Hybrid Model Representation of a TLP Including Flexible Topsides in Non-Linear Regular Waves
DEFF Research Database (Denmark)
Wehmeyer, Christof; Ferri, Francesco; Andersen, Morten Thøtt
2014-01-01
technologies able to solve this challenge is the floating wind turbine foundation. For the ultimate limit state, where higher order wave loads have a significant influence, a design tool that couples non-linear excitations with structural dynamics is required. To properly describe the behavior...
Understanding Linear Functions and Their Representations
Wells, Pamela J.
2015-01-01
Linear functions are an important part of the middle school mathematics curriculum. Students in the middle grades gain fluency by working with linear functions in a variety of representations (NCTM 2001). Presented in this article is an activity that was used with five eighth-grade classes at three different schools. The activity contains 15 cards…
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.
Boundary representation modelling techniques
2006-01-01
Provides the most complete presentation of boundary representation solid modelling yet publishedOffers basic reference information for software developers, application developers and users Includes a historical perspective as well as giving a background for modern research.
Orbit Representations from Linear mod 1 Transformations
Directory of Open Access Journals (Sweden)
Carlos Correia Ramos
2012-05-01
Full Text Available We show that every point $x_0in [0,1]$ carries a representationof a $C^*$-algebra that encodes the orbit structure of thelinear mod 1 interval map $f_{eta,alpha}(x=eta x +alpha$. Such $C^*$-algebra is generated by partial isometries arising from the subintervals of monotonicity of the underlying map $f_{eta,alpha}$. Then we prove that such representation is irreducible. Moreover two such of representations are unitarily equivalent if and only if the points belong to the same generalized orbit, for every $alphain [0,1[$ and $etageq 1$.
Linear Numerical-Magnitude Representations Aid Children's Memory for Numbers
Thompson, Clarissa A.; Siegler, Robert S.
2010-01-01
We investigated the relation between children's numerical-magnitude representations and their memory for numbers. Results of three experiments indicated that the more linear children's magnitude representations were, the more closely their memory of the numbers approximated the numbers presented. This relation was present for preschoolers and…
Standard model of knowledge representation
Yin, Wensheng
2016-09-01
Knowledge representation is the core of artificial intelligence research. Knowledge representation methods include predicate logic, semantic network, computer programming language, database, mathematical model, graphics language, natural language, etc. To establish the intrinsic link between various knowledge representation methods, a unified knowledge representation model is necessary. According to ontology, system theory, and control theory, a standard model of knowledge representation that reflects the change of the objective world is proposed. The model is composed of input, processing, and output. This knowledge representation method is not a contradiction to the traditional knowledge representation method. It can express knowledge in terms of multivariate and multidimensional. It can also express process knowledge, and at the same time, it has a strong ability to solve problems. In addition, the standard model of knowledge representation provides a way to solve problems of non-precision and inconsistent knowledge.
On a representation of linear differential equations
Czech Academy of Sciences Publication Activity Database
Neuman, František
2010-01-01
Roč. 52, 1-2 (2010), s. 355-360 ISSN 0895-7177 Grant - others:GA ČR(CZ) GA201/08/0469 Institutional research plan: CEZ:AV0Z10190503 Keywords : Brandt and Ehresmann groupoinds * transformations * canonical forms * linear differential equations Subject RIV: BA - General Mathematics Impact factor: 1.066, year: 2010 http://www.sciencedirect.com/science/article/pii/S0895717710001184
Directory of Open Access Journals (Sweden)
Tanwiwat Jaikuna
2017-02-01
Full Text Available Purpose: To develop an in-house software program that is able to calculate and generate the biological dose distribution and biological dose volume histogram by physical dose conversion using the linear-quadratic-linear (LQL model. Material and methods : The Isobio software was developed using MATLAB version 2014b to calculate and generate the biological dose distribution and biological dose volume histograms. The physical dose from each voxel in treatment planning was extracted through Computational Environment for Radiotherapy Research (CERR, and the accuracy was verified by the differentiation between the dose volume histogram from CERR and the treatment planning system. An equivalent dose in 2 Gy fraction (EQD2 was calculated using biological effective dose (BED based on the LQL model. The software calculation and the manual calculation were compared for EQD2 verification with pair t-test statistical analysis using IBM SPSS Statistics version 22 (64-bit. Results: Two and three-dimensional biological dose distribution and biological dose volume histogram were displayed correctly by the Isobio software. Different physical doses were found between CERR and treatment planning system (TPS in Oncentra, with 3.33% in high-risk clinical target volume (HR-CTV determined by D90%, 0.56% in the bladder, 1.74% in the rectum when determined by D2cc, and less than 1% in Pinnacle. The difference in the EQD2 between the software calculation and the manual calculation was not significantly different with 0.00% at p-values 0.820, 0.095, and 0.593 for external beam radiation therapy (EBRT and 0.240, 0.320, and 0.849 for brachytherapy (BT in HR-CTV, bladder, and rectum, respectively. Conclusions : The Isobio software is a feasible tool to generate the biological dose distribution and biological dose volume histogram for treatment plan evaluation in both EBRT and BT.
On the discretization of linear fractional representations of LPV systems
Toth, R.; Lovera, M.; Heuberger, P.S.C.; Corno, M.; Hof, Van den P.M.J.
2012-01-01
Commonly, controllers for linear parameter-varying (LPV) systems are designed in continuous time using a linear fractional representation (LFR) of the plant. However, the resulting controllers are implemented on digital hardware. Furthermore, discrete-time LPV synthesis approaches require a
Global Linear Representations of Nonlinear Systems and the Adjoint Map
Banks, S.P.
1988-01-01
In this paper we shall study the global linearization of nonlinear systems on a manifold by two methods. The first consists of an expansion of the vector field in the space of square integrable vector fields. In the second method we use the adjoint representation of the Lie algebra vector fields to obtain an infinite-dimensional matrix representation of the system. A connection between the two approaches will be developed.
Linear parameter varying representations for nonlinear control design
Carter, Lance Huntington
Linear parameter varying (LPV) systems are investigated as a framework for gain-scheduled control design and optimal hybrid control. An LPV system is defined as a linear system whose dynamics depend upon an a priori unknown but measurable exogenous parameter. A gain-scheduled autopilot design is presented for a bank-to-turn (BTT) missile. The method is novel in that the gain-scheduled design does not involve linearizations about operating points. Instead, the missile dynamics are brought to LPV form via a state transformation. This idea is applied to the design of a coupled longitudinal/lateral BTT missile autopilot. The pitch and yaw/roll dynamics are separately transformed to LPV form, where the cross axis states are treated as "exogenous" parameters. These are actually endogenous variables, so such a plant is called "quasi-LPV." Once in quasi-LPV form, a family of robust controllers using mu synthesis is designed for both the pitch and yaw/roll channels, using angle-of-attack and roll rate as the scheduling variables. The closed-loop time response is simulated using the original nonlinear model and also using perturbed aerodynamic coefficients. Modeling and control of engine idle speed is investigated using LPV methods. It is shown how generalized discrete nonlinear systems may be transformed into quasi-LPV form. A discrete nonlinear engine model is developed and expressed in quasi-LPV form with engine speed as the scheduling variable. An example control design is presented using linear quadratic methods. Simulations are shown comparing the LPV based controller performance to that using PID control. LPV representations are also shown to provide a setting for hybrid systems. A hybrid system is characterized by control inputs consisting of both analog signals and discrete actions. A solution is derived for the optimal control of hybrid systems with generalized cost functions. This is shown to be computationally intensive, so a suboptimal strategy is proposed that
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
Digital models for architectonical representation
Directory of Open Access Journals (Sweden)
Stefano Brusaporci
2011-12-01
Full Text Available Digital instruments and technologies enrich architectonical representation and communication opportunities. Computer graphics is organized according the two phases of visualization and construction, that is modeling and rendering, structuring dichotomy of software technologies. Visualization modalities give different kinds of representations of the same 3D model and instruments produce a separation between drawing and image’s creation. Reverse modeling can be related to a synthesis process, ‘direct modeling’ follows an analytic procedure. The difference between interactive and not interactive applications is connected to the possibilities offered by informatics instruments, and relates to modeling and rendering. At the same time the word ‘model’ describes different phenomenon (i.e. files: mathematical model of the building and of the scene; raster representation and post-processing model. All these correlated different models constitute the architectonical interpretative model, that is a simulation of reality made by the model for improving the knowledge.
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,
Supersymmetry breaking in the linear representation of the dilaton
International Nuclear Information System (INIS)
Gaida, I.
1995-01-01
String effective theories with N=1 supersymmetry in 4 dimensions are subject of the discussion. These theories are effective in the sense, that they are low-energy limits of a given higher dimensional string theory after dimensional reduction and integrating out all heavy modes. At tree level the gauge coupling constant can be expressed by the vacuum expectation value of the dilaton superfield S:g 2 =2 -1 . Throughout this text S+ anti S will be denoted as the chiral representation of the dilaton. It has been shown that there exists a supersymmetric legendre transformation called supersymmetric duality, which transforms S+ anti S into a linear superfield L, where L will be called the linear representation of the dilaton. (orig.)
A representation theorem for linear discrete-space systems
Directory of Open Access Journals (Sweden)
Sandberg Irwin W.
1998-01-01
Full Text Available The cornerstone of the theory of discrete-time single-input single-output linear systems is the idea that every such system has an input–output map H that can be represented by a convolution or the familiar generalization of a convolution. This thinking involves an oversight which is corrected in this note by adding an additional term to the representation.
DEFF Research Database (Denmark)
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 of these cri......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....
Guideline Knowledge Representation Model (GLIKREM)
Czech Academy of Sciences Publication Activity Database
Buchtela, David; Peleška, Jan; Veselý, Arnošt; Zvárová, Jana; Zvolský, Miroslav
2008-01-01
Roč. 4, č. 1 (2008), s. 17-23 ISSN 1801-5603 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : knowledge representation * GLIF model * guidelines Subject RIV: IN - Informatics, Computer Science http://www.ejbi.org/articles/200812/34/1.html
Preon representations and composite models
International Nuclear Information System (INIS)
Kang, Kyungsik
1982-01-01
This is a brief report on the preon models which are investigated by In-Gyu Koh, A. N. Schellekens and myself and based on complex, anomaly-free and asymptotically free representations of SU(3) to SU(8), SO(4N+2) and E 6 with no more than two different preons. Complete list of the representations that are complex anomaly-free and asymptotically free has been given by E. Eichten, I.-G. Koh and myself. The assumptions made about the ground state composites and the role of Fermi statistics to determine the metaflavor wave functions are discussed in some detail. We explain the method of decompositions of tensor products with definite permutation properties which has been developed for this purpose by I.-G. Koh, A.N. Schellekens and myself. An example based on an anomaly-free representation of the confining metacolor group SU(5) is discussed
DEFF Research Database (Denmark)
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....... of these criteria are widely used ones, while the remaining four are ones derived from the H-principle of mathematical modeling. Many examples from practice show that the criteria derived from the H-principle function better than the known and popular criteria for the number of components. We shall briefly review...
Non linear viscoelastic models
DEFF Research Database (Denmark)
Agerkvist, Finn T.
2011-01-01
Viscoelastic eects are often present in loudspeaker suspensions, this can be seen in the displacement transfer function which often shows a frequency dependent value below the resonance frequency. In this paper nonlinear versions of the standard linear solid model (SLS) are investigated....... The simulations show that the nonlinear version of the Maxwell SLS model can result in a time dependent small signal stiness while the Kelvin Voight version does not....
Towards New Mappings between Emotion Representation Models
Directory of Open Access Journals (Sweden)
Agnieszka Landowska
2018-02-01
Full Text Available There are several models for representing emotions in affect-aware applications, and available emotion recognition solutions provide results using diverse emotion models. As multimodal fusion is beneficial in terms of both accuracy and reliability of emotion recognition, one of the challenges is mapping between the models of affect representation. This paper addresses this issue by: proposing a procedure to elaborate new mappings, recommending a set of metrics for evaluation of the mapping accuracy, and delivering new mapping matrices for estimating the dimensions of a Pleasure-Arousal-Dominance model from Ekman’s six basic emotions. The results are based on an analysis using three datasets that were constructed based on affect-annotated lexicons. The new mappings were obtained with linear regression learning methods. The proposed mappings showed better results on the datasets in comparison with the state-of-the-art matrix. The procedure, as well as the proposed metrics, might be used, not only in evaluation of the mappings between representation models, but also in comparison of emotion recognition and annotation results. Moreover, the datasets are published along with the paper and new mappings might be created and evaluated using the proposed methods. The study results might be interesting for both researchers and developers, who aim to extend their software solutions with affect recognition techniques.
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
Wilkie, Karina J.; Ayalon, Michal
2018-02-01
A foundational component of developing algebraic thinking for meaningful calculus learning is the idea of "function" that focuses on the relationship between varying quantities. Students have demonstrated widespread difficulties in learning calculus, particularly interpreting and modeling dynamic events, when they have a poor understanding of relationships between variables. Yet, there are differing views on how to develop students' functional thinking over time. In the Australian curriculum context, linear relationships are introduced to lower secondary students with content that reflects a hybrid of traditional and reform algebra pedagogy. This article discusses an investigation into Australian secondary students' understanding of linear functional relationships from Years 7 to 12 (approximately 12 to 18 years old; n = 215) in their approaches to three tasks (finding rate of change, pattern generalisation and interpretation of gradient) involving four different representations (table, geometric growing pattern, equation and graph). From the findings, it appears that these students' knowledge of linear functions remains context-specific rather than becoming connected over time.
International Nuclear Information System (INIS)
Raoelina Andriambololona; Ranaivoson, R.T.R.; Rakotoson, H.; Solofoarisina, W.C.
2015-04-01
We present a study on linear canonical transformation in the framework of a phase space representation of quantum mechanics that we have introduced in our previous work. We begin with a brief recall about the so called phase space representation. We give the definition of linear canonical transformation with the transformation law of coordinate and momentum operators. We establish successively the transformation laws of mean values, dispersions, basis state and wave functions.Then we introduce the concept of isodispersion linear canonical transformation.
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.
A Distributional Representation Model For Collaborative Filtering
Junlin, Zhang; Heng, Cai; Tongwen, Huang; Huiping, Xue
2015-01-01
In this paper, we propose a very concise deep learning approach for collaborative filtering that jointly models distributional representation for users and items. The proposed framework obtains better performance when compared against current state-of-art algorithms and that made the distributional representation model a promising direction for further research in the collaborative filtering.
Processes and Reasoning in Representations of Linear Functions
Adu-Gyamfi, Kwaku; Bossé, Michael J.
2014-01-01
This study examined student actions, interpretations, and language in respect to questions raised regarding tabular, graphical, and algebraic representations in the context of functions. The purpose was to investigate students' interpretations and specific ways of working within table, graph, and the algebraic on notions fundamental to a…
Brunton, Steven L; Brunton, Bingni W; Proctor, Joshua L; Kutz, J Nathan
2016-01-01
In this wIn this work, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to an invariant subspace spanned by specially chosen observable functions. The Koopman operator is an infinite-dimensional linear operator that evolves functions of the state of a dynamical system. Dominant terms in the Koopman expansion are typically computed using dynamic mode decomposition (DMD). DMD uses linear measurements of the state variables, and it has recently been shown that this may be too restrictive for nonlinear systems. Choosing the right nonlinear observable functions to form an invariant subspace where it is possible to obtain linear reduced-order models, especially those that are useful for control, is an open challenge. Here, we investigate the choice of observable functions for Koopman analysis that enable the use of optimal linear control techniques on nonlinear problems. First, to include a cost on the state of the system, as in linear quadratic regulator (LQR) control, it is helpful to include these states in the observable subspace, as in DMD. However, we find that this is only possible when there is a single isolated fixed point, as systems with multiple fixed points or more complicated attractors are not globally topologically conjugate to a finite-dimensional linear system, and cannot be represented by a finite-dimensional linear Koopman subspace that includes the state. We then present a data-driven strategy to identify relevant observable functions for Koopman analysis by leveraging a new algorithm to determine relevant terms in a dynamical system by ℓ1-regularized regression of the data in a nonlinear function space; we also show how this algorithm is related to DMD. Finally, we demonstrate the usefulness of nonlinear observable subspaces in the design of Koopman operator optimal control laws for fully nonlinear systems using techniques from linear optimal control.ork, we explore finite
International Nuclear Information System (INIS)
Oeckl, Robert
2012-01-01
We establish a precise isomorphism between the Schrödinger representation and the holomorphic representation in linear and affine field theory. In the linear case, this isomorphism is induced by a one-to-one correspondence between complex structures and Schrödinger vacua. In the affine case we obtain similar results, with the role of the vacuum now taken by a whole family of coherent states. In order to establish these results we exhibit a rigorous construction of the Schrödinger representation and use a suitable generalization of the Segal-Bargmann transform. Our construction is based on geometric quantization and applies to any real polarization and its pairing with any Kähler polarization.
Brunton, Steven L.; Brunton, Bingni W.; Proctor, Joshua L.; Kutz, J. Nathan
2016-01-01
In this work, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to an invariant subspace spanned by specially chosen observable functions. The Koopman operator is an infinite-dimensional linear operator that evolves functions of the state of a dynamical system. Dominant terms in the Koopman expansion are typically computed using dynamic mode decomposition (DMD). DMD uses linear measurements of the state variables, and it has recently been shown that this may be too restrictive for nonlinear systems. Choosing the right nonlinear observable functions to form an invariant subspace where it is possible to obtain linear reduced-order models, especially those that are useful for control, is an open challenge. Here, we investigate the choice of observable functions for Koopman analysis that enable the use of optimal linear control techniques on nonlinear problems. First, to include a cost on the state of the system, as in linear quadratic regulator (LQR) control, it is helpful to include these states in the observable subspace, as in DMD. However, we find that this is only possible when there is a single isolated fixed point, as systems with multiple fixed points or more complicated attractors are not globally topologically conjugate to a finite-dimensional linear system, and cannot be represented by a finite-dimensional linear Koopman subspace that includes the state. We then present a data-driven strategy to identify relevant observable functions for Koopman analysis by leveraging a new algorithm to determine relevant terms in a dynamical system by ℓ1-regularized regression of the data in a nonlinear function space; we also show how this algorithm is related to DMD. Finally, we demonstrate the usefulness of nonlinear observable subspaces in the design of Koopman operator optimal control laws for fully nonlinear systems using techniques from linear optimal control. PMID:26919740
Improving Representational Competence with Concrete Models
Stieff, Mike; Scopelitis, Stephanie; Lira, Matthew E.; DeSutter, Dane
2016-01-01
Representational competence is a primary contributor to student learning in science, technology, engineering, and math (STEM) disciplines and an optimal target for instruction at all educational levels. We describe the design and implementation of a learning activity that uses concrete models to improve students' representational competence and…
Introduction to generalized linear models
Dobson, Annette J
2008-01-01
Introduction Background Scope Notation Distributions Related to the Normal Distribution Quadratic Forms Estimation Model Fitting Introduction Examples Some Principles of Statistical Modeling Notation and Coding for Explanatory Variables Exponential Family and Generalized Linear Models Introduction Exponential Family of Distributions Properties of Distributions in the Exponential Family Generalized Linear Models Examples Estimation Introduction Example: Failure Times for Pressure Vessels Maximum Likelihood Estimation Poisson Regression Example Inference Introduction Sampling Distribution for Score Statistics Taylor Series Approximations Sampling Distribution for MLEs Log-Likelihood Ratio Statistic Sampling Distribution for the Deviance Hypothesis Testing Normal Linear Models Introduction Basic Results Multiple Linear Regression Analysis of Variance Analysis of Covariance General Linear Models Binary Variables and Logistic Regression Probability Distributions ...
(Non) linear regression modelling
Cizek, P.; Gentle, J.E.; Hardle, W.K.; Mori, Y.
2012-01-01
We will study causal relationships of a known form between random variables. Given a model, we distinguish one or more dependent (endogenous) variables Y = (Y1,…,Yl), l ∈ N, which are explained by a model, and independent (exogenous, explanatory) variables X = (X1,…,Xp),p ∈ N, which explain or
Explorative methods in linear models
DEFF Research Database (Denmark)
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....
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
General regression and representation model for classification.
Directory of Open Access Journals (Sweden)
Jianjun Qian
Full Text Available Recently, the regularized coding-based classification methods (e.g. SRC and CRC show a great potential for pattern classification. However, most existing coding methods assume that the representation residuals are uncorrelated. In real-world applications, this assumption does not hold. In this paper, we take account of the correlations of the representation residuals and develop a general regression and representation model (GRR for classification. GRR not only has advantages of CRC, but also takes full use of the prior information (e.g. the correlations between representation residuals and representation coefficients and the specific information (weight matrix of image pixels to enhance the classification performance. GRR uses the generalized Tikhonov regularization and K Nearest Neighbors to learn the prior information from the training data. Meanwhile, the specific information is obtained by using an iterative algorithm to update the feature (or image pixel weights of the test sample. With the proposed model as a platform, we design two classifiers: basic general regression and representation classifier (B-GRR and robust general regression and representation classifier (R-GRR. The experimental results demonstrate the performance advantages of proposed methods over state-of-the-art algorithms.
Exploring multivariate representations of indices along linear geographic features
Bleisch, Susanne; Hollenstein, Daria
2018-05-01
A study of the walkability of a Swiss town required finding suitable representations of multivariate geographical da-ta. The goal was to represent multiple indices of walkability concurrently and visualizing the data along the street network it relates to. Different indices of pedestrian friendliness were assessed for short street sections and then mapped to an overlaid grid. Basic and composite glyphs were designed using square- or triangle-areas to display one to four index values concurrently within the grid structure. Color was used to indicate different indices. Implement-ing visualizations for different combinations of index sets, we find that single values can be emphasized or de-emphasized by selecting the color scheme accordingly and that different color selections either allow perceiving sin-gle values or overall trends over the evaluated area. Values for up to four indices can be displayed in combination within the resulting geovisualizations and the underlying gridded road network references the data to its real world locations.
Linear Parametric Model Checking of Timed Automata
DEFF Research Database (Denmark)
Hune, Tohmas Seidelin; Romijn, Judi; Stoelinga, Mariëlle
2001-01-01
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...... 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...
The effect of linear guide representation for topology optimization on a five-axis milling machine
Yüksel, Esra; Yuksel, Esra
2017-01-01
Topology optimization is a countermeasure to obtain lightweight and stiff structures for machine tools. Topology optimizations are applied at component level due to computational limitations, therefore linear guides’ rolling elements are underestimated in most of the cases. Stiffness of the entire assembly depends on the least stiff components which are identified as linear guides in the current literature. In this study, effects of linear guide’s representation in virtual environment are inv...
Sparse Linear Identifiable Multivariate Modeling
DEFF Research Database (Denmark)
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......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...
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,…
International Nuclear Information System (INIS)
Davis, J. E.; Eddy, M. J.; Sutton, T. M.; Altomari, T. J.
2007-01-01
Solid modeling computer software systems provide for the design of three-dimensional solid models used in the design and analysis of physical components. The current state-of-the-art in solid modeling representation uses a boundary representation format in which geometry and topology are used to form three-dimensional boundaries of the solid. The geometry representation used in these systems is cubic B-spline curves and surfaces - a network of cubic B-spline functions in three-dimensional Cartesian coordinate space. Many Monte Carlo codes, however, use a geometry representation in which geometry units are specified by intersections and unions of half-spaces. This paper describes an algorithm for converting from a boundary representation to a half-space representation. (authors)
Clifford Algebras and Spinorial Representation of Linear Canonical Transformations in Quantum Theory
International Nuclear Information System (INIS)
Raoelina Andriambololona; Ranaivoson, R.T.R.; Rakotoson, H.
2017-11-01
This work is a continuation of previous works that we have done concerning linear canonical transformations and a phase space representation of quantum theory. It is mainly focused on the description of an approach which permits to establish spinorial representation of linear canonical transformations. It begins with an introduction section in which the reason and context of the content are discussed. The introduction section is followed by a brief recall about Clifford algebra and spin group. The description of the approach is started with the presentation of an adequate parameterization of linear canonical transformations which permits to represent them with special pseudo-orthogonal transformations in an operators space. The establishment of the spinorial representation is deduced using relation between special pseudo-orthogonal groups and spin groups. The cases of one dimension quantum mechanics and general multidimensional theory are both studied. The case of linear canonical transformation related to Minkowski space is particularly studied and it is shown that Lorentz transformation may be considered as particular case of linear canonical transformation. Some results from the spinorial representation are also exploited to define operators which may be used to establish equations for fields if one considers the possibility of envisaging a field theory which admits as main symmetry group the group constituted by linear canonical transformations.
Representation of stress distributions inprismatic and cylindrical linear elements
Directory of Open Access Journals (Sweden)
Fernando Giménez-Palomares
2017-08-01
Full Text Available The loads applied on a linear structural element generate internal forces in the cross sections which, in turn, result in stresses along the element. The nature, extent and shape of stress distributions are required parameters to compute the strength of structural elements or machinery components in order to its analysis or design. In this work, it is presented a virtual laboratory which allows to obtain different stress distributions in an isostatic beam, prismatic or cylindrical, subjected to axial forces, shear forces and bending moments. The virtual laboratory permits a great interactivity, allowing the simulation of various real situations in which the user can modify the magnitude and direction of acting loads, and also the boundary conditions of the beam. The ultimate goal of this paper is to present a tool aimed to support the learning and teaching of subjects related to Elasticy and Strength of Materials that are found in bachelor university degrees.
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
Linear and nonlinear optical signals in probability and phase-space representations
International Nuclear Information System (INIS)
Man'ko, Margarita A
2006-01-01
Review of different representations of signals including the phase-space representations and tomographic representations is presented. The signals under consideration are either linear or nonlinear ones. The linear signals satisfy linear quantumlike Schroedinger and von Neumann equations. Nonlinear signals satisfy nonlinear Schroedinger equations as well as Gross-Pitaevskii equation describing solitons in Bose-Einstein condensate. The Ville-Wigner distributions for solitons are considered in comparison with tomographic-probability densities describing solitons completely. different kinds of tomographies - symplectic tomography, optical tomography and Fresnel tomography are reviewed. New kind of map of the signals onto probability distributions of discrete photon number-like variable is discussed. Mutual relations between different transformations of signal functions are established in explicit form. Such characteristics of the signal-probability distribution as entropy is discussed
Internal Representational Models of Attachment Relationships.
Crittenden, Patricia M.
This paper outlines several properties of internal representational models (IRMs) and offers terminology that may help to differentiate the models. Properties of IRMs include focus, memory systems, content, cognitive function, "metastructure," quality of attachment, behavioral strategies, and attitude toward attachment. An IRM focuses on…
L1-norm locally linear representation regularization multi-source adaptation learning.
Tao, Jianwen; Wen, Shiting; Hu, Wenjun
2015-09-01
In most supervised domain adaptation learning (DAL) tasks, one has access only to a small number of labeled examples from target domain. Therefore the success of supervised DAL in this "small sample" regime needs the effective utilization of the large amounts of unlabeled data to extract information that is useful for generalization. Toward this end, we here use the geometric intuition of manifold assumption to extend the established frameworks in existing model-based DAL methods for function learning by incorporating additional information about the target geometric structure of the marginal distribution. We would like to ensure that the solution is smooth with respect to both the ambient space and the target marginal distribution. In doing this, we propose a novel L1-norm locally linear representation regularization multi-source adaptation learning framework which exploits the geometry of the probability distribution, which has two techniques. Firstly, an L1-norm locally linear representation method is presented for robust graph construction by replacing the L2-norm reconstruction measure in LLE with L1-norm one, which is termed as L1-LLR for short. Secondly, considering the robust graph regularization, we replace traditional graph Laplacian regularization with our new L1-LLR graph Laplacian regularization and therefore construct new graph-based semi-supervised learning framework with multi-source adaptation constraint, which is coined as L1-MSAL method. Moreover, to deal with the nonlinear learning problem, we also generalize the L1-MSAL method by mapping the input data points from the input space to a high-dimensional reproducing kernel Hilbert space (RKHS) via a nonlinear mapping. Promising experimental results have been obtained on several real-world datasets such as face, visual video and object. Copyright © 2015 Elsevier Ltd. All rights reserved.
Updating Linear Schedules with Lowest Cost: a Linear Programming Model
Biruk, Sławomir; Jaśkowski, Piotr; Czarnigowska, Agata
2017-10-01
Many civil engineering projects involve sets of tasks repeated in a predefined sequence in a number of work areas along a particular route. A useful graphical representation of schedules of such projects is time-distance diagrams that clearly show what process is conducted at a particular point of time and in particular location. With repetitive tasks, the quality of project performance is conditioned by the ability of the planner to optimize workflow by synchronizing the works and resources, which usually means that resources are planned to be continuously utilized. However, construction processes are prone to risks, and a fully synchronized schedule may expire if a disturbance (bad weather, machine failure etc.) affects even one task. In such cases, works need to be rescheduled, and another optimal schedule should be built for the changed circumstances. This typically means that, to meet the fixed completion date, durations of operations have to be reduced. A number of measures are possible to achieve such reduction: working overtime, employing more resources or relocating resources from less to more critical tasks, but they all come at a considerable cost and affect the whole project. The paper investigates the problem of selecting the measures that reduce durations of tasks of a linear project so that the cost of these measures is kept to the minimum and proposes an algorithm that could be applied to find optimal solutions as the need to reschedule arises. Considering that civil engineering projects, such as road building, usually involve less process types than construction projects, the complexity of scheduling problems is lower, and precise optimization algorithms can be applied. Therefore, the authors put forward a linear programming model of the problem and illustrate its principle of operation with an example.
A Model of Representational Spaces in Human Cortex.
Guntupalli, J Swaroop; Hanke, Michael; Halchenko, Yaroslav O; Connolly, Andrew C; Ramadge, Peter J; Haxby, James V
2016-06-01
Current models of the functional architecture of human cortex emphasize areas that capture coarse-scale features of cortical topography but provide no account for population responses that encode information in fine-scale patterns of activity. Here, we present a linear model of shared representational spaces in human cortex that captures fine-scale distinctions among population responses with response-tuning basis functions that are common across brains and models cortical patterns of neural responses with individual-specific topographic basis functions. We derive a common model space for the whole cortex using a new algorithm, searchlight hyperalignment, and complex, dynamic stimuli that provide a broad sampling of visual, auditory, and social percepts. The model aligns representations across brains in occipital, temporal, parietal, and prefrontal cortices, as shown by between-subject multivariate pattern classification and intersubject correlation of representational geometry, indicating that structural principles for shared neural representations apply across widely divergent domains of information. The model provides a rigorous account for individual variability of well-known coarse-scale topographies, such as retinotopy and category selectivity, and goes further to account for fine-scale patterns that are multiplexed with coarse-scale topographies and carry finer distinctions. © The Author 2016. Published by Oxford University Press.
Decomposable log-linear models
DEFF Research Database (Denmark)
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...... The present paper considers discrete probability models with exact computational properties. In relation to contingency tables this means closed form expressions of the maksimum likelihood estimate and its distribution. The model class includes what is known as decomposable graphicalmodels, which......-hierarchical models, models with structural zeroes, models described by quasi independence and models for level merging. Also, they have a very natural interpretation as they may be formulated by a structured set of conditional independencies between two events given some other event. In relation to contingency...
Linear and Generalized Linear Mixed Models and Their Applications
Jiang, Jiming
2007-01-01
This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models, and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. The book offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it has included recently developed methods, such as mixed model diagnostics, mixed model selection, and jackknife method in the context of mixed models. The book is aimed at students, researchers and other practitioners who are interested
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. Copyright © 2015 Elsevier Inc. All rights reserved.
Asymptotic behaviour of a non-commutative rational series with a nonnegative linear representation
Directory of Open Access Journals (Sweden)
Philippe Dumas
2007-01-01
Full Text Available We analyse the asymptotic behaviour in the mean of a non-commutative rational series, which originates from differential cryptanalysis, using tools from probability theory, and from analytic number theory. We derive a Fourier representation of a first-order summation function obtained by interpreting this rational series as a non-classical rational sequence via the octal numeration system. The method is applicable to a wide class of sequences rational with respect to a numeration system essentially under the condition that they admit a linear representation with nonnegative coefficients.
Modelling Loudspeaker Non-Linearities
DEFF Research Database (Denmark)
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
DEFF Research Database (Denmark)
Bonat, W. H.; Jørgensen, Bent
2016-01-01
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......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...
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
International Nuclear Information System (INIS)
Kalmykov, Mikhail Yu.; Kniehl, Bernd A.
2012-05-01
We argue that the Mellin-Barnes representations of Feynman diagrams can be used for obtaining linear systems of homogeneous differential equations for the original Feynman diagrams with arbitrary powers of propagators without recourse to the integration-by-parts technique. These systems of differential equation can be used (i) for the differential reductions to sets of basic functions and (ii) for counting the numbers of master-integrals.
Integrating piecewise linear representation and ensemble neural network for stock price prediction
Asaduzzaman, Md.; Shahjahan, Md.; Ahmed, Fatema Johera; Islam, Md. Monirul; Murase, Kazuyuki
2014-01-01
Stock Prices are considered to be very dynamic and susceptible to quick changes because of the underlying nature of the financial domain, and in part because of the interchange between known parameters and unknown factors. Of late, several researchers have used Piecewise Linear Representation (PLR) to predict the stock market pricing. However, some improvements are needed to avoid the appropriate threshold of the trading decision, choosing the input index as well as improving the overall perf...
A Cheap Linear Attention Mechanism with Fast Lookups and Fixed-Size Representations
de Brébisson, Alexandre; Vincent, Pascal
2016-01-01
The softmax content-based attention mechanism has proven to be very beneficial in many applications of recurrent neural networks. Nevertheless it suffers from two major computational limitations. First, its computations for an attention lookup scale linearly in the size of the attended sequence. Second, it does not encode the sequence into a fixed-size representation but instead requires to memorize all the hidden states. These two limitations restrict the use of the softmax attention mechani...
Metric versus observable operator representation, higher spin models
Fring, Andreas; Frith, Thomas
2018-02-01
We elaborate further on the metric representation that is obtained by transferring the time-dependence from a Hermitian Hamiltonian to the metric operator in a related non-Hermitian system. We provide further insight into the procedure on how to employ the time-dependent Dyson relation and the quasi-Hermiticity relation to solve time-dependent Hermitian Hamiltonian systems. By solving both equations separately we argue here that it is in general easier to solve the former. We solve the mutually related time-dependent Schrödinger equation for a Hermitian and non-Hermitian spin 1/2, 1 and 3/2 model with time-independent and time-dependent metric, respectively. In all models the overdetermined coupled system of equations for the Dyson map can be decoupled algebraic manipulations and reduces to simple linear differential equations and an equation that can be converted into the non-linear Ermakov-Pinney equation.
Nonabelian Gauged Linear Sigma Model
Institute of Scientific and Technical Information of China (English)
Yongbin RUAN
2017-01-01
The gauged linear sigma model (GLSM for short) is a 2d quantum field theory introduced by Witten twenty years ago.Since then,it has been investigated extensively in physics by Hori and others.Recently,an algebro-geometric theory (for both abelian and nonabelian GLSMs) was developed by the author and his collaborators so that he can start to rigorously compute its invariants and check against physical predications.The abelian GLSM was relatively better understood and is the focus of current mathematical investigation.In this article,the author would like to look over the horizon and consider the nonabelian GLSM.The nonabelian case possesses some new features unavailable to the abelian GLSM.To aid the future mathematical development,the author surveys some of the key problems inspired by physics in the nonabelian GLSM.
Lifted linear phase filter banks and the polyphase-with-advance representation
Energy Technology Data Exchange (ETDEWEB)
Brislawn, C. M. (Christopher M.); Wohlberg, B. E. (Brendt E.)
2004-01-01
A matrix theory is developed for the noncausal polyphase-with-advance representation that underlies the theory of lifted perfect reconstruction filter banks and wavelet transforms as developed by Sweldens and Daubechies. This theory provides the fundamental lifting methodology employed in the ISO/IEC JPEG-2000 still image coding standard, which the authors helped to develop. Lifting structures for polyphase-with-advance filter banks are depicted in Figure 1. In the analysis bank of Figure 1(a), the first lifting step updates x{sub 0} with a filtered version of x{sub 1} and the second step updates x{sub 1} with a filtered version of x{sub 0}; gain factors 1/K and K normalize the lowpass- and highpass-filtered output subbands. Each of these steps is inverted by the corresponding operations in the synthesis bank shown in Figure 1(b). Lifting steps correspond to upper- or lower-triangular matrices, S{sub i}(z), in a cascade-form decomposition of the polyphase analysis matrix, H{sub a}(z). Lifting structures can also be implemented reversibly (i.e., losslessly in fixed-precision arithmetic) by rounding the lifting updates to integer values. Our treatment of the polyphase-with-advance representation develops an extensive matrix algebra framework that goes far beyond the results of. Specifically, we focus on analyzing and implementing linear phase two-channel filter banks via linear phase lifting cascade schemes. Whole-sample symmetric (WS) and half-sample symmetric (HS) linear phase filter banks are characterized completely in terms of the polyphase-with-advance representation. The theory benefits significantly from a number of new group-theoretic structures arising in the polyphase-with-advance matrix algebra from the lifting factorization of linear phase filter banks.
Right-Linear Languages Generated in Systems of Knowledge Representation based on LSG
Directory of Open Access Journals (Sweden)
Daniela Danciulescu
2017-04-01
Full Text Available In Tudor (Preda (2010 a method for formal languages generation based on labeled stratified graph representations is sketched. The author proves that the considered method can generate regular languages and context-sensitive languages by considering an exemplification of the proposed method for a particular regular language and another one for a particular contextsensitive language. At the end of the study, the author highlights some open problems for future research among which we remind: (1 The study of the language families that can be generated by means of these structures; (2 The study of the infiniteness of the languages that can be represented in stratified graphs. In this paper, we extend the method presented in Tudor (Preda(2010, by considering the stratified graph formalism in a system of knowledge representation and reasoning. More precisely, we propose a method that can be applied for generating any Right Linear Language construction. Our method is proved and exemplified in several cases.
Fonger, Nicole L.; Davis, Jon D.; Rohwer, Mary Lou
2018-01-01
This research addresses the issue of how to support students' representational fluency--the ability to create, move within, translate across, and derive meaning from external representations of mathematical ideas. The context of solving linear equations in a combined computer algebra system (CAS) and paper-and-pencil classroom environment is…
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...
Deep supervised, but not unsupervised, models may explain IT cortical representation.
Directory of Open Access Journals (Sweden)
Seyed-Mahdi Khaligh-Razavi
2014-11-01
Full Text Available Inferior temporal (IT cortex in human and nonhuman primates serves visual object recognition. Computational object-vision models, although continually improving, do not yet reach human performance. It is unclear to what extent the internal representations of computational models can explain the IT representation. Here we investigate a wide range of computational model representations (37 in total, testing their categorization performance and their ability to account for the IT representational geometry. The models include well-known neuroscientific object-recognition models (e.g. HMAX, VisNet along with several models from computer vision (e.g. SIFT, GIST, self-similarity features, and a deep convolutional neural network. We compared the representational dissimilarity matrices (RDMs of the model representations with the RDMs obtained from human IT (measured with fMRI and monkey IT (measured with cell recording for the same set of stimuli (not used in training the models. Better performing models were more similar to IT in that they showed greater clustering of representational patterns by category. In addition, better performing models also more strongly resembled IT in terms of their within-category representational dissimilarities. Representational geometries were significantly correlated between IT and many of the models. However, the categorical clustering observed in IT was largely unexplained by the unsupervised models. The deep convolutional network, which was trained by supervision with over a million category-labeled images, reached the highest categorization performance and also best explained IT, although it did not fully explain the IT data. Combining the features of this model with appropriate weights and adding linear combinations that maximize the margin between animate and inanimate objects and between faces and other objects yielded a representation that fully explained our IT data. Overall, our results suggest that explaining
Nonlinear Modeling by Assembling Piecewise Linear Models
Yao, Weigang; Liou, Meng-Sing
2013-01-01
To preserve nonlinearity of a full order system over a parameters range of interest, we propose a simple modeling approach by assembling a set of piecewise local solutions, including the first-order Taylor series terms expanded about some sampling states. The work by Rewienski and White inspired our use of piecewise linear local solutions. The assembly of these local approximations is accomplished by assigning nonlinear weights, through radial basis functions in this study. The efficacy of the proposed procedure is validated for a two-dimensional airfoil moving at different Mach numbers and pitching motions, under which the flow exhibits prominent nonlinear behaviors. All results confirm that our nonlinear model is accurate and stable for predicting not only aerodynamic forces but also detailed flowfields. Moreover, the model is robustness-accurate for inputs considerably different from the base trajectory in form and magnitude. This modeling preserves nonlinearity of the problems considered in a rather simple and accurate manner.
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…
Vortices, semi-local vortices in gauged linear sigma model
International Nuclear Information System (INIS)
Kim, Namkwon
1998-11-01
We consider the static (2+1)D gauged linear sigma model. By analyzing the governing system of partial differential equations, we investigate various aspects of the model. We show the existence of energy finite vortices under a partially broken symmetry on R 2 with the necessary condition suggested by Y. Yang. We also introduce generalized semi-local vortices and show the existence of energy finite semi-local vortices under a certain condition. The vacuum manifold for the semi-local vortices turns out to be graded. Besides, with a special choice of a representation, we show that the O(3) sigma model of which target space is nonlinear is a singular limit of the gauged linear sigma model of which target space is linear. (author)
Core seismic behaviour: linear and non-linear models
International Nuclear Information System (INIS)
Bernard, M.; Van Dorsselaere, M.; Gauvain, M.; Jenapierre-Gantenbein, M.
1981-08-01
The usual methodology for the core seismic behaviour analysis leads to a double complementary approach: to define a core model to be included in the reactor-block seismic response analysis, simple enough but representative of basic movements (diagrid or slab), to define a finer core model, with basic data issued from the first model. This paper presents the history of the different models of both kinds. The inert mass model (IMM) yielded a first rough diagrid movement. The direct linear model (DLM), without shocks and with sodium as an added mass, let to two different ones: DLM 1 with independent movements of the fuel and radial blanket subassemblies, and DLM 2 with a core combined movement. The non-linear (NLM) ''CORALIE'' uses the same basic modelization (Finite Element Beams) but accounts for shocks. It studies the response of a diameter on flats and takes into account the fluid coupling and the wrapper tube flexibility at the pad level. Damping consists of one modal part of 2% and one part due to shocks. Finally, ''CORALIE'' yields the time-history of the displacements and efforts on the supports, but damping (probably greater than 2%) and fluid-structures interaction are still to be precised. The validation experiments were performed on a RAPSODIE core mock-up on scale 1, in similitude of 1/3 as to SPX 1. The equivalent linear model (ELM) was developed for the SPX 1 reactor-block response analysis and a specified seismic level (SB or SM). It is composed of several oscillators fixed to the diagrid and yields the same maximum displacements and efforts than the NLM. The SPX 1 core seismic analysis with a diagrid input spectrum which corresponds to a 0,1 g group acceleration, has been carried out with these models: some aspects of these calculations are presented here
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
Knowledge Representation Using Multilevel Flow Model in Expert System
International Nuclear Information System (INIS)
Wang, Wenlin; Yang, Ming
2015-01-01
As for the knowledge representation, of course, there are a great many methods available for knowledge representation. These include frames, causal models, and many others. This paper presents a novel method called Multilevel Flow Model (MFM), which is used for knowledge representation in G2 expert system. Knowledge representation plays a vital role in constructing knowledge bases. Moreover, it also has impact on building of generic fault model as well as knowledge bases. The MFM is particularly useful to describe system knowledge concisely as domain map in expert system when domain experts are not available
Knowledge Representation Using Multilevel Flow Model in Expert System
Energy Technology Data Exchange (ETDEWEB)
Wang, Wenlin; Yang, Ming [Harbin Engineering University, Harbin (China)
2015-05-15
As for the knowledge representation, of course, there are a great many methods available for knowledge representation. These include frames, causal models, and many others. This paper presents a novel method called Multilevel Flow Model (MFM), which is used for knowledge representation in G2 expert system. Knowledge representation plays a vital role in constructing knowledge bases. Moreover, it also has impact on building of generic fault model as well as knowledge bases. The MFM is particularly useful to describe system knowledge concisely as domain map in expert system when domain experts are not available.
High dimensional model representation method for fuzzy structural dynamics
Adhikari, S.; Chowdhury, R.; Friswell, M. I.
2011-03-01
Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.
Sparse Representation Based Binary Hypothesis Model for Hyperspectral Image Classification
Directory of Open Access Journals (Sweden)
Yidong Tang
2016-01-01
Full Text Available The sparse representation based classifier (SRC and its kernel version (KSRC have been employed for hyperspectral image (HSI classification. However, the state-of-the-art SRC often aims at extended surface objects with linear mixture in smooth scene and assumes that the number of classes is given. Considering the small target with complex background, a sparse representation based binary hypothesis (SRBBH model is established in this paper. In this model, a query pixel is represented in two ways, which are, respectively, by background dictionary and by union dictionary. The background dictionary is composed of samples selected from the local dual concentric window centered at the query pixel. Thus, for each pixel the classification issue becomes an adaptive multiclass classification problem, where only the number of desired classes is required. Furthermore, the kernel method is employed to improve the interclass separability. In kernel space, the coding vector is obtained by using kernel-based orthogonal matching pursuit (KOMP algorithm. Then the query pixel can be labeled by the characteristics of the coding vectors. Instead of directly using the reconstruction residuals, the different impacts the background dictionary and union dictionary have on reconstruction are used for validation and classification. It enhances the discrimination and hence improves the performance.
Directory of Open Access Journals (Sweden)
Chao Luo
Full Text Available A novel algebraic approach is proposed to study dynamics of asynchronous random Boolean networks where a random number of nodes can be updated at each time step (ARBNs. In this article, the logical equations of ARBNs are converted into the discrete-time linear representation and dynamical behaviors of systems are investigated. We provide a general formula of network transition matrices of ARBNs as well as a necessary and sufficient algebraic criterion to determine whether a group of given states compose an attractor of length[Formula: see text] in ARBNs. Consequently, algorithms are achieved to find all of the attractors and basins in ARBNs. Examples are showed to demonstrate the feasibility of the proposed scheme.
Actuarial statistics with generalized linear mixed models
Antonio, K.; Beirlant, J.
2007-01-01
Over the last decade the use of generalized linear models (GLMs) in actuarial statistics has received a lot of attention, starting from the actuarial illustrations in the standard text by McCullagh and Nelder [McCullagh, P., Nelder, J.A., 1989. Generalized linear models. In: Monographs on Statistics
International Nuclear Information System (INIS)
Khrennikov, A.
2005-01-01
We constructed the representation of contextual probabilistic dynamics in the complex Hilbert space. Thus dynamics of the wave function can be considered as Hilbert space projection of realistic dynamics in a pre space. The basic condition for representing the pre space-dynamics is the law of statistical conservation of energy-conservation of probabilities. The construction of the dynamical representation is an important step in the development of contextual statistical viewpoint of quantum processes. But the contextual statistical model is essentially more general than the quantum one. Therefore in general the Hilbert space projection of the pre space dynamics can be nonlinear and even irreversible (but it is always unitary). There were found conditions of linearity and reversibility of the Hilbert space dynamical projection. We also found conditions for the conventional Schrodinger dynamics (including time-dependent Hamiltonians). We remark that in general even the Schrodinger dynamics is based just on the statistical conservation of energy; for individual systems the law of conservation of energy can be violated (at least in our theoretical model)
National Research Council Canada - National Science Library
Little, Daniel
2006-01-01
...). The reason this is so is due to hierarchies that we take for granted. By hierarchies I mean that there is a layer of representation of us as individuals, as military professional, as members of a military unit and as citizens of an entire nation...
Comparing linear probability model coefficients across groups
DEFF Research Database (Denmark)
Holm, Anders; Ejrnæs, Mette; Karlson, Kristian Bernt
2015-01-01
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......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....
Maximum error-bounded Piecewise Linear Representation for online stream approximation
Xie, Qing; Pang, Chaoyi; Zhou, Xiaofang; Zhang, Xiangliang; Deng, Ke
2014-01-01
Given a time series data stream, the generation of error-bounded Piecewise Linear Representation (error-bounded PLR) is to construct a number of consecutive line segments to approximate the stream, such that the approximation error does not exceed a prescribed error bound. In this work, we consider the error bound in L∞ norm as approximation criterion, which constrains the approximation error on each corresponding data point, and aim on designing algorithms to generate the minimal number of segments. In the literature, the optimal approximation algorithms are effectively designed based on transformed space other than time-value space, while desirable optimal solutions based on original time domain (i.e., time-value space) are still lacked. In this article, we proposed two linear-time algorithms to construct error-bounded PLR for data stream based on time domain, which are named OptimalPLR and GreedyPLR, respectively. The OptimalPLR is an optimal algorithm that generates minimal number of line segments for the stream approximation, and the GreedyPLR is an alternative solution for the requirements of high efficiency and resource-constrained environment. In order to evaluate the superiority of OptimalPLR, we theoretically analyzed and compared OptimalPLR with the state-of-art optimal solution in transformed space, which also achieves linear complexity. We successfully proved the theoretical equivalence between time-value space and such transformed space, and also discovered the superiority of OptimalPLR on processing efficiency in practice. The extensive results of empirical evaluation support and demonstrate the effectiveness and efficiency of our proposed algorithms.
Maximum error-bounded Piecewise Linear Representation for online stream approximation
Xie, Qing
2014-04-04
Given a time series data stream, the generation of error-bounded Piecewise Linear Representation (error-bounded PLR) is to construct a number of consecutive line segments to approximate the stream, such that the approximation error does not exceed a prescribed error bound. In this work, we consider the error bound in L∞ norm as approximation criterion, which constrains the approximation error on each corresponding data point, and aim on designing algorithms to generate the minimal number of segments. In the literature, the optimal approximation algorithms are effectively designed based on transformed space other than time-value space, while desirable optimal solutions based on original time domain (i.e., time-value space) are still lacked. In this article, we proposed two linear-time algorithms to construct error-bounded PLR for data stream based on time domain, which are named OptimalPLR and GreedyPLR, respectively. The OptimalPLR is an optimal algorithm that generates minimal number of line segments for the stream approximation, and the GreedyPLR is an alternative solution for the requirements of high efficiency and resource-constrained environment. In order to evaluate the superiority of OptimalPLR, we theoretically analyzed and compared OptimalPLR with the state-of-art optimal solution in transformed space, which also achieves linear complexity. We successfully proved the theoretical equivalence between time-value space and such transformed space, and also discovered the superiority of OptimalPLR on processing efficiency in practice. The extensive results of empirical evaluation support and demonstrate the effectiveness and efficiency of our proposed algorithms.
International Nuclear Information System (INIS)
Ehsani, Amir
2015-01-01
Algebras with a pair of non-associative binary operations (f, g) which are satisfy in the balanced quadratic functional equations with four object variables considered. First, we obtain a linear representation for the operations, of this kind of binary algebras (A,f,g), over an abelian group (A, +) and then we generalize the linear representation of operations, to an algebra (A,F) with non-associative binary operations which are satisfy in the balanced quadratic functional equations with four object variables. (paper)
Minimal representations of supersymmetry and 1D N-extended σ-models
International Nuclear Information System (INIS)
Toppan, Francesco
2008-01-01
We discuss the minimal representations of the 1D N-Extended Supersymmetry algebra (the Z 2 -graded symmetry algebra of the Supersymmetric Quantum Mechanics) linearly realized on a finite number of fields depending on a real parameter t, the time. Their knowledge allows to construct one-dimensional sigma-models with extended off-shell supersymmetries without using superfields (author)
Spaghetti Bridges: Modeling Linear Relationships
Kroon, Cindy D.
2016-01-01
Mathematics and science are natural partners. One of many examples of this partnership occurs when scientific observations are made, thus providing data that can be used for mathematical modeling. Developing mathematical relationships elucidates such scientific principles. This activity describes a data-collection activity in which students employ…
Do Knowledge-Component Models Need to Incorporate Representational Competencies?
Rau, Martina Angela
2017-01-01
Traditional knowledge-component models describe students' content knowledge (e.g., their ability to carry out problem-solving procedures or their ability to reason about a concept). In many STEM domains, instruction uses multiple visual representations such as graphs, figures, and diagrams. The use of visual representations implies a…
Non-linear finite element modeling
DEFF Research Database (Denmark)
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...
Correlations and Non-Linear Probability Models
DEFF Research Database (Denmark)
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....
2006-09-01
two weeks to arrive. Source: http://beergame.mit.edu/ Permission Granted – MIT Supply Chain Forum 2005 Professor Sterman –Sloan School of...Management - MITSource: http://web.mit.edu/jsterman/www/ SDG /beergame.html Rules of Engagement The MIT Beer Game Simulation 04-04 Slide Number 10 Professor...Sterman –Sloan School of Management - MITSource: http://web.mit.edu/jsterman/www/ SDG /beergame.html What is the Significance of Representation
Utility of low-order linear nuclear-power-plant models in plant diagnostics and control
International Nuclear Information System (INIS)
Tylee, J.L.
1981-01-01
A low-order, linear model of a pressurized water reactor (PWR) plant is described and evaluated. The model consists of 23 linear, first-order difference equations and simulates all subsystems of both the primary and secondary sides of the plant. Comparisons between the calculated model response and available test data show the model to be an adequate representation of the actual plant dynamics. Suggested use for the model in an on-line digital plant diagnostics and control system are presented
Extended Linear Models with Gaussian Priors
DEFF Research Database (Denmark)
Quinonero, Joaquin
2002-01-01
In extended linear models the input space is projected onto a feature space by means of an arbitrary non-linear transformation. A linear model is then applied to the feature space to construct the model output. The dimension of the feature space can be very large, or even infinite, giving the model...... a very big flexibility. Support Vector Machines (SVM's) and Gaussian processes are two examples of such models. In this technical report I present a model in which the dimension of the feature space remains finite, and where a Bayesian approach is used to train the model with Gaussian priors...... 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....
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...
Linear mixed models in sensometrics
DEFF Research Database (Denmark)
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...... an open-source software tool ConsumerCheck was developed in this project and now is available for everyone. will represent a major step forward when concerns this important problem in modern consumer driven product development. Standard statistical software packages can be used for some of the purposes......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...
Two problems from the theory of semiotic control models. I. Representations of semiotic models
Energy Technology Data Exchange (ETDEWEB)
Osipov, G S
1981-11-01
Two problems from the theory of semiotic control models are being stated, in particular the representation of models and the semantic analysis of themtheory of semiotic control models are being stated, in particular the representation of models and the semantic analysis of them. Algebraic representation of semiotic models, covering of representations, their reduction and equivalence are discussed. The interrelations between functional and structural characteristics of semiotic models are investigated. 20 references.
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
A Knowledge-Based Representation Scheme for Environmental Science Models
Keller, Richard M.; Dungan, Jennifer L.; Lum, Henry, Jr. (Technical Monitor)
1994-01-01
One of the primary methods available for studying environmental phenomena is the construction and analysis of computational models. We have been studying how artificial intelligence techniques can be applied to assist in the development and use of environmental science models within the context of NASA-sponsored activities. We have identified several high-utility areas as potential targets for research and development: model development; data visualization, analysis, and interpretation; model publishing and reuse, training and education; and framing, posing, and answering questions. Central to progress on any of the above areas is a representation for environmental models that contains a great deal more information than is present in a traditional software implementation. In particular, a traditional software implementation is devoid of any semantic information that connects the code with the environmental context that forms the background for the modeling activity. Before we can build AI systems to assist in model development and usage, we must develop a representation for environmental models that adequately describes a model's semantics and explicitly represents the relationship between the code and the modeling task at hand. We have developed one such representation in conjunction with our work on the SIGMA (Scientists' Intelligent Graphical Modeling Assistant) environment. The key feature of the representation is that it provides a semantic grounding for the symbols in a set of modeling equations by linking those symbols to an explicit representation of the underlying environmental scenario.
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
BIM-enabled Conceptual Modelling and Representation of Building Circulation
Lee, Jin Kook; Kim, Mi Jeong
2014-01-01
This paper describes how a building information modelling (BIM)-based approach for building circulation enables us to change the process of building design in terms of its computational representation and processes, focusing on the conceptual modelling and representation of circulation within buildings. BIM has been designed for use by several BIM authoring tools, in particular with the widely known interoperable industry foundation classes (IFCs), which follow an object-oriented data modelli...
Converting biomolecular modelling data based on an XML representation.
Sun, Yudong; McKeever, Steve
2008-08-25
Biomolecular modelling has provided computational simulation based methods for investigating biological processes from quantum chemical to cellular levels. Modelling such microscopic processes requires atomic description of a biological system and conducts in fine timesteps. Consequently the simulations are extremely computationally demanding. To tackle this limitation, different biomolecular models have to be integrated in order to achieve high-performance simulations. The integration of diverse biomolecular models needs to convert molecular data between different data representations of different models. This data conversion is often non-trivial, requires extensive human input and is inevitably error prone. In this paper we present an automated data conversion method for biomolecular simulations between molecular dynamics and quantum mechanics/molecular mechanics models. Our approach is developed around an XML data representation called BioSimML (Biomolecular Simulation Markup Language). BioSimML provides a domain specific data representation for biomolecular modelling which can effciently support data interoperability between different biomolecular simulation models and data formats.
A linear model of ductile plastic damage
International Nuclear Information System (INIS)
Lemaitre, J.
1983-01-01
A three-dimensional model of isotropic ductile plastic damage based on a continuum damage variable on the effective stress concept and on thermodynamics is derived. As shown by experiments on several metals and alloys, the model, integrated in the case of proportional loading, is linear with respect to the accumulated plastic strain and shows a large influence of stress triaxiality [fr
Ker, H. W.
2014-01-01
Multilevel data are very common in educational research. Hierarchical linear models/linear mixed-effects models (HLMs/LMEs) are often utilized to analyze multilevel data nowadays. This paper discusses the problems of utilizing ordinary regressions for modeling multilevel educational data, compare the data analytic results from three regression…
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 ...
Cognition and procedure representational requirements for predictive human performance models
Corker, K.
1992-01-01
Models and modeling environments for human performance are becoming significant contributors to early system design and analysis procedures. Issues of levels of automation, physical environment, informational environment, and manning requirements are being addressed by such man/machine analysis systems. The research reported here investigates the close interaction between models of human cognition and models that described procedural performance. We describe a methodology for the decomposition of aircrew procedures that supports interaction with models of cognition on the basis of procedures observed; that serves to identify cockpit/avionics information sources and crew information requirements; and that provides the structure to support methods for function allocation among crew and aiding systems. Our approach is to develop an object-oriented, modular, executable software representation of the aircrew, the aircraft, and the procedures necessary to satisfy flight-phase goals. We then encode in a time-based language, taxonomies of the conceptual, relational, and procedural constraints among the cockpit avionics and control system and the aircrew. We have designed and implemented a goals/procedures hierarchic representation sufficient to describe procedural flow in the cockpit. We then execute the procedural representation in simulation software and calculate the values of the flight instruments, aircraft state variables and crew resources using the constraints available from the relationship taxonomies. The system provides a flexible, extensible, manipulative and executable representation of aircrew and procedures that is generally applicable to crew/procedure task-analysis. The representation supports developed methods of intent inference, and is extensible to include issues of information requirements and functional allocation. We are attempting to link the procedural representation to models of cognitive functions to establish several intent inference methods
Ground Motion Models for Future Linear Colliders
International Nuclear Information System (INIS)
Seryi, Andrei
2000-01-01
Optimization of the parameters of a future linear collider requires comprehensive models of ground motion. Both general models of ground motion and specific models of the particular site and local conditions are essential. Existing models are not completely adequate, either because they are too general, or because they omit important peculiarities of ground motion. The model considered in this paper is based on recent ground motion measurements performed at SLAC and at other accelerator laboratories, as well as on historical data. The issues to be studied for the models to become more predictive are also discussed
Cohen, Dale J; Quinlan, Philip T
2018-02-01
The bounded number-line task has been used extensively to assess the numerical competence of both children and adults. One consistent finding has been that young children display a logarithmic response function, whereas older children and adults display a more linear response function. Traditionally, these log-linear functions have been interpreted as providing a transparent window onto the nature of the participants' psychological representations of quantity (termed here a direct response strategy). Here we show that the direct response strategy produces the log-linear response function regardless of whether the psychological representation of quantity is compressive or expansive. Simply put, the log-linear response function results from task constraints rather than from the psychological representation of quantities. We also demonstrate that a proportion/subtraction response strategy produces response patterns that almost perfectly correlate with the psychological representation of quantity. We therefore urge researchers not to interpret the log-linear response pattern in terms of numerical representation.
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 linear models; 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.
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.
Modelling point patterns with linear structures
DEFF Research Database (Denmark)
Møller, Jesper; Rasmussen, Jakob Gulddahl
2009-01-01
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...... consider simulations of this model and compare with real data....
Modelling point patterns with linear structures
DEFF Research Database (Denmark)
Møller, Jesper; Rasmussen, Jakob Gulddahl
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...... consider simulations of this model and compare with real data....
Optimal designs for linear mixture models
Mendieta, E.J.; Linssen, H.N.; Doornbos, R.
1975-01-01
In a recent paper Snee and Marquardt [8] considered designs for linear mixture models, where the components are subject to individual lower and/or upper bounds. When the number of components is large their algorithm XVERT yields designs far too extensive for practical purposes. The purpose of this
Optimal designs for linear mixture models
Mendieta, E.J.; Linssen, H.N.; Doornbos, R.
1975-01-01
In a recent paper Snee and Marquardt (1974) considered designs for linear mixture models, where the components are subject to individual lower and/or upper bounds. When the number of components is large their algorithm XVERT yields designs far too extensive for practical purposes. The purpose of
Linear factor copula models and their properties
Krupskii, Pavel; Genton, Marc G.
2018-01-01
We consider a special case of factor copula models with additive common factors and independent components. These models are flexible and parsimonious with O(d) parameters where d is the dimension. The linear structure allows one to obtain closed form expressions for some copulas and their extreme‐value limits. These copulas can be used to model data with strong tail dependencies, such as extreme data. We study the dependence properties of these linear factor copula models and derive the corresponding limiting extreme‐value copulas with a factor structure. We show how parameter estimates can be obtained for these copulas and apply one of these copulas to analyse a financial data set.
Linear factor copula models and their properties
Krupskii, Pavel
2018-04-25
We consider a special case of factor copula models with additive common factors and independent components. These models are flexible and parsimonious with O(d) parameters where d is the dimension. The linear structure allows one to obtain closed form expressions for some copulas and their extreme‐value limits. These copulas can be used to model data with strong tail dependencies, such as extreme data. We study the dependence properties of these linear factor copula models and derive the corresponding limiting extreme‐value copulas with a factor structure. We show how parameter estimates can be obtained for these copulas and apply one of these copulas to analyse a financial data set.
Diagnostics for Linear Models With Functional Responses
Xu, Hongquan; Shen, Qing
2005-01-01
Linear models where the response is a function and the predictors are vectors are useful in analyzing data from designed experiments and other situations with functional observations. Residual analysis and diagnostics are considered for such models. Studentized residuals are defined and their properties are studied. Chi-square quantile-quantile plots are proposed to check the assumption of Gaussian error process and outliers. Jackknife residuals and an associated test are proposed to det...
Non-linear Loudspeaker Unit Modelling
DEFF Research Database (Denmark)
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 thr...... frequencies and different displacement levels. The model errors are discussed and analysed including a test with loudspeaker unit where the diaphragm is removed....
A quasi-linear gyrokinetic transport model for tokamak plasmas
International Nuclear Information System (INIS)
Casati, A.
2009-10-01
After a presentation of some basics around nuclear fusion, this research thesis introduces the framework of the tokamak strategy to deal with confinement, hence the main plasma instabilities which are responsible for turbulent transport of energy and matter in such a system. The author also briefly introduces the two principal plasma representations, the fluid and the kinetic ones. He explains why the gyro-kinetic approach has been preferred. A tokamak relevant case is presented in order to highlight the relevance of a correct accounting of the kinetic wave-particle resonance. He discusses the issue of the quasi-linear response. Firstly, the derivation of the model, called QuaLiKiz, and its underlying hypotheses to get the energy and the particle turbulent flux are presented. Secondly, the validity of the quasi-linear response is verified against the nonlinear gyro-kinetic simulations. The saturation model that is assumed in QuaLiKiz, is presented and discussed. Then, the author qualifies the global outcomes of QuaLiKiz. Both the quasi-linear energy and the particle flux are compared to the expectations from the nonlinear simulations, across a wide scan of tokamak relevant parameters. Therefore, the coupling of QuaLiKiz within the integrated transport solver CRONOS is presented: this procedure allows the time-dependent transport problem to be solved, hence the direct application of the model to the experiment. The first preliminary results regarding the experimental analysis are finally discussed
On push-forward representations in the standard gyrokinetic model
International Nuclear Information System (INIS)
Miyato, N.; Yagi, M.; Scott, B. D.
2015-01-01
Two representations of fluid moments in terms of a gyro-center distribution function and gyro-center coordinates, which are called push-forward representations, are compared in the standard electrostatic gyrokinetic model. In the representation conventionally used to derive the gyrokinetic Poisson equation, the pull-back transformation of the gyro-center distribution function contains effects of the gyro-center transformation and therefore electrostatic potential fluctuations, which is described by the Poisson brackets between the distribution function and scalar functions generating the gyro-center transformation. Usually, only the lowest order solution of the generating function at first order is considered to explicitly derive the gyrokinetic Poisson equation. This is true in explicitly deriving representations of scalar fluid moments with polarization terms. One also recovers the particle diamagnetic flux at this order because it is associated with the guiding-center transformation. However, higher-order solutions are needed to derive finite Larmor radius terms of particle flux including the polarization drift flux from the conventional representation. On the other hand, the lowest order solution is sufficient for the other representation, in which the gyro-center transformation part is combined with the guiding-center one and the pull-back transformation of the distribution function does not appear
On push-forward representations in the standard gyrokinetic model
Energy Technology Data Exchange (ETDEWEB)
Miyato, N., E-mail: miyato.naoaki@jaea.go.jp; Yagi, M. [Japan Atomic Energy Agency, 2-116 Omotedate, Obuchi, Rokkasho, Aomori 039-3212 (Japan); Scott, B. D. [Max-Planck-Institut für Plasmaphysik, D-85748 Garching (Germany)
2015-01-15
Two representations of fluid moments in terms of a gyro-center distribution function and gyro-center coordinates, which are called push-forward representations, are compared in the standard electrostatic gyrokinetic model. In the representation conventionally used to derive the gyrokinetic Poisson equation, the pull-back transformation of the gyro-center distribution function contains effects of the gyro-center transformation and therefore electrostatic potential fluctuations, which is described by the Poisson brackets between the distribution function and scalar functions generating the gyro-center transformation. Usually, only the lowest order solution of the generating function at first order is considered to explicitly derive the gyrokinetic Poisson equation. This is true in explicitly deriving representations of scalar fluid moments with polarization terms. One also recovers the particle diamagnetic flux at this order because it is associated with the guiding-center transformation. However, higher-order solutions are needed to derive finite Larmor radius terms of particle flux including the polarization drift flux from the conventional representation. On the other hand, the lowest order solution is sufficient for the other representation, in which the gyro-center transformation part is combined with the guiding-center one and the pull-back transformation of the distribution function does not appear.
A Description Logic Based Knowledge Representation Model for Concept Understanding
DEFF Research Database (Denmark)
Badie, Farshad
2017-01-01
This research employs Description Logics in order to focus on logical description and analysis of the phenomenon of ‘concept understanding’. The article will deal with a formal-semantic model for figuring out the underlying logical assumptions of ‘concept understanding’ in knowledge representation...... systems. In other words, it attempts to describe a theoretical model for concept understanding and to reflect the phenomenon of ‘concept understanding’ in terminological knowledge representation systems. Finally, it will design an ontology that schemes the structure of concept understanding based...
A Fuzzy Knowledge Representation Model for Student Performance Assessment
DEFF Research Database (Denmark)
Badie, Farshad
Knowledge representation models based on Fuzzy Description Logics (DLs) can provide a foundation for reasoning in intelligent learning environments. While basic DLs are suitable for expressing crisp concepts and binary relationships, Fuzzy DLs are capable of processing degrees of truth/completene......Knowledge representation models based on Fuzzy Description Logics (DLs) can provide a foundation for reasoning in intelligent learning environments. While basic DLs are suitable for expressing crisp concepts and binary relationships, Fuzzy DLs are capable of processing degrees of truth....../completeness about vague or imprecise information. This paper tackles the issue of representing fuzzy classes using OWL2 in a dataset describing Performance Assessment Results of Students (PARS)....
Yanti, Y. R.; Amin, S. M.; Sulaiman, R.
2018-01-01
This study described representation of students who have musical, logical-mathematic and naturalist intelligence in solving a problem. Subjects were selected on the basis of multiple intelligence tests (TPM) consists of 108 statements, with 102 statements adopted from Chislet and Chapman and 6 statements equal to eksistensial intelligences. Data were analyzed based on problem-solving tests (TPM) and interviewing. See the validity of the data then problem-solving tests (TPM) and interviewing is given twice with an analyzed using the representation indikator and the problem solving step. The results showed that: the stage of presenting information known, stage of devising a plan, and stage of carrying out the plan those three subjects were using same form of representation. While he stage of presenting information asked and stage of looking back, subject of logical-mathematic was using different forms of representation with subjects of musical and naturalist intelligence. From this research is expected to provide input to the teacher in determining the learning strategy that will be used by considering the representation of students with the basis of multiple intelligences.
[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.
Effect Displays in R for Generalised Linear Models
Directory of Open Access Journals (Sweden)
John Fox
2003-07-01
Full Text Available This paper describes the implementation in R of a method for tabular or graphical display of terms in a complex generalised linear model. By complex, I mean a model that contains terms related by marginality or hierarchy, such as polynomial terms, or main effects and interactions. I call these tables or graphs effect displays. Effect displays are constructed by identifying high-order terms in a generalised linear model. Fitted values under the model are computed for each such term. The lower-order "relatives" of a high-order term (e.g., main effects marginal to an interaction are absorbed into the term, allowing the predictors appearing in the high-order term to range over their values. The values of other predictors are fixed at typical values: for example, a covariate could be fixed at its mean or median, a factor at its proportional distribution in the data, or to equal proportions in its several levels. Variations of effect displays are also described, including representation of terms higher-order to any appearing in the model.
Crystal structure representations for machine learning models of formation energies
Energy Technology Data Exchange (ETDEWEB)
Faber, Felix [Department of Chemistry, Institute of Physical Chemistry and National Center for Computational Design and Discovery of Novel Materials, University of Basel Switzerland; Lindmaa, Alexander [Department of Physics, Chemistry and Biology, Linköping University, SE-581 83 Linköping Sweden; von Lilienfeld, O. Anatole [Department of Chemistry, Institute of Physical Chemistry and National Center for Computational Design and Discovery of Novel Materials, University of Basel Switzerland; Argonne Leadership Computing Facility, Argonne National Laboratory, 9700 S. Cass Avenue Lemont Illinois 60439; Armiento, Rickard [Department of Physics, Chemistry and Biology, Linköping University, SE-581 83 Linköping Sweden
2015-04-20
We introduce and evaluate a set of feature vector representations of crystal structures for machine learning (ML) models of formation energies of solids. ML models of atomization energies of organic molecules have been successful using a Coulomb matrix representation of the molecule. We consider three ways to generalize such representations to periodic systems: (i) a matrix where each element is related to the Ewald sum of the electrostatic interaction between two different atoms in the unit cell repeated over the lattice; (ii) an extended Coulomb-like matrix that takes into account a number of neighboring unit cells; and (iii) an ansatz that mimics the periodicity and the basic features of the elements in the Ewald sum matrix using a sine function of the crystal coordinates of the atoms. The representations are compared for a Laplacian kernel with Manhattan norm, trained to reproduce formation energies using a dataset of 3938 crystal structures obtained from the Materials Project. For training sets consisting of 3000 crystals, the generalization error in predicting formation energies of new structures corresponds to (i) 0.49, (ii) 0.64, and (iii) 0.37eV/atom for the respective representations.
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.
Modeling of Volatility with Non-linear Time Series Model
Kim Song Yon; Kim Mun Chol
2013-01-01
In this paper, non-linear time series models are used to describe volatility in financial time series data. To describe volatility, two of the non-linear time series are combined into form TAR (Threshold Auto-Regressive Model) with AARCH (Asymmetric Auto-Regressive Conditional Heteroskedasticity) error term and its parameter estimation is studied.
Thresholding projection estimators in functional linear models
Cardot, Hervé; Johannes, Jan
2010-01-01
We consider the problem of estimating the regression function in functional linear regression models by proposing a new type of projection estimators which combine dimension reduction and thresholding. The introduction of a threshold rule allows to get consistency under broad assumptions as well as minimax rates of convergence under additional regularity hypotheses. We also consider the particular case of Sobolev spaces generated by the trigonometric basis which permits to get easily mean squ...
Decomposed Implicit Models of Piecewise - Linear Networks
Directory of Open Access Journals (Sweden)
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.
A knowledge representation model for the optimisation of electricity generation mixes
International Nuclear Information System (INIS)
Chee Tahir, Aidid; Bañares-Alcántara, René
2012-01-01
Highlights: ► Prototype energy model which uses semantic representation (ontologies). ► Model accepts both quantitative and qualitative based energy policy goals. ► Uses logic inference to formulate equations for linear optimisation. ► Proposes electricity generation mix based on energy policy goals. -- Abstract: Energy models such as MARKAL, MESSAGE and DNE-21 are optimisation tools which aid in the formulation of energy policies. The strength of these models lie in their solid theoretical foundations built on rigorous mathematical equations designed to process numerical (quantitative) data related to economics and the environment. Nevertheless, a complete consideration of energy policy issues also requires the consideration of the political and social aspects of energy. These political and social issues are often associated with non-numerical (qualitative) information. To enable the evaluation of these aspects in a computer model, we hypothesise that a different approach to energy model optimisation design is required. A prototype energy model that is based on a semantic representation using ontologies and is integrated to engineering models implemented in Java has been developed. The model provides both quantitative and qualitative evaluation capabilities through the use of logical inference. The semantic representation of energy policy goals is used (i) to translate a set of energy policy goals into a set of logic queries which is then used to determine the preferred electricity generation mix and (ii) to assist in the formulation of a set of equations which is then solved in order to obtain a proposed electricity generation mix. Scenario case studies have been developed and tested on the prototype energy model to determine its capabilities. Knowledge queries were made on the semantic representation to determine an electricity generation mix which fulfilled a set of energy policy goals (e.g. CO 2 emissions reduction, water conservation, energy supply
From the Osterwalder canvas to an alternative business model representation
Verrue, Johan
2015-01-01
The Osterwalder business model canvas (BMC) is used by many entrepreneurs, managers, consultants and business schools. In our research we have investigated whether the canvas is a valid instrument for gaining an in-depth, accurate insight into business models. Therefore we have performed initial multiple case study research which concluded that the canvas does not generate valid business model (BM) representations. In our second multiple case study, we have constructed an alternative BM frame...
Optical model representation of coupled channel effects
International Nuclear Information System (INIS)
Wall, N.S.; Cowley, A.A.; Johnson, R.C.; Kobas, A.M.
1977-01-01
A modification to the usual 6-parameter Woods-Saxon parameterization of the optical model for the scattering of composite particles is proposed. This additional real term reflects the effect of coupling other channels to the elastic scattering. The analyses favor a repulsive interaction for this term, especially for alpha particles. It is found that the repulsive term when combined with a Woods-Saxon term yields potentials with central values and volume integrals similar to those found by uncoupled elastic scattering calculations. These values are V(r = 0) approximately equal to 125 MeV and J/4A approximately equal to 300 MeV-fm 3
A Fuzzy Knowledge Representation Model for Student Performance Assessment
DEFF Research Database (Denmark)
Badie, Farshad
Knowledge representation models based on Fuzzy Description Logics (DLs) can provide a foundation for reasoning in intelligent learning environments. While basic DLs are suitable for expressing crisp concepts and binary relationships, Fuzzy DLs are capable of processing degrees of truth/completene...
Thinking Egyptian: Active Models for Understanding Spatial Representation.
Schiferl, Ellen
This paper highlights how introductory textbooks on Egyptian art inhibit understanding by reinforcing student preconceptions, and demonstrates another approach to discussing space with a classroom exercise and software. The alternative approach, an active model for spatial representation, introduced here was developed by adapting classroom…
From spiking neuron models to linear-nonlinear models.
Ostojic, Srdjan; Brunel, Nicolas
2011-01-20
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.
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...
Multiscale geometric modeling of macromolecules II: Lagrangian representation
Feng, Xin; Xia, Kelin; Chen, Zhan; Tong, Yiying; Wei, Guo-Wei
2013-01-01
Geometric modeling of biomolecules plays an essential role in the conceptualization of biolmolecular structure, function, dynamics and transport. Qualitatively, geometric modeling offers a basis for molecular visualization, which is crucial for the understanding of molecular structure and interactions. Quantitatively, geometric modeling bridges the gap between molecular information, such as that from X-ray, NMR and cryo-EM, and theoretical/mathematical models, such as molecular dynamics, the Poisson-Boltzmann equation and the Nernst-Planck equation. In this work, we present a family of variational multiscale geometric models for macromolecular systems. Our models are able to combine multiresolution geometric modeling with multiscale electrostatic modeling in a unified variational framework. We discuss a suite of techniques for molecular surface generation, molecular surface meshing, molecular volumetric meshing, and the estimation of Hadwiger’s functionals. Emphasis is given to the multiresolution representations of biomolecules and the associated multiscale electrostatic analyses as well as multiresolution curvature characterizations. The resulting fine resolution representations of a biomolecular system enable the detailed analysis of solvent-solute interaction, and ion channel dynamics, while our coarse resolution representations highlight the compatibility of protein-ligand bindings and possibility of protein-protein interactions. PMID:23813599
Converting Biomolecular Modelling Data Based on an XML Representation
Directory of Open Access Journals (Sweden)
Sun Yudong
2008-06-01
Full Text Available Biomolecular modelling has provided computational simulation based methods for investigating biological processes from quantum chemical to cellular levels. Modelling such microscopic processes requires atomic description of a biological system and conducts in fine timesteps. Consequently the simulations are extremely computationally demanding. To tackle this limitation, different biomolecular models have to be integrated in order to achieve high-performance simulations. The integration of diverse biomolecular models needs to convert molecular data between different data representations of different models. This data conversion is often non-trivial, requires extensive human input and is inevitably error prone. In this paper we present an automated data conversion method for biomolecular simulations between molecular dynamics and quantum mechanics/molecular mechanics models. Our approach is developed around an XML data representation called BioSimML (Biomolecular Simulation Markup Language. BioSimML provides a domain specific data representation for biomolecular modelling which can effciently support data interoperability between different biomolecular simulation models and data formats.
From scenarios to domain models: processes and representations
Haddock, Gail; Harbison, Karan
1994-03-01
The domain specific software architectures (DSSA) community has defined a philosophy for the development of complex systems. This philosophy improves productivity and efficiency by increasing the user's role in the definition of requirements, increasing the systems engineer's role in the reuse of components, and decreasing the software engineer's role to the development of new components and component modifications only. The scenario-based engineering process (SEP), the first instantiation of the DSSA philosophy, has been adopted by the next generation controller project. It is also the chosen methodology of the trauma care information management system project, and the surrogate semi-autonomous vehicle project. SEP uses scenarios from the user to create domain models and define the system's requirements. Domain knowledge is obtained from a variety of sources including experts, documents, and videos. This knowledge is analyzed using three techniques: scenario analysis, task analysis, and object-oriented analysis. Scenario analysis results in formal representations of selected scenarios. Task analysis of the scenario representations results in descriptions of tasks necessary for object-oriented analysis and also subtasks necessary for functional system analysis. Object-oriented analysis of task descriptions produces domain models and system requirements. This paper examines the representations that support the DSSA philosophy, including reference requirements, reference architectures, and domain models. The processes used to create and use the representations are explained through use of the scenario-based engineering process. Selected examples are taken from the next generation controller project.
Eu, Byung Chan
2008-09-07
In the traditional theories of irreversible thermodynamics and fluid mechanics, the specific volume and molar volume have been interchangeably used for pure fluids, but in this work we show that they should be distinguished from each other and given distinctive statistical mechanical representations. In this paper, we present a general formula for the statistical mechanical representation of molecular domain (volume or space) by using the Voronoi volume and its mean value that may be regarded as molar domain (volume) and also the statistical mechanical representation of volume flux. By using their statistical mechanical formulas, the evolution equations of volume transport are derived from the generalized Boltzmann equation of fluids. Approximate solutions of the evolution equations of volume transport provides kinetic theory formulas for the molecular domain, the constitutive equations for molar domain (volume) and volume flux, and the dissipation of energy associated with volume transport. Together with the constitutive equation for the mean velocity of the fluid obtained in a previous paper, the evolution equations for volume transport not only shed a fresh light on, and insight into, irreversible phenomena in fluids but also can be applied to study fluid flow problems in a manner hitherto unavailable in fluid dynamics and irreversible thermodynamics. Their roles in the generalized hydrodynamics will be considered in the sequel.
MODELING OF DYNAMIC SYSTEMS WITH MODULATION BY MEANS OF KRONECKER VECTOR-MATRIX REPRESENTATION
Directory of Open Access Journals (Sweden)
A. S. Vasilyev
2015-09-01
Full Text Available The paper deals with modeling of dynamic systems with modulation by the possibilities of state-space method. This method, being the basis of modern control theory, is based on the possibilities of vector-matrix formalism of linear algebra and helps to solve various problems of technical control of continuous and discrete nature invariant with respect to the dimension of their “input-output” objects. Unfortunately, it turned its back on the wide group of control systems, which hardware environment modulates signals. The marked system deficiency is partially offset by this paper, which proposes Kronecker vector-matrix representations for purposes of system representation of processes with signal modulation. The main result is vector-matrix representation of processes with modulation with no formal difference from continuous systems. It has been found that abilities of these representations could be effectively used in research of systems with modulation. Obtained model representations of processes with modulation are best adapted to the state-space method. These approaches for counting eigenvalues of Kronecker matrix summaries, that are matrix basis of model representations of processes described by Kronecker vector products, give the possibility to use modal direction in research of dynamics for systems with modulation. It is shown that the use of controllability for eigenvalues of general matrixes applied to Kronecker structures enabled to divide successfully eigenvalue spectrum into directed and not directed components. Obtained findings including design problems for models of dynamic processes with modulation based on the features of Kronecker vector and matrix structures, invariant with respect to the dimension of input-output relations, are applicable in the development of alternate current servo drives.
Linear accelerator modeling: development and application
International Nuclear Information System (INIS)
Jameson, R.A.; Jule, W.D.
1977-01-01
Most of the parameters of a modern linear accelerator can be selected by simulating the desired machine characteristics in a computer code and observing how the parameters affect the beam dynamics. The code PARMILA is used at LAMPF for the low-energy portion of linacs. Collections of particles can be traced with a free choice of input distributions in six-dimensional phase space. Random errors are often included in order to study the tolerances which should be imposed during manufacture or in operation. An outline is given of the modifications made to the model, the results of experiments which indicate the validity of the model, and the use of the model to optimize the longitudinal tuning of the Alvarez linac
Running vacuum cosmological models: linear scalar perturbations
Energy Technology Data Exchange (ETDEWEB)
Perico, E.L.D. [Instituto de Física, Universidade de São Paulo, Rua do Matão 1371, CEP 05508-090, São Paulo, SP (Brazil); Tamayo, D.A., E-mail: elduartep@usp.br, E-mail: tamayo@if.usp.br [Departamento de Astronomia, Universidade de São Paulo, Rua do Matão 1226, CEP 05508-900, São Paulo, SP (Brazil)
2017-08-01
In cosmology, phenomenologically motivated expressions for running vacuum are commonly parameterized as linear functions typically denoted by Λ( H {sup 2}) or Λ( R ). Such models assume an equation of state for the vacuum given by P-bar {sub Λ} = - ρ-bar {sub Λ}, relating its background pressure P-bar {sub Λ} with its mean energy density ρ-bar {sub Λ} ≡ Λ/8π G . 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 ρ-bar {sub Λ} = Σ {sub i} ρ-bar {sub Λ} {sub i} . 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( H {sup 2}) 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.
Evaluating and improving the representation of heteroscedastic errors in hydrological models
McInerney, D. J.; Thyer, M. A.; Kavetski, D.; Kuczera, G. A.
2013-12-01
Appropriate representation of residual errors in hydrological modelling is essential for accurate and reliable probabilistic predictions. In particular, residual errors of hydrological models are often heteroscedastic, with large errors associated with high rainfall and runoff events. Recent studies have shown that using a weighted least squares (WLS) approach - where the magnitude of residuals are assumed to be linearly proportional to the magnitude of the flow - captures some of this heteroscedasticity. In this study we explore a range of Bayesian approaches for improving the representation of heteroscedasticity in residual errors. We compare several improved formulations of the WLS approach, the well-known Box-Cox transformation and the more recent log-sinh transformation. Our results confirm that these approaches are able to stabilize the residual error variance, and that it is possible to improve the representation of heteroscedasticity compared with the linear WLS approach. We also find generally good performance of the Box-Cox and log-sinh transformations, although as indicated in earlier publications, the Box-Cox transform sometimes produces unrealistically large prediction limits. Our work explores the trade-offs between these different uncertainty characterization approaches, investigates how their performance varies across diverse catchments and models, and recommends practical approaches suitable for large-scale applications.
Non linear permanent magnets modelling with the finite element method
International Nuclear Information System (INIS)
Chavanne, J.; Meunier, G.; Sabonnadiere, J.C.
1989-01-01
In order to perform the calculation of permanent magnets with the finite element method, it is necessary to take into account the anisotropic behaviour of hard magnetic materials (Ferrites, NdFeB, SmCo5). In linear cases, the permeability of permanent magnets is a tensor. This one is fully described with the permeabilities parallel and perpendicular to the easy axis of the magnet. In non linear cases, the model uses a texture function which represents the distribution of the local easy axis of the cristallytes of the magnet. This function allows a good representation of the angular dependance of the coercitive field of the magnet. As a result, it is possible to express the magnetic induction B and the tensor as functions of the field and the texture parameter. This model has been implemented in the software FLUX3D where the tensor is used for the Newton-Raphson procedure. 3D demagnetization of a ferrite magnet by a NdFeB magnet is a suitable representative example. They analyze the results obtained for an ideally oriented ferrite magnet and a real one using a measured texture parameter
Aspects of general linear modelling of migration.
Congdon, P
1992-01-01
"This paper investigates the application of general linear modelling principles to analysing migration flows between areas. Particular attention is paid to specifying the form of the regression and error components, and the nature of departures from Poisson randomness. Extensions to take account of spatial and temporal correlation are discussed as well as constrained estimation. The issue of specification bears on the testing of migration theories, and assessing the role migration plays in job and housing markets: the direction and significance of the effects of economic variates on migration depends on the specification of the statistical model. The application is in the context of migration in London and South East England in the 1970s and 1980s." excerpt
BIM-Enabled Conceptual Modelling and Representation of Building Circulation
Directory of Open Access Journals (Sweden)
Jin Kook Lee
2014-08-01
Full Text Available This paper describes how a building information modelling (BIM-based approach for building circulation enables us to change the process of building design in terms of its computational representation and processes, focusing on the conceptual modelling and representation of circulation within buildings. BIM has been designed for use by several BIM authoring tools, in particular with the widely known interoperable industry foundation classes (IFCs, which follow an object-oriented data modelling methodology. Advances in BIM authoring tools, using space objects and their relations defined in an IFC's schema, have made it possible to model, visualize and analyse circulation within buildings prior to their construction. Agent-based circulation has long been an interdisciplinary topic of research across several areas, including design computing, computer science, architectural morphology, human behaviour and environmental psychology. Such conventional approaches to building circulation are centred on navigational knowledge about built environments, and represent specific circulation paths and regulations. This paper, however, places emphasis on the use of ‘space objects’ in BIM-enabled design processes rather than on circulation agents, the latter of which are not defined in the IFCs' schemas. By introducing and reviewing some associated research and projects, this paper also surveys how such a circulation representation is applicable to the analysis of building circulation-related rules.
Model Selection with the Linear Mixed Model for Longitudinal Data
Ryoo, Ji Hoon
2011-01-01
Model building or model selection with linear mixed models (LMMs) is complicated by the presence of both fixed effects and random effects. The fixed effects structure and random effects structure are codependent, so selection of one influences the other. Most presentations of LMM in psychology and education are based on a multilevel or…
Modelling and Predicting Backstroke Start Performance Using Non-Linear and Linear Models.
de Jesus, Karla; Ayala, Helon V H; de Jesus, Kelly; Coelho, Leandro Dos S; Medeiros, Alexandre I A; Abraldes, José A; Vaz, Mário A P; Fernandes, Ricardo J; Vilas-Boas, João Paulo
2018-03-01
Our aim was to compare non-linear and linear mathematical model responses for backstroke start performance prediction. Ten swimmers randomly completed eight 15 m backstroke starts with feet over the wedge, four with hands on the highest horizontal and four on the vertical handgrip. Swimmers were videotaped using a dual media camera set-up, with the starts being performed over an instrumented block with four force plates. Artificial neural networks were applied to predict 5 m start time using kinematic and kinetic variables and to determine the accuracy of the mean absolute percentage error. Artificial neural networks predicted start time more robustly than the linear model with respect to changing training to the validation dataset for the vertical handgrip (3.95 ± 1.67 vs. 5.92 ± 3.27%). Artificial neural networks obtained a smaller mean absolute percentage error than the linear model in the horizontal (0.43 ± 0.19 vs. 0.98 ± 0.19%) and vertical handgrip (0.45 ± 0.19 vs. 1.38 ± 0.30%) using all input data. The best artificial neural network validation revealed a smaller mean absolute error than the linear model for the horizontal (0.007 vs. 0.04 s) and vertical handgrip (0.01 vs. 0.03 s). Artificial neural networks should be used for backstroke 5 m start time prediction due to the quite small differences among the elite level performances.
Sparse representation based image interpolation with nonlocal autoregressive modeling.
Dong, Weisheng; Zhang, Lei; Lukac, Rastislav; Shi, Guangming
2013-04-01
Sparse representation is proven to be a promising approach to image super-resolution, where the low-resolution (LR) image is usually modeled as the down-sampled version of its high-resolution (HR) counterpart after blurring. When the blurring kernel is the Dirac delta function, i.e., the LR image is directly down-sampled from its HR counterpart without blurring, the super-resolution problem becomes an image interpolation problem. In such cases, however, the conventional sparse representation models (SRM) become less effective, because the data fidelity term fails to constrain the image local structures. In natural images, fortunately, many nonlocal similar patches to a given patch could provide nonlocal constraint to the local structure. In this paper, we incorporate the image nonlocal self-similarity into SRM for image interpolation. More specifically, a nonlocal autoregressive model (NARM) is proposed and taken as the data fidelity term in SRM. We show that the NARM-induced sampling matrix is less coherent with the representation dictionary, and consequently makes SRM more effective for image interpolation. Our extensive experimental results demonstrate that the proposed NARM-based image interpolation method can effectively reconstruct the edge structures and suppress the jaggy/ringing artifacts, achieving the best image interpolation results so far in terms of PSNR as well as perceptual quality metrics such as SSIM and FSIM.
Modeling patterns in data using linear and related models
International Nuclear Information System (INIS)
Engelhardt, M.E.
1996-06-01
This report considers the use of linear models for analyzing data related to reliability and safety issues of the type usually associated with nuclear power plants. The report discusses some of the general results of linear regression analysis, such as the model assumptions and properties of the estimators of the parameters. The results are motivated with examples of operational data. Results about the important case of a linear regression model with one covariate are covered in detail. This case includes analysis of time trends. The analysis is applied with two different sets of time trend data. Diagnostic procedures and tests for the adequacy of the model are discussed. Some related methods such as weighted regression and nonlinear models are also considered. A discussion of the general linear model is also included. Appendix A gives some basic SAS programs and outputs for some of the analyses discussed in the body of the report. Appendix B is a review of some of the matrix theoretic results which are useful in the development of linear models
Electron Model of Linear-Field FFAG
Koscielniak, Shane R
2005-01-01
A fixed-field alternating-gradient accelerator (FFAG) that employs only linear-field elements ushers in a new regime in accelerator design and dynamics. The linear-field machine has the ability to compact an unprecedented range in momenta within a small component aperture. With a tune variation which results from the natural chromaticity, the beam crosses many strong, uncorrec-table, betatron resonances during acceleration. Further, relativistic particles in this machine exhibit a quasi-parabolic time-of-flight that cannot be addressed with a fixed-frequency rf system. This leads to a new concept of bucketless acceleration within a rotation manifold. With a large energy jump per cell, there is possibly strong synchro-betatron coupling. A few-MeV electron model has been proposed to demonstrate the feasibility of these untested acceleration features and to investigate them at length under a wide range of operating conditions. This paper presents a lattice optimized for a 1.3 GHz rf, initial technology choices f...
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...
Generalized Linear Models in Vehicle Insurance
Directory of Open Access Journals (Sweden)
Silvie Kafková
2014-01-01
Full Text Available Actuaries in insurance companies try to find the best model for an estimation of insurance premium. It depends on many risk factors, e.g. the car characteristics and the profile of the driver. In this paper, an analysis of the portfolio of vehicle insurance data using a generalized linear model (GLM is performed. The main advantage of the approach presented in this article is that the GLMs are not limited by inflexible preconditions. Our aim is to predict the relation of annual claim frequency on given risk factors. Based on a large real-world sample of data from 57 410 vehicles, the present study proposed a classification analysis approach that addresses the selection of predictor variables. The models with different predictor variables are compared by analysis of deviance and Akaike information criterion (AIC. Based on this comparison, the model for the best estimate of annual claim frequency is chosen. All statistical calculations are computed in R environment, which contains stats package with the function for the estimation of parameters of GLM and the function for analysis of deviation.
Nonlinear price impact from linear models
Patzelt, Felix; Bouchaud, Jean-Philippe
2017-12-01
The impact of trades on asset prices is a crucial aspect of market dynamics for academics, regulators, and practitioners alike. Recently, universal and highly nonlinear master curves were observed for price impacts aggregated on all intra-day scales (Patzelt and Bouchaud 2017 arXiv:1706.04163). Here we investigate how well these curves, their scaling, and the underlying return dynamics are captured by linear ‘propagator’ models. We find that the classification of trades as price-changing versus non-price-changing can explain the price impact nonlinearities and short-term return dynamics to a very high degree. The explanatory power provided by the change indicator in addition to the order sign history increases with increasing tick size. To obtain these results, several long-standing technical issues for model calibration and testing are addressed. We present new spectral estimators for two- and three-point cross-correlations, removing the need for previously used approximations. We also show when calibration is unbiased and how to accurately reveal previously overlooked biases. Therefore, our results contribute significantly to understanding both recent empirical results and the properties of a popular class of impact models.
Kane, Michael T.; Mroch, Andrew A.; Suh, Youngsuk; Ripkey, Douglas R.
2009-01-01
This paper analyzes five linear equating models for the "nonequivalent groups with anchor test" (NEAT) design with internal anchors (i.e., the anchor test is part of the full test). The analysis employs a two-dimensional framework. The first dimension contrasts two general approaches to developing the equating relationship. Under a "parameter…
A Representation for Gaining Insight into Clinical Decision Models
Jimison, Holly B.
1988-01-01
For many medical domains uncertainty and patient preferences are important components of decision making. Decision theory is useful as a representation for such medical models in computer decision aids, but the methodology has typically had poor performance in the areas of explanation and user interface. The additional representation of probabilities and utilities as random variables serves to provide a framework for graphical and text insight into complicated decision models. The approach allows for efficient customization of a generic model that describes the general patient population of interest to a patient- specific model. Monte Carlo simulation is used to calculate the expected value of information and sensitivity for each model variable, thus providing a metric for deciding what to emphasize in the graphics and text summary. The computer-generated explanation includes variables that are sensitive with respect to the decision or that deviate significantly from what is typically observed. These techniques serve to keep the assessment and explanation of the patient's decision model concise, allowing the user to focus on the most important aspects for that patient.
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…
From linear to generalized linear mixed models: A case study in repeated measures
Compared to traditional linear mixed models, generalized linear mixed models (GLMMs) can offer better correspondence between response variables and explanatory models, yielding more efficient estimates and tests in the analysis of data from designed experiments. Using proportion data from a designed...
Improved dust representation in the Community Atmosphere Model
Albani, S.; Mahowald, N. M.; Perry, A. T.; Scanza, R. A.; Zender, C. S.; Heavens, N. G.; Maggi, V.; Kok, J. F.; Otto-Bliesner, B. L.
2014-09-01
Aerosol-climate interactions constitute one of the major sources of uncertainty in assessing changes in aerosol forcing in the anthropocene as well as understanding glacial-interglacial cycles. Here we focus on improving the representation of mineral dust in the Community Atmosphere Model and assessing the impacts of the improvements in terms of direct effects on the radiative balance of the atmosphere. We simulated the dust cycle using different parameterization sets for dust emission, size distribution, and optical properties. Comparing the results of these simulations with observations of concentration, deposition, and aerosol optical depth allows us to refine the representation of the dust cycle and its climate impacts. We propose a tuning method for dust parameterizations to allow the dust module to work across the wide variety of parameter settings which can be used within the Community Atmosphere Model. Our results include a better representation of the dust cycle, most notably for the improved size distribution. The estimated net top of atmosphere direct dust radiative forcing is -0.23 ± 0.14 W/m2 for present day and -0.32 ± 0.20 W/m2 at the Last Glacial Maximum. From our study and sensitivity tests, we also derive some general relevant findings, supporting the concept that the magnitude of the modeled dust cycle is sensitive to the observational data sets and size distribution chosen to constrain the model as well as the meteorological forcing data, even within the same modeling framework, and that the direct radiative forcing of dust is strongly sensitive to the optical properties and size distribution used.
Montoye, Alexander H K; Begum, Munni; Henning, Zachary; Pfeiffer, Karin A
2017-02-01
This study had three purposes, all related to evaluating energy expenditure (EE) prediction accuracy from body-worn accelerometers: (1) compare linear regression to linear mixed models, (2) compare linear models to artificial neural network models, and (3) compare accuracy of accelerometers placed on the hip, thigh, and wrists. Forty individuals performed 13 activities in a 90 min semi-structured, laboratory-based protocol. Participants wore accelerometers on the right hip, right thigh, and both wrists and a portable metabolic analyzer (EE criterion). Four EE prediction models were developed for each accelerometer: linear regression, linear mixed, and two ANN models. EE prediction accuracy was assessed using correlations, root mean square error (RMSE), and bias and was compared across models and accelerometers using repeated-measures analysis of variance. For all accelerometer placements, there were no significant differences for correlations or RMSE between linear regression and linear mixed models (correlations: r = 0.71-0.88, RMSE: 1.11-1.61 METs; p > 0.05). For the thigh-worn accelerometer, there were no differences in correlations or RMSE between linear and ANN models (ANN-correlations: r = 0.89, RMSE: 1.07-1.08 METs. Linear models-correlations: r = 0.88, RMSE: 1.10-1.11 METs; p > 0.05). Conversely, one ANN had higher correlations and lower RMSE than both linear models for the hip (ANN-correlation: r = 0.88, RMSE: 1.12 METs. Linear models-correlations: r = 0.86, RMSE: 1.18-1.19 METs; p linear models for the wrist-worn accelerometers (ANN-correlations: r = 0.82-0.84, RMSE: 1.26-1.32 METs. Linear models-correlations: r = 0.71-0.73, RMSE: 1.55-1.61 METs; p models offer a significant improvement in EE prediction accuracy over linear models. Conversely, linear models showed similar EE prediction accuracy to machine learning models for hip- and thigh
Test results for three prototype models of a linear induction launcher
International Nuclear Information System (INIS)
Zabar, Z.; Lu, X.N.; He, J.L.; Birenbaum, L.; Levi, E.; Kuznetsov, S.B.; Nahemow, M.D.
1991-01-01
This paper reports on the work on the linear induction launcher (LIL) started with an analytical study tht was followed by computer simulations and then was tested by laboratory models. Two mathematical representations have been developed to describe the launcher. The first, based on the field approach with sinusoidal excitation, has been validated by static tests on a small scale prototype fed at constant current and variable frequency. The second, a transient representation using computer simulation allows consideration of energization by means of a capacitor bank and a power conditioner. Tests performed on three small-scale prototypes up to 100 m/s muzzle velocities show good agreement with predicted performance
Najeebullah Khan; Adnan Hussein; Zahid Awan; Bakhtiar Khan
2012-01-01
This study measured the impacts of six independent variables (political rights, election system type, political quota, literacy rate, labor force participation and GDP per capita at current price in US dollar) on the dependent variable (percentage of women representation in national legislature) using multiple linear regression models. At a first step we developed and tested the model without of sample data of Pakistan. For model construction and validation ten years data from the year 1999 a...
Yang, Licai; Shen, Jun; Bao, Shudi; Wei, Shoushui
2013-10-01
To treat the problem of identification performance and the complexity of the algorithm, we proposed a piecewise linear representation and dynamic time warping (PLR-DTW) method for ECG biometric identification. Firstly we detected R peaks to get the heartbeats after denoising preprocessing. Then we used the PLR method to keep important information of an ECG signal segment while reducing the data dimension at the same time. The improved DTW method was used for similarity measurements between the test data and the templates. The performance evaluation was carried out on the two ECG databases: PTB and MIT-BIH. The analystic results showed that compared to the discrete wavelet transform method, the proposed PLR-DTW method achieved a higher accuracy rate which is nearly 8% of rising, and saved about 30% operation time, and this demonstrated that the proposed method could provide a better performance.
Evaluating the double Poisson generalized linear model.
Zou, Yaotian; Geedipally, Srinivas Reddy; Lord, Dominique
2013-10-01
The objectives of this study are to: (1) examine the applicability of the double Poisson (DP) generalized linear model (GLM) for analyzing motor vehicle crash data characterized by over- and under-dispersion and (2) compare the performance of the DP GLM with the Conway-Maxwell-Poisson (COM-Poisson) GLM in terms of goodness-of-fit and theoretical soundness. The DP distribution has seldom been investigated and applied since its first introduction two decades ago. The hurdle for applying the DP is related to its normalizing constant (or multiplicative constant) which is not available in closed form. This study proposed a new method to approximate the normalizing constant of the DP with high accuracy and reliability. The DP GLM and COM-Poisson GLM were developed using two observed over-dispersed datasets and one observed under-dispersed dataset. The modeling results indicate that the DP GLM with its normalizing constant approximated by the new method can handle crash data characterized by over- and under-dispersion. Its performance is comparable to the COM-Poisson GLM in terms of goodness-of-fit (GOF), although COM-Poisson GLM provides a slightly better fit. For the over-dispersed data, the DP GLM performs similar to the NB GLM. Considering the fact that the DP GLM can be easily estimated with inexpensive computation and that it is simpler to interpret coefficients, it offers a flexible and efficient alternative for researchers to model count data. Copyright © 2013 Elsevier Ltd. All rights reserved.
Petri Nets as Models of Linear Logic
DEFF Research Database (Denmark)
Engberg, Uffe Henrik; Winskel, Glynn
1990-01-01
The chief purpose of this paper is to appraise the feasibility of Girad's linear logic as a specification language for parallel processes. To this end we propose an interpretation of linear logic in Petri nets, with respect to which we investigate the expressive power of the logic...
Sparse linear models: Variational approximate inference and Bayesian experimental design
International Nuclear Information System (INIS)
Seeger, Matthias W
2009-01-01
A wide range of problems such as signal reconstruction, denoising, source separation, feature selection, and graphical model search are addressed today by posterior maximization for linear models with sparsity-favouring prior distributions. The Bayesian posterior contains useful information far beyond its mode, which can be used to drive methods for sampling optimization (active learning), feature relevance ranking, or hyperparameter estimation, if only this representation of uncertainty can be approximated in a tractable manner. In this paper, we review recent results for variational sparse inference, and show that they share underlying computational primitives. We discuss how sampling optimization can be implemented as sequential Bayesian experimental design. While there has been tremendous recent activity to develop sparse estimation, little attendance has been given to sparse approximate inference. In this paper, we argue that many problems in practice, such as compressive sensing for real-world image reconstruction, are served much better by proper uncertainty approximations than by ever more aggressive sparse estimation algorithms. Moreover, since some variational inference methods have been given strong convex optimization characterizations recently, theoretical analysis may become possible, promising new insights into nonlinear experimental design.
Sparse linear models: Variational approximate inference and Bayesian experimental design
Energy Technology Data Exchange (ETDEWEB)
Seeger, Matthias W [Saarland University and Max Planck Institute for Informatics, Campus E1.4, 66123 Saarbruecken (Germany)
2009-12-01
A wide range of problems such as signal reconstruction, denoising, source separation, feature selection, and graphical model search are addressed today by posterior maximization for linear models with sparsity-favouring prior distributions. The Bayesian posterior contains useful information far beyond its mode, which can be used to drive methods for sampling optimization (active learning), feature relevance ranking, or hyperparameter estimation, if only this representation of uncertainty can be approximated in a tractable manner. In this paper, we review recent results for variational sparse inference, and show that they share underlying computational primitives. We discuss how sampling optimization can be implemented as sequential Bayesian experimental design. While there has been tremendous recent activity to develop sparse estimation, little attendance has been given to sparse approximate inference. In this paper, we argue that many problems in practice, such as compressive sensing for real-world image reconstruction, are served much better by proper uncertainty approximations than by ever more aggressive sparse estimation algorithms. Moreover, since some variational inference methods have been given strong convex optimization characterizations recently, theoretical analysis may become possible, promising new insights into nonlinear experimental design.
Time representation in reinforcement learning models of the basal ganglia
Directory of Open Access Journals (Sweden)
Samuel Joseph Gershman
2014-01-01
Full Text Available Reinforcement learning models have been influential in understanding many aspects of basal ganglia function, from reward prediction to action selection. Time plays an important role in these models, but there is still no theoretical consensus about what kind of time representation is used by the basal ganglia. We review several theoretical accounts and their supporting evidence. We then discuss the relationship between reinforcement learning models and the timing mechanisms that have been attributed to the basal ganglia. We hypothesize that a single computational system may underlie both reinforcement learning and interval timing—the perception of duration in the range of seconds to hours. This hypothesis, which extends earlier models by incorporating a time-sensitive action selection mechanism, may have important implications for understanding disorders like Parkinson's disease in which both decision making and timing are impaired.
Energy Technology Data Exchange (ETDEWEB)
Bonnet, G [Commissariat a l' Energie Atomique, Grenoble (France). Centre d' Etudes Nucleaires
1961-07-01
When studying the behaviour of a magnetic resonance transducer formed by the association of an electrical network and of a set of nuclear spins, it is possible to bring about a representation that is analytically equivalent by means of an entirely electrical model, available for transients as well as steady-state. A detailed study of the validity conditions justifies its use in most cases. Also proposed is a linearity criterion of Bloch's equations in transient state that is simply the prolongation of the well-known condition of non-saturation in the steady-state. (author) [French] L'etude du comportement d'un transducteur a resonance magnetique forme de l'association d'un reseau electrique et d'un ensemble de noyaux dotes de spin, montre qu'il est possible d'en deduire une representation analytiquement equivalente au moyen d'un modele entierement electrique utilisable pour un regime transitoire aussi bien que pour un regime permanent. Une etude detaillee des conditions de validite permet d'en justifier l'emploi dans la majorite des cas. On propose enfin un critere de linearite des equations de Bloch en regime transitoire, qui constitue un prolongement de la condition connue de non-saturation en regime stationnaire. (auteur)
Linear approximation model network and its formation via ...
Indian Academy of Sciences (India)
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 ...
Representation of Northern Hemisphere winter storm tracks in climate models
Energy Technology Data Exchange (ETDEWEB)
Greeves, C.Z.; Pope, V.D.; Stratton, R.A.; Martin, G.M. [Met Office Hadley Centre for Climate Prediction and Research, Exeter (United Kingdom)
2007-06-15
Northern Hemisphere winter storm tracks are a key element of the winter weather and climate at mid-latitudes. Before projections of climate change are made for these regions, it is necessary to be sure that climate models are able to reproduce the main features of observed storm tracks. The simulated storm tracks are assessed for a variety of Hadley Centre models and are shown to be well modelled on the whole. The atmosphere-only model with the semi-Lagrangian dynamical core produces generally more realistic storm tracks than the model with the Eulerian dynamical core, provided the horizontal resolution is high enough. The two models respond in different ways to changes in horizontal resolution: the model with the semi-Lagrangian dynamical core has much reduced frequency and strength of cyclonic features at lower resolution due to reduced transient eddy kinetic energy. The model with Eulerian dynamical core displays much smaller changes in frequency and strength of features with changes in horizontal resolution, but the location of the storm tracks as well as secondary development are sensitive to resolution. Coupling the atmosphere-only model (with semi-Lagrangian dynamical core) to an ocean model seems to affect the storm tracks largely via errors in the tropical representation. For instance a cold SST bias in the Pacific and a lack of ENSO variability lead to large changes in the Pacific storm track. Extratropical SST biases appear to have a more localised effect on the storm tracks. (orig.)
XML for data representation and model specification in neuroscience.
Crook, Sharon M; Howell, Fred W
2007-01-01
EXtensible Markup Language (XML) technology provides an ideal representation for the complex structure of models and neuroscience data, as it is an open file format and provides a language-independent method for storing arbitrarily complex structured information. XML is composed of text and tags that explicitly describe the structure and semantics of the content of the document. In this chapter, we describe some of the common uses of XML in neuroscience, with case studies in representing neuroscience data and defining model descriptions based on examples from NeuroML. The specific methods that we discuss include (1) reading and writing XML from applications, (2) exporting XML from databases, (3) using XML standards to represent neuronal morphology data, (4) using XML to represent experimental metadata, and (5) creating new XML specifications for models.
Linear regression crash prediction models : issues and proposed solutions.
2010-05-01
The paper develops a linear regression model approach that can be applied to : crash data to predict vehicle crashes. The proposed approach involves novice data aggregation : to satisfy linear regression assumptions; namely error structure normality ...
Game Theory and its Relationship with Linear Programming Models ...
African Journals Online (AJOL)
Game Theory and its Relationship with Linear Programming Models. ... This paper shows that game theory and linear programming problem are closely related subjects since any computing method devised for ... AJOL African Journals Online.
Representations of the Virasoro algebra from lattice models
International Nuclear Information System (INIS)
Koo, W.M.; Saleur, H.
1994-01-01
We investigate in detail how the Virasoro algebra appears in the scaling limit of the simplest lattice models of XXZ or RSOS type. Our approach is straightforward but to our knowledge had never been tried so far. We simply formulate a conjecture for the lattice stress-energy tensor motivated by the exact derivation of lattice global Ward identities. We then check that the proper algebraic relations are obeyed in the scaling limit. The latter is under reasonable control thanks to the Bethe-ansatz solution. The results, which are mostly numerical for technical reasons, are remarkably precise. They are also corroborated by exact pieces of information from various sources, in particular Temperley-Lieb algebra representation theory. Most features of the Virasoro algebra (like central term, null vectors, metric properties, etc.) can thus be observed using the lattice models. This seems of general interest for lattice field theory, and also more specifically for finding relations between conformal invariance and lattice integrability, since a basis for the irreducible representations of the Virasoro algebra should now follow (at least in principle) from Bethe-ansatz computations. ((orig.))
A linear time layout algorithm for business process models
Gschwind, T.; Pinggera, J.; Zugal, S.; Reijers, H.A.; Weber, B.
2014-01-01
The layout of a business process model influences how easily it can beunderstood. Existing layout features in process modeling tools often rely on graph representations, but do not take the specific properties of business process models into account. In this paper, we propose an algorithm that is
Evaluation, Use, and Refinement of Knowledge Representations through Acquisition Modeling
Pearl, Lisa
2017-01-01
Generative approaches to language have long recognized the natural link between theories of knowledge representation and theories of knowledge acquisition. The basic idea is that the knowledge representations provided by Universal Grammar enable children to acquire language as reliably as they do because these representations highlight the…
A Note on the Identifiability of Generalized Linear Mixed Models
DEFF Research Database (Denmark)
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...
Standard representation and unified stability analysis for dynamic artificial neural network models.
Kim, Kwang-Ki K; Patrón, Ernesto Ríos; Braatz, Richard D
2018-02-01
An overview is provided of dynamic artificial neural network models (DANNs) for nonlinear dynamical system identification and control problems, and convex stability conditions are proposed that are less conservative than past results. The three most popular classes of dynamic artificial neural network models are described, with their mathematical representations and architectures followed by transformations based on their block diagrams that are convenient for stability and performance analyses. Classes of nonlinear dynamical systems that are universally approximated by such models are characterized, which include rigorous upper bounds on the approximation errors. A unified framework and linear matrix inequality-based stability conditions are described for different classes of dynamic artificial neural network models that take additional information into account such as local slope restrictions and whether the nonlinearities within the DANNs are odd. A theoretical example shows reduced conservatism obtained by the conditions. Copyright © 2017. Published by Elsevier Ltd.
The Calogero model - anyonic representation, fermionic extension and supersymmetry
Energy Technology Data Exchange (ETDEWEB)
Brink, L [Inst. of Theoretical Physics, Goeteborg (Sweden); Hansson, T H [Inst. of Theoretical Physics, Univ. of Stockholm (Sweden); Konstein, S [Dept. of Theoretical Physics, P.N. Lebedev Inst., Moscow (Russian Federation); Vasiliev, M A [Dept. of Theoretical Physics, P.N. Lebedev Inst., Moscow (Russian Federation)
1993-07-26
We discuss several applications and extensions of our previous operator solution of the N-body quantum-mechanical Calogero problem, i.e. N particles in one dimension subject to a two-body interaction of the form 1/2[Sigma][sub i,j] (x[sub i]-x[sub j])[sup 2]+g/(x[sub i]-x[sub j])[sup 2]. Using a complex representation of the deformed Heisenberg algebra underlying the Calogero model, we explicitly establish the equivalence between this system and anyons in the lowest Landau level. A construction based on supersymmetry is used to extend our operator method to include fermions, and we obtain an explicit solution of the supersymmetric Calogero model constructed by Freedman and Mende. We also show how the dynamical OSp(2; 2) supersymmetry is realized by bilinears of modified creation and annihilation operators, and how to construct a supersymmetric extension of the deformed Heisenberg algebra. (orig.)
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 MODEL FOR NON ISOSCELES ABSORBERS.
Energy Technology Data Exchange (ETDEWEB)
BERG,J.S.
2003-05-12
Previous analyses have assumed that wedge absorbers are triangularly shaped with equal angles for the two faces. In this case, to linear order, the energy loss depends only on the position in the direction of the face tilt, and is independent of the incoming angle. One can instead construct an absorber with entrance and exit faces facing rather general directions. In this case, the energy loss can depend on both the position and the angle of the particle in question. This paper demonstrates that and computes the effect to linear order.
Knowledge representation to support reasoning based on multiple models
Gillam, April; Seidel, Jorge P.; Parker, Alice C.
1990-01-01
Model Based Reasoning is a powerful tool used to design and analyze systems, which are often composed of numerous interactive, interrelated subsystems. Models of the subsystems are written independently and may be used together while they are still under development. Thus the models are not static. They evolve as information becomes obsolete, as improved artifact descriptions are developed, and as system capabilities change. Researchers are using three methods to support knowledge/data base growth, to track the model evolution, and to handle knowledge from diverse domains. First, the representation methodology is based on having pools, or types, of knowledge from which each model is constructed. In addition information is explicit. This includes the interactions between components, the description of the artifact structure, and the constraints and limitations of the models. The third principle we have followed is the separation of the data and knowledge from the inferencing and equation solving mechanisms. This methodology is used in two distinct knowledge-based systems: one for the design of space systems and another for the synthesis of VLSI circuits. It has facilitated the growth and evolution of our models, made accountability of results explicit, and provided credibility for the user community. These capabilities have been implemented and are being used in actual design projects.
Equivalent linear damping characterization in linear and nonlinear force-stiffness muscle models.
Ovesy, Marzieh; Nazari, Mohammad Ali; Mahdavian, Mohammad
2016-02-01
In the current research, the muscle equivalent linear damping coefficient which is introduced as the force-velocity relation in a muscle model and the corresponding time constant are investigated. In order to reach this goal, a 1D skeletal muscle model was used. Two characterizations of this model using a linear force-stiffness relationship (Hill-type model) and a nonlinear one have been implemented. The OpenSim platform was used for verification of the model. The isometric activation has been used for the simulation. The equivalent linear damping and the time constant of each model were extracted by using the results obtained from the simulation. The results provide a better insight into the characteristics of each model. It is found that the nonlinear models had a response rate closer to the reality compared to the Hill-type models.
An online re-linearization scheme suited for Model Predictive and Linear Quadratic Control
DEFF Research Database (Denmark)
Henriksen, Lars Christian; Poulsen, Niels Kjølstad
This technical note documents the equations for primal-dual interior-point quadratic programming problem solver used for MPC. The algorithm exploits the special structure of the MPC problem and is able to reduce the computational burden such that the computational burden scales with prediction...... horizon length in a linear way rather than cubic, which would be the case if the structure was not exploited. It is also shown how models used for design of model-based controllers, e.g. linear quadratic and model predictive, can be linearized both at equilibrium and non-equilibrium points, making...
Representation of an open repository in groundwater flow models
International Nuclear Information System (INIS)
Painter, Scott; Sun, Alexander
2005-08-01
The effect of repository tunnels on groundwater flow has been identified as a potential issue for the nuclear waste repository being considered by SKB for a fractured granite formation in Sweden. In particular, the following pre-closure and post-closure processes have been identified as being important: inflows into open tunnels as functions of estimated grouting efficiencies, drawdown of the water table in the vicinity of the repository, upcoming of saline water, 'turnover' of surface water in the upper bedrock, and resaturation of backfilled tunnels following repository closure. The representation of repository tunnels within groundwater models is addressed in this report. The primary focus is on far-field flow that is modeled with a continuum porous medium approximation. Of particular interest are the consequences of the tunnel representation on the transient response of the groundwater system to repository operations and repository closure, as well as modeling issues such as how the water-table free surface and the coupling to near-surface hydrogeology should be handled. The overall objectives are to understand the consequences of current representations and to identify appropriate approximations for representing open tunnels in future groundwater modeling studies. The following conclusions can be drawn from the results of the simulations: 1. Two-phase flow may be induced in the vicinity of repository tunnels during repository pre-closure operations, but the formation of a two-phase flow region will not significantly affect far-field flow or inflows into tunnels. 2. The water table will be drawn down to the repository horizon and tunnel inflows will reach a steady-state value within about 5 years. 3. Steady-state inflows at the repository edge are estimated to be about 250 m 3 /year per meter of tunnel. Inflows will be greater during the transient de-watering period and less for tunnel locations closer to the repository center. 4. Significant amounts of water
Representation of an open repository in groundwater flow models
Energy Technology Data Exchange (ETDEWEB)
Painter, Scott; Sun, Alexander [Southwest Research Inst., San Antonio, TX (United States). Center for Nuclear Waste Regulatory Analyses
2005-08-01
The effect of repository tunnels on groundwater flow has been identified as a potential issue for the nuclear waste repository being considered by SKB for a fractured granite formation in Sweden. In particular, the following pre-closure and post-closure processes have been identified as being important: inflows into open tunnels as functions of estimated grouting efficiencies, drawdown of the water table in the vicinity of the repository, upcoming of saline water, 'turnover' of surface water in the upper bedrock, and resaturation of backfilled tunnels following repository closure. The representation of repository tunnels within groundwater models is addressed in this report. The primary focus is on far-field flow that is modeled with a continuum porous medium approximation. Of particular interest are the consequences of the tunnel representation on the transient response of the groundwater system to repository operations and repository closure, as well as modeling issues such as how the water-table free surface and the coupling to near-surface hydrogeology should be handled. The overall objectives are to understand the consequences of current representations and to identify appropriate approximations for representing open tunnels in future groundwater modeling studies. The following conclusions can be drawn from the results of the simulations: 1. Two-phase flow may be induced in the vicinity of repository tunnels during repository pre-closure operations, but the formation of a two-phase flow region will not significantly affect far-field flow or inflows into tunnels. 2. The water table will be drawn down to the repository horizon and tunnel inflows will reach a steady-state value within about 5 years. 3. Steady-state inflows at the repository edge are estimated to be about 250 m{sup 3}/year per meter of tunnel. Inflows will be greater during the transient de-watering period and less for tunnel locations closer to the repository center. 4. Significant
Tried and True: Springing into Linear Models
Darling, Gerald
2012-01-01
In eighth grade, students usually learn about forces in science class and linear relationships in math class, crucial topics that form the foundation for further study in science and engineering. An activity that links these two fundamental concepts involves measuring the distance a spring stretches as a function of how much weight is suspended…
Model Predictive Control for Linear Complementarity and Extended Linear Complementarity Systems
Directory of Open Access Journals (Sweden)
Bambang Riyanto
2005-11-01
Full Text Available In this paper, we propose model predictive control method for linear complementarity and extended linear complementarity systems by formulating optimization along prediction horizon as mixed integer quadratic program. Such systems contain interaction between continuous dynamics and discrete event systems, and therefore, can be categorized as hybrid systems. As linear complementarity and extended linear complementarity systems finds applications in different research areas, such as impact mechanical systems, traffic control and process control, this work will contribute to the development of control design method for those areas as well, as shown by three given examples.
Ordinal Log-Linear Models for Contingency Tables
Directory of Open Access Journals (Sweden)
Brzezińska Justyna
2016-12-01
Full Text Available A log-linear analysis is a method providing a comprehensive scheme to describe the association for categorical variables in a contingency table. The log-linear model specifies how the expected counts depend on the levels of the categorical variables for these cells and provide detailed information on the associations. The aim of this paper is to present theoretical, as well as empirical, aspects of ordinal log-linear models used for contingency tables with ordinal variables. We introduce log-linear models for ordinal variables: linear-by-linear association, row effect model, column effect model and RC Goodman’s model. Algorithm, advantages and disadvantages will be discussed in the paper. An empirical analysis will be conducted with the use of R.
Directory of Open Access Journals (Sweden)
Tsung-han Tsai
2013-05-01
Full Text Available There is some confusion in political science, and the social sciences in general, about the meaning and interpretation of interaction effects in models with non-interval, non-normal outcome variables. Often these terms are casually thrown into a model specification without observing that their presence fundamentally changes the interpretation of the resulting coefficients. This article explains the conditional nature of reported coefficients in models with interactions, defining the necessarily different interpretation required by generalized linear models. Methodological issues are illustrated with an application to voter information structured by electoral systems and resulting legislative behavior and democratic representation in comparative politics.
Recent Updates to the GEOS-5 Linear Model
Holdaway, Dan; Kim, Jong G.; Errico, Ron; Gelaro, Ronald; Mahajan, Rahul
2014-01-01
Global Modeling and Assimilation Office (GMAO) is close to having a working 4DVAR system and has developed a linearized version of GEOS-5.This talk outlines a series of improvements made to the linearized dynamics, physics and trajectory.Of particular interest is the development of linearized cloud microphysics, which provides the framework for 'all-sky' data assimilation.
State space model extraction of thermohydraulic systems – Part I: A linear graph approach
International Nuclear Information System (INIS)
Uren, K.R.; Schoor, G. van
2013-01-01
Thermohydraulic simulation codes are increasingly making use of graphical design interfaces. The user can quickly and easily design a thermohydraulic system by placing symbols on the screen resembling system components. These components can then be connected to form a system representation. Such system models may then be used to obtain detailed simulations of the physical system. Usually this kind of simulation models are too complex and not ideal for control system design. Therefore, a need exists for automated techniques to extract lumped parameter models useful for control system design. The goal of this first paper, in a two part series, is to propose a method that utilises a graphical representation of a thermohydraulic system, and a lumped parameter modelling approach, to extract state space models. In this methodology each physical domain of the thermohydraulic system is represented by a linear graph. These linear graphs capture the interaction between all components within and across energy domains – hydraulic, thermal and mechanical. These linear graphs are analysed using a graph-theoretic approach to derive reduced order state space models. These models capture the dominant dynamics of the thermohydraulic system and are ideal for control system design purposes. The proposed state space model extraction method is demonstrated by considering a U-tube system. A non-linear state space model is extracted representing both the hydraulic and thermal domain dynamics of the system. The simulated state space model is compared with a Flownex ® model of the U-tube. Flownex ® is a validated systems thermal-fluid simulation software package. - Highlights: • A state space model extraction methodology based on graph-theoretic concepts. • An energy-based approach to consider multi-domain systems in a common framework. • Allow extraction of transparent (white-box) state space models automatically. • Reduced order models containing only independent state
Double generalized linear compound poisson models to insurance claims data
DEFF Research Database (Denmark)
Andersen, Daniel Arnfeldt; Bonat, Wagner Hugo
2017-01-01
This paper describes the specification, estimation and comparison of double generalized linear compound Poisson models based on the likelihood paradigm. The models are motivated by insurance applications, where the distribution of the response variable is composed by a degenerate distribution...... implementation and illustrate the application of double generalized linear compound Poisson models using a data set about car insurances....
Determining Predictor Importance in Hierarchical Linear Models Using Dominance Analysis
Luo, Wen; Azen, Razia
2013-01-01
Dominance analysis (DA) is a method used to evaluate the relative importance of predictors that was originally proposed for linear regression models. This article proposes an extension of DA that allows researchers to determine the relative importance of predictors in hierarchical linear models (HLM). Commonly used measures of model adequacy in…
Thurstonian models for sensory discrimination tests as generalized linear models
DEFF Research Database (Denmark)
Brockhoff, Per B.; Christensen, Rune Haubo Bojesen
2010-01-01
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......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...
A Neuronal Network Model for Pitch Selectivity and Representation.
Huang, Chengcheng; Rinzel, John
2016-01-01
Pitch is a perceptual correlate of periodicity. Sounds with distinct spectra can elicit the same pitch. Despite the importance of pitch perception, understanding the cellular mechanism of pitch perception is still a major challenge and a mechanistic model of pitch is lacking. A multi-stage neuronal network model is developed for pitch frequency estimation using biophysically-based, high-resolution coincidence detector neurons. The neuronal units respond only to highly coincident input among convergent auditory nerve fibers across frequency channels. Their selectivity for only very fast rising slopes of convergent input enables these slope-detectors to distinguish the most prominent coincidences in multi-peaked input time courses. Pitch can then be estimated from the first-order interspike intervals of the slope-detectors. The regular firing pattern of the slope-detector neurons are similar for sounds sharing the same pitch despite the distinct timbres. The decoded pitch strengths also correlate well with the salience of pitch perception as reported by human listeners. Therefore, our model can serve as a neural representation for pitch. Our model performs successfully in estimating the pitch of missing fundamental complexes and reproducing the pitch variation with respect to the frequency shift of inharmonic complexes. It also accounts for the phase sensitivity of pitch perception in the cases of Schroeder phase, alternating phase and random phase relationships. Moreover, our model can also be applied to stochastic sound stimuli, iterated-ripple-noise, and account for their multiple pitch perceptions.
Chaos game representation (CGR)-walk model for DNA sequences
International Nuclear Information System (INIS)
Jie, Gao; Zhen-Yuan, Xu
2009-01-01
Chaos game representation (CGR) is an iterative mapping technique that processes sequences of units, such as nucleotides in a DNA sequence or amino acids in a protein, in order to determine the coordinates of their positions in a continuous space. This distribution of positions has two features: one is unique, and the other is source sequence that can be recovered from the coordinates so that the distance between positions may serve as a measure of similarity between the corresponding sequences. A CGR-walk model is proposed based on CGR coordinates for the DNA sequences. The CGR coordinates are converted into a time series, and a long-memory ARFIMA (p, d, q) model, where ARFIMA stands for autoregressive fractionally integrated moving average, is introduced into the DNA sequence analysis. This model is applied to simulating real CGR-walk sequence data of ten genomic sequences. Remarkably long-range correlations are uncovered in the data, and the results from these models are reasonably fitted with those from the ARFIMA (p, d, q) model. (cross-disciplinary physics and related areas of science and technology)
Linear control theory for gene network modeling.
Directory of Open Access Journals (Sweden)
Yong-Jun Shin
Full Text Available 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.
Zhang, Xu; Wang, Dongqing; Yu, Zaiyang; Chen, Xiang; Li, Sheng; Zhou, Ping
2017-11-01
This study examines the electromyogram (EMG)-torque relation for chronic stroke survivors using a novel EMG complexity representation. Ten stroke subjects performed a series of submaximal isometric elbow flexion tasks using their affected and contralateral arms, respectively, while a 20-channel linear electrode array was used to record surface EMG from the biceps brachii muscles. The sample entropy (SampEn) of surface EMG signals was calculated with both global and local tolerance schemes. A regression analysis was performed between SampEn of each channel's surface EMG and elbow flexion torque. It was found that a linear regression can be used to well describe the relation between surface EMG SampEn and the torque. Each channel's root mean square (RMS) amplitude of surface EMG signal in the different torque level was computed to determine the channel with the highest EMG amplitude. The slope of the regression (observed from the channel with the highest EMG amplitude) was smaller on the impaired side than on the nonimpaired side in 8 of the 10 subjects, regardless of the tolerance scheme (global or local) and the range of torques (full or matched range) used for comparison. The surface EMG signals from the channels above the estimated muscle innervation zones demonstrated significantly lower levels of complexity compared with other channels between innervation zones and muscle tendons. The study provides a novel point of view of the EMG-torque relation in the complexity domain, and reveals its alterations post stroke, which are associated with complex neural and muscular changes post stroke. The slope difference between channels with regard to innervation zones also confirms the relevance of electrode position in surface EMG analysis.
Forecasting Volatility of Dhaka Stock Exchange: Linear Vs Non-linear models
Directory of Open Access Journals (Sweden)
Masudul Islam
2012-10-01
Full Text Available Prior information about a financial market is very essential for investor to invest money on parches share from the stock market which can strengthen the economy. The study examines the relative ability of various models to forecast daily stock indexes future volatility. The forecasting models that employed from simple to relatively complex ARCH-class models. It is found that among linear models of stock indexes volatility, the moving average model ranks first using root mean square error, mean absolute percent error, Theil-U and Linex loss function criteria. We also examine five nonlinear models. These models are ARCH, GARCH, EGARCH, TGARCH and restricted GARCH models. We find that nonlinear models failed to dominate linear models utilizing different error measurement criteria and moving average model appears to be the best. Then we forecast the next two months future stock index price volatility by the best (moving average model.
DEFF Research Database (Denmark)
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...
Strickland, Tricia K.; Maccini, Paula
2013-01-01
We examined the effects of the Concrete-Representational-Abstract Integration strategy on the ability of secondary students with learning disabilities to multiply linear algebraic expressions embedded within contextualized area problems. A multiple-probe design across three participants was used. Results indicated that the integration of the…
Linear and non-linear autoregressive models for short-term wind speed forecasting
International Nuclear Information System (INIS)
Lydia, M.; Suresh Kumar, S.; Immanuel Selvakumar, A.; Edwin Prem Kumar, G.
2016-01-01
Highlights: • Models for wind speed prediction at 10-min intervals up to 1 h built on time-series wind speed data. • Four different multivariate models for wind speed built based on exogenous variables. • Non-linear models built using three data mining algorithms outperform the linear models. • Autoregressive models based on wind direction perform better than other models. - Abstract: Wind speed forecasting aids in estimating the energy produced from wind farms. The soaring energy demands of the world and minimal availability of conventional energy sources have significantly increased the role of non-conventional sources of energy like solar, wind, etc. Development of models for wind speed forecasting with higher reliability and greater accuracy is the need of the hour. In this paper, models for predicting wind speed at 10-min intervals up to 1 h have been built based on linear and non-linear autoregressive moving average models with and without external variables. The autoregressive moving average models based on wind direction and annual trends have been built using data obtained from Sotavento Galicia Plc. and autoregressive moving average models based on wind direction, wind shear and temperature have been built on data obtained from Centre for Wind Energy Technology, Chennai, India. While the parameters of the linear models are obtained using the Gauss–Newton algorithm, the non-linear autoregressive models are developed using three different data mining algorithms. The accuracy of the models has been measured using three performance metrics namely, the Mean Absolute Error, Root Mean Squared Error and Mean Absolute Percentage Error.
The Linked Dual Representation model of vocal perception and production
Directory of Open Access Journals (Sweden)
Sean eHutchins
2013-11-01
Full Text Available The voice is one of the most important media for communication, yet there is a wide range of abilities in both the perception and production of the voice. In this article, we review this range of abilities, focusing on pitch accuracy as a particularly informative case, and look at the factors underlying these abilities. Several classes of models have been posited describing the relationship between vocal perception and production, and we review the evidence for and against each class of model. We look at how the voice is different from other musical instruments and review evidence about both the association and the dissociation between vocal perception and production abilities. Finally, we introduce the Linked Dual Representation model, a new approach which can account for the broad patterns in prior findings, including trends in the data which might seem to be countervailing. We discuss how this model interacts with higher-order cognition and examine its predictions about several aspects of vocal perception and production.
Applicability of linear and non-linear potential flow models on a Wavestar float
DEFF Research Database (Denmark)
Bozonnet, Pauline; Dupin, Victor; Tona, Paolino
2017-01-01
as a model based on non-linear potential flow theory and weakscatterer hypothesis are successively considered. Simple tests, such as dip tests, decay tests and captive tests enable to highlight the improvements obtained with the introduction of nonlinearities. Float motion under wave actions and without...... control action, limited to small amplitude motion with a single float, is well predicted by the numerical models, including the linear one. Still, float velocity is better predicted by accounting for non-linear hydrostatic and Froude-Krylov forces.......Numerical models based on potential flow theory, including different types of nonlinearities are compared and validated against experimental data for the Wavestar wave energy converter technology. Exact resolution of the rotational motion, non-linear hydrostatic and Froude-Krylov forces as well...
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).
2016-01-05
Computer-aided transformation of PDE models: languages, representations, and a calculus of operations A domain-specific embedded language called...languages, representations, and a calculus of operations Report Title A domain-specific embedded language called ibvp was developed to model initial...Computer-aided transformation of PDE models: languages, representations, and a calculus of operations 1 Vision and background Physical and engineered systems
On form factors of the conjugated field in the non-linear Schroedinger model
Energy Technology Data Exchange (ETDEWEB)
Kozlowski, K.K.
2011-05-15
Izergin-Korepin's lattice discretization of the non-linear Schroedinger model along with Oota's inverse problem provides one with determinant representations for the form factors of the lattice discretized conjugated field operator. We prove that these form factors converge, in the zero lattice spacing limit, to those of the conjugated field operator in the continuous model. We also compute the large-volume asymptotic behavior of such form factors in the continuous model. These are in particular characterized by Fredholm determinants of operators acting on closed contours. We provide a way of defining these Fredholm determinants in the case of generic paramaters. (orig.)
2009-09-01
Resources and Performance. Action Group 19. Representation of Human Behavior. Lanchester , F. W. (1916). Aircraft in warfare . The dawn of the fourth...Operations and non-kinetic warfare . The second keynote presentation, by Mr. Mike Greenley, CAE Inc. provided an industry perspective, noting the need for...concentrated on tactical-conventional warfare and the emergence of world-wide “irregular warfare ” and “small wars” drive the present and future need
Grms or graphical representation of model spaces. Vol. I Basics
International Nuclear Information System (INIS)
Duch, W.
1986-01-01
This book presents a novel approach to the many-body problem in quantum chemistry, nuclear shell-theory and solid-state theory. Many-particle model spaces are visualized using graphs, each path of a graph labeling a single basis function or a subspace of functions. Spaces of a very high dimension are represented by small graphs. Model spaces have structure that is reflected in the architecture of the corresponding graphs, that in turn is reflected in the structure of the matrices corresponding to operators acting in these spaces. Insight into this structure leads to formulation of very efficient computer algorithms. Calculation of matrix elements is reduced to comparison of paths in a graph, without ever looking at the functions themselves. Using only very rudimentary mathematical tools graphical rules of matrix element calculation in abelian cases are derived, in particular segmentation rules obtained in the unitary group approached are rederived. The graphs are solutions of Diophantine equations of the type appearing in different branches of applied mathematics. Graphical representation of model spaces should find as many applications as has been found for diagramatical methods in perturbation theory
The Lie-Poisson structure of integrable classical non-linear sigma models
International Nuclear Information System (INIS)
Bordemann, M.; Forger, M.; Schaeper, U.; Laartz, J.
1993-01-01
The canonical structure of classical non-linear sigma models on Riemannian symmetric spaces, which constitute the most general class of classical non-linear sigma models known to be integrable, is shown to be governed by a fundamental Poisson bracket relation that fits into the r-s-matrix formalism for non-ultralocal integrable models first discussed by Maillet. The matrices r and s are computed explicitly and, being field dependent, satisfy fundamental Poisson bracket relations of their own, which can be expressed in terms of a new numerical matrix c. It is proposed that all these Poisson brackets taken together are representation conditions for a new kind of algebra which, for this class of models, replaces the classical Yang-Baxter algebra governing the canonical structure of ultralocal models. The Poisson brackets for the transition matrices are also computed, and the notorious regularization problem associated with the definition of the Poisson brackets for the monodromy matrices is discussed. (orig.)
Killing scalar of non-linear σ-model on G/H realizing the classical exchange algebra
International Nuclear Information System (INIS)
Aoyama, Shogo
2014-01-01
The Poisson brackets for non-linear σ-models on G/H are set up on the light-like plane. A quantity which transforms irreducibly by the Killing vectors, called Killing scalar, is constructed in an arbitrary representation of G. It is shown to satisfy the classical exchange algebra
A test for the parameters of multiple linear regression models ...
African Journals Online (AJOL)
A test for the parameters of multiple linear regression models is developed for conducting tests simultaneously on all the parameters of multiple linear regression models. The test is robust relative to the assumptions of homogeneity of variances and absence of serial correlation of the classical F-test. Under certain null and ...
Modeling Non-Linear Material Properties in Composite Materials
2016-06-28
Technical Report ARWSB-TR-16013 MODELING NON-LINEAR MATERIAL PROPERTIES IN COMPOSITE MATERIALS Michael F. Macri Andrew G...REPORT TYPE Technical 3. DATES COVERED (From - To) 4. TITLE AND SUBTITLE MODELING NON-LINEAR MATERIAL PROPERTIES IN COMPOSITE MATERIALS ...systems are increasingly incorporating composite materials into their design. Many of these systems subject the composites to environmental conditions
Modeling a space-variant cortical representation for apparent motion.
Wurbs, Jeremy; Mingolla, Ennio; Yazdanbakhsh, Arash
2013-08-06
Receptive field sizes of neurons in early primate visual areas increase with eccentricity, as does temporal processing speed. The fovea is evidently specialized for slow, fine movements while the periphery is suited for fast, coarse movements. In either the fovea or periphery discrete flashes can produce motion percepts. Grossberg and Rudd (1989) used traveling Gaussian activity profiles to model long-range apparent motion percepts. We propose a neural model constrained by physiological data to explain how signals from retinal ganglion cells to V1 affect the perception of motion as a function of eccentricity. Our model incorporates cortical magnification, receptive field overlap and scatter, and spatial and temporal response characteristics of retinal ganglion cells for cortical processing of motion. Consistent with the finding of Baker and Braddick (1985), in our model the maximum flash distance that is perceived as an apparent motion (Dmax) increases linearly as a function of eccentricity. Baker and Braddick (1985) made qualitative predictions about the functional significance of both stimulus and visual system parameters that constrain motion perception, such as an increase in the range of detectable motions as a function of eccentricity and the likely role of higher visual processes in determining Dmax. We generate corresponding quantitative predictions for those functional dependencies for individual aspects of motion processing. Simulation results indicate that the early visual pathway can explain the qualitative linear increase of Dmax data without reliance on extrastriate areas, but that those higher visual areas may serve as a modulatory influence on the exact Dmax increase.
Directory of Open Access Journals (Sweden)
Almonte, R. A.
2016-01-01
Full Text Available El artículo presenta un análisis de investigaciones relacionadas con la formación de conceptos del álgebra lineal, orientadas desde la teoría “descomposición genética” de Dubinsky y la teoria “representación semiótica” de Duval, con el propósito de identificar en las investigaciones el uso de cada concepción teórica y sus aplicaciones en la formación de conceptos básicos de álgebra lineal, se señala como los autores la utilizan para dar explicación a la situación problema tratada, la metodología empleada y resultados obtenidos. Se señalan también las propuestas didácticas recomendadas. Fueron seleccionados articulos y tesis doctorales publicados entre los años 2008 y 2013 en revistas de investigacion de matematica educativa. ABSTRACT: The article presents a synthesis of research reports related to the teaching of linear algebra concepts from the perspective of Dubinsky’s "genetic decomposition" theory and Duval’s "semiotic representation" theory, in order to identify its reference and application in a sample of educational research. The findings include the explanation given to the particular problem-situation, the methodology and outcomes. Pedagogical proposals recommended are also drawn. Articles and dissertations published between 2008 and 2013 in research journals of mathematics education were sampled.
Reliability modelling and simulation of switched linear system ...
African Journals Online (AJOL)
Reliability modelling and simulation of switched linear system control using temporal databases. ... design of fault-tolerant real-time switching systems control and modelling embedded micro-schedulers for complex systems maintenance.
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.
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...
Approximating chiral quark models with linear σ-models
International Nuclear Information System (INIS)
Broniowski, Wojciech; Golli, Bojan
2003-01-01
We study the approximation of chiral quark models with simpler models, obtained via gradient expansion. The resulting Lagrangian of the type of the linear σ-model contains, at the lowest level of the gradient-expanded meson action, an additional term of the form ((1)/(2))A(σ∂ μ σ+π∂ μ π) 2 . We investigate the dynamical consequences of this term and its relevance to the phenomenology of the soliton models of the nucleon. It is found that the inclusion of the new term allows for a more efficient approximation of the underlying quark theory, especially in those cases where dynamics allows for a large deviation of the chiral fields from the chiral circle, such as in quark models with non-local regulators. This is of practical importance, since the σ-models with valence quarks only are technically much easier to treat and simpler to solve than the quark models with the full-fledged Dirac sea
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.
Linear Regression Models for Estimating True Subsurface ...
Indian Academy of Sciences (India)
47
The objective is to minimize the processing time and computer memory required. 10 to carry out inversion .... to the mainland by two long bridges. .... term. In this approach, the model converges when the squared sum of the differences. 143.
Numerical modelling in non linear fracture mechanics
Directory of Open Access Journals (Sweden)
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.
May, Josephine
2018-01-01
Building on the author's previous work on Australian national cinema and schooling, this article explores the representation of the female primary school teacher in the television mini-series entitled "Marion" (Australian Broadcasting Commission, 1974). Using narrative analysis, it argues that this representation is disruptive of…
A phenomenological biological dose model for proton therapy based on linear energy transfer spectra.
Rørvik, Eivind; Thörnqvist, Sara; Stokkevåg, Camilla H; Dahle, Tordis J; Fjaera, Lars Fredrik; Ytre-Hauge, Kristian S
2017-06-01
The relative biological effectiveness (RBE) of protons varies with the radiation quality, quantified by the linear energy transfer (LET). Most phenomenological models employ a linear dependency of the dose-averaged LET (LET d ) to calculate the biological dose. However, several experiments have indicated a possible non-linear trend. Our aim was to investigate if biological dose models including non-linear LET dependencies should be considered, by introducing a LET spectrum based dose model. The RBE-LET relationship was investigated by fitting of polynomials from 1st to 5th degree to a database of 85 data points from aerobic in vitro experiments. We included both unweighted and weighted regression, the latter taking into account experimental uncertainties. Statistical testing was performed to decide whether higher degree polynomials provided better fits to the data as compared to lower degrees. The newly developed models were compared to three published LET d based models for a simulated spread out Bragg peak (SOBP) scenario. The statistical analysis of the weighted regression analysis favored a non-linear RBE-LET relationship, with the quartic polynomial found to best represent the experimental data (P = 0.010). The results of the unweighted regression analysis were on the borderline of statistical significance for non-linear functions (P = 0.053), and with the current database a linear dependency could not be rejected. For the SOBP scenario, the weighted non-linear model estimated a similar mean RBE value (1.14) compared to the three established models (1.13-1.17). The unweighted model calculated a considerably higher RBE value (1.22). The analysis indicated that non-linear models could give a better representation of the RBE-LET relationship. However, this is not decisive, as inclusion of the experimental uncertainties in the regression analysis had a significant impact on the determination and ranking of the models. As differences between the models were
Multiscale geometric modeling of macromolecules I: Cartesian representation
Xia, Kelin; Feng, Xin; Chen, Zhan; Tong, Yiying; Wei, Guo-Wei
2014-01-01
This paper focuses on the geometric modeling and computational algorithm development of biomolecular structures from two data sources: Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in the Eulerian (or Cartesian) representation. Molecular surface (MS) contains non-smooth geometric singularities, such as cusps, tips and self-intersecting facets, which often lead to computational instabilities in molecular simulations, and violate the physical principle of surface free energy minimization. Variational multiscale surface definitions are proposed based on geometric flows and solvation analysis of biomolecular systems. Our approach leads to geometric and potential driven Laplace-Beltrami flows for biomolecular surface evolution and formation. The resulting surfaces are free of geometric singularities and minimize the total free energy of the biomolecular system. High order partial differential equation (PDE)-based nonlinear filters are employed for EMDB data processing. We show the efficacy of this approach in feature-preserving noise reduction. After the construction of protein multiresolution surfaces, we explore the analysis and characterization of surface morphology by using a variety of curvature definitions. Apart from the classical Gaussian curvature and mean curvature, maximum curvature, minimum curvature, shape index, and curvedness are also applied to macromolecular surface analysis for the first time. Our curvature analysis is uniquely coupled to the analysis of electrostatic surface potential, which is a by-product of our variational multiscale solvation models. As an expository investigation, we particularly emphasize the numerical algorithms and computational protocols for practical applications of the above multiscale geometric models. Such information may otherwise be scattered over the vast literature on this topic. Based on the curvature and electrostatic analysis from our multiresolution surfaces, we introduce a new concept, the
Multiscale geometric modeling of macromolecules I: Cartesian representation
Energy Technology Data Exchange (ETDEWEB)
Xia, Kelin [Department of Mathematics, Michigan State University, MI 48824 (United States); Feng, Xin [Department of Computer Science and Engineering, Michigan State University, MI 48824 (United States); Chen, Zhan [Department of Mathematics, Michigan State University, MI 48824 (United States); Tong, Yiying [Department of Computer Science and Engineering, Michigan State University, MI 48824 (United States); Wei, Guo-Wei, E-mail: wei@math.msu.edu [Department of Mathematics, Michigan State University, MI 48824 (United States); Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824 (United States)
2014-01-15
This paper focuses on the geometric modeling and computational algorithm development of biomolecular structures from two data sources: Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in the Eulerian (or Cartesian) representation. Molecular surface (MS) contains non-smooth geometric singularities, such as cusps, tips and self-intersecting facets, which often lead to computational instabilities in molecular simulations, and violate the physical principle of surface free energy minimization. Variational multiscale surface definitions are proposed based on geometric flows and solvation analysis of biomolecular systems. Our approach leads to geometric and potential driven Laplace–Beltrami flows for biomolecular surface evolution and formation. The resulting surfaces are free of geometric singularities and minimize the total free energy of the biomolecular system. High order partial differential equation (PDE)-based nonlinear filters are employed for EMDB data processing. We show the efficacy of this approach in feature-preserving noise reduction. After the construction of protein multiresolution surfaces, we explore the analysis and characterization of surface morphology by using a variety of curvature definitions. Apart from the classical Gaussian curvature and mean curvature, maximum curvature, minimum curvature, shape index, and curvedness are also applied to macromolecular surface analysis for the first time. Our curvature analysis is uniquely coupled to the analysis of electrostatic surface potential, which is a by-product of our variational multiscale solvation models. As an expository investigation, we particularly emphasize the numerical algorithms and computational protocols for practical applications of the above multiscale geometric models. Such information may otherwise be scattered over the vast literature on this topic. Based on the curvature and electrostatic analysis from our multiresolution surfaces, we introduce a new concept, the
Integer Representations towards Efficient Counting in the Bit Probe Model
DEFF Research Database (Denmark)
Brodal, Gerth Stølting; Greve, Mark; Pandey, Vineet
2011-01-01
Abstract We consider the problem of representing numbers in close to optimal space and supporting increment, decrement, addition and subtraction operations efficiently. We study the problem in the bit probe model and analyse the number of bits read and written to perform the operations, both...... in the worst-case and in the average-case. A counter is space-optimal if it represents any number in the range [0,...,2 n − 1] using exactly n bits. We provide a space-optimal counter which supports increment and decrement operations by reading at most n − 1 bits and writing at most 3 bits in the worst......-case. To the best of our knowledge, this is the first such representation which supports these operations by always reading strictly less than n bits. For redundant counters where we only need to represent numbers in the range [0,...,L] for some integer L bits, we define the efficiency...
The representation of knowledge within model-based control systems
International Nuclear Information System (INIS)
Weygand, D.P.; Koul, R.
1987-01-01
Representation of knowledge in artificially intelligent systems is discussed. Types of knowledge that might need to be represented in AI systems are listed, and include knowledge about objects, events, knowledge about how to do things, and knowledge about what human beings know (meta-knowledge). The use of knowledge in AI systems is discussed in terms of acquiring and retrieving knowledge and reasoning about known facts. Different kinds of reasonings or representations are ghen described with some examples given. These include formal reasoning or logical representation, which is related to mathematical logic, production systems, which are based on the idea of condition-action pairs (production), procedural reasoning, which uses pre-formed plans to solve problems, frames, which provide a structure for representing knowledge in an organized manner, direct analogical representations, which represent knowledge in such a manner that permits some observation without deduction
Random effect selection in generalised linear models
DEFF Research Database (Denmark)
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...
Model Order Reduction for Non Linear Mechanics
Pinillo, Rubén
2017-01-01
Context: Automotive industry is moving towards a new generation of cars. Main idea: Cars are furnished with radars, cameras, sensors, etc… providing useful information about the environment surrounding the car. Goals: Provide an efficient model for the radar input/output. Reducing computational costs by means of big data techniques.
Identification of Influential Points in a Linear Regression Model
Directory of Open Access Journals (Sweden)
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.
Heterotic sigma models and non-linear strings
International Nuclear Information System (INIS)
Hull, C.M.
1986-01-01
The two-dimensional supersymmetric non-linear sigma models are examined with respect to the heterotic string. The paper was presented at the workshop on :Supersymmetry and its applications', Cambridge, United Kingdom, 1985. The non-linear sigma model with Wess-Zumino-type term, the coupling of the fermionic superfields to the sigma model, super-conformal invariance, and the supersymmetric string, are all discussed. (U.K.)
Linear latent variable models: the lava-package
DEFF Research Database (Denmark)
Holst, Klaus Kähler; Budtz-Jørgensen, Esben
2013-01-01
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......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...
On-line control models for the Stanford Linear Collider
International Nuclear Information System (INIS)
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
The representation of knowledge within model-based control systems
International Nuclear Information System (INIS)
Weygand, D.P.; Koul, R.
1987-01-01
The ability to represent knowledge is often considered essential to build systems with reasoning capabilities. In computer science, a good solution often depends on a good representation. The first step in development of most computer applications is selection of a representation for the input, output, and intermediate results that the program will operate upon. For applications in artificial intelligence, this initial choice of representation is especially important. This is because the possible representational paradigms are diverse and the forcing criteria for the choice are usually not clear in the beginning. Yet, the consequences of an inadequate choice can be devastating in the later state of a project if it is discovered that critical information cannot be encoded within the chosen representational paradigm. Problems arise when designing representational systems to support any kind of Knowledge-Base System, that is a computer system that uses knowledge to perform some task. The general case of knowledge-based systems can be thought of as reasoning agents applying knowledge to achieve goals. Artificial Intelligence (AI) research involves building computer systems to perform tasks of perception and reasoning, as well as storage and retrieval of data. The problem of automatically perceiving large patterns in data is a perceptual task that begins to be important for many expert systems applications. Most of AI research assumes that what needs to be represented is known a priori; an AI researcher's job is just figuring out how to encode the information in the system's data structure and procedures. 10 refs
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.
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
Modelling a linear PM motor including magnetic saturation
Polinder, H.; Slootweg, J.G.; Compter, J.C.; Hoeijmakers, M.J.
2002-01-01
The use of linear permanent-magnet (PM) actuators increases in a wide variety of applications because of the high force density, robustness and accuracy. The paper describes the modelling of a linear PM motor applied in, for example, wafer steppers, including magnetic saturation. This is important
Application of the simplex method of linear programming model to ...
African Journals Online (AJOL)
This work discussed how the simplex method of linear programming could be used to maximize the profit of any business firm using Saclux Paint Company as a case study. It equally elucidated the effect variation in the optimal result obtained from linear programming model, will have on any given firm. It was demonstrated ...
Genetic parameters for racing records in trotters using linear and generalized linear models.
Suontama, M; van der Werf, J H J; Juga, J; Ojala, M
2012-09-01
Heritability and repeatability and genetic and phenotypic correlations were estimated for trotting race records with linear and generalized linear models using 510,519 records on 17,792 Finnhorses and 513,161 records on 25,536 Standardbred trotters. Heritability and repeatability were estimated for single racing time and earnings traits with linear models, and logarithmic scale was used for racing time and fourth-root scale for earnings to correct for nonnormality. Generalized linear models with a gamma distribution were applied for single racing time and with a multinomial distribution for single earnings traits. In addition, genetic parameters for annual earnings were estimated with linear models on the observed and fourth-root scales. Racing success traits of single placings, winnings, breaking stride, and disqualifications were analyzed using generalized linear models with a binomial distribution. Estimates of heritability were greatest for racing time, which ranged from 0.32 to 0.34. Estimates of heritability were low for single earnings with all distributions, ranging from 0.01 to 0.09. Annual earnings were closer to normal distribution than single earnings. Heritability estimates were moderate for annual earnings on the fourth-root scale, 0.19 for Finnhorses and 0.27 for Standardbred trotters. Heritability estimates for binomial racing success variables ranged from 0.04 to 0.12, being greatest for winnings and least for breaking stride. Genetic correlations among racing traits were high, whereas phenotypic correlations were mainly low to moderate, except correlations between racing time and earnings were high. On the basis of a moderate heritability and moderate to high repeatability for racing time and annual earnings, selection of horses for these traits is effective when based on a few repeated records. Because of high genetic correlations, direct selection for racing time and annual earnings would also result in good genetic response in racing success.
Khaligh-Razavi, Seyed-Mahdi; Henriksson, Linda; Kay, Kendrick; Kriegeskorte, Nikolaus
2017-02-01
Studies of the primate visual system have begun to test a wide range of complex computational object-vision models. Realistic models have many parameters, which in practice cannot be fitted using the limited amounts of brain-activity data typically available. Task performance optimization (e.g. using backpropagation to train neural networks) provides major constraints for fitting parameters and discovering nonlinear representational features appropriate for the task (e.g. object classification). Model representations can be compared to brain representations in terms of the representational dissimilarities they predict for an image set. This method, called representational similarity analysis (RSA), enables us to test the representational feature space as is (fixed RSA) or to fit a linear transformation that mixes the nonlinear model features so as to best explain a cortical area's representational space (mixed RSA). Like voxel/population-receptive-field modelling, mixed RSA uses a training set (different stimuli) to fit one weight per model feature and response channel (voxels here), so as to best predict the response profile across images for each response channel. We analysed response patterns elicited by natural images, which were measured with functional magnetic resonance imaging (fMRI). We found that early visual areas were best accounted for by shallow models, such as a Gabor wavelet pyramid (GWP). The GWP model performed similarly with and without mixing, suggesting that the original features already approximated the representational space, obviating the need for mixing. However, a higher ventral-stream visual representation (lateral occipital region) was best explained by the higher layers of a deep convolutional network and mixing of its feature set was essential for this model to explain the representation. We suspect that mixing was essential because the convolutional network had been trained to discriminate a set of 1000 categories, whose frequencies
Directory of Open Access Journals (Sweden)
Daryl McPadden
2017-11-01
Full Text Available Representation use is a critical skill for learning, problem solving, and communicating in science, especially in physics where multiple representations often scaffold the understanding of a phenomenon. University Modeling Instruction, which is an active-learning, research-based introductory physics curriculum centered on students’ use of scientific models, has made representation use a primary learning goal with explicit class time devoted to introducing and coordinating representations as part of the model building process. However, because of the semester break, the second semester course, Modeling Instruction-Electricity and Magnetism (MI-EM, contains a mixture of students who are returning from the Modeling Instruction-mechanics course (to whom we refer to as “returning students” and students who are new to Modeling Instruction with the MI-EM course (to whom we refer to as “new students”. In this study, we analyze the impact of MI-EM on students’ representation choices across the introductory physics content for these different groups of students by examining both what individual representations students choose and their average number of representations on a modified card-sort survey with a variety of mechanics and EM questions. Using Wilcoxon-signed-rank tests, Wilcoxon-Mann-Whitney tests, Cliff’s delta effect sizes, and box plots, we compare students’ representation choices from pre- to postsemester, from new and returning students, and from mechanics and EM content. We find that there is a significant difference between returning and new students’ representation choices, which serves as a baseline comparison between Modeling Instruction and traditional lecture-based physics classes. We also find that returning students maintain a high representation use across the MI-EM semester, while new students see significant growth in their representation use regardless of content.
Bengtson, Barbara J.
2013-01-01
Understanding the linear relationship of numbers is essential for doing practical and abstract mathematics throughout education and everyday life. There is evidence that number line activities increase learners' number sense, improving the linearity of mental number line representations (Siegler & Ramani, 2009). Mental representations of…
Stull, Andrew T.; Hegarty, Mary
2016-01-01
This study investigated the development of representational competence among organic chemistry students by using 3D (concrete and virtual) models as aids for teaching students to translate between multiple 2D diagrams. In 2 experiments, students translated between different diagrams of molecules and received verbal feedback in 1 of the following 3…
Linear approximation model network and its formation via ...
Indian Academy of Sciences (India)
niques, an alternative `linear approximation model' (LAM) network approach is .... network is LPV, existing LTI theory is difficult to apply (Kailath 1980). ..... Beck J V, Arnold K J 1977 Parameter estimation in engineering and science (New York: ...
Sphaleron in a non-linear sigma model
International Nuclear Information System (INIS)
Sogo, Kiyoshi; Fujimoto, Yasushi.
1989-08-01
We present an exact classical saddle point solution in a non-linear sigma model. It has a topological charge 1/2 and mediates the vacuum transition. The quantum fluctuations and the transition rate are also examined. (author)
On D-branes from gauged linear sigma models
International Nuclear Information System (INIS)
Govindarajan, S.; Jayaraman, T.; Sarkar, T.
2001-01-01
We study both A-type and B-type D-branes in the gauged linear sigma model by considering worldsheets with boundary. The boundary conditions on the matter and vector multiplet fields are first considered in the large-volume phase/non-linear sigma model limit of the corresponding Calabi-Yau manifold, where we find that we need to add a contact term on the boundary. These considerations enable to us to derive the boundary conditions in the full gauged linear sigma model, including the addition of the appropriate boundary contact terms, such that these boundary conditions have the correct non-linear sigma model limit. Most of the analysis is for the case of Calabi-Yau manifolds with one Kaehler modulus (including those corresponding to hypersurfaces in weighted projective space), though we comment on possible generalisations
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.
Study of linear induction motor characteristics : the Mosebach model
1976-05-31
This report covers the Mosebach theory of the double-sided linear induction motor, starting with the ideallized model and accompanying assumptions, and ending with relations for thrust, airgap power, and motor efficiency. Solutions of the magnetic in...
Study of linear induction motor characteristics : the Oberretl model
1975-05-30
The Oberretl theory of the double-sided linear induction motor (LIM) is examined, starting with the idealized model and accompanying assumptions, and ending with relations for predicted thrust, airgap power, and motor efficiency. The effect of varyin...
Optimization Research of Generation Investment Based on Linear Programming Model
Wu, Juan; Ge, Xueqian
Linear programming is an important branch of operational research and it is a mathematical method to assist the people to carry out scientific management. GAMS is an advanced simulation and optimization modeling language and it will combine a large number of complex mathematical programming, such as linear programming LP, nonlinear programming NLP, MIP and other mixed-integer programming with the system simulation. In this paper, based on the linear programming model, the optimized investment decision-making of generation is simulated and analyzed. At last, the optimal installed capacity of power plants and the final total cost are got, which provides the rational decision-making basis for optimized investments.
Improving the spatial representation of basin hydrology and flow processes in the SWAT model
Rathjens, Hendrik
2014-01-01
This dissertation aims at improving the spatial representation of basin hydrology and flow processes in the SWAT model. Die vorliegende Dissertation stellt die methodischen Grundlage zur räumlich differenzierten Modellierung mit dem Modell SWAT dar.
Energy Technology Data Exchange (ETDEWEB)
Karahan, Aydin, E-mail: karahan@mit.ed [Center for Advanced Nuclear Energy Systems, Nuclear Science and Engineering Department, Massachusetts Institute of Technology, 77 Massachusetts Avenue, 24-204, Cambridge, MA 02139 (United States); Kazimi, Mujid S. [Center for Advanced Nuclear Energy Systems, Nuclear Science and Engineering Department, Massachusetts Institute of Technology, 77 Massachusetts Avenue, 24-204, Cambridge, MA 02139 (United States)
2011-02-15
Research highlights: Essence of more physics based modeling approaches to the fuel behavior problem is emphasized. Demonstrations on modeling of metallic and oxide fuel dimensional changes and fission gas behavior with more physics based and semi-empirical approaches are given. Essence of fuel clad chemical interaction modeling of the metallic fuel in an appropriate way and implications during short and long term transients for sodium fast reactor applications are discussed. - Abstract: This work emphasizes the relevance of representation of appropriate mechanisms for understanding the actual physical behavior of the fuel pin under irradiation. Replacing fully empirical simplified treatments with more rigorous semi-empirical models which include the important pieces of physics, would open the path to more accurately capture the sensitivity to various parameters such as operating conditions, geometry, composition, and enhance the uncertainty quantification process. Steady state and transient fuel behavior demonstration examples and implications are given for sodium fast reactor metallic fuels by using FEAST-METAL. The essence of appropriate modeling of the fuel clad mechanical interaction and fuel clad chemical interaction of the metallic fuels are emphasized. Furthermore, validation efforts for oxide fuel pellet swelling behavior at high temperature and high burnup LWR conditions and comparison with FRAPCON-EP and FRAPCON-3.4 codes will be given. The value of discriminating the oxide fuel swelling modes, instead of applying a linear line, is pointed out. Future directions on fuel performance modeling will be addressed.
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 comparison of linear tyre models for analysing shimmy
Besselink, I.J.M.; Maas, J.W.L.H.; Nijmeijer, H.
2011-01-01
A comparison is made between three linear, dynamic tyre models using low speed step responses and yaw oscillation tests. The match with the measurements improves with increasing complexity of the tyre model. Application of the different tyre models to a two degree of freedom trailing arm suspension
Unification of three linear models for the transient visual system
Brinker, den A.C.
1989-01-01
Three different linear filters are considered as a model describing the experimentally determined triphasic impulse responses of discs. These impulse responses arc associated with the transient visual system. Each model reveals a different feature of the system. Unification of the models is
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
Directory of Open Access Journals (Sweden)
H. Vazquez-Leal
2014-01-01
Full Text Available We present a homotopy continuation method (HCM for finding multiple operating points of nonlinear circuits composed of devices modelled by using piecewise linear (PWL representations. We propose an adaptation of the modified spheres path tracking algorithm to trace the homotopy trajectories of PWL circuits. In order to assess the benefits of this proposal, four nonlinear circuits composed of piecewise linear modelled devices are analysed to determine their multiple operating points. The results show that HCM can find multiple solutions within a single homotopy trajectory. Furthermore, we take advantage of the fact that homotopy trajectories are PWL curves meant to replace the multidimensional interpolation and fine tuning stages of the path tracking algorithm with a simple and highly accurate procedure based on the parametric straight line equation.
Linearized models for a new magnetic control in MAST
Energy Technology Data Exchange (ETDEWEB)
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.
Linearized models for a new magnetic control in MAST
International Nuclear Information System (INIS)
Artaserse, G.; Maviglia, F.; Albanese, R.; McArdle, G.J.; Pangione, L.
2013-01-01
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
An, Gary
2009-01-01
The sheer volume of biomedical research threatens to overwhelm the capacity of individuals to effectively process this information. Adding to this challenge is the multiscale nature of both biological systems and the research community as a whole. Given this volume and rate of generation of biomedical information, the research community must develop methods for robust representation of knowledge in order for individuals, and the community as a whole, to "know what they know." Despite increasing emphasis on "data-driven" research, the fact remains that researchers guide their research using intuitively constructed conceptual models derived from knowledge extracted from publications, knowledge that is generally qualitatively expressed using natural language. Agent-based modeling (ABM) is a computational modeling method that is suited to translating the knowledge expressed in biomedical texts into dynamic representations of the conceptual models generated by researchers. The hierarchical object-class orientation of ABM maps well to biomedical ontological structures, facilitating the translation of ontologies into instantiated models. Furthermore, ABM is suited to producing the nonintuitive behaviors that often "break" conceptual models. Verification in this context is focused at determining the plausibility of a particular conceptual model, and qualitative knowledge representation is often sufficient for this goal. Thus, utilized in this fashion, ABM can provide a powerful adjunct to other computational methods within the research process, as well as providing a metamodeling framework to enhance the evolution of biomedical ontologies.
Kitaev honeycomb model. Majorana fermion representation and disorder
International Nuclear Information System (INIS)
Zschocke, Fabian
2016-01-01
Majorana representation we are able to formulate the problem in a way that can be analyzed using Wilson's numerical renormalization group. The numerics reveal an impurity entropy which can be explained by localized Majorana fermions. Through the representation of the Kitaev model in terms of quasi-particles an elegant description of a complex, strongly correlated system is possible. The results of this thesis indicate that these Majorana acquire a relevant physical meaning. If one can localize them, for example with the help of magnetic impurities, a direct experimental observation would be feasible.
McPadden, Daryl; Brewe, Eric
2017-01-01
Representation use is a critical skill for learning, problem solving, and communicating in science, especially in physics where multiple representations often scaffold the understanding of a phenomenon. University Modeling Instruction, which is an active-learning, research-based introductory physics curriculum centered on students' use of…
H∞ /H2 model reduction through dilated linear matrix inequalities
DEFF Research Database (Denmark)
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 $n,r,s in field{N}$. Arb......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...
Non-linear Growth Models in Mplus and SAS
Grimm, Kevin J.; Ram, Nilam
2013-01-01
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. PMID:23882134
Variance Function Partially Linear Single-Index Models1.
Lian, Heng; Liang, Hua; Carroll, Raymond J
2015-01-01
We consider heteroscedastic regression models where the mean function is a partially linear single index model and the variance function depends upon a generalized partially linear single index model. We do not insist that the variance function depend only upon the mean function, as happens in the classical generalized partially linear single index model. We develop efficient and practical estimation methods for the variance function and for the mean function. Asymptotic theory for the parametric and nonparametric parts of the model is developed. Simulations illustrate the results. An empirical example involving ozone levels is used to further illustrate the results, and is shown to be a case where the variance function does not depend upon the mean function.
Comparison between linear quadratic and early time dose models
International Nuclear Information System (INIS)
Chougule, A.A.; Supe, S.J.
1993-01-01
During the 70s, much interest was focused on fractionation in radiotherapy with the aim of improving tumor control rate without producing unacceptable normal tissue damage. To compare the radiobiological effectiveness of various fractionation schedules, empirical formulae such as Nominal Standard Dose, Time Dose Factor, Cumulative Radiation Effect and Tumour Significant Dose, were introduced and were used despite many shortcomings. It has been claimed that a recent linear quadratic model is able to predict the radiobiological responses of tumours as well as normal tissues more accurately. We compared Time Dose Factor and Tumour Significant Dose models with the linear quadratic model for tumour regression in patients with carcinomas of the cervix. It was observed that the prediction of tumour regression estimated by the Tumour Significant Dose and Time Dose factor concepts varied by 1.6% from that of the linear quadratic model prediction. In view of the lack of knowledge of the precise values of the parameters of the linear quadratic model, it should be applied with caution. One can continue to use the Time Dose Factor concept which has been in use for more than a decade as its results are within ±2% as compared to that predicted by the linear quadratic model. (author). 11 refs., 3 figs., 4 tabs
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).
Non-linear calibration models for near infrared spectroscopy
DEFF Research Database (Denmark)
Ni, Wangdong; Nørgaard, Lars; Mørup, Morten
2014-01-01
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), 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...
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.
Interactive Shape Modeling using a Skeleton-Mesh Co-Representation
DEFF Research Database (Denmark)
Bærentzen, Jacob Andreas; Abdrashitov, Rinat; Singh, Karan
2014-01-01
We introduce the Polar-Annular Mesh representation (PAM). A PAM is a mesh-skeleton co-representation designed for the modeling of 3D organic, articulated shapes. A PAM represents a manifold mesh as a partition of polar (triangle fans) and annular (rings of quads) regions. The skeletal topology of...... a PAM to a quad-only mesh. We further present a PAM-based multi-touch sculpting application in order to demonstrate its utility as a shape representation for the interactive modeling of organic, articulated figures as well as for editing and posing of pre-existing models....
Matrix model and time-like linear dila ton matter
International Nuclear Information System (INIS)
Takayanagi, Tadashi
2004-01-01
We consider a matrix model description of the 2d string theory whose matter part is given by a time-like linear dilaton CFT. This is equivalent to the c=1 matrix model with a deformed, but very simple Fermi surface. Indeed, after a Lorentz transformation, the corresponding 2d spacetime is a conventional linear dila ton background with a time-dependent tachyon field. We show that the tree level scattering amplitudes in the matrix model perfectly agree with those computed in the world-sheet theory. The classical trajectories of fermions correspond to the decaying D-boranes in the time-like linear dilaton CFT. We also discuss the ground ring structure. Furthermore, we study the properties of the time-like Liouville theory by applying this matrix model description. We find that its ground ring structure is very similar to that of the minimal string. (author)
TENSOR DECOMPOSITIONS AND SPARSE LOG-LINEAR MODELS
Johndrow, James E.; Bhattacharya, Anirban; Dunson, David B.
2017-01-01
Contingency table analysis routinely relies on log-linear models, with latent structure analysis providing a common alternative. Latent structure models lead to a reduced rank tensor factorization of the probability mass function for multivariate categorical data, while log-linear models achieve dimensionality reduction through sparsity. Little is known about the relationship between these notions of dimensionality reduction in the two paradigms. We derive several results relating the support of a log-linear model to nonnegative ranks of the associated probability tensor. Motivated by these findings, we propose a new collapsed Tucker class of tensor decompositions, which bridge existing PARAFAC and Tucker decompositions, providing a more flexible framework for parsimoniously characterizing multivariate categorical data. Taking a Bayesian approach to inference, we illustrate empirical advantages of the new decompositions. PMID:29332971
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
Pozo, Carlos; Marín-Sanguino, Alberto; Alves, Rui; Guillén-Gosálbez, Gonzalo; Jiménez, Laureano; Sorribas, Albert
2011-08-25
Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.
Directory of Open Access Journals (Sweden)
Sorribas Albert
2011-08-01
Full Text Available Abstract Background Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.
Improving the Representation of Soluble Iron in Climate Models
Energy Technology Data Exchange (ETDEWEB)
Perez Garcia-Pando, Carlos [Columbia Univ., New York, NY (United States)
2016-03-13
attached to aggregates of other minerals. This is another challenge that has been tackled by the project. The project has produced a major step forward on our understanding of the key processes needed to predict the mineral composition of dust aerosols by connecting theory, modeling and observations. The project has produced novel semi-empirical and theoretical methods to estimate the emitted size distribution and mineral composition of dust aerosols. These methods account for soil aggregates that are potentially emitted from the original undisturbed soil but are destroyed during wet sieving. The methods construct the emitted size distribution of individual minerals building upon brittle fragmentation theory, reconstructions of wet-sieved soil mineral size distributions, and/or characteristic mineral size distributions estimated from observations at times of high concentration. Based on an unprecedented evaluation with a new global compilation of observations produced with the project support, we showed that the new methods remedy some key deficiencies compared to the previous state-of-the-art. This includes the correct representation of Fe-bearing phyllosilicates at silt sizes, where they are abundant according to observations. In addition, the quartz fraction of silt particles is in better agreement with measured values. In addition, we represent an additional class of iron oxide aerosol that is a small impurity embedded within other minerals, allowing it to travel farther than in its pure crystalline state. We assume that these impurities are least frequent in soils rich in iron oxides (as a result of the assumed effect of weathering that creates pure iron oxide crystals). The mineral composition of dust is also important to other interaction with climate - through shortwave absorption and radiative forcing, nucleation of cloud droplets and ice crystals, and the heterogeneous formation of sulfates and nitrates - and to its impacts upon human health. Despite the
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.
1985-01-01
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.
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.
CONTRIBUTIONS TO THE FINITE ELEMENT MODELING OF LINEAR ULTRASONIC MOTORS
Directory of Open Access Journals (Sweden)
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
Linear and Nonlinear Career Models: Metaphors, Paradigms, and Ideologies.
Buzzanell, Patrice M.; Goldzwig, Steven R.
1991-01-01
Examines the linear or bureaucratic career models (dominant in career research, metaphors, paradigms, and ideologies) which maintain career myths of flexibility and individualized routes to success in organizations incapable of offering such versatility. Describes nonlinear career models which offer suggestive metaphors for re-visioning careers…
International Nuclear Information System (INIS)
Khrennikov, Andrei
2003-01-01
The contextual approach to the Kolmogorov probability model gives the possibility to represent this conventional model as a quantum structure, i.e., by using complex amplitudes of probabilities (or in the abstract approach - in a Hilbert space). Classical (Kolmogorovian) random variables are represented by in general noncommutative operators in the Hilbert space. The existence of such a contextual representation of the Kolmogorovian model looks very surprising in the view of the orthodox quantum tradition. However, our model can peacefully coexist with various 'no-go' theorems (e.g., von Neumann, Kochen and Specker, Bell, ...)
Directory of Open Access Journals (Sweden)
Tomas eVeloz
2015-11-01
Full Text Available Quantum models of concept combinations have been successful in representing various experimental situations that cannot be accommodated by traditional models based on classical probability or fuzzy set theory. In many cases, the focus has been on producing a representation that fits experimental results to validate quantum models. However, these representations are not always consistent with the cognitive modeling principles. Moreover, some important issues related to the representation of concepts such as the dimensionality of the realization space, the uniqueness of solutions, and the compatibility of measurements, have been overlooked.In this paper, we provide a dimensional analysis of the realization space for the two-sector Fock space model for conjunction of concepts focusing on the first and second sectors separately. We then introduce various representation of concepts that arise from the use of unitary operators in the realization space. In these concrete representations, a pair of concepts and their combination are modeled by a single conceptual state, and by a collection of exemplar-dependent operators. Therefore, they are consistent with cognitive modeling principles. %Moreover, we show that each representation is unique up to change of basis. This framework not only provides a uniform approach to model an entire data set, but, because all measurement operators are expressed in the same basis, allows us to address the question of compatibility of measurements. In particular, we present evidence that it may be possible to predict non-commutative effects from partial measurements of conceptual combinations.
Low-energy limit of the extended Linear Sigma Model
Energy Technology Data Exchange (ETDEWEB)
Divotgey, Florian [Johann Wolfgang Goethe-Universitaet, Institut fuer Theoretische Physik, Frankfurt am Main (Germany); Kovacs, Peter [Wigner Research Center for Physics, Hungarian Academy of Sciences, Institute for Particle and Nuclear Physics, Budapest (Hungary); GSI Helmholtzzentrum fuer Schwerionenforschung, ExtreMe Matter Institute, Darmstadt (Germany); Giacosa, Francesco [Johann Wolfgang Goethe-Universitaet, Institut fuer Theoretische Physik, Frankfurt am Main (Germany); Jan-Kochanowski University, Institute of Physics, Kielce (Poland); Rischke, Dirk H. [Johann Wolfgang Goethe-Universitaet, Institut fuer Theoretische Physik, Frankfurt am Main (Germany); University of Science and Technology of China, Interdisciplinary Center for Theoretical Study and Department of Modern Physics, Hefei, Anhui (China)
2018-01-15
The extended Linear Sigma Model is an effective hadronic model based on the linear realization of chiral symmetry SU(N{sub f}){sub L} x SU(N{sub f}){sub R}, with (pseudo)scalar and (axial-)vector mesons as degrees of freedom. In this paper, we study the low-energy limit of the extended Linear Sigma Model (eLSM) for N{sub f} = flavors by integrating out all fields except for the pions, the (pseudo-)Nambu-Goldstone bosons of chiral symmetry breaking. The resulting low-energy effective action is identical to Chiral Perturbation Theory (ChPT) after choosing a representative for the coset space generated by chiral symmetry breaking and expanding it in powers of (derivatives of) the pion fields. The tree-level values of the coupling constants of the effective low-energy action agree remarkably well with those of ChPT. (orig.)
Linear Power-Flow Models in Multiphase Distribution Networks: Preprint
Energy Technology Data Exchange (ETDEWEB)
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.
Haili, Hasnawati; Maknun, Johar; Siahaan, Parsaoran
2017-08-01
Physics is a lessons that related to students' daily experience. Therefore, before the students studying in class formally, actually they have already have a visualization and prior knowledge about natural phenomenon and could wide it themselves. The learning process in class should be aimed to detect, process, construct, and use students' mental model. So, students' mental model agree with and builds in the right concept. The previous study held in MAN 1 Muna informs that in learning process the teacher did not pay attention students' mental model. As a consequence, the learning process has not tried to build students' mental modelling ability (MMA). The purpose of this study is to describe the improvement of students' MMA as a effect of problem solving based learning model with multiple representations approach. This study is pre experimental design with one group pre post. It is conducted in XI IPA MAN 1 Muna 2016/2017. Data collection uses problem solving test concept the kinetic theory of gasses and interview to get students' MMA. The result of this study is clarification students' MMA which is categorized in 3 category; High Mental Modelling Ability (H-MMA) for 7Mental Modelling Ability (M-MMA) for 3Mental Modelling Ability (L-MMA) for 0 ≤ x ≤ 3 score. The result shows that problem solving based learning model with multiple representations approach can be an alternative to be applied in improving students' MMA.
Modelling and measurement of a moving magnet linear compressor performance
International Nuclear Information System (INIS)
Liang, Kun; Stone, Richard; Davies, Gareth; Dadd, Mike; Bailey, Paul
2014-01-01
A novel moving magnet linear compressor with clearance seals and flexure bearings has been designed and constructed. It is suitable for a refrigeration system with a compact heat exchanger, such as would be needed for CPU cooling. The performance of the compressor has been experimentally evaluated with nitrogen and a mathematical model has been developed to evaluate the performance of the linear compressor. The results from the compressor model and the measurements have been compared in terms of cylinder pressure, the ‘P–V’ loop, stroke, mass flow rate and shaft power. The cylinder pressure was not measured directly but was derived from the compressor dynamics and the motor magnetic force characteristics. The comparisons indicate that the compressor model is well validated and can be used to study the performance of this type of compressor, to help with design optimization and the identification of key parameters affecting the system transients. The electrical and thermodynamic losses were also investigated, particularly for the design point (stroke of 13 mm and pressure ratio of 3.0), since a full understanding of these can lead to an increase in compressor efficiency. - Highlights: • Model predictions of the performance of a novel moving magnet linear compressor. • Prototype linear compressor performance measurements using nitrogen. • Reconstruction of P–V loops using a model of the dynamics and electromagnetics. • Close agreement between the model and measurements for the P–V loops. • The design point motor efficiency was 74%, with potential improvements identified
The minimal linear σ model for the Goldstone Higgs
International Nuclear Information System (INIS)
Feruglio, F.; Gavela, M.B.; Kanshin, K.; Machado, P.A.N.; Rigolin, S.; Saa, S.
2016-01-01
In the context of the minimal SO(5) linear σ-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 σ. Varying the σ 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.
A variational formulation for linear models in coupled dynamic thermoelasticity
International Nuclear Information System (INIS)
Feijoo, R.A.; Moura, C.A. de.
1981-07-01
A variational formulation for linear models in coupled dynamic thermoelasticity which quite naturally motivates the design of a numerical scheme for the problem, is studied. When linked to regularization or penalization techniques, this algorithm may be applied to more general models, namely, the ones that consider non-linear constraints associated to variational inequalities. The basic postulates of Mechanics and Thermodynamics as well as some well-known mathematical techniques are described. A thorough description of the algorithm implementation with the finite-element method is also provided. Proofs for existence and uniqueness of solutions and for convergence of the approximations are presented, and some numerical results are exhibited. (Author) [pt
Energy Technology Data Exchange (ETDEWEB)
Bryan, Frank [Univ. of Connecticut, Storrs, CT (United States); Dennis, John [Univ. of Connecticut, Storrs, CT (United States); MacCready, Parker [Univ. of Connecticut, Storrs, CT (United States); Whitney, Michael M. [Univ. of Connecticut, Storrs, CT (United States)
2016-09-30
This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation.
Villeneuve, Jérôme; Cadoz, Claude; Castagné, Nicolas
2015-01-01
The motivation of this paper is to highlight the importance of visual representations for artists when modeling and simulating mass-interaction physical networks in the context of sound synthesis and musical composition. GENESIS is a musician-oriented software environment for sound synthesis and musical composition. However, despite this orientation, a substantial amount of effort has been put into building a rich variety of tools based on static or dynamic visual representations of models an...
Cheng, Hong
2015-01-01
This unique text/reference presents a comprehensive review of the state of the art in sparse representations, modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation, highlighting the practical application of compressed sensing research in visual recognition and computer vision. Topics and features: provides a thorough introduction to the fundamentals of sparse representation, modeling and learning, and the application of these techniques in visual recognition; describes sparse recovery approaches, robust and efficient sparse represen
Energy Technology Data Exchange (ETDEWEB)
Bryan, Frank [Univ. of Washington, Seattle, WA (United States); Dennis, John [Univ. of Washington, Seattle, WA (United States); MacCready, Parker [Univ. of Washington, Seattle, WA (United States); Whitney, Michael [Univ. of Washington, Seattle, WA (United States)
2016-10-20
This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation.
DEFF Research Database (Denmark)
Ommen, Torben Schmidt; Markussen, Wiebke Brix; Elmegaard, Brian
2014-01-01
In the paper, three frequently used operation optimisation methods are examined with respect to their impact on operation management of the combined utility technologies for electric power and DH (district heating) of eastern Denmark. The investigation focusses on individual plant operation...... 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...... as a benchmark, as this type is frequently used, and has the lowest amount of constraints of the three. A comparison of the optimised operation of a number of units shows significant differences between the three methods. Compared to the reference, the use of binary integer variables, increases operation...
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…
Functional linear models for association analysis of quantitative traits.
Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao
2013-11-01
Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. © 2013 WILEY
Modeling urban landscape: New paradigms and challenges in territorial representation
Directory of Open Access Journals (Sweden)
Sheyla Aguilar de Santana
2013-05-01
Full Text Available This paper aims to give a brief background on the production of urban space considering the social functions of the city, the needs of contemporary urban reforms and the need for tools that assist in decision making. This state of the art about the production space justifies the current studies on the development of geoprocessing tools, techniques and methodologies that attempt the needs of creating interpretive portraits of urban landscapes to facilitate dialogue between urban technical, administrators and community. In this sense, it is presented how GIS has been working within the context of urban planning and appointed the new challenges and paradigms of territorial representation.
Practical likelihood analysis for spatial generalized linear mixed models
DEFF Research Database (Denmark)
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......, respectively, examples of binomial and count datasets modeled by spatial generalized linear mixed models. Our results show that the Laplace approximation provides similar estimates to Markov Chain Monte Carlo likelihood, Monte Carlo expectation maximization, and modified Laplace approximation. Some advantages...... 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...
A roadmap for improving the representation of photosynthesis in Earth system models.
Rogers, Alistair; Medlyn, Belinda E; Dukes, Jeffrey S; Bonan, Gordon; von Caemmerer, Susanne; Dietze, Michael C; Kattge, Jens; Leakey, Andrew D B; Mercado, Lina M; Niinemets, Ülo; Prentice, I Colin; Serbin, Shawn P; Sitch, Stephen; Way, Danielle A; Zaehle, Sönke
2017-01-01
Accurate representation of photosynthesis in terrestrial biosphere models (TBMs) is essential for robust projections of global change. However, current representations vary markedly between TBMs, contributing uncertainty to projections of global carbon fluxes. Here we compared the representation of photosynthesis in seven TBMs by examining leaf and canopy level responses of photosynthetic CO 2 assimilation (A) to key environmental variables: light, temperature, CO 2 concentration, vapor pressure deficit and soil water content. We identified research areas where limited process knowledge prevents inclusion of physiological phenomena in current TBMs and research areas where data are urgently needed for model parameterization or evaluation. We provide a roadmap for new science needed to improve the representation of photosynthesis in the next generation of terrestrial biosphere and Earth system models. No claim to original US Government works New Phytologist © 2016 New Phytologist Trust.
Stochastic modeling of mode interactions via linear parabolized stability equations
Ran, Wei; Zare, Armin; Hack, M. J. Philipp; Jovanovic, Mihailo
2017-11-01
Low-complexity approximations of the Navier-Stokes equations have been widely used in the analysis of wall-bounded shear flows. In particular, the parabolized stability equations (PSE) and Floquet theory have been employed to capture the evolution of primary and secondary instabilities in spatially-evolving flows. We augment linear PSE with Floquet analysis to formally treat modal interactions and the evolution of secondary instabilities in the transitional boundary layer via a linear progression. To this end, we leverage Floquet theory by incorporating the primary instability into the base flow and accounting for different harmonics in the flow state. A stochastic forcing is introduced into the resulting linear dynamics to model the effect of nonlinear interactions on the evolution of modes. We examine the H-type transition scenario to demonstrate how our approach can be used to model nonlinear effects and capture the growth of the fundamental and subharmonic modes observed in direct numerical simulations and experiments.
International Nuclear Information System (INIS)
Ketov, S.V.
1996-01-01
The simplest free-field realizations of the exceptional non-linear (quadratically generated, or W-type) N=8 and N=7 superconformal algebras with Spin(7) and G 2 affine currents, respectively, are investigated. Both the N=8 and N=7 algebras are found to admit unitary and highest-weight irreducible representations in terms of a single free boson and free fermions in 8 of Spin(7) or 7 of G 2 , respectively, at level k=1 and the corresponding central charges c 8 =26/5 and c 7 =5. (orig.)
A knowledge representation meta-model for rule-based modelling of signalling networks
Directory of Open Access Journals (Sweden)
Adrien Basso-Blandin
2016-03-01
Full Text Available The study of cellular signalling pathways and their deregulation in disease states, such as cancer, is a large and extremely complex task. Indeed, these systems involve many parts and processes but are studied piecewise and their literatures and data are consequently fragmented, distributed and sometimes—at least apparently—inconsistent. This makes it extremely difficult to build significant explanatory models with the result that effects in these systems that are brought about by many interacting factors are poorly understood. The rule-based approach to modelling has shown some promise for the representation of the highly combinatorial systems typically found in signalling where many of the proteins are composed of multiple binding domains, capable of simultaneous interactions, and/or peptide motifs controlled by post-translational modifications. However, the rule-based approach requires highly detailed information about the precise conditions for each and every interaction which is rarely available from any one single source. Rather, these conditions must be painstakingly inferred and curated, by hand, from information contained in many papers—each of which contains only part of the story. In this paper, we introduce a graph-based meta-model, attuned to the representation of cellular signalling networks, which aims to ease this massive cognitive burden on the rule-based curation process. This meta-model is a generalization of that used by Kappa and BNGL which allows for the flexible representation of knowledge at various levels of granularity. In particular, it allows us to deal with information which has either too little, or too much, detail with respect to the strict rule-based meta-model. Our approach provides a basis for the gradual aggregation of fragmented biological knowledge extracted from the literature into an instance of the meta-model from which we can define an automated translation into executable Kappa programs.
Linear modeling of possible mechanisms for parkinson tremor generation
Lohnberg, P.
1978-01-01
The power of Parkinson tremor is expressed in terms of possibly changed frequency response functions between relevant variables in the neuromuscular system. The derivation starts out from a linear loopless equivalent model of mechanisms for general tremor generation. Hypothetical changes in this
Current algebra of classical non-linear sigma models
International Nuclear Information System (INIS)
Forger, M.; Laartz, J.; Schaeper, U.
1992-01-01
The current algebra of classical non-linear sigma models on arbitrary Riemannian manifolds is analyzed. It is found that introducing, in addition to the Noether current j μ associated with the global symmetry of the theory, a composite scalar field j, the algebra closes under Poisson brackets. (orig.)
Mathematical modelling and linear stability analysis of laser fusion cutting
International Nuclear Information System (INIS)
Hermanns, Torsten; Schulz, Wolfgang; Vossen, Georg; Thombansen, Ulrich
2016-01-01
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.
Non Linear signa models probing the string structure
International Nuclear Information System (INIS)
Abdalla, E.
1987-01-01
The introduction of a term depending on the extrinsic curvature to the string action, and related non linear sigma models defined on a symmetric space SO(D)/SO(2) x SO(d-2) is descussed . Coupling to fermions are also treated. (author) [pt
Confidence Intervals for Assessing Heterogeneity in Generalized Linear Mixed Models
Wagler, Amy E.
2014-01-01
Generalized linear mixed models are frequently applied to data with clustered categorical outcomes. The effect of clustering on the response is often difficult to practically assess partly because it is reported on a scale on which comparisons with regression parameters are difficult to make. This article proposes confidence intervals for…
Penalized Estimation in Large-Scale Generalized Linear Array Models
DEFF Research Database (Denmark)
Lund, Adam; Vincent, Martin; Hansen, Niels Richard
2017-01-01
Large-scale generalized linear array models (GLAMs) can be challenging to fit. Computation and storage of its tensor product design matrix can be impossible due to time and memory constraints, and previously considered design matrix free algorithms do not scale well with the dimension...
Expressions for linearized perturbations in ideal-fluid cosmological models
International Nuclear Information System (INIS)
Ratra, B.
1988-01-01
We present closed-form solutions of the relativistic linear perturbation equations (in synchronous gauge) that govern the evolution of inhomogeneities in homogeneous, spatially flat, ideal-fluid, cosmological models. These expressions, which are valid for irregularities on any scale, allow one to analytically interpolate between the known approximate solutions which are valid at early times and at late times
S-AMP for non-linear observation models
DEFF Research Database (Denmark)
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...
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 simulation model of a coordinated decentralized linear supply chain
Ashayeri, Jalal; Cannella, S.; Lopez Campos, M.; Miranda, P.A.
2015-01-01
This paper presents a simulation-based study of a coordinated, decentralized linear supply chain (SC) system. In the proposed model, any supply tier considers its successors as part of its inventory system and generates replenishment orders on the basis of its partners’ operational information. We
Mathematical modelling and linear stability analysis of laser fusion cutting
Energy Technology Data Exchange (ETDEWEB)
Hermanns, Torsten; Schulz, Wolfgang [RWTH Aachen University, Chair for Nonlinear Dynamics, Steinbachstr. 15, 52047 Aachen (Germany); Vossen, Georg [Niederrhein University of Applied Sciences, Chair for Applied Mathematics and Numerical Simulations, Reinarzstr.. 49, 47805 Krefeld (Germany); Thombansen, Ulrich [RWTH Aachen University, Chair for Laser Technology, Steinbachstr. 15, 52047 Aachen (Germany)
2016-06-08
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.
Performances Of Estimators Of Linear Models With Autocorrelated ...
African Journals Online (AJOL)
The performances of five estimators of linear models with Autocorrelated error terms are compared when the independent variable is autoregressive. The results reveal that the properties of the estimators when the sample size is finite is quite similar to the properties of the estimators when the sample size is infinite although ...
Performances of estimators of linear auto-correlated error model ...
African Journals Online (AJOL)
The performances of five estimators of linear models with autocorrelated disturbance terms are compared when the independent variable is exponential. The results reveal that for both small and large samples, the Ordinary Least Squares (OLS) compares favourably with the Generalized least Squares (GLS) estimators in ...
A non-linear dissipative model of magnetism
Czech Academy of Sciences Publication Activity Database
Durand, P.; Paidarová, Ivana
2010-01-01
Roč. 89, č. 6 (2010), s. 67004 ISSN 1286-4854 R&D Projects: GA AV ČR IAA100400501 Institutional research plan: CEZ:AV0Z40400503 Keywords : non-linear dissipative model of magnetism * thermodynamics * physical chemistry Subject RIV: CF - Physical ; Theoretical Chemistry http://epljournal.edpsciences.org/
Modeling and verifying non-linearities in heterodyne displacement interferometry
Cosijns, S.J.A.G.; Haitjema, H.; Schellekens, P.H.J.
2002-01-01
The non-linearities in a heterodyne laser interferometer system occurring from the phase measurement system of the interferometer andfrom non-ideal polarization effects of the optics are modeled into one analytical expression which includes the initial polarization state ofthe laser source, the
DEFF Research Database (Denmark)
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....
Identifiability Results for Several Classes of Linear Compartment Models.
Meshkat, Nicolette; Sullivant, Seth; Eisenberg, Marisa
2015-08-01
Identifiability concerns finding which unknown parameters of a model can be estimated, uniquely or otherwise, from given input-output data. If some subset of the parameters of a model cannot be determined given input-output data, then we say the model is unidentifiable. In this work, we study linear compartment models, which are a class of biological models commonly used in pharmacokinetics, physiology, and ecology. In past work, we used commutative algebra and graph theory to identify a class of linear compartment models that we call identifiable cycle models, which are unidentifiable but have the simplest possible identifiable functions (so-called monomial cycles). Here we show how to modify identifiable cycle models by adding inputs, adding outputs, or removing leaks, in such a way that we obtain an identifiable model. We also prove a constructive result on how to combine identifiable models, each corresponding to strongly connected graphs, into a larger identifiable model. We apply these theoretical results to several real-world biological models from physiology, cell biology, and ecology.
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.
Non-linear time variant model intended for polypyrrole-based actuators
Farajollahi, Meisam; Madden, John D. W.; Sassani, Farrokh
2014-03-01
Polypyrrole-based actuators are of interest due to their biocompatibility, low operation voltage and relatively high strain and force. Modeling and simulation are very important to predict the behaviour of each actuator. To develop an accurate model, we need to know the electro-chemo-mechanical specifications of the Polypyrrole. In this paper, the non-linear time-variant model of Polypyrrole film is derived and proposed using a combination of an RC transmission line model and a state space representation. The model incorporates the potential dependent ionic conductivity. A function of ionic conductivity of Polypyrrole vs. local charge is proposed and implemented in the non-linear model. Matching of the measured and simulated electrical response suggests that ionic conductivity of Polypyrrole decreases significantly at negative potential vs. silver/silver chloride and leads to reduced current in the cyclic voltammetry (CV) tests. The next stage is to relate the distributed charging of the polymer to actuation via the strain to charge ratio. Further work is also needed to identify ionic and electronic conductivities as well as capacitance as a function of oxidation state so that a fully predictive model can be created.
Campoamor-Stursberg, R.
2018-03-01
A procedure for the construction of nonlinear realizations of Lie algebras in the context of Vessiot-Guldberg-Lie algebras of first-order systems of ordinary differential equations (ODEs) is proposed. The method is based on the reduction of invariants and projection of lowest-dimensional (irreducible) representations of Lie algebras. Applications to the description of parameterized first-order systems of ODEs related by contraction of Lie algebras are given. In particular, the kinematical Lie algebras in (2 + 1)- and (3 + 1)-dimensions are realized simultaneously as Vessiot-Guldberg-Lie algebras of parameterized nonlinear systems in R3 and R4, respectively.
Linear Dynamics Model for Steam Cooled Fast Power Reactors
Energy Technology Data Exchange (ETDEWEB)
Vollmer, H
1968-04-15
A linear analytical dynamic model is developed for steam cooled fast power reactors. All main components of such a plant are investigated on a general though relatively simple basis. The model is distributed in those parts concerning the core but lumped as to the external plant components. Coolant is considered as compressible and treated by the actual steam law. Combined use of analogue and digital computer seems most attractive.
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
One-loop dimensional reduction of the linear σ model
International Nuclear Information System (INIS)
Malbouisson, A.P.C.; Silva-Neto, M.B.; Svaiter, N.F.
1997-05-01
We perform the dimensional reduction of the linear σ model at one-loop level. The effective of the reduced theory obtained from the integration over the nonzero Matsubara frequencies is exhibited. Thermal mass and coupling constant renormalization constants are given, as well as the thermal renormalization group which controls the dependence of the counterterms on the temperature. We also recover, for the reduced theory, the vacuum instability of the model for large N. (author)
Artificial Neural Network versus Linear Models Forecasting Doha Stock Market
Yousif, Adil; Elfaki, Faiz
2017-12-01
The purpose of this study is to determine the instability of Doha stock market and develop forecasting models. Linear time series models are used and compared with a nonlinear Artificial Neural Network (ANN) namely Multilayer Perceptron (MLP) Technique. It aims to establish the best useful model based on daily and monthly data which are collected from Qatar exchange for the period starting from January 2007 to January 2015. Proposed models are for the general index of Qatar stock exchange and also for the usages in other several sectors. With the help of these models, Doha stock market index and other various sectors were predicted. The study was conducted by using various time series techniques to study and analyze data trend in producing appropriate results. After applying several models, such as: Quadratic trend model, double exponential smoothing model, and ARIMA, it was concluded that ARIMA (2,2) was the most suitable linear model for the daily general index. However, ANN model was found to be more accurate than time series models.
A linearized dispersion relation for orthorhombic pseudo-acoustic modeling
Song, Xiaolei; Alkhalifah, Tariq Ali
2012-01-01
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.
Veloz, Tomas; Desjardins, Sylvie
2015-01-01
Quantum models of concept combinations have been successful in representing various experimental situations that cannot be accommodated by traditional models based on classical probability or fuzzy set theory. In many cases, the focus has been on producing a representation that fits experimental results to validate quantum models. However, these representations are not always consistent with the cognitive modeling principles. Moreover, some important issues related to the representation of concepts such as the dimensionality of the realization space, the uniqueness of solutions, and the compatibility of measurements, have been overlooked. In this paper, we provide a dimensional analysis of the realization space for the two-sector Fock space model for conjunction of concepts focusing on the first and second sectors separately. We then introduce various representation of concepts that arise from the use of unitary operators in the realization space. In these concrete representations, a pair of concepts and their combination are modeled by a single conceptual state, and by a collection of exemplar-dependent operators. Therefore, they are consistent with cognitive modeling principles. This framework not only provides a uniform approach to model an entire data set, but, because all measurement operators are expressed in the same basis, allows us to address the question of compatibility of measurements. In particular, we present evidence that it may be possible to predict non-commutative effects from partial measurements of conceptual combinations.
Directory of Open Access Journals (Sweden)
Tae-Hyoung Kim
2017-01-01
Full Text Available This paper studies the metaheuristic optimizer-based direct identification of a multiple-mode system consisting of a finite set of linear regression representations of subsystems. To this end, the concept of a multiple-mode linear regression model is first introduced, and its identification issues are established. A method for reducing the identification problem for multiple-mode models to an optimization problem is also described in detail. Then, to overcome the difficulties that arise because the formulated optimization problem is inherently ill-conditioned and nonconvex, the cyclic-network-topology-based constrained particle swarm optimizer (CNT-CPSO is introduced, and a concrete procedure for the CNT-CPSO-based identification methodology is developed. This scheme requires no prior knowledge of the mode transitions between subsystems and, unlike some conventional methods, can handle a large amount of data without difficulty during the identification process. This is one of the distinguishing features of the proposed method. The paper also considers an extension of the CNT-CPSO-based identification scheme that makes it possible to simultaneously obtain both the optimal parameters of the multiple submodels and a certain decision parameter involved in the mode transition criteria. Finally, an experimental setup using a DC motor system is established to demonstrate the practical usability of the proposed metaheuristic optimizer-based identification scheme for developing a multiple-mode linear regression model.
Non-linear sigma model on the fuzzy supersphere
International Nuclear Information System (INIS)
Kurkcuoglu, Seckin
2004-01-01
In this note we develop fuzzy versions of the supersymmetric non-linear sigma model on the supersphere S (2,2) . In hep-th/0212133 Bott projectors have been used to obtain the fuzzy C P 1 model. Our approach utilizes the use of supersymmetric extensions of these projectors. Here we obtain these (super)-projectors and quantize them in a fashion similar to the one given in hep-th/0212133. We discuss the interpretation of the resulting model as a finite dimensional matrix model. (author)
Optimal difference-based estimation for partially linear models
Zhou, Yuejin; Cheng, Yebin; Dai, Wenlin; Tong, Tiejun
2017-01-01
Difference-based methods have attracted increasing attention for analyzing partially linear models in the recent literature. In this paper, we first propose to solve the optimal sequence selection problem in difference-based estimation for the linear component. To achieve the goal, a family of new sequences and a cross-validation method for selecting the adaptive sequence are proposed. We demonstrate that the existing sequences are only extreme cases in the proposed family. Secondly, we propose a new estimator for the residual variance by fitting a linear regression method to some difference-based estimators. Our proposed estimator achieves the asymptotic optimal rate of mean squared error. Simulation studies also demonstrate that our proposed estimator performs better than the existing estimator, especially when the sample size is small and the nonparametric function is rough.
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...
Optimal difference-based estimation for partially linear models
Zhou, Yuejin
2017-12-16
Difference-based methods have attracted increasing attention for analyzing partially linear models in the recent literature. In this paper, we first propose to solve the optimal sequence selection problem in difference-based estimation for the linear component. To achieve the goal, a family of new sequences and a cross-validation method for selecting the adaptive sequence are proposed. We demonstrate that the existing sequences are only extreme cases in the proposed family. Secondly, we propose a new estimator for the residual variance by fitting a linear regression method to some difference-based estimators. Our proposed estimator achieves the asymptotic optimal rate of mean squared error. Simulation studies also demonstrate that our proposed estimator performs better than the existing estimator, especially when the sample size is small and the nonparametric function is rough.
International Nuclear Information System (INIS)
Mazumdar, Tanay; Degweker, S.B.
2017-01-01
Highlights: • In Method of Characteristics, the neutron source within a mesh is expanded up to linear term. • This expansion reduces the number of meshes as compared to flat source assumption. • Poor representation of circular geometry with coarser meshes is corrected. • Few benchmark problems are solved to show the advantages of linear expansion of source. • The advantage of the present formalism is quite visible in problems with large flux gradient. - Abstract: A common assumption in the solution of the neutron transport equation by the Method of Characteristics (MOC) is that the source (or flux) is constant within a mesh. This assumption is adequate provided the meshes are small enough so that the spatial variation of flux within a mesh may be ignored. Whether a mesh is small enough or not depends upon the flux gradient across a mesh, which in turn depends on factors like the presence of strong absorbers, localized sources or vacuum boundaries. The flat flux assumption often requires a very large number of meshes for solving the neutron transport equation with acceptable accuracy as was observed in our earlier work on the subject. A significant reduction in the required number of meshes is attainable by using a higher order representation of the flux within a mesh. In this paper, we expand the source within a mesh up to first order (linear) terms, which permits the use of larger sized (and therefore fewer) meshes and thereby reduces the computation time without compromising the accuracy of calculation. Since the division of the geometry into meshes is through an automatic triangulation procedure using the Bowyer-Watson algorithm, representation of circular objects (cylindrical fuel rods) with coarse meshes is poorer and causes geometry related errors. A numerical recipe is presented to make a correction to the automatic triangulation process and thereby eliminate this source of error. A number of benchmark problems are analyzed to emphasize the
A penalized framework for distributed lag non-linear models.
Gasparrini, Antonio; Scheipl, Fabian; Armstrong, Ben; Kenward, Michael G
2017-09-01
Distributed lag non-linear models (DLNMs) are a modelling tool for describing potentially non-linear and delayed dependencies. Here, we illustrate an extension of the DLNM framework through the use of penalized splines within generalized additive models (GAM). This extension offers built-in model selection procedures and the possibility of accommodating assumptions on the shape of the lag structure through specific penalties. In addition, this framework includes, as special cases, simpler models previously proposed for linear relationships (DLMs). Alternative versions of penalized DLNMs are compared with each other and with the standard unpenalized version in a simulation study. Results show that this penalized extension to the DLNM class provides greater flexibility and improved inferential properties. The framework exploits recent theoretical developments of GAMs and is implemented using efficient routines within freely available software. Real-data applications are illustrated through two reproducible examples in time series and survival analysis. © 2017 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.
General mirror pairs for gauged linear sigma models
Energy Technology Data Exchange (ETDEWEB)
Aspinwall, Paul S.; Plesser, M. Ronen [Departments of Mathematics and Physics, Duke University,Box 90320, Durham, NC 27708-0320 (United States)
2015-11-05
We carefully analyze the conditions for an abelian gauged linear σ-model to exhibit nontrivial IR behavior described by a nonsingular superconformal field theory determining a superstring vacuum. This is done without reference to a geometric phase, by associating singular behavior to a noncompact space of (semi-)classical vacua. We find that models determined by reflexive combinatorial data are nonsingular for generic values of their parameters. This condition has the pleasant feature that the mirror of a nonsingular gauged linear σ-model is another such model, but it is clearly too strong and we provide an example of a non-reflexive mirror pair. We discuss a weaker condition inspired by considering extremal transitions, which is also mirror symmetric and which we conjecture to be sufficient. We apply these ideas to extremal transitions and to understanding the way in which both Berglund-Hübsch mirror symmetry and the Vafa-Witten mirror orbifold with discrete torsion can be seen as special cases of the general combinatorial duality of gauged linear σ-models. In the former case we encounter an example showing that our weaker condition is still not necessary.
General mirror pairs for gauged linear sigma models
International Nuclear Information System (INIS)
Aspinwall, Paul S.; Plesser, M. Ronen
2015-01-01
We carefully analyze the conditions for an abelian gauged linear σ-model to exhibit nontrivial IR behavior described by a nonsingular superconformal field theory determining a superstring vacuum. This is done without reference to a geometric phase, by associating singular behavior to a noncompact space of (semi-)classical vacua. We find that models determined by reflexive combinatorial data are nonsingular for generic values of their parameters. This condition has the pleasant feature that the mirror of a nonsingular gauged linear σ-model is another such model, but it is clearly too strong and we provide an example of a non-reflexive mirror pair. We discuss a weaker condition inspired by considering extremal transitions, which is also mirror symmetric and which we conjecture to be sufficient. We apply these ideas to extremal transitions and to understanding the way in which both Berglund-Hübsch mirror symmetry and the Vafa-Witten mirror orbifold with discrete torsion can be seen as special cases of the general combinatorial duality of gauged linear σ-models. In the former case we encounter an example showing that our weaker condition is still not necessary.
Robust Linear Models for Cis-eQTL Analysis.
Rantalainen, Mattias; Lindgren, Cecilia M; Holmes, Christopher C
2015-01-01
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.
Energy Technology Data Exchange (ETDEWEB)
Belgiorno, Francesco [Politecnico di Milano, Dipartimento di Matematica, Milano (Italy); INdAM-GNFM, Milano (Italy); Cacciatori, Sergio L. [Universita dell' Insubria, Department of Science and High Technology, Como (Italy); INFN sezione di Milano, Milano (Italy); Dalla Piazza, Francesco [Universita ' ' La Sapienza' ' , Dipartimento di Matematica, Roma (Italy); Doronzo, Michele [Universita dell' Insubria, Department of Science and High Technology, Como (Italy)
2016-06-15
We investigate the quantisation in the Heisenberg representation of a model which represents a simplification of the Hopfield model for dielectric media, where the electromagnetic field is replaced by a scalar field φ and the role of the polarisation field is played by a further scalar field ψ. The model, which is quadratic in the fields, is still characterised by a non-trivial physical content, as the physical particles correspond to the polaritons of the standard Hopfield model of condensed matter physics. Causality is also taken into account and a discussion of the standard interaction representation is also considered. (orig.)
Eigenstates of complex linear combinations of J1, J2, J3 for any representation of SU(2)
International Nuclear Information System (INIS)
Bacry, H.; Technion-Israel Inst. of Tech., Haifa. Dept. of Physics)
1977-05-01
The states which minimalize the uncertainty relation ΔJ 1 ΔJ 2 >=1/2/ 3 >/ are eigenstates of complex linear combinations of J 1 and J 2 . This kind of states is shown to have a very simple geometrical interpretation in the constellation formalism. A detailed description is given in the present pap
Linear models for joint association and linkage QTL mapping
Directory of Open Access Journals (Sweden)
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.
Scoring predictive models using a reduced representation of proteins: model and energy definition.
Fogolari, Federico; Pieri, Lidia; Dovier, Agostino; Bortolussi, Luca; Giugliarelli, Gilberto; Corazza, Alessandra; Esposito, Gennaro; Viglino, Paolo
2007-03-23
Reduced representations of proteins have been playing a keyrole in the study of protein folding. Many such models are available, with different representation detail. Although the usefulness of many such models for structural bioinformatics applications has been demonstrated in recent years, there are few intermediate resolution models endowed with an energy model capable, for instance, of detecting native or native-like structures among decoy sets. The aim of the present work is to provide a discrete empirical potential for a reduced protein model termed here PC2CA, because it employs a PseudoCovalent structure with only 2 Centers of interactions per Amino acid, suitable for protein model quality assessment. All protein structures in the set top500H have been converted in reduced form. The distribution of pseudobonds, pseudoangle, pseudodihedrals and distances between centers of interactions have been converted into potentials of mean force. A suitable reference distribution has been defined for non-bonded interactions which takes into account excluded volume effects and protein finite size. The correlation between adjacent main chain pseudodihedrals has been converted in an additional energetic term which is able to account for cooperative effects in secondary structure elements. Local energy surface exploration is performed in order to increase the robustness of the energy function. The model and the energy definition proposed have been tested on all the multiple decoys' sets in the Decoys'R'us database. The energetic model is able to recognize, for almost all sets, native-like structures (RMSD less than 2.0 A). These results and those obtained in the blind CASP7 quality assessment experiment suggest that the model compares well with scoring potentials with finer granularity and could be useful for fast exploration of conformational space. Parameters are available at the url: http://www.dstb.uniud.it/~ffogolari/download/.
A Graphical User Interface to Generalized Linear Models in MATLAB
Directory of Open Access Journals (Sweden)
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.
MAGDM linear-programming models with distinct uncertain preference structures.
Xu, Zeshui S; Chen, Jian
2008-10-01
Group decision making with preference information on alternatives is an interesting and important research topic which has been receiving more and more attention in recent years. The purpose of this paper is to investigate multiple-attribute group decision-making (MAGDM) problems with distinct uncertain preference structures. We develop some linear-programming models for dealing with the MAGDM problems, where the information about attribute weights is incomplete, and the decision makers have their preferences on alternatives. The provided preference information can be represented in the following three distinct uncertain preference structures: 1) interval utility values; 2) interval fuzzy preference relations; and 3) interval multiplicative preference relations. We first establish some linear-programming models based on decision matrix and each of the distinct uncertain preference structures and, then, develop some linear-programming models to integrate all three structures of subjective uncertain preference information provided by the decision makers and the objective information depicted in the decision matrix. Furthermore, we propose a simple and straightforward approach in ranking and selecting the given alternatives. It is worth pointing out that the developed models can also be used to deal with the situations where the three distinct uncertain preference structures are reduced to the traditional ones, i.e., utility values, fuzzy preference relations, and multiplicative preference relations. Finally, we use a practical example to illustrate in detail the calculation process of the developed approach.
Casero-Alonso, V; López-Fidalgo, J; Torsney, B
2017-01-01
Binary response models are used in many real applications. For these models the Fisher information matrix (FIM) is proportional to the FIM of a weighted simple linear regression model. The same is also true when the weight function has a finite integral. Thus, optimal designs for one binary model are also optimal for the corresponding weighted linear regression model. The main objective of this paper is to provide a tool for the construction of MV-optimal designs, minimizing the maximum of the variances of the estimates, for a general design space. MV-optimality is a potentially difficult criterion because of its nondifferentiability at equal variance designs. A methodology for obtaining MV-optimal designs where the design space is a compact interval [a, b] will be given for several standard weight functions. The methodology will allow us to build a user-friendly computer tool based on Mathematica to compute MV-optimal designs. Some illustrative examples will show a representation of MV-optimal designs in the Euclidean plane, taking a and b as the axes. The applet will be explained using two relevant models. In the first one the case of a weighted linear regression model is considered, where the weight function is directly chosen from a typical family. In the second example a binary response model is assumed, where the probability of the outcome is given by a typical probability distribution. Practitioners can use the provided applet to identify the solution and to know the exact support points and design weights. Copyright Â© 2016 Elsevier Ireland Ltd. All rights reserved.
A parametric FE modeling of brake for non-linear analysis
Energy Technology Data Exchange (ETDEWEB)
Ahmed,Ibrahim; Fatouh, Yasser [Automotive and Tractors Technology Department, Faculty of Industrial Education, Helwan University, Cairo (Egypt); Aly, Wael [Refrigeration and Air-Conditioning Technology Department, Faculty of Industrial Education, Helwan University, Cairo (Egypt)
2013-07-01
A parametric modeling of a drum brake based on 3-D Finite Element Methods (FEM) for non-contact analysis is presented. Many parameters are examined during this study such as the effect of drum-lining interface stiffness, coefficient of friction, and line pressure on the interface contact. Firstly, the modal analysis of the drum brake is also studied to get the natural frequency and instability of the drum to facilitate transforming the modal elements to non-contact elements. It is shown that the Unsymmetric solver of the modal analysis is efficient enough to solve this linear problem after transforming the non-linear behavior of the contact between the drum and the lining to a linear behavior. A SOLID45 which is a linear element is used in the modal analysis and then transferred to non-linear elements which are Targe170 and Conta173 that represent the drum and lining for contact analysis study. The contact analysis problems are highly non-linear and require significant computer resources to solve it, however, the contact problem give two significant difficulties. Firstly, the region of contact is not known based on the boundary conditions such as line pressure, and drum and friction material specs. Secondly, these contact problems need to take the friction into consideration. Finally, it showed a good distribution of the nodal reaction forces on the slotted lining contact surface and existing of the slot in the middle of the lining can help in wear removal due to the friction between the lining and the drum. Accurate contact stiffness can give a good representation for the pressure distribution between the lining and the drum. However, a full contact of the front part of the slotted lining could occur in case of 20, 40, 60 and 80 bar of piston pressure and a partially contact between the drum and lining can occur in the rear part of the slotted lining.
DEFF Research Database (Denmark)
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...
Modelling of Asphalt Concrete Stiffness in the Linear Viscoelastic Region
Mazurek, Grzegorz; Iwański, Marek
2017-10-01
Stiffness modulus is a fundamental parameter used in the modelling of the viscoelastic behaviour of bituminous mixtures. On the basis of the master curve in the linear viscoelasticity range, the mechanical properties of asphalt concrete at different loading times and temperatures can be predicted. This paper discusses the construction of master curves under rheological mathematical models i.e. the sigmoidal function model (MEPDG), the fractional model, and Bahia and co-workers’ model in comparison to the results from mechanistic rheological models i.e. the generalized Huet-Sayegh model, the generalized Maxwell model and the Burgers model. For the purposes of this analysis, the reference asphalt concrete mix (denoted as AC16W) intended for the binder coarse layer and for traffic category KR3 (5×105 controlled strain mode. The fixed strain level was set at 25με to guarantee that the stiffness modulus of the asphalt concrete would be tested in a linear viscoelasticity range. The master curve was formed using the time-temperature superposition principle (TTSP). The stiffness modulus of asphalt concrete was determined at temperatures 10°C, 20°C and 40°C and at loading times (frequency) of 0.1, 0.3, 1, 3, 10, 20 Hz. The model parameters were fitted to the rheological models using the original programs based on the nonlinear least squares sum method. All the rheological models under analysis were found to be capable of predicting changes in the stiffness modulus of the reference asphalt concrete to satisfactory accuracy. In the cases of the fractional model and the generalized Maxwell model, their accuracy depends on a number of elements in series. The best fit was registered for Bahia and co-workers model, generalized Maxwell model and fractional model. As for predicting the phase angle parameter, the largest discrepancies between experimental and modelled results were obtained using the fractional model. Except the Burgers model, the model matching quality was
A Gloss Composition and Context Clustering Based Distributed Word Sense Representation Model
Directory of Open Access Journals (Sweden)
Tao Chen
2015-08-01
Full Text Available In recent years, there has been an increasing interest in learning a distributed representation of word sense. Traditional context clustering based models usually require careful tuning of model parameters, and typically perform worse on infrequent word senses. This paper presents a novel approach which addresses these limitations by first initializing the word sense embeddings through learning sentence-level embeddings from WordNet glosses using a convolutional neural networks. The initialized word sense embeddings are used by a context clustering based model to generate the distributed representations of word senses. Our learned representations outperform the publicly available embeddings on half of the metrics in the word similarity task, 6 out of 13 sub tasks in the analogical reasoning task, and gives the best overall accuracy in the word sense effect classification task, which shows the effectiveness of our proposed distributed distribution learning model.
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.
Linear Model for Optimal Distributed Generation Size Predication
Directory of Open Access Journals (Sweden)
Ahmed Al Ameri
2017-01-01
Full Text Available This article presents a linear model predicting optimal size of Distributed Generation (DG that addresses the minimum power loss. This method is based fundamentally on strong coupling between active power and voltage angle as well as between reactive power and voltage magnitudes. This paper proposes simplified method to calculate the total power losses in electrical grid for different distributed generation sizes and locations. The method has been implemented and tested on several IEEE bus test systems. The results show that the proposed method is capable of predicting approximate optimal size of DG when compared with precision calculations. The method that linearizes a complex model showed a good result, which can actually reduce processing time required. The acceptable accuracy with less time and memory required can help the grid operator to assess power system integrated within large-scale distribution generation.
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.
A Non-Gaussian Spatial Generalized Linear Latent Variable Model
Irincheeva, Irina; Cantoni, Eva; Genton, Marc G.
2012-01-01
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.
NON-LINEAR FINITE ELEMENT MODELING OF DEEP DRAWING PROCESS
Directory of Open Access Journals (Sweden)
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.
Dynamic generalized linear models for monitoring endemic diseases
DEFF Research Database (Denmark)
Lopes Antunes, Ana Carolina; Jensen, Dan; Hisham Beshara Halasa, Tariq
2016-01-01
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...... and eradication programmes based on changes in PRRS sero-prevalence was explored. Results showed a declining trend in PRRS sero-prevalence between 2007 and 2014 suggesting that Danish herds are slowly eradicating PRRS. The simulation study demonstrated the flexibility of DGLMs in adapting to changes intrends...... 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...
Estimation and Inference for Very Large Linear Mixed Effects Models
Gao, K.; Owen, A. B.
2016-01-01
Linear mixed models with large imbalanced crossed random effects structures pose severe computational problems for maximum likelihood estimation and for Bayesian analysis. The costs can grow as fast as $N^{3/2}$ when there are N observations. Such problems arise in any setting where the underlying factors satisfy a many to many relationship (instead of a nested one) and in electronic commerce applications, the N can be quite large. Methods that do not account for the correlation structure can...
Using Quartile-Quartile Lines as Linear Models
Gordon, Sheldon P.
2015-01-01
This article introduces the notion of the quartile-quartile line as an alternative to the regression line and the median-median line to produce a linear model based on a set of data. It is based on using the first and third quartiles of a set of (x, y) data. Dynamic spreadsheets are used as exploratory tools to compare the different approaches and…
NON-LINEAR MODELING OF THE RHIC INTERACTION REGIONS
International Nuclear Information System (INIS)
TOMAS, R.; FISCHER, W.; JAIN, A.; LUO, Y.; PILAT, F.
2004-01-01
For RHIC's collision lattices the dominant sources of transverse non-linearities are located in the interaction regions. The field quality is available for most of the magnets in the interaction regions from the magnetic measurements, or from extrapolations of these measurements. We discuss the implementation of these measurements in the MADX models of the Blue and the Yellow rings and their impact on beam stability
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.
Using Structured Knowledge Representation for Context-Sensitive Probabilistic Modeling
National Research Council Canada - National Science Library
Sakhanenko, Nikita A; Luger, George F
2008-01-01
We propose a context-sensitive probabilistic modeling system (COSMOS) that reasons about a complex, dynamic environment through a series of applications of smaller, knowledge-focused models representing contextually relevant information...
A knowledge representation of local pandemic influenza planning models.
Islam, Runa; Brandeau, Margaret L; Das, Amar K
2007-10-11
Planning for pandemic flu outbreak at the small-government level can be aided through the use of mathematical policy models. Formulating and analyzing policy models, however, can be a time- and expertise-expensive process. We believe that a knowledge-based system for facilitating the instantiation of locale- and problem-specific policy models can reduce some of these costs. In this work, we present the ontology we have developed for pandemic influenza policy models.
Comparison of Linear Prediction Models for Audio Signals
Directory of Open Access Journals (Sweden)
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.
Linear theory for filtering nonlinear multiscale systems with model error.
Berry, Tyrus; Harlim, John
2014-07-08
In this paper, we study filtering of multiscale dynamical systems with model error arising from limitations in resolving the smaller scale processes. In particular, the analysis assumes the availability of continuous-time noisy observations of all components of the slow variables. Mathematically, this paper presents new results on higher order asymptotic expansion of the first two moments of a conditional measure. In particular, we are interested in the application of filtering multiscale problems in which the conditional distribution is defined over the slow variables, given noisy observation of the slow variables alone. From the mathematical analysis, we learn that for a continuous time linear model with Gaussian noise, there exists a unique choice of parameters in a linear reduced model for the slow variables which gives the optimal filtering when only the slow variables are observed. Moreover, these parameters simultaneously give the optimal equilibrium statistical estimates of the underlying system, and as a consequence they can be estimated offline from the equilibrium statistics of the true signal. By examining a nonlinear test model, we show that the linear theory extends in this non-Gaussian, nonlinear configuration as long as we know the optimal stochastic parametrization and the correct observation model. However, when the stochastic parametrization model is inappropriate, parameters chosen for good filter performance may give poor equilibrium statistical estimates and vice versa; this finding is based on analytical and numerical results on our nonlinear test model and the two-layer Lorenz-96 model. Finally, even when the correct stochastic ansatz is given, it is imperative to estimate the parameters simultaneously and to account for the nonlinear feedback of the stochastic parameters into the reduced filter estimates. In numerical experiments on the two-layer Lorenz-96 model, we find that the parameters estimated online , as part of a filtering
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 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.
A non-linear dimension reduction methodology for generating data-driven stochastic input models
Ganapathysubramanian, Baskar; Zabaras, Nicholas
2008-06-01
Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem of manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space Rn. An isometric mapping F from M to a low-dimensional, compact, connected set A⊂Rd(d≪n) is constructed. Given only a finite set of samples of the data, the methodology uses arguments from graph theory and differential geometry to construct the isometric transformation F:M→A. Asymptotic convergence of the representation of M by A is shown. This mapping F serves as an accurate, low-dimensional, data-driven representation of the property variations. The reduced-order model of the material topology and thermal diffusivity variations is subsequently used as an input in the solution of stochastic partial differential equations that describe the evolution of dependant variables. A sparse grid collocation strategy (Smolyak algorithm) is utilized to solve these stochastic equations efficiently. We showcase the methodology by constructing low
A non-linear dimension reduction methodology for generating data-driven stochastic input models
International Nuclear Information System (INIS)
Ganapathysubramanian, Baskar; Zabaras, Nicholas
2008-01-01
Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem of manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space R n . An isometric mapping F from M to a low-dimensional, compact, connected set A is contained in R d (d<< n) is constructed. Given only a finite set of samples of the data, the methodology uses arguments from graph theory and differential geometry to construct the isometric transformation F:M→A. Asymptotic convergence of the representation of M by A is shown. This mapping F serves as an accurate, low-dimensional, data-driven representation of the property variations. The reduced-order model of the material topology and thermal diffusivity variations is subsequently used as an input in the solution of stochastic partial differential equations that describe the evolution of dependant variables. A sparse grid collocation strategy (Smolyak algorithm) is utilized to solve these stochastic equations efficiently. We showcase the methodology
Neutron stars in non-linear coupling models
International Nuclear Information System (INIS)
Taurines, Andre R.; Vasconcellos, Cesar A.Z.; Malheiro, Manuel; Chiapparini, Marcelo
2001-01-01
We present a class of relativistic models for nuclear matter and neutron stars which exhibits a parameterization, through mathematical constants, of the non-linear meson-baryon couplings. For appropriate choices of the parameters, it recovers current QHD models found in the literature: Walecka, ZM and ZM3 models. We have found that the ZM3 model predicts a very small maximum neutron star mass, ∼ 0.72M s un. A strong similarity between the results of ZM-like models and those with exponential couplings is noted. Finally, we discuss the very intense scalar condensates found in the interior of neutron stars which may lead to negative effective masses. (author)
Neutron stars in non-linear coupling models
Energy Technology Data Exchange (ETDEWEB)
Taurines, Andre R.; Vasconcellos, Cesar A.Z. [Rio Grande do Sul Univ., Porto Alegre, RS (Brazil); Malheiro, Manuel [Universidade Federal Fluminense, Niteroi, RJ (Brazil); Chiapparini, Marcelo [Universidade do Estado, Rio de Janeiro, RJ (Brazil)
2001-07-01
We present a class of relativistic models for nuclear matter and neutron stars which exhibits a parameterization, through mathematical constants, of the non-linear meson-baryon couplings. For appropriate choices of the parameters, it recovers current QHD models found in the literature: Walecka, ZM and ZM3 models. We have found that the ZM3 model predicts a very small maximum neutron star mass, {approx} 0.72M{sub s}un. A strong similarity between the results of ZM-like models and those with exponential couplings is noted. Finally, we discuss the very intense scalar condensates found in the interior of neutron stars which may lead to negative effective masses. (author)
Modelling of Rotational Capacity in Reinforced Linear Elements
DEFF Research Database (Denmark)
Hestbech, Lars; Hagsten, Lars German; Fisker, Jakob
2011-01-01
on the rotational capacity of the plastic hinges. The documentation of ductility can be a difficult task as modelling of rotational capacity in plastic hinges of frames is not fully developed. On the basis of the Theory of Plasticity a model is developed to determine rotational capacity in plastic hinges in linear......The Capacity Design Method forms the basis of several seismic design codes. This design philosophy allows plastic deformations in order to decrease seismic demands in structures. However, these plastic deformations must be localized in certain zones where ductility requirements can be documented...... reinforced concrete elements. The model is taking several important parameters into account. Empirical values is avoided which is considered an advantage compared to previous models. Furthermore, the model includes force variations in the reinforcement due to moment distributions and shear as well...
Sahin, Rubina; Tapadia, Kavita
2015-01-01
The three widely used isotherms Langmuir, Freundlich and Temkin were examined in an experiment using fluoride (F⁻) ion adsorption on a geo-material (limonite) at four different temperatures by linear and non-linear models. Comparison of linear and non-linear regression models were given in selecting the optimum isotherm for the experimental results. The coefficient of determination, r², was used to select the best theoretical isotherm. The four Langmuir linear equations (1, 2, 3, and 4) are discussed. Langmuir isotherm parameters obtained from the four Langmuir linear equations using the linear model differed but they were the same when using the nonlinear model. Langmuir-2 isotherm is one of the linear forms, and it had the highest coefficient of determination (r² = 0.99) compared to the other Langmuir linear equations (1, 3 and 4) in linear form, whereas, for non-linear, Langmuir-4 fitted best among all the isotherms because it had the highest coefficient of determination (r² = 0.99). The results showed that the non-linear model may be a better way to obtain the parameters. In the present work, the thermodynamic parameters show that the absorption of fluoride onto limonite is both spontaneous (ΔG 0). Scanning electron microscope and X-ray diffraction images also confirm the adsorption of F⁻ ion onto limonite. The isotherm and kinetic study reveals that limonite can be used as an adsorbent for fluoride removal. In future we can develop new technology for fluoride removal in large scale by using limonite which is cost-effective, eco-friendly and is easily available in the study area.
Potts Model with Invisible Colors : Random-Cluster Representation and Pirogov–Sinai Analysis
Enter, Aernout C.D. van; Iacobelli, Giulio; Taati, Siamak
We study a recently introduced variant of the ferromagnetic Potts model consisting of a ferromagnetic interaction among q “visible” colors along with the presence of r non-interacting “invisible” colors. We introduce a random-cluster representation for the model, for which we prove the existence of
Delice, Ali; Kertil, Mahmut
2015-01-01
This article reports the results of a study that investigated pre-service mathematics teachers' modelling processes in terms of representational fluency in a modelling activity related to a cassette player. A qualitative approach was used in the data collection process. Students' individual and group written responses to the mathematical modelling…
Network Traffic Monitoring Using Poisson Dynamic Linear Models
Energy Technology Data Exchange (ETDEWEB)
Merl, D. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2011-05-09
In this article, we discuss an approach for network forensics using a class of nonstationary Poisson processes with embedded dynamic linear models. As a modeling strategy, the Poisson DLM (PoDLM) provides a very flexible framework for specifying structured effects that may influence the evolution of the underlying Poisson rate parameter, including diurnal and weekly usage patterns. We develop a novel particle learning algorithm for online smoothing and prediction for the PoDLM, and demonstrate the suitability of the approach to real-time deployment settings via a new application to computer network traffic monitoring.
On the chiral phase transition in the linear sigma model
International Nuclear Information System (INIS)
Tran Huu Phat; Nguyen Tuan Anh; Le Viet Hoa
2003-01-01
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. (author)
Bayesian Subset Modeling for High-Dimensional Generalized Linear Models
Liang, Faming; Song, Qifan; Yu, Kai
2013-01-01
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
Application of linearized model to the stability analysis of the pressurized water reactor
International Nuclear Information System (INIS)
Li Haipeng; Huang Xiaojin; Zhang Liangju
2008-01-01
A Linear Time-Invariant model of the Pressurized Water Reactor is formulated through the linearization of the nonlinear model. The model simulation results show that the linearized model agrees well with the nonlinear model under small perturbation. Based upon the Lyapunov's First Method, the linearized model is applied to the stability analysis of the Pressurized Water Reactor. The calculation results show that the methodology of linearization to stability analysis is conveniently feasible. (authors)
Role of Statistical Random-Effects Linear Models in Personalized Medicine.
Diaz, Francisco J; Yeh, Hung-Wen; de Leon, Jose
2012-03-01
Some empirical studies and recent developments in pharmacokinetic theory suggest that statistical random-effects linear models are valuable tools that allow describing simultaneously patient populations as a whole and patients as individuals. This remarkable characteristic indicates that these models may be useful in the development of personalized medicine, which aims at finding treatment regimes that are appropriate for particular patients, not just appropriate for the average patient. In fact, published developments show that random-effects linear models may provide a solid theoretical framework for drug dosage individualization in chronic diseases. In particular, individualized dosages computed with these models by means of an empirical Bayesian approach may produce better results than dosages computed with some methods routinely used in therapeutic drug monitoring. This is further supported by published empirical and theoretical findings that show that random effects linear models may provide accurate representations of phase III and IV steady-state pharmacokinetic data, and may be useful for dosage computations. These models have applications in the design of clinical algorithms for drug dosage individualization in chronic diseases; in the computation of dose correction factors; computation of the minimum number of blood samples from a patient that are necessary for calculating an optimal individualized drug dosage in therapeutic drug monitoring; measure of the clinical importance of clinical, demographic, environmental or genetic covariates; study of drug-drug interactions in clinical settings; the implementation of computational tools for web-site-based evidence farming; design of pharmacogenomic studies; and in the development of a pharmacological theory of dosage individualization.
A Linear Viscoelastic Model Calibration of Sylgard 184.
Energy Technology Data Exchange (ETDEWEB)
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.
Predicting Madura cattle growth curve using non-linear model
Widyas, N.; Prastowo, S.; Widi, T. S. M.; Baliarti, E.
2018-03-01
Madura cattle is Indonesian native. It is a composite breed that has undergone hundreds of years of selection and domestication to reach nowadays remarkable uniformity. Crossbreeding has reached the isle of Madura and the Madrasin, a cross between Madura cows and Limousine semen emerged. This paper aimed to compare the growth curve between Madrasin and one type of pure Madura cows, the common Madura cattle (Madura) using non-linear models. Madura cattles are kept traditionally thus reliable records are hardly available. Data were collected from small holder farmers in Madura. Cows from different age classes (5years) were observed, and body measurements (chest girth, body length and wither height) were taken. In total 63 Madura and 120 Madrasin records obtained. Linear model was built with cattle sub-populations and age as explanatory variables. Body weights were estimated based on the chest girth. Growth curves were built using logistic regression. Results showed that within the same age, Madrasin has significantly larger body compared to Madura (plogistic models fit better for Madura and Madrasin cattle data; with the estimated MSE for these models were 39.09 and 759.28 with prediction accuracy of 99 and 92% for Madura and Madrasin, respectively. Prediction of growth curve using logistic regression model performed well in both types of Madura cattle. However, attempts to administer accurate data on Madura cattle are necessary to better characterize and study these cattle.
A non-linear model of information seeking behaviour
Directory of Open Access Journals (Sweden)
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.
Global numerical modeling of magnetized plasma in a linear device
DEFF Research Database (Denmark)
Magnussen, Michael Løiten
Understanding the turbulent transport in the plasma-edge in fusion devices is of utmost importance in order to make precise predictions for future fusion devices. The plasma turbulence observed in linear devices shares many important features with the turbulence observed in the edge of fusion dev...... with simulations performed at different ionization levels, using a simple model for plasma interaction with neutrals. It is found that the steady state and the saturated state of the system bifurcates when the neutral interaction dominates the electron-ion collisions.......Understanding the turbulent transport in the plasma-edge in fusion devices is of utmost importance in order to make precise predictions for future fusion devices. The plasma turbulence observed in linear devices shares many important features with the turbulence observed in the edge of fusion...... devices, and are easier to diagnose due to lower temperatures and a better access to the plasma. In order to gain greater insight into this complex turbulent behavior, numerical simulations of plasma in a linear device are performed in this thesis. Here, a three-dimensional drift-fluid model is derived...
Predicting birth weight with conditionally linear transformation models.
Möst, Lisa; Schmid, Matthias; Faschingbauer, Florian; Hothorn, Torsten
2016-12-01
Low and high birth weight (BW) are important risk factors for neonatal morbidity and mortality. Gynecologists must therefore accurately predict BW before delivery. Most prediction formulas for BW are based on prenatal ultrasound measurements carried out within one week prior to birth. Although successfully used in clinical practice, these formulas focus on point predictions of BW but do not systematically quantify uncertainty of the predictions, i.e. they result in estimates of the conditional mean of BW but do not deliver prediction intervals. To overcome this problem, we introduce conditionally linear transformation models (CLTMs) to predict BW. Instead of focusing only on the conditional mean, CLTMs model the whole conditional distribution function of BW given prenatal ultrasound parameters. Consequently, the CLTM approach delivers both point predictions of BW and fetus-specific prediction intervals. Prediction intervals constitute an easy-to-interpret measure of prediction accuracy and allow identification of fetuses subject to high prediction uncertainty. Using a data set of 8712 deliveries at the Perinatal Centre at the University Clinic Erlangen (Germany), we analyzed variants of CLTMs and compared them to standard linear regression estimation techniques used in the past and to quantile regression approaches. The best-performing CLTM variant was competitive with quantile regression and linear regression approaches in terms of conditional coverage and average length of the prediction intervals. We propose that CLTMs be used because they are able to account for possible heteroscedasticity, kurtosis, and skewness of the distribution of BWs. © The Author(s) 2014.
Influence of input matrix representation on topic modelling performance
CSIR Research Space (South Africa)
De Waal, A
2010-11-01
Full Text Available Topic models explain a collection of documents with a small set of distributions over terms. These distributions over terms define the topics. Topic models ignore the structure of documents and use a bag-of-words approach which relies solely...
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.
Challenges in land model representation of heat transfer in snow and frozen soils
Musselman, K. N.; Clark, M. P.; Nijssen, B.; Arnold, J.
2017-12-01
Accurate model simulations of soil thermal and moisture states are critical for realistic estimates of exchanges of energy, water, and biogeochemical fluxes at the land-atmosphere interface. In cold regions, seasonal snow-cover and organic soils form insulating barriers, modifying the heat and moisture exchange that would otherwise occur between mineral soils and the atmosphere. The thermal properties of these media are highly dynamic functions of mass, water and ice content. Land surface models vary in their representation of snow and soil processes, and thus in the treatment of insulation and heat exchange. For some models, recent development efforts have improved representation of heat transfer in cold regions, such as with multi-layer snow treatment, inclusion of soil freezing and organic soil properties, yet model deficiencies remain prevalent. We evaluate models that participated in the Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) experiment for proficiency in simulating heat transfer between the soil through the snowpack to the atmosphere. Using soil observations from cold region sites and a controlled experiment with Structure for Unifying Multiple Modeling Alternatives (SUMMA), we explore the impact of snow and soil model decisions and parameter values on heat transfer model skill. Specifically, we use SUMMA to mimic the spread of behaviors exhibited by the models that participated in PLUMBER. The experiment allows us to isolate relationships between model skill and process representation. The results are aimed to better understand existing model challenges and identify potential advances for cold region models.
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.
Directory of Open Access Journals (Sweden)
D. V. Rose
2010-09-01
Full Text Available A 3D fully electromagnetic (EM model of the principal pulsed-power components of a high-current linear transformer driver (LTD has been developed. LTD systems are a relatively new modular and compact pulsed-power technology based on high-energy density capacitors and low-inductance switches located within a linear-induction cavity. We model 1-MA, 100-kV, 100-ns rise-time LTD cavities [A. A. Kim et al., Phys. Rev. ST Accel. Beams 12, 050402 (2009PRABFM1098-440210.1103/PhysRevSTAB.12.050402] which can be used to drive z-pinch and material dynamics experiments. The model simulates the generation and propagation of electromagnetic power from individual capacitors and triggered gas switches to a radially symmetric output line. Multiple cavities, combined to provide voltage addition, drive a water-filled coaxial transmission line. A 3D fully EM model of a single 1-MA 100-kV LTD cavity driving a simple resistive load is presented and compared to electrical measurements. A new model of the current loss through the ferromagnetic cores is developed for use both in circuit representations of an LTD cavity and in the 3D EM simulations. Good agreement between the measured core current, a simple circuit model, and the 3D simulation model is obtained. A 3D EM model of an idealized ten-cavity LTD accelerator is also developed. The model results demonstrate efficient voltage addition when driving a matched impedance load, in good agreement with an idealized circuit model.
Galvan, Jose Ramon; Saxena, Abhinav; Goebel, Kai Frank
2012-01-01
This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process, and how it relates to uncertainty representation, management and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for two while considering prognostics in making critical decisions.
Linearized vector radiative transfer model MCC++ for a spherical atmosphere
International Nuclear Information System (INIS)
Postylyakov, O.V.
2004-01-01
Application of radiative transfer models has shown that optical remote sensing requires extra characteristics of radiance field in addition to the radiance intensity itself. Simulation of spectral measurements, analysis of retrieval errors and development of retrieval algorithms are in need of derivatives of radiance with respect to atmospheric constituents under investigation. The presented vector spherical radiative transfer model MCC++ was linearized, which allows the calculation of derivatives of all elements of the Stokes vector with respect to the volume absorption coefficient simultaneously with radiance calculation. The model MCC++ employs Monte Carlo algorithm for radiative transfer simulation and takes into account aerosol and molecular scattering, gas and aerosol absorption, and Lambertian surface albedo. The model treats a spherically symmetrical atmosphere. Relation of the estimated derivatives with other forms of radiance derivatives: the weighting functions used in gas retrieval and the air mass factors used in the DOAS retrieval algorithms, is obtained. Validation of the model against other radiative models is overviewed. The computing time of the intensity for the MCC++ model is about that for radiative models treating sphericity of the atmosphere approximately and is significantly shorter than that for the full spherical models used in the comparisons. The simultaneous calculation of all derivatives (i.e. with respect to absorption in all model atmosphere layers) and the intensity is only 1.2-2 times longer than the calculation of the intensity only
Hamid, Ka; Yusoff, An; Rahman, Mza; Mohamad, M; Hamid, Aia
2012-04-01
This fMRI study is about modelling the effective connectivity between Heschl's gyrus (HG) and the superior temporal gyrus (STG) in human primary auditory cortices. MATERIALS #ENTITYSTARTX00026; Ten healthy male participants were required to listen to white noise stimuli during functional magnetic resonance imaging (fMRI) scans. Statistical parametric mapping (SPM) was used to generate individual and group brain activation maps. For input region determination, two intrinsic connectivity models comprising bilateral HG and STG were constructed using dynamic causal modelling (DCM). The models were estimated and inferred using DCM while Bayesian Model Selection (BMS) for group studies was used for model comparison and selection. Based on the winning model, six linear and six non-linear causal models were derived and were again estimated, inferred, and compared to obtain a model that best represents the effective connectivity between HG and the STG, balancing accuracy and complexity. Group results indicated significant asymmetrical activation (p(uncorr) Model comparison results showed strong evidence of STG as the input centre. The winning model is preferred by 6 out of 10 participants. The results were supported by BMS results for group studies with the expected posterior probability, r = 0.7830 and exceedance probability, ϕ = 0.9823. One-sample t-tests performed on connection values obtained from the winning model indicated that the valid connections for the winning model are the unidirectional parallel connections from STG to bilateral HG (p model comparison between linear and non-linear models using BMS prefers non-linear connection (r = 0.9160, ϕ = 1.000) from which the connectivity between STG and the ipsi- and contralateral HG is gated by the activity in STG itself. We are able to demonstrate that the effective connectivity between HG and STG while listening to white noise for the respective participants can be explained by a non-linear dynamic causal model with
Exactly soluble two-state quantum models with linear couplings
International Nuclear Information System (INIS)
Torosov, B T; Vitanov, N V
2008-01-01
A class of exact analytic solutions of the time-dependent Schroedinger equation is presented for a two-state quantum system coherently driven by a nonresonant external field. The coupling is a linear function of time with a finite duration and the detuning is constant. Four special models are considered in detail, namely the shark, double-shark, tent and zigzag models. The exact solution is derived by rotation of the Landau-Zener propagator at an angle of π/4 and is expressed in terms of Weber's parabolic cylinder function. Approximations for the transition probabilities are derived for all four models by using the asymptotics of the Weber function; these approximations demonstrate various effects of physical interest for each model
A Neuronal Network Model for Pitch Selectivity and Representation
Huang, Chengcheng; Rinzel, John
2016-01-01
Pitch is a perceptual correlate of periodicity. Sounds with distinct spectra can elicit the same pitch. Despite the importance of pitch perception, understanding the cellular mechanism of pitch perception is still a major challenge and a mechanistic model of pitch is lacking. A multi-stage neuronal network model is developed for pitch frequency estimation using biophysically-based, high-resolution coincidence detector neurons. The neuronal units respond only to highly coincident input among c...
Parametric Linear Hybrid Automata for Complex Environmental Systems Modeling
Directory of Open Access Journals (Sweden)
Samar Hayat Khan Tareen
2015-07-01
Full Text Available Environmental systems, whether they be weather patterns or predator-prey relationships, are dependent on a number of different variables, each directly or indirectly affecting the system at large. Since not all of these factors are known, these systems take on non-linear dynamics, making it difficult to accurately predict meaningful behavioral trends far into the future. However, such dynamics do not warrant complete ignorance of different efforts to understand and model close approximations of these systems. Towards this end, we have applied a logical modeling approach to model and analyze the behavioral trends and systematic trajectories that these systems exhibit without delving into their quantification. This approach, formalized by René Thomas for discrete logical modeling of Biological Regulatory Networks (BRNs and further extended in our previous studies as parametric biological linear hybrid automata (Bio-LHA, has been previously employed for the analyses of different molecular regulatory interactions occurring across various cells and microbial species. As relationships between different interacting components of a system can be simplified as positive or negative influences, we can employ the Bio-LHA framework to represent different components of the environmental system as positive or negative feedbacks. In the present study, we highlight the benefits of hybrid (discrete/continuous modeling which lead to refinements among the fore-casted behaviors in order to find out which ones are actually possible. We have taken two case studies: an interaction of three microbial species in a freshwater pond, and a more complex atmospheric system, to show the applications of the Bio-LHA methodology for the timed hybrid modeling of environmental systems. Results show that the approach using the Bio-LHA is a viable method for behavioral modeling of complex environmental systems by finding timing constraints while keeping the complexity of the model
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...
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...
Representation and Incorporation of Close Others' Responses: The RICOR Model of Social Influence.
Smith, Eliot R; Mackie, Diane M
2015-08-03
We propose a new model of social influence, which can occur spontaneously and in the absence of typically assumed motives. We assume that perceivers routinely construct representations of other people's experiences and responses (beliefs, attitudes, emotions, and behaviors), when observing others' responses or simulating the responses of unobserved others. Like representations made accessible by priming, these representations may then influence the process that generates perceivers' own responses, without intention or awareness, especially when there is a strong social connection to the other. We describe evidence for the basic properties and important moderators of this process, which distinguish it from other mechanisms such as informational, normative, or social identity influence. The model offers new perspectives on the role of others' values in producing cultural differences, the persistence and power of stereotypes, the adaptive reasons for being influenced by others' responses, and the impact of others' views about the self. © 2015 by the Society for Personality and Social Psychology, Inc.
Sensitivity experiments to mountain representations in spectral models
Directory of Open Access Journals (Sweden)
U. Schlese
2000-06-01
Full Text Available This paper describes a set of sensitivity experiments to several formulations of orography. Three sets are considered: a "Standard" orography consisting of an envelope orography produced originally for the ECMWF model, a"Navy" orography directly from the US Navy data and a "Scripps" orography based on the data set originally compiled several years ago at Scripps. The last two are mean orographies which do not use the envelope enhancement. A new filtering technique for handling the problem of Gibbs oscillations in spectral models has been used to produce the "Navy" and "Scripps" orographies, resulting in smoother fields than the "Standard" orography. The sensitivity experiments show that orography is still an important factor in controlling the model performance even in this class of models that use a semi-lagrangian formulation for water vapour, that in principle should be less sensitive to Gibbs oscillations than the Eulerian formulation. The largest impact can be seen in the stationary waves (asymmetric part of the geopotential at 500 mb where the differences in total height and spatial pattern generate up to 60 m differences, and in the surface fields where the Gibbs removal procedure is successful in alleviating the appearance of unrealistic oscillations over the ocean. These results indicate that Gibbs oscillations also need to be treated in this class of models. The best overall result is obtained using the "Navy" data set, that achieves a good compromise between amplitude of the stationary waves and smoothness of the surface fields.
Yang, Kangjian; Yang, Ping; Wang, Shuai; Dong, Lizhi; Xu, Bing
2018-05-01
We propose a method to identify tip-tilt disturbance model for Linear Quadratic Gaussian control. This identification method based on Levenberg-Marquardt method conducts with a little prior information and no auxiliary system and it is convenient to identify the tip-tilt disturbance model on-line for real-time control. This identification method makes it easy that Linear Quadratic Gaussian control runs efficiently in different adaptive optics systems for vibration mitigation. The validity of the Linear Quadratic Gaussian control associated with this tip-tilt disturbance model identification method is verified by experimental data, which is conducted in replay mode by simulation.
Ontology and modeling patterns for state-based behavior representation
Castet, Jean-Francois; Rozek, Matthew L.; Ingham, Michel D.; Rouquette, Nicolas F.; Chung, Seung H.; Kerzhner, Aleksandr A.; Donahue, Kenneth M.; Jenkins, J. Steven; Wagner, David A.; Dvorak, Daniel L.;
2015-01-01
This paper provides an approach to capture state-based behavior of elements, that is, the specification of their state evolution in time, and the interactions amongst them. Elements can be components (e.g., sensors, actuators) or environments, and are characterized by state variables that vary with time. The behaviors of these elements, as well as interactions among them are represented through constraints on state variables. This paper discusses the concepts and relationships introduced in this behavior ontology, and the modeling patterns associated with it. Two example cases are provided to illustrate their usage, as well as to demonstrate the flexibility and scalability of the behavior ontology: a simple flashlight electrical model and a more complex spacecraft model involving instruments, power and data behaviors. Finally, an implementation in a SysML profile is provided.
Bayesian uncertainty quantification in linear models for diffusion MRI.
Sjölund, Jens; Eklund, Anders; Özarslan, Evren; Herberthson, Magnus; Bånkestad, Maria; Knutsson, Hans
2018-03-29
Diffusion MRI (dMRI) is a valuable tool in the assessment of tissue microstructure. By fitting a model to the dMRI signal it is possible to derive various quantitative features. Several of the most popular dMRI signal models are expansions in an appropriately chosen basis, where the coefficients are determined using some variation of least-squares. However, such approaches lack any notion of uncertainty, which could be valuable in e.g. group analyses. In this work, we use a probabilistic interpretation of linear least-squares methods to recast popular dMRI models as Bayesian ones. This makes it possible to quantify the uncertainty of any derived quantity. In particular, for quantities that are affine functions of the coefficients, the posterior distribution can be expressed in closed-form. We simulated measurements from single- and double-tensor models where the correct values of several quantities are known, to validate that the theoretically derived quantiles agree with those observed empirically. We included results from residual bootstrap for comparison and found good agreement. The validation employed several different models: Diffusion Tensor Imaging (DTI), Mean Apparent Propagator MRI (MAP-MRI) and Constrained Spherical Deconvolution (CSD). We also used in vivo data to visualize maps of quantitative features and corresponding uncertainties, and to show how our approach can be used in a group analysis to downweight subjects with high uncertainty. In summary, we convert successful linear models for dMRI signal estimation to probabilistic models, capable of accurate uncertainty quantification. Copyright © 2018 Elsevier Inc. All rights reserved.
Modelling non-linear effects of dark energy
Bose, Benjamin; Baldi, Marco; Pourtsidou, Alkistis
2018-04-01
We investigate the capabilities of perturbation theory in capturing non-linear effects of dark energy. We test constant and evolving w models, as well as models involving momentum exchange between dark energy and dark matter. Specifically, we compare perturbative predictions at 1-loop level against N-body results for four non-standard equations of state as well as varying degrees of momentum exchange between dark energy and dark matter. The interaction is modelled phenomenologically using a time dependent drag term in the Euler equation. We make comparisons at the level of the matter power spectrum and the redshift space monopole and quadrupole. The multipoles are modelled using the Taruya, Nishimichi and Saito (TNS) redshift space spectrum. We find perturbation theory does very well in capturing non-linear effects coming from dark sector interaction. We isolate and quantify the 1-loop contribution coming from the interaction and from the non-standard equation of state. We find the interaction parameter ξ amplifies scale dependent signatures in the range of scales considered. Non-standard equations of state also give scale dependent signatures within this same regime. In redshift space the match with N-body is improved at smaller scales by the addition of the TNS free parameter σv. To quantify the importance of modelling the interaction, we create mock data sets for varying values of ξ using perturbation theory. This data is given errors typical of Stage IV surveys. We then perform a likelihood analysis using the first two multipoles on these sets and a ξ=0 modelling, ignoring the interaction. We find the fiducial growth parameter f is generally recovered even for very large values of ξ both at z=0.5 and z=1. The ξ=0 modelling is most biased in its estimation of f for the phantom w=‑1.1 case.
Spatial generalised linear mixed models based on distances.
Melo, Oscar O; Mateu, Jorge; Melo, Carlos E
2016-10-01
Risk models derived from environmental data have been widely shown to be effective in delineating geographical areas of risk because they are intuitively easy to understand. We present a new method based on distances, which allows the modelling of continuous and non-continuous random variables through distance-based spatial generalised linear mixed models. The parameters are estimated using Markov chain Monte Carlo maximum likelihood, which is a feasible and a useful technique. The proposed method depends on a detrending step built from continuous or categorical explanatory variables, or a mixture among them, by using an appropriate Euclidean distance. The method is illustrated through the analysis of the variation in the prevalence of Loa loa among a sample of village residents in Cameroon, where the explanatory variables included elevation, together with maximum normalised-difference vegetation index and the standard deviation of normalised-difference vegetation index calculated from repeated satellite scans over time. © The Author(s) 2013.
Linear mixing model applied to AVHRR LAC data
Holben, Brent N.; Shimabukuro, Yosio E.
1993-01-01
A linear mixing model was applied to coarse spatial resolution data from the NOAA Advanced Very High Resolution Radiometer. The reflective component of the 3.55 - 3.93 microns channel was extracted and used with the two reflective channels 0.58 - 0.68 microns and 0.725 - 1.1 microns to run a Constraine Least Squares model to generate vegetation, soil, and shade fraction images for an area in the Western region of Brazil. The Landsat Thematic Mapper data covering the Emas National park region was used for estimating the spectral response of the mixture components and for evaluating the mixing model results. The fraction images were compared with an unsupervised classification derived from Landsat TM data acquired on the same day. The relationship between the fraction images and normalized difference vegetation index images show the potential of the unmixing techniques when using coarse resolution data for global studies.
Accelerating transient simulation of linear reduced order models.
Energy Technology Data Exchange (ETDEWEB)
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.
Behavioral modeling of the dominant dynamics in input-output transfer of linear(ized) circuits
Beelen, T.G.J.; Maten, ter E.J.W.; Sihaloho, H.J.; Eijndhoven, van S.J.L.
2010-01-01
We present a powerful procedure for determining both the dominant dynamics of the inputoutput transfer and the corresponding most influential circuit parameters of a linear(ized) circuit. The procedure consists of several steps in which a specific (sub)problem is solved and its solution is used in
Non Linear Modelling and Control of Hydraulic Actuators
Directory of Open Access Journals (Sweden)
B. Šulc
2002-01-01
Full Text Available This paper deals with non-linear modelling and control of a differential hydraulic actuator. The nonlinear state space equations are derived from basic physical laws. They are more powerful than the transfer function in the case of linear models, and they allow the application of an object oriented approach in simulation programs. The effects of all friction forces (static, Coulomb and viscous have been modelled, and many phenomena that are usually neglected are taken into account, e.g., the static term of friction, the leakage between the two chambers and external space. Proportional Differential (PD and Fuzzy Logic Controllers (FLC have been applied in order to make a comparison by means of simulation. Simulation is performed using Matlab/Simulink, and some of the results are compared graphically. FLC is tuned in a such way that it produces a constant control signal close to its maximum (or minimum, where possible. In the case of PD control the occurrence of peaks cannot be avoided. These peaks produce a very high velocity that oversteps the allowed values.
Modeling Pan Evaporation for Kuwait by Multiple Linear Regression
Almedeij, Jaber
2012-01-01
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. PMID:23226984
A linear model for flow over complex terrain
Energy Technology Data Exchange (ETDEWEB)
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.
Linear-quadratic model predictions for tumor control probability
International Nuclear Information System (INIS)
Yaes, R.J.
1987-01-01
Sigmoid dose-response curves for tumor control are calculated from the linear-quadratic model parameters α and Β, obtained from human epidermoid carcinoma cell lines, and are much steeper than the clinical dose-response curves for head and neck cancers. One possible explanation is the presence of small radiation-resistant clones arising from mutations in an initially homogeneous tumor. Using the mutation theory of Delbruck and Luria and of Goldie and Coldman, the authors discuss the implications of such radiation-resistant clones for clinical radiation therapy
Inventory model using bayesian dynamic linear model for demand forecasting
Directory of Open Access Journals (Sweden)
Marisol Valencia-Cárdenas
2014-12-01
Full Text Available An important factor of manufacturing process is the inventory management of terminated product. Constantly, industry is looking for better alternatives to establish an adequate plan of production and stored quantities, with optimal cost, getting quantities in a time horizon, which permits to define resources and logistics with anticipation, needed to distribute products on time. Total absence of historical data, required by many statistical models to forecast, demands the search for other kind of accurate techniques. This work presents an alternative that not only permits to forecast, in an adjusted way, but also, to provide optimal quantities to produce and store with an optimal cost, using Bayesian statistics. The proposal is illustrated with real data. Palabras clave: estadística bayesiana, optimización, modelo de inventarios, modelo lineal dinámico bayesiano. Keywords: Bayesian statistics, opti
Spatial Processes in Linear Ordering
von Hecker, Ulrich; Klauer, Karl Christoph; Wolf, Lukas; Fazilat-Pour, Masoud
2016-01-01
Memory performance in linear order reasoning tasks (A > B, B > C, C > D, etc.) shows quicker, and more accurate responses to queries on wider (AD) than narrower (AB) pairs on a hypothetical linear mental model (A -- B -- C -- D). While indicative of an analogue representation, research so far did not provide positive evidence for spatial…
Finite difference modelling of the temperature rise in non-linear medical ultrasound fields.
Divall, S A; Humphrey, V F
2000-03-01
Non-linear propagation of ultrasound can lead to increased heat generation in medical diagnostic imaging due to the preferential absorption of harmonics of the original frequency. A numerical model has been developed and tested that is capable of predicting the temperature rise due to a high amplitude ultrasound field. The acoustic field is modelled using a numerical solution to the Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation, known as the Bergen Code, which is implemented in cylindrical symmetric form. A finite difference representation of the thermal equations is used to calculate the resulting temperature rises. The model allows for the inclusion of a number of layers of tissue with different acoustic and thermal properties and accounts for the effects of non-linear propagation, direct heating by the transducer, thermal diffusion and perfusion in different tissues. The effect of temperature-dependent skin perfusion and variation in background temperature between the skin and deeper layers of the body are included. The model has been tested against analytic solutions for simple configurations and then used to estimate temperature rises in realistic obstetric situations. A pulsed 3 MHz transducer operating with an average acoustic power of 200 mW leads to a maximum steady state temperature rise inside the foetus of 1.25 degrees C compared with a 0.6 degree C rise for the same transmitted power under linear propagation conditions. The largest temperature rise occurs at the skin surface, with the temperature rise at the foetus limited to less than 2 degrees C for the range of conditions considered.
Shape prior modeling using sparse representation and online dictionary learning.
Zhang, Shaoting; Zhan, Yiqiang; Zhou, Yan; Uzunbas, Mustafa; Metaxas, Dimitris N
2012-01-01
The recently proposed sparse shape composition (SSC) opens a new avenue for shape prior modeling. Instead of assuming any parametric model of shape statistics, SSC incorporates shape priors on-the-fly by approximating a shape instance (usually derived from appearance cues) by a sparse combination of shapes in a training repository. Theoretically, one can increase the modeling capability of SSC by including as many training shapes in the repository. However, this strategy confronts two limitations in practice. First, since SSC involves an iterative sparse optimization at run-time, the more shape instances contained in the repository, the less run-time efficiency SSC has. Therefore, a compact and informative shape dictionary is preferred to a large shape repository. Second, in medical imaging applications, training shapes seldom come in one batch. It is very time consuming and sometimes infeasible to reconstruct the shape dictionary every time new training shapes appear. In this paper, we propose an online learning method to address these two limitations. Our method starts from constructing an initial shape dictionary using the K-SVD algorithm. When new training shapes come, instead of re-constructing the dictionary from the ground up, we update the existing one using a block-coordinates descent approach. Using the dynamically updated dictionary, sparse shape composition can be gracefully scaled up to model shape priors from a large number of training shapes without sacrificing run-time efficiency. Our method is validated on lung localization in X-Ray and cardiac segmentation in MRI time series. Compared to the original SSC, it shows comparable performance while being significantly more efficient.
Hattori, Masasi
2016-12-01
This paper presents a new theory of syllogistic reasoning. The proposed model assumes there are probabilistic representations of given signature situations. Instead of conducting an exhaustive search, the model constructs an individual-based "logical" mental representation that expresses the most probable state of affairs, and derives a necessary conclusion that is not inconsistent with the model using heuristics based on informativeness. The model is a unification of previous influential models. Its descriptive validity has been evaluated against existing empirical data and two new experiments, and by qualitative analyses based on previous empirical findings, all of which supported the theory. The model's behavior is also consistent with findings in other areas, including working memory capacity. The results indicate that people assume the probabilities of all target events mentioned in a syllogism to be almost equal, which suggests links between syllogistic reasoning and other areas of cognition. Copyright © 2016 The Author(s). Published by Elsevier B.V. All rights reserved.
The Bogolubov Representation of the Polaron Model and Its Completely Integrable RPA-Approximation
International Nuclear Information System (INIS)
Bogolubov, Nikolai N. Jr.; Prykarpatsky, Yarema A.; Ghazaryan, Anna A.
2009-12-01
The polaron model in ionic crystal is studied in the N. Bogolubov representation using a special RPA-approximation. A new exactly solvable approximated polaron model is derived and described in detail. Its free energy at finite temperature is calculated analytically. The polaron free energy in the constant magnetic field at finite temperature is also discussed. Based on the structure of the N. Bogolubov unitary transformed polaron Hamiltonian a very important new result is stated: the full polaron model is exactly solvable. (author)
Solano, Javier; Duarte, José; Vargas, Erwin; Cabrera, Jhon; Jácome, Andrés; Botero, Mónica; Rey, Juan
2016-10-01
This paper addresses the Energetic Macroscopic Representation EMR, the modelling and the control of photovoltaic panel PVP generation systems for simulation purposes. The model of the PVP considers the variations on irradiance and temperature. A maximum power point tracking MPPT algorithm is considered to control the power converter. A novel EMR is proposed to consider the dynamic model of the PVP with variations in the irradiance and the temperature. The EMR is evaluated through simulations of a PVP generation system.
Modeling biological tissue growth: discrete to continuum representations.
Hywood, Jack D; Hackett-Jones, Emily J; Landman, Kerry A
2013-09-01
There is much interest in building deterministic continuum models from discrete agent-based models governed by local stochastic rules where an agent represents a biological cell. In developmental biology, cells are able to move and undergo cell division on and within growing tissues. A growing tissue is itself made up of cells which undergo cell division, thereby providing a significant transport mechanism for other cells within it. We develop a discrete agent-based model where domain agents represent tissue cells. Each agent has the ability to undergo a proliferation event whereby an additional domain agent is incorporated into the lattice. If a probability distribution describes the waiting times between proliferation events for an individual agent, then the total length of the domain is a random variable. The average behavior of these stochastically proliferating agents defining the growing lattice is determined in terms of a Fokker-Planck equation, with an advection and diffusion term. The diffusion term differs from the one obtained Landman and Binder [J. Theor. Biol. 259, 541 (2009)] when the rate of growth of the domain is specified, but the choice of agents is random. This discrepancy is reconciled by determining a discrete-time master equation for this process and an associated asymmetric nonexclusion random walk, together with consideration of synchronous and asynchronous updating schemes. All theoretical results are confirmed with numerical simulations. This study furthers our understanding of the relationship between agent-based rules, their implementation, and their associated partial differential equations. Since tissue growth is a significant cellular transport mechanism during embryonic growth, it is important to use the correct partial differential equation description when combining with other cellular functions.
On a Modeling of Online User Behavior Using Function Representation
Directory of Open Access Journals (Sweden)
Pavel Pesout
2012-01-01
Full Text Available Understanding the online user system requirements has become very crucial for online services providers. The existence of many users and services leads to different users’ needs. The objective of this presented piece of work is to explore the algorithms of how to optimize providers supply with proposing a new way to represent user requirements as continuous functions depending on time. We address the problems of the prediction the of system requirements and reducing model complexity by creating the typical user behavior profiles.
Phenomenology of non-minimal supersymmetric models at linear colliders
International Nuclear Information System (INIS)
Porto, Stefano
2015-06-01
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
Generic process model structures: towards a standard notation for abstract representations
CSIR Research Space (South Africa)
Van Der Merwe, A
2007-10-01
Full Text Available in the case of objects, or repositories in the case of process models. The creation of the MIT Process Handbook was a step in this direction. However, although the authors used object-oriented concepts in the abstract representations, they did not rigorously...
CSIR Research Space (South Africa)
Garland, Rebecca M
2016-11-01
Full Text Available Aerosol particles can have large impacts on air quality and on the climate system. Regional climate models for Africa have not been well-tested and validated for their representation and simulation of aerosol particles. This study aimed to validate...
Representations of the Poincare group, position operator and the bi-local model
International Nuclear Information System (INIS)
Sohkawa, Tohru
1978-01-01
We propose two types of representations of the Poincare group which give general frameworks for introduction of internal degrees of freedom of a particle. The bi-local model recently proposed by Takabayasi is constructed through our frameworks. In this study, new covariant and non-covariant position operators are introduced and discussed. (author)
A Semiotic Model of Destination Representations Applied to Cultural and Heritage Tourism Marketing
DEFF Research Database (Denmark)
Pennington, Jody; Thomsen, Robert Chr.
2010-01-01
, and symbolic qualities, each of which destination marketers should consider in choosing representations because of the influence those qualities exert on reception. It is argued that the semiotic model can help marketers make informed decisions about the relevance and probable impact of the iconicity...
Using Bar Representations as a Model for Connecting Concepts of Rational Number.
Middleton, James A.; van den Heuvel-Panhuizen, Marja; Shew, Julia A.
1998-01-01
Examines bar models as graphical representations of rational numbers and presents related real life problems. Concludes that, through pairing the fraction bars with ratio tables and other ways of teaching numbers, numeric strategies become connected with visual strategies that allow students with diverse ways of thinking to share their…
Model of geophysical fields representation in problems of complex correlation-extreme navigation
Directory of Open Access Journals (Sweden)
Volodymyr KHARCHENKO
2015-09-01
Full Text Available A model of the optimal representation of spatial data for the task of complex correlation-extreme navigation is developed based on the criterion of minimum deviation of the correlation functions of the original and the resulting fields. Calculations are presented for one-dimensional case using the approximation of the correlation function by Fourier series. It is shown that in the presence of different geophysical map data fields their representation is possible by single template with optimal sampling without distorting the form of the correlation functions.
Population decoding of motor cortical activity using a generalized linear model with hidden states.
Lawhern, Vernon; Wu, Wei; Hatsopoulos, Nicholas; Paninski, Liam
2010-06-15
Generalized linear models (GLMs) have been developed for modeling and decoding population neuronal spiking activity in the motor cortex. These models provide reasonable characterizations between neural activity and motor behavior. However, they lack a description of movement-related terms which are not observed directly in these experiments, such as muscular activation, the subject's level of attention, and other internal or external states. Here we propose to include a multi-dimensional hidden state to address these states in a GLM framework where the spike count at each time is described as a function of the hand state (position, velocity, and acceleration), truncated spike history, and the hidden state. The model can be identified by an Expectation-Maximization algorithm. We tested this new method in two datasets where spikes were simultaneously recorded using a multi-electrode array in the primary motor cortex of two monkeys. It was found that this method significantly improves the model-fitting over the classical GLM, for hidden dimensions varying from 1 to 4. This method also provides more accurate decoding of hand state (reducing the mean square error by up to 29% in some cases), while retaining real-time computational efficiency. These improvements on representation and decoding over the classical GLM model suggest that this new approach could contribute as a useful tool to motor cortical decoding and prosthetic applications. Copyright (c) 2010 Elsevier B.V. All rights reserved.
Population Decoding of Motor Cortical Activity using a Generalized Linear Model with Hidden States
Lawhern, Vernon; Wu, Wei; Hatsopoulos, Nicholas G.; Paninski, Liam
2010-01-01
Generalized linear models (GLMs) have been developed for modeling and decoding population neuronal spiking activity in the motor cortex. These models provide reasonable characterizations between neural activity and motor behavior. However, they lack a description of movement-related terms which are not observed directly in these experiments, such as muscular activation, the subject's level of attention, and other internal or external states. Here we propose to include a multi-dimensional hidden state to address these states in a GLM framework where the spike count at each time is described as a function of the hand state (position, velocity, and acceleration), truncated spike history, and the hidden state. The model can be identified by an Expectation-Maximization algorithm. We tested this new method in two datasets where spikes were simultaneously recorded using a multi-electrode array in the primary motor cortex of two monkeys. It was found that this method significantly improves the model-fitting over the classical GLM, for hidden dimensions varying from 1 to 4. This method also provides more accurate decoding of hand state (lowering the Mean Square Error by up to 29% in some cases), while retaining real-time computational efficiency. These improvements on representation and decoding over the classical GLM model suggest that this new approach could contribute as a useful tool to motor cortical decoding and prosthetic applications. PMID:20359500
Non-Linear Slosh Damping Model Development and Validation
Yang, H. Q.; West, Jeff
2015-01-01
Propellant tank slosh dynamics are typically represented by a mechanical model of spring mass damper. This mechanical model is then included in the equation of motion of the entire vehicle for Guidance, Navigation and Control (GN&C) analysis. For a partially-filled smooth wall propellant tank, the critical damping based on classical empirical correlation is as low as 0.05%. Due to this low value of damping, propellant slosh is potential sources of disturbance critical to the stability of launch and space vehicles. It is postulated that the commonly quoted slosh damping is valid only under the linear regime where the slosh amplitude is small. With the increase of slosh amplitude, the critical damping value should also increase. If this nonlinearity can be verified and validated, the slosh stability margin can be significantly improved, and the level of conservatism maintained in the GN&C analysis can be lessened. The purpose of this study is to explore and to quantify the dependence of slosh damping with slosh amplitude. Accurately predicting the extremely low damping value of a smooth wall tank is very challenging for any Computational Fluid Dynamics (CFD) tool. One must resolve thin boundary layers near the wall and limit numerical damping to minimum. This computational study demonstrates that with proper grid resolution, CFD can indeed accurately predict the low damping physics from smooth walls under the linear regime. Comparisons of extracted damping values with experimental data for different tank sizes show very good agreements. Numerical simulations confirm that slosh damping is indeed a function of slosh amplitude. When slosh amplitude is low, the damping ratio is essentially constant, which is consistent with the empirical correlation. Once the amplitude reaches a critical value, the damping ratio becomes a linearly increasing function of the slosh amplitude. A follow-on experiment validated the developed nonlinear damping relationship. This discovery can
Can representational trajectory reveal the nature of an internal model of gravity?
De Sá Teixeira, Nuno; Hecht, Heiko
2014-05-01
The memory for the vanishing location of a horizontally moving target is usually displaced forward in the direction of motion (representational momentum) and downward in the direction of gravity (representational gravity). Moreover, this downward displacement has been shown to increase with time (representational trajectory). However, the degree to which different kinematic events change the temporal profile of these displacements remains to be determined. The present article attempts to fill this gap. In the first experiment, we replicate the finding that representational momentum for downward-moving targets is bigger than for upward motions, showing, moreover, that it increases rapidly during the first 300 ms, stabilizing afterward. This temporal profile, but not the increased error for descending targets, is shown to be disrupted when eye movements are not allowed. In the second experiment, we show that the downward drift with time emerges even for static targets. Finally, in the third experiment, we report an increased error for upward-moving targets, as compared with downward movements, when the display is compatible with a downward ego-motion by including vection cues. Thus, the errors in the direction of gravity are compatible with the perceived event and do not merely reflect a retinotopic bias. Overall, these results provide further evidence for an internal model of gravity in the visual representational system.
Weck, Philippe F; Kim, Eunja; Wang, Yifeng; Kruichak, Jessica N; Mills, Melissa M; Matteo, Edward N; Pellenq, Roland J-M
2017-08-01
Molecular structures of kerogen control hydrocarbon production in unconventional reservoirs. Significant progress has been made in developing model representations of various kerogen structures. These models have been widely used for the prediction of gas adsorption and migration in shale matrix. However, using density functional perturbation theory (DFPT) calculations and vibrational spectroscopic measurements, we here show that a large gap may still remain between the existing model representations and actual kerogen structures, therefore calling for new model development. Using DFPT, we calculated Fourier transform infrared (FTIR) spectra for six most widely used kerogen structure models. The computed spectra were then systematically compared to the FTIR absorption spectra collected for kerogen samples isolated from Mancos, Woodford and Marcellus formations representing a wide range of kerogen origin and maturation conditions. Limited agreement between the model predictions and the measurements highlights that the existing kerogen models may still miss some key features in structural representation. A combination of DFPT calculations with spectroscopic measurements may provide a useful diagnostic tool for assessing the adequacy of a proposed structural model as well as for future model development. This approach may eventually help develop comprehensive infrared (IR)-fingerprints for tracing kerogen evolution.
Representation of the contextual statistical model by hyperbolic amplitudes
International Nuclear Information System (INIS)
Khrennikov, Andrei
2005-01-01
We continue the development of a so-called contextual statistical model (here context has the meaning of a complex of physical conditions). It is shown that, besides contexts producing the conventional trigonometric cos-interference, there exist contexts producing the hyperbolic cos-interference. Starting with the corresponding interference formula of total probability we represent such contexts by hyperbolic probabilistic amplitudes or in the abstract formalism by normalized vectors of a hyperbolic analogue of the Hilbert space. There is obtained a hyperbolic Born's rule. Incompatible observables are represented by noncommutative operators. This paper can be considered as the first step towards hyperbolic quantum probability. We also discuss possibilities of experimental verification of hyperbolic quantum mechanics: in physics of elementary particles, string theory as well as in experiments with nonphysical systems, e.g., in psychology, cognitive sciences, and economy
Linear collider signal of anomaly mediated supersymmetry breaking model
International Nuclear Information System (INIS)
Ghosh Dilip Kumar; Kundu, Anirban; Roy, Probir; Roy, Sourov
2001-01-01
Though the minimal model of anomaly mediated supersymmetry breaking has been significantly constrained by recent experimental and theoretical work, there are still allowed regions of the parameter space for moderate to large values of tan β. We show that these regions will be comprehensively probed in a √s = 1 TeV e + e - linear collider. Diagnostic signals to this end are studied by zeroing in on a unique and distinct feature of a large class of models in this genre: a neutral winolike Lightest Supersymmetric Particle closely degenerate in mass with a winolike chargino. The pair production processes e + e - → e tilde L ± e tilde L ± , e tilde R ± e tilde R ± , e tilde L ± e tilde R ± , ν tilde anti ν tilde, χ tilde 1 0 χ tilde 2 0 , χ tilde 2 0 χ tilde 2 0 are all considered at √s = 1 TeV corresponding to the proposed TESLA linear collider in two natural categories of mass ordering in the sparticle spectra. The signals analysed comprise multiple combinations of fast charged leptons (any of which can act as the trigger) plus displaced vertices X D (any of which can be identified by a heavy ionizing track terminating in the detector) and/or associated soft pions with characteristic momentum distributions. (author)
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.
Probabilistic model of ligaments and tendons: Quasistatic linear stretching
Bontempi, M.
2009-03-01
Ligaments and tendons have a significant role in the musculoskeletal system and are frequently subjected to injury. This study presents a model of collagen fibers, based on the study of a statistical distribution of fibers when they are subjected to quasistatic linear stretching. With respect to other methodologies, this model is able to describe the behavior of the bundle using less ad hoc hypotheses and is able to describe all the quasistatic stretch-load responses of the bundle, including the yield and failure regions described in the literature. It has two other important results: the first is that it is able to correlate the mechanical behavior of the bundle with its internal structure, and it suggests a methodology to deduce the fibers population distribution directly from the tensile-test data. The second is that it can follow fibers’ structure evolution during the stretching and it is possible to study the internal adaptation of fibers in physiological and pathological conditions.
Linear mixing model applied to coarse resolution satellite data
Holben, Brent N.; Shimabukuro, Yosio E.
1992-01-01
A linear mixing model typically applied to high resolution data such as Airborne Visible/Infrared Imaging Spectrometer, Thematic Mapper, and Multispectral Scanner System is applied to the NOAA Advanced Very High Resolution Radiometer coarse resolution satellite data. The reflective portion extracted from the middle IR channel 3 (3.55 - 3.93 microns) is used with channels 1 (0.58 - 0.68 microns) and 2 (0.725 - 1.1 microns) to run the Constrained Least Squares model to generate fraction images for an area in the west central region of Brazil. The derived fraction images are compared with an unsupervised classification and the fraction images derived from Landsat TM data acquired in the same day. In addition, the relationship betweeen these fraction images and the well known NDVI images are presented. The results show the great potential of the unmixing techniques for applying to coarse resolution data for global studies.
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.
Locally supersymmetric D=3 non-linear sigma models
International Nuclear Information System (INIS)
Wit, B. de; Tollsten, A.K.; Nicolai, H.
1993-01-01
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 Kaehler, respectively. All N>2 theories are associated with Einstein spaces. For N=3 the target space is quaternionic, while for N=4 it generally decomposes, into two separate quaternionic spaces, associated with inequivalent supermultiplets. For N=5, 6, 8 there is a unique (symmetric) space for any given number of supermultiplets. Beyond that there are only theories based on a single supermultiplet for N=9, 10, 12 and 16, associated with coset spaces with the exceptional isometry groups F 4(-20) , E 6(-14) , E 7(-5) and E 8(+8) , respectively. For N=3 and N ≥ 5 the D=2 theories obtained by dimensional reduction are two-loop finite. (orig.)
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.
Synthetic Domain Theory and Models of Linear Abadi & Plotkin Logic
DEFF Research Database (Denmark)
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...
Improving the representation of soluble iron in climate models
Energy Technology Data Exchange (ETDEWEB)
Mahowald, Natalie [Cornell Univ., Ithaca, NY (United States)
2016-11-29
Funding from this grant supported Rachel Sanza, Yan Zhang and partially Samuel Albani. Substantial progress has been made on inclusion of mineralogy, showing the quality of the simulations, and the impact on radiation in the CAM4 and CAM5 (Scanza et al., 2015). In addition, the elemental distribution has been evaluated (and partially supported by this grant) (Zhang et al., 2015), showing that using spatial distributions of mineralogy, improved resperentation of Fe, Ca and Al are possible, compared to the limited available data. A new intermediate complexity soluble iron scheme was implemented in the Bulk Aerosol Model (BAM), which was completed as part of Rachel Scanza’s PhD thesis. Currently Rachel is writing up at least two first author papers describing the general methods and comparison to observations (Scanza et al., in prep.), as well as papers describing the sensitivity to preindustrial conditions and interannual variability. This work lead to the lead PI being asked to write a commentary in Nature (Mahowald, 2013) and two review papers (Mahowald et al., 2014, Mahowald et al., submitted) and contributed to related papers (Albani et al., 2016, Albani et al., 2014, Albani et al., 2015).
Schiffler, Ralf
2014-01-01
This book is intended to serve as a textbook for a course in Representation Theory of Algebras at the beginning graduate level. The text has two parts. In Part I, the theory is studied in an elementary way using quivers and their representations. This is a very hands-on approach and requires only basic knowledge of linear algebra. The main tool for describing the representation theory of a finite-dimensional algebra is its Auslander-Reiten quiver, and the text introduces these quivers as early as possible. Part II then uses the language of algebras and modules to build on the material developed before. The equivalence of the two approaches is proved in the text. The last chapter gives a proof of Gabriel’s Theorem. The language of category theory is developed along the way as needed.
The quantum Rabi model and Lie algebra representations of sl2
International Nuclear Information System (INIS)
Wakayama, Masato; Yamasaki, Taishi
2014-01-01
The aim of the present paper is to understand the spectral problem of the quantum Rabi model in terms of Lie algebra representations of sl 2 (R). We define a second order element of the universal enveloping algebra U(sl 2 ) of sl 2 (R), which, through the image of a principal series representation of sl 2 (R), provides a picture equivalent to the quantum Rabi model drawn by confluent Heun differential equations. By this description, in particular, we give a representation theoretic interpretation of the degenerate part of the spectrum (i.e., Judd's eigenstates) of the Rabi Hamiltonian due to Kuś in 1985, which is a part of the exceptional spectrum parameterized by integers. We also discuss the non-degenerate part of the exceptional spectrum of the model, in addition to the Judd eigenstates, from a viewpoint of infinite dimensional irreducible submodules (or subquotients) of the non-unitary principal series such as holomorphic discrete series representations of sl 2 (R). (paper)
Solving large mixed linear models using preconditioned conjugate gradient iteration.
Strandén, I; Lidauer, M
1999-12-01
Continuous evaluation of dairy cattle with a random regression test-day model requires a fast solving method and algorithm. A new computing technique feasible in Jacobi and conjugate gradient based iterative methods using iteration on data is presented. In the new computing technique, the calculations in multiplication of a vector by a matrix were recorded to three steps instead of the commonly used two steps. The three-step method was implemented in a general mixed linear model program that used preconditioned conjugate gradient iteration. Performance of this program in comparison to other general solving programs was assessed via estimation of breeding values using univariate, multivariate, and random regression test-day models. Central processing unit time per iteration with the new three-step technique was, at best, one-third that needed with the old technique. Performance was best with the test-day model, which was the largest and most complex model used. The new program did well in comparison to other general software. Programs keeping the mixed model equations in random access memory required at least 20 and 435% more time to solve the univariate and multivariate animal models, respectively. Computations of the second best iteration on data took approximately three and five times longer for the animal and test-day models, respectively, than did the new program. Good performance was due to fast computing time per iteration and quick convergence to the final solutions. Use of preconditioned conjugate gradient based methods in solving large breeding value problems is supported by our findings.
Linear mixed-effects modeling approach to FMRI group analysis.
Chen, Gang; Saad, Ziad S; Britton, Jennifer C; Pine, Daniel S; Cox, Robert W
2013-06-01
Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance-covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as experiments are designed with different degrees of sophistication, these traditional methods can become cumbersome, or even be unable to handle the situation at hand. For example, most current FMRI software packages have difficulty analyzing the following scenarios at group level: (1) taking within-subject variability into account when there are effect estimates from multiple runs or sessions; (2) continuous explanatory variables (covariates) modeling in the presence of a within-subject (repeated measures) factor, multiple subject-grouping (between-subjects) factors, or the mixture of both; (3) subject-specific adjustments in covariate modeling; (4) group analysis with estimation of hemodynamic response (HDR) function by multiple basis functions; (5) various cases of missing data in longitudinal studies; and (6) group studies involving family members or twins. Here we present a linear mixed-effects modeling (LME) methodology that extends the conventional group analysis approach to analyze many complicated cases, including the six prototypes delineated above, whose analyses would be otherwise either difficult or unfeasible under traditional frameworks such as AN(C)OVA and general linear model (GLM). In addition, the strength of the LME framework lies in its flexibility to model and estimate the variance-covariance structures for both random effects and residuals. The intraclass correlation (ICC) values can be easily obtained with an LME model with crossed random effects, even at the presence of confounding fixed effects. The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the sensitivity
Energy Technology Data Exchange (ETDEWEB)
Reisch, F; Vayssier, G
1969-05-15
This non-linear model serves as one of the blocks in a series of codes to study the transient behaviour of BWR or PWR type reactors. This program is intended to be the hydrodynamic part of the BWR core representation or the hydrodynamic part of the PWR heat exchanger secondary side representation. The equations have been prepared for the CSMP digital simulation language. By using the most suitable integration routine available, the ratio of simulation time to real time is about one on an IBM 360/75 digital computer. Use of the slightly different language DSL/40 on an IBM 7044 computer takes about four times longer. The code has been tested against the Eindhoven loop with satisfactory agreement.
Continuous versus discontinuous albedo representations in a simple diffusive climate model
Simmons, P. A.; Griffel, D. H.
1988-07-01
A one-dimensional annually and zonally averaged energy-balance model, with diffusive meridional heat transport and including icealbedo feedback, is considered. This type of model is found to be very sensitive to the form of albedo used. The solutions for a discontinuous step-function albedo are compared to those for a more realistic smoothly varying albedo. The smooth albedo gives a closer fit to present conditions, but the discontinuous form gives a better representation of climates in earlier epochs.
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.
Linear model applied to the evaluation of pharmaceutical stability data
Directory of Open Access Journals (Sweden)
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.
Fourth standard model family neutrino at future linear colliders
International Nuclear Information System (INIS)
Ciftci, A.K.; Ciftci, R.; Sultansoy, S.
2005-01-01
It is known that flavor democracy favors the existence of the fourth standard model (SM) family. In order to give nonzero masses for the first three-family fermions flavor democracy has to be slightly broken. A parametrization for democracy breaking, which gives the correct values for fundamental fermion masses and, at the same time, predicts quark and lepton Cabibbo-Kobayashi-Maskawa (CKM) matrices in a good agreement with the experimental data, is proposed. The pair productions of the fourth SM family Dirac (ν 4 ) and Majorana (N 1 ) neutrinos at future linear colliders with √(s)=500 GeV, 1 TeV, and 3 TeV are considered. The cross section for the process e + e - →ν 4 ν 4 (N 1 N 1 ) and the branching ratios for possible decay modes of the both neutrinos are determined. The decays of the fourth family neutrinos into muon channels (ν 4 (N 1 )→μ ± W ± ) provide cleanest signature at e + e - colliders. Meanwhile, in our parametrization this channel is dominant. W bosons produced in decays of the fourth family neutrinos will be seen in detector as either di-jets or isolated leptons. As an example, we consider the production of 200 GeV mass fourth family neutrinos at √(s)=500 GeV linear colliders by taking into account di-muon plus four jet events as signatures
Influence of the void fraction in the linear reactivity model
International Nuclear Information System (INIS)
Castillo, J.A.; Ramirez, J.R.; Alonso, G.
2003-01-01
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)
Characteristics and Properties of a Simple Linear Regression Model
Directory of Open Access Journals (Sweden)
Kowal Robert
2016-12-01
Full Text Available A simple linear regression model is one of the pillars of classic econometrics. Despite the passage of time, it continues to raise interest both from the theoretical side as well as from the application side. One of the many fundamental questions in the model concerns determining derivative characteristics and studying the properties existing in their scope, referring to the first of these aspects. The literature of the subject provides several classic solutions in that regard. In the paper, a completely new design is proposed, based on the direct application of variance and its properties, resulting from the non-correlation of certain estimators with the mean, within the scope of which some fundamental dependencies of the model characteristics are obtained in a much more compact manner. The apparatus allows for a simple and uniform demonstration of multiple dependencies and fundamental properties in the model, and it does it in an intuitive manner. The results were obtained in a classic, traditional area, where everything, as it might seem, has already been thoroughly studied and discovered.
A simple non-linear model of immune response
International Nuclear Information System (INIS)
Gutnikov, Sergei; Melnikov, Yuri
2003-01-01
It is still unknown why the adaptive immune response in the natural immune system based on clonal proliferation of lymphocytes requires interaction of at least two different cell types with the same antigen. We present a simple mathematical model illustrating that the system with separate types of cells for antigen recognition and patogen destruction provides more robust adaptive immunity than the system where just one cell type is responsible for both recognition and destruction. The model is over-simplified as we did not have an intention of describing the natural immune system. However, our model provides a tool for testing the proposed approach through qualitative analysis of the immune system dynamics in order to construct more sophisticated models of the immune systems that exist in the living nature. It also opens a possibility to explore specific features of highly non-linear dynamics in nature-inspired computational paradigms like artificial immune systems and immunocomputing . We expect this paper to be of interest not only for mathematicians but also for biologists; therefore we made effort to explain mathematics in sufficient detail for readers without professional mathematical background
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. Copyright © 2016 The Author. Published by Elsevier Ltd.. All rights reserved.
Explicit state representation and the ATLAS event data model: theory and practice
International Nuclear Information System (INIS)
Nowak, M; Snyder, S; Cranmer, K; Malon, D; Gemmeren, P v; Schaffer, A; Binet, S
2008-01-01
In anticipation of data taking, ATLAS has undertaken a program of work to develop an explicit state representation of the experiment's complex transient event data model. This effort has provided both an opportunity to consider explicitly the structure, organization, and content of the ATLAS persistent event store before writing tens of petabytes of data (replacing simple streaming, which uses the persistent store as a core dump of transient memory), and a locus for support of event data model evolution, including significant refactoring, beyond the automatic schema evolution capabilities of underlying persistence technologies. ATLAS has encountered the need for such non-trivial schema evolution on several occasions already. This paper describes the state representation strategy (transient/persistent separation) and its implementation, including both the payoffs that ATLAS has seen (significant and sometimes surprising space and performance improvements, the extra layer notwithstanding, and extremely general schema evolution support) and the costs (additional and relatively pervasive additional infrastructure development and maintenance). The paper further discusses how these costs are mitigated, and how ATLAS is able to implement this strategy without losing the ability to take advantage of the (improving!) automatic schema evolution capabilities of underlying technology layers when appropriate. Implications of state representations for direct ROOT browsability, and current strategies for associating physics analysis views with such state representations, are also described
A Non-linear Stochastic Model for an Office Building with Air Infiltration
DEFF Research Database (Denmark)
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...
Distributing Correlation Coefficients of Linear Structure-Activity/Property Models
Directory of Open Access Journals (Sweden)
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.
Modeling and analysis of linearized wheel-rail contact dynamics
International Nuclear Information System (INIS)
Soomro, Z.
2014-01-01
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. (author)
Human visual modeling and image deconvolution by linear filtering
International Nuclear Information System (INIS)
Larminat, P. de; Barba, D.; Gerber, R.; Ronsin, J.
1978-01-01
The problem is the numerical restoration of images degraded by passing through a known and spatially invariant linear system, and by the addition of a stationary noise. We propose an improvement of the Wiener's filter to allow the restoration of such images. This improvement allows to reduce the important drawbacks of classical Wiener's filter: the voluminous data processing, the lack of consideration of the vision's characteristivs which condition the perception by the observer of the restored image. In a first paragraph, we describe the structure of the visual detection system and a modelling method of this system. In the second paragraph we explain a restoration method by Wiener filtering that takes the visual properties into account and that can be adapted to the local properties of the image. Then the results obtained on TV images or scintigrams (images obtained by a gamma-camera) are commented [fr
Convergence diagnostics for Eigenvalue problems with linear regression model
International Nuclear Information System (INIS)
Shi, Bo; Petrovic, Bojan
2011-01-01
Although the Monte Carlo method has been extensively used for criticality/Eigenvalue problems, a reliable, robust, and efficient convergence diagnostics method is still desired. Most methods are based on integral parameters (multiplication factor, entropy) and either condense the local distribution information into a single value (e.g., entropy) or even disregard it. We propose to employ the detailed cycle-by-cycle local flux evolution obtained by using mesh tally mechanism to assess the source and flux convergence. By applying a linear regression model to each individual mesh in a mesh tally for convergence diagnostics, a global convergence criterion can be obtained. We exemplify this method on two problems and obtain promising diagnostics results. (author)
A Dynamic Linear Modeling Approach to Public Policy Change
DEFF Research Database (Denmark)
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...
Baryon and meson phenomenology in the extended Linear Sigma Model
Energy Technology Data Exchange (ETDEWEB)
Giacosa, Francesco; Habersetzer, Anja; Teilab, Khaled; Eshraim, Walaa; Divotgey, Florian; Olbrich, Lisa; Gallas, Susanna; Wolkanowski, Thomas; Janowski, Stanislaus; Heinz, Achim; Deinet, Werner; Rischke, Dirk H. [Institute for Theoretical Physics, J. W. Goethe University, Max-von-Laue-Str. 1, 60438 Frankfurt am Main (Germany); Kovacs, Peter; Wolf, Gyuri [Institute for Particle and Nuclear Physics, Wigner Research Center for Physics, Hungarian Academy of Sciences, H-1525 Budapest (Hungary); Parganlija, Denis [Institute for Theoretical Physics, Vienna University of Technology, Wiedner Hauptstr. 8-10, A-1040 Vienna (Austria)
2014-07-01
The vacuum phenomenology obtained within the so-called extended Linear Sigma Model (eLSM) is presented. The eLSM Lagrangian is constructed by including from the very beginning vector and axial-vector d.o.f., and by requiring dilatation invariance and chiral symmetry. After a general introduction of the approach, particular attention is devoted to the latest results. In the mesonic sector the strong decays of the scalar and the pseudoscalar glueballs, the weak decays of the tau lepton into vector and axial-vector mesons, and the description of masses and decays of charmed mesons are shown. In the baryonic sector the omega production in proton-proton scattering and the inclusion of baryons with strangeness are described.
Non Abelian T-duality in Gauged Linear Sigma Models
Bizet, Nana Cabo; Martínez-Merino, Aldo; Zayas, Leopoldo A. Pando; Santos-Silva, Roberto
2018-04-01
Abelian T-duality in Gauged Linear Sigma Models (GLSM) forms the basis of the physical understanding of Mirror Symmetry as presented by Hori and Vafa. We consider an alternative formulation of Abelian T-duality on GLSM's as a gauging of a global U(1) symmetry with the addition of appropriate Lagrange multipliers. For GLSMs with Abelian gauge groups and without superpotential we reproduce the dual models introduced by Hori and Vafa. We extend the construction to formulate non-Abelian T-duality on GLSMs with global non-Abelian symmetries. The equations of motion that lead to the dual model are obtained for a general group, they depend in general on semi-chiral superfields; for cases such as SU(2) they depend on twisted chiral superfields. We solve the equations of motion for an SU(2) gauged group with a choice of a particular Lie algebra direction of the vector superfield. This direction covers a non-Abelian sector that can be described by a family of Abelian dualities. The dual model Lagrangian depends on twisted chiral superfields and a twisted superpotential is generated. We explore some non-perturbative aspects by making an Ansatz for the instanton corrections in the dual theories. We verify that the effective potential for the U(1) field strength in a fixed configuration on the original theory matches the one of the dual theory. Imposing restrictions on the vector superfield, more general non-Abelian dual models are obtained. We analyze the dual models via the geometry of their susy vacua.
A comparison of linear interpolation models for iterative CT reconstruction.
Hahn, Katharina; Schöndube, Harald; Stierstorfer, Karl; Hornegger, Joachim; Noo, Frédéric
2016-12-01
Recent reports indicate that model-based iterative reconstruction methods may improve image quality in computed tomography (CT). One difficulty with these methods is the number of options available to implement them, including the selection of the forward projection model and the penalty term. Currently, the literature is fairly scarce in terms of guidance regarding this selection step, whereas these options impact image quality. Here, the authors investigate the merits of three forward projection models that rely on linear interpolation: the distance-driven method, Joseph's method, and the bilinear method. The authors' selection is motivated by three factors: (1) in CT, linear interpolation is often seen as a suitable trade-off between discretization errors and computational cost, (2) the first two methods are popular with manufacturers, and (3) the third method enables assessing the importance of a key assumption in the other methods. One approach to evaluate forward projection models is to inspect their effect on discretized images, as well as the effect of their transpose on data sets, but significance of such studies is unclear since the matrix and its transpose are always jointly used in iterative reconstruction. Another approach is to investigate the models in the context they are used, i.e., together with statistical weights and a penalty term. Unfortunately, this approach requires the selection of a preferred objective function and does not provide clear information on features that are intrinsic to the model. The authors adopted the following two-stage methodology. First, the authors analyze images that progressively include components of the singular value decomposition of the model in a reconstructed image without statistical weights and penalty term. Next, the authors examine the impact of weights and penalty on observed differences. Image quality metrics were investigated for 16 different fan-beam imaging scenarios that enabled probing various aspects
International Nuclear Information System (INIS)
Uren, Kenneth Richard; Schoor, George van
2013-01-01
This second paper in a two part series presents the application of a developed state space model extraction methodology applied to a Brayton cycle-based PCU (power conversion unit) of a PBMR (pebble bed modular reactor). The goal is to investigate if the state space extraction methodology can cope with larger and more complex thermohydraulic systems. In Part I the state space model extraction methodology for the purpose of control was described in detail and a state space representation was extracted for a U-tube system to illustrate the concept. In this paper a 25th order nonlinear state space representation in terms of the different energy domains is extracted. This state space representation is solved and the responses of a number of important states are compared with results obtained from a PBMR PCU Flownex ® model. Flownex ® is a validated thermo fluid simulation software package. The results show that the state space model closely resembles the dynamics of the PBMR PCU. This kind of model may be used for nonlinear MIMO (multi-input, multi-output) type of control strategies. However, there is still a need for linear state space models since many control system design and analysis techniques require a linear state space model. This issue is also addressed in this paper by showing how a linear state space model can be derived from the extracted nonlinear state space model. The linearised state space model is also validated by comparing the state space model to an existing linear Simulink ® model of the PBMR PCU system. - Highlights: • State space model extraction of a pebble bed modular reactor PCU (power conversion unit). • A 25th order nonlinear time varying state space model is obtained. • Linearisation of a nonlinear state space model for use in power output control. • Non-minimum phase characteristic that is challenging in terms of control. • Models derived are useful for MIMO control strategies
Cherkasskaya, Eugenia; Rosario, Margaret
2017-11-01
The etiology of low female sexual desire, the most prevalent sexual complaint in women, is multi-determined, implicating biological and psychological factors, including women's early parent-child relationships and bodily self-representations. The current study evaluated a model that hypothesized that sexual body self-representations (sexual subjectivity, self-objectification, genital self-image) explain (i.e., mediate) the relation between internalized working models of parent-child relationships (attachment, separation-individuation, parental identification) and sexual desire in heterosexual women. We recruited 614 young, heterosexual women (M = 25.5 years, SD = 4.63) through social media. The women completed an online survey. Structural equation modeling was used. The hypotheses were supported in that the relation between internalized working models of parent-child relationships (attachment and separation-individuation) and sexual desire was mediated by sexual body self-representations (sexual body esteem, self-objectification, genital self-image). However, parental identification was not related significantly to sexual body self-representations or sexual desire in the model. Current findings demonstrated that understanding female sexual desire necessitates considering women's internalized working models of early parent-child relationships and their experiences of their bodies in a sexual context. Treatment of low or absent desire in women would benefit from modalities that emphasize early parent-child relationships as well as interventions that foster mind-body integration.
Optimizing Biorefinery Design and Operations via Linear Programming Models
Energy Technology Data Exchange (ETDEWEB)
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
Prather, Edward
2018-01-01
Astronomy education researchers in the Department of Astronomy at the University of Arizona have been investigating a new framework for getting students to engage in discussions about fundamental astronomy topics. This framework is intended to also provide students with explicit feedback on the correctness and coherency of their mental models on these topics. This framework builds upon our prior efforts to create productive Pedagogical Discipline Representations (PDR). Students are asked to work collaboratively to generate their own representations (drawings, graphs, data tables, etc.) that reflect important characteristics of astrophysical scenarios presented in class. We have found these representation tasks offer tremendous insight into the broad range of ideas and knowledge students possess after instruction that includes both traditional lecture and actively learning strategies. In particular, we find that some of our students are able to correctly answer challenging multiple-choice questions on topics, however, they struggle to accurately create representations of these same topics themselves. Our work illustrates that some of our students are not developing a robust level of discipline fluency with many core ideas in astronomy, even after engaging with active learning strategies.
International Nuclear Information System (INIS)
Thuburn, J.; Woollings, T.J.
2005-01-01
Accurate representation of different kinds of wave motion is essential for numerical models of the atmosphere, but is sensitive to details of the discretization. In this paper, numerical dispersion relations are computed for different vertical discretizations of the compressible Euler equations and compared with the analytical dispersion relation. A height coordinate, an isentropic coordinate, and a terrain-following mass-based coordinate are considered, and, for each of these, different choices of prognostic variables and grid staggerings are considered. The discretizations are categorized according to whether their dispersion relations are optimal, are near optimal, have a single zero-frequency computational mode, or are problematic in other ways. Some general understanding of the factors that affect the numerical dispersion properties is obtained: heuristic arguments concerning the normal mode structures, and the amount of averaging and coarse differencing in the finite difference scheme, are shown to be useful guides to which configurations will be optimal; the number of degrees of freedom in the discretization is shown to be an accurate guide to the existence of computational modes; there is only minor sensitivity to whether the equations for thermodynamic variables are discretized in advective form or flux form; and an accurate representation of acoustic modes is found to be a prerequisite for accurate representation of inertia-gravity modes, which, in turn, is found to be a prerequisite for accurate representation of Rossby modes
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.
Monteghetti, Florian; Matignon, Denis; Piot, Estelle; Pascal, Lucas
2016-09-01
A methodology to design broadband time-domain impedance boundary conditions (TDIBCs) from the analysis of acoustical models is presented. The derived TDIBCs are recast exclusively as first-order differential equations, well-suited for high-order numerical simulations. Broadband approximations are yielded from an elementary linear least squares optimization that is, for most models, independent of the absorbing material geometry. This methodology relies on a mathematical technique referred to as the oscillatory-diffusive (or poles and cuts) representation, and is applied to a wide range of acoustical models, drawn from duct acoustics and outdoor sound propagation, which covers perforates, semi-infinite ground layers, as well as cavities filled with a porous medium. It is shown that each of these impedance models leads to a different TDIBC. Comparison with existing numerical models, such as multi-pole or extended Helmholtz resonator, provides insights into their suitability. Additionally, the broadly-applicable fractional polynomial impedance models are analyzed using fractional calculus.
Linear programming model can explain respiration of fermentation products
Möller, Philip; Liu, Xiaochen; Schuster, Stefan
2018-01-01
Many differentiated cells rely primarily on mitochondrial oxidative phosphorylation for generating energy in the form of ATP needed for cellular metabolism. In contrast most tumor cells instead rely on aerobic glycolysis leading to lactate to about the same extent as on respiration. Warburg found that cancer cells to support oxidative phosphorylation, tend to ferment glucose or other energy source into lactate even in the presence of sufficient oxygen, which is an inefficient way to generate ATP. This effect also occurs in striated muscle cells, activated lymphocytes and microglia, endothelial cells and several mammalian cell types, a phenomenon termed the “Warburg effect”. The effect is paradoxical at first glance because the ATP production rate of aerobic glycolysis is much slower than that of respiration and the energy demands are better to be met by pure oxidative phosphorylation. We tackle this question by building a minimal model including three combined reactions. The new aspect in extension to earlier models is that we take into account the possible uptake and oxidation of the fermentation products. We examine the case where the cell can allocate protein on several enzymes in a varying distribution and model this by a linear programming problem in which the objective is to maximize the ATP production rate under different combinations of constraints on enzymes. Depending on the cost of reactions and limitation of the substrates, this leads to pure respiration, pure fermentation, and a mixture of respiration and fermentation. The model predicts that fermentation products are only oxidized when glucose is scarce or its uptake is severely limited. PMID:29415045
Linear programming model can explain respiration of fermentation products.
Möller, Philip; Liu, Xiaochen; Schuster, Stefan; Boley, Daniel
2018-01-01
Many differentiated cells rely primarily on mitochondrial oxidative phosphorylation for generating energy in the form of ATP needed for cellular metabolism. In contrast most tumor cells instead rely on aerobic glycolysis leading to lactate to about the same extent as on respiration. Warburg found that cancer cells to support oxidative phosphorylation, tend to ferment glucose or other energy source into lactate even in the presence of sufficient oxygen, which is an inefficient way to generate ATP. This effect also occurs in striated muscle cells, activated lymphocytes and microglia, endothelial cells and several mammalian cell types, a phenomenon termed the "Warburg effect". The effect is paradoxical at first glance because the ATP production rate of aerobic glycolysis is much slower than that of respiration and the energy demands are better to be met by pure oxidative phosphorylation. We tackle this question by building a minimal model including three combined reactions. The new aspect in extension to earlier models is that we take into account the possible uptake and oxidation of the fermentation products. We examine the case where the cell can allocate protein on several enzymes in a varying distribution and model this by a linear programming problem in which the objective is to maximize the ATP production rate under different combinations of constraints on enzymes. Depending on the cost of reactions and limitation of the substrates, this leads to pure respiration, pure fermentation, and a mixture of respiration and fermentation. The model predicts that fermentation products are only oxidized when glucose is scarce or its uptake is severely limited.
International Nuclear Information System (INIS)
Niccoli, G.
2009-12-01
In an earlier paper (G. Niccoli and J. Teschner, 2009), the spectrum (eigenvalues and eigenstates) of a lattice regularizations of the Sine-Gordon model has been completely characterized in terms of polynomial solutions with certain properties of the Baxter equation. This characterization for cyclic representations has been derived by the use of the Separation of Variables (SOV) method of Sklyanin and by the direct construction of the Baxter Q-operator family. Here, we reconstruct the Baxter Q-operator and the same characterization of the spectrum by only using the SOV method. This analysis allows us to deduce the main features required for the extension to cyclic representations of other integrable quantum models of this kind of spectrum characterization. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Niccoli, G.
2009-12-15
In an earlier paper (G. Niccoli and J. Teschner, 2009), the spectrum (eigenvalues and eigenstates) of a lattice regularizations of the Sine-Gordon model has been completely characterized in terms of polynomial solutions with certain properties of the Baxter equation. This characterization for cyclic representations has been derived by the use of the Separation of Variables (SOV) method of Sklyanin and by the direct construction of the Baxter Q-operator family. Here, we reconstruct the Baxter Q-operator and the same characterization of the spectrum by only using the SOV method. This analysis allows us to deduce the main features required for the extension to cyclic representations of other integrable quantum models of this kind of spectrum characterization. (orig.)
On the Representation of Subgrid Microtopography Effects in Process-based Hydrologic Models
Jan, A.; Painter, S. L.; Coon, E. T.
2017-12-01
Increased availability of high-resolution digital elevation are enabling process-based hydrologic modeling on finer and finer scales. However, spatial variability in surface elevation (microtopography) exists below the scale of a typical hyper-resolution grid cell and has the potential to play a significant role in water retention, runoff, and surface/subsurface interactions. Though the concept of microtopographic features (depressions, obstructions) and the associated implications on flow and discharge are well established, representing those effects in watershed-scale integrated surface/subsurface hydrology models remains a challenge. Using the complex and coupled hydrologic environment of the Arctic polygonal tundra as an example, we study the effects of submeter topography and present a subgrid model parameterized by small-scale spatial heterogeneities for use in hyper-resolution models with polygons at a scale of 15-20 meters forming the surface cells. The subgrid model alters the flow and storage terms in the diffusion wave equation for surface flow. We compare our results against sub-meter scale simulations (acts as a benchmark for our simulations) and hyper-resolution models without the subgrid representation. The initiation of runoff in the fine-scale simulations is delayed and the recession curve is slowed relative to simulated runoff using the hyper-resolution model with no subgrid representation. Our subgrid modeling approach improves the representation of runoff and water retention relative to models that ignore subgrid topography. We evaluate different strategies for parameterizing subgrid model and present a classification-based method to efficiently move forward to larger landscapes. This work was supported by the Interoperable Design of Extreme-scale Application Software (IDEAS) project and the Next-Generation Ecosystem Experiments-Arctic (NGEE Arctic) project. NGEE-Arctic is supported by the Office of Biological and Environmental Research in the
Transport coefficients from SU(3) Polyakov linear-σ model
International Nuclear Information System (INIS)
Tawfik, A.; Diab, A.
2015-01-01
In the mean field approximation, the grand potential of SU(3) Polyakov linear-σ model (PLSM) is analyzed for the order parameter of the light and strange chiral phase-transitions, σ l and σ s , respectively, and for the deconfinement order parameters φ and φ*. Furthermore, the subtracted condensate Δ l,s and the chiral order-parameters M b are compared with lattice QCD calculations. By using the dynamical quasiparticle model (DQPM), which can be considered as a system of noninteracting massive quasiparticles, we have evaluated the decay width and the relaxation time of quarks and gluons. In the framework of LSM and with Polyakov loop corrections included, the interaction measure Δ/T 4 , the specific heat c v and speed of sound squared c s 2 have been determined, as well as the temperature dependence of the normalized quark number density n q /T 3 and the quark number susceptibilities χ q /T 2 at various values of the baryon chemical potential. The electric and heat conductivity, σ e and κ, and the bulk and shear viscosities normalized to the thermal entropy, ζ/s and η/s, are compared with available results of lattice QCD calculations.
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.
Generalized Functional Linear Models With Semiparametric Single-Index Interactions
Li, Yehua; Wang, Naisyin; Carroll, Raymond J.
2010-01-01
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.
Hu, Eric Y; Bouteiller, Jean-Marie C; Song, Dong; Baudry, Michel; Berger, Theodore W
2015-01-01
Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO) synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations.
Modeling containment of large wildfires using generalized linear mixed-model analysis
Mark Finney; Isaac C. Grenfell; Charles W. McHugh
2009-01-01
Billions of dollars are spent annually in the United States to contain large wildland fires, but the factors contributing to suppression success remain poorly understood. We used a regression model (generalized linear mixed-model) to model containment probability of individual fires, assuming that containment was a repeated-measures problem (fixed effect) and...
Stochastic linear hybrid systems: Modeling, estimation, and application
Seah, Chze Eng
Hybrid systems are dynamical systems which have interacting continuous state and discrete state (or mode). Accurate modeling and state estimation of hybrid systems are important in many applications. We propose a hybrid system model, known as the Stochastic Linear Hybrid System (SLHS), to describe hybrid systems with stochastic linear system dynamics in each mode and stochastic continuous-state-dependent mode transitions. We then develop a hybrid estimation algorithm, called the State-Dependent-Transition Hybrid Estimation (SDTHE) algorithm, to estimate the continuous state and discrete state of the SLHS from noisy measurements. It is shown that the SDTHE algorithm is more accurate or more computationally efficient than existing hybrid estimation algorithms. Next, we develop a performance analysis algorithm to evaluate the performance of the SDTHE algorithm in a given operating scenario. We also investigate sufficient conditions for the stability of the SDTHE algorithm. The proposed SLHS model and SDTHE algorithm are illustrated to be useful in several applications. In Air Traffic Control (ATC), to facilitate implementations of new efficient operational concepts, accurate modeling and estimation of aircraft trajectories are needed. In ATC, an aircraft's trajectory can be divided into a number of flight modes. Furthermore, as the aircraft is required to follow a given flight plan or clearance, its flight mode transitions are dependent of its continuous state. However, the flight mode transitions are also stochastic due to navigation uncertainties or unknown pilot intents. Thus, we develop an aircraft dynamics model in ATC based on the SLHS. The SDTHE algorithm is then used in aircraft tracking applications to estimate the positions/velocities of aircraft and their flight modes accurately. Next, we develop an aircraft conformance monitoring algorithm to detect any deviations of aircraft trajectories in ATC that might compromise safety. In this application, the SLHS
IRF models associated with representations of the Lie superalgebras gl(m|n) and sl(m|n)
International Nuclear Information System (INIS)
Deguchi, T.; Fujii, A.
1991-01-01
This paper presents two families of exactly solvable interaction round a face (IRF) models associated with representations of the Lie superalgebras gl(m/n) and sl(m/n). These IRF models are the generalizations of integrable spin chains with bosons and fermions. The authors present fusion models associated with higher representations of gl(m/n) and sl(m/n). The authors introduce restricted IRF models both for gl(m/n) and sl(m/n)
Identification of an Equivalent Linear Model for a Non-Linear Time-Variant RC-Structure
DEFF Research Database (Denmark)
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......This paper considers estimation of the maximum softening for a RC-structure subjected to earthquake excitation. The so-called Maximum Softening damage indicator relates the global damage state of the RC-structure to the relative decrease of the fundamental eigenfrequency in an equivalent linear...
Sakti, Apurba; Gallagher, Kevin G.; Sepulveda, Nestor; Uckun, Canan; Vergara, Claudio; de Sisternes, Fernando J.; Dees, Dennis W.; Botterud, Audun
2017-02-01
We develop three novel enhanced mixed integer-linear representations of the power limit of the battery and its efficiency as a function of the charge and discharge power and the state of charge of the battery, which can be directly implemented in large-scale power systems models and solved with commercial optimization solvers. Using these battery representations, we conduct a techno-economic analysis of the performance of a 10 MWh lithium-ion battery system testing the effect of a 5-min vs. a 60-min price signal on profits using real time prices from a selected node in the MISO electricity market. Results show that models of lithium-ion batteries where the power limits and efficiency are held constant overestimate profits by 10% compared to those obtained from an enhanced representation that more closely matches the real behavior of the battery. When the battery system is exposed to a 5-min price signal, the energy arbitrage profitability improves by 60% compared to that from hourly price exposure. These results indicate that a more accurate representation of li-ion batteries as well as the market rules that govern the frequency of electricity prices can play a major role on the estimation of the value of battery technologies for power grid applications.
Discrete series representations for sl(2|1), Meixner polynomials and oscillator models
International Nuclear Information System (INIS)
Jafarov, E I; Van der Jeugt, J
2012-01-01
We explore a model for a one-dimensional quantum oscillator based on the Lie superalgebra sl(2|1). For this purpose, a class of discrete series representations of sl(2|1) is constructed, each representation characterized by a real number β > 0. In this model, the position and momentum operators of the oscillator are odd elements of sl(2|1) and their expressions involve an arbitrary parameter γ. In each representation, the spectrum of the Hamiltonian is the same as that of a canonical oscillator. The spectrum of a position operator can be continuous or infinite discrete, depending on the value of γ. We determine the position wavefunctions both in the continuous and the discrete case and discuss their properties. In the discrete case, these wavefunctions are given in terms of Meixner polynomials. From the embedding osp(1|2) subset of sl(2|1), it can be seen why the case γ = 1 corresponds to a paraboson oscillator. Consequently, taking the values (β, γ) = (1/2, 1) in the sl(2|1) model yields a canonical oscillator. (paper)
Ho, Yuh-Shan
2006-01-01
A comparison was made of the linear least-squares method and a trial-and-error non-linear method of the widely used pseudo-second-order kinetic model for the sorption of cadmium onto ground-up tree fern. Four pseudo-second-order kinetic linear equations are discussed. Kinetic parameters obtained from the four kinetic linear equations using the linear method differed but they were the same when using the non-linear method. A type 1 pseudo-second-order linear kinetic model has the highest coefficient of determination. Results show that the non-linear method may be a better way to obtain the desired parameters.
Casellas, J; Bach, R
2012-06-01
Lambing interval is a relevant reproductive indicator for sheep populations under continuous mating systems, although there is a shortage of selection programs accounting for this trait in the sheep industry. Both the historical assumption of small genetic background and its unorthodox distribution pattern have limited its implementation as a breeding objective. In this manuscript, statistical performances of 3 alternative parametrizations [i.e., symmetric Gaussian mixed linear (GML) model, skew-Gaussian mixed linear (SGML) model, and piecewise Weibull proportional hazard (PWPH) model] have been compared to elucidate the preferred methodology to handle lambing interval data. More specifically, flock-by-flock analyses were performed on 31,986 lambing interval records (257.3 ± 0.2 d) from 6 purebred Ripollesa flocks. Model performances were compared in terms of deviance information criterion (DIC) and Bayes factor (BF). For all flocks, PWPH models were clearly preferred; they generated a reduction of 1,900 or more DIC units and provided BF estimates larger than 100 (i.e., PWPH models against linear models). These differences were reduced when comparing PWPH models with different number of change points for the baseline hazard function. In 4 flocks, only 2 change points were required to minimize the DIC, whereas 4 and 6 change points were needed for the 2 remaining flocks. These differences demonstrated a remarkable degree of heterogeneity across sheep flocks that must be properly accounted for in genetic evaluation models to avoid statistical biases and suboptimal genetic trends. Within this context, all 6 Ripollesa flocks revealed substantial genetic background for lambing interval with heritabilities ranging between 0.13 and 0.19. This study provides the first evidence of the suitability of PWPH models for lambing interval analysis, clearly discarding previous parametrizations focused on mixed linear models.
A neural network model of semantic memory linking feature-based object representation and words.
Cuppini, C; Magosso, E; Ursino, M
2009-06-01
Recent theories in cognitive neuroscience suggest that semantic memory is a distributed process, which involves many cortical areas and is based on a multimodal representation of objects. The aim of this work is to extend a previous model of object representation to realize a semantic memory, in which sensory-motor representations of objects are linked with words. The model assumes that each object is described as a collection of features, coded in different cortical areas via a topological organization. Features in different objects are segmented via gamma-band synchronization of neural oscillators. The feature areas are further connected with a lexical area, devoted to the representation of words. Synapses among the feature areas, and among the lexical area and the feature areas are trained via a time-dependent Hebbian rule, during a period in which individual objects are presented together with the corresponding words. Simulation results demonstrate that, during the retrieval phase, the network can deal with the simultaneous presence of objects (from sensory-motor inputs) and words (from acoustic inputs), can correctly associate objects with words and segment objects even in the presence of incomplete information. Moreover, the network can realize some semantic links among words representing objects with shared features. These results support the idea that semantic memory can be described as an integrated process, whose content is retrieved by the co-activation of different multimodal regions. In perspective, extended versions of this model may be used to test conceptual theories, and to provide a quantitative assessment of existing data (for instance concerning patients with neural deficits).
Behavioral and macro modeling using piecewise linear techniques
Kruiskamp, M.W.; Leenaerts, D.M.W.; Antao, B.
1998-01-01
In this paper we will demonstrate that most digital, analog as well as behavioral components can be described using piecewise linear approximations of their real behavior. This leads to several advantages from the viewpoint of simulation. We will also give a method to store the resulting linear
Simultaneous Balancing and Model Reduction of Switched Linear Systems
Monshizadeh, Nima; Trentelman, Hendrikus; Camlibel, M.K.
2011-01-01
In this paper, first, balanced truncation of linear systems is revisited. Then, simultaneous balancing of multiple linear systems is investigated. Necessary and sufficient conditions are introduced to identify the case where simultaneous balancing is possible. The validity of these conditions is not
Genomic prediction based on data from three layer lines using non-linear regression models.
Huang, Heyun; Windig, Jack J; Vereijken, Addie; Calus, Mario P L
2014-11-06
Most studies on genomic prediction with reference populations that include multiple lines or breeds have used linear models. Data heterogeneity due to using multiple populations may conflict with model assumptions used in linear regression methods. In an attempt to alleviate potential discrepancies between assumptions of linear models and multi-population data, two types of alternative models were used: (1) a multi-trait genomic best linear unbiased prediction (GBLUP) model that modelled trait by line combinations as separate but correlated traits and (2) non-linear models based on kernel learning. These models were compared to conventional linear models for genomic prediction for two lines of brown layer hens (B1 and B2) and one line of white hens (W1). The three lines each had 1004 to 1023 training and 238 to 240 validation animals. Prediction accuracy was evaluated by estimating the correlation between observed phenotypes and predicted breeding values. When the training dataset included only data from the evaluated line, non-linear models yielded at best a similar accuracy as linear models. In some cases, when adding a distantly related line, the linear models showed a slight decrease in performance, while non-linear models generally showed no change in accuracy. When only information from a closely related line was used for training, linear models and non-linear radial basis function (RBF) kernel models performed similarly. The multi-trait GBLUP model took advantage of the estimated genetic correlations between the lines. Combining linear and non-linear models improved the accuracy of multi-line genomic prediction. Linear models and non-linear RBF models performed very similarly for genomic prediction, despite the expectation that non-linear models could deal better with the heterogeneous multi-population data. This heterogeneity of the data can be overcome by modelling trait by line combinations as separate but correlated traits, which avoids the occasional
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...