist in such circumstances by measuring or predicting events that cannot be directly observed. The 3 models discussed in this review illustrate instances in which mathematical models were used to identify individuals with innate resistance to Mtb infection, determine the etiology of tuberculosis in patients treated with tumor necrosis factor antagonists, and predict the risk of relapse in persons undergoing tuberculosis treatment. These examples illustrate the power of various types of mathematic models to increase knowledge and thereby inform interventions in the present global tuberculosis epidemic.
A Note on the Identifiability of Generalized Linear Mixed Models
Labouriau, Rodrigo
2014-01-01
I present here a simple proof that, under general regularity conditions, the standard parametrization of generalized linear mixed model is identifiable. The proof is based on the assumptions of generalized linear mixed models on the first and second order moments and some general mild regularity ...... conditions, and, therefore, is extensible to quasi-likelihood based generalized linear models. In particular, binomial and Poisson mixed models with dispersion parameter are identifiable when equipped with the standard parametrization......I present here a simple proof that, under general regularity conditions, the standard parametrization of generalized linear mixed model is identifiable. The proof is based on the assumptions of generalized linear mixed models on the first and second order moments and some general mild regularity...
OPTIMUM DESIGN AND NON-LINEAR MODEL OF POWERPLANT HYDRAULIC MOUNT SYSTEM
Shi Wenku; Min Haitao; Dang Zhaolong
2003-01-01
6-DOF non-linear mechanics model of powerplant hydraulic mount system is established. Optimum design of the powerplant hydraulic mount system is made with the hydraulic mount parameters as variables and with uncoupling of energy, rational disposition of nature frequency and minimum of reactive force at mount's location as objective functions. And based on the optimum design, software named ODPHMS (optimum design of powerplant hydraulic mount system) used in powerplant mount system optimum design is developed.
Assessment of parametric uncertainty for groundwater reactive transport modeling,
Shi, Xiaoqing; Ye, Ming; Curtis, Gary P.; Miller, Geoffery L.; Meyer, Philip D.; Kohler, Matthias; Yabusaki, Steve; Wu, Jichun
2014-01-01
The validity of using Gaussian assumptions for model residuals in uncertainty quantification of a groundwater reactive transport model was evaluated in this study. Least squares regression methods explicitly assume Gaussian residuals, and the assumption leads to Gaussian likelihood functions, model parameters, and model predictions. While the Bayesian methods do not explicitly require the Gaussian assumption, Gaussian residuals are widely used. This paper shows that the residuals of the reactive transport model are non-Gaussian, heteroscedastic, and correlated in time; characterizing them requires using a generalized likelihood function such as the formal generalized likelihood function developed by Schoups and Vrugt (2010). For the surface complexation model considered in this study for simulating uranium reactive transport in groundwater, parametric uncertainty is quantified using the least squares regression methods and Bayesian methods with both Gaussian and formal generalized likelihood functions. While the least squares methods and Bayesian methods with Gaussian likelihood function produce similar Gaussian parameter distributions, the parameter distributions of Bayesian uncertainty quantification using the formal generalized likelihood function are non-Gaussian. In addition, predictive performance of formal generalized likelihood function is superior to that of least squares regression and Bayesian methods with Gaussian likelihood function. The Bayesian uncertainty quantification is conducted using the differential evolution adaptive metropolis (DREAM(zs)) algorithm; as a Markov chain Monte Carlo (MCMC) method, it is a robust tool for quantifying uncertainty in groundwater reactive transport models. For the surface complexation model, the regression-based local sensitivity analysis and Morris- and DREAM(ZS)-based global sensitivity analysis yield almost identical ranking of parameter importance. The uncertainty analysis may help select appropriate likelihood
A linear model of population dynamics
Lushnikov, A. A.; Kagan, A. I.
2016-08-01
The Malthus process of population growth is reformulated in terms of the probability w(n,t) to find exactly n individuals at time t assuming that both the birth and the death rates are linear functions of the population size. The master equation for w(n,t) is solved exactly. It is shown that w(n,t) strongly deviates from the Poisson distribution and is expressed in terms either of Laguerre’s polynomials or a modified Bessel function. The latter expression allows for considerable simplifications of the asymptotic analysis of w(n,t).
Injecting Abstract Interpretations into Linear Cost Models
David Cachera
2010-06-01
Full Text Available We present a semantics based framework for analysing the quantitative behaviour of programs with regard to resource usage. We start from an operational semantics equipped with costs. The dioid structure of the set of costs allows for defining the quantitative semantics as a linear operator. We then present an abstraction technique inspired from abstract interpretation in order to effectively compute global cost information from the program. Abstraction has to take two distinct notions of order into account: the order on costs and the order on states. We show that our abstraction technique provides a correct approximation of the concrete cost computations.
Modelling point patterns with linear structures
Møller, Jesper; Rasmussen, Jakob Gulddahl
Many observed spatial point patterns contain points placed roughly on line segments. Point patterns exhibiting such structures can be found for example in archaeology (locations of bronze age graves in Denmark) and geography (locations of mountain tops). We consider a particular class of point...... processes whose realizations contain such linear structures. Such a point process is constructed sequentially by placing one point at a time. The points are placed in such a way that new points are often placed close to previously placed points, and the points form roughly line shaped structures. We...
Modelling point patterns with linear structures
Møller, Jesper; Rasmussen, Jakob Gulddahl
2009-01-01
Many observed spatial point patterns contain points placed roughly on line segments. Point patterns exhibiting such structures can be found for example in archaeology (locations of bronze age graves in Denmark) and geography (locations of mountain tops). We consider a particular class of point...... processes whose realizations contain such linear structures. Such a point process is constructed sequentially by placing one point at a time. The points are placed in such a way that new points are often placed close to previously placed points, and the points form roughly line shaped structures. We...
Applications of the Linear Logistic Test Model in Psychometric Research
Kubinger, Klaus D.
2009-01-01
The linear logistic test model (LLTM) breaks down the item parameter of the Rasch model as a linear combination of some hypothesized elementary parameters. Although the original purpose of applying the LLTM was primarily to generate test items with specified item difficulty, there are still many other potential applications, which may be of use…
Quantitative Models and Analysis for Reactive Systems
Thrane, Claus
phones and websites. Acknowledging that now more than ever, systems come in contact with the physical world, we need to revise the way we construct models and verification algorithms, to take into account the behavior of systems in the presence of approximate, or quantitative information, provided......, allowing verification procedures to quantify judgements, on how suitable a model is for a given specification — hence mitigating the usual harsh distinction between satisfactory and non-satisfactory system designs. This information, among other things, allows us to evaluate the robustness of our framework......, by studying how small changes to our models affect the verification results. A key source of motivation for this work can be found in The Embedded Systems Design Challenge [HS06] posed by Thomas A. Henzinger and Joseph Sifakis. It contains a call for advances in the state-of-the-art of systems verification...
Modeling local item dependence with the hierarchical generalized linear model.
Jiao, Hong; Wang, Shudong; Kamata, Akihito
2005-01-01
Local item dependence (LID) can emerge when the test items are nested within common stimuli or item groups. This study proposes a three-level hierarchical generalized linear model (HGLM) to model LID when LID is due to such contextual effects. The proposed three-level HGLM was examined by analyzing simulated data sets and was compared with the Rasch-equivalent two-level HGLM that ignores such a nested structure of test items. The results demonstrated that the proposed model could capture LID and estimate its magnitude. Also, the two-level HGLM resulted in larger mean absolute differences between the true and the estimated item difficulties than those from the proposed three-level HGLM. Furthermore, it was demonstrated that the proposed three-level HGLM estimated the ability distribution variance unaffected by the LID magnitude, while the two-level HGLM with no LID consideration increasingly underestimated the ability variance as the LID magnitude increased.
Employment of CB models for non-linear dynamic analysis
Klein, M. R. M.; Deloo, P.; Fournier-Sicre, A.
1990-01-01
The non-linear dynamic analysis of large structures is always very time, effort and CPU consuming. Whenever possible the reduction of the size of the mathematical model involved is of main importance to speed up the computational procedures. Such reduction can be performed for the part of the structure which perform linearly. Most of the time, the classical Guyan reduction process is used. For non-linear dynamic process where the non-linearity is present at interfaces between different structures, Craig-Bampton models can provide a very rich information, and allow easy selection of the relevant modes with respect to the phenomenon driving the non-linearity. The paper presents the employment of Craig-Bampton models combined with Newmark direct integration for solving non-linear friction problems appearing at the interface between the Hubble Space Telescope and its solar arrays during in-orbit maneuvers. Theory, implementation in the FEM code ASKA, and practical results are shown.
Modeling reactive flow and transport in natural systems
Lichtner, P.C. [Center for Nuclear Waste Regulatory Analyses, S.Antonio, TX (United States)
1998-12-31
A general formulation of reactive transport equations in a porous medium has been presented including homogeneous reactions of aqueous species, heterogenous reactions of minerals, and microbiological processes. The canonical form of chemical reactions was introduced and the transformation between primary or basis species derived. The use of parallel linearly-dependent reactions was discussed for incorporating different reaction rate mechanisms. It was demonstrated how the electron may be used in reactive transport equations with redox reactions formulated in terms of half-cell reactions. A single component system was investigated for both a one-dimensional porous medium and a two-dimensional geometry incorporating fracture-matrix interaction. Finally two multicomponent examples were considered using the computer code MULTIFLO of in situ leaching of copper ore and acid mine drainage.
Latent log-linear models for handwritten digit classification.
Deselaers, Thomas; Gass, Tobias; Heigold, Georg; Ney, Hermann
2012-06-01
We present latent log-linear models, an extension of log-linear models incorporating latent variables, and we propose two applications thereof: log-linear mixture models and image deformation-aware log-linear models. The resulting models are fully discriminative, can be trained efficiently, and the model complexity can be controlled. Log-linear mixture models offer additional flexibility within the log-linear modeling framework. Unlike previous approaches, the image deformation-aware model directly considers image deformations and allows for a discriminative training of the deformation parameters. Both are trained using alternating optimization. For certain variants, convergence to a stationary point is guaranteed and, in practice, even variants without this guarantee converge and find models that perform well. We tune the methods on the USPS data set and evaluate on the MNIST data set, demonstrating the generalization capabilities of our proposed models. Our models, although using significantly fewer parameters, are able to obtain competitive results with models proposed in the literature.
Multivariate statistical modelling based on generalized linear models
Fahrmeir, Ludwig
1994-01-01
This book is concerned with the use of generalized linear models for univariate and multivariate regression analysis. Its emphasis is to provide a detailed introductory survey of the subject based on the analysis of real data drawn from a variety of subjects including the biological sciences, economics, and the social sciences. Where possible, technical details and proofs are deferred to an appendix in order to provide an accessible account for non-experts. Topics covered include: models for multi-categorical responses, model checking, time series and longitudinal data, random effects models, and state-space models. Throughout, the authors have taken great pains to discuss the underlying theoretical ideas in ways that relate well to the data at hand. As a result, numerous researchers whose work relies on the use of these models will find this an invaluable account to have on their desks. "The basic aim of the authors is to bring together and review a large part of recent advances in statistical modelling of m...
Ommen, Torben Schmidt; Markussen, Wiebke Brix; Elmegaard, Brian
2014-01-01
differences and differences between the solution found by each optimisation method. One of the investigated approaches utilises LP (linear programming) for optimisation, one uses LP with binary operation constraints, while the third approach uses NLP (non-linear programming). The LP model is used...... of selected units by 23%, while for a non-linear approach the increase can be higher than 39%. The results indicate a higher coherence between the two latter approaches, and that the MLP (mixed integer programming) optimisation is most appropriate from a viewpoint of accuracy and runtime. © 2014 Elsevier Ltd...
The Optimal Linear Combination of Multiple Predictors Under the Generalized Linear Models.
Jin, Hua; Lu, Ying
2009-11-15
Multiple alternative diagnostic tests for one disease are commonly available to clinicians. It's important to use all the good diagnostic predictors simultaneously to establish a new predictor with higher statistical utility. Under the generalized linear model for binary outcomes, the linear combination of multiple predictors in the link function is proved optimal in the sense that the area under the receiver operating characteristic (ROC) curve of this combination is the largest among all possible linear combination. The result was applied to analysis of the data from the Study of Osteoporotic Fractures (SOF) with comparison to Su and Liu's approach.
General expression for linear and nonlinear time series models
Ren HUANG; Feiyun XU; Ruwen CHEN
2009-01-01
The typical time series models such as ARMA, AR, and MA are founded on the normality and stationarity of a system and expressed by a linear difference equation; therefore, they are strictly limited to the linear system. However, some nonlinear factors are within the practical system; thus, it is difficult to fit the model for real systems with the above models. This paper proposes a general expression for linear and nonlinear auto-regressive time series models (GNAR). With the gradient optimization method and modified AIC information criteria integrated with the prediction error, the parameter estimation and order determination are achieved. The model simulation and experiments show that the GNAR model can accurately approximate to the dynamic characteristics of the most nonlinear models applied in academics and engineering. The modeling and prediction accuracy of the GNAR model is superior to the classical time series models. The proposed GNAR model is flexible and effective.
Dynamic Model of Linear Induction Motor Considering the End Effects
H. A. Hairik
2009-01-01
Full Text Available In this paper the dynamic behavior of linear induction motor is described by a mathematical model taking into account the end effects and the core losses. The need for such a model rises due to the complexity of linear induction motors electromagnetic field theory. The end affects by introducing speed dependent scale factor to the magnetizing inductance and series resistance in the d-axis equivalent circuit. Simulation results are presented to show the validity of the model during both no-load and sudden load change intervals. This model can also be used directly in simulation researches for linear induction motor vector control drive systems.
Bao Xue ZHANG; Bai Sen LIU; Chang Yu LU
2004-01-01
Consider the partitioned linear regression model A = (y, X1β1 + X2β2, σ2V) and its four reduced linear models, where y is an n × 1 observable random vector with E(y) = Xβ and dispersion matrix Var(y) = σ2V, where σ2 is an unknown positive scalar, V is an n × n known symmetric nonnegative definite matrix, X = (X1: X2) is an n× (p+q) known design matrix with rank(X) = r ≤ (p+q),andβ = (β'1:β'2)' withβ1 andβ2 being p × 1 and q × 1 vectors of unknown parameters, respectively. In this article the formulae for the differences between the best linear unbiased estimators of M2X1β1under the model A and its best linear unbiased estimators under the reduced linear models of A are given,where M2 = I - X2X2+. Furthermore, the necessary and sufficient conditions for the equalities between the best linear unbiased estimators of M2X1β1 under the model A and those under its reduced linear models are established. Lastly, we also study the connections between the model A and its linear transformation model.
Linear Latent Force Models using Gaussian Processes
Álvarez, Mauricio A; Lawrence, Neil D
2011-01-01
Purely data driven approaches for machine learning present difficulties when data is scarce relative to the complexity of the model or when the model is forced to extrapolate. On the other hand, purely mechanistic approaches need to identify and specify all the interactions in the problem at hand (which may not be feasible) and still leave the issue of how to parameterize the system. In this paper, we present a hybrid approach using Gaussian processes and differential equations to combine data driven modelling with a physical model of the system. We show how different, physically-inspired, kernel functions can be developed through sensible, simple, mechanistic assumptions about the underlying system. The versatility of our approach is illustrated with three case studies from motion capture, computational biology and geostatistics.
Numerical modelling in non linear fracture mechanics
Viggo Tvergaard
2007-07-01
Full Text Available Some numerical studies of crack propagation are based on using constitutive models that accountfor damage evolution in the material. When a critical damage value has been reached in a materialpoint, it is natural to assume that this point has no more carrying capacity, as is done numerically in the elementvanish technique. In the present review this procedure is illustrated for micromechanically based materialmodels, such as a ductile failure model that accounts for the nucleation and growth of voids to coalescence, and a model for intergranular creep failure with diffusive growth of grain boundary cavities leading to micro-crack formation. The procedure is also illustrated for low cycle fatigue, based on continuum damage mechanics. In addition, the possibility of crack growth predictions for elastic-plastic solids using cohesive zone models to represent the fracture process is discussed.
Tsai, C. H.; Yeh, G. T.
2015-12-01
In this investigation, a coupled model of multiphase flow, reactive biogeochemical transport, thermal transport and geo-mechanics in subsurface media is presented. It iteratively solves the mass conservation equation for fluid flow, thermal transport equation for temperature, reactive biogeochemical transport equations for concentration distributions, and solid momentum equation for displacement with successive linearization algorithm. With species-based equations of state, density of a phase in the system is obtained by summing up concentrations of all species. This circumvents the problem of having to use empirical functions. Moreover, reaction rates of all species are incorporated in mass conservation equation for fluid flow. Formation enthalpy of all species is included in the law of energy conservation as a source-sink term. Finite element methods are used to discretize the governing equations. Numerical experiments are presented to examine the accuracy and robustness of the proposed model. The results demonstrate the feasibility and capability of present model in subsurface media.
Linear latent variable models: the lava-package
Holst, Klaus Kähler; Budtz-Jørgensen, Esben
2013-01-01
An R package for specifying and estimating linear latent variable models is presented. The philosophy of the implementation is to separate the model specification from the actual data, which leads to a dynamic and easy way of modeling complex hierarchical structures. Several advanced features...... are implemented including robust standard errors for clustered correlated data, multigroup analyses, non-linear parameter constraints, inference with incomplete data, maximum likelihood estimation with censored and binary observations, and instrumental variable estimators. In addition an extensive simulation...
On-line control models for the Stanford Linear Collider
Sheppard, J.C.; Helm, R.H.; Lee, M.J.; Woodley, M.D.
1983-03-01
Models for computer control of the SLAC three-kilometer linear accelerator and damping rings have been developed as part of the control system for the Stanford Linear Collider. Some of these models have been tested experimentally and implemented in the control program for routine linac operations. This paper will describe the development and implementation of these models, as well as some of the operational results.
Identification of Influential Points in a Linear Regression Model
Jan Grosz
2011-03-01
Full Text Available The article deals with the detection and identification of influential points in the linear regression model. Three methods of detection of outliers and leverage points are described. These procedures can also be used for one-sample (independentdatasets. This paper briefly describes theoretical aspects of several robust methods as well. Robust statistics is a powerful tool to increase the reliability and accuracy of statistical modelling and data analysis. A simulation model of the simple linear regression is presented.
Extended Linear Models with Gaussian Priors
Quinonero, Joaquin
2002-01-01
on the parameters. The Relevance Vector Machine, introduced by Tipping, is a particular case of such a model. I give the detailed derivations of the expectation-maximisation (EM) algorithm used in the training. These derivations are not found in the literature, and might be helpful for newcomers....
Random effect selection in generalised linear models
Denwood, Matt; Houe, Hans; Forkman, Björn;
We analysed abattoir recordings of meat inspection codes with possible relevance to onfarm animal welfare in cattle. Random effects logistic regression models were used to describe individual-level data obtained from 461,406 cattle slaughtered in Denmark. Our results demonstrate that the largest...
Generalized Linear Models with Applications in Engineering and the Sciences
Myers, Raymond H; Vining, G Geoffrey; Robinson, Timothy J
2012-01-01
Praise for the First Edition "The obvious enthusiasm of Myers, Montgomery, and Vining and their reliance on their many examples as a major focus of their pedagogy make Generalized Linear Models a joy to read. Every statistician working in any area of applied science should buy it and experience the excitement of these new approaches to familiar activities."-Technometrics Generalized Linear Models: With Applications in Engineering and the Sciences, Second Edition continues to provide a clear introduction to the theoretical foundations and key applications of generalized linear models (GLMs). Ma
Linear Factor Models and the Estimation of Expected Returns
Sarisoy, Cisil; de Goeij, Peter; Werker, Bas
2015-01-01
Estimating expected returns on individual assets or portfolios is one of the most fundamental problems of finance research. The standard approach, using historical averages,produces noisy estimates. Linear factor models of asset pricing imply a linear relationship between expected returns and exposu
Linear and Nonlinear Thinking: A Multidimensional Model and Measure
Groves, Kevin S.; Vance, Charles M.
2015-01-01
Building upon previously developed and more general dual-process models, this paper provides empirical support for a multidimensional thinking style construct comprised of linear thinking and multiple dimensions of nonlinear thinking. A self-report assessment instrument (Linear/Nonlinear Thinking Style Profile; LNTSP) is presented and…
Model Reduction by Moment Matching for Linear Switched Systems
Bastug, Mert; Petreczky, Mihaly; Wisniewski, Rafal;
2014-01-01
A moment-matching method for the model reduction of linear switched systems (LSSs) is developed. The method is based based upon a partial realization theory of LSSs and it is similar to the Krylov subspace methods used for moment matching for linear systems. The results are illustrated by numeric...
Linear and Nonlinear Thinking: A Multidimensional Model and Measure
Groves, Kevin S.; Vance, Charles M.
2015-01-01
Building upon previously developed and more general dual-process models, this paper provides empirical support for a multidimensional thinking style construct comprised of linear thinking and multiple dimensions of nonlinear thinking. A self-report assessment instrument (Linear/Nonlinear Thinking Style Profile; LNTSP) is presented and…
Bayesian Subset Modeling for High-Dimensional Generalized Linear Models
Liang, Faming
2013-06-01
This article presents a new prior setting for high-dimensional generalized linear models, which leads to a Bayesian subset regression (BSR) with the maximum a posteriori model approximately equivalent to the minimum extended Bayesian information criterion model. The consistency of the resulting posterior is established under mild conditions. Further, a variable screening procedure is proposed based on the marginal inclusion probability, which shares the same properties of sure screening and consistency with the existing sure independence screening (SIS) and iterative sure independence screening (ISIS) procedures. However, since the proposed procedure makes use of joint information from all predictors, it generally outperforms SIS and ISIS in real applications. This article also makes extensive comparisons of BSR with the popular penalized likelihood methods, including Lasso, elastic net, SIS, and ISIS. The numerical results indicate that BSR can generally outperform the penalized likelihood methods. The models selected by BSR tend to be sparser and, more importantly, of higher prediction ability. In addition, the performance of the penalized likelihood methods tends to deteriorate as the number of predictors increases, while this is not significant for BSR. Supplementary materials for this article are available online. © 2013 American Statistical Association.
Transient Response Model of Standing Wave Piezoelectric Linear Ultrasonic Motor
SHI Yunlai; CHEN Chao; ZHAO Chunsheng
2012-01-01
A transient response model for describing the starting and stopping characteristics of the standing wave piezoelectric linear ultrasonic motor was presented.Based on the contact dynamic model,the kinetic equation of the motor was derived.The starting and stopping characteristics of the standing wave piezoelectric linear ultrasonic motor according to different loads,contact stiffness and inertia mass were described and analyzed,respectively.To validate the transient response model,a standing wave piezoelectric linear ultrasonic motor based on in-plane modes was used to carry out the simulation and experimental study.The corresponding results showed that the simulation of the motor performances based on the proposed model agreed well with the experimental results.This model will helpful to improve the stepping characteristics and the control flexibility of the standing wave piezoelectric linear ultrasonic motor.
A linear algebra model for quasispecies
García-Pelayo, Ricardo
2002-06-01
In the present work we present a simple model of the population genetics of quasispecies. We show that the error catastrophe arises because in Biology the mutation rates are almost zero and the mutations themselves are almost neutral. We obtain and discuss previously known results from the point of view of this model. New results are: the fitness of a sequence in terms of its abundance in the quasispecies, a formula for the stable distribution of a quasispecies in which the fitness depends only on the Hamming distance to the master sequence, the time it takes the master sequence to generate a stable quasispecies (such as in the infection by a virus) and the fitness of quasispecies.
Modeling and optimization of ultrasonic linear motors
Fernandez Lopez, José; Perriard, Yves
2007-01-01
Ultrasonic motors have received much attention these last years, in particular with regard to their modeling and their design principle. Their operating principle is based on piezoelectric ceramics that convert electrical energy into mechanical energy in the form of vibrations of an elastic body whose surface points perform an elliptic motion with a frequency in the ultrasonic range (≥ 20 kHz). The moving part, which is pressed against the vibrating body by a prestressing force, can move than...
Forecasting telecommunications data with linear models
Madden, Gary G; Tan, Joachim
2007-01-01
For telecommunication companies to successfully manage their business, companies rely on mapping future trends and usage patterns. However, the evolution of telecommunications technology and systems in the provision of services renders imperfections in telecommunications data and impinges on a company’s’ ability to properly evaluate and plan their business. ITU Recommendation E.507 provides a selection of econometric models for forecasting these trends. However, no specific guidance is given....
Circular and linear modeling of female sexual desire and arousal.
Hayes, Richard D
2011-03-01
There is debate in the scientific literature regarding which model most accurately represents the female sexual response. Traditionally, sex research has been conducted within the framework of the linear sexual response model proposed by Masters and Johnson, modified by Kaplan, then Robinson. Criticism of linear models prompted the development of a composite model of the female sexual response by Basson et al., which included linear and circular pathways. This review aims to systematically assess published studies to determine the extent to which circular and linear models or pathways reflect the female sexual response. Medline, EMBASE, and PsychINFO databases were searched for original data papers and review articles. Inclusion criteria were that articles were published since 1990, in English, and compared linear and circular sexual response models or addressed aspects of these models. Reviews were required to be systematic and include a meta-analysis. Of the 898 studies identified through the initial literature search, 13 original studies and one review met the inclusion criteria. Two studies directly compared models providing limited evidence that most women identify with linear sexual response pathways. However, there is increasing evidence that circular pathways may accurately reflect some aspects of the female sexual response. Further comparative studies are encouraged.
Reactive transport modeling has been conducted to describe the performance of the permeable reactive barrier at the Coast Guard Support Center near Elizabeth City, NC. The reactive barrier was installed to treat groundwater contaminated by hexavalent chromium and chlorinated org...
Measurements and models of reactive transport in geological media
Berkowitz, Brian; Dror, Ishai; Hansen, Scott K.; Scher, Harvey
2016-12-01
Reactive chemical transport plays a key role in geological media across scales, from pore scale to aquifer scale. Systems can be altered by changes in solution chemistry and a wide variety of chemical transformations, including precipitation/dissolution reactions that cause feedbacks that directly affect the flow and transport regime. The combination of these processes with advective-dispersive-diffusive transport in heterogeneous media leads to a rich spectrum of complex dynamics. The principal challenge in modeling reactive transport is to account for the subtle effects of fluctuations in the flow field and species concentrations; spatial or temporal averaging generally suppresses these effects. Moreover, it is critical to ground model conceptualizations and test model outputs against laboratory experiments and field measurements. This review emphasizes the integration of these aspects, considering carefully designed and controlled experiments at both laboratory and field scales, in the context of development and solution of reactive transport models based on continuum-scale and particle tracking approaches. We first discuss laboratory experiments and field measurements that define the scope of the phenomena and provide data for model comparison. We continue by surveying models involving advection-dispersion-reaction equation and continuous time random walk formulations. The integration of measurements and models is then examined, considering a series of case studies in different frameworks. We delineate the underlying assumptions, and strengths and weaknesses, of these analyses, and the role of probabilistic effects. We also show the key importance of quantifying the spreading and mixing of reactive species, recognizing the role of small-scale physical and chemical fluctuations that control the initiation of reactions.
Linear Sigma Models With Strongly Coupled Phases -- One Parameter Models
Hori, Kentaro
2013-01-01
We systematically construct a class of two-dimensional $(2,2)$ supersymmetric gauged linear sigma models with phases in which a continuous subgroup of the gauge group is totally unbroken. We study some of their properties by employing a recently developed technique. The focus of the present work is on models with one K\\"ahler parameter. The models include those corresponding to Calabi-Yau threefolds, extending three examples found earlier by a few more, as well as Calabi-Yau manifolds of other dimensions and non-Calabi-Yau manifolds. The construction leads to predictions of equivalences of D-brane categories, systematically extending earlier examples. There is another type of surprise. Two distinct superconformal field theories corresponding to Calabi-Yau threefolds with different Hodge numbers, $h^{2,1}=23$ versus $h^{2,1}=59$, have exactly the same quantum K\\"ahler moduli space. The strong-weak duality plays a crucial r\\^ole in confirming this, and also is useful in the actual computation of the metric on t...
Optimization for decision making linear and quadratic models
Murty, Katta G
2010-01-01
While maintaining the rigorous linear programming instruction required, Murty's new book is unique in its focus on developing modeling skills to support valid decision-making for complex real world problems, and includes solutions to brand new algorithms.
Linear Characteristic Graphical Models: Representation, Inference and Applications
Bickson, Danny
2010-01-01
Heavy-tailed distributions naturally occur in many real life problems. Unfortunately, it is typically not possible to compute inference in closed-form in graphical models which involve such heavy-tailed distributions. In this work, we propose a novel simple linear graphical model for independent latent random variables, called linear characteristic model (LCM), defined in the characteristic function domain. Using stable distributions, a heavy-tailed family of distributions which is a generalization of Cauchy, L\\'evy and Gaussian distributions, we show for the first time, how to compute both exact and approximate inference in such a linear multivariate graphical model. LCMs are not limited to stable distributions, in fact LCMs are always defined for any random variables (discrete, continuous or a mixture of both). We provide a realistic problem from the field of computer networks to demonstrate the applicability of our construction. Other potential application is iterative decoding of linear channels with non-...
The linear model and hypothesis a general unifying theory
Seber, George
2015-01-01
This book provides a concise and integrated overview of hypothesis testing in four important subject areas, namely linear and nonlinear models, multivariate analysis, and large sample theory. The approach used is a geometrical one based on the concept of projections and their associated idempotent matrices, thus largely avoiding the need to involve matrix ranks. It is shown that all the hypotheses encountered are either linear or asymptotically linear, and that all the underlying models used are either exactly or asymptotically linear normal models. This equivalence can be used, for example, to extend the concept of orthogonality in the analysis of variance to other models, and to show that the asymptotic equivalence of the likelihood ratio, Wald, and Score (Lagrange Multiplier) hypothesis tests generally applies.
Mäntysaari Esa A
2006-06-01
Full Text Available Abstract A method based on Taylor series expansion for estimation of location parameters and variance components of non-linear mixed effects models was considered. An attractive property of the method is the opportunity for an easily implemented algorithm. Estimation of non-linear mixed effects models can be done by common methods for linear mixed effects models, and thus existing programs can be used after small modifications. The applicability of this algorithm in animal breeding was studied with simulation using a Gompertz function growth model in pigs. Two growth data sets were analyzed: a full set containing observations from the entire growing period, and a truncated time trajectory set containing animals slaughtered prematurely, which is common in pig breeding. The results from the 50 simulation replicates with full data set indicate that the linearization approach was capable of estimating the original parameters satisfactorily. However, estimation of the parameters related to adult weight becomes unstable in the case of a truncated data set.
Linear stability analysis of a nuclear reactor using the lumped model
Kale Vivek A.
2016-01-01
Full Text Available The stability analysis of a nuclear reactor is an important aspect in the design and operation of the reactor. A stable neutronic response to perturbations is essential from the safety point of view. In this paper, a general methodology has been developed for the linear stability analysis of nuclear reactors using the lumped reactor model. The reactor kinetics has been modelled using the point kinetics equations and the reactivity feedbacks from fuel, coolant and xenon have been modelled through the appropriate time dependent equations. These governing equations are linearized considering small perturbations in the reactor state around a steady operating point. The characteristic equation of the system is used to establish the stability zone of the reactor considering the reactivity coefficients as parameters. This methodology has been used to identify the stability region of a typical pressurized heavy water reactor. It is shown that the positive reactivity feedback from xenon narrows down the stability region. Further, it is observed that the neutron kinetics parameters (such as the number of delayed neutron precursor groups considered, the neutron generation time, the delayed neutron fractions, etc. do not have a significant influence on the location of the stability boundary. The stability boundary is largely influenced by the parameters governing the evolution of the fuel and coolant temperature and xenon concentration.
Generalized linear mixed models modern concepts, methods and applications
Stroup, Walter W
2012-01-01
PART I The Big PictureModeling BasicsWhat Is a Model?Two Model Forms: Model Equation and Probability DistributionTypes of Model EffectsWriting Models in Matrix FormSummary: Essential Elements for a Complete Statement of the ModelDesign MattersIntroductory Ideas for Translating Design and Objectives into ModelsDescribing ""Data Architecture"" to Facilitate Model SpecificationFrom Plot Plan to Linear PredictorDistribution MattersMore Complex Example: Multiple Factors with Different Units of ReplicationSetting the StageGoals for Inference with Models: OverviewBasic Tools of InferenceIssue I: Data
A BEHAVIORAL-APPROACH TO LINEAR EXACT MODELING
ANTOULAS, AC; WILLEMS, JC
1993-01-01
The behavioral approach to system theory provides a parameter-free framework for the study of the general problem of linear exact modeling and recursive modeling. The main contribution of this paper is the solution of the (continuous-time) polynomial-exponential time series modeling problem. Both re
Scaling and linear response in the GOY model
Kadanoff, Leo; Lohse, Detlef; Schörghofer, Norbert
1997-01-01
The GOY model is a model for turbulence in which two conserved quantities cascade up and down a linear array of shells. When the viscosity parameter, small nu, Greek, is small the model has a qualitative behavior which is similar to the Kolmogorov theories of turbulence. Here a static solution to th
A hierarchical linear model for tree height prediction.
Vicente J. Monleon
2003-01-01
Measuring tree height is a time-consuming process. Often, tree diameter is measured and height is estimated from a published regression model. Trees used to develop these models are clustered into stands, but this structure is ignored and independence is assumed. In this study, hierarchical linear models that account explicitly for the clustered structure of the data...
Modelling Nonlinear Sequence Generators in terms of Linear Cellular Automata
Fúster-Sabater, Amparo; 10.1016/j.apm.2005.08.013
2010-01-01
In this work, a wide family of LFSR-based sequence generators, the so-called Clock-Controlled Shrinking Generators (CCSGs), has been analyzed and identified with a subset of linear Cellular Automata (CA). In fact, a pair of linear models describing the behavior of the CCSGs can be derived. The algorithm that converts a given CCSG into a CA-based linear model is very simple and can be applied to CCSGs in a range of practical interest. The linearity of these cellular models can be advantageously used in two different ways: (a) for the analysis and/or cryptanalysis of the CCSGs and (b) for the reconstruction of the output sequence obtained from this kind of generators.
Linearized models for a new magnetic control in MAST
Artaserse, G., E-mail: giovanni.artaserse@enea.it [Associazione Euratom-ENEA sulla Fusione, Via Enrico Fermi 45, I-00044 Frascati (RM) (Italy); Maviglia, F.; Albanese, R. [Associazione Euratom-ENEA-CREATE sulla Fusione, Via Claudio 21, I-80125 Napoli (Italy); McArdle, G.J.; Pangione, L. [EURATOM/CCFE Fusion Association, Culham Science Centre, Abingdon, Oxon, OX14 3DB (United Kingdom)
2013-10-15
Highlights: ► We applied linearized models for a new magnetic control on MAST tokamak. ► A suite of procedures, conceived to be machine independent, have been used. ► We carried out model-based simulations, taking into account eddy currents effects. ► Comparison with the EFIT flux maps and the experimental magnetic signals are shown. ► A current driven model for the dynamic simulations of the experimental data have been performed. -- Abstract: The aim of this work is to provide reliable linearized models for the design and assessment of a new magnetic control system for MAST (Mega Ampère Spherical Tokamak) using rtEFIT, which can easily be exported to MAST Upgrade. Linearized models for magnetic control have been obtained using the 2D axisymmetric finite element code CREATE L. MAST linearized models include equivalent 2D axisymmetric schematization of poloidal field (PF) coils, vacuum vessel, and other conducting structures. A plasmaless and a double null configuration have been chosen as benchmark cases for the comparison with experimental data and EFIT reconstructions. Good agreement has been found with the EFIT flux map and the experimental signals coming from magnetic probes with only few mismatches probably due to broken sensors. A suite of procedures (equipped with a user friendly interface to be run even remotely) to provide linearized models for magnetic control is now available on the MAST linux machines. A new current driven model has been used to obtain a state space model having the PF coil currents as inputs. Dynamic simulations of experimental data have been carried out using linearized models, including modelling of the effects of the passive structures, showing a fair agreement. The modelling activity has been useful also to reproduce accurately the interaction between plasma current and radial position control loops.
Modeling Routing Overhead Generated by Wireless Reactive Routing Protocols
Javaid, Nadeem; Javaid, Akmal; Malik, Shahzad A
2011-01-01
In this paper, we have modeled the routing over- head generated by three reactive routing protocols; Ad-hoc On-demand Distance Vector (AODV), Dynamic Source Routing (DSR) and DYnamic MANET On-deman (DYMO). Routing performed by reactive protocols consists of two phases; route discovery and route maintenance. Total cost paid by a protocol for efficient routing is sum of the cost paid in the form of energy consumed and time spent. These protocols majorly focus on the optimization performed by expanding ring search algorithm to control the flooding generated by the mechanism of blind flooding. So, we have modeled the energy consumed and time spent per packet both for route discovery and route maintenance. The proposed framework is evaluated in NS-2 to compare performance of the chosen routing protocols.
Langevin model for reactive transport in porous media
Tartakovsky, Alexandre M.
2010-08-01
Existing continuum models for reactive transport in porous media tend to overestimate the extent of solute mixing and mixing-controlled reactions because the continuum models treat both the mechanical and diffusive mixings as an effective Fickian process. Recently, we have proposed a phenomenological Langevin model for flow and transport in porous media [A. M. Tartakovsky, D. M. Tartakovsky, and P. Meakin, Phys. Rev. Lett. 101, 044502 (2008)10.1103/PhysRevLett.101.044502]. In the Langevin model, the fluid flow in a porous continuum is governed by a combination of a Langevin equation and a continuity equation. Pore-scale velocity fluctuations, the source of mechanical dispersion, are represented by the white noise. The advective velocity (the solution of the Langevin flow equation) causes the mechanical dispersion of a solute. Molecular diffusion and sub-pore-scale Taylor-type dispersion are modeled by an effective stochastic advection-diffusion equation. Here, we propose a method for parameterization of the model for a synthetic porous medium, and we use the model to simulate multicomponent reactive transport in the porous medium. The detailed comparison of the results of the Langevin model with pore-scale and continuum (Darcy) simulations shows that: (1) for a wide range of Peclet numbers the Langevin model predicts the mass of reaction product more accurately than the Darcy model; (2) for small Peclet numbers predictions of both the Langevin and the Darcy models agree well with a prediction of the pore-scale model; and (3) the accuracy of the Langevin and Darcy model deteriorates with the increasing Peclet number but the accuracy of the Langevin model decreases more slowly than the accuracy of the Darcy model. These results show that the separate treatment of advective and diffusive mixing in the stochastic transport model is more accurate than the classical advection-dispersion theory, which uses a single effective diffusion coefficient (the dispersion
Representing Microbial Processes in Environmental Reactive Transport Models
van Cappellen, P.
2009-04-01
Microorganisms play a key role in the biogeochemical functioning of the earth's surface and shallow subsurface. In the context of reactive transport modeling, a major challenge is to derive, parameterize, calibrate and verify mathematical expressions for microbially-mediated reactions in the environmental. This is best achieved by combining field observations, laboratory experiments, theoretical principles and modeling. Here, I will illustrate such an integrated approach for the case of microbial respiration processes in aquatic sediments. Important issues that will be covered include experimental design, model consistency and performance, as well as the bioenergetics and transient behavior of geomicrobial reaction systems.
Distributed Lag Linear and Non-Linear Models in R: The Package dlnm
Antonio Gasparrini
2011-08-01
Full Text Available Distributed lag non-linear models (DLNMs represent a modeling framework to flexibly describe associations showing potentially non-linear and delayed effects in time series data. This methodology rests on the definition of a crossbasis, a bi-dimensional functional space expressed by the combination of two sets of basis functions, which specify the relationships in the dimensions of predictor and lags, respectively. This framework is implemented in the R package dlnm, which provides functions to perform the broad range of models within the DLNM family and then to help interpret the results, with an emphasis on graphical representation. This paper offers an overview of the capabilities of the package, describing the conceptual and practical steps to specify and interpret DLNMs with an example of application to real data.
Non-linear Growth Models in Mplus and SAS.
Grimm, Kevin J; Ram, Nilam
2009-10-01
Non-linear growth curves or growth curves that follow a specified non-linear function in time enable researchers to model complex developmental patterns with parameters that are easily interpretable. In this paper we describe how a variety of sigmoid curves can be fit using the Mplus structural modeling program and the non-linear mixed-effects modeling procedure NLMIXED in SAS. Using longitudinal achievement data collected as part of a study examining the effects of preschool instruction on academic gain we illustrate the procedures for fitting growth models of logistic, Gompertz, and Richards functions. Brief notes regarding the practical benefits, limitations, and choices faced in the fitting and estimation of such models are included.
A quasi-linear gyrokinetic transport model for tokamak plasmas
Casati, Alessandro
2012-01-01
The development of a quasi-linear gyrokinetic transport model for tokamak plasmas, ultimately designed to provide physically comprehensive predictions of the time evolution of the thermodynamic relevant quantities, is a task that requires tight links among theoretical, experimental and numerical studies. The framework of the model here proposed, which operates a reduction of complexity on the nonlinear self-organizing plasma dynamics, allows in fact multiple validations of the current understanding of the tokamak micro-turbulence. The main outcomes of this work stem from the fundamental steps involved by the formulation of such a reduced transport model, namely: (1) the verification of the quasi-linear plasma response against the nonlinearly computed solution, (2) the improvement of the turbulent saturation model through an accurate validation of the nonlinear codes against the turbulence measurements, (3) the integration of the quasi-linear model within an integrated transport solver.
Linear approximation model network and its formation via evolutionary computation
Yun Li; Kay Chen Tan
2000-04-01
To overcome the deficiency of `local model network' (LMN) techniques, an alternative `linear approximation model' (LAM) network approach is proposed. Such a network models a nonlinear or practical system with multiple linear models fitted along operating trajectories, where individual models are simply networked through output or parameter interpolation. The linear models are valid for the entire operating trajectory and hence overcome the local validity of LMN models, which impose the predetermination of a scheduling variable that predicts characteristic changes of the nonlinear system. LAMs can be evolved fromsampled step response data directly, eliminating the need forlocal linearisation upon a pre-model using derivatives of the nonlinear system. The structural difference between a LAM network and an LMN isthat the overall model of the latteris a parameter-varying system and hence nonlinear,while the formerremains linear time-invariant (LTI). Hence, existing LTI and transfer function theory applies to a LAM network, which is therefore easy to use for control system design. Validation results show that the proposed method offers a simple, transparent and accurate multivariable modelling technique for nonlinear systems.
Phylogenetic mixtures and linear invariants for equal input models.
Casanellas, Marta; Steel, Mike
2017-04-01
The reconstruction of phylogenetic trees from molecular sequence data relies on modelling site substitutions by a Markov process, or a mixture of such processes. In general, allowing mixed processes can result in different tree topologies becoming indistinguishable from the data, even for infinitely long sequences. However, when the underlying Markov process supports linear phylogenetic invariants, then provided these are sufficiently informative, the identifiability of the tree topology can be restored. In this paper, we investigate a class of processes that support linear invariants once the stationary distribution is fixed, the 'equal input model'. This model generalizes the 'Felsenstein 1981' model (and thereby the Jukes-Cantor model) from four states to an arbitrary number of states (finite or infinite), and it can also be described by a 'random cluster' process. We describe the structure and dimension of the vector spaces of phylogenetic mixtures and of linear invariants for any fixed phylogenetic tree (and for all trees-the so called 'model invariants'), on any number n of leaves. We also provide a precise description of the space of mixtures and linear invariants for the special case of [Formula: see text] leaves. By combining techniques from discrete random processes and (multi-) linear algebra, our results build on a classic result that was first established by James Lake (Mol Biol Evol 4:167-191, 1987).
A Linearization Approach for Rational Nonlinear Models in Mathematical Physics
Robert A. Van Gorder
2012-01-01
In this paper, a novel method for linearization of rational second order nonlinear models is discussed. In particular, we discuss an application of the 5 expansion method （created to deal with problems in Quantum Field Theory） which will enable both the linearization and perturbation expansion of such equations. Such a method allows for one to quickly obtain the order zero perturbation theory in terms of certain special functions which are governed by linear equations. Higher order perturbation theories can then be obtained in terms of such special functions. One benefit to such a method is that it may be applied even to models without small physical parameters, as the perturbation is given in terms of the degree of nonlinearity, rather than any physical parameter. As an application, we discuss a method of linearizing the six Painlev~ equations by an application of the method. In addition to highlighting the benefits of the method, we discuss certain shortcomings of the method.
Estimation and variable selection for generalized additive partial linear models
Wang, Li
2011-08-01
We study generalized additive partial linear models, proposing the use of polynomial spline smoothing for estimation of nonparametric functions, and deriving quasi-likelihood based estimators for the linear parameters. We establish asymptotic normality for the estimators of the parametric components. The procedure avoids solving large systems of equations as in kernel-based procedures and thus results in gains in computational simplicity. We further develop a class of variable selection procedures for the linear parameters by employing a nonconcave penalized quasi-likelihood, which is shown to have an asymptotic oracle property. Monte Carlo simulations and an empirical example are presented for illustration. © Institute of Mathematical Statistics, 2011.
Linear Modeling of Multiple Sclerosis and Its Subgroubs
Yeliz Karaca
2015-03-01
Full Text Available OBJECTIVE: In this study,120 patients diagnosed with clinical multiple sclerosis (MS of relapsing remitting type (RRMS, secondary progressive type (SPMS and primary progressive type (PPMS were examined, as well as 19 healthy subjects. All subjects were between the ages of 20 and 55. Disability levels of MS symptoms were determined using Expanded Disability Status Scale (EDSS. We focused on three regions in the brain, brain stem, periventricular corpus callosum, and upper cervical regions EDSS scores and number of lesions in these three regions are considered as the parameters of the linear mathematical model to determine the subgroups of the disease. METHODS: Initially, the distinction between healthy subjects and patients was made. Then, if the subject was determined to have MS, the distinction of type, i.e. RRMS, SPMS/PPMS, and later, RRMS/SPMS distinction was made. In all determinations linear models were used and number of lesions in the specified three regions and EDSS scores were assumed as the parameters of the model. The coefficients of the models were obtained by least squares method. RESULTS: In the linear model attached to MR parameters, there was 100% success for distinction of patients and healthy subjects. Success for distinction of RRMS and SPMS/PPMS patients and RRMS/SPMS patients was 94% and 78.94%, respectively is attained. Based on EDSS scores, linear model provides 99% success in the distinction between patients and healthy subjects. In the models created for the distinction between groups, success rate was 94% was for RRMS-SPMS/PPMS and 64% for RRMS/SPMS. CONCLUSION: The correlation of MS diagnosis using various features obtained from MR images and EDSS scores with subgroups of the disease and the possibility of developing a linear model were determined. Using the features having the highest correlation rate, various linear models were developed and high success was achieved.
Vaccination strategies for SEIR models using feedback linearization. Preliminary results
De la Sen, M; Alonso-Quesada, S
2011-01-01
A linearization-based feedback-control strategy for a SEIR epidemic model is discussed. The vaccination objective is the asymptotically tracking of the removed-by-immunity population to the total population while achieving simultaneously the remaining population (i.e. susceptible plus infected plus infectious) to asymptotically tend to zero. The disease controlpolicy is designed based on a feedback linearization technique which provides a general method to generate families of vaccination policies with sound technical background.
Performance modeling and prediction for linear algebra algorithms
Iakymchuk, Roman
2012-01-01
This dissertation incorporates two research projects: performance modeling and prediction for dense linear algebra algorithms, and high-performance computing on clouds. The first project is focused on dense matrix computations, which are often used as computational kernels for numerous scientific applications. To solve a particular mathematical operation, linear algebra libraries provide a variety of algorithms. The algorithm of choice depends, obviously, on its performance. Performance of su...
Confirming the Lanchestrian linear-logarithmic model of attrition
Hartley, D.S. III.
1990-12-01
This paper is the fourth in a series of reports on the breakthrough research in historical validation of attrition in conflict. Significant defense policy decisions, including weapons acquisition and arms reduction, are based in part on models of conflict. Most of these models are driven by their attrition algorithms, usually forms of the Lanchester square and linear laws. None of these algorithms have been validated. The results of this paper confirm the results of earlier papers, using a large database of historical results. The homogeneous linear-logarithmic Lanchestrian attrition model is validated to the extent possible with current initial and final force size data and is consistent with the Iwo Jima data. A particular differential linear-logarithmic model is described that fits the data very well. A version of Helmbold's victory predicting parameter is also confirmed, with an associated probability function. 37 refs., 73 figs., 68 tabs.
MODELLING AND CONTROLLING OF INDUCTION MOTOR BY USING LINEAR ADRC
CH. NAGA KOTI KUMAR,
2011-04-01
Full Text Available In this paper we present a new novel approach for the speed control of an IM using Linear Active Disturbance Rejection Controller [LADRC]. The field oriented control of IM needs the accuratemathematical model of IM, but it is very difficult to develop an accurate mathematical model. The LADRC does depend on the mathematical model so it is very robust to changes in plant parameters. This controller can also estimate and compensate the general disturbances which include the unknown internal dynamics and external disturbances by using the Extended State Observer, which can reduce the system to a linear one.
Linear mixed models a practical guide using statistical software
West, Brady T; Galecki, Andrzej T
2006-01-01
Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), Linear Mixed Models: A Practical Guide Using Statistical Software provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of clustered and longitudinal data. This easy-to-navigate reference details the use of procedures for fitting LMMs in five popular statistical software packages: SAS, SPSS, Stata, R/S-plus, and HLM. The authors introduce basic theoretical concepts, present a heuristic approach to fitting LMMs based on bo
Modeling food matrix effects on chemical reactivity: Challenges and perspectives.
Capuano, Edoardo; Oliviero, Teresa; van Boekel, Martinus A J S
2017-06-29
The same chemical reaction may be different in terms of its position of the equilibrium (i.e., thermodynamics) and its kinetics when studied in different foods. The diversity in the chemical composition of food and in its structural organization at macro-, meso-, and microscopic levels, that is, the food matrix, is responsible for this difference. In this viewpoint paper, the multiple, and interconnected ways the food matrix can affect chemical reactivity are summarized. Moreover, mechanistic and empirical approaches to explain and predict the effect of food matrix on chemical reactivity are described. Mechanistic models aim to quantify the effect of food matrix based on a detailed understanding of the chemical and physical phenomena occurring in food. Their applicability is limited at the moment to very simple food systems. Empirical modeling based on machine learning combined with data-mining techniques may represent an alternative, useful option to predict the effect of the food matrix on chemical reactivity and to identify chemical and physical properties to be further tested. In such a way the mechanistic understanding of the effect of the food matrix on chemical reactions can be improved.
A random effects generalized linear model for reliability compositive evaluation
无
2009-01-01
This paper first proposes a random effects generalized linear model to evaluate the storage life of one kind of high reliable and small sample-sized products by combining multi-sources information of products coming from the same population but stored at different environments. The relevant algorithms are also provided. Simulation results manifest the soundness and effectiveness of the proposed model.
CONTRIBUTIONS TO THE FINITE ELEMENT MODELING OF LINEAR ULTRASONIC MOTORS
Oana CHIVU
2013-05-01
Full Text Available The present paper is concerned with the main modeling elements as produced by means of thefinite element method of linear ultrasonic motors. Hence, first the model is designed and then a modaland harmonic analysis are carried out in view of outlining the main outcomes
CONSISTENCY OF LS ESTIMATOR IN SIMPLE LINEAR EV REGRESSION MODELS
Liu Jixue; Chen Xiru
2005-01-01
Consistency of LS estimate of simple linear EV model is studied. It is shown that under some common assumptions of the model, both weak and strong consistency of the estimate are equivalent but it is not so for quadratic-mean consistency.
Inverse Modelling Problems in Linear Algebra Undergraduate Courses
Martinez-Luaces, Victor E.
2013-01-01
This paper will offer an analysis from a theoretical point of view of mathematical modelling, applications and inverse problems of both causation and specification types. Inverse modelling problems give the opportunity to establish connections between theory and practice and to show this fact, a simple linear algebra example in two different…
Locally supersymmetric D=3 non-linear sigma models
Wit, B. de; Tollsten, A. K.; Nicolai, H.
1992-01-01
We study non-linear sigma models with N local supersymmetries in three space-time dimensions. For N=1 and 2 the target space of these models is Riemannian or Kahler, respectively. All N>2 theories are associated with Einstein spaces. For N=3 the target space is quaternionic, while for N=4 it general
Applying the General Linear Model to Repeated Measures Problems.
Pohlmann, John T.; McShane, Michael G.
The purpose of this paper is to demonstrate the use of the general linear model (GLM) in problems with repeated measures on a dependent variable. Such problems include pretest-posttest designs, multitrial designs, and groups by trials designs. For each of these designs, a GLM analysis is demonstrated wherein full models are formed and restrictions…
Inverse Modelling Problems in Linear Algebra Undergraduate Courses
Martinez-Luaces, Victor E.
2013-01-01
This paper will offer an analysis from a theoretical point of view of mathematical modelling, applications and inverse problems of both causation and specification types. Inverse modelling problems give the opportunity to establish connections between theory and practice and to show this fact, a simple linear algebra example in two different…
Optical linear algebra processors: noise and error-source modeling.
Casasent, D; Ghosh, A
1985-06-01
The modeling of system and component noise and error sources in optical linear algebra processors (OLAP's) are considered, with attention to the frequency-multiplexed OLAP. General expressions are obtained for the output produced as a function of various component errors and noise. A digital simulator for this model is discussed.
Optical linear algebra processors - Noise and error-source modeling
Casasent, D.; Ghosh, A.
1985-01-01
The modeling of system and component noise and error sources in optical linear algebra processors (OLAPs) are considered, with attention to the frequency-multiplexed OLAP. General expressions are obtained for the output produced as a function of various component errors and noise. A digital simulator for this model is discussed.
A random effects generalized linear model for reliability compositive evaluation
ZHAO Hui; YU Dan
2009-01-01
This paper first proposes a random effects generalized linear model to evaluate the storage life of one kind of high reliable and small sample-sized products by combining multi-sources information of products coming from the same population but stored at different environments.The relevant algorithms are also provided.Simulation results manifest the soundness and effectiveness of the proposed model.
Logical consistency and sum-constrained linear models
van Perlo -ten Kleij, Frederieke; Steerneman, A.G.M.; Koning, Ruud H.
2006-01-01
A topic that has received quite some attention in the seventies and eighties is logical consistency of sum-constrained linear models. Loosely defined, a sum-constrained model is logically consistent if the restrictions on the parameters and explanatory variables are such that the sum constraint is a
Hasan ABBASI NOZARI; Hamed DEHGHAN BANADAKI; Mohammad MOKHTARE; Somaveh HEKMATI VAHED
2012-01-01
This study deals with the neuro-fuzzy (NF) modelling of a real industrial winding process in which the acquired NF model can be exploited to improve control performance and achieve a robust fault-tolerant system.A new simulator model is proposed for a winding process using non-linear identification based on a recurrent local linear neuro-fuzzy (RLLNF) network trained by local linear model tree (LOLIMOT),which is an incremental tree-based learning algorithm.The proposed NF models are compared with other known intelligent identifiers,namely multilayer perceptron (MLP) and radial basis function (RBF).Comparison of our proposed non-linear models and associated models obtained through the least square error (LSE) technique (the optimal modelling method for linear systems) confirms that the winding process is a non-linear system.Experimental results show the effectiveness of our proposed NF modelling approach.
Neural Network Hydrological Modelling: Linear Output Activation Functions?
Abrahart, R. J.; Dawson, C. W.
2005-12-01
The power to represent non-linear hydrological processes is of paramount importance in neural network hydrological modelling operations. The accepted wisdom requires non-polynomial activation functions to be incorporated in the hidden units such that a single tier of hidden units can thereafter be used to provide a 'universal approximation' to whatever particular hydrological mechanism or function is of interest to the modeller. The user can select from a set of default activation functions, or in certain software packages, is able to define their own function - the most popular options being logistic, sigmoid and hyperbolic tangent. If a unit does not transform its inputs it is said to possess a 'linear activation function' and a combination of linear activation functions will produce a linear solution; whereas the use of non-linear activation functions will produce non-linear solutions in which the principle of superposition does not hold. For hidden units, speed of learning and network complexities are important issues. For the output units, it is desirable to select an activation function that is suited to the distribution of the target values: e.g. binary targets (logistic); categorical targets (softmax); continuous-valued targets with a bounded range (logistic / tanh); positive target values with no known upper bound (exponential; but beware of overflow); continuous-valued targets with no known bounds (linear). It is also standard practice in most hydrological applications to use the default software settings and to insert a set of identical non-linear activation functions in the hidden layer and output layer processing units. Mixed combinations have nevertheless been reported in several hydrological modelling papers and the full ramifications of such activities requires further investigation and assessment i.e. non-linear activation functions in the hidden units connected to linear or clipped-linear activation functions in the output unit. There are two
The CREST reactive-burn model for explosives
Maheswaran M-A.
2011-01-01
Full Text Available CREST is an innovative reactive-burn model that has been developed at AWE for simulating shock initiation and detonation propagation behaviour in explosives. The model has a different basis from other reactive-burn models in that its reaction rate is independent of local flow variables behind the shock wave e.g. pressure and temperature. The foundation for CREST, based on a detailed analysis of data from particle-velocity gauge experiments, is that the reaction rate depends only on the local shock strength and the time since the shock passed. Since a measure of shock strength is the entropy of the non-reacted explosive, which remains constant behind a shock, CREST uses an entropy-dependent reaction rate. This paper will provide an overview of the CREST model and its predictive capability. In particular, it will be shown that the model can predict a wide range of experimental phenomena for both shock initiation (e.g. the effects of porosity and initial temperature on sustained-shock and thin-flyer initiation and detonation propagation (e.g. the diameter effect curve and detonation failure cones using a single set of coefficients.
Impact of mineralogical heterogeneity on reactive transport modelling
Liu, Min; Shabaninejad, Mehdi; Mostaghimi, Peyman
2017-07-01
Impact of mineralogical heterogeneity of rocks in reactive modelling is investigated by applying a pore scale model based on the Lattice Boltzmann and Finite Volume Methods. Mass transport, chemical reaction and solid structure modification are included in the model. A two-dimensional mineral map of a sandstone rock is acquired using the imaging technique of QEMSCAN SEM with Energy-Dispersive X-ray Spectroscopy (EDS). The mineralogical heterogeneity is explored by conducting multi-mineral reaction simulations on images containing various minerals. The results are then compared with the prediction of single mineral dissolution modelling. Dissolution patterns and permeability variations of multi-mineral and single mineral reactions are presented. The errors of single mineral reaction modelling are also estimated. Numerical results show that mineralogical heterogeneity can cause significant errors in permeability prediction, if a uniform mineral distribution is assumed. The errors are smaller in high Péclet regimes than in low Péclet regimes in this sample.
Unifying Model-Based and Reactive Programming within a Model-Based Executive
Williams, Brian C.; Gupta, Vineet; Norvig, Peter (Technical Monitor)
1999-01-01
Real-time, model-based, deduction has recently emerged as a vital component in AI's tool box for developing highly autonomous reactive systems. Yet one of the current hurdles towards developing model-based reactive systems is the number of methods simultaneously employed, and their corresponding melange of programming and modeling languages. This paper offers an important step towards unification. We introduce RMPL, a rich modeling language that combines probabilistic, constraint-based modeling with reactive programming constructs, while offering a simple semantics in terms of hidden state Markov processes. We introduce probabilistic, hierarchical constraint automata (PHCA), which allow Markov processes to be expressed in a compact representation that preserves the modularity of RMPL programs. Finally, a model-based executive, called Reactive Burton is described that exploits this compact encoding to perform efficIent simulation, belief state update and control sequence generation.
Enabling linear model for the IMGC-02 absolute gravimeter
Nagornyi, V D; Svitlov, S
2013-01-01
Measurement procedures of most rise-and-fall absolute gravimeters has to resolve singularity at the apex of the trajectory caused by the discrete fringe counting in the Michelson-type interferometers. Traditionally the singularity is addressed by implementing non-linear models of the trajectory, but they introduce problems of their own, such as biasness, non-uniqueness, and instability of the gravity estimates. Using IMGC-02 gravimeter as example, we show that the measurement procedure of the rise-and-fall gravimeters can be based on the linear models which successfully resolve the singularity and provide rigorous estimates of the gravity value. The linear models also facilitate further enhancements of the instrument, such as accounting for new types of disturbances and active compensation for the vibrations.
Linear Power-Flow Models in Multiphase Distribution Networks: Preprint
Bernstein, Andrey; Dall' Anese, Emiliano
2017-05-26
This paper considers multiphase unbalanced distribution systems and develops approximate power-flow models where bus-voltages, line-currents, and powers at the point of common coupling are linearly related to the nodal net power injections. The linearization approach is grounded on a fixed-point interpretation of the AC power-flow equations, and it is applicable to distribution systems featuring (i) wye connections; (ii) ungrounded delta connections; (iii) a combination of wye-connected and delta-connected sources/loads; and, (iv) a combination of line-to-line and line-to-grounded-neutral devices at the secondary of distribution transformers. The proposed linear models can facilitate the development of computationally-affordable optimization and control applications -- from advanced distribution management systems settings to online and distributed optimization routines. Performance of the proposed models is evaluated on different test feeders.
Defining a Family of Cognitive Diagnosis Models Using Log-Linear Models with Latent Variables
Henson, Robert A.; Templin, Jonathan L.; Willse, John T.
2009-01-01
This paper uses log-linear models with latent variables (Hagenaars, in "Loglinear Models with Latent Variables," 1993) to define a family of cognitive diagnosis models. In doing so, the relationship between many common models is explicitly defined and discussed. In addition, because the log-linear model with latent variables is a general model for…
Efficient estimation of moments in linear mixed models
Wu, Ping; Zhu, Li-Xing; 10.3150/10-BEJ330
2012-01-01
In the linear random effects model, when distributional assumptions such as normality of the error variables cannot be justified, moments may serve as alternatives to describe relevant distributions in neighborhoods of their means. Generally, estimators may be obtained as solutions of estimating equations. It turns out that there may be several equations, each of them leading to consistent estimators, in which case finding the efficient estimator becomes a crucial problem. In this paper, we systematically study estimation of moments of the errors and random effects in linear mixed models.
A new estimate of the parameters in linear mixed models
王松桂; 尹素菊
2002-01-01
In linear mixed models, there are two kinds of unknown parameters: one is the fixed effect, theother is the variance component. In this paper, new estimates of these parameters, called the spectral decom-position estimates, are proposed, Some important statistical properties of the new estimates are established,in particular the linearity of the estimates of the fixed effects with many statistical optimalities. A new methodis applied to two important models which are used in economics, finance, and mechanical fields. All estimatesobtained have good statistical and practical meaning.
Precise Asymptotics of Error Variance Estimator in Partially Linear Models
Shao-jun Guo; Min Chen; Feng Liu
2008-01-01
In this paper, we focus our attention on the precise asymptoties of error variance estimator in partially linear regression models, yi = xTi β + g(ti) +εi, 1 ≤i≤n, {εi,i = 1,... ,n } are i.i.d random errors with mean 0 and positive finite variance q2. Following the ideas of Allan Gut and Aurel Spataru[7,8] and Zhang[21],on precise asymptotics in the Baum-Katz and Davis laws of large numbers and precise rate in laws of the iterated logarithm, respectively, and subject to some regular conditions, we obtain the corresponding results in partially linear regression models.
Regularization Paths for Generalized Linear Models via Coordinate Descent
Jerome Friedman
2010-02-01
Full Text Available We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multi- nomial regression problems while the penalties include ℓ1 (the lasso, ℓ2 (ridge regression and mixtures of the two (the elastic net. The algorithms use cyclical coordinate descent, computed along a regularization path. The methods can handle large problems and can also deal efficiently with sparse features. In comparative timings we find that the new algorithms are considerably faster than competing methods.
A Mathematical Theory of the Gauged Linear Sigma Model
Fan, Huijun; Ruan, Yongbin
2015-01-01
We construct a rigorous mathematical theory of Witten's Gauged Linear Sigma Model (GLSM). Our theory applies to a wide range of examples, including many cases with non-Abelian gauge group. Both the Gromov-Witten theory of a Calabi-Yau complete intersection X and the Landau-Ginzburg dual (FJRW-theory) of X can be expressed as gauged linear sigma models. Furthermore, the Landau-Ginzburg/Calabi-Yau correspondence can be interpreted as a variation of the moment map or a deformation of GIT in the GLSM. This paper focuses primarily on the algebraic theory, while a companion article will treat the analytic theory.
The minimal linear sigma model for the Goldstone Higgs
Feruglio, Ferruccio; Kanshin, Kirill; Machado, Pedro Accioly Nogueira; Rigolin, Stefano; Saa, Sara
2016-01-01
In the context of the minimal SO(5) linear {\\sigma}-model, a complete renormalizable Lagrangian -including gauge bosons and fermions- is considered, with the symmetry softly broken to SO(4). The scalar sector describes both the electroweak Higgs doublet and the singlet {\\sigma}. Varying the {\\sigma} mass would allow to sweep from the regime of perturbative ultraviolet completion to the non-linear one assumed in models in which the Higgs particle is a low-energy remnant of some strong dynamics. We analyze the phenomenological implications and constraints from precision observables and LHC data. Furthermore, we derive the d <= 6 effective Lagrangian in the limit of heavy exotic fermions.
Dynamic generalized linear models for monitoring endemic diseases
Lopes Antunes, Ana Carolina; Jensen, Dan Børge; Halasa, T.
The objective was to use a Dynamic Generalized Linear Model (DGLM) based on abinomial distribution with a linear trend, for monitoring the PRRS (Porcine Reproductive and Respiratory Syndrome sero-prevalence in Danish swine herds. The DGLM was described and its performance for monitoring control...... in sero-prevalence. Based on this, it was possible to detect variations in the growth model component. This study is a proof-of-concept, demonstrating the use of DGLMs for monitoring endemic diseases. In addition, the principles stated might be useful in general research on monitoring and surveillance...
Formal Requirements Modeling for Reactive Systems with Coloured Petri Nets
Tjell, Simon
This dissertation presents the contributions of seven publications all concerned with the application of Coloured Petri Nets (CPN) to requirements modeling for reactive systems. The publications are introduced along with relevant background material and related work, and their contributions...... interface composed of recognizable artifacts and activities. The presentation of the three publications related to Use Cases is followed by a the presentation of a publication formalizing some of the guidelines applied for structuring the CPN requirements models|namely the guidelines that make it possible...... activity. The traces are automatically recorded during execution of the model. The second publication presents a formally specified framework for automating a large part of the tasks related to integrating Problem Frames with CPN. The framework is specified in VDM++, and allows the modeler to automatically...
Physicochemical model for reactive sputtering of hot target
Shapovalov, Viktor I.; Karzin, Vitaliy V.; Bondarenko, Anastasia S.
2017-02-01
A physicochemical model for reactive magnetron sputtering of a metal target is described in this paper. The target temperature in the model is defined as a function of the ion current density. Synthesis of the coating occurs due to the surface chemical reaction. The law of mass action, the Langmuir isotherm and the Arrhenius equation for non-isothermal conditions were used for mathematical description of the reaction. The model takes into consideration thermal electron emission and evaporation of the target surface. The system of eight algebraic equations, describing the model, was solved for the tantalum target sputtered in the oxygen environment. It was established that the hysteresis effect disappears with the increase of the ion current density.
A new mobile-immobile model for reactive solute transport with scale-dependent dispersion
Gao, Guangyao; Zhan, Hongbin; Feng, Shaoyuan; Fu, Bojie; Ma, Ying; Huang, Guanhua
2010-08-01
This study proposed a new mobile-immobile model (MIM) to describe reactive solute transport with scale-dependent dispersion in heterogeneous porous media. The model was derived from the conventional MIM but assumed the dispersivity to be a linear or exponential function of travel distance. The linear adsorption and the first-order degradation of solute were also considered in the model. The Laplace transform technique and the de Hoog numerical Laplace inversion method were applied to solve the developed model. Solute breakthrough curves (BTCs) obtained from MIM with scale-dependent and constant dispersions were compared, and a constant effective dispersivity was provided to reflect the lumped scale-dependent dispersion effect. The effective dispersivity was calculated by arithmetically averaging the distance-dependent dispersivity. With this effective dispersivity, MIM could produce similar BTC as that from MIM with scale-dependent dispersion in porous media with moderate heterogeneity. The applicability of the proposed new model was tested with concentration data from a 1,250-cm long and highly heterogeneous soil column. The simulation results indicated that MIM with constant and linear distance-dependent dispersivities were unable to adequately describe the measured BTCs in the column, while MIM with exponential distance-dependent dispersivity satisfactorily captured the evolution of BTCs.
Crystal Growth Models of Dexamethasone Sodium Phosphate in a MSMPR Reactive Crystallizer
郝红勋; 王静康; 王永莉; 侯宝红
2005-01-01
The reactive crystallization process of dexamethasone sodium phosphate was investigated in a continuous mixed-suspension, mixed-product-removal(MSMPR) crystallizer. Analyzing experimental data, it was found that the growth of product crystal was size-dependent. The Bransom, CR, ASL, M J2 and M J3 size-dependent growth models were discussed in details. Using experimental steady state population density data of dexamethasone sodium phosphate, parameters of five size-dependent growth models were determined by the method of non-linear least-squares. By comparison of experimental population density and linear growth rate data with those obtained from the five size-dependent growth models, it was found that the MJ3 model predicts the growth more accurately than do the other four models. Based on the theory of population balance, the crystal nucleation and growth rate equations of dexamethasone sodium phosphate were determined by non-linear regression method. The effects of different operation parameters such as supersaturation, magma density and temperature on the quality of product crystal were also discussed, and the optimal operation conditions were derived.
Confirming the Lanchestrian linear-logarithmic model of attrition
Hartley, D.S. III.
1990-12-01
This paper is the fourth in a series of reports on the breakthrough research in historical validation of attrition in conflict. Significant defense policy decisions, including weapons acquisition and arms reduction, are based in part on models of conflict. Most of these models are driven by their attrition algorithms, usually forms of the Lanchester square and linear laws. None of these algorithms have been validated. The results of this paper confirm the results of earlier papers, using a large database of historical results. The homogeneous linear-logarithmic Lanchestrian attrition model is validated to the extent possible with current initial and final force size data and is consistent with the Iwo Jima data. A particular differential linear-logarithmic model is described that fits the data very well. A version of Helmbold's victory predicting parameter is also confirmed, with an associated probability function. The implications of these findings are potentially far-reaching. Two-sided daily attrition data on a large number of battles is needed to absolutely confirm these results. Such a confirmation will require that numerous computer conflict models containing square and linear law based attrition algorithms be reexamined. It is conceivable that complex mixed, heterogeneous, square plus linear law algorithms may produce the same results as a homogeneous mixed linear-logarithmic law algorithm; however, such an occurrence is by no means assured. Even without such absolute confirmation, the results of this research allow the analysis of combat data for the effects of training, weather, leadership, and other human factors, unencumbered by the force size effects.
Control Rod Driveline Reactivity Feedback Model for Liquid Metal Reactors
Kwon, Young-Min; Jeong, Hae-Yong; Chang, Won-Pyo; Cho, Chung-Ho; Lee, Yong-Bum
2008-01-15
The thermal expansion of the control rod drivelines (CRDL) is one important passive mitigator under all unprotected accident conditions in the metal and oxide cores. When the CRDL are washed by hot sodium in the coolant outlet plenum, the CRDL thermally expands and causes the control rods to be inserted further down into the active core region, providing a negative reactivity feedback. Since the control rods are attached to the top of the vessel head and the core attaches to the bottom of the reactor vessel (RV), the expansion of the vessel wall as it heats will either lower the core or raise the control rods supports. This contrary thermal expansion of the reactor vessel wall pulls the control rods out of the core somewhat, providing a positive reactivity feedback. However this is not a safety factor early in a transient because its time constant is relatively large. The total elongated length is calculated by subtracting the vessel expansion from the CRDL expansion to determine the net control rod expansion into the core. The system-wide safety analysis code SSC-K includes the CRDL/RV reactivity feedback model in which control rod and vessel expansions are calculated using single-nod temperatures for the vessel and CRDL masses. The KALIMER design has the upper internal structures (UIS) in which the CRDLs are positioned outside the structure where they are exposed to the mixed sodium temperature exiting the core. A new method to determine the CRDL expansion is suggested. Two dimensional hot pool thermal hydraulic model (HP2D) originally developed for the analysis of the stratification phenomena in the hot pool is utilized for a detailed heat transfer between the CRDL mass and the hot pool coolant. However, the reactor vessel wall temperature is still calculated by a simple lumped model.
Piecewise linear and Boolean models of chemical reaction networks
Veliz-Cuba, Alan; Kumar, Ajit; Josić, Krešimir
2014-01-01
Models of biochemical networks are frequently complex and high-dimensional. Reduction methods that preserve important dynamical properties are therefore essential for their study. Interactions in biochemical networks are frequently modeled using Hill functions (xn/(Jn + xn)). Reduced ODEs and Boolean approximations of such model networks have been studied extensively when the exponent n is large. However, while the case of small constant J appears in practice, it is not well understood. We provide a mathematical analysis of this limit, and show that a reduction to a set of piecewise linear ODEs and Boolean networks can be mathematically justified. The piecewise linear systems have closed form solutions that closely track those of the fully nonlinear model. The simpler, Boolean network can be used to study the qualitative behavior of the original system. We justify the reduction using geometric singular perturbation theory and compact convergence, and illustrate the results in network models of a toggle switch and an oscillator. PMID:25412739
Piecewise linear and Boolean models of chemical reaction networks.
Veliz-Cuba, Alan; Kumar, Ajit; Josić, Krešimir
2014-12-01
Models of biochemical networks are frequently complex and high-dimensional. Reduction methods that preserve important dynamical properties are therefore essential for their study. Interactions in biochemical networks are frequently modeled using Hill functions ([Formula: see text]). Reduced ODEs and Boolean approximations of such model networks have been studied extensively when the exponent [Formula: see text] is large. However, while the case of small constant [Formula: see text] appears in practice, it is not well understood. We provide a mathematical analysis of this limit and show that a reduction to a set of piecewise linear ODEs and Boolean networks can be mathematically justified. The piecewise linear systems have closed-form solutions that closely track those of the fully nonlinear model. The simpler, Boolean network can be used to study the qualitative behavior of the original system. We justify the reduction using geometric singular perturbation theory and compact convergence, and illustrate the results in network models of a toggle switch and an oscillator.
New NIR Calibration Models Speed Biomass Composition and Reactivity Characterization
2015-09-01
Obtaining accurate chemical composition and reactivity (measures of carbohydrate release and yield) information for biomass feedstocks in a timely manner is necessary for the commercialization of biofuels. This highlight describes NREL's work to use near-infrared (NIR) spectroscopy and partial least squares multivariate analysis to develop calibration models to predict the feedstock composition and the release and yield of soluble carbohydrates generated by a bench-scale dilute acid pretreatment and enzymatic hydrolysis assay. This highlight is being developed for the September 2015 Alliance S&T Board meeting.
Modelling reactive transport in a phosphogypsum dump, Venezia, Italia
Calcara, Massimo; Borgia, Andrea; Cattaneo, Laura; Bartolo, Sergio; Clemente, Gianni; Glauco Amoroso, Carlo; Lo Re, Fabio; Tozzato, Elena
2013-04-01
We develop a reactive-transport porous media flow model for a phosphogypsum dump located on the intertidal deposits of the Venetian Lagoon: 1. we construct a complex conceptual and geologic model from field data using the GMS™ graphical user interface; 2. the geological model is mapped onto a rectangular MODFLOW grid; 3. using the TMT2 FORTRAN90 code we translate this grid into the MESH, INCON and GENER input files for the TOUGH2 series of codes; 4. we run TOUGH-REACT to model flow and reactive transport in the dump and the sediments below it. The model includes 3 different dump materials (phosphogypsum, bituminous and hazardous wastes) with the pores saturated by specific fluids. The sediments below the dump are formed by an intertidal sequence of calcareous sands and silts, in addition to clays and organic deposits, all of which are initially saturated with lagoon salty waters. The recharge rain-water dilutes the dump fluids. In turn, the percolates from the dump react with the underlying sediments and the sea water that saturates them. Simulation results have been compared with chemical sampled analyses. In fact, in spite of the simplicity of our model we are able to show how the pH becomes neutral at a short distance below the dump, a fact observed during aquifer monitoring. The spatial and temporal evolution of dissolution and precipitation reactions occur in our model much alike reality. Mobility of some elements, such as divalent iron, are reduced by specific and concurrent conditions of pH from near-neutrality to moderately high values and positive redox potential; opposite conditions favour mobility of potentially toxic metals such as Cr, As Cd and Pb. Vertical movement are predominant. Trend should be therefore heavily influenced by pH and Eh values. If conditions are favourable to mobility, concentration of these substances in the bottom strata could be high. However, simulation suggest that the sediments tend to reduce the transport potential of
Can Ising model and/or QKPZ equation properly describe reactive-wetting interface dynamics?
Efraim, Yael; Taitelbaum, Haim
2009-09-01
The reactive-wetting process, e.g. spreading of a liquid droplet on a reactive substrate is known as a complex, non-linear process with high sensitivity to minor fluctuations. The dynamics and geometry of the interface (triple line) between the materials is supposed to shed light on the main mechanisms of the process. We recently studied a room temperature reactive-wetting system of a small (˜ 150 μm) Hg droplet that spreads on a thin (˜ 4000 Å) Ag substrate. We calculated the kinetic roughening exponents (growth and roughness), as well as the persistence exponent of points on the advancing interface. In this paper we address the question whether there exists a well-defined model to describe the interface dynamics of this system, by performing two sets of numerical simulations. The first one is a simulation of an interface propagating according to the QKPZ equation, and the second one is a landscape of an Ising chain with ferromagnetic interactions in zero temperature. We show that none of these models gives a full description of the dynamics of the experimental reactivewetting system, but each one of them has certain common growth properties with it. We conjecture that this results from a microscopic behavior different from the macroscopic one. The microscopic mechanism, reflected by the persistence exponent, resembles the Ising behavior, while in the macroscopic scale, exemplified by the growth exponent, the dynamics looks more like the QKPZ dynamics.
Curtis, Gary P.; Lu, Dan; Ye, Ming
2015-01-01
While Bayesian model averaging (BMA) has been widely used in groundwater modeling, it is infrequently applied to groundwater reactive transport modeling because of multiple sources of uncertainty in the coupled hydrogeochemical processes and because of the long execution time of each model run. To resolve these problems, this study analyzed different levels of uncertainty in a hierarchical way, and used the maximum likelihood version of BMA, i.e., MLBMA, to improve the computational efficiency. This study demonstrates the applicability of MLBMA to groundwater reactive transport modeling in a synthetic case in which twenty-seven reactive transport models were designed to predict the reactive transport of hexavalent uranium (U(VI)) based on observations at a former uranium mill site near Naturita, CO. These reactive transport models contain three uncertain model components, i.e., parameterization of hydraulic conductivity, configuration of model boundary, and surface complexation reactions that simulate U(VI) adsorption. These uncertain model components were aggregated into the alternative models by integrating a hierarchical structure into MLBMA. The modeling results of the individual models and MLBMA were analyzed to investigate their predictive performance. The predictive logscore results show that MLBMA generally outperforms the best model, suggesting that using MLBMA is a sound strategy to achieve more robust model predictions relative to a single model. MLBMA works best when the alternative models are structurally distinct and have diverse model predictions. When correlation in model structure exists, two strategies were used to improve predictive performance by retaining structurally distinct models or assigning smaller prior model probabilities to correlated models. Since the synthetic models were designed using data from the Naturita site, the results of this study are expected to provide guidance for real-world modeling. Limitations of applying MLBMA to the
Non-linear calibration models for near infrared spectroscopy.
Ni, Wangdong; Nørgaard, Lars; Mørup, Morten
2014-02-27
Different calibration techniques are available for spectroscopic applications that show nonlinear behavior. This comprehensive comparative study presents a comparison of different nonlinear calibration techniques: kernel PLS (KPLS), support vector machines (SVM), least-squares SVM (LS-SVM), relevance vector machines (RVM), Gaussian process regression (GPR), artificial neural network (ANN), and Bayesian ANN (BANN). In this comparison, partial least squares (PLS) regression is used as a linear benchmark, while the relationship of the methods is considered in terms of traditional calibration by ridge regression (RR). The performance of the different methods is demonstrated by their practical applications using three real-life near infrared (NIR) data sets. Different aspects of the various approaches including computational time, model interpretability, potential over-fitting using the non-linear models on linear problems, robustness to small or medium sample sets, and robustness to pre-processing, are discussed. The results suggest that GPR and BANN are powerful and promising methods for handling linear as well as nonlinear systems, even when the data sets are moderately small. The LS-SVM is also attractive due to its good predictive performance for both linear and nonlinear calibrations.
Dynamic Response of Linear Mechanical Systems Modeling, Analysis and Simulation
Angeles, Jorge
2012-01-01
Dynamic Response of Linear Mechanical Systems: Modeling, Analysis and Simulation can be utilized for a variety of courses, including junior and senior-level vibration and linear mechanical analysis courses. The author connects, by means of a rigorous, yet intuitive approach, the theory of vibration with the more general theory of systems. The book features: A seven-step modeling technique that helps structure the rather unstructured process of mechanical-system modeling A system-theoretic approach to deriving the time response of the linear mathematical models of mechanical systems The modal analysis and the time response of two-degree-of-freedom systems—the first step on the long way to the more elaborate study of multi-degree-of-freedom systems—using the Mohr circle Simple, yet powerful simulation algorithms that exploit the linearity of the system for both single- and multi-degree-of-freedom systems Examples and exercises that rely on modern computational toolboxes for both numerical and symbolic compu...
RF Circuit linearity optimization using a general weak nonlinearity model
Cheng, W.; Oude Alink, M.S.; Annema, Anne J.; Croon, Jeroen A.; Nauta, Bram
2012-01-01
This paper focuses on optimizing the linearity in known RF circuits, by exploring the circuit design space that is usually available in today’s deep submicron CMOS technologies. Instead of using brute force numerical optimizers we apply a generalized weak nonlinearity model that only involves AC
EMPIRICAL LIKELIHOOD FOR LINEAR MODELS UNDER m-DEPENDENT ERRORS
QinYongsong; JiangBo; LiYufang
2005-01-01
In this paper，the empirical likelihood confidence regions for the regression coefficient in a linear model are constructed under m-dependent errors. It is shown that the blockwise empirical likelihood is a good way to deal with dependent samples.
Mathematical modelling and linear stability analysis of laser fusion cutting
Hermanns, Torsten; Schulz, Wolfgang; Vossen, Georg; Thombansen, Ulrich
2016-06-01
A model for laser fusion cutting is presented and investigated by linear stability analysis in order to study the tendency for dynamic behavior and subsequent ripple formation. The result is a so called stability function that describes the correlation of the setting values of the process and the process' amount of dynamic behavior.
Plane answers to complex questions the theory of linear models
Christensen, Ronald
1987-01-01
This book was written to rigorously illustrate the practical application of the projective approach to linear models. To some, this may seem contradictory. I contend that it is possible to be both rigorous and illustrative and that it is possible to use the projective approach in practical applications. Therefore, unlike many other books on linear models, the use of projections and sub spaces does not stop after the general theory. They are used wherever I could figure out how to do it. Solving normal equations and using calculus (outside of maximum likelihood theory) are anathema to me. This is because I do not believe that they contribute to the understanding of linear models. I have similar feelings about the use of side conditions. Such topics are mentioned when appropriate and thenceforward avoided like the plague. On the other side of the coin, I just as strenuously reject teaching linear models with a coordinate free approach. Although Joe Eaton assures me that the issues in complicated problems freq...
A least squares estimation method for the linear learning model
B. Wierenga (Berend)
1978-01-01
textabstractThe author presents a new method for estimating the parameters of the linear learning model. The procedure, essentially a least squares method, is easy to carry out and avoids certain difficulties of earlier estimation procedures. Applications to three different data sets are reported, a
Tests of risk premia in linear factor models
Kleibergen, F.
2009-01-01
We show that statistical inference on the risk premia in linear factor models that is based on the Fama-MacBeth (FM) and generalized least squares (GLS) two-pass risk premia estimators is misleading when the β’s are small and/or the number of assets is large. We propose novel statistics, that are ba
Tests of risk premia in linear factor models
Kleibergen, F.R.
2005-01-01
We show that inference on risk premia in linear factor models that is based on the Fama-MacBeth and GLS risk premia estimators is misleading when the ß’s are small and/or the number of assets is large. We propose some novel statistics that remain trustworthy in these cases. The inadequacy of Fama-Ma
Tests of risk premia in linear factor models
Kleibergen, F.
2009-01-01
We show that statistical inference on the risk premia in linear factor models that is based on the Fama-MacBeth (FM) and generalized least squares (GLS) two-pass risk premia estimators is misleading when the β’s are small and/or the number of assets is large. We propose novel statistics, that are
Combined forecasts from linear and nonlinear time series models
N. Terui (Nobuhiko); H.K. van Dijk (Herman)
1999-01-01
textabstractCombined forecasts from a linear and a nonlinear model are investigated for time series with possibly nonlinear characteristics. The forecasts are combined by a constant coefficient regression method as well as a time varying method. The time varying method allows for a locally (non)line
Tableaux and Systemes : Early French Contributions to Linear Production Models
Steenge, Albertus; van den Berg, Richard
2017-01-01
Properly speaking the history of linear production modelling begins in the second half of the 18th century. A comparison between Francois Quesnay's Tableaux economiques and Achilles-Nicolas Isnard’s systèmes des richesses provides insights into the various possible directions within this nascent bra
The Moduli Space in the Gauged Linear Sigma Model
Fan, Huijun; Ruan, Yongbin
2016-01-01
This is a survey article for the mathematical theory of Witten's Gauged Linear Sigma Model, as developed recently by the authors. Instead of developing the theory in the most general setting, in this paper we focus on the description of the moduli.
S-AMP for non-linear observation models
Cakmak, Burak; Winther, Ole; Fleury, Bernard H.
2015-01-01
Recently we presented the S-AMP approach, an extension of approximate message passing (AMP), to be able to handle general invariant matrix ensembles. In this contribution we extend S-AMP to non-linear observation models. We obtain generalized AMP (GAMP) as the special case when the measurement...
Holst, René; Jørgensen, Bent
2015-01-01
The paper proposes a versatile class of multiplicative generalized linear longitudinal mixed models (GLLMM) with additive dispersion components, based on explicit modelling of the covariance structure. The class incorporates a longitudinal structure into the random effects models and retains...... a marginal as well as a conditional interpretation. The estimation procedure is based on a computationally efficient quasi-score method for the regression parameters combined with a REML-like bias-corrected Pearson estimating function for the dispersion and correlation parameters. This avoids...... the multidimensional integral of the conventional GLMM likelihood and allows an extension of the robust empirical sandwich estimator for use with both association and regression parameters. The method is applied to a set of otholit data, used for age determination of fish....
Intuitionistic Fuzzy Weighted Linear Regression Model with Fuzzy Entropy under Linear Restrictions.
Kumar, Gaurav; Bajaj, Rakesh Kumar
2014-01-01
In fuzzy set theory, it is well known that a triangular fuzzy number can be uniquely determined through its position and entropies. In the present communication, we extend this concept on triangular intuitionistic fuzzy number for its one-to-one correspondence with its position and entropies. Using the concept of fuzzy entropy the estimators of the intuitionistic fuzzy regression coefficients have been estimated in the unrestricted regression model. An intuitionistic fuzzy weighted linear regression (IFWLR) model with some restrictions in the form of prior information has been considered. Further, the estimators of regression coefficients have been obtained with the help of fuzzy entropy for the restricted/unrestricted IFWLR model by assigning some weights in the distance function.
Practical likelihood analysis for spatial generalized linear mixed models
Bonat, W. H.; Ribeiro, Paulo Justiniano
2016-01-01
We investigate an algorithm for maximum likelihood estimation of spatial generalized linear mixed models based on the Laplace approximation. We compare our algorithm with a set of alternative approaches for two datasets from the literature. The Rhizoctonia root rot and the Rongelap are, respectiv......We investigate an algorithm for maximum likelihood estimation of spatial generalized linear mixed models based on the Laplace approximation. We compare our algorithm with a set of alternative approaches for two datasets from the literature. The Rhizoctonia root rot and the Rongelap are...... of Laplace approximation include the computation of the maximized log-likelihood value, which can be used for model selection and tests, and the possibility to obtain realistic confidence intervals for model parameters based on profile likelihoods. The Laplace approximation also avoids the tuning...
Benchmarking reactive transport models at a hillslope scale
Kalbacher, T.; He, W.; Nixdorf, E.; Jang, E.; Fleckenstein, J. H.; Kolditz, O.
2015-12-01
The hillslope scale is an important transition between the field scale and the catchment scale. The water flow in the unsaturated zone of a hillslope can be highly dynamic, which can lead to dynamic changes of groundwater flow or stream outflow. Additionally, interactions among host rock formation, soil properties and recharge water from precipitation or anthropogenic activities (mining, agriculture etc.) can influence the water quality of groundwater and stream in the long term. To simulate reactive transport processes at such a scale is a challenging task. On the one hand, simulation of water flow in a coupled soil-aquifer system often involves solving of highly non-linear PDEs such as Richards equation; on the other hand, one has to consider complicated biogeochemical reactions (e.g. water-rock interactions, biological degradation, redox reactions). Both aspects are computationally expensive and have high requirements on the numerical precision and stabilities of the employed code. The primary goals of this study are as follows: i) Identify the bottlenecks and quantitatively analyse their influence on simulation of biogeochemical reactions at a hillslope scale; ii) find or suggest practical strategies to deal with these bottlenecks, thus to provide detailed hints for future improvements of reactive transport simulators. To achieve these goals, the parallelized reactive transport simulator OGS#IPhreeqc has been applied to simulate two benchmark examples. The first example is about uranium leaching based on Šimůnek et al. (2012), which considers the leaching of uranium from a mill tailing and accompanied mineral dissolution/precipitation. The geochemical system is then extended to include redox reactions in the second example. Based on these examples, the numerical stability and parallel performance of the tool is analysed. ReferenceŠimůnek, J., Jacques, D., Šejna, M., van Genuchten, M. T.: The HP2 program for HYDRUS (2D/3D), A coupled code for simulating two
Fang, Yilin; Scheibe, Timothy D.; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E.; Lovley, Derek R.
2011-03-01
The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint-based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species and multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The
Defects in the discrete non-linear Schroedinger model
Doikou, Anastasia, E-mail: adoikou@upatras.gr [University of Patras, Department of Engineering Sciences, Physics Division, GR-26500 Patras (Greece)
2012-01-01
The discrete non-linear Schroedinger (NLS) model in the presence of an integrable defect is examined. The problem is viewed from a purely algebraic point of view, starting from the fundamental algebraic relations that rule the model. The first charges in involution are explicitly constructed, as well as the corresponding Lax pairs. These lead to sets of difference equations, which include particular terms corresponding to the impurity point. A first glimpse regarding the corresponding continuum limit is also provided.
Deterministic operations research models and methods in linear optimization
Rader, David J
2013-01-01
Uniquely blends mathematical theory and algorithm design for understanding and modeling real-world problems Optimization modeling and algorithms are key components to problem-solving across various fields of research, from operations research and mathematics to computer science and engineering. Addressing the importance of the algorithm design process. Deterministic Operations Research focuses on the design of solution methods for both continuous and discrete linear optimization problems. The result is a clear-cut resource for understanding three cornerstones of deterministic operations resear
Linear Sigma Model Toolshed for D-brane Physics
Hellerman, Simeon
2001-08-23
Building on earlier work, we construct linear sigma models for strings on curved spaces in the presence of branes. Our models include an extremely general class of brane-worldvolume gauge field configurations. We explain in an accessible manner the mathematical ideas which suggest appropriate worldsheet interactions for generating a given open string background. This construction provides an explanation for the appearance of the derived category in D-brane physic complementary to that of recent work of Douglas.
Prediction of Typhoon Tracks Using Dynamic Linear Models
Keon-Tae SOHN; H. Joe KWON; Ae-Sook SUH
2003-01-01
This paper presents a study on the statistical forecasts of typhoon tracks. Numerical models havetheir own systematic errors, like a bias. In order to improve the accuracy of track forecasting, a statisticalmodel called DLM (dynamic linear model) is applied to remove the systematic error. In the analysis oftyphoons occurring over the western North Pacific in 1997 and 2000, DLM is useful as an adaptive modelfor the prediction of typhoon tracks.
Estimation linear model using block generalized inverse of a matrix
Jasińska, Elżbieta; Preweda, Edward
2013-01-01
The work shows the principle of generalized linear model, point estimation, which can be used as a basis for determining the status of movements and deformations of engineering objects. The structural model can be put on any boundary conditions, for example, to ensure the continuity of the deformations. Estimation by the method of least squares was carried out taking into account the terms and conditions of the Gauss- Markov for quadratic forms stored using Lagrange function. The original sol...
Linear lattice modeling of the recycler ring at Fermilab
Xiao, Meiqin; Valishev, Alexander; Nagaslaev, Vladimir P.; /Fermilab; Sajaev, Vadim; /Argonne
2006-06-01
Substantial differences are found in tunes and beta functions between the existing linear model and the real storage ring. They result in difficulties when tuning the machine to new lattice conditions. We are trying to correct the errors by matching the model into the real machine using Orbit Response Matrix (ORM) Fit method. The challenges with ORM particularly in the Recycler ring and the results are presented in this paper.
Finite element modeling of nanotube structures linear and non-linear models
Awang, Mokhtar; Muhammad, Ibrahim Dauda
2016-01-01
This book presents a new approach to modeling carbon structures such as graphene and carbon nanotubes using finite element methods, and addresses the latest advances in numerical studies for these materials. Based on the available findings, the book develops an effective finite element approach for modeling the structure and the deformation of grapheme-based materials. Further, modeling processing for single-walled and multi-walled carbon nanotubes is demonstrated in detail.
Samper, J.; Mon, A.; Montenegro, L.; Naves, A.; Fernández, J.
2016-12-01
High-level radioactive waste disposal in a deep geological repository is based on a multibarrier concept which combines natural barriers such as the geological formation and artificial barriers such as metallic containers, bentonite and concrete buffers and sealing materials. The stability and performance of the bentonite barrier could be affected by the corrosion products at the canister-bentonite interface and the hyperalkaline conditions caused by the degradation of concrete at the bentonite-concrete interface. Additionally, the host clay formation could also be affected by the hyperalkaline plume at the concrete-clay interface. Here we present a nonisothermal reactive transport model of the long-term interactions of the compacted bentonite with the corrosion products of a carbon-steel canister and the concrete liner of the engineered barrier of a high-level radioactive waste repository in clay. This problem involves large pH changes with a hyperalkaline high-pH plume, complex mineral dissolution/precipitation patterns, cation exchange reactions and proton surface complexation. These reactions lead to large changes in porosity which can even lead to pore clogging. Model results show that magnetite, the main corrosion product, precipitates and reduces significantly the porosity of the bentonite near the canister. The degradation of the concrete liner leads to the precipitation of secondary minerals and the reduction of the porosity of the bentonite and the clay formation at their interfaces with the concrete liner. The zones affected by pore clogging at the canister-bentonite, bentonite-concrete and concrete-clay interfaces at 1 Ma are equal to 10, 25 and 25 mm thick, respectively. The results of our simulations share many of the features of the models reported by others for engineered barrier systems at similar chemical conditions, including: 1) Narrow alteration zones; and 2) Pore clogging at the canister-bentonite, bentonite-concrete and concrete
Adaptive Mesh Refinement in Reactive Transport Modeling of Subsurface Environments
Molins, S.; Day, M.; Trebotich, D.; Graves, D. T.
2015-12-01
Adaptive mesh refinement (AMR) is a numerical technique for locally adjusting the resolution of computational grids. AMR makes it possible to superimpose levels of finer grids on the global computational grid in an adaptive manner allowing for more accurate calculations locally. AMR codes rely on the fundamental concept that the solution can be computed in different regions of the domain with different spatial resolutions. AMR codes have been applied to a wide range of problem including (but not limited to): fully compressible hydrodynamics, astrophysical flows, cosmological applications, combustion, blood flow, heat transfer in nuclear reactors, and land ice and atmospheric models for climate. In subsurface applications, in particular, reactive transport modeling, AMR may be particularly useful in accurately capturing concentration gradients (hence, reaction rates) that develop in localized areas of the simulation domain. Accurate evaluation of reaction rates is critical in many subsurface applications. In this contribution, we will discuss recent applications that bring to bear AMR capabilities on reactive transport problems from the pore scale to the flood plain scale.
Boolean Variables in Economic Models Solved by Linear Programming
Lixandroiu D.
2014-12-01
Full Text Available The article analyses the use of logical variables in economic models solved by linear programming. Focus is given to the presentation of the way logical constraints are obtained and of the definition rules based on predicate logic. Emphasis is also put on the possibility to use logical variables in constructing a linear objective function on intervals. Such functions are encountered when costs or unitary receipts are different on disjunct intervals of production volumes achieved or sold. Other uses of Boolean variables are connected to constraint systems with conditions and the case of a variable which takes values from a finite set of integers.
General Linear Models: An Integrated Approach to Statistics
Andrew Faulkner
2008-09-01
Full Text Available Generally, in psychology, the various statistical analyses are taught independently from each other. As a consequence, students struggle to learn new statistical analyses, in contexts that differ from their textbooks. This paper gives a short introduction to the general linear model (GLM, in which it is showed that ANOVA (one-way, factorial, repeated measure and analysis of covariance is simply a multiple correlation/regression analysis (MCRA. Generalizations to other cases, such as multivariate and nonlinear analysis, are also discussed. It can easily be shown that every popular linear analysis can be derived from understanding MCRA.
Modeling Reactive Transport in Coupled Groundwater-Conduit Systems
Spiessl, S. M.; Sauter, M.; Zheng, C.; Viswanathan, H. S.
2002-05-01
Modeling reactive transport in coupled groundwater-conduit systems requires consideration of two transport time scales in the flow and transport models. Consider for example a subsurface mine consisting of a network of highly conductive shafts, drifts or ventilation raises (i.e., conduits) within the considerably less permeable ore material (i.e., matrix). In the conduits, potential contaminants can travel much more rapidly than in the background aquifer (matrix). Since conduits cannot necessarily be regarded as a continuum, double continuum models are only of limited use for simulation of contaminant transport in such coupled groundwater-conduit systems. This study utilizes a "hybrid" flow and transport model in which contaminants can in essence be transported at a slower time scale in the matrix and at a faster time scale in the conduits. The hybrid flow model uses an approach developed by Clemens et al. (1996), which is based on the modelling of flow in a discrete pipe network, coupled to a continuum representing the low-permeability inter-conduit matrix blocks. Laminar or turbulent flow can be simulated in the different pipes depending on the flow conditions in the model domain. The three-dimensional finite-difference groundwater flow model MODFLOW (Harbaugh and McDonald, 1996) is used to simulate flow in the continuum. Contaminant transport within the matrix is simulated with a continuum approach using the three-dimensional multi-species solute transport model MT3DMS (Zheng and Wang, 1999), while that in the conduit system is simulated with a one-dimensional advective transport model. As a first step for reactive transport modeling in such systems, only equilibrium reactions among multiple species are considered by coupling the hybrid transport model to a geochemical speciation package. An idealized mine network developed by Viswanathan and Sauter (2001) is used as a test problem in this study. The numerical experiment is based on reference date collected from
Solving linear integer programming problems by a novel neural model.
Cavalieri, S
1999-02-01
The paper deals with integer linear programming problems. As is well known, these are extremely complex problems, even when the number of integer variables is quite low. Literature provides examples of various methods to solve such problems, some of which are of a heuristic nature. This paper proposes an alternative strategy based on the Hopfield neural network. The advantage of the strategy essentially lies in the fact that hardware implementation of the neural model allows for the time required to obtain a solution so as not depend on the size of the problem to be solved. The paper presents a particular class of integer linear programming problems, including well-known problems such as the Travelling Salesman Problem and the Set Covering Problem. After a brief description of this class of problems, it is demonstrated that the original Hopfield model is incapable of supplying valid solutions. This is attributed to the presence of constant bias currents in the dynamic of the neural model. A demonstration of this is given and then a novel neural model is presented which continues to be based on the same architecture as the Hopfield model, but introduces modifications thanks to which the integer linear programming problems presented can be solved. Some numerical examples and concluding remarks highlight the solving capacity of the novel neural model.
G.G. Zhemerov
2015-12-01
Full Text Available Purpose. The contradictions in the use of the term «reactive power» require justification by clarifying its physical meaning. The aim of the paper is to reveal the physical meaning of the term «reactive power» applied to three-phase three-wire and four-wire energy supply systems. Methodology. We have applied the modern theory of instantaneous active and reactive power, the graphical filling complex branched energy supply system of simplified design scheme, the theory of electrical circuits, computer Matlab-simulation. Results. We have provided answers to six basic questions that reveal the physical meaning and definition of the concept of «reactive power». We have justified the assumptions suggesting a universal calculation formula to determine the relative total power loss in the three-phase energy supply system as the sum of four components caused by: a minimal losses, reactive power, active power pulsations and instantaneous current flow in the neutral wire. Originality. We have developed the definition that reveals the physical meaning of the term «reactive power» for three-phase energy supply systems corresponding to modern theories of instantaneous active and reactive power. Practical value. We have proposed energy efficiency method ideas of energy supply systems with non-linear load based on the additional components of the power losses calculation. The further development of the method will allow to amend the design, selection and operation of the power active filters practices.
Robust linear parameter varying induction motor control with polytopic models
Dalila Khamari
2013-01-01
Full Text Available This paper deals with a robust controller for an induction motor which is represented as a linear parameter varying systems. To do so linear matrix inequality (LMI based approach and robust Lyapunov feedback controller are associated. This new approach is related to the fact that the synthesis of a linear parameter varying (LPV feedback controller for the inner loop take into account rotor resistance and mechanical speed as varying parameter. An LPV flux observer is also synthesized to estimate rotor flux providing reference to cited above regulator. The induction motor is described as a polytopic model because of speed and rotor resistance affine dependence their values can be estimated on line during systems operations. The simulation results are presented to confirm the effectiveness of the proposed approach where robustness stability and high performances have been achieved over the entire operating range of the induction motor.
Modeling and analysis of linear hyperbolic systems of balance laws
Bartecki, Krzysztof
2016-01-01
This monograph focuses on the mathematical modeling of distributed parameter systems in which mass/energy transport or wave propagation phenomena occur and which are described by partial differential equations of hyperbolic type. The case of linear (or linearized) 2 x 2 hyperbolic systems of balance laws is considered, i.e., systems described by two coupled linear partial differential equations with two variables representing physical quantities, depending on both time and one-dimensional spatial variable. Based on practical examples of a double-pipe heat exchanger and a transportation pipeline, two typical configurations of boundary input signals are analyzed: collocated, wherein both signals affect the system at the same spatial point, and anti-collocated, in which the input signals are applied to the two different end points of the system. The results of this book emerge from the practical experience of the author gained during his studies conducted in the experimental installation of a heat exchange cente...
Comparison of linear modes in kinetic plasma models
Camporeale, Enrico
2016-01-01
We compare, in an extensive and systematic way, linear theory results obtained with the hybrid (ion-kinetic and electron-fluid), the gyrokinetic and the fully-kinetic plasma models. We present a test case with parameters that are relevant for solar wind turbulence at small scales, which is a topic now recognized to need a kinetic treatment, to a certain extent. We comment on the comparison of low-frequency single modes (Alfv\\'{e}n/ion-cyclotron, ion-acoustic, and fast modes) for a wide range of propagation angles, and on the overall spectral properties of the linear operators, for quasi-perpendicular propagation. The methodology and the results presented in this paper will be valuable when choosing which model should be used in regimes where the assumptions of each model are not trivially satisfied.
Contact Analysis and Modeling of Standing Wave Linear Ultrasonic Motor
SHI Yunlai; ZHAO Chunsheng; ZHANG Jianhui
2011-01-01
A contact model for describing the contact mechanics between the stator and slider of the standing wave linear ultrasonic motor was presented.The proposed model starts from the assumption that the vibration characteristics of the stator is not affected by the contact process.A modified friction models was used to analyze the contact problems.Firstly,the dynamic normal contact force,interface friction force,and steady-state characteristics were analyzed.Secondly,the influences of the contact layer material,the dynamic characteristics of the stator,and the pre-load on motor performance were simulated.Finally,to validate the contact model,a linear ultrasonic motor based on in-plane modes was used as an example.The corresponding results show that a set of simulation of motor performances based on the proposed contact mechanism is in good agreement with experimental results.This model is helpful to understanding the operation principle of the standing wave linear motor and thus contributes to the design of these tvpes of motor.
Nonrigid Registration of Monomodal MRI Using Linear Viscoelastic Model
Jian Yang
2014-01-01
Full Text Available This paper describes a method for nonrigid registration of monomodal MRI based on physical laws. The proposed method assumes that the properties of image deformations are like those of viscoelastic matter, which exhibits the properties of both an elastic solid and a viscous fluid. Therefore, the deformation fields of the deformed image are constrained by both sets of properties. After global registration, the local shape variations are assumed to have the properties of the Maxwell model of linear viscoelasticity, and the deformation fields are constrained by the corresponding partial differential equations. To speed up the registration, an adaptive force is introduced according to the maximum displacement of each iteration. Both synthetic datasets and real datasets are used to evaluate the proposed method. We compare the results of the linear viscoelastic model with those of the fluid model on the basis of both the standard and adaptive forces. The results demonstrate that the adaptive force increases in both models and that the linear viscoelastic model improves the registration accuracy.
Robust Linear Models for Cis-eQTL Analysis.
Mattias Rantalainen
Full Text Available Expression Quantitative Trait Loci (eQTL analysis enables characterisation of functional genetic variation influencing expression levels of individual genes. In outbread populations, including humans, eQTLs are commonly analysed using the conventional linear model, adjusting for relevant covariates, assuming an allelic dosage model and a Gaussian error term. However, gene expression data generally have noise that induces heavy-tailed errors relative to the Gaussian distribution and often include atypical observations, or outliers. Such departures from modelling assumptions can lead to an increased rate of type II errors (false negatives, and to some extent also type I errors (false positives. Careful model checking can reduce the risk of type-I errors but often not type II errors, since it is generally too time-consuming to carefully check all models with a non-significant effect in large-scale and genome-wide studies. Here we propose the application of a robust linear model for eQTL analysis to reduce adverse effects of deviations from the assumption of Gaussian residuals. We present results from a simulation study as well as results from the analysis of real eQTL data sets. Our findings suggest that in many situations robust models have the potential to provide more reliable eQTL results compared to conventional linear models, particularly in respect to reducing type II errors due to non-Gaussian noise. Post-genomic data, such as that generated in genome-wide eQTL studies, are often noisy and frequently contain atypical observations. Robust statistical models have the potential to provide more reliable results and increased statistical power under non-Gaussian conditions. The results presented here suggest that robust models should be considered routinely alongside other commonly used methodologies for eQTL analysis.
Linear models for joint association and linkage QTL mapping
Fernando Rohan L
2009-09-01
Full Text Available Abstract Background Populational linkage disequilibrium and within-family linkage are commonly used for QTL mapping and marker assisted selection. The combination of both results in more robust and accurate locations of the QTL, but models proposed so far have been either single marker, complex in practice or well fit to a particular family structure. Results We herein present linear model theory to come up with additive effects of the QTL alleles in any member of a general pedigree, conditional to observed markers and pedigree, accounting for possible linkage disequilibrium among QTLs and markers. The model is based on association analysis in the founders; further, the additive effect of the QTLs transmitted to the descendants is a weighted (by the probabilities of transmission average of the substitution effects of founders' haplotypes. The model allows for non-complete linkage disequilibrium QTL-markers in the founders. Two submodels are presented: a simple and easy to implement Haley-Knott type regression for half-sib families, and a general mixed (variance component model for general pedigrees. The model can use information from all markers. The performance of the regression method is compared by simulation with a more complex IBD method by Meuwissen and Goddard. Numerical examples are provided. Conclusion The linear model theory provides a useful framework for QTL mapping with dense marker maps. Results show similar accuracies but a bias of the IBD method towards the center of the region. Computations for the linear regression model are extremely simple, in contrast with IBD methods. Extensions of the model to genomic selection and multi-QTL mapping are straightforward.
Ignition and Growth Reactive Flow Model for IMX-101
Tarver, Craig M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2016-02-19
A set of Ignition and Growth (I&G) reactive flow model parameters is developed for the explosive IMX-101 containing DNAN, NQ, and NTO using the available shock initiation and detonation wave propagation experimental data. The unreacted equation of state for IMX-101 is based on experimental data from gas gun experiments by Furnish et al. and is similar to that of TNT. The product equation of state for IMX-101 is based on CHEETAH chemical equilibrium calculations and cylinder test experimental data. The IMX-101 reaction rate parameters are developed using hydrodynamic reactive flow simulations of several shock initiation and detonation experiments. One set of I&G parameters does a good job of reproducing both shock initiation and detonation experimental data. This is due to the fact that IMX-101 reacts over a relatively small pressure range from about 7 GPa to 20 GPa (C-J pressure). Advanced experiments using embedded gauges and/or laser interferometry could lead to better parameters.
On linear models and parameter identifiability in experimental biological systems.
Lamberton, Timothy O; Condon, Nicholas D; Stow, Jennifer L; Hamilton, Nicholas A
2014-10-07
A key problem in the biological sciences is to be able to reliably estimate model parameters from experimental data. This is the well-known problem of parameter identifiability. Here, methods are developed for biologists and other modelers to design optimal experiments to ensure parameter identifiability at a structural level. The main results of the paper are to provide a general methodology for extracting parameters of linear models from an experimentally measured scalar function - the transfer function - and a framework for the identifiability analysis of complex model structures using linked models. Linked models are composed by letting the output of one model become the input to another model which is then experimentally measured. The linked model framework is shown to be applicable to designing experiments to identify the measured sub-model and recover the input from the unmeasured sub-model, even in cases that the unmeasured sub-model is not identifiable. Applications for a set of common model features are demonstrated, and the results combined in an example application to a real-world experimental system. These applications emphasize the insight into answering "where to measure" and "which experimental scheme" questions provided by both the parameter extraction methodology and the linked model framework. The aim is to demonstrate the tools' usefulness in guiding experimental design to maximize parameter information obtained, based on the model structure.
Category-theoretic models of linear Abadi & Plotkin Logic
Birkedal, Lars; Møgelberg, Rasmus Ejlers; Lerchedahl Petersen, Rasmus
2008-01-01
This paper presents a sound and complete category-theoretic notion of models for Linear Abadi & Plotkin Logic [Birkedal et al., 2006], a logic suitable for reasoning about parametricity in combination with recursion. A subclass of these called parametric LAPL structures can be seen as an axiomati......This paper presents a sound and complete category-theoretic notion of models for Linear Abadi & Plotkin Logic [Birkedal et al., 2006], a logic suitable for reasoning about parametricity in combination with recursion. A subclass of these called parametric LAPL structures can be seen...... as an axiomatization of domain theoretic models of parametric polymorphism, and we show how to solve general (nested) recursive domain equations in these. parametric LAPL structures constitute a general notion of model of parametricity in a setting with recursion. In future papers we will demonstrate this by showing...... how many different models of parametricity and recursion give rise to parametric LAPL structures, including Simpson and Rosolini’s set theoretic models [Rosolini and Simpson, 2004], a syntactic model based on Lily [Pitts, 2000, Bierman et al., 2000] and a model based on admissible pers over...
Technical note: A linear model for predicting δ13 Cprotein.
Pestle, William J; Hubbe, Mark; Smith, Erin K; Stevenson, Joseph M
2015-08-01
Development of a model for the prediction of δ(13) Cprotein from δ(13) Ccollagen and Δ(13) Cap-co . Model-generated values could, in turn, serve as "consumer" inputs for multisource mixture modeling of paleodiet. Linear regression analysis of previously published controlled diet data facilitated the development of a mathematical model for predicting δ(13) Cprotein (and an experimentally generated error term) from isotopic data routinely generated during the analysis of osseous remains (δ(13) Cco and Δ(13) Cap-co ). Regression analysis resulted in a two-term linear model (δ(13) Cprotein (%) = (0.78 × δ(13) Cco ) - (0.58× Δ(13) Cap-co ) - 4.7), possessing a high R-value of 0.93 (r(2) = 0.86, P < 0.01), and experimentally generated error terms of ±1.9% for any predicted individual value of δ(13) Cprotein . This model was tested using isotopic data from Formative Period individuals from northern Chile's Atacama Desert. The model presented here appears to hold significant potential for the prediction of the carbon isotope signature of dietary protein using only such data as is routinely generated in the course of stable isotope analysis of human osseous remains. These predicted values are ideal for use in multisource mixture modeling of dietary protein source contribution. © 2015 Wiley Periodicals, Inc.
Residuals analysis of the generalized linear models for longitudinal data.
Chang, Y C
2000-05-30
The generalized estimation equation (GEE) method, one of the generalized linear models for longitudinal data, has been used widely in medical research. However, the related sensitivity analysis problem has not been explored intensively. One of the possible reasons for this was due to the correlated structure within the same subject. We showed that the conventional residuals plots for model diagnosis in longitudinal data could mislead a researcher into trusting the fitted model. A non-parametric method, named the Wald-Wolfowitz run test, was proposed to check the residuals plots both quantitatively and graphically. The rationale proposedin this paper is well illustrated with two real clinical studies in Taiwan.
A Graphical User Interface to Generalized Linear Models in MATLAB
Peter Dunn
1999-07-01
Full Text Available Generalized linear models unite a wide variety of statistical models in a common theoretical framework. This paper discusses GLMLAB-software that enables such models to be fitted in the popular mathematical package MATLAB. It provides a graphical user interface to the powerful MATLAB computational engine to produce a program that is easy to use but with many features, including offsets, prior weights and user-defined distributions and link functions. MATLAB's graphical capacities are also utilized in providing a number of simple residual diagnostic plots.
Linear chaos for the Quick-Thinking-Driver model
Conejero, J. A.; Arcila, M. Murillo; Seoane-Sepúlveda, J. B.
2015-01-01
In recent years, the topic of car-following has experimented an increased importance in traffic engineering and safety research. This has become a very interesting topic because of the development of driverless cars \\cite{google_driverless_cars}. Driving models which describe the interaction between adjacent vehicles in the same lane have a big interest in simulation modeling, such as the Quick-Thinking-Driver model. A non-linear version of it can be given using the logistic map, and then cha...
Estimation in partial linear EV models with replicated observations
CUI; Hengjian
2004-01-01
The aim of this work is to construct the parameter estimators in the partial linear errors-in-variables (EV) models and explore their asymptotic properties. Unlike other related References, the assumption of known error covariance matrix is removed when the sample can be repeatedly drawn at each designed point from the model. The estimators of interested regression parameters, and the model error variance, as well as the nonparametric function, are constructed. Under some regular conditions, all of the estimators prove strongly consistent. Meanwhile, the asymptotic normality for the estimator of regression parameter is also presented. A simulation study is reported to illustrate our asymptotic results.
Physicochemical model for reactive sputtering of hot target
Shapovalov, Viktor I., E-mail: vishapovalov@mail.ru; Karzin, Vitaliy V.; Bondarenko, Anastasia S.
2017-02-05
A physicochemical model for reactive magnetron sputtering of a metal target is described in this paper. The target temperature in the model is defined as a function of the ion current density. Synthesis of the coating occurs due to the surface chemical reaction. The law of mass action, the Langmuir isotherm and the Arrhenius equation for non-isothermal conditions were used for mathematical description of the reaction. The model takes into consideration thermal electron emission and evaporation of the target surface. The system of eight algebraic equations, describing the model, was solved for the tantalum target sputtered in the oxygen environment. It was established that the hysteresis effect disappears with the increase of the ion current density. - Highlights: • When model is applied for a cold target, hysteresis width is proportional to the ion current density. • Two types of processes of hot target sputtering are possible, depending on the current density: with and without the hysteresis. • Sputtering process is dominant at current densities less than 50 A/m{sup 2} and evaporation can be neglected. • For current densities over 50 A/m{sup 2} the hysteresis width reaches its maximum and the role of evaporation increases.
NON-LINEAR FINITE ELEMENT MODELING OF DEEP DRAWING PROCESS
Hasan YILDIZ
2004-03-01
Full Text Available Deep drawing process is one of the main procedures used in different branches of industry. Finding numerical solutions for determination of the mechanical behaviour of this process will save time and money. In die surfaces, which have complex geometries, it is hard to determine the effects of parameters of sheet metal forming. Some of these parameters are wrinkling, tearing, and determination of the flow of the thin sheet metal in the die and thickness change. However, the most difficult one is determination of material properties during plastic deformation. In this study, the effects of all these parameters are analyzed before producing the dies. The explicit non-linear finite element method is chosen to be used in the analysis. The numerical results obtained for non-linear material and contact models are also compared with the experiments. A good agreement between the numerical and the experimental results is obtained. The results obtained for the models are given in detail.
A Non-Gaussian Spatial Generalized Linear Latent Variable Model
Irincheeva, Irina
2012-08-03
We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.
A non-linear model of economic production processes
Ponzi, A.; Yasutomi, A.; Kaneko, K.
2003-06-01
We present a new two phase model of economic production processes which is a non-linear dynamical version of von Neumann's neoclassical model of production, including a market price-setting phase as well as a production phase. The rate of an economic production process is observed, for the first time, to depend on the minimum of its input supplies. This creates highly non-linear supply and demand dynamics. By numerical simulation, production networks are shown to become unstable when the ratio of different products to total processes increases. This provides some insight into observed stability of competitive capitalist economies in comparison to monopolistic economies. Capitalist economies are also shown to have low unemployment.
Confidence Intervals of Variance Functions in Generalized Linear Model
Yong Zhou; Dao-ji Li
2006-01-01
In this paper we introduce an appealing nonparametric method for estimating variance and conditional variance functions in generalized linear models (GLMs), when designs are fixed points and random variables respectively. Bias-corrected confidence bands are proposed for the (conditional) variance by local linear smoothers. Nonparametric techniques are developed in deriving the bias-corrected confidence intervals of the (conditional) variance. The asymptotic distribution of the proposed estimator is established and show that the bias-corrected confidence bands asymptotically have the correct coverage properties. A small simulation is performed when unknown regression parameter is estimated by nonparametric quasi-likelihood. The results are also applicable to nonparametric autoregressive times series model with heteroscedastic conditional variance.
Order reduction of large-scale linear oscillatory system models
Trudnowksi, D.J. (Pacific Northwest Lab., Richland, WA (United States))
1994-02-01
Eigen analysis and signal analysis techniques of deriving representations of power system oscillatory dynamics result in very high-order linear models. In order to apply many modern control design methods, the models must be reduced to a more manageable order while preserving essential characteristics. Presented in this paper is a model reduction method well suited for large-scale power systems. The method searches for the optimal subset of the high-order model that best represents the system. An Akaike information criterion is used to define the optimal reduced model. The method is first presented, and then examples of applying it to Prony analysis and eigenanalysis models of power systems are given.
The Optimal Selection for Restricted Linear Models with Average Estimator
Qichang Xie
2014-01-01
Full Text Available The essential task of risk investment is to select an optimal tracking portfolio among various portfolios. Statistically, this process can be achieved by choosing an optimal restricted linear model. This paper develops a statistical procedure to do this, based on selecting appropriate weights for averaging approximately restricted models. The method of weighted average least squares is adopted to estimate the approximately restricted models under dependent error setting. The optimal weights are selected by minimizing a k-class generalized information criterion (k-GIC, which is an estimate of the average squared error from the model average fit. This model selection procedure is shown to be asymptotically optimal in the sense of obtaining the lowest possible average squared error. Monte Carlo simulations illustrate that the suggested method has comparable efficiency to some alternative model selection techniques.
American petroleum industry: an application of linear rational expectations modeling
Dimelis, S.P.
1987-01-01
Objectives of this study are to account for the storable and exhaustible nature of crude petroleum as well as the dynamic interaction of agents operating within the stochastic environment of the mutually interrelated markets of crude petroleum and refined petroleum products. To this end, the linear rational expectations modeling is employed, that give estimable functional forms that avoid the common objections to fixed and ad hoc distributed lag modeling addressed by Nerlove (1972) and Lucas (1976), respectively. The formulation and the econometric specification of the model are documented with a statistical and vector autoregression analysis of the stylized facts pertaining to the actual data during the post World War II period. Most of the important features characterizing behavior in the crude petroleum and refined petroleum products markets such as exhaustible resource extraction costs and inventory holding costs are captured in the model. The foreign and domestic demand and supplies are specified. The model is then solved simultaneously to derive the rational expectations equilibrium laws of motion in these markets. An estimable form of the model is generated which is linear in the variables but highly nonlinear in the parameters. The model is tested empirically using annual data over the period 1047 to 1984.
LINEAR MODELS FOR MANAGING SOURCES OF GROUNDWATER POLLUTION.
Gorelick, Steven M.; Gustafson, Sven-Ake; ,
1984-01-01
Mathematical models for the problem of maintaining a specified groundwater quality while permitting solute waste disposal at various facilities distributed over space are discussed. The pollutants are assumed to be chemically inert and their concentrations in the groundwater are governed by linear equations for advection and diffusion. The aim is to determine a disposal policy which maximises the total amount of pollutants released during a fixed time T while meeting the condition that the concentration everywhere is below prescribed levels.
Conditional likelihood inference in generalized linear mixed models.
Sartori, Nicola; Severini , T.A
2002-01-01
Consider a generalized linear model with a canonical link function, containing both fixed and random effects. In this paper, we consider inference about the fixed effects based on a conditional likelihood function. It is shown that this conditional likelihood function is valid for any distribution of the random effects and, hence, the resulting inferences about the fixed effects are insensitive to misspecification of the random effects distribution. Inferences based on the conditional likelih...
Credibility analysis of risk classes by generalized linear model
Erdemir, Ovgucan Karadag; Sucu, Meral
2016-06-01
In this paper generalized linear model (GLM) and credibility theory which are frequently used in nonlife insurance pricing are combined for reliability analysis. Using full credibility standard, GLM is associated with limited fluctuation credibility approach. Comparison criteria such as asymptotic variance and credibility probability are used to analyze the credibility of risk classes. An application is performed by using one-year claim frequency data of a Turkish insurance company and results of credible risk classes are interpreted.
State Predictive Model Following Control System for Linear Time Delays
Da-Zhong Wang; Shu-Jing Wu; Shigenori Okubo
2009-01-01
In this paper, we propose a new state predictive model following control system (MFCS). The considered system has linear time delays. With the MFCS method, we obtain a simple input control law. The bounded property of the internal states for the control is given and the utility of this control design is guaranteed. Finally, an example is given to illustrate the effectiveness of the proposed method.
General Linear Models: An Integrated Approach to Statistics
Andrew Faulkner; Sylvain Chartier
2008-01-01
Generally, in psychology, the various statistical analyses are taught independently from each other. As a consequence, students struggle to learn new statistical analyses, in contexts that differ from their textbooks. This paper gives a short introduction to the general linear model (GLM), in which it is showed that ANOVA (one-way, factorial, repeated measure and analysis of covariance) is simply a multiple correlation/regression analysis (MCRA). Generalizations to other cases, such as multiv...
Numerical modeling of linear friction welding:a literature review
李文亚; 郭嘉; 马铁军; A.Vairis
2014-01-01
Linear friction welding (LFW)is a solid state process for joining metals together.While this process was developed originally for titanium alloys (e.g.blisks),over the past decade a number ofmaterials were found to be weldable with LFW. In this review,the current status ofunderstanding and development ofLFW are presented.Particular emphasis has been given to the modeling ofthe LFW process.Finally,opportunities for further research and development ofLFW are identified.
Electromagnetic axial anomaly in a generalized linear sigma model
Fariborz, Amir H.; Jora, Renata
2017-06-01
We construct the electromagnetic anomaly effective term for a generalized linear sigma model with two chiral nonets, one with a quark-antiquark structure, the other one with a four-quark content. We compute in the leading order of this framework the decays into two photons of six pseudoscalars: π0(137 ), π0(1300 ), η (547 ), η (958 ), η (1295 ) and η (1760 ). Our results agree well with the available experimental data.
Holographic transports and stability in anisotropic linear axion model
Ge, Xian-Hui; Niu, Chao; Sin, Sang-Jin
2014-01-01
We study thermoelectric conductivities and shear viscosities in a holographically anisotropic model. Momentum relaxation is realized through perturbing the linear axion field. AC conductivity exhibits a conherent/incoherent metal transition. The longitudinal shear viscosity for prolate anisotropy violates the bound conjectured by Kovtun-Son-Starinets. We also find that thermodynamic and dynamical instabilities are not always equivalent, which provides a counter example of the Gubser-Mitra conjecture.
Information inefficiency in a random linear economy model
Jerico, Joao Pedro
2016-01-01
We study the effects of introducing information inefficiency in a model for a random linear economy with a representative consumer. This is done by considering statistical, instead of classical, economic general equilibria. Employing two different approaches we show that inefficiency increases the consumption set of a consumer but decreases her expected utility. In this scenario economic activity grows while welfare shrinks, that is the opposite of the behavior obtained by considering a rational consumer.
Comparison of Linear Prediction Models for Audio Signals
2009-03-01
Full Text Available While linear prediction (LP has become immensely popular in speech modeling, it does not seem to provide a good approach for modeling audio signals. This is somewhat surprising, since a tonal signal consisting of a number of sinusoids can be perfectly predicted based on an (all-pole LP model with a model order that is twice the number of sinusoids. We provide an explanation why this result cannot simply be extrapolated to LP of audio signals. If noise is taken into account in the tonal signal model, a low-order all-pole model appears to be only appropriate when the tonal components are uniformly distributed in the Nyquist interval. Based on this observation, different alternatives to the conventional LP model can be suggested. Either the model should be changed to a pole-zero, a high-order all-pole, or a pitch prediction model, or the conventional LP model should be preceded by an appropriate frequency transform, such as a frequency warping or downsampling. By comparing these alternative LP models to the conventional LP model in terms of frequency estimation accuracy, residual spectral flatness, and perceptual frequency resolution, we obtain several new and promising approaches to LP-based audio modeling.
Comparison of Linear Prediction Models for Audio Signals
van Waterschoot Toon
2008-01-01
Full Text Available While linear prediction (LP has become immensely popular in speech modeling, it does not seem to provide a good approach for modeling audio signals. This is somewhat surprising, since a tonal signal consisting of a number of sinusoids can be perfectly predicted based on an (all-pole LP model with a model order that is twice the number of sinusoids. We provide an explanation why this result cannot simply be extrapolated to LP of audio signals. If noise is taken into account in the tonal signal model, a low-order all-pole model appears to be only appropriate when the tonal components are uniformly distributed in the Nyquist interval. Based on this observation, different alternatives to the conventional LP model can be suggested. Either the model should be changed to a pole-zero, a high-order all-pole, or a pitch prediction model, or the conventional LP model should be preceded by an appropriate frequency transform, such as a frequency warping or downsampling. By comparing these alternative LP models to the conventional LP model in terms of frequency estimation accuracy, residual spectral flatness, and perceptual frequency resolution, we obtain several new and promising approaches to LP-based audio modeling.
Zhang, Fan [ORNL; Yeh, Gour-Tsyh [University of Central Florida, Orlando; Parker, Jack C [ORNL; Brooks, Scott C [ORNL; Pace, Molly [ORNL; Kim, Young Jin [ORNL; Jardine, Philip M [ORNL; Watson, David B [ORNL
2007-01-01
This paper presents a reaction-based water quality transport model in subsurface flow systems. Transport of chemical species with a variety of chemical and physical processes is mathematically described by M partial differential equations (PDEs). Decomposition via Gauss-Jordan column reduction of the reaction network transforms M species reactive transport equations into two sets of equations: a set of thermodynamic equilibrium equations representing NE equilibrium reactions and a set of reactive transport equations of M-NE kinetic-variables involving no equilibrium reactions (a kinetic-variable is a linear combination of species). The elimination of equilibrium reactions from reactive transport equations allows robust and efficient numerical integration. The model solves the PDEs of kinetic-variables rather than individual chemical species, which reduces the number of reactive transport equations and simplifies the reaction terms in the equations. A variety of numerical methods are investigated for solving the coupled transport and reaction equations. Simulation comparisons with exact solutions were performed to verify numerical accuracy and assess the effectiveness of various numerical strategies to deal with different application circumstances. Two validation examples involving simulations of uranium transport in soil columns are presented to evaluate the ability of the model to simulate reactive transport with complex reaction networks involving both kinetic and equilibrium reactions.
Zhang, Fan; Yeh, Gour-Tsyh; Parker, Jack C.; Brooks, Scott C.; Pace, Molly N.; Kim, Young-Jin; Jardine, Philip M.; Watson, David B.
2007-06-01
This paper presents a reaction-based water quality transport model in subsurface flow systems. Transport of chemical species with a variety of chemical and physical processes is mathematically described by M partial differential equations (PDEs). Decomposition via Gauss-Jordan column reduction of the reaction network transforms M species reactive transport equations into two sets of equations: a set of thermodynamic equilibrium equations representing NE equilibrium reactions and a set of reactive transport equations of M- NE kinetic-variables involving no equilibrium reactions (a kinetic-variable is a linear combination of species). The elimination of equilibrium reactions from reactive transport equations allows robust and efficient numerical integration. The model solves the PDEs of kinetic-variables rather than individual chemical species, which reduces the number of reactive transport equations and simplifies the reaction terms in the equations. A variety of numerical methods are investigated for solving the coupled transport and reaction equations. Simulation comparisons with exact solutions were performed to verify numerical accuracy and assess the effectiveness of various numerical strategies to deal with different application circumstances. Two validation examples involving simulations of uranium transport in soil columns are presented to evaluate the ability of the model to simulate reactive transport with complex reaction networks involving both kinetic and equilibrium reactions.
Reactive modelling of 1,2-DCA and DOC near the shoreline.
Colombani, N; Pantano, A; Mastrocicco, M; Petitta, M
2014-11-15
1,2-Dichloroethane (1,2-DCA) was found to be the most abundant compound among chlorinated hydrocarbons detected in a petrochemical plant in southern Italy. This site is located near the coastline, and it is set above an unconfined coastal aquifer, where seawater intrusion is present. The presence of organic and inorganic contaminants at this site has required the implementation of remediation strategies, consisting of pumping wells (hydraulic barrier) and a horizontal flow barrier. The purpose of this work was to assess the influence of salt water intrusion on the degradation rate of 1,2-DCA. This was done on a three-dimensional domain relative to a limited portion of a well characterized field site, accounting for density-dependent flow and reactive transport modelling of 1,2-DCA and Dissolved Organic Carbon (DOC). The modelling procedure was performed employing SEAWAT-4.0 and PHT3D, to reproduce the complex three-dimensional flow and transport domain. In order to determine the fate of 1,2-DCA, detailed field investigations provided intensive depth profile information. Different, kinetically controlled degradation rates were simulated to explain the observed, selective degradation of pollutants in groundwater. Calibration of the model was accomplished by comparison with the two different sets of measurements obtained from the MLS devices and from pumping wells. With the calibrated model, it was possible to distinguish between dispersive non-reactive processes and bacterially mediated reactions. In the non-reactive model, 1,2-DCA sorption was simulated using linear sorption coefficient determined with field data and 1,2-DCA degradation was simulated using a first order decay coefficient using literature data as initial guess. Finally, on the reactive transport model, where a two-step approach with partial equilibrium approach was implemented, the effects of neglecting the cation exchange capacity, omitting density-dependent flow, and refining the vertical
Validating a quasi-linear transport model versus nonlinear simulations
Casati, A.; Bourdelle, C.; Garbet, X.; Imbeaux, F.; Candy, J.; Clairet, F.; Dif-Pradalier, G.; Falchetto, G.; Gerbaud, T.; Grandgirard, V.; Gürcan, Ö. D.; Hennequin, P.; Kinsey, J.; Ottaviani, M.; Sabot, R.; Sarazin, Y.; Vermare, L.; Waltz, R. E.
2009-08-01
In order to gain reliable predictions on turbulent fluxes in tokamak plasmas, physics based transport models are required. Nonlinear gyrokinetic electromagnetic simulations for all species are still too costly in terms of computing time. On the other hand, interestingly, the quasi-linear approximation seems to retain the relevant physics for fairly reproducing both experimental results and nonlinear gyrokinetic simulations. Quasi-linear fluxes are made of two parts: (1) the quasi-linear response of the transported quantities and (2) the saturated fluctuating electrostatic potential. The first one is shown to follow well nonlinear numerical predictions; the second one is based on both nonlinear simulations and turbulence measurements. The resulting quasi-linear fluxes computed by QuaLiKiz (Bourdelle et al 2007 Phys. Plasmas 14 112501) are shown to agree with the nonlinear predictions when varying various dimensionless parameters, such as the temperature gradients, the ion to electron temperature ratio, the dimensionless collisionality, the effective charge and ranging from ion temperature gradient to trapped electron modes turbulence.
Bayesian model selection for constrained multivariate normal linear models
Mulder, J.
2010-01-01
The expectations that researchers have about the structure in the data can often be formulated in terms of equality constraints and/or inequality constraints on the parameters in the model that is used. In a (M)AN(C)OVA model, researchers have expectations about the differences between the
Gupta, Shikha; Basant, Nikita; Mohan, Dinesh; Singh, Kunwar P
2016-07-01
The persistence and the removal of organic chemicals from the atmosphere are largely determined by their reactions with the OH radical and O3. Experimental determinations of the kinetic rate constants of OH and O3 with a large number of chemicals are tedious and resource intensive and development of computational approaches has widely been advocated. Recently, ensemble machine learning (EML) methods have emerged as unbiased tools to establish relationship between independent and dependent variables having a nonlinear dependence. In this study, EML-based, temperature-dependent quantitative structure-reactivity relationship (QSRR) models have been developed for predicting the kinetic rate constants for OH (kOH) and O3 (kO3) reactions with diverse chemicals. Structural diversity of chemicals was evaluated using a Tanimoto similarity index. The generalization and prediction abilities of the constructed models were established through rigorous internal and external validation performed employing statistical checks. In test data, the EML QSRR models yielded correlation (R (2)) of ≥0.91 between the measured and the predicted reactivities. The applicability domains of the constructed models were determined using methods based on descriptors range, Euclidean distance, leverage, and standardization approaches. The prediction accuracies for the higher reactivity compounds were relatively better than those of the low reactivity compounds. Proposed EML QSRR models performed well and outperformed the previous reports. The proposed QSRR models can make predictions of rate constants at different temperatures. The proposed models can be useful tools in predicting the reactivities of chemicals towards OH radical and O3 in the atmosphere.
On the Development of Parameterized Linear Analytical Longitudinal Airship Models
Kulczycki, Eric A.; Johnson, Joseph R.; Bayard, David S.; Elfes, Alberto; Quadrelli, Marco B.
2008-01-01
In order to explore Titan, a moon of Saturn, airships must be able to traverse the atmosphere autonomously. To achieve this, an accurate model and accurate control of the vehicle must be developed so that it is understood how the airship will react to specific sets of control inputs. This paper explains how longitudinal aircraft stability derivatives can be used with airship parameters to create a linear model of the airship solely by combining geometric and aerodynamic airship data. This method does not require system identification of the vehicle. All of the required data can be derived from computational fluid dynamics and wind tunnel testing. This alternate method of developing dynamic airship models will reduce time and cost. Results are compared to other stable airship dynamic models to validate the methods. Future work will address a lateral airship model using the same methods.
Esteley, Cristina B.; Villarreal, Monica E.; Alagia, Humberto R.
2010-01-01
Over the past several years, we have been exploring and researching a phenomenon that occurs among undergraduate students that we called extension of linear models to non-linear contexts or overgeneralization of linear models. This phenomenon appears when some students use linear representations in situations that are non-linear. In a first phase,…
Jet propagation within a Linearized Boltzmann Transport model
Luo, Tan; He, Yayun [Key Laboratory of Quark and Lepton Physics (MOE) and Institute of Particle Physics, Central China Normal University, Wuhan 430079 (China); Wang, Xin-Nian [Key Laboratory of Quark and Lepton Physics (MOE) and Institute of Particle Physics, Central China Normal University, Wuhan 430079 (China); Nuclear Science Division, Mailstop 70R0319, Lawrence Berkeley National Laboratory, Berkeley, CA 94740 (United States); Zhu, Yan [Departamento de Física de Partículas and IGFAE, Universidade de Santiago de Compostela, E-15706 Santiago de Compostela, Galicia (Spain)
2014-12-15
A Linearized Boltzmann Transport (LBT) model has been developed for the study of parton propagation inside quark–gluon plasma. Both leading and thermal recoiled partons are tracked in order to include the effect of jet-induced medium excitation. In this talk, we present a study within the LBT model in which we implement the complete set of elastic parton scattering processes. We investigate elastic parton energy loss and their energy and length dependence. We further investigate energy loss and transverse shape of reconstructed jets. Contributions from the recoiled thermal partons and jet-induced medium excitations are found to have significant influences on the jet energy loss and transverse profile.
Model-Checking Linear-Time Properties of Quantum Systems
Ying, Mingsheng; Yu, Nengkun; Feng, Yuan
2011-01-01
We define a formal framework for reasoning about linear-time properties of quantum systems in which quantum automata are employed in the modeling of systems and certain closed subspaces of state (Hilbert) spaces are used as the atomic propositions about the behavior of systems. We provide an algorithm for verifying invariants of quantum automata. Then automata-based model-checking technique is generalized for the verification of safety properties recognizable by reversible automata and omega-properties recognizable by reversible Buechi automata.
H∞ /H2 model reduction through dilated linear matrix inequalities
Adegas, Fabiano Daher; Stoustrup, Jakob
2012-01-01
This paper presents sufficient dilated linear matrix inequalities (LMI) conditions to the $H_{infty}$ and $H_{2}$ model reduction problem. A special structure of the auxiliary (slack) variables allows the original model of order $n$ to be reduced to an order $r=n/s$ where $n,r,s in field...... not satisfactorily approximates the original system, an iterative algorithm based on dilated LMIs is proposed to significantly improve the approximation bound. The effectiveness of the method is accessed by numerical experiments. The method is also applied to the $H_2$ order reduction of a flexible wind turbine...
A linear model for the dynamics of fish larvae
Noureddine Ghouali
2004-11-01
Full Text Available We consider a linear model for the growth and the dispersion of fish larvae of certain species. Dispersion is modeled as entailed by the combination of transport and vertical diffusion. We generalize the work of Boushaba, Arino and Boussouar [5,6] in the sense that horizontal velocities are uniform throughout the water column; but we deal with vertical component velocity and vertical diffusion depending on the space variables and on time, which was not the case in [5,6]. This new vision leads us to non-autonomous problems, the aim of this work is to show the existence, uniqueness, and positivity of solutions.
On the Chiral Phase Transition in the Linear Sigma Model
Phat, T H; Hoa, L V; Phat, Tran Huu; Anh, Nguyen Tuan; Hoa, Le Viet
2004-01-01
The Cornwall-Jackiw-Tomboulis (CJT) effective action for composite operators at finite temperature is used to investigate the chiral phase transition within the framework of the linear sigma model as the low-energy effective model of quantum chromodynamics (QCD). A new renormalization prescription for the CJT effective action in the Hartree-Fock (HF) approximation is proposed. A numerical study, which incorporates both thermal and quantum effect, shows that in this approximation the phase transition is of first order. However, taking into account the higher-loop diagrams contribution the order of phase transition is unchanged.
A non-linear model of information seeking behaviour
Allen E. Foster
2005-01-01
Full Text Available The results of a qualitative, naturalistic, study of information seeking behaviour are reported in this paper. The study applied the methods recommended by Lincoln and Guba for maximising credibility, transferability, dependability, and confirmability in data collection and analysis. Sampling combined purposive and snowball methods, and led to a final sample of 45 inter-disciplinary researchers from the University of Sheffield. In-depth semi-structured interviews were used to elicit detailed examples of information seeking. Coding of interview transcripts took place in multiple iterations over time and used Atlas-ti software to support the process. The results of the study are represented in a non-linear Model of Information Seeking Behaviour. The model describes three core processes (Opening, Orientation, and Consolidation and three levels of contextual interaction (Internal Context, External Context, and Cognitive Approach, each composed of several individual activities and attributes. The interactivity and shifts described by the model show information seeking to be non-linear, dynamic, holistic, and flowing. The paper concludes by describing the whole model of behaviours as analogous to an artist's palette, in which activities remain available throughout information seeking. A summary of key implications of the model and directions for further research are included.
Non-linear model for compression tests on articular cartilage.
Grillo, Alfio; Guaily, Amr; Giverso, Chiara; Federico, Salvatore
2015-07-01
Hydrated soft tissues, such as articular cartilage, are often modeled as biphasic systems with individually incompressible solid and fluid phases, and biphasic models are employed to fit experimental data in order to determine the mechanical and hydraulic properties of the tissues. Two of the most common experimental setups are confined and unconfined compression. Analytical solutions exist for the unconfined case with the linear, isotropic, homogeneous model of articular cartilage, and for the confined case with the non-linear, isotropic, homogeneous model. The aim of this contribution is to provide an easily implementable numerical tool to determine a solution to the governing differential equations of (homogeneous and isotropic) unconfined and (inhomogeneous and isotropic) confined compression under large deformations. The large-deformation governing equations are reduced to equivalent diffusive equations, which are then solved by means of finite difference (FD) methods. The solution strategy proposed here could be used to generate benchmark tests for validating complex user-defined material models within finite element (FE) implementations, and for determining the tissue's mechanical and hydraulic properties from experimental data.
A Linear Viscoelastic Model Calibration of Sylgard 184.
Long, Kevin Nicholas; Brown, Judith Alice
2017-04-01
We calibrate a linear thermoviscoelastic model for solid Sylgard 184 (90-10 formulation), a lightly cross-linked, highly flexible isotropic elastomer for use both in Sierra / Solid Mechanics via the Universal Polymer Model as well as in Sierra / Structural Dynamics (Salinas) for use as an isotropic viscoelastic material. Material inputs for the calibration in both codes are provided. The frequency domain master curve of oscillatory shear was obtained from a report from Los Alamos National Laboratory (LANL). However, because the form of that data is different from the constitutive models in Sierra, we also present the mapping of the LANL data onto Sandia’s constitutive models. Finally, blind predictions of cyclic tension and compression out to moderate strains of 40 and 20% respectively are compared with Sandia’s legacy cure schedule material. Although the strain rate of the data is unknown, the linear thermoviscoelastic model accurately predicts the experiments out to moderate strains for the slower strain rates, which is consistent with the expectation that quasistatic test procedures were likely followed. This good agreement comes despite the different cure schedules between the Sandia and LANL data.
Wavefront Sensing for WFIRST with a Linear Optical Model
Jurling, Alden S.; Content, David A.
2012-01-01
In this paper we develop methods to use a linear optical model to capture the field dependence of wavefront aberrations in a nonlinear optimization-based phase retrieval algorithm for image-based wavefront sensing. The linear optical model is generated from a ray trace model of the system and allows the system state to be described in terms of mechanical alignment parameters rather than wavefront coefficients. This approach allows joint optimization over images taken at different field points and does not require separate convergence of phase retrieval at individual field points. Because the algorithm exploits field diversity, multiple defocused images per field point are not required for robustness. Furthermore, because it is possible to simultaneously fit images of many stars over the field, it is not necessary to use a fixed defocus to achieve adequate signal-to-noise ratio despite having images with high dynamic range. This allows high performance wavefront sensing using in-focus science data. We applied this technique in a simulation model based on the Wide Field Infrared Survey Telescope (WFIRST) Intermediate Design Reference Mission (IDRM) imager using a linear optical model with 25 field points. We demonstrate sub-thousandth-wave wavefront sensing accuracy in the presence of noise and moderate undersampling for both monochromatic and polychromatic images using 25 high-SNR target stars. Using these high-quality wavefront sensing results, we are able to generate upsampled point-spread functions (PSFs) and use them to determine PSF ellipticity to high accuracy in order to reduce the systematic impact of aberrations on the accuracy of galactic ellipticity determination for weak-lensing science.
Wavefront sensing for WFIRST with a linear optical model
Jurling, Alden S.; Content, David A.
2012-09-01
In this paper we develop methods to use a linear optical model to capture the field dependence of wavefront aberrations in a nonlinear optimization-based phase retrieval algorithm for image-based wavefront sensing. The linear optical model is generated from a ray trace model of the system and allows the system state to be described in terms of mechanical alignment parameters rather than wavefront coefficients. This approach allows joint optimization over images taken at different field points and does not require separate convergence of phase retrieval at individual field points. Because the algorithm exploits field diversity, multiple defocused images per field point are not required for robustness. Furthermore, because it is possible to simultaneously fit images of many stars over the field, it is not necessary to use a fixed defocus to achieve adequate signal-to-noise ratio despite having images with high dynamic range. This allows high performance wavefront sensing using in-focus science data. We applied this technique in a simulation model based on the Wide Field Infrared Survey Telescope (WFIRST) Intermediate Design Reference Mission (IDRM) imager using a linear optical model with 25 field points. We demonstrate sub-thousandth-wave wavefront sensing accuracy in the presence of noise and moderate undersampling for both monochromatic and polychromatic images using 25 high-SNR target stars. Using these high-quality wavefront sensing results, we are able to generate upsampled point-spread functions (PSFs) and use them to determine PSF ellipticity to high accuracy in order to reduce the systematic impact of aberrations on the accuracy of galactic ellipticity determination for weak-lensing science.
Richly parameterized linear models additive, time series, and spatial models using random effects
Hodges, James S
2013-01-01
A First Step toward a Unified Theory of Richly Parameterized Linear ModelsUsing mixed linear models to analyze data often leads to results that are mysterious, inconvenient, or wrong. Further compounding the problem, statisticians lack a cohesive resource to acquire a systematic, theory-based understanding of models with random effects.Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects takes a first step in developing a full theory of richly parameterized models, which would allow statisticians to better understand their analysis results. The aut
Non-linear rheology in a model biological tissue
Matoz-Fernandez, D A; Barrat, Jean-Louis; Bertin, Eric; Martens, Kirsten
2016-01-01
Mechanical signaling plays a key role in biological processes like embryo development and cancer growth. One prominent way to probe mechanical properties of tissues is to study their response to externally applied forces. Using a particle-based model featuring random apoptosis and environment-dependent division rates, we evidence a crossover from linear flow to a shear-thinning regime with increasing shear rate. To rationalize this non-linear flow we derive a theoretical mean-field scenario that accounts for the interplay of mechanical and active noise in local stresses. These noises are respectively generated by the elastic response of the cell matrix to cell rearrangements and by the internal activity.
A linearized dispersion relation for orthorhombic pseudo-acoustic modeling
Song, Xiaolei
2012-11-04
Wavefield extrapolation in acoustic orthorhombic anisotropic media suffers from wave-mode coupling and stability limitations in the parameter range. We introduce a linearized form of the dispersion relation for acoustic orthorhombic media to model acoustic wavefields. We apply the lowrank approximation approach to handle the corresponding space-wavenumber mixed-domain operator. Numerical experiments show that the proposed wavefield extrapolator is accurate and practically free of dispersions. Further, there is no coupling of qSv and qP waves, because we use the analytical dispersion relation. No constraints on Thomsen\\'s parameters are required for stability. The linearized expression may provide useful application for parameter estimation in orthorhombic media.
Chabanas, M; Marecaux, C; Swider, P; Boutault, F; Chabanas, Matthieu; Payan, Yohan; Marecaux, Christophe; Swider, Pascal; Boutault, Franck
2004-01-01
A Finite Element model of the face soft tissue is proposed to simulate the morphological outcomes of maxillofacial surgery. Three modelling options are implemented: a linear elastic model with small and large deformation hypothesis, and an hyperelastic Mooney-Rivlin model. An evaluation procedure based on a qualitative and quantitative comparison of the simulations with a post-operative CT scan is detailed. It is then applied to one clinical case to evaluate the differences between the three models, and with the actual patient morphology. First results shows in particular that for a "simple" clinical procedure where stress is less than 20%, a linear model seams sufficient for a correct modelling.
Repopulation Kinetics and the Linear-Quadratic Model
O'Rourke, S. F. C.; McAneney, H.; Starrett, C.; O'Sullivan, J. M.
2009-08-01
The standard Linear-Quadratic (LQ) survival model for radiotherapy is used to investigate different schedules of radiation treatment planning for advanced head and neck cancer. We explore how these treament protocols may be affected by different tumour repopulation kinetics between treatments. The laws for tumour cell repopulation include the logistic and Gompertz models and this extends the work of Wheldon et al. [1], which was concerned with the case of exponential repopulation between treatments. Treatment schedules investigated include standarized and accelerated fractionation. Calculations based on the present work show, that even with growth laws scaled to ensure that the repopulation kinetics for advanced head and neck cancer are comparable, considerable variation in the survival fraction to orders of magnitude emerged. Calculations show that application of the Gompertz model results in a significantly poorer prognosis for tumour eradication. Gaps in treatment also highlight the differences in the LQ model with the effect of repopulation kinetics included.
Schäfer, Dirk; Schäfer, Wolfgang; Kinzelbach, Wolfgang
1998-05-01
The reactive transport model TBC (transport, biochemistry, and chemistry) numerically solves the equations for reactive transport in three-dimensional saturated groundwater flow. A finite element approximation and a standard Galerkin method are used. Solute transport is coupled to microbially mediated organic carbon degradation. Microbial growth is assumed to follow Monod-type kinetics. Substrate consumption and release of metabolic products is coupled to microbial growth via yield coefficients and stoichiometric relations. Additionally, the effects of microbial activity on selected inorganic chemical species in the aquifer can be considered. TBC allows the user to specify a wide range of possible biochemical and chemical reactions in the input file. This makes TBC a powerful and flexible simulation tool. It was developed to simulate reactive processes related to in situ bioremediation, but further fields of application are laboratory column studies on redox processes coupled to organic carbon degradation, field cases of intrinsic biodegradation, and early diagenetic processes in sediments.
Linear mixed models a practical guide using statistical software
West, Brady T; Galecki, Andrzej T
2014-01-01
Highly recommended by JASA, Technometrics, and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition continues to lead readers step by step through the process of fitting LMMs. This second edition covers additional topics on the application of LMMs that are valuable for data analysts in all fields. It also updates the case studies using the latest versions of the software procedures and provides up-to-date information on the options and features of the software procedures available for fitting LMMs in SAS, SPSS, Stata, R/S-plus, and HLM.New to the Second Edition A new chapter on models with crossed random effects that uses a case study to illustrate software procedures capable of fitting these models Power analysis methods for longitudinal and clustered study designs, including software options for power analyses and suggest...
Finite Population Correction for Two-Level Hierarchical Linear Models.
Lai, Mark H C; Kwok, Oi-Man; Hsiao, Yu-Yu; Cao, Qian
2017-03-16
The research literature has paid little attention to the issue of finite population at a higher level in hierarchical linear modeling. In this article, we propose a method to obtain finite-population-adjusted standard errors of Level-1 and Level-2 fixed effects in 2-level hierarchical linear models. When the finite population at Level-2 is incorrectly assumed as being infinite, the standard errors of the fixed effects are overestimated, resulting in lower statistical power and wider confidence intervals. The impact of ignoring finite population correction is illustrated by using both a real data example and a simulation study with a random intercept model and a random slope model. Simulation results indicated that the bias in the unadjusted fixed-effect standard errors was substantial when the Level-2 sample size exceeded 10% of the Level-2 population size; the bias increased with a larger intraclass correlation, a larger number of clusters, and a larger average cluster size. We also found that the proposed adjustment produced unbiased standard errors, particularly when the number of clusters was at least 30 and the average cluster size was at least 10. We encourage researchers to consider the characteristics of the target population for their studies and adjust for finite population when appropriate. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Linear models for multivariate, time series, and spatial data
Christensen, Ronald
1991-01-01
This is a companion volume to Plane Answers to Complex Questions: The Theory 0/ Linear Models. It consists of six additional chapters written in the same spirit as the last six chapters of the earlier book. Brief introductions are given to topics related to linear model theory. No attempt is made to give a comprehensive treatment of the topics. Such an effort would be futile. Each chapter is on a topic so broad that an in depth discussion would require a book-Iength treatment. People need to impose structure on the world in order to understand it. There is a limit to the number of unrelated facts that anyone can remem ber. If ideas can be put within a broad, sophisticatedly simple structure, not only are they easier to remember but often new insights become avail able. In fact, sophisticatedly simple models of the world may be the only ones that work. I have often heard Arnold Zellner say that, to the best of his knowledge, this is true in econometrics. The process of modeling is fundamental to understand...
THE SEPARATION OF URANIUM ISOTOPES BY GASEOUS DIFFUSION: A LINEAR PROGRAMMING MODEL,
URANIUM, ISOTOPE SEPARATION), (*GASEOUS DIFFUSION SEPARATION, LINEAR PROGRAMMING ), (* LINEAR PROGRAMMING , GASEOUS DIFFUSION SEPARATION), MATHEMATICAL MODELS, GAS FLOW, NUCLEAR REACTORS, OPERATIONS RESEARCH
A two-fluid model for reactive dilute solid-liquid mixtures with phase changes
Reis, Martina Costa; Wang, Yongqi
2016-12-01
Based on the Eulerian spatial averaging theory and the Müller-Liu entropy principle, a two-fluid model for reactive dilute solid-liquid mixtures is presented. Initially, some averaging theorems and properties of average quantities are discussed and, then, averaged balance equations including interfacial source terms are postulated. Moreover, constitutive equations are proposed for a reactive dilute solid-liquid mixture, where the formation of the solid phase is due to a precipitation chemical reaction that involves ions dissolved in the liquid phase. To this end, principles of constitutive theory are used to propose linearized constitutive equations that account for diffusion, heat conduction, viscous and drag effects, and interfacial deformations. A particularity of the model is that the mass interfacial source term is regarded as an independent constitutive variable. The obtained results show that the inclusion of the mass interfacial source term into the set of independent constitutive variables permits to easily describe the phase changes associated with precipitation chemical reactions.
A two-fluid model for reactive dilute solid-liquid mixtures with phase changes
Reis, Martina Costa; Wang, Yongqi
2017-03-01
Based on the Eulerian spatial averaging theory and the Müller-Liu entropy principle, a two-fluid model for reactive dilute solid-liquid mixtures is presented. Initially, some averaging theorems and properties of average quantities are discussed and, then, averaged balance equations including interfacial source terms are postulated. Moreover, constitutive equations are proposed for a reactive dilute solid-liquid mixture, where the formation of the solid phase is due to a precipitation chemical reaction that involves ions dissolved in the liquid phase. To this end, principles of constitutive theory are used to propose linearized constitutive equations that account for diffusion, heat conduction, viscous and drag effects, and interfacial deformations. A particularity of the model is that the mass interfacial source term is regarded as an independent constitutive variable. The obtained results show that the inclusion of the mass interfacial source term into the set of independent constitutive variables permits to easily describe the phase changes associated with precipitation chemical reactions.
Parappagoudar, Mahesh B.; Pratihar, Dilip K.; Datta, Gouranga L.
2008-08-01
A cement-bonded moulding sand system takes a fairly long time to attain the required strength. Hence, the moulds prepared with cement as a bonding material will have to wait a long time for the metal to be poured. In this work, an accelerator was used to accelerate the process of developing the bonding strength. Regression analysis was carried out on the experimental data collected as per statistical design of experiments (DOE) to establish input-output relationships of the process. The experiments were conducted to measure compression strength and hardness (output parameters) by varying the input variables, namely amount of cement, amount of accelerator, water in the form of cement-to-water ratio, and testing time. A two-level full-factorial design was used for linear regression model, whereas a three-level central composite design (CCD) had been utilized to develop non-linear regression model. Surface plots and main effects plots were used to study the effects of amount of cement, amount of accelerator, water and testing time on compression strength, and mould hardness. It was observed from both the linear as well as non-linear models that amount of cement, accelerator, and testing time have some positive contributions, whereas cement-to-water ratio has negative contribution to both the above responses. Compression strength was found to have linear relationship with the amount of cement and accelerator, and non-linear relationship with the remaining process parameters. Mould hardness was seen to vary linearly with testing time and non-linearly with the other parameters. Analysis of variance (ANOVA) was performed to test statistical adequacy of the models. Twenty random test cases were considered to test and compare their performances. Non-linear regression models were found to perform better than the linear models for both the responses. An attempt was also made to express compression strength of the moulding sand system as a function of mould hardness.
Nucleic acid reactivity: challenges for next-generation semiempirical quantum models.
Huang, Ming; Giese, Timothy J; York, Darrin M
2015-07-01
Semiempirical quantum models are routinely used to study mechanisms of RNA catalysis and phosphoryl transfer reactions using combined quantum mechanical (QM)/molecular mechanical methods. Herein, we provide a broad assessment of the performance of existing semiempirical quantum models to describe nucleic acid structure and reactivity to quantify their limitations and guide the development of next-generation quantum models with improved accuracy. Neglect of diatomic differential overlap and self-consistent density-functional tight-binding semiempirical models are evaluated against high-level QM benchmark calculations for seven biologically important datasets. The datasets include: proton affinities, polarizabilities, nucleobase dimer interactions, dimethyl phosphate anion, nucleoside sugar and glycosidic torsion conformations, and RNA phosphoryl transfer model reactions. As an additional baseline, comparisons are made with several commonly used density-functional models, including M062X and B3LYP (in some cases with dispersion corrections). The results show that, among the semiempirical models examined, the AM1/d-PhoT model is the most robust at predicting proton affinities. AM1/d-PhoT and DFTB3-3ob/OPhyd reproduce the MP2 potential energy surfaces of 6 associative RNA phosphoryl transfer model reactions reasonably well. Further, a recently developed linear-scaling "modified divide-and-conquer" model exhibits the most accurate results for binding energies of both hydrogen bonded and stacked nucleobase dimers. The semiempirical models considered here are shown to underestimate the isotropic polarizabilities of neutral molecules by approximately 30%. The semiempirical models also fail to adequately describe torsion profiles for the dimethyl phosphate anion, the nucleoside sugar ring puckers, and the rotations about the nucleoside glycosidic bond. The modeling of pentavalent phosphorus, particularly with thio substitutions often used experimentally as mechanistic
Non Linear Force Free Field Modeling for a Pseudostreamer
Karna, Nishu; Savcheva, Antonia; Gibson, Sarah; Tassev, Svetlin V.
2017-08-01
In this study we present a magnetic configuration of a pseudostreamer observed on April 18, 2015 on southern west limb embedding a filament cavity. We constructed Non Linear Force Free Field (NLFFF) model using the flux rope insertion method. The NLFFF model produces the three-dimensional coronal magnetic field constrained by observed coronal structures and photospheric magnetogram. SDO/HMI magnetogram was used as an input for the model. The high spatial and temporal resolution of the SDO/AIA allows us to select best-fit models that match the observations. The MLSO/CoMP observations provide full-Sun observations of the magnetic field in the corona. The primary observables of CoMP are the four Stokes parameters (I, Q, U, V). In addition, we perform a topology analysis of the models in order to determine the location of quasi-separatrix layers (QSLs). QSLs are used as a proxy to determine where the strong electric current sheets can develop in the corona and also provide important information about the connectivity in complicated magnetic field configuration. We present the major properties of the 3D QSL and FLEDGE maps and the evolution of 3D coronal structures during the magnetofrictional process. We produce FORWARD-modeled observables from our NLFFF models and compare to a toy MHD FORWARD model and the observations.
Modeling reactive transport with particle tracking and kernel estimators
Rahbaralam, Maryam; Fernandez-Garcia, Daniel; Sanchez-Vila, Xavier
2015-04-01
Groundwater reactive transport models are useful to assess and quantify the fate and transport of contaminants in subsurface media and are an essential tool for the analysis of coupled physical, chemical, and biological processes in Earth Systems. Particle Tracking Method (PTM) provides a computationally efficient and adaptable approach to solve the solute transport partial differential equation. On a molecular level, chemical reactions are the result of collisions, combinations, and/or decay of different species. For a well-mixed system, the chem- ical reactions are controlled by the classical thermodynamic rate coefficient. Each of these actions occurs with some probability that is a function of solute concentrations. PTM is based on considering that each particle actually represents a group of molecules. To properly simulate this system, an infinite number of particles is required, which is computationally unfeasible. On the other hand, a finite number of particles lead to a poor-mixed system which is limited by diffusion. Recent works have used this effect to actually model incomplete mix- ing in naturally occurring porous media. In this work, we demonstrate that this effect in most cases should be attributed to a defficient estimation of the concentrations and not to the occurrence of true incomplete mixing processes in porous media. To illustrate this, we show that a Kernel Density Estimation (KDE) of the concentrations can approach the well-mixed solution with a limited number of particles. KDEs provide weighting functions of each particle mass that expands its region of influence, hence providing a wider region for chemical reactions with time. Simulation results show that KDEs are powerful tools to improve state-of-the-art simulations of chemical reactions and indicates that incomplete mixing in diluted systems should be modeled based on alternative conceptual models and not on a limited number of particles.
New holographic dark energy model with non-linear interaction
Oliveros, A
2014-01-01
In this paper the cosmological evolution of a holographic dark energy model with a non-linear interaction between the dark energy and dark matter components in a FRW type flat universe is analysed. In this context, the deceleration parameter $q$ and the equation state $w_{\\Lambda}$ are obtained. We found that, as the square of the speed of sound remains positive, the model is stable under perturbations since early times; it also shows that the evolution of the matter and dark energy densities are of the same order for a long period of time, avoiding the so--called coincidence problem. We have also made the correspondence of the model with the dark energy densities and pressures for the quintessence and tachyon fields. From this correspondence we have reconstructed the potential of scalar fields and their dynamics.
Adaptive Error Estimation in Linearized Ocean General Circulation Models
Chechelnitsky, Michael Y.
1999-01-01
Data assimilation methods are routinely used in oceanography. The statistics of the model and measurement errors need to be specified a priori. This study addresses the problem of estimating model and measurement error statistics from observations. We start by testing innovation based methods of adaptive error estimation with low-dimensional models in the North Pacific (5-60 deg N, 132-252 deg E) to TOPEX/POSEIDON (TIP) sea level anomaly data, acoustic tomography data from the ATOC project, and the MIT General Circulation Model (GCM). A reduced state linear model that describes large scale internal (baroclinic) error dynamics is used. The methods are shown to be sensitive to the initial guess for the error statistics and the type of observations. A new off-line approach is developed, the covariance matching approach (CMA), where covariance matrices of model-data residuals are "matched" to their theoretical expectations using familiar least squares methods. This method uses observations directly instead of the innovations sequence and is shown to be related to the MT method and the method of Fu et al. (1993). Twin experiments using the same linearized MIT GCM suggest that altimetric data are ill-suited to the estimation of internal GCM errors, but that such estimates can in theory be obtained using acoustic data. The CMA is then applied to T/P sea level anomaly data and a linearization of a global GFDL GCM which uses two vertical modes. We show that the CMA method can be used with a global model and a global data set, and that the estimates of the error statistics are robust. We show that the fraction of the GCM-T/P residual variance explained by the model error is larger than that derived in Fukumori et al.(1999) with the method of Fu et al.(1993). Most of the model error is explained by the barotropic mode. However, we find that impact of the change in the error statistics on the data assimilation estimates is very small. This is explained by the large
Linear system identification via backward-time observer models
Juang, Jer-Nan; Phan, Minh
1993-01-01
This paper presents an algorithm to identify a state-space model of a linear system using a backward-time approach. The procedure consists of three basic steps. First, the Markov parameters of a backward-time observer are computed from experimental input-output data. Second, the backward-time observer Markov parameters are decomposed to obtain the backward-time system Markov parameters (backward-time pulse response samples) from which a backward-time state-space model is realized using the Eigensystem Realization Algorithm. Third, the obtained backward-time state space model is converted to the usual forward-time representation. Stochastic properties of this approach will be discussed. Experimental results are given to illustrate when and to what extent this concept works.
Accelerating transient simulation of linear reduced order models.
Thornquist, Heidi K.; Mei, Ting; Keiter, Eric Richard; Bond, Brad
2011-10-01
Model order reduction (MOR) techniques have been used to facilitate the analysis of dynamical systems for many years. Although existing model reduction techniques are capable of providing huge speedups in the frequency domain analysis (i.e. AC response) of linear systems, such speedups are often not obtained when performing transient analysis on the systems, particularly when coupled with other circuit components. Reduced system size, which is the ostensible goal of MOR methods, is often insufficient to improve transient simulation speed on realistic circuit problems. It can be shown that making the correct reduced order model (ROM) implementation choices is crucial to the practical application of MOR methods. In this report we investigate methods for accelerating the simulation of circuits containing ROM blocks using the circuit simulator Xyce.
Analysis of Robust Quasi-deviances for Generalized Linear Models
Eva Cantoni
2004-04-01
Full Text Available Generalized linear models (McCullagh and Nelder 1989 are a popular technique for modeling a large variety of continuous and discrete data. They assume that the response variables Yi , for i = 1, . . . , n, come from a distribution belonging to the exponential family, such that E[Yi ] = ?i and V[Yi ] = V (?i , and that ?i = g(?i = xiT?, where ? ? IR p is the vector of parameters, xi ? IR p, and g(. is the link function. The non-robustness of the maximum likelihood and the maximum quasi-likelihood estimators has been studied extensively in the literature. For model selection, the classical analysis-of-deviance approach shares the same bad robustness properties. To cope with this, Cantoni and Ronchetti (2001 propose a robust approach based on robust quasi-deviance functions for estimation and variable selection. We refer to that paper for a deeper discussion and the review of the literature.
Model Based Adaptive Piecewise Linear Controller for Complicated Control Systems
Tain-Sou Tsay
2014-01-01
Full Text Available A model based adaptive piecewise linear control scheme for industry processes with specifications on peak overshoots and rise times is proposed. It is a gain stabilized control technique. Large gain is used for large tracking error to get fast response. Small gain is used between large and small tracking error for good performance. Large gain is used again for small tracking error to cope with large disturbance. Parameters of the three-segment piecewise linear controller are found by an automatic regulating time series which is function of output characteristics of the plant and reference model. The time series will be converged to steady values after the time response of the considered system matching that of the reference model. The proposed control scheme is applied to four numerical examples which have been compensated by PID controllers. Parameters of PID controllers are found by optimization method. It gives an almost command independent response and gives significant improvements for response time and performance.
Modeling Pan Evaporation for Kuwait by Multiple Linear Regression
Jaber Almedeij
2012-01-01
Full Text Available Evaporation is an important parameter for many projects related to hydrology and water resources systems. This paper constitutes the first study conducted in Kuwait to obtain empirical relations for the estimation of daily and monthly pan evaporation as functions of available meteorological data of temperature, relative humidity, and wind speed. The data used here for the modeling are daily measurements of substantial continuity coverage, within a period of 17 years between January 1993 and December 2009, which can be considered representative of the desert climate of the urban zone of the country. Multiple linear regression technique is used with a procedure of variable selection for fitting the best model forms. The correlations of evaporation with temperature and relative humidity are also transformed in order to linearize the existing curvilinear patterns of the data by using power and exponential functions, respectively. The evaporation models suggested with the best variable combinations were shown to produce results that are in a reasonable agreement with observation values.
Non-linear DSGE Models and The Optimized Particle Filter
Andreasen, Martin Møller
This paper improves the accuracy and speed of particle filtering for non-linear DSGE models with potentially non-normal shocks. This is done by introducing a new proposal distribution which i) incorporates information from new observables and ii) has a small optimization step that minimizes...... the distance to the optimal proposal distribution. A particle filter with this proposal distribution is shown to deliver a high level of accuracy even with relatively few particles, and this filter is therefore much more efficient than the standard particle filter....
Investigation of $\\eta'N$ system using linear sigma model
Sakai, Shuntaro
2016-01-01
In this paper, we investigate the $\\eta'N$ system using the three-flavor linear sigma model including the effect of the flavor SU(3) symmetry breaking. The $\\eta'N$ bound state is found also in the case including the flavor symmetry braking and the coupling with the $\\eta N$ and $\\pi N$ channels. The $\\eta'N$ interaction becomes more attractive with the inclusion of the flavor symmetry breaking which causes the mixing between the singlet and octet scalar mesons. The existence of such a bound state would have some impact on the $\\eta'$-nucleus system, which is of interest from the theoretical and experimental viewpoint.
ROBUST ESTIMATION IN PARTIAL LINEAR MIXED MODEL FOR LONGITUDINAL DATA
Qin Guoyou; Zhu Zhongyi
2008-01-01
In this article, robust generalized estimating equation for the analysis of par- tial linear mixed model for longitudinal data is used. The authors approximate the non- parametric function by a regression spline. Under some regular conditions, the asymptotic properties of the estimators are obtained. To avoid the computation of high-dimensional integral, a robust Monte Carlo Newton-Raphson algorithm is used. Some simulations are carried out to study the performance of the proposed robust estimators. In addition, the authors also study the robustness and the efficiency of the proposed estimators by simulation. Finally, two real longitudinal data sets are analyzed.
Diffusion and wave behaviour in linear Voigt model
De Angelis, Monica
2012-01-01
A boundary value problem related to a third- order parabolic equation with a small parameter is analized. This equation models the one-dimensional evolution of many dissipative media as viscoelastic fluids or solids, viscous gases, superconducting materials, incompressible and electrically conducting fluids. Moreover, the third-order parabolic operator regularizes various non linear second order wave equations. In this paper, the hyperbolic and parabolic behaviour of the solution is estimated by means of slow time and fast time. As consequence, a rigorous asymptotic approximation for the solution is established.
A linear model for flow over complex terrain
Frank, H.P. [Risoe National Lab., Wind Energy and Atmospheric Physics Dept., Roskilde (Denmark)
1999-03-01
A linear flow model similar to WA{sup s}P or LINCOM has been developed. Major differences are an isentropic temperature equation which allows internal gravity waves, and vertical advection of the shear of the mean flow. The importance of these effects are illustrated by examples. Resource maps are calculated from a distribution of geostrophic winds and stratification for Pyhaetunturi Fell in northern Finland and Acqua Spruzza in Italy. Stratification becomes important if the inverse Froude number formulated with the width of the hill becomes of order one or greater. (au) EU-JOULE-3. 16 refs.
Adaptive quasi-likelihood estimate in generalized linear models
CHEN Xia; CHEN Xiru
2005-01-01
This paper gives a thorough theoretical treatment on the adaptive quasilikelihood estimate of the parameters in the generalized linear models. The unknown covariance matrix of the response variable is estimated by the sample. It is shown that the adaptive estimator defined in this paper is asymptotically most efficient in the sense that it is asymptotic normal, and the covariance matrix of the limit distribution coincides with the one for the quasi-likelihood estimator for the case that the covariance matrix of the response variable is completely known.
Yuanyuan ZOU; Shaoyuan LI
2007-01-01
In this paper,a linear programming method is proposed to solve model predictive control for a class of hybrid systems.Firstly,using the(max,+)algebra,a typical subclass of hybrid systems called max-plus-linear(MPL)systems is obtained.And then,model predictive control(MPC)framework is extended to MPL systems.In general,the nonlinear optimization approach or extended linear complementarity problem(ELCP)were applied to solve the MPL-MPC optimization problem.A new optimization method based on canonical forms for max-min-plus-scaling(MMPS)functions (using the operations maximization,minimization,addition and scalar multiplication)with linear constraints on the inputs is presented.The proposed approach consists in solving several linear programming problems and is more efficient than nonlinear optimization.The validity of the algorithm is illustrated by an example.
Filtering nonlinear dynamical systems with linear stochastic models
Harlim, J.; Majda, A. J.
2008-06-01
An important emerging scientific issue is the real time filtering through observations of noisy signals for nonlinear dynamical systems as well as the statistical accuracy of spatio-temporal discretizations for filtering such systems. From the practical standpoint, the demand for operationally practical filtering methods escalates as the model resolution is significantly increased. For example, in numerical weather forecasting the current generation of global circulation models with resolution of 35 km has a total of billions of state variables. Numerous ensemble based Kalman filters (Evensen 2003 Ocean Dyn. 53 343-67 Bishop et al 2001 Mon. Weather Rev. 129 420-36 Anderson 2001 Mon. Weather Rev. 129 2884-903 Szunyogh et al 2005 Tellus A 57 528-45 Hunt et al 2007 Physica D 230 112-26) show promising results in addressing this issue; however, all these methods are very sensitive to model resolution, observation frequency, and the nature of the turbulent signals when a practical limited ensemble size (typically less than 100) is used. In this paper, we implement a radical filtering approach to a relatively low (40) dimensional toy model, the L-96 model (Lorenz 1996 Proc. on Predictability (ECMWF, 4-8 September 1995) pp 1-18) in various chaotic regimes in order to address the 'curse of ensemble size' for complex nonlinear systems. Practically, our approach has several desirable features such as extremely high computational efficiency, filter robustness towards variations of ensemble size (we found that the filter is reasonably stable even with a single realization) which makes it feasible for high dimensional problems, and it is independent of any tunable parameters such as the variance inflation coefficient in an ensemble Kalman filter. This radical filtering strategy decouples the problem of filtering a spatially extended nonlinear deterministic system to filtering a Fourier diagonal system of parametrized linear stochastic differential equations (Majda and Grote
Phenomenology of non-minimal supersymmetric models at linear colliders
Porto, Stefano
2015-06-15
The focus of this thesis is on the phenomenology of several non-minimal supersymmetric models in the context of future linear colliders (LCs). Extensions of the minimal supersymmetric Standard Model (MSSM) may accommodate the observed Higgs boson mass at about 125 GeV in a more natural way than the MSSM, with a richer phenomenology. We consider both F-term extensions of the MSSM, as for instance the non-minimal supersymmetric Standard Model (NMSSM), as well as D-terms extensions arising at low energies from gauge extended supersymmetric models. The NMSSM offers a solution to the μ-problem with an additional gauge singlet supermultiplet. The enlarged neutralino sector of the NMSSM can be accurately studied at a LC and used to distinguish the model from the MSSM. We show that exploiting the power of the polarised beams of a LC can be used to reconstruct the neutralino and chargino sector and eventually distinguish the NMSSM even considering challenging scenarios that resemble the MSSM. Non-decoupling D-terms extensions of the MSSM can raise the tree-level Higgs mass with respect to the MSSM. This is done through additional contributions to the Higgs quartic potential, effectively generated by an extended gauge group. We study how this can happen and we show how these additional non-decoupling D-terms affect the SM-like Higgs boson couplings to fermions and gauge bosons. We estimate how the deviations from the SM couplings can be spotted at the Large Hadron Collider (LHC) and at the International Linear Collider (ILC), showing how the ILC would be suitable for the model identication. Since our results prove that a linear collider is a fundamental machine for studying supersymmetry phenomenology at a high level of precision, we argue that also a thorough comprehension of the physics at the interaction point (IP) of a LC is needed. Therefore, we finally consider the possibility of observing intense electromagnetic field effects and nonlinear quantum electrodynamics
Microbially Mediated Kinetic Sulfur Isotope Fractionation: Reactive Transport Modeling Benchmark
Wanner, C.; Druhan, J. L.; Cheng, Y.; Amos, R. T.; Steefel, C. I.; Ajo Franklin, J. B.
2014-12-01
Microbially mediated sulfate reduction is a ubiquitous process in many subsurface systems. Isotopic fractionation is characteristic of this anaerobic process, since sulfate reducing bacteria (SRB) favor the reduction of the lighter sulfate isotopologue (S32O42-) over the heavier isotopologue (S34O42-). Detection of isotopic shifts have been utilized as a proxy for the onset of sulfate reduction in subsurface systems such as oil reservoirs and aquifers undergoing uranium bioremediation. Reactive transport modeling (RTM) of kinetic sulfur isotope fractionation has been applied to field and laboratory studies. These RTM approaches employ different mathematical formulations in the representation of kinetic sulfur isotope fractionation. In order to test the various formulations, we propose a benchmark problem set for the simulation of kinetic sulfur isotope fractionation during microbially mediated sulfate reduction. The benchmark problem set is comprised of four problem levels and is based on a recent laboratory column experimental study of sulfur isotope fractionation. Pertinent processes impacting sulfur isotopic composition such as microbial sulfate reduction and dispersion are included in the problem set. To date, participating RTM codes are: CRUNCHTOPE, TOUGHREACT, MIN3P and THE GEOCHEMIST'S WORKBENCH. Preliminary results from various codes show reasonable agreement for the problem levels simulating sulfur isotope fractionation in 1D.
Predictive modeling of reactive wetting and metal joining.
van Swol, Frank B.
2013-09-01
The performance, reproducibility and reliability of metal joints are complex functions of the detailed history of physical processes involved in their creation. Prediction and control of these processes constitutes an intrinsically challenging multi-physics problem involving heating and melting a metal alloy and reactive wetting. Understanding this process requires coupling strong molecularscale chemistry at the interface with microscopic (diffusion) and macroscopic mass transport (flow) inside the liquid followed by subsequent cooling and solidification of the new metal mixture. The final joint displays compositional heterogeneity and its resulting microstructure largely determines the success or failure of the entire component. At present there exists no computational tool at Sandia that can predict the formation and success of a braze joint, as current capabilities lack the ability to capture surface/interface reactions and their effect on interface properties. This situation precludes us from implementing a proactive strategy to deal with joining problems. Here, we describe what is needed to arrive at a predictive modeling and simulation capability for multicomponent metals with complicated phase diagrams for melting and solidification, incorporating dissolutive and composition-dependent wetting.
Foundation stiffness in the linear modeling of wind turbines
Chiang, Chih-Hung; Yu, Chih-Peng; Chen, Yan-Hao; Lai, Jiunnren; Hsu, Keng-Tsang; Cheng, Chia-Chi
2017-04-01
Effects of foundation stiffness on the linear vibrations of wind turbine systems are of concerns for both planning and construction of wind turbine systems. Current study performed numerical modeling for such a problem using linear spectral finite elements. The effects of foundation stiffness were investigated for various combinations of shear wave velocity of soil, size of tower base plate, and pile length. Multiple piles are also included in the models such that the foundation stiffness can be analyzed more realistically. The results indicate that the shear wave velocity of soil and the size of tower base plate have notable effects on the dominant frequency of the turbine-tower system. The larger the lateral dimension, the stiffer the foundation. Large pile cap and multiple spaced piles result in higher stiffness than small pile cap and a mono-pile. The lateral stiffness of a mono-pile mainly depends on the shear wave velocity of soil with the exception for a very short pile that the end constraints may affect the lateral vibration of the superstructure. Effective pile length may be determined by comparing the simulation results of the frictional pile to those of the end-bearing pile.
Linearization models for parabolic dynamical systems via Abel's functional equation
Elin, Mark; Reich, Simeon; Shoikhet, David
2009-01-01
We study linearization models for continuous one-parameter semigroups of parabolic type. In particular, we introduce new limit schemes to obtain solutions of Abel's functional equation and to study asymptotic behavior of such semigroups. The crucial point is that these solutions are univalent functions convex in one direction. In a parallel direction, we find analytic conditions which determine certain geometric properties of those functions, such as the location of their images in either a half-plane or a strip, and their containing either a half-plane or a strip. In the context of semigroup theory these geometric questions may be interpreted as follows: is a given one-parameter continuous semigroup either an outer or an inner conjugate of a group of automorphisms? In other words, the problem is finding a fractional linear model of the semigroup which is defined by a group of automorphisms of the open unit disk. Our results enable us to establish some new important analytic and geometric characteristics of t...
Low-energy limit of the extended Linear Sigma Model
Divotgey, Florian; Giacosa, Francesco; Rischke, Dirk H
2016-01-01
The extended Linear Sigma Model (eLSM) is an effective hadronic model based on the linear realization of chiral symmetry $SU(N_f)_L \\times SU(N_f)_R$, with (pseudo)scalar and (axial-)vector mesons as degrees of freedom. In this paper, we study the low-energy limit of the eLSM for $N_f=2$ flavors by integrating out all fields except for the pions, the (pseudo-)Nambu--Goldstone bosons of chiral symmetry breaking. We only keep terms entering at tree level and up to fourth order in powers of derivatives of the pion fields. Up to this order, there are four low-energy coupling constants in the resulting low-energy effective action. We show that the latter is formally identical to Chiral Perturbation Theory (ChPT), after choosing a representative for the coset space generated by chiral symmetry breaking and expanding up to fourth order in powers of derivatives of the pion fields. Two of the low-energy coupling constants of the eLSM are uniquely determined by a fit to hadron masses and decay widths. We find that thei...
Acoustic FMRI noise: linear time-invariant system model.
Rizzo Sierra, Carlos V; Versluis, Maarten J; Hoogduin, Johannes M; Duifhuis, Hendrikus Diek
2008-09-01
Functional magnetic resonance imaging (fMRI) enables sites of brain activation to be localized in human subjects. For auditory system studies, however, the acoustic noise generated by the scanner tends to interfere with the assessments of this activation. Understanding and modeling fMRI acoustic noise is a useful step to its reduction. To study acoustic noise, the MR scanner is modeled as a linear electroacoustical system generating sound pressure signals proportional to the time derivative of the input gradient currents. The transfer function of one MR scanner is determined for two different input specifications: 1) by using the gradient waveform calculated by the scanner software and 2) by using a recording of the gradient current. Up to 4 kHz, the first method is shown as reliable as the second one, and its use is encouraged when direct measurements of gradient currents are not possible. Additionally, the linear order and average damping properties of the gradient coil system are determined by impulse response analysis. Since fMRI is often based on echo planar imaging (EPI) sequences, a useful validation of the transfer function prediction ability can be obtained by calculating the acoustic output for the EPI sequence. We found a predicted sound pressure level (SPL) for the EPI sequence of 104 dB SPL compared to a measured value of 102 dB SPL. As yet, the predicted EPI pressure waveform shows similarity as well as some differences with the directly measured EPI pressure waveform.
Linear versus quadratic portfolio optimization model with transaction cost
Razak, Norhidayah Bt Ab; Kamil, Karmila Hanim; Elias, Siti Masitah
2014-06-01
Optimization model is introduced to become one of the decision making tools in investment. Hence, it is always a big challenge for investors to select the best model that could fulfill their goal in investment with respect to risk and return. In this paper we aims to discuss and compare the portfolio allocation and performance generated by quadratic and linear portfolio optimization models namely of Markowitz and Maximin model respectively. The application of these models has been proven to be significant and popular among others. However transaction cost has been debated as one of the important aspects that should be considered for portfolio reallocation as portfolio return could be significantly reduced when transaction cost is taken into consideration. Therefore, recognizing the importance to consider transaction cost value when calculating portfolio' return, we formulate this paper by using data from Shariah compliant securities listed in Bursa Malaysia. It is expected that, results from this paper will effectively justify the advantage of one model to another and shed some lights in quest to find the best decision making tools in investment for individual investors.
Some generalisations of linear-graph modelling for dynamic systems
de Silva, Clarence W.; Pourazadi, Shahram
2013-11-01
Proper modelling of a dynamic system can benefit analysis, simulation, design, evaluation and control of the system. The linear-graph (LG) approach is suitable for modelling lumped-parameter dynamic systems. By using the concepts of graph trees, it provides a graphical representation of the system, with a direct correspondence to the physical component topology. This paper systematically extends the application of LGs to multi-domain (mixed-domain or multi-physics) dynamic systems by presenting a unified way to represent different domains - mechanical, electrical, thermal and fluid. Preservation of the structural correspondence across domains is a particular advantage of LGs when modelling mixed-domain systems. The generalisation of Thevenin and Norton equivalent circuits to mixed-domain systems, using LGs, is presented. The structure of an LG model may follow a specific pattern. Vector LGs are introduced to take advantage of such patterns, giving a general LG representation for them. Through these vector LGs, the model representation becomes simpler and rather compact, both topologically and parametrically. A new single LG element is defined to facilitate the modelling of distributed-parameter (DP) systems. Examples are presented using multi-domain systems (a motion-control system and a flow-controlled pump), a multi-body mechanical system (robot manipulator) and DP systems (structural rods) to illustrate the application and advantages of the methodologies developed in the paper.
Synthetic Domain Theory and Models of Linear Abadi & Plotkin Logic
Møgelberg, Rasmus Ejlers; Birkedal, Lars; Rosolini, Guiseppe
2008-01-01
Plotkin suggested using a polymorphic dual intuitionistic/linear type theory (PILLY) as a metalanguage for parametric polymorphism and recursion. In recent work the first two authors and R.L. Petersen have defined a notion of parametric LAPL-structure, which are models of PILLY, in which one can...... reason using parametricity and, for example, solve a large class of domain equations, as suggested by Plotkin.In this paper, we show how an interpretation of a strict version of Bierman, Pitts and Russo's language Lily into synthetic domain theory presented by Simpson and Rosolini gives rise...... to a parametric LAPL-structure. This adds to the evidence that the notion of LAPL-structure is a general notion, suitable for treating many different parametric models, and it provides formal proofs of consequences of parametricity expected to hold for the interpretation. Finally, we show how these results...
Explicit estimating equations for semiparametric generalized linear latent variable models
Ma, Yanyuan
2010-07-05
We study generalized linear latent variable models without requiring a distributional assumption of the latent variables. Using a geometric approach, we derive consistent semiparametric estimators. We demonstrate that these models have a property which is similar to that of a sufficient complete statistic, which enables us to simplify the estimating procedure and explicitly to formulate the semiparametric estimating equations. We further show that the explicit estimators have the usual root n consistency and asymptotic normality. We explain the computational implementation of our method and illustrate the numerical performance of the estimators in finite sample situations via extensive simulation studies. The advantage of our estimators over the existing likelihood approach is also shown via numerical comparison. We employ the method to analyse a real data example from economics. © 2010 Royal Statistical Society.
Relating Cohesive Zone Model to Linear Elastic Fracture Mechanics
Wang, John T.
2010-01-01
The conditions required for a cohesive zone model (CZM) to predict a failure load of a cracked structure similar to that obtained by a linear elastic fracture mechanics (LEFM) analysis are investigated in this paper. This study clarifies why many different phenomenological cohesive laws can produce similar fracture predictions. Analytical results for five cohesive zone models are obtained, using five different cohesive laws that have the same cohesive work rate (CWR-area under the traction-separation curve) but different maximum tractions. The effect of the maximum traction on the predicted cohesive zone length and the remote applied load at fracture is presented. Similar to the small scale yielding condition for an LEFM analysis to be valid. the cohesive zone length also needs to be much smaller than the crack length. This is a necessary condition for a CZM to obtain a fracture prediction equivalent to an LEFM result.
Reactive surface area in geochemical models - Lessons learned from a natural analogue
Koenen, M.; Wasch, L.J.
2013-01-01
Many uncertainties exist in geochemical modeling. Mineral reactive surface area is one of the uncertain parameters. QEMSCAN analyses are performed on sandstone samples from a Dutch CO2 natural analogue to determine reactive surface areas. Geochemical modeling is performed using QEMSCAN surface areas
Modeling Stratospheric Constituents: Reactive Species That Regulate Ozone
Salawitch, Ross J.
2000-01-01
Photochemical loss of stratospheric ozone occurs primarily by catalytic cycles whose rates are limited by the concentration of OH, HO2, NO2, ClO, and/or BrO as well as the concentration of either atomic oxygen or of ozone itself. Once the concentrations of these gases are established, the photochemical loss rate of O3 depends on the rate coefficient of only a handful of key reactions. We have developed a method for testing our understanding of stratospheric ozone photochemistry by comparing measured and modeled concentrations of reactive hydrogen, nitrogen, chlorine and bromine radicals using a photochemical steady state model constrained by observed concentrations of long-lived precursors (e.g., NO(y), Cl(y), Br(y), O3, H2O, CH4) and environmental parameters such as ozone column, reflectivity, and aerosol surface area. We will show based on analyses of observations obtained by aircraft, balloon, and satellite platforms during the POLARIS campaign that our overall understanding of the processes that regulate these radical species is very good. The most notable current discrepancies are the tendency to underestimate observed NO2 by 15 to 30% for air masses that experience near continuous solar illumination over a 24 hour period and the tendency to underestimate observed OH and H02 by about 10 to 20% during midday and by much larger amounts at high solar zenith angle (SZA > 85). Possible resolutions to these discrepancies will be discussed. This study was carried out in close collaboration with many members of the POLARIS science team.
Electroweak Corrections and Unitarity in Linear Moose Models
Chivukula, R S; Kurachi, M; Simmons, E H; Tanabashi, M; He, Hong-Jian; Kurachi, Masafumi; Simmons, Elizabeth H.; Tanabashi, Masaharu
2004-01-01
We calculate the form of the corrections to the electroweak interactions in the class of Higgsless models which can be "deconstructed'' to a chain of SU(2) gauge groups adjacent to a chain of U(1) gauge groups, and with the fermions coupled to any single SU(2) group and to any single U(1) group along the chain. The primary advantage of our technique is that the size of corrections to electroweak processes can be directly related to the spectrum of vector bosons ("KK modes"). In Higgsless models, this spectrum is constrained by unitarity. Our methods also allow for arbitrary background 5-D geometry, spatially dependent gauge-couplings, and brane kinetic energy terms. We find that, due to the size of corrections to electroweak processes in any unitary theory, Higgsless models with localized fermions are disfavored by precision electroweak data. Although we stress our results as they apply to continuum Higgsless 5-D models, they apply to any linear moose model including those with only a few extra vector bosons....
On the unnecessary ubiquity of hierarchical linear modeling.
McNeish, Daniel; Stapleton, Laura M; Silverman, Rebecca D
2017-03-01
In psychology and the behavioral sciences generally, the use of the hierarchical linear model (HLM) and its extensions for discrete outcomes are popular methods for modeling clustered data. HLM and its discrete outcome extensions, however, are certainly not the only methods available to model clustered data. Although other methods exist and are widely implemented in other disciplines, it seems that psychologists have yet to consider these methods in substantive studies. This article compares and contrasts HLM with alternative methods including generalized estimating equations and cluster-robust standard errors. These alternative methods do not model random effects and thus make a smaller number of assumptions and are interpreted identically to single-level methods with the benefit that estimates are adjusted to reflect clustering of observations. Situations where these alternative methods may be advantageous are discussed including research questions where random effects are and are not required, when random effects can change the interpretation of regression coefficients, challenges of modeling with random effects with discrete outcomes, and examples of published psychology articles that use HLM that may have benefitted from using alternative methods. Illustrative examples are provided and discussed to demonstrate the advantages of the alternative methods and also when HLM would be the preferred method. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Generalized linear models with coarsened covariates: a practical Bayesian approach.
Johnson, Timothy R; Wiest, Michelle M
2014-06-01
Coarsened covariates are a common and sometimes unavoidable phenomenon encountered in statistical modeling. Covariates are coarsened when their values or categories have been grouped. This may be done to protect privacy or to simplify data collection or analysis when researchers are not aware of their drawbacks. Analyses with coarsened covariates based on ad hoc methods can compromise the validity of inferences. One valid method for accounting for a coarsened covariate is to use a marginal likelihood derived by summing or integrating over the unknown realizations of the covariate. However, algorithms for estimation based on this approach can be tedious to program and can be computationally expensive. These are significant obstacles to their use in practice. To overcome these limitations, we show that when expressed as a Bayesian probability model, a generalized linear model with a coarsened covariate can be posed as a tractable missing data problem where the missing data are due to censoring. We also show that this model is amenable to widely available general-purpose software for simulation-based inference for Bayesian probability models, providing researchers a very practical approach for dealing with coarsened covariates.
Non-linear scaling of a musculoskeletal model of the lower limb using statistical shape models.
Nolte, Daniel; Tsang, Chui Kit; Zhang, Kai Yu; Ding, Ziyun; Kedgley, Angela E; Bull, Anthony M J
2016-10-03
Accurate muscle geometry for musculoskeletal models is important to enable accurate subject-specific simulations. Commonly, linear scaling is used to obtain individualised muscle geometry. More advanced methods include non-linear scaling using segmented bone surfaces and manual or semi-automatic digitisation of muscle paths from medical images. In this study, a new scaling method combining non-linear scaling with reconstructions of bone surfaces using statistical shape modelling is presented. Statistical Shape Models (SSMs) of femur and tibia/fibula were used to reconstruct bone surfaces of nine subjects. Reference models were created by morphing manually digitised muscle paths to mean shapes of the SSMs using non-linear transformations and inter-subject variability was calculated. Subject-specific models of muscle attachment and via points were created from three reference models. The accuracy was evaluated by calculating the differences between the scaled and manually digitised models. The points defining the muscle paths showed large inter-subject variability at the thigh and shank - up to 26mm; this was found to limit the accuracy of all studied scaling methods. Errors for the subject-specific muscle point reconstructions of the thigh could be decreased by 9% to 20% by using the non-linear scaling compared to a typical linear scaling method. We conclude that the proposed non-linear scaling method is more accurate than linear scaling methods. Thus, when combined with the ability to reconstruct bone surfaces from incomplete or scattered geometry data using statistical shape models our proposed method is an alternative to linear scaling methods.
Selection between Linear Factor Models and Latent Profile Models Using Conditional Covariances
Halpin, Peter F.; Maraun, Michael D.
2010-01-01
A method for selecting between K-dimensional linear factor models and (K + 1)-class latent profile models is proposed. In particular, it is shown that the conditional covariances of observed variables are constant under factor models but nonlinear functions of the conditioning variable under latent profile models. The performance of a convenient…
Selection between Linear Factor Models and Latent Profile Models Using Conditional Covariances
Halpin, Peter F.; Maraun, Michael D.
2010-01-01
A method for selecting between K-dimensional linear factor models and (K + 1)-class latent profile models is proposed. In particular, it is shown that the conditional covariances of observed variables are constant under factor models but nonlinear functions of the conditioning variable under latent profile models. The performance of a convenient…
Feedbacks, climate sensitivity, and the limits of linear models
Rugenstein, M.; Knutti, R.
2015-12-01
The term "feedback" is used ubiquitously in climate research, but implies varied meanings in different contexts. From a specific process that locally affects a quantity, to a formal framework that attempts to determine a global response to a forcing, researchers use this term to separate, simplify, and quantify parts of the complex Earth system. We combine large (>120 member) ensemble GCM and EMIC step forcing simulations over a broad range of forcing levels with a historical and educational perspective to organize existing ideas around feedbacks and linear forcing-feedback models. With a new method overcoming internal variability and initial condition problems we quantify the non-constancy of the climate feedback parameter. Our results suggest a strong state- and forcing-dependency of feedbacks, which is not considered appropriately in many studies. A non-constant feedback factor likely explains some of the differences in estimates of equilibrium climate sensitivity from different methods and types of data. We discuss implications for the definition of the forcing term and its various adjustments. Clarifying the value and applicability of the linear forcing feedback framework and a better quantification of feedbacks on various timescales and spatial scales remains a high priority in order to better understand past and predict future changes in the climate system.
Linear model applied to the evaluation of pharmaceutical stability data
Renato Cesar Souza
2013-09-01
Full Text Available The expiry date on the packaging of a product gives the consumer the confidence that the product will retain its identity, content, quality and purity throughout the period of validity of the drug. The definition of this term in the pharmaceutical industry is based on stability data obtained during the product registration. By the above, this work aims to apply the linear regression according to the guideline ICH Q1E, 2003, to evaluate some aspects of a product undergoing in a registration phase in Brazil. With this propose, the evaluation was realized with the development center of a multinational company in Brazil, with samples of three different batches composed by two active principal ingredients in two different packages. Based on the preliminary results obtained, it was possible to observe the difference of degradation tendency of the product in two different packages and the relationship between the variables studied, added knowledge so new models of linear equations can be applied and developed for other products.
Direction of Effects in Multiple Linear Regression Models.
Wiedermann, Wolfgang; von Eye, Alexander
2015-01-01
Previous studies analyzed asymmetric properties of the Pearson correlation coefficient using higher than second order moments. These asymmetric properties can be used to determine the direction of dependence in a linear regression setting (i.e., establish which of two variables is more likely to be on the outcome side) within the framework of cross-sectional observational data. Extant approaches are restricted to the bivariate regression case. The present contribution extends the direction of dependence methodology to a multiple linear regression setting by analyzing distributional properties of residuals of competing multiple regression models. It is shown that, under certain conditions, the third central moments of estimated regression residuals can be used to decide upon direction of effects. In addition, three different approaches for statistical inference are discussed: a combined D'Agostino normality test, a skewness difference test, and a bootstrap difference test. Type I error and power of the procedures are assessed using Monte Carlo simulations, and an empirical example is provided for illustrative purposes. In the discussion, issues concerning the quality of psychological data, possible extensions of the proposed methods to the fourth central moment of regression residuals, and potential applications are addressed.
Modeling of the jack rabbit series of experiments with a temperature based reactive burn model
Desbiens, Nicolas
2017-01-01
The Jack Rabbit experiments, performed by Lawrence Livermore National Laboratory, focus on detonation wave corner turning and shock desensitization. Indeed, while important for safety or charge design, the behaviour of explosives in these regimes is poorly understood. In this paper, our temperature based reactive burn model is calibrated for LX-17 and compared to the Jack Rabbit data. It is shown that our model can reproduce the corner turning and shock desensitization behaviour of four out of the five experiments.
Chambon, Julie Claire Claudia; Bjerg, Poul Løgstrup; Scheutz, Charlotte;
2013-01-01
Reductive dechlorination is a major degradation pathway of chlorinated ethenes in anaerobic subsurface environments, and reactive kinetic models describing the degradation process are needed in fate and transport models of these contaminants. However, reductive dechlorination is a complex biologi...
Statistical Inference for Partially Linear Regression Models with Measurement Errors
Jinhong YOU; Qinfeng XU; Bin ZHOU
2008-01-01
In this paper, the authors investigate three aspects of statistical inference for the partially linear regression models where some covariates are measured with errors. Firstly,a bandwidth selection procedure is proposed, which is a combination of the difference-based technique and GCV method. Secondly, a goodness-of-fit test procedure is proposed,which is an extension of the generalized likelihood technique. Thirdly, a variable selection procedure for the parametric part is provided based on the nonconcave penalization and corrected profile least squares. Same as "Variable selection via nonconcave penalized like-lihood and its oracle properties" (J. Amer. Statist. Assoc., 96, 2001, 1348-1360), it is shown that the resulting estimator has an oracle property with a proper choice of regu-larization parameters and penalty function. Simulation studies are conducted to illustrate the finite sample performances of the proposed procedures.
Adaptive Unified Biased Estimators of Parameters in Linear Model
Hu Yang; Li-xing Zhu
2004-01-01
To tackle multi collinearity or ill-conditioned design matrices in linear models,adaptive biased estimators such as the time-honored Stein estimator,the ridge and the principal component estimators have been studied intensively.To study when a biased estimator uniformly outperforms the least squares estimator,some suficient conditions are proposed in the literature.In this paper,we propose a unified framework to formulate a class of adaptive biased estimators.This class includes all existing biased estimators and some new ones.A suficient condition for outperforming the least squares estimator is proposed.In terms of selecting parameters in the condition,we can obtain all double-type conditions in the literature.
Modeling and Analysis of Linearized Wheel-Rail Contact Dynamics
Zulfiqar Ali Soomro
2014-07-01
Full Text Available The dynamics of the railway vehicles are nonlinear and depend upon several factors including vehicle speed, normal load and adhesion level. The presence of contaminants on the railway track makes them unpredictable too. Therefore in order to develop an effective control strategy it is important to analyze the effect of each factor on dynamic response thoroughly. In this paper a linearized model of a railway wheel-set is developed and is later analyzed by varying the speed and adhesion level by keeping the normal load constant. A wheel-set is the wheel-axle assembly of a railroad car. Patch contact is the study of the deformation of solids that touch each other at one or more points
Distributing Correlation Coefficients of Linear Structure-Activity/Property Models
Sorana D. BOLBOACA
2011-12-01
Full Text Available Quantitative structure-activity/property relationships are mathematical relationships linking chemical structure and activity/property in a quantitative manner. These in silico approaches are frequently used to reduce animal testing and risk-assessment, as well as to increase time- and cost-effectiveness in characterization and identification of active compounds. The aim of our study was to investigate the pattern of correlation coefficients distribution associated to simple linear relationships linking the compounds structure with their activities. A set of the most common ordnance compounds found at naval facilities with a limited data set with a range of toxicities on aquatic ecosystem and a set of seven properties was studied. Statistically significant models were selected and investigated. The probability density function of the correlation coefficients was investigated using a series of possible continuous distribution laws. Almost 48% of the correlation coefficients proved fit Beta distribution, 40% fit Generalized Pareto distribution, and 12% fit Pert distribution.
A Dynamic Linear Modeling Approach to Public Policy Change
Loftis, Matthew; Mortensen, Peter Bjerre
2017-01-01
Theories of public policy change, despite their differences, converge on one point of strong agreement. The relationship between policy and its causes can and does change over time. This consensus yields numerous empirical implications, but our standard analytical tools are inadequate for testing...... them. As a result, the dynamic and transformative relationships predicted by policy theories have been left largely unexplored in time-series analysis of public policy. This paper introduces dynamic linear modeling (DLM) as a useful statistical tool for exploring time-varying relationships in public...... policy. The paper offers a detailed exposition of the DLM approach and illustrates its usefulness with a time series analysis of U.S. defense policy from 1957-2010. The results point the way for a new attention to dynamics in the policy process and the paper concludes with a discussion of how...
dglars: An R Package to Estimate Sparse Generalized Linear Models
Luigi Augugliaro
2014-09-01
Full Text Available dglars is a publicly available R package that implements the method proposed in Augugliaro, Mineo, and Wit (2013, developed to study the sparse structure of a generalized linear model. This method, called dgLARS, is based on a differential geometrical extension of the least angle regression method proposed in Efron, Hastie, Johnstone, and Tibshirani (2004. The core of the dglars package consists of two algorithms implemented in Fortran 90 to efficiently compute the solution curve: a predictor-corrector algorithm, proposed in Augugliaro et al. (2013, and a cyclic coordinate descent algorithm, proposed in Augugliaro, Mineo, and Wit (2012. The latter algorithm, as shown here, is significantly faster than the predictor-corrector algorithm. For comparison purposes, we have implemented both algorithms.
Effects of the Tsallis distribution in the linear sigma model
Ishihara, Masamichi
2014-01-01
The effects of the Tsallis distribution which has a parameter $q$ on physical quantities are studied using the linear sigma model in chiral phase transitions. The temperature dependences of the condensate and mass for various $q$ are shown, where the Tsallis distribution approaches the Boltzmann-Gibbs distribution as $q$ approaches $1$. The critical temperature and energy density are described with digamma function, and the $q$ dependences of these quantities and the extension of Stefan-Boltzmann limit of the energy density are shown. The following facts are clarified. The chiral symmetry restoration for $q>1$ occurs at low temperature, compared with the restoration for $q=1$. The sigma mass and pion mass reflect the restoration. The critical temperature decreases monotonically as $q$ increases. The small deviation from the Boltzmann-Gibbs distribution results in the large deviations of physical quantities, especially the energy density. It is displayed from the energetic point of view that the small deviatio...
Linear $\\Sigma$ Model in the Gaussian Functional Approximation
Nakamura, I
2001-01-01
We apply a self-consistent relativistic mean-field variational ``Gaussian functional'' (or Hartree) approximation to the linear $\\sigma$ model with spontaneously and explicitly broken chiral O(4) symmetry. We set up the self-consistency, or ``gap'' and the Bethe-Salpeter equations. We check and confirm the chiral Ward-Takahashi identities, among them the Nambu-Goldstone theorem and the (partial) axial current conservation [CAC], both in and away from the chiral limit. With explicit chiral symmetry breaking we confirm the Dashen relation for the pion mass and partial CAC. We solve numerically the gap and Bethe-Salpeter equations, discuss the solutions' properties and the particle content of the theory.
K factor estimation in distribution transformers using linear regression models
Juan Miguel Astorga Gómez
2016-06-01
Full Text Available Background: Due to massive incorporation of electronic equipment to distribution systems, distribution transformers are subject to operation conditions other than the design ones, because of the circulation of harmonic currents. It is necessary to quantify the effect produced by these harmonic currents to determine the capacity of the transformer to withstand these new operating conditions. The K-factor is an indicator that estimates the ability of a transformer to withstand the thermal effects caused by harmonic currents. This article presents a linear regression model to estimate the value of the K-factor, from total current harmonic content obtained with low-cost equipment.Method: Two distribution transformers that feed different loads are studied variables, current total harmonic distortion factor K are recorded, and the regression model that best fits the data field is determined. To select the regression model the coefficient of determination R2 and the Akaike Information Criterion (AIC are used. With the selected model, the K-factor is estimated to actual operating conditions.Results: Once determined the model it was found that for both agricultural cargo and industrial mining, present harmonic content (THDi exceeds the values that these transformers can drive (average of 12.54% and minimum 8,90% in the case of agriculture and average value of 18.53% and a minimum of 6.80%, for industrial mining case.Conclusions: When estimating the K factor using polynomial models it was determined that studied transformers can not withstand the current total harmonic distortion of their current loads. The appropriate K factor for studied transformer should be 4; this allows transformers support the current total harmonic distortion of their respective loads.
Whalley, Lisa K.; Stone, Daniel; Bandy, Brian; Dunmore, Rachel; Hamilton, Jacqueline F.; Hopkins, James; Lee, James D.; Lewis, Alastair C.; Heard, Dwayne E.
2016-02-01
Near-continuous measurements of hydroxyl radical (OH) reactivity in the urban background atmosphere of central London during the summer of 2012 are presented. OH reactivity behaviour is seen to be broadly dependent on air mass origin, with the highest reactivity and the most pronounced diurnal profile observed when air had passed over central London to the east, prior to measurement. Averaged over the entire observation period of 26 days, OH reactivity peaked at ˜ 27 s-1 in the morning, with a minimum of ˜ 15 s-1 during the afternoon. A maximum OH reactivity of 116 s-1 was recorded on one day during morning rush hour. A detailed box model using the Master Chemical Mechanism was used to calculate OH reactivity, and was constrained with an extended measurement data set of volatile organic compounds (VOCs) derived from a gas chromatography flame ionisation detector (GC-FID) and a two-dimensional GC instrument which included heavier molecular weight (up to C12) aliphatic VOCs, oxygenated VOCs and the biogenic VOCs α-pinene and limonene. Comparison was made between observed OH reactivity and modelled OH reactivity using (i) a standard suite of VOC measurements (C2-C8 hydrocarbons and a small selection of oxygenated VOCs) and (ii) a more comprehensive inventory including species up to C12. Modelled reactivities were lower than those measured (by 33 %) when only the reactivity of the standard VOC suite was considered. The difference between measured and modelled reactivity was improved, to within 15 %, if the reactivity of the higher VOCs (⩾ C9) was also considered, with the reactivity of the biogenic compounds of α-pinene and limonene and their oxidation products almost entirely responsible for this improvement. Further improvements in the model's ability to reproduce OH reactivity (to within 6 %) could be achieved if the reactivity and degradation mechanism of unassigned two-dimensional GC peaks were estimated. Neglecting the contribution of the higher VOCs (⩾ C
Modelling of Rough Contact between Linear Viscoelastic Materials
Sergiu Spinu
2017-01-01
Full Text Available The important gradients of stress arising in rough mechanical contacts due to interaction at the asperity level are responsible for damage mechanisms like rolling contact fatigue, wear, or crack propagation. The deterministic approach to this process requires computationally effective numerical solutions, capable of handling very fine meshes that capture the particular features of the investigated contacting surface. The spatial discretization needs to be supported by temporal sampling of the simulation window when time-dependent viscoelastic constitutive laws are considered in the description of the material response. Moreover, when real surface microtopography is considered, steep slopes inevitably lead to localized plastic deformation at the tip of the asperities that are first brought into contact. A computer model for the rough contact of linear viscoelastic materials, capable of handling deterministic contact geometry, complex viscoelastic models, and arbitrary loading histories, is advanced in this paper. Plasticity is considered in a simplified manner that preserves the information regarding the contact area and the pressure distribution without computing the residual strains and stresses. The model is expected to predict the contact behavior of deterministic rough surfaces as resulting from practical engineering applications, thus assisting the design of durable machine elements using elastomers or rubbers.
Bayesian inference for generalized linear models for spiking neurons
Sebastian Gerwinn
2010-05-01
Full Text Available Generalized Linear Models (GLMs are commonly used statistical methods for modelling the relationship between neural population activity and presented stimuli. When the dimension of the parameter space is large, strong regularization has to be used in order to fit GLMs to datasets of realistic size without overfitting. By imposing properly chosen priors over parameters, Bayesian inference provides an effective and principled approach for achieving regularization. Here we show how the posterior distribution over model parameters of GLMs can be approximated by a Gaussian using the Expectation Propagation algorithm. In this way, we obtain an estimate of the posterior mean and posterior covariance, allowing us to calculate Bayesian confidence intervals that characterize the uncertainty about the optimal solution. From the posterior we also obtain a different point estimate, namely the posterior mean as opposed to the commonly used maximum a posteriori estimate. We systematically compare the different inference techniques on simulated as well as on multi-electrode recordings of retinal ganglion cells, and explore the effects of the chosen prior and the performance measure used. We find that good performance can be achieved by choosing an Laplace prior together with the posterior mean estimate.
Linear and nonlinear viscoelastic arterial wall models: application on animals
Ghigo, Arthur; Armentano, Ricardo; Lagrée, Pierre-Yves; Fullana, Jose-Maria
2016-01-01
This work deals with the viscoelasticity of the arterial wall and its influence on the pulse waves. We describe the viscoelasticity by a non-linear Kelvin-Voigt model in which the coefficients are fitted using experimental time series of pressure and radius measured on a sheep's arterial network. We obtained a good agreement between the results of the nonlinear Kelvin-Voigt model and the experimental measurements. We found that the viscoelastic relaxation time-defined by the ratio between the viscoelastic coefficient and the Young's modulus-is nearly constant throughout the network. Therefore, as it is well known that smaller arteries are stiffer, the viscoelastic coefficient rises when approaching the peripheral sites to compensate the rise of the Young's modulus, resulting in a higher damping effect. We incorporated the fitted viscoelastic coefficients in a nonlinear 1D fluid model to compute the pulse waves in the network. The damping effect of viscoelasticity on the high frequency waves is clear especiall...
Non-linear Constitutive Model for the Oligocarbonate Polyurethane Material
Marek Pawlikowski
2014-01-01
The polyurethane,which was the subject of the constitutive research presented in the paper,was based on oligocarbonate diols Desmophen C2100 produced by Bayer@.The constitutive modelling was performed with a view to applying the material as the inlay of intervertebral disc prostheses.The polyurethane was assumed to be non-linearly viscohyperelastic,isotropic and incompressible.The constitutive equation was derived from the postulated strain energy function.The elastic and rheological constants were identified on the basis of experimental tests,i.e.relaxation tests and monotonic uniaxial tests at two different strain rates,i.e.λ =0.1 min-1 and λ =1.0 min-1.The stiffness tensor was derived and introduced to Abaqus@finite element (FE) software in order to numerically validate the constitutive model.The results of the constants identification and numerical implementation show that the derived constitutive equation is fully adequate to model stress-strain behavior of the polyurethane material.
Identification of an Equivalent Linear Model for a Non-Linear Time-Variant RC-Structure
Kirkegaard, Poul Henning; Andersen, P.; Brincker, Rune
are investigated and compared with ARMAX models used on a running window. The techniques are evaluated using simulated data generated by the non-linear finite element program SARCOF modeling a 10-storey 3-bay concrete structure subjected to amplitude modulated Gaussian white noise filtered through a Kanai...
Verma, Dinkar, E-mail: dinkar@iitk.ac.in [Nuclear Engineering and Technology Program, Indian Institute of Technology Kanpur, Kanpur 208 016 (India); Kalra, Manjeet Singh, E-mail: drmanjeet.singh@dituniversity.edu.in [DIT University, Dehradun 248 009 (India); Wahi, Pankaj, E-mail: wahi@iitk.ac.in [Department of Mechanical Engineering, Indian Institute of Technology Kanpur, Kanpur 208 016 (India)
2017-04-15
Highlights: • A simplified model with nonlinear void reactivity feedback is studied. • Method of multiple scales for nonlinear analysis and oscillation characteristics. • Second order void reactivity dominates in determining system dynamics. • Opposing signs of linear and quadratic void reactivity enhances global safety. - Abstract: In the present work, the effect of nonlinear void reactivity on the dynamics of a simplified lumped-parameter model for a boiling water reactor (BWR) is investigated. A mathematical model of five differential equations comprising of neutronics and thermal-hydraulics encompassing the nonlinearities associated with both the reactivity feedbacks and the heat transfer process has been used. To this end, we have considered parameters relevant to RBMK for which the void reactivity is known to be nonlinear. A nonlinear analysis of the model exploiting the method of multiple time scales (MMTS) predicts the occurrence of the two types of Hopf bifurcation, namely subcritical and supercritical, leading to the evolution of limit cycles for a range of parameters. Numerical simulations have been performed to verify the analytical results obtained by MMTS. The study shows that the nonlinear reactivity has a significant influence on the system dynamics. A parametric study with varying nominal reactor power and operating conditions in coolant channel has also been performed which shows the effect of change in concerned parameter on the boundary between regions of sub- and super-critical Hopf bifurcations in the space constituted by the two coefficients of reactivities viz. the void and the Doppler coefficient of reactivities. In particular, we find that introduction of a negative quadratic term in the void reactivity feedback significantly increases the supercritical region and dominates in determining the system dynamics.
a Linear Model for Meandering Rivers with Arbitrarily Varying Width
Frascati, A.; Lanzoni, S.
2011-12-01
Alluvial rivers usually exhibit quite complex planforms, characterized by a wide variety of alternating bends, that have attracted the interest of a large number of researchers. Much less attention has been paid to another striking feature observed in alluvial rivers, namely the relatively regular spatial variations attained by the channel width. Actively meandering channels, in fact, generally undergo spatial oscillations systematically correlated with channel curvature, with cross sections wider at bends than at crossings. Some other streams have been observed to exhibit irregular width variations. Conversely, rivers flowing in highly vegetated flood plains, i.e. canaliform rivers, may exhibit an opposite behavior, owing to the combined effects of bank erodibility and floodplain depositional processes which, in turn, are strictly linked to vegetation cover. Similarly to streamline curvatures induced by bends, the presence of along channel width variations may have remarkable effects on the flow field and sediment dynamics and, thereby, on the equilibrium river bed configuration. In particular, spatial distribution of channel curvature typically determines the formation of a rhythmic bar-pool pattern in the channel bed strictly associated with the development of river meanders. Channel width variations are on the contrary characterized by a sequence of narrowing, yielding a central scour, alternated to the downstream development of a widening associated with the formation of a central bar. Here we present a morphodynamic model that predict at a linear level the spatial distribution of the flow field and the equilibrium bed configuration of an alluvial river characterized by arbitrary along channel distributions of both the channel axis curvature and the channel width. The mathematical model is averaged over the depth and describes the steady, non-uniform flow and sediment transport in sinuous channels with a noncohesive bed. The governing two-dimensional equations
Optimizing Biorefinery Design and Operations via Linear Programming Models
Talmadge, Michael; Batan, Liaw; Lamers, Patrick; Hartley, Damon; Biddy, Mary; Tao, Ling; Tan, Eric
2017-03-28
The ability to assess and optimize economics of biomass resource utilization for the production of fuels, chemicals and power is essential for the ultimate success of a bioenergy industry. The team of authors, consisting of members from the National Renewable Energy Laboratory (NREL) and the Idaho National Laboratory (INL), has developed simple biorefinery linear programming (LP) models to enable the optimization of theoretical or existing biorefineries. The goal of this analysis is to demonstrate how such models can benefit the developing biorefining industry. It focuses on a theoretical multi-pathway, thermochemical biorefinery configuration and demonstrates how the biorefinery can use LP models for operations planning and optimization in comparable ways to the petroleum refining industry. Using LP modeling tools developed under U.S. Department of Energy's Bioenergy Technologies Office (DOE-BETO) funded efforts, the authors investigate optimization challenges for the theoretical biorefineries such as (1) optimal feedstock slate based on available biomass and prices, (2) breakeven price analysis for available feedstocks, (3) impact analysis for changes in feedstock costs and product prices, (4) optimal biorefinery operations during unit shutdowns / turnarounds, and (5) incentives for increased processing capacity. These biorefinery examples are comparable to crude oil purchasing and operational optimization studies that petroleum refiners perform routinely using LPs and other optimization models. It is important to note that the analyses presented in this article are strictly theoretical and they are not based on current energy market prices. The pricing structure assigned for this demonstrative analysis is consistent with $4 per gallon gasoline, which clearly assumes an economic environment that would favor the construction and operation of biorefineries. The analysis approach and examples provide valuable insights into the usefulness of analysis tools for
On the relation between the linear factor model and the latent profile model
Halpin, P.F.; Dolan, C.V.; Grasman, R.P.P.P.; de Boeck, P.
2011-01-01
The relationship between linear factor models and latent profile models is addressed within the context of maximum likelihood estimation based on the joint distribution of the manifest variables. Although the two models are well known to imply equivalent covariance decompositions, in general they do
On the Relation between the Linear Factor Model and the Latent Profile Model
Halpin, Peter F.; Dolan, Conor V.; Grasman, Raoul P. P. P.; De Boeck, Paul
2011-01-01
The relationship between linear factor models and latent profile models is addressed within the context of maximum likelihood estimation based on the joint distribution of the manifest variables. Although the two models are well known to imply equivalent covariance decompositions, in general they do not yield equivalent estimates of the…
Linear models for sound from supersonic reacting mixing layers
Chary, P. Shivakanth; Samanta, Arnab
2016-12-01
We perform a linearized reduced-order modeling of the aeroacoustic sound sources in supersonic reacting mixing layers to explore their sensitivities to some of the flow parameters in radiating sound. Specifically, we investigate the role of outer modes as the effective flow compressibility is raised, when some of these are expected to dominate over the traditional Kelvin-Helmholtz (K-H) -type central mode. Although the outer modes are known to be of lesser importance in the near-field mixing, how these radiate to the far-field is uncertain, on which we focus. On keeping the flow compressibility fixed, the outer modes are realized via biasing the respective mean densities of the fast (oxidizer) or slow (fuel) side. Here the mean flows are laminar solutions of two-dimensional compressible boundary layers with an imposed composite (turbulent) spreading rate, which we show to significantly alter the growth of instability waves by saturating them earlier, similar to in nonlinear calculations, achieved here via solving the linear parabolized stability equations. As the flow parameters are varied, instability of the slow modes is shown to be more sensitive to heat release, potentially exceeding equivalent central modes, as these modes yield relatively compact sound sources with lesser spreading of the mixing layer, when compared to the corresponding fast modes. In contrast, the radiated sound seems to be relatively unaffected when the mixture equivalence ratio is varied, except for a lean mixture which is shown to yield a pronounced effect on the slow mode radiation by reducing its modal growth.
Linear System Models for Ultrasonic Imaging: Application to Signal Statistics
Zemp, Roger J.; Abbey, Craig K.; Insana, Michael F.
2009-01-01
Linear equations for modeling echo signals from shift-variant systems forming ultrasonic B-mode, Doppler, and strain images are analyzed and extended. The approach is based on a solution to the homogeneous wave equation for random inhomogeneous media. When the system is shift-variant, the spatial sensitivity function—defined as a spatial weighting function that determines the scattering volume for a fixed point of time—has advantages over the point-spread function traditionally used to analyze ultrasound systems. Spatial sensitivity functions are necessary for determining statistical moments in the context of rigorous image quality assessment, and they are time-reversed copies of point-spread functions for shift variant systems. A criterion is proposed to assess the validity of a local shift-invariance assumption. The analysis reveals realistic situations in which in-phase signals are correlated to the corresponding quadrature signals, which has strong implications for assessing lesion detectability. Also revealed is an opportunity to enhance near- and far-field spatial resolution by matched filtering unfocused beams. The analysis connects several well-known approaches to modeling ultrasonic echo signals. PMID:12839176
Convergence results for a coarsening model using global linearization
Gallay, T; Gallay, Th.
2002-01-01
We study a coarsening model describing the dynamics of interfaces in the one-dimensional Allen-Cahn equation. Given a partition of the real line into intervals of length greater than one, the model consists in constantly eliminating the shortest interval of the partition by merging it with its two neighbors. We show that the mean-field equation for the time-dependent distribution of interval lengths can be explicitly solved using a global linearization transformation. This allows us to derive rigorous results on the long-time asymptotics of the solutions. If the average length of the intervals is finite, we prove that all distributions approach a uniquely determined self-similar solution. We also obtain global stability results for the family of self-similar profiles which correspond to distributions with infinite expectation. eliminating the shortest interval of the partition by merging it with its two neighbors. We show that the mean-field equation for the time-dependent distribution of interval lengths can...
Generalized Functional Linear Models With Semiparametric Single-Index Interactions
Li, Yehua
2010-06-01
We introduce a new class of functional generalized linear models, where the response is a scalar and some of the covariates are functional. We assume that the response depends on multiple covariates, a finite number of latent features in the functional predictor, and interaction between the two. To achieve parsimony, the interaction between the multiple covariates and the functional predictor is modeled semiparametrically with a single-index structure. We propose a two step estimation procedure based on local estimating equations, and investigate two situations: (a) when the basis functions are pre-determined, e.g., Fourier or wavelet basis functions and the functional features of interest are known; and (b) when the basis functions are data driven, such as with functional principal components. Asymptotic properties are developed. Notably, we show that when the functional features are data driven, the parameter estimates have an increased asymptotic variance, due to the estimation error of the basis functions. Our methods are illustrated with a simulation study and applied to an empirical data set, where a previously unknown interaction is detected. Technical proofs of our theoretical results are provided in the online supplemental materials.
Linear Programming Graphic Method Modelling%Linear Programming图解法建模研讨
宋占奎
2010-01-01
对仅有两个变量的Linear Programming,通过图解法求最优解.建立了数学模型并求得了最优解.从图解法可以直观地看出,仅有两个变量的Linear Programming的解有唯一最优解、无穷多个最优解、无界解和无可行解四种情况.若其有最优解,则必定会在其顶点上得到;若在多个顶点上得到最优解,则其有无穷多个最优解.
朱文强
2011-01-01
无功补偿优化规划在配电网规划设计中主要考虑的优化目标网损最小、投资最省、综合经济效益最大等。对不同的目标，采用不同的无功配置规划。文中建立了针对配电网络的线性规划求解法的数学模型，以综合经济效益最大为目标函数，以无功平衡、电压为约束条件，结合无功潮流的最优化，计算出运行参数后通过多次迭代计算可获得最佳无功优化。%As the optimization of reactive power compensation plays a key role in planning and design of the distribution network, the chief considerations of optimization targets are the minimum transmission loss ,the minimum investment and the maximum overall economic efficiency, adopting different reactive configuration planning according to different targets. A mathematical model is built in accordance with linear programming method of distribution network. It makes the maximum overall economic efficiency as the objective function, takes reactive power balance and voltage qualification as constraints and combines the optimization of reactive power flow. Through repeatedly using the iterative method after calculating the operating parameters, we obtain reactive power optimization.
Linear regression model selection using p-values when the model dimension grows
Pokarowski, Piotr; Teisseyre, Paweł
2012-01-01
We consider a new criterion-based approach to model selection in linear regression. Properties of selection criteria based on p-values of a likelihood ratio statistic are studied for families of linear regression models. We prove that such procedures are consistent i.e. the minimal true model is chosen with probability tending to 1 even when the number of models under consideration slowly increases with a sample size. The simulation study indicates that introduced methods perform promisingly when compared with Akaike and Bayesian Information Criteria.
Kooths, Stefan; Mitze, Timo Friedel; Ringhut, Eric
2004-01-01
This paper compares the predictive power of linear econometric and non-linear computational models for forecasting the inflation rate in the European Monetary Union (EMU). Various models of both types are developed using different monetary and real activity indicators. They are compared according...... to a battery of parametric and non-parametric test statistics to measure their performance in one- and four-step ahead forecasts of quarterly data. Using genetic-neural fuzzy systems we find the computational approach superior to some degree and show how to combine both techniques successfully....
Model-Based Testing of a Reactive System with Coloured Petri Nets
Tjell, Simon
2006-01-01
In this paper, a reactive and nondeterministic system is tested. This is doneby applying a generic model that has been specified as a configurable Coloured PetriNet. In this way, model-based testing is possible for a wide class of reactive system atthe level of discrete events. Concurrently...... executed tasks are specified at a high levelof abstraction and test traces are collected through state space analysis of the model....
Formal modeling and verification of fractional order linear systems.
Zhao, Chunna; Shi, Likun; Guan, Yong; Li, Xiaojuan; Shi, Zhiping
2016-05-01
This paper presents a formalization of a fractional order linear system in a higher-order logic (HOL) theorem proving system. Based on the formalization of the Grünwald-Letnikov (GL) definition, we formally specify and verify the linear and superposition properties of fractional order systems. The proof provides a rigor and solid underpinnings for verifying concrete fractional order linear control systems. Our implementation in HOL demonstrates the effectiveness of our approach in practical applications.
Michoud, Vincent; Locoge, Nadine; Dusanter, Sébastien
2015-04-01
The Hydroxyl radical (OH) is the main daytime oxidant in the troposphere, leading to the oxidation of Volatile Organic Compounds (VOCs) and the formation of harmful pollutants such as ozone (O3) and Secondary Organic Aerosols (SOA). While OH plays a key role in tropospheric chemistry, recent studies have highlighted that there are still uncertainties associated with the OH budget, i.e the identification of sources and sinks and the quantification of production and loss rates of this radical. It has been demonstrated that ambient measurements of the total OH loss rate (also called total OH reactivity) can be used to identify and reduce these uncertainties. In this context, the Comparative Reactivity Method (CRM), developed by Sinha et al. (ACP, 2008), is a promising technique to measure total OH reactivity in ambient air and has already been used during several field campaigns. This technique relies on monitoring competitive reactions of OH with ambient trace gases and a reference compound (pyrrole) in a sampling reactor to derive ambient OH reactivity. However, this technique requires a complex data processing chain that has yet to be carefully investigated in the laboratory. In this study, we present a detailed characterization of a CRM instrument developed at Mines Douai, France. Experiments have been performed to investigate the dependence of the CRM response on humidity, ambient NOx levels, and the pyrrole-to-OH ratio inside the sampling reactor. Box modelling of the chemistry occurring in the reactor has also been performed to assess our theoretical understanding of the CRM measurement. This work shows that the CRM response is sensitive to both humidity and NOx, which can be accounted for during data processing using parameterizations depending on the pyrrole-to-OH ratio. The agreement observed between laboratory studies and model results suggests a good understanding of the chemistry occurring in the sampling reactor and gives confidence in the CRM
Reactive Transport Modeling and Geophysical Monitoring of Bioclogging at Reservoir Scale
Surasani, V.; Commer, M.; Ajo Franklin, J. B.; Li, L.; Hubbard, S. S.
2012-12-01
In Microbial-Enhanced-Hydrocarbon-Recovery (MEHR), preferential bioclogging targets the growth of the biofilms (def. immobilized biopolymers with active cells embodied in it) in highly permeable thief zones to enhance sweep efficiency in oil reservoirs. During MEHR, understanding and controlling bioclogging is hindered by the lack of advanced modeling and monitoring tools; these deficiencies contribute to suboptimal performance. Our focus in this study was on developing a systematic approach to understand and monitor bioclogging at the reservoir scale using a combination of reactive transport modeling and geophysical imaging tools (EM & seismic). In this study, we created a realistic reservoir model from a heterogeneous gas reservoir in the Southern Sacramento basin, California; the model well (Citizen Green #1) was characterized using sonic, electrical, nuclear, and NMR logs for hydrologic and geophysical properties. From the simplified 2D log data model, a strip of size 150m x75m with several high permeability streaks is identified for bioclogging simulation experiments. From the NMR log data it is observed that a good linear correlation exist between logarithmic permeability (0.55- 3.34 log (mD)) versus porosity (0.041-0.28). L. mesenteroides was chosen as the model bacteria. In the presence of sucrose, it enzymatically catalyzes the production of dextran, a useful bioclogging agent. Using microbial kinetics from our laboratory experiment and reservoir heterogeneity, a reactive transport model (RTM) is established for two kinds of bioclogging treatments based on whether microbes are present in situ or are supplied externally. In both cases, sucrose media (1.5 M) is injected at the rate of 1 liter/s for 20 days into the center of high permeable strip to stimulate microbes. Simulations show that the high dextran production was deep into the formation from the injection well. This phenomenon can be explained precisely with bacterial kinetics and injection rate. In
Seyed Abolghasem Mortazavi
2014-03-01
Full Text Available Water resources sustainability is one of the major issues in the agricultural sustainability. In this study sustainability of water resources has been investigated by use of linear and non-linear models in six models based on optimal utilization of water resources in the north parts farms of Iran because of incorrect use of agricultural water resources, from 2011 to 2012. Also “gross margin per a unit of water consumption” and “employment per a unit of water consumption” are used as indicators for assessing the sustainability of cropping patterns. The results show that cropping pattern of fractional goal programming (FGP model has been near to current situation and has shown realistic conditions according to expertise and advantage of this area in cultivation of certain crops. So the FGP model has desirability in each of indicators than other five models.
Modeling of flow and reactive transport in IPARS
Wheeler, Mary Fanett
2012-03-11
In this work, we describe a number of efficient and locally conservative methods for subsurface flow and reactive transport that have been or are currently being implemented in the IPARS (Integrated Parallel and Accurate Reservoir Simulator). For flow problems, we consider discontinuous Galerkin (DG) methods and mortar mixed finite element methods. For transport problems, we employ discontinuous Galerkin methods and Godunov-mixed methods. For efficient treatment of reactive transport simulations, we present a number of state-of-the-art dynamic mesh adaptation strategies and implementations. Operator splitting approaches and iterative coupling techniques are also discussed. Finally, numerical examples are provided to illustrate the capability of IPARS to treat general biogeochemistry as well as the effectivity of mesh adaptations with DG for transport. © 2012 Bentham Science Publishers. All rights reserved.
Parameter estimation and hypothesis testing in linear models
Koch, Karl-Rudolf
1999-01-01
The necessity to publish the second edition of this book arose when its third German edition had just been published. This second English edition is there fore a translation of the third German edition of Parameter Estimation and Hypothesis Testing in Linear Models, published in 1997. It differs from the first English edition by the addition of a new chapter on robust estimation of parameters and the deletion of the section on discriminant analysis, which has been more completely dealt with by the author in the book Bayesian In ference with Geodetic Applications, Springer-Verlag, Berlin Heidelberg New York, 1990. Smaller additions and deletions have been incorporated, to im prove the text, to point out new developments or to eliminate errors which became apparent. A few examples have been also added. I thank Springer-Verlag for publishing this second edition and for the assistance in checking the translation, although the responsibility of errors remains with the author. I also want to express my thanks...
Linear Growth of Structure in the Symmetron Model
Brax, Philippe; Davis, Anne-Christine; Li, Baojiu; Schmauch, Benoit; Shaw, Douglas J
2011-01-01
In the symmetron mechanism, the fifth force mediated by a coupled scalar field (the symmetron) is suppressed in high-density regions due to the restoration of symmetry in the symmetron potential. In this paper we study the background cosmology and large scale structure formation in the linear perturbation regime of the symmetron model. Analytic solutions to the symmetron in the cosmological background are found, which agree well with numerical results. We discuss the effect of the symmetron perturbation on the growth of matter perturbation, in particular the implications of the brief period of tachyonic instability caused by the negative mass squared of the symmetron during symmetry breaking. Our analysis and numerical results show that this instability has only very small effects on the growth of structures on sub-horizon scales, and even at horizon scales its influence is not as drastic as naively expected. The symmetron fifth force in the non-tachyonic regime does affect the formation of structure in a non...
Sampled-data models for linear and nonlinear systems
Yuz, Juan I
2014-01-01
Sampled-data Models for Linear and Nonlinear Systems provides a fresh new look at a subject with which many researchers may think themselves familiar. Rather than emphasising the differences between sampled-data and continuous-time systems, the authors proceed from the premise that, with modern sampling rates being as high as they are, it is becoming more appropriate to emphasise connections and similarities. The text is driven by three motives: · the ubiquity of computers in modern control and signal-processing equipment means that sampling of systems that really evolve continuously is unavoidable; · although superficially straightforward, sampling can easily produce erroneous results when not treated properly; and · the need for a thorough understanding of many aspects of sampling among researchers and engineers dealing with applications to which they are central. The authors tackle many misconceptions which, although appearing reasonable at first sight, are in fact either p...
Piecewise linear models for the quasiperiodic transition to chaos
Campbell, D K; Tresser, C; Uherka, D J; Campbell, David K; Galeeva, Roza; Tresser, Charles; Uherka, David J
1995-01-01
We formulate and study analytically and computationally two families of piecewise linear degree one circle maps. These families offer the rare advantage of being non-trivial but essentially solvable models for the phenomenon of mode-locking and the quasi-periodic transition to chaos. For instance, for these families, we obtain complete solutions to several questions still largely unanswered for families of smooth circle maps. Our main results describe (1) the sets of maps in these families having some prescribed rotation interval; (2) the boundaries between zero and positive topological entropy and between zero length and non-zero length rotation interval; and (3) the structure and bifurcations of the attractors in one of these families. We discuss the interpretation of these maps as low-order spline approximations to the classic ``sine-circle'' map and examine more generally the implications of our results for the case of smooth circle maps. We also mention a possible connection to recent experiments on mode...
Investigating follow-up outcome change using hierarchical linear modeling.
Ogrodniczuk, J S; Piper, W E; Joyce, A S
2001-03-01
Individual change in outcome during a one-year follow-up period for 98 patients who received either interpretive or supportive psychotherapy was examined using hierarchical linear modeling (HLM). This followed a previous study that had investigated average (treatment condition) change during follow-up using traditional methods of data analysis (repeated measures ANOVA, chi-square tests). We also investigated whether two patient personality characteristics-quality of object relations (QOR) and psychological mindedness (PM)-predicted individual change. HLM procedures yielded findings that were not detected using traditional methods of data analysis. New findings indicated that the rate of individual change in outcome during follow-up varied significantly among the patients. QOR was directly related to favorable individual change for supportive therapy patients, but not for patients who received interpretive therapy. The findings have implications for determining which patients will show long-term benefit following short-term supportive therapy and how to enhance it. The study also found significant associations between QOR and final outcome level.
Generalized linear model for estimation of missing daily rainfall data
Rahman, Nurul Aishah; Deni, Sayang Mohd; Ramli, Norazan Mohamed
2017-04-01
The analysis of rainfall data with no missingness is vital in various applications including climatological, hydrological and meteorological study. The issue of missing data is a serious concern since it could introduce bias and lead to misleading conclusions. In this study, five imputation methods including simple arithmetic average, normal ratio method, inverse distance weighting method, correlation coefficient weighting method and geographical coordinate were used to estimate the missing data. However, these imputation methods ignored the seasonality in rainfall dataset which could give more reliable estimation. Thus this study is aimed to estimate the missingness in daily rainfall data by using generalized linear model with gamma and Fourier series as the link function and smoothing technique, respectively. Forty years daily rainfall data for the period from 1975 until 2014 which consists of seven stations at Kelantan region were selected for the analysis. The findings indicated that the imputation methods could provide more accurate estimation values based on the least mean absolute error, root mean squared error and coefficient of variation root mean squared error when seasonality in the dataset are considered.
Statistical Modelling of Cardiovascular Data. An Introduction to Linear Mixed Models
Gonçalves, Paulo; Lenoir, Christophe; Heymes, Christophe; Swynghedauw, Bernard; Lavergne, Christian
2005-01-01
Most of statistical approaches in cardiovascular research were based on variance analysis (ANOVA). However, most of the time, the assumption that data are independent is violated since several measures are performed on the same subject (repeated measures). In addition, the presence of intra- and inter-observers variability can potentially obscure significant differences. The linear mixed model (LMM) is an extended multivariate linear regression method of analysis that accounts for both fixed ...
Modeling the dynamics of Plasmodium vivax infection and hypnozoite reactivation in vivo.
Adeshina I Adekunle
2015-03-01
Full Text Available The dynamics of Plasmodium vivax infection is characterized by reactivation of hypnozoites at varying time intervals. The relative contribution of new P. vivax infection and reactivation of dormant liver stage hypnozoites to initiation of blood stage infection is unclear. In this study, we investigate the contribution of new inoculations of P. vivax sporozoites to primary infection versus reactivation of hypnozoites by modeling the dynamics of P. vivax infection in Thailand in patients receiving treatment for either blood stage infection alone (chloroquine, or the blood and liver stages of infection (chloroquine + primaquine. In addition, we also analysed rates of infection in a study in Papua New Guinea (PNG where patients were treated with either artesunate, or artesunate + primaquine. Our results show that up to 96% of the P. vivax infection is due to hypnozoite reactivation in individuals living in endemic areas in Thailand. Similar analysis revealed the around 70% of infections in the PNG cohort were due to hypnozoite reactivation. We show how the age of the cohort, primaquine drug failure, and seasonality may affect estimates of the ratio of primary P. vivax infection to hypnozoite reactivation. Modeling of P. vivax primary infection and hypnozoite reactivation provides important insights into infection dynamics, and suggests that 90-96% of blood stage infections arise from hypnozoite reactivation. Major differences in infection kinetics between Thailand and PNG suggest the likelihood of drug failure in PNG.
PEIXOTO F. C.
1999-01-01
Full Text Available Fragmentation kinetics is employed to model a continuous reactive mixture. An explicit solution is found and experimental data on the catalytic cracking of a mixture of alkanes are used for deactivation and kinetic parameter estimation.
Honsberger, Michael J; Taylor, Jane R; Corlett, Philip R
2015-05-01
Sub-anesthetic doses of the NMDA antagonist ketamine have been shown to model the formation and stability of delusion in human subjects. The latter has been predicted to be due to aberrant prediction error resulting in enhanced destabilization of beliefs. To extend the scope of this model, we investigated the effect of administration of low dose systemic ketamine on memory in a rodent model of memory reconsolidation. Systemic ketamine was administered either prior to or immediately following auditory fear memory reactivation in rats. Memory strength was assessed by measuring freezing behavior 24h later. Follow up experiments were designed to investigate an effect of pre-reactivation ketamine on short-term memory (STM), closely related memories, and basolateral amygdala (BLA) specific destabilization mechanisms. Rats given pre-reactivation, but not post-reactivation, ketamine showed larger freezing responses 24h later compared to vehicle. This enhancement was not observed 3h after the memory reactivation, nor was it seen in a closely related contextual memory. Prior inhibition of a known destabilization mechanism in the BLA blocked the effect of pre-reactivation ketamine. Pre- but not post-reactivation ketamine enhances fear memory. These data together with recent data in human subjects supports a model of delusion fixity that proposes that aberrant prediction errors result in enhanced destabilization and strengthening of delusional belief. Copyright © 2015 Elsevier B.V. All rights reserved.
Modelling and Inverse-Modelling: Experiences with O.D.E. Linear Systems in Engineering Courses
Martinez-Luaces, Victor
2009-01-01
In engineering careers courses, differential equations are widely used to solve problems concerned with modelling. In particular, ordinary differential equations (O.D.E.) linear systems appear regularly in Chemical Engineering, Food Technology Engineering and Environmental Engineering courses, due to the usefulness in modelling chemical kinetics,…
The Modeling and Simulation of Reactive Distillation for the Esterification Process
朱建华; 沈复
2003-01-01
In this paper,a generalized model of the reactive distillation processes was developed via rate-based approach. The homotopy-continuation method was employed to solve the complicated nonlinear model equations efficiently. The simulation on the reactive distillation processes was carried out with the profiles of stage temperature,composition and flow rate for both vapor and liquid phases obtained. Based on careful analysis of the simulation results, the pitfalls in experimental design were detected. Finally, a software package for the simulation of reactive distillation processes was developed.
Expanding the role of reactive transport models in critical zone processes
Li, Li; Maher, Kate; Navarre-Sitchler, Alexis; Druhan, Jennifer; Meile, Christof; Lawrence, Corey; Moore, Joel; Perdrial, Julia; Sullivan, Pamela; Thompson, Aaron; Jin, Lixin; Bolton, Edward W.; Brantley, Susan L.; Dietrich, William E.; Mayer, K. Ulrich; Steefel, Carl; Valocchi, Albert J.; Zachara, John M.; Kocar, Benjamin D.; McIntosh, Jennifer; Tutolo, Benjamin M.; Kumar, Mukesh; Sonnenthal, Eric; Bao, Chen; Beisman, Joe
2017-01-01
Models test our understanding of processes and can reach beyond the spatial and temporal scales of measurements. Multi-component Reactive Transport Models (RTMs), initially developed more than three decades ago, have been used extensively to explore the interactions of geothermal, hydrologic, geochemical, and geobiological processes in subsurface systems. Driven by extensive data sets now available from intensive measurement efforts, there is a pressing need to couple RTMs with other community models to explore non-linear interactions among the atmosphere, hydrosphere, biosphere, and geosphere. Here we briefly review the history of RTM development, summarize the current state of RTM approaches, and identify new research directions, opportunities, and infrastructure needs to broaden the use of RTMs. In particular, we envision the expanded use of RTMs in advancing process understanding in the Critical Zone, the veneer of the Earth that extends from the top of vegetation to the bottom of groundwater. We argue that, although parsimonious models are essential at larger scales, process-based models offer tools to explore the highly nonlinear coupling that characterizes natural systems. We present seven testable hypotheses that emphasize the unique capabilities of process-based RTMs for (1) elucidating chemical weathering and its physical and biogeochemical drivers; (2) understanding the interactions among roots, micro-organisms, carbon, water, and minerals in the rhizosphere; (3) assessing the effects of heterogeneity across spatial and temporal scales; and (4) integrating the vast quantity of novel data, including “omics” data (genomics, transcriptomics, proteomics, metabolomics), elemental concentration and speciation data, and isotope data into our understanding of complex earth surface systems. With strong support from data-driven sciences, we are now in an exciting era where integration of RTM framework into other community models will facilitate process
A general and simple method for obtaining R2 from generalized linear mixed‐effects models
Nakagawa, Shinichi; Schielzeth, Holger; O'Hara, Robert B
2013-01-01
The use of both linear and generalized linear mixed‐effects models ( LMM s and GLMM s) has become popular not only in social and medical sciences, but also in biological sciences, especially in the field of ecology and evolution...
Grajeda, Laura M; Ivanescu, Andrada; Saito, Mayuko; Crainiceanu, Ciprian; Jaganath, Devan; Gilman, Robert H; Crabtree, Jean E; Kelleher, Dermott; Cabrera, Lilia; Cama, Vitaliano; Checkley, William
2016-01-01
Childhood growth is a cornerstone of pediatric research. Statistical models need to consider individual trajectories to adequately describe growth outcomes. Specifically, well-defined longitudinal models are essential to characterize both population and subject-specific growth. Linear mixed-effect models with cubic regression splines can account for the nonlinearity of growth curves and provide reasonable estimators of population and subject-specific growth, velocity and acceleration. We provide a stepwise approach that builds from simple to complex models, and account for the intrinsic complexity of the data. We start with standard cubic splines regression models and build up to a model that includes subject-specific random intercepts and slopes and residual autocorrelation. We then compared cubic regression splines vis-à-vis linear piecewise splines, and with varying number of knots and positions. Statistical code is provided to ensure reproducibility and improve dissemination of methods. Models are applied to longitudinal height measurements in a cohort of 215 Peruvian children followed from birth until their fourth year of life. Unexplained variability, as measured by the variance of the regression model, was reduced from 7.34 when using ordinary least squares to 0.81 (p linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p linear regression equation for both estimation and prediction of population- and individual-level growth in height. We show that cubic regression splines are superior to linear regression splines for the case of a small number of knots in both estimation and prediction with the full linear mixed effect model (AIC 19,352 vs. 19,598, respectively). While the regression parameters are more complex to interpret in the former, we argue that inference for any problem depends more on the estimated curve or differences in curves rather
A Generalised Concept of Dominance in Linear Programming Models
Drynan, Ross G.
1987-01-01
The notion of dominance most familiar to agricultural economists is perhaps the decision theoretic concept entailed in comparing one risky prospect to others. But dominance concepts are also relevant in the linear programming context, for example in identifying redundant constraints. In this note, the standard concept of dominance in linear programming is generalized by defining dominance with respect to differing levels of information about the programming problem.
Developing ontological model of computational linear algebra - preliminary considerations
Wasielewska, K.; Ganzha, M.; Paprzycki, M.; Lirkov, I.
2013-10-01
The aim of this paper is to propose a method for application of ontologically represented domain knowledge to support Grid users. The work is presented in the context provided by the Agents in Grid system, which aims at development of an agent-semantic infrastructure for efficient resource management in the Grid. Decision support within the system should provide functionality beyond the existing Grid middleware, specifically, help the user to choose optimal algorithm and/or resource to solve a problem from a given domain. The system assists the user in at least two situations. First, for users without in-depth knowledge about the domain, it should help them to select the method and the resource that (together) would best fit the problem to be solved (and match the available resources). Second, if the user explicitly indicates the method and the resource configuration, it should "verify" if her choice is consistent with the expert recommendations (encapsulated in the knowledge base). Furthermore, one of the goals is to simplify the use of the selected resource to execute the job; i.e., provide a user-friendly method of submitting jobs, without required technical knowledge about the Grid middleware. To achieve the mentioned goals, an adaptable method of expert knowledge representation for the decision support system has to be implemented. The selected approach is to utilize ontologies and semantic data processing, supported by multicriterial decision making. As a starting point, an area of computational linear algebra was selected to be modeled, however, the paper presents a general approach that shall be easily extendable to other domains.
A log-linear multidimensional Rasch model for capture-recapture.
Pelle, E; Hessen, D J; van der Heijden, P G M
2016-02-20
In this paper, a log-linear multidimensional Rasch model is proposed for capture-recapture analysis of registration data. In the model, heterogeneity of capture probabilities is taken into account, and registrations are viewed as dichotomously scored indicators of one or more latent variables that can account for correlations among registrations. It is shown how the probability of a generic capture profile is expressed under the log-linear multidimensional Rasch model and how the parameters of the traditional log-linear model are derived from those of the log-linear multidimensional Rasch model. Finally, an application of the model to neural tube defects data is presented.
Cogo, Joao Roberto [Escola Federal de Engenharia de Itajuba, MG (Brazil)
1994-12-31
The non linear electrical loads can give rise to a number of disturbances in electrical power networks. Among them, the high consumption of relative power is to be noted and so is the several harmonic components which may be injected in the industry system and very often in the utility system. So, by using appropriate technical considerations, as well as measurements in typical special electrical loads, such negative effects are analyzed and ways of minimizing them are suggested. (author) 3 refs., 11 figs., 6 tabs.
Shengqiang Wang
2012-06-01
Full Text Available This paper presents a new reactive adsorbent used to effectively remove 4,6-dimethyldibenzothiophene (4,6-DMDBT from model transportation diesel fuels. This reactive adsorbent was composed of formaldehyde, phosphotungstic acid and mesoporous silica gel. The experiment was based on an assumed condensation reaction of 4,6-DMDBT with formaldehyde using phosphotungstic acid as catalyst in pore spaces. The effect of temperature and the amount of formaldehyde and phosphotungstic acid loaded on the substrate were investigated in a batch system. In the breakthrough experiment, three different model diesel fuels containing 1000 mg/kg 4,6-DMDBT were pumped through a fixed-bed reactor packed with reactive adsorbent at constant temperature and atmospheric pressure, respectively. The experimental results showed that sulfur-free model fuel was obtained at 80ºC despite the presence of aromatics. The sulfur capacity of regenerated reactive adsorbent was almost totally recovered.
A Non-linear Stochastic Model for an Office Building with Air Infiltration
Thavlov, Anders; Madsen, Henrik
2015-01-01
This paper presents a non-linear heat dynamic model for a multi-room office building with air infiltration. Several linear and non-linear models, with and without air infiltration, are investigated and compared. The models are formulated using stochastic differential equations and the model param...... heat load reduction during peak load hours, control of indoor air temperature and for generating forecasts of power consumption from space heating....
Maximum Likelihood in a Generalized Linear Finite Mixture Model by Using the EM Algorithm
Jansen, R.C.
A generalized linear finite mixture model and an EM algorithm to fit the model to data are described. By this approach the finite mixture model is embedded within the general framework of generalized linear models (GLMs). Implementation of the proposed EM algorithm can be readily done in statistical
Model Checking for a General Linear Model with Nonignorable Missing Covariates
Zhi-hua SUN; Wai-Cheung IP; Heung WONG
2012-01-01
In this paper,we investigate the model checking problem for a general linear model with nonignorable missing covariates.We show that,without any parametric model assumption for the response probability,the least squares method yields consistent estimators for the linear model even if only the complete data are applied.This makes it feasible to propose two testing procedures for the corresponding model checking problem:a score type lack-of-fit test and a test based on the empirical process.The asymptotic properties of the test statistics are investigated.Both tests are shown to have asymptotic power 1 for local alternatives converging to the null at the rate n-(r),0 ≤ (r) ＜ 1/2.Simulation results show that both tests perform satisfactorily.
Numerical Modelling of Multi-Phase Multi-Component Reactive Transport in the Earth's interior
Oliveira, Beñat; Afonso, Juan Carlos; Zlotnik, Sergio; Tilhac, Romain
2017-04-01
We present a conceptual and numerical approach to model processes in the Earth's interior that involve multiple phases that simultaneously interact thermally, mechanically and chemically. The approach is truly multiphase in the sense that each dynamic phase is explicitly modelled with an individual set of mass, momentum, energy and chemical mass balance equations coupled via interfacial interaction terms. It is also truly multi-component in the sense that the compositions of the system and its constituent thermodynamic phases are expressed by a full set of fundamental chemical components (e.g. SiO_2, Al_2O_3, MgO, etc) rather than proxies. In contrast to previous approaches these chemical components evolve, react with, and partition into, different phases with different physical properties according to an internally-consistent thermodynamic model. This enables a thermodynamically-consistent coupling of the governing set of balance equations. Interfacial processes such as surface tensions and/or surface energy contributions to the dynamics and energetics of the system are also taken into account. The model presented here describes the evolution of systems governed by Multi-Phase Multi-Component Reactive Transport (MPMCRT) based on Ensemble Averaging and Classical Irreversible Thermodynamics principles. This novel approach provides a flexible platform to study the dynamics and non-linear feedbacks occurring within various natural systems at different scales. This notably includes major- and trace-element transport, diffusion-controlled trace-element re-equilibration or rheological changes associated with melt generation and migration in the Earth's mantle.
Surface modeling for optical fabrication with linear ion source
Wu, Lixiang; Shao, Jianda
2016-01-01
We present a concept of surface decomposition extended from double Fourier series to nonnegative sinusoidal wave surfaces, on the basis of which linear ion sources apply to the ultra-precision fabrication of complex surfaces and diffractive optics. It is the first time that we have a surface descriptor for building a relationship between the fabrication process of optical surfaces and the surface characterization based on PSD analysis, which akin to Zernike polynomials used for mapping the relationship between surface errors and Seidel aberrations. Also, we demonstrate that the one-dimensional scanning of linear ion source is applicable to the removal of surface errors caused by small-tool polishing in raster scan mode as well as the fabrication of beam sampling grating of high diffractive uniformity without a post-processing procedure. The simulation results show that, in theory, optical fabrication with linear ion source is feasible and even of higher output efficiency compared with the conventional approac...
A new identification method for fuzzy linear models of non-linear dynamic systems
de Bruin, H.A.E.; Roffel, B.
1996-01-01
The most promising methods for identifying a fuzzy model are data clustering, cluster merging and subsequent projection of the clusters on the input variable space. This article proposes to modify this procedure by adding a cluster rotation step, and a method for the direct calculation of the
Recursive subspace identification of linear and non-linear Wiener state-space models
Lovera, Marco; Gustafsson, Tony; Verhaegen, M.H.G.
2000-01-01
The problem of MIMO recursive identification is analyzed within the framework of subspace model identification (SMI) and the use of recent signal processing algorithms for the recursive update of the singular value decomposition (SVD) is proposed. To accommodate for arbitrary correlation of the dist
Linear and logistic models with time dependent coefficients
Youness Mir
2016-01-01
Full Text Available We sutdy the effects of some properties of the carrying capacity on the solution of the linear and logistic differential equations. We present results concerning the behaviour and the asymptotic behaviour of their solutions. Special attention is paid when the carrying capacity is an increasing or a decreasing positive function. For more general carrying capacity, we obtain bounds for the corresponding solution by constructing appropriate subsolution and supersolution. We also present a decomposition of the solution of the linear, and logistic, differential equation as a product of the carrying capacity and the solution to the corresponding differential equation with a constant carrying capacity.
Collier, W.; Milian Sanz, J.
2016-09-01
The length and flexibility of wind turbine blades are increasing over time. Typically, the dynamic response of the blades is analysed using linear models of blade deflection, enhanced by various ad-hoc non-linear correction models. For blades undergoing large deflections, the small deflection assumption inherent to linear models becomes less valid. It has previously been demonstrated that linear and nonlinear blade models can show significantly different blade response, particularly for blade torsional deflection, leading to load prediction differences. There is a need to evaluate how load predictions from these two approaches compare to measurement data from the field. In this paper, time domain simulations in turbulent wind are carried out using the aero-elastic code Bladed with linear and non-linear blade deflection models. The turbine blade load and deflection simulation results are compared to measurement data from an onshore prototype of the GE 6MW Haliade turbine, which features 73.5m long LM blades. Both linear and non-linear blade models show a good match to measurement turbine load and blade deflections. Only the blade loads differ significantly between the two models, with other turbine loads not strongly affected. The non-linear blade model gives a better match to the measured blade root flapwise damage equivalent load, suggesting that the flapwise dynamic behaviour is better captured by the non-linear blade model. Conversely, the linear blade model shows a better match to measurements in some areas such as blade edgewise damage equivalent load.
Liu Gang
2009-01-01
Full Text Available By using the methods of linear algebra and matrix inequality theory, we obtain the characterization of admissible estimators in the general multivariate linear model with respect to inequality restricted parameter set. In the classes of homogeneous and general linear estimators, the necessary and suffcient conditions that the estimators of regression coeffcient function are admissible are established.
Model Reduction of Linear Switched Systems by Restricting Discrete Dynamics
Bastug, Mert; Petreczky, Mihaly; Wisniewski, Rafal
2014-01-01
We present a procedure for reducing the number of continuous states of discrete-time linear switched systems, such that the reduced system has the same behavior as the original system for a subset of switching sequences. The proposed method is expected to be useful for abstraction based control s...
Piecewise-polynomial and cascade models of predistorter for linearization of power amplifier
2012-01-01
To combat non-linear signal distortions in a power amplifier we suggest using predistorter with cascade structure in which first and second nodes have piecewise-polynomial and polynomial models. On example of linearizing the Winner–Hammerstein amplifier model we demonstrate that cascade structure of predistorter improves precision of amplifier’s linearization. To simplify predistorter’s synthesis the degree of polynomial model used in first node should be moderate, while precision should be i...
Beardsell, Alec; Collier, William; Han, Tao
2016-09-01
There is a trend in the wind industry towards ever larger and more flexible turbine blades. Blade tip deflections in modern blades now commonly exceed 10% of blade length. Historically, the dynamic response of wind turbine blades has been analysed using linear models of blade deflection which include the assumption of small deflections. For modern flexible blades, this assumption is becoming less valid. In order to continue to simulate dynamic turbine performance accurately, routine use of non-linear models of blade deflection may be required. This can be achieved by representing the blade as a connected series of individual flexible linear bodies - referred to in this paper as the multi-part approach. In this paper, Bladed is used to compare load predictions using single-part and multi-part blade models for several turbines. The study examines the impact on fatigue and extreme loads and blade deflection through reduced sets of load calculations based on IEC 61400-1 ed. 3. Damage equivalent load changes of up to 16% and extreme load changes of up to 29% are observed at some turbine load locations. It is found that there is no general pattern in the loading differences observed between single-part and multi-part blade models. Rather, changes in fatigue and extreme loads with a multi-part blade model depend on the characteristics of the individual turbine and blade. Key underlying causes of damage equivalent load change are identified as differences in edgewise- torsional coupling between the multi-part and single-part models, and increased edgewise rotor mode damping in the multi-part model. Similarly, a causal link is identified between torsional blade dynamics and changes in ultimate load results.
Kumar, K Vasanth
2007-04-02
Kinetic experiments were carried out for the sorption of safranin onto activated carbon particles. The kinetic data were fitted to pseudo-second order model of Ho, Sobkowsk and Czerwinski, Blanchard et al. and Ritchie by linear and non-linear regression methods. Non-linear method was found to be a better way of obtaining the parameters involved in the second order rate kinetic expressions. Both linear and non-linear regression showed that the Sobkowsk and Czerwinski and Ritchie's pseudo-second order models were the same. Non-linear regression analysis showed that both Blanchard et al. and Ho have similar ideas on the pseudo-second order model but with different assumptions. The best fit of experimental data in Ho's pseudo-second order expression by linear and non-linear regression method showed that Ho pseudo-second order model was a better kinetic expression when compared to other pseudo-second order kinetic expressions.
OH radical reactivity in an Indiana Forest: Measurements and model comparisons
Sigler, P. S. R.; Bottorff, B.; Lew, M.; Stevens, P. S.; Leonardis, T.; Locoge, N.; Sklaveniti, S.; Dusanter, S.; Kundu, S.; Wood, E. C. D.; Gentner, D. R.
2015-12-01
The hydroxyl (OH) radicals plays an important role in the chemistry of the atmosphere. OH radical reactions initiate the oxidation of volatile organic compounds (VOCs) which can lead to the production of ozone and secondary organic aerosols in the atmosphere. In addition, reactions of OH radicals controls the lifetime of methane and other greenhouse gases that affect the radiative balance of the atmosphere. Previous measurements of total hydroxyl radical reactivity in forest environments have found discrepancies between measured values and those calculated from collocated measurements of biogenic VOC (BVOC) concentrations. Additional measurements of total OH reactivity together with measurements of BVOCs are needed to understand the source of this missing reactivity and to further constrain atmospheric chemistry models. Total hydroxyl radical (OH) reactivity was measured using a turbulent flow reactor were made during summer 2015 as part of the Indiana Radical, Reactivity and Ozone Production Intercomparison (IRRONIC). This campaign took place in a forested area at the Indiana Research and Teaching Preserve (IURTP) near the Bloomington campus characterized by high mixing ratios of isoprene and low mixing ratios of NOx. Measurements of a suite of VOCs and oxygenated VOCs was also conducted at the site, allowing a comparison of the observed reactivity with the expected OH reactivity from these measurements.
Siade, A. J.; Prommer, H.; Welter, D.
2014-12-01
Groundwater management and remediation requires the implementation of numerical models in order to evaluate the potential anthropogenic impacts on aquifer systems. In many situations, the numerical model must, not only be able to simulate groundwater flow and transport, but also geochemical and biological processes. Each process being simulated carries with it a set of parameters that must be identified, along with differing potential sources of model-structure error. Various data types are often collected in the field and then used to calibrate the numerical model; however, these data types can represent very different processes and can subsequently be sensitive to the model parameters in extremely complex ways. Therefore, developing an appropriate weighting strategy to address the contributions of each data type to the overall least-squares objective function is not straightforward. This is further compounded by the presence of potential sources of model-structure errors that manifest themselves differently for each observation data type. Finally, reactive transport models are highly nonlinear, which can lead to convergence failure for algorithms operating on the assumption of local linearity. In this study, we propose a variation of the popular, particle swarm optimization algorithm to address trade-offs associated with the calibration of one data type over another. This method removes the need to specify weights between observation groups and instead, produces a multi-dimensional Pareto front that illustrates the trade-offs between data types. We use the PEST++ run manager, along with the standard PEST input/output structure, to implement parallel programming across multiple desktop computers using TCP/IP communications. This allows for very large swarms of particles without the need of a supercomputing facility. The method was applied to a case study in which modeling was used to gain insight into the mobilization of arsenic at a deepwell injection site
Reactive attachment disorder--a theoretical model beyond attachment.
Minnis, Helen; Marwick, Helen; Arthur, Julie; McLaughlin, Alexis
2006-09-01
Despite its importance in public health, reactive attachment disorder (RAD) is an under-researched and little used clinical category. Abnormalities of social relatedness have long been documented in children who have been abused, neglected or institutionalised, but there have been more recent efforts to define these behaviours within the psychiatric nosology. There has been an implicit assumption that the central deficit in RAD is in the attachment system, but this has caused controversy and may have blocked research. We propose that RAD is better construed within the framework of intersubjectivity, which has a central role in the development of core brain and social functions and may also have had an important role in the evolution of a key human characteristic-complex social functioning. This broader framework may potentially explain apparently diverse symptoms such as indiscriminate friendliness and negative or unpredictable reunion responses. Finally, we suggest that a change of name may be useful in progressing the field, but accept that this may be difficult until there is better agreement in the clinical and scientific communities about the core features and aetiology of this disorder.
Bayesian model choice and information criteria in sparse generalized linear models
Foygel, Rina
2011-01-01
We consider Bayesian model selection in generalized linear models that are high-dimensional, with the number of covariates p being large relative to the sample size n, but sparse in that the number of active covariates is small compared to p. Treating the covariates as random and adopting an asymptotic scenario in which p increases with n, we show that Bayesian model selection using certain priors on the set of models is asymptotically equivalent to selecting a model using an extended Bayesian information criterion. Moreover, we prove that the smallest true model is selected by either of these methods with probability tending to one. Having addressed random covariates, we are also able to give a consistency result for pseudo-likelihood approaches to high-dimensional sparse graphical modeling. Experiments on real data demonstrate good performance of the extended Bayesian information criterion for regression and for graphical models.
Generation companies decision-making modeling by linear control theory
Gutierrez-Alcaraz, G. [Programa de Graduados e Investigacion en Ingenieria Electrica. Departamento de Ingenieria Electrica y Electronica, Instituto Tecnologico de Morelia. Av. Tecnologico 1500, Col. Lomas de Santiaguito 58120. Morelia, Mich. (Mexico); Sheble, Gerald B. [INESC Porto, Faculdade de Engenharia, Universidade do Porto, Campus da FEUP, Rua Dr. Roberto Frias, 4200-465 Porto (Portugal)
2010-07-15
This paper proposes four decision-making procedures to be employed by electric generating companies as part of their bidding strategies when competing in an oligopolistic market: naive, forward, adaptive, and moving average expectations. Decision-making is formulated in a dynamic framework by using linear control theory. The results reveal that interactions among all GENCOs affect market dynamics. Several numerical examples are reported, and conclusions are presented. (author)
AN ADA LINEAR ALGEBRA PACKAGE MODELED AFTER HAL/S
Klumpp, A. R.
1994-01-01
This package extends the Ada programming language to include linear algebra capabilities similar to those of the HAL/S programming language. The package is designed for avionics applications such as Space Station flight software. In addition to the HAL/S built-in functions, the package incorporates the quaternion functions used in the Shuttle and Galileo projects, and routines from LINPAK that solve systems of equations involving general square matrices. Language conventions in this package follow those of HAL/S to the maximum extent practical and minimize the effort required for writing new avionics software and translating existent software into Ada. Valid numeric types in this package include scalar, vector, matrix, and quaternion declarations. (Quaternions are fourcomponent vectors used in representing motion between two coordinate frames). Single precision and double precision floating point arithmetic is available in addition to the standard double precision integer manipulation. Infix operators are used instead of function calls to define dot products, cross products, quaternion products, and mixed scalar-vector, scalar-matrix, and vector-matrix products. The package contains two generic programs: one for floating point, and one for integer. The actual component type is passed as a formal parameter to the generic linear algebra package. The procedures for solving systems of linear equations defined by general matrices include GEFA, GECO, GESL, and GIDI. The HAL/S functions include ABVAL, UNIT, TRACE, DET, INVERSE, TRANSPOSE, GET, PUT, FETCH, PLACE, and IDENTITY. This package is written in Ada (Version 1.2) for batch execution and is machine independent. The linear algebra software depends on nothing outside the Ada language except for a call to a square root function for floating point scalars (such as SQRT in the DEC VAX MATHLIB library). This program was developed in 1989, and is a copyrighted work with all copyright vested in NASA.
A NEW TEST FOR NORMALITY IN LINEAR AUTOREGRESSIVE MODELS
CHEN Min; WU Guofu; Gemai Chen
2002-01-01
A nonparametric test for normality of linear autoregressive time series isproposed in this paper. The test is based on the best one-step forecast in mean squarewith time reverse. Some asymptotic theory is developed for the test, and it is shown thatthe test is easy to use and has good powers. The empirical percentage points to conductthe test in practice are provided and three examples using real data are included.
AN ADA LINEAR ALGEBRA PACKAGE MODELED AFTER HAL/S
Klumpp, A. R.
1994-01-01
This package extends the Ada programming language to include linear algebra capabilities similar to those of the HAL/S programming language. The package is designed for avionics applications such as Space Station flight software. In addition to the HAL/S built-in functions, the package incorporates the quaternion functions used in the Shuttle and Galileo projects, and routines from LINPAK that solve systems of equations involving general square matrices. Language conventions in this package follow those of HAL/S to the maximum extent practical and minimize the effort required for writing new avionics software and translating existent software into Ada. Valid numeric types in this package include scalar, vector, matrix, and quaternion declarations. (Quaternions are fourcomponent vectors used in representing motion between two coordinate frames). Single precision and double precision floating point arithmetic is available in addition to the standard double precision integer manipulation. Infix operators are used instead of function calls to define dot products, cross products, quaternion products, and mixed scalar-vector, scalar-matrix, and vector-matrix products. The package contains two generic programs: one for floating point, and one for integer. The actual component type is passed as a formal parameter to the generic linear algebra package. The procedures for solving systems of linear equations defined by general matrices include GEFA, GECO, GESL, and GIDI. The HAL/S functions include ABVAL, UNIT, TRACE, DET, INVERSE, TRANSPOSE, GET, PUT, FETCH, PLACE, and IDENTITY. This package is written in Ada (Version 1.2) for batch execution and is machine independent. The linear algebra software depends on nothing outside the Ada language except for a call to a square root function for floating point scalars (such as SQRT in the DEC VAX MATHLIB library). This program was developed in 1989, and is a copyrighted work with all copyright vested in NASA.
Reactive transport modeling in variably saturated porous media with OGS-IPhreeqc
He, W.; Beyer, C.; Fleckenstein, J. H.; Jang, E.; Kalbacher, T.; Shao, H.; Wang, W.; Kolditz, O.
2014-12-01
Worldwide, sustainable water resource management becomes an increasingly challenging task due to the growth of population and extensive applications of fertilizer in agriculture. Moreover, climate change causes further stresses to both water quantity and quality. Reactive transport modeling in the coupled soil-aquifer system is a viable approach to assess the impacts of different land use and groundwater exploitation scenarios on the water resources. However, the application of this approach is usually limited in spatial scale and to simplified geochemical systems due to the huge computational expense involved. Such computational expense is not only caused by solving the high non-linearity of the initial boundary value problems of water flow in the unsaturated zone numerically with rather fine spatial and temporal discretization for the correct mass balance and numerical stability, but also by the intensive computational task of quantifying geochemical reactions. In the present study, a flexible and efficient tool for large scale reactive transport modeling in variably saturated porous media and its applications are presented. The open source scientific software OpenGeoSys (OGS) is coupled with the IPhreeqc module of the geochemical solver PHREEQC. The new coupling approach makes full use of advantages from both codes: OGS provides a flexible choice of different numerical approaches for simulation of water flow in the vadose zone such as the pressure-based or mixed forms of Richards equation; whereas the IPhreeqc module leads to a simplification of data storage and its communication with OGS, which greatly facilitates the coupling and code updating. Moreover, a parallelization scheme with MPI (Message Passing Interface) is applied, in which the computational task of water flow and mass transport is partitioned through domain decomposition, whereas the efficient parallelization of geochemical reactions is achieved by smart allocation of computational workload over
Reactive transport modeling in the subsurface environment with OGS-IPhreeqc
He, Wenkui; Beyer, Christof; Fleckenstein, Jan; Jang, Eunseon; Kalbacher, Thomas; Naumov, Dimitri; Shao, Haibing; Wang, Wenqing; Kolditz, Olaf
2015-04-01
Worldwide, sustainable water resource management becomes an increasingly challenging task due to the growth of population and extensive applications of fertilizer in agriculture. Moreover, climate change causes further stresses to both water quantity and quality. Reactive transport modeling in the coupled soil-aquifer system is a viable approach to assess the impacts of different land use and groundwater exploitation scenarios on the water resources. However, the application of this approach is usually limited in spatial scale and to simplified geochemical systems due to the huge computational expense involved. Such computational expense is not only caused by solving the high non-linearity of the initial boundary value problems of water flow in the unsaturated zone numerically with rather fine spatial and temporal discretization for the correct mass balance and numerical stability, but also by the intensive computational task of quantifying geochemical reactions. In the present study, a flexible and efficient tool for large scale reactive transport modeling in variably saturated porous media and its applications are presented. The open source scientific software OpenGeoSys (OGS) is coupled with the IPhreeqc module of the geochemical solver PHREEQC. The new coupling approach makes full use of advantages from both codes: OGS provides a flexible choice of different numerical approaches for simulation of water flow in the vadose zone such as the pressure-based or mixed forms of Richards equation; whereas the IPhreeqc module leads to a simplification of data storage and its communication with OGS, which greatly facilitates the coupling and code updating. Moreover, a parallelization scheme with MPI (Message Passing Interface) is applied, in which the computational task of water flow and mass transport is partitioned through domain decomposition, whereas the efficient parallelization of geochemical reactions is achieved by smart allocation of computational workload over
Results and Comparison from the SAM Linear Fresnel Technology Performance Model: Preprint
Wagner, M. J.
2012-04-01
This paper presents the new Linear Fresnel technology performance model in NREL's System Advisor Model. The model predicts the financial and technical performance of direct-steam-generation Linear Fresnel power plants, and can be used to analyze a range of system configurations. This paper presents a brief discussion of the model formulation and motivation, and provides extensive discussion of the model performance and financial results. The Linear Fresnel technology is also compared to other concentrating solar power technologies in both qualitative and quantitative measures. The Linear Fresnel model - developed in conjunction with the Electric Power Research Institute - provides users with the ability to model a variety of solar field layouts, fossil backup configurations, thermal receiver designs, and steam generation conditions. This flexibility aims to encompass current market solutions for the DSG Linear Fresnel technology, which is seeing increasing exposure in fossil plant augmentation and stand-alone power generation applications.
A Comparison of Alternative Estimators of Linearly Aggregated Macro Models
Fikri Akdeniz
2012-07-01
Full Text Available Normal 0 false false false TR X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Times New Roman","serif"; mso-ansi-language:TR; mso-fareast-language:TR;} This paper deals with the linear aggregation problem. For the true underlying micro relations, which explain the micro behavior of the individuals, no restrictive rank conditions are assumed. Thus the analysis is presented in a framework utilizing generalized inverses of singular matrices. We investigate several estimators for certain linear transformations of the systematic part of the corresponding macro relations. Homogeneity of micro parameters is discussed. Best linear unbiased estimation for micro parameters is described.
Reactive transport modeling of plug-flow reactor experiments: quartz and tuff dissolution at 240°C
Johnson, James W.; Knauss, Kevin G.; Glassley, William E.; DeLoach, Laura D.; Tompson, Andrew F. B.
1998-08-01
Extension of reactive transport modeling to predict the coupled thermal, hydrological, and chemical evolution of complex geological systems is predicated on successful application of the approach to simulate well-constrained physical experiments. In this study, steady-state effluent concentrations and dissolution/precipitation features associated with crushed quartz and tuff dissolution at 240°C have been determined experimentally using a plug-flow reactor (PFR) and scanning electron microscopy (SEM) techniques, then modeled with the reactive transport simulator GIMRT ( Steefel and Yabusaki, 1996) using a linear rate law from transition state theory (TST) . For quartz dissolution, interdependence of the specific surface area ( Am) and reaction rate constant ( km) predicted from the modeling agrees closely with that obtained from an analytical solution to the reaction-transport equation without diffusion/dispersion, verifying the advection-dominant nature of the PFR experiments. Independently-determined Aqtz and kqtz from the literature are shown to be internally consistent with respect to the model and analytical interdependence, implying appropriateness of the linear TST rate law and adequacy of BET-determined Am for use in modeling PFR experiments. Applications of this integrated approach for monomineralic dissolution include assessment of internal consistency among independent Am and km data, estimation of km from BET-determined Am, and rapid evaluation of alternative rate laws. For tuff dissolution, accurate simulation of the experimental steady-state effluent concentrations (to within 3% for Na, Al and K; to within 15% for Si and Ca) and dearth of alteration phases (complex systems for which development of experimental analogs is impractical or impossible.
Equivalent Models and Exact Linearization by the Optimal Control of Monod Kinetics Models
Krassimira Ljakova
2004-10-01
Full Text Available The well-known global biotechnological models are non-linear and nonstationary. In addition the process variables are difficult to measure, the model parameters are time varying, the measurement noise and measurement delay increase the control problems, etc. One possible way to solve some of these problems is to determine the most simple and easy for use equivalent models. The differential geometric approach [DGA] and especially the exact linearization permit an easy application of the optimal control. The approach and its application in the control of the biotechnological process are discussed in the paper. The optimization technique is used for fed-batch and continuos biotechnological processes when the specific growth rate is described by the Monod kinetics.
Rith-Najarian, Leslie R; McLaughlin, Katie A; Sheridan, Margaret A; Nock, Matthew K
2014-03-01
Extensive research among adults supports the biopsychosocial (BPS) model of challenge and threat, which describes relationships among stress appraisals, physiological stress reactivity, and performance; however, no previous studies have examined these relationships in adolescents. Perceptions of stressors as well as physiological reactivity to stress increase during adolescence, highlighting the importance of understanding the relationships among stress appraisals, physiological reactivity, and performance during this developmental period. In this study, 79 adolescent participants reported on stress appraisals before and after a Trier Social Stress Test in which they performed a speech task. Physiological stress reactivity was defined by changes in cardiac output and total peripheral resistance from a baseline rest period to the speech task, and performance on the speech was coded using an objective rating system. We observed in adolescents only two relationships found in past adult research on the BPS model variables: (1) pre-task stress appraisal predicted post-task stress appraisal and (2) performance predicted post-task stress appraisal. Physiological reactivity during the speech was unrelated to pre- and post-task stress appraisals and to performance. We conclude that the lack of association between post-task stress appraisal and physiological stress reactivity suggests that adolescents might have low self-awareness of physiological emotional arousal. Our findings further suggest that adolescent stress appraisals are based largely on their performance during stressful situations. Developmental implications of this potential lack of awareness of one's physiological and emotional state during adolescence are discussed.
Solid phase studies and geochemical modelling of low-cost permeable reactive barriers
Bartzas, Georgios, E-mail: gbartzas@metal.ntua.gr [Laboratory of Metallurgy, School of Mining and Metallurgical Engineering, National Technical University of Athens, Zografos Campus, 15780 Athens (Greece); Komnitsas, Kostas [Department of Mineral Resources Engineering, Technical University of Crete, 73100 Chania (Greece)
2010-11-15
A continuous column experiment was carried out under dynamic flow conditions in order to study the efficiency of low-cost permeable reactive barriers (PRBs) to remove several inorganic contaminants from acidic solutions. A 50:50 w/w waste iron/sand mixture was used as candidate reactive media in order to activate precipitation and promote sorption and reduction-oxidation mechanisms. Solid phase studies of the exhausted reactive products after column shutdown, using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD), confirmed that the principal Fe corrosion products identified in the reactive zone are amorphous iron (hydr)oxides (maghemite/magnetite and goethite), intermediate products (sulfate green rust), and amorphous metal sulfides such as amFeS and/or mackinawite. Geochemical modelling of the metal removal processes, including interactions between reactive media, heavy metal ions and sulfates, and interpretation of the ionic profiles was also carried out by using the speciation/mass transfer computer code PHREEQC-2 and the WATEQ4F database. Mineralogical characterization studies as well as geochemical modelling calculations also indicate that the effect of sulfate and silica sand on the efficiency of the reactive zone should be considered carefully during design and operation of low-cost field PRBs.
Predicting recycling behaviour: Comparison of a linear regression model and a fuzzy logic model.
Vesely, Stepan; Klöckner, Christian A; Dohnal, Mirko
2016-03-01
In this paper we demonstrate that fuzzy logic can provide a better tool for predicting recycling behaviour than the customarily used linear regression. To show this, we take a set of empirical data on recycling behaviour (N=664), which we randomly divide into two halves. The first half is used to estimate a linear regression model of recycling behaviour, and to develop a fuzzy logic model of recycling behaviour. As the first comparison, the fit of both models to the data included in estimation of the models (N=332) is evaluated. As the second comparison, predictive accuracy of both models for "new" cases (hold-out data not included in building the models, N=332) is assessed. In both cases, the fuzzy logic model significantly outperforms the regression model in terms of fit. To conclude, when accurate predictions of recycling and possibly other environmental behaviours are needed, fuzzy logic modelling seems to be a promising technique. Copyright © 2015 Elsevier Ltd. All rights reserved.
A Non-linear Stochastic Model for an Office Building with Air Infiltration
Thavlov, Anders; Madsen, Henrik
2015-01-01
This paper presents a non-linear heat dynamic model for a multi-room office building with air infiltration. Several linear and non-linear models, with and without air infiltration, are investigated and compared. The models are formulated using stochastic differential equations and the model...... parameters are estimated using a maximum likelihood technique. Based on the maximum likelihood value, the different models are statistically compared to each other using Wilk's likelihood ratio test. The model showing the best performance is finally verified in both the time domain and the frequency domain...
Muayad Al-Qaisy
2013-04-01
Full Text Available In this article, multi-input multi-output (MIMO linear model predictive controller (LMPC based on state space model and nonlinear model predictive controller based on neural network (NNMPC are applied on a continuous stirred tank reactor (CSTR. The idea is to have a good control system that will be able to give optimal performance, reject high load disturbance, and track set point change. In order to study the performance of the two model predictive controllers, MIMO Proportional-Integral-Derivative controller (PID strategy is used as benchmark. The LMPC, NNMPC, and PID strategies are used for controlling the residual concentration (CA and reactor temperature (T. NNMPC control shows a superior performance over the LMPC and PID controllers by presenting a smaller overshoot and shorter settling time.
Dynamic behaviour of reactive distillation tray columns described with a non-equilibrium cell model
Baur, R.; Taylor, R.; Krishna, R.
2001-01-01
In this paper we develop a generic, dynamic, nonequilibrium (NEQ) cell model for reactive distillation (RD) tray columns. The features of our model are (1) the use of Maxwell–Stefan equations for describing mass transfer between fluid phases, (2) the reaction is assumed to take place in the liquid
Patel, R.A.; Perko, J.; Jaques, D.; De Schutter, G.; Ye, G.; Van Breugel, K.
2013-01-01
A Lattice Boltzmann (LB) based reactive transport model intended to capture reactions and solid phase changes occurring at the pore scale is presented. The proposed approach uses LB method to compute multi component mass transport. The LB multi-component transport model is then coupled with the well
MCMC for non-linear state space models using ensembles of latent sequences
2013-01-01
Non-linear state space models are a widely-used class of models for biological, economic, and physical processes. Fitting these models to observed data is a difficult inference problem that has no straightforward solution. We take a Bayesian approach to the inference of unknown parameters of a non-linear state model; this, in turn, requires the availability of efficient Markov Chain Monte Carlo (MCMC) sampling methods for the latent (hidden) variables and model parameters. Using the ensemble ...
Generalized linear models for categorical and continuous limited dependent variables
Smithson, Michael
2013-01-01
Introduction and OverviewThe Nature of Limited Dependent VariablesOverview of GLMsEstimation Methods and Model EvaluationOrganization of This BookDiscrete VariablesBinary VariablesLogistic RegressionThe Binomial GLMEstimation Methods and IssuesAnalyses in R and StataExercisesNominal Polytomous VariablesMultinomial Logit ModelConditional Logit and Choice ModelsMultinomial Processing Tree ModelsEstimation Methods and Model EvaluationAnalyses in R and StataExercisesOrdinal Categorical VariablesModeling Ordinal Variables: Common Practice versus Best PracticeOrdinal Model AlternativesCumulative Mod
The Fast Linear Accelerator Modeling Engine for FRIB Online Model Service
He, Z; Davidsaver, M; Fukushima, K; Shen, G; Ikegami, M
2016-01-01
Commissioning of a large accelerator facility like FRIB needs support from an online beam dynamics model. Considering the new physics challenges of FRIB such as modeling of non-axisymmetric superconducting RF cavities and multi-charge state acceleration, there is no readily available online beam tuning code. The design code of FRIB super-conducting linac, IMPACT-Z, is not suitable for online tuning because of its code design and running speed. Therefore, the Fast Linear Accelerator Modeling Engine (FLAME), specifically designed to fulfill FRIB's online modeling challenges, is proposed. The physics model of FLAME, especially its novel way of modeling non-axisymmetric superconducting RF cavities using a multipole expansion based thin-lens kick model, is discussed in detail, and the benchmark results against FRIB design code is presented, after which the software design strategy of FLAME and its execution speed is presented.
New Fuel Pin Axial Expansion Reactivity Feedback Model in MARS-LMR
Choi, Chiwoong; Ha, Kwiseok [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2015-10-15
In this study, the sensitivity tests are conducted. In the case of the UTOP event, a sensitivity test for the reactivity insertion amount and rate were conducted. This analysis can give a requirement for margin of control rod stop system (CRSS). For example, the CRSS in the PRISM designed based on the 0.4 $ reactivity insertion, which is analyzed with safety analysis of UTOP event. Moreover, the sensitivity tests for weighting factor in the core radial expansion reactivity feedback model were also carried out for all ATWS events. Currently, the reactivity feedback model for the PGSFR is not validated yet. However, the reactivity feedback models in the MARS-LMR are validating with various plant-based data including EBR-II SHRT. The ATWS events for the PGSFR classified in the design extended condition including UTOP, ULOF, and ULOHS are analyzed with MARS-LMR. In this study, the sensitivity tests for reactivity insertion amount and rate in the UTOP event are conducted. The reactivity insertion amount is obviously an influential parameter. The reactivity insertion amount can give a requirement for design of the CRSS, therefore, this sensitivity result is very important to the CRSS. In addition, sensitivity tests for the weighting factor in the radial expansion reactivity model are carried out. The weighting factor for a grid plate, W{sub GP}, which means contribution of feedback in the grid plate is changed for all unprotected events. The grid plate expansion is governed by a core inlet temperature. As the W{sub GP} is increased, the power in the UTOP and the ULOF is increased, however, the power in the ULOHS is decreased. The higher power during transient means lower reactivity feedback and smaller expansion. Thus, the core outlet temperature rise is dominant in the UTOP and ULOF events, however, the core inlet temperature rise is dominant in the ULOHS. Therefore, the grid plate expansion in the ULOHS is predominant. These analysis results will give better
A note on fractional linear pure birth and pure death processes in epidemic models
Garra, Roberto; 10.1016/j.physa.2011.06.005
2011-01-01
In this note we highlight the role of fractional linear birth and linear death processes recently studied in \\citet{sakhno} and \\citet{pol}, in relation to epidemic models with empirical power law distribution of the events. Taking inspiration from a formal analogy between the equation of self consistency of the epidemic type aftershock sequences (ETAS) model, and the fractional differential equation describing the mean value of fractional linear growth processes, we show some interesting applications of fractional modelling to study \\textit{ab initio} epidemic processes without the assumption of any empirical distribution. We also show that, in the frame of fractional modelling, subcritical regimes can be linked to linear fractional death processes and supercritical regimes to linear fractional birth processes. Moreover we discuss a simple toy model to underline the possible application of these stochastic growth models to more general epidemic phenomena such as tumoral growth.
Modeling thermal sensation in a Mediterranean climate—a comparison of linear and ordinal models
Pantavou, Katerina; Lykoudis, Spyridon
2014-08-01
A simple thermo-physiological model of outdoor thermal sensation adjusted with psychological factors is developed aiming to predict thermal sensation in Mediterranean climates. Microclimatic measurements simultaneously with interviews on personal and psychological conditions were carried out in a square, a street canyon and a coastal location of the greater urban area of Athens, Greece. Multiple linear and ordinal regression were applied in order to estimate thermal sensation making allowance for all the recorded parameters or specific, empirically selected, subsets producing so-called extensive and empirical models, respectively. Meteorological, thermo-physiological and overall models - considering psychological factors as well - were developed. Predictions were improved when personal and psychological factors were taken into account as compared to meteorological models. The model based on ordinal regression reproduced extreme values of thermal sensation vote more adequately than the linear regression one, while the empirical model produced satisfactory results in relation to the extensive model. The effects of adaptation and expectation on thermal sensation vote were introduced in the models by means of the exposure time, season and preference related to air temperature and irradiation. The assessment of thermal sensation could be a useful criterion in decision making regarding public health, outdoor spaces planning and tourism.
Pore scale modeling of reactive transport involved in geologic CO2 sequestration
Kang, Qinjin [Los Alamos National Laboratory; Lichtner, Peter C [Los Alamos National Laboratory; Viswanathan, Hari S [Los Alamos National Laboratory; Abdel-fattah, Amr I [Los Alamos National Laboratory
2009-01-01
We apply a multi-component reactive transport lattice Boltzmann model developed in previolls studies to modeling the injection of a C02 saturated brine into various porous media structures at temperature T=25 and 80 C. The porous media are originally consisted of calcite. A chemical system consisting of Na+, Ca2+, Mg2+, H+, CO2(aq), and CI-is considered. The fluid flow, advection and diHusion of aqueous species, homogeneous reactions occurring in the bulk fluid, as weB as the dissolution of calcite and precipitation of dolomite are simulated at the pore scale. The effects of porous media structure on reactive transport are investigated. The results are compared with continuum scale modeling and the agreement and discrepancy are discussed. This work may shed some light on the fundamental physics occurring at the pore scale for reactive transport involved in geologic C02 sequestration.
An I(2) cointegration model with piecewise linear trends
Kurita, Takamitsu; Bohn Nielsen, Heino; Rahbæk, Anders
2011-01-01
This paper presents likelihood analysis of the I(2) cointegrated vector autoregression which allows for piecewise linear deterministic terms. Limiting behaviour of the maximum likelihood estimators are derived, which is used to further derive the limiting distribution of the likelihood ratio...... statistic for the cointegration ranks, extending Nielsen and Rahbek. The provided asymptotic theory extends also the results in Johansen et al. where asymptotic inference is discussed in detail for one of the cointegration parameters. An empirical analysis of US consumption, income and wealth, 1965...
Linear moose model with pairs of degenerate gauge boson triplets
Casalbuoni, Roberto; Coradeschi, Francesco; de Curtis, Stefania; Dominici, Daniele
2008-05-01
The possibility of a strongly interacting electroweak symmetry breaking sector, as opposed to the weakly interacting light Higgs of the standard model, is not yet ruled out by experiments. In this paper we make an extensive study of a deconstructed model (or “moose” model) providing an effective description of such a strong symmetry breaking sector, and show its compatibility with experimental data for a wide portion of the model parameter space. The model is a direct generalization of the previously proposed D-BESS model.
Littlest Higgs model and pair production at international linear collider
P Poulose
2007-11-01
Among the viable alternatives to the standard Higgs mechanism is the recently proposed Little Higgs model. The advantage here is that the model has an elementary light neutral scalar particle, which arises dynamically as against its ad hoc introduction in the standard model. The model also avoids hierarchy problem. We have investigated the pair production at ILC to study the littlest Higgs model using different observables. Specifically, polarization fraction of boson is expected to be measured very accurately at ILC. We use this to put limit on the scale parameter, , in the model.
Deepak Swami; P K Sharma; C S P Ojha
2014-12-01
In this paper, we have studied the behaviour of reactive solute transport through stratified porous medium under the influence of multi-process nonequilibrium transport model. Various experiments were carried out in the laboratory and the experimental breakthrough curves were observed at spatially placed sampling points for stratified porous medium. Batch sorption studies were also performed to estimate the sorption parameters of the material used in stratified aquifer system. The effects of distance dependent dispersion and tailing are visible in the experimental breakthrough curves. The presence of physical and chemical non-equilibrium are observed from the pattern of breakthrough curves. Multi-process non-equilibrium model represents the combined effect of physical and chemical non-ideality in the stratified aquifer system. The results show that the incorporation of distance dependent dispersivity in multi-process non-equilibrium model provides best fit of observed data through stratified porous media. Also, the exponential distance dependent dispersivity is more suitable for large distances and at small distances, linear or constant dispersivity function can be considered for simulating reactive solute in stratified porous medium.