Parzen, Emanuel
1962-01-01
Well-written and accessible, this classic introduction to stochastic processes and related mathematics is appropriate for advanced undergraduate students of mathematics with a knowledge of calculus and continuous probability theory. The treatment offers examples of the wide variety of empirical phenomena for which stochastic processes provide mathematical models, and it develops the methods of probability model-building.Chapter 1 presents precise definitions of the notions of a random variable and a stochastic process and introduces the Wiener and Poisson processes. Subsequent chapters examine
Borodin, Andrei N
2017-01-01
This book provides a rigorous yet accessible introduction to the theory of stochastic processes. A significant part of the book is devoted to the classic theory of stochastic processes. In turn, it also presents proofs of well-known results, sometimes together with new approaches. Moreover, the book explores topics not previously covered elsewhere, such as distributions of functionals of diffusions stopped at different random times, the Brownian local time, diffusions with jumps, and an invariance principle for random walks and local times. Supported by carefully selected material, the book showcases a wealth of examples that demonstrate how to solve concrete problems by applying theoretical results. It addresses a broad range of applications, focusing on concrete computational techniques rather than on abstract theory. The content presented here is largely self-contained, making it suitable for researchers and graduate students alike.
Stochastic and deterministic processes regulate spatio-temporal variation in seed bank diversity
Alejandro A. Royo; Todd E. Ristau
2013-01-01
Seed banks often serve as reservoirs of taxonomic and genetic diversity that buffer plant populations and influence post-disturbance vegetation trajectories; yet evaluating their importance requires understanding how their composition varies within and across spatial and temporal scales (α- and β-diversity). Shifts in seed bank diversity are strongly...
Stochastic processes inference theory
Rao, Malempati M
2014-01-01
This is the revised and enlarged 2nd edition of the authors’ original text, which was intended to be a modest complement to Grenander's fundamental memoir on stochastic processes and related inference theory. The present volume gives a substantial account of regression analysis, both for stochastic processes and measures, and includes recent material on Ridge regression with some unexpected applications, for example in econometrics. The first three chapters can be used for a quarter or semester graduate course on inference on stochastic processes. The remaining chapters provide more advanced material on stochastic analysis suitable for graduate seminars and discussions, leading to dissertation or research work. In general, the book will be of interest to researchers in probability theory, mathematical statistics and electrical and information theory.
Composite stochastic processes
Kampen, N.G. van
Certain problems in physics and chemistry lead to the definition of a class of stochastic processes. Although they are not Markovian they can be treated explicitly to some extent. In particular, the probability distribution for large times can be found. It is shown to obey a master equation. This
Research in Stochastic Processes.
1982-10-31
Office of Scientific Research Grant AFOSR F49620 82 C 0009 Period: 1 Noveber 1981 through 31 October 1982 Title: Research in Stochastic Processes Co...STA4ATIS CAMBANIS The work briefly described here was developed in connection with problems arising from and related to the statistical comunication
Essentials of stochastic processes
Durrett, Richard
2016-01-01
Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students (MS and PhD students from math, statistics, economics, computer science, engineering, and finance departments) who have had a course in probability theory. It covers Markov chains in discrete and continuous time, Poisson processes, renewal processes, martingales, and option pricing. One can only learn a subject by seeing it in action, so there are a large number of examples and more than 300 carefully chosen exercises to deepen the reader’s understanding. Drawing from teaching experience and student feedback, there are many new examples and problems with solutions that use TI-83 to eliminate the tedious details of solving linear equations by hand, and the collection of exercises is much improved, with many more biological examples. Originally included in previous editions, material too advanced for this first course in stochastic processes has been eliminated while treatm...
Stochastic conditional intensity processes
DEFF Research Database (Denmark)
Bauwens, Luc; Hautsch, Nikolaus
2006-01-01
model allows for a wide range of (cross-)autocorrelation structures in multivariate point processes. The model is estimated by simulated maximum likelihood (SML) using the efficient importance sampling (EIS) technique. By modeling price intensities based on NYSE trading, we provide significant evidence......In this article, we introduce the so-called stochastic conditional intensity (SCI) model by extending Russell’s (1999) autoregressive conditional intensity (ACI) model by a latent common dynamic factor that jointly drives the individual intensity components. We show by simulations that the proposed...... for a joint latent factor and show that its inclusion allows for an improved and more parsimonious specification of the multivariate intensity process...
Stochastic processes in cell biology
Bressloff, Paul C
2014-01-01
This book develops the theory of continuous and discrete stochastic processes within the context of cell biology. A wide range of biological topics are covered including normal and anomalous diffusion in complex cellular environments, stochastic ion channels and excitable systems, stochastic calcium signaling, molecular motors, intracellular transport, signal transduction, bacterial chemotaxis, robustness in gene networks, genetic switches and oscillators, cell polarization, polymerization, cellular length control, and branching processes. The book also provides a pedagogical introduction to the theory of stochastic process – Fokker Planck equations, stochastic differential equations, master equations and jump Markov processes, diffusion approximations and the system size expansion, first passage time problems, stochastic hybrid systems, reaction-diffusion equations, exclusion processes, WKB methods, martingales and branching processes, stochastic calculus, and numerical methods. This text is primarily...
Stochastic processes and quantum theory
International Nuclear Information System (INIS)
Klauder, J.R.
1975-01-01
The author analyses a variety of stochastic processes, namely real time diffusion phenomena, which are analogues of imaginary time quantum theory and convariant imaginary time quantum field theory. He elaborates some standard properties involving probability measures and stochastic variables and considers a simple class of examples. Finally he develops the fact that certain stochastic theories actually exhibit divergences that simulate those of covariant quantum field theory and presents examples of both renormaizable and unrenormalizable behavior. (V.J.C.)
An introduction to probability and stochastic processes
Melsa, James L
2013-01-01
Geared toward college seniors and first-year graduate students, this text is designed for a one-semester course in probability and stochastic processes. Topics covered in detail include probability theory, random variables and their functions, stochastic processes, linear system response to stochastic processes, Gaussian and Markov processes, and stochastic differential equations. 1973 edition.
Applied probability and stochastic processes
Sumita, Ushio
1999-01-01
Applied Probability and Stochastic Processes is an edited work written in honor of Julien Keilson. This volume has attracted a host of scholars in applied probability, who have made major contributions to the field, and have written survey and state-of-the-art papers on a variety of applied probability topics, including, but not limited to: perturbation method, time reversible Markov chains, Poisson processes, Brownian techniques, Bayesian probability, optimal quality control, Markov decision processes, random matrices, queueing theory and a variety of applications of stochastic processes. The book has a mixture of theoretical, algorithmic, and application chapters providing examples of the cutting-edge work that Professor Keilson has done or influenced over the course of his highly-productive and energetic career in applied probability and stochastic processes. The book will be of interest to academic researchers, students, and industrial practitioners who seek to use the mathematics of applied probability i...
Probability, Statistics, and Stochastic Processes
Olofsson, Peter
2011-01-01
A mathematical and intuitive approach to probability, statistics, and stochastic processes This textbook provides a unique, balanced approach to probability, statistics, and stochastic processes. Readers gain a solid foundation in all three fields that serves as a stepping stone to more advanced investigations into each area. This text combines a rigorous, calculus-based development of theory with a more intuitive approach that appeals to readers' sense of reason and logic, an approach developed through the author's many years of classroom experience. The text begins with three chapters that d
The dynamics of stochastic processes
DEFF Research Database (Denmark)
Basse-O'Connor, Andreas
In the present thesis the dynamics of stochastic processes is studied with a special attention to the semimartingale property. This is mainly motivated by the fact that semimartingales provide the class of the processes for which it is possible to define a reasonable stochastic calculus due...... to the Bichteler-Dellacherie Theorem. The semimartingale property of Gaussian processes is characterized in terms of their covariance function, spectral measure and spectral representation. In addition, representation and expansion of filtration results are provided as well. Special attention is given to moving...... average processes, and when the driving process is a Lévy or a chaos process the semimartingale property is characterized in the filtration spanned by the driving process and in the natural filtration when the latter is a Brownian motion. To obtain some of the above results an integrability of seminorm...
Distance covariance for stochastic processes
DEFF Research Database (Denmark)
Matsui, Muneya; Mikosch, Thomas Valentin; Samorodnitsky, Gennady
2017-01-01
The distance covariance of two random vectors is a measure of their dependence. The empirical distance covariance and correlation can be used as statistical tools for testing whether two random vectors are independent. We propose an analog of the distance covariance for two stochastic processes...
Fourier analysis and stochastic processes
Brémaud, Pierre
2014-01-01
This work is unique as it provides a uniform treatment of the Fourier theories of functions (Fourier transforms and series, z-transforms), finite measures (characteristic functions, convergence in distribution), and stochastic processes (including arma series and point processes). It emphasises the links between these three themes. The chapter on the Fourier theory of point processes and signals structured by point processes is a novel addition to the literature on Fourier analysis of stochastic processes. It also connects the theory with recent lines of research such as biological spike signals and ultrawide-band communications. Although the treatment is mathematically rigorous, the convivial style makes the book accessible to a large audience. In particular, it will be interesting to anyone working in electrical engineering and communications, biology (point process signals) and econometrics (arma models). A careful review of the prerequisites (integration and probability theory in the appendix, Hilbert spa...
Introduction to stochastic processes
Cinlar, Erhan
2013-01-01
Clear presentation employs methods that recognize computer-related aspects of theory. Topics include expectations and independence, Bernoulli processes and sums of independent random variables, Markov chains, renewal theory, more. 1975 edition.
Dynamical and hamiltonian dilations of stochastic processes
International Nuclear Information System (INIS)
Baumgartner, B.; Gruemm, H.-R.
1982-01-01
This is a study of the problem, which stochastic processes could arise from dynamical systems by loss of information. The notions of ''dilation'' and ''approximate dilation'' of a stochastic process are introduced to give exact definitions of this particular relationship. It is shown that every generalized stochastic process is approximately dilatable by a sequence of dynamical systems, but for stochastic processes in full generality one needs nets. (Author)
Stochastic processes and filtering theory
Jazwinski, Andrew H
1970-01-01
This unified treatment of linear and nonlinear filtering theory presents material previously available only in journals, and in terms accessible to engineering students. Its sole prerequisites are advanced calculus, the theory of ordinary differential equations, and matrix analysis. Although theory is emphasized, the text discusses numerous practical applications as well.Taking the state-space approach to filtering, this text models dynamical systems by finite-dimensional Markov processes, outputs of stochastic difference, and differential equations. Starting with background material on probab
Verification of Stochastic Process Calculi
DEFF Research Database (Denmark)
Skrypnyuk, Nataliya
algorithms for constructing bisimulation relations, computing (overapproximations of) sets of reachable states and computing the expected time reachability, the last for a linear fragment of IMC. In all the cases we have the complexities of algorithms which are low polynomial in the size of the syntactic....... In support of this claim we have developed analysis methods that belong to a particular type of Static Analysis { Data Flow / Pathway Analysis. These methods have previously been applied to a number of non-stochastic process calculi. In this thesis we are lifting them to the stochastic calculus...... of Interactive Markov Chains (IMC). We have devised the Pathway Analysis of IMC that is not only correct in the sense of overapproximating all possible behaviour scenarios, as is usual for Static Analysis methods, but is also precise. This gives us the possibility to explicitly decide on the trade-o between...
Stochastic processes, slaves and supersymmetry
International Nuclear Information System (INIS)
Drummond, I T; Horgan, R R
2012-01-01
We extend the work of Tănase-Nicola and Kurchan on the structure of diffusion processes and the associated supersymmetry algebra by examining the responses of a simple statistical system to external disturbances of various kinds. We consider both the stochastic differential equations (SDEs) for the process and the associated diffusion equation. The influence of the disturbances can be understood by augmenting the original SDE with an equation for slave variables. The evolution of the slave variables describes the behaviour of line elements carried along in the stochastic flow. These line elements, together with the associated surface and volume elements constructed from them, provide the basis of the supersymmetry properties of the theory. For ease of visualization, and in order to emphasize a helpful electromagnetic analogy, we work in three dimensions. The results are all generalizable to higher dimensions and can be specialized to one and two dimensions. The electromagnetic analogy is a useful starting point for calculating asymptotic results at low temperature that can be compared with direct numerical evaluations. We also examine the problems that arise in a direct numerical simulation of the stochastic equation together with the slave equations. We pay special attention to the dependence of the slave variable statistics on temperature. We identify in specific models the critical temperature below which the slave variable distribution ceases to have a variance and consider the effect on estimates of susceptibilities. (paper)
Mathematical statistics and stochastic processes
Bosq, Denis
2013-01-01
Generally, books on mathematical statistics are restricted to the case of independent identically distributed random variables. In this book however, both this case AND the case of dependent variables, i.e. statistics for discrete and continuous time processes, are studied. This second case is very important for today's practitioners.Mathematical Statistics and Stochastic Processes is based on decision theory and asymptotic statistics and contains up-to-date information on the relevant topics of theory of probability, estimation, confidence intervals, non-parametric statistics and rob
Probability, Statistics, and Stochastic Processes
Olofsson, Peter
2012-01-01
This book provides a unique and balanced approach to probability, statistics, and stochastic processes. Readers gain a solid foundation in all three fields that serves as a stepping stone to more advanced investigations into each area. The Second Edition features new coverage of analysis of variance (ANOVA), consistency and efficiency of estimators, asymptotic theory for maximum likelihood estimators, empirical distribution function and the Kolmogorov-Smirnov test, general linear models, multiple comparisons, Markov chain Monte Carlo (MCMC), Brownian motion, martingales, and
Ambit processes and stochastic partial differential equations
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole; Benth, Fred Espen; Veraart, Almut
Ambit processes are general stochastic processes based on stochastic integrals with respect to Lévy bases. Due to their flexible structure, they have great potential for providing realistic models for various applications such as in turbulence and finance. This papers studies the connection betwe...... ambit processes and solutions to stochastic partial differential equations. We investigate this relationship from two angles: from the Walsh theory of martingale measures and from the viewpoint of the Lévy noise analysis....
Discrete stochastic processes and applications
Collet, Jean-François
2018-01-01
This unique text for beginning graduate students gives a self-contained introduction to the mathematical properties of stochastics and presents their applications to Markov processes, coding theory, population dynamics, and search engine design. The book is ideal for a newly designed course in an introduction to probability and information theory. Prerequisites include working knowledge of linear algebra, calculus, and probability theory. The first part of the text focuses on the rigorous theory of Markov processes on countable spaces (Markov chains) and provides the basis to developing solid probabilistic intuition without the need for a course in measure theory. The approach taken is gradual beginning with the case of discrete time and moving on to that of continuous time. The second part of this text is more applied; its core introduces various uses of convexity in probability and presents a nice treatment of entropy.
Statistical inference for stochastic processes
National Research Council Canada - National Science Library
Basawa, Ishwar V; Prakasa Rao, B. L. S
1980-01-01
The aim of this monograph is to attempt to reduce the gap between theory and applications in the area of stochastic modelling, by directing the interest of future researchers to the inference aspects...
Space-time-modulated stochastic processes
Giona, Massimiliano
2017-10-01
Starting from the physical problem associated with the Lorentzian transformation of a Poisson-Kac process in inertial frames, the concept of space-time-modulated stochastic processes is introduced for processes possessing finite propagation velocity. This class of stochastic processes provides a two-way coupling between the stochastic perturbation acting on a physical observable and the evolution of the physical observable itself, which in turn influences the statistical properties of the stochastic perturbation during its evolution. The definition of space-time-modulated processes requires the introduction of two functions: a nonlinear amplitude modulation, controlling the intensity of the stochastic perturbation, and a time-horizon function, which modulates its statistical properties, providing irreducible feedback between the stochastic perturbation and the physical observable influenced by it. The latter property is the peculiar fingerprint of this class of models that makes them suitable for extension to generic curved-space times. Considering Poisson-Kac processes as prototypical examples of stochastic processes possessing finite propagation velocity, the balance equations for the probability density functions associated with their space-time modulations are derived. Several examples highlighting the peculiarities of space-time-modulated processes are thoroughly analyzed.
International Nuclear Information System (INIS)
Biteau, J.
2013-01-01
Fifty years after the discovery that quasars are extragalactic sources, their bright cores (AGN) and the jets that some of them exhibit still have plenty of secrets to share, particularly through observations in the gamma-ray band. Above 100 GeV, Cherenkov telescopes such as H.E.S.S. have detected 50 AGN, mostly blazars, objects whose jets are pointed toward the observer. The detection of two faint ones, 1ES 1312-423 and SHBL J001355.9-185406, is described in this thesis. Their multiwavelength spectra are reproduced with a synchrotron self-Compton model. The γ rays emitted by blazars are partly absorbed by the extragalactic background light (EBL), the second most intense cosmological background, which carries the integrated history of star formation. The first detection of this absorption above 100 GeV is performed, enabling the measurement of the EBL peak-amplitude in the optical band at the 20% level. In addition to these spectral studies, the fast flux-variations of blazars are investigated using the outbursts of PKS 2155-304 seen by H.E.S.S.. The observation of a skewed flux distribution and of an R.M.S.-flux correlation are interpreted within a kinematic model, where the emission is a realization of a stochastic process. (author)
Soil Erosion as a stochastic process
Casper, Markus C.
2015-04-01
corrected experimentally. To overcome this disadvantage of our actual models, soil erosion models are needed that are able to use stochastic directly variables and parameter distributions. There are only some minor approaches in this direction. The most advanced is the model "STOSEM" proposed by Sidorchuk in 2005. In this model, only a small part of the soil erosion processes is described, the aggregate detachment and the aggregate transport by flowing water. The concept is highly simplified, for example, many parameters are temporally invariant. Nevertheless, the main problem is that our existing measurements and experiments are not geared to provide stochastic parameters (e.g. as probability density functions); in the best case they deliver a statistical validation of the mean values. Again, we get effective parameters, spatially and temporally averaged. There is an urgent need for laboratory and field experiments on overland flow structure, raindrop effects and erosion rate, which deliver information on spatial and temporal structure of soil and surface properties and processes.
Stochastic differential equation model to Prendiville processes
Energy Technology Data Exchange (ETDEWEB)
Granita, E-mail: granitafc@gmail.com [Dept. of Mathematical Science, Universiti Teknologi Malaysia, 81310, Johor Malaysia (Malaysia); Bahar, Arifah [Dept. of Mathematical Science, Universiti Teknologi Malaysia, 81310, Johor Malaysia (Malaysia); UTM Center for Industrial & Applied Mathematics (UTM-CIAM) (Malaysia)
2015-10-22
The Prendiville process is another variation of the logistic model which assumes linearly decreasing population growth rate. It is a continuous time Markov chain (CTMC) taking integer values in the finite interval. The continuous time Markov chain can be approximated by stochastic differential equation (SDE). This paper discusses the stochastic differential equation of Prendiville process. The work started with the forward Kolmogorov equation in continuous time Markov chain of Prendiville process. Then it was formulated in the form of a central-difference approximation. The approximation was then used in Fokker-Planck equation in relation to the stochastic differential equation of the Prendiville process. The explicit solution of the Prendiville process was obtained from the stochastic differential equation. Therefore, the mean and variance function of the Prendiville process could be easily found from the explicit solution.
Stochastic differential equation model to Prendiville processes
International Nuclear Information System (INIS)
Granita; Bahar, Arifah
2015-01-01
The Prendiville process is another variation of the logistic model which assumes linearly decreasing population growth rate. It is a continuous time Markov chain (CTMC) taking integer values in the finite interval. The continuous time Markov chain can be approximated by stochastic differential equation (SDE). This paper discusses the stochastic differential equation of Prendiville process. The work started with the forward Kolmogorov equation in continuous time Markov chain of Prendiville process. Then it was formulated in the form of a central-difference approximation. The approximation was then used in Fokker-Planck equation in relation to the stochastic differential equation of the Prendiville process. The explicit solution of the Prendiville process was obtained from the stochastic differential equation. Therefore, the mean and variance function of the Prendiville process could be easily found from the explicit solution
Modelling and application of stochastic processes
1986-01-01
The subject of modelling and application of stochastic processes is too vast to be exhausted in a single volume. In this book, attention is focused on a small subset of this vast subject. The primary emphasis is on realization and approximation of stochastic systems. Recently there has been considerable interest in the stochastic realization problem, and hence, an attempt has been made here to collect in one place some of the more recent approaches and algorithms for solving the stochastic realiza tion problem. Various different approaches for realizing linear minimum-phase systems, linear nonminimum-phase systems, and bilinear systems are presented. These approaches range from time-domain methods to spectral-domain methods. An overview of the chapter contents briefly describes these approaches. Also, in most of these chapters special attention is given to the problem of developing numerically ef ficient algorithms for obtaining reduced-order (approximate) stochastic realizations. On the application side,...
Stochastic Processes in Epidemic Theory
Lefèvre, Claude; Picard, Philippe
1990-01-01
This collection of papers gives a representative cross-selectional view of recent developments in the field. After a survey paper by C. Lefèvre, 17 other research papers look at stochastic modeling of epidemics, both from a theoretical and a statistical point of view. Some look more specifically at a particular disease such as AIDS, malaria, schistosomiasis and diabetes.
Stochastic processes in mechanical engineering
Brouwers, J.J.H.
2006-01-01
Stochastic or random vibrations occur in a variety of applications of mechanicalengineering. Examples are: the dynamics of a vehicle on an irregular roadsurface; the variation in time of thermodynamic variables in municipal wasteincinerators due to fluctuations in heating value of the waste; the
Towards Model Checking Stochastic Process Algebra
Hermanns, H.; Grieskamp, W.; Santen, T.; Katoen, Joost P.; Stoddart, B.; Meyer-Kayser, J.; Siegle, M.
2000-01-01
Stochastic process algebras have been proven useful because they allow behaviour-oriented performance and reliability modelling. As opposed to traditional performance modelling techniques, the behaviour- oriented style supports composition and abstraction in a natural way. However, analysis of
Selected papers on noise and stochastic processes
1954-01-01
Six classic papers on stochastic process, selected to meet the needs of physicists, applied mathematicians, and engineers. Contents: 1.Chandrasekhar, S.: Stochastic Problems in Physics and Astronomy. 2. Uhlenbeck, G. E. and Ornstein, L. S.: On the Theory of the Browninan Motion. 3. Ming Chen Wang and Uhlenbeck, G. E.: On the Theory of the Browninan Motion II. 4. Rice, S. O.: Mathematical Analysis of Random Noise. 5. Kac, Mark: Random Walk and the Theory of Brownian Motion. 6. Doob, J. L.: The Brownian Movement and Stochastic Equations. Unabridged republication of the Dover reprint (1954). Pre
Joint effects of habitat configuration and temporal stochasticity on population dynamics
Jennifer M. Fraterrigo; Scott M. Pearson; Monica G. Turner
2009-01-01
Habitat configuration and temporal stochasticity in the environment are recognized as important drivers of population structure, yet few studies have examined the combined influence of these factors....
Is human failure a stochastic process?
International Nuclear Information System (INIS)
Dougherty, Ed M.
1997-01-01
Human performance results in failure events that occur with a risk-significant frequency. System analysts have taken for granted the random (stochastic) nature of these events in engineering assessments such as risk assessment. However, cognitive scientists and error technologists, at least those who have interest in human reliability, have, over the recent years, claimed that human error does not need this stochastic framework. Yet they still use the language appropriate to stochastic processes. This paper examines the potential for the stochastic nature of human failure production as the basis for human reliability analysis. It distinguishes and leaves to others, however, the epistemic uncertainties over the possible probability models for the real variability of human performance
Lectures on Topics in Spatial Stochastic Processes
Capasso, Vincenzo; Ivanoff, B Gail; Dozzi, Marco; Dalang, Robert C; Mountford, Thomas S
2003-01-01
The theory of stochastic processes indexed by a partially ordered set has been the subject of much research over the past twenty years. The objective of this CIME International Summer School was to bring to a large audience of young probabilists the general theory of spatial processes, including the theory of set-indexed martingales and to present the different branches of applications of this theory, including stochastic geometry, spatial statistics, empirical processes, spatial estimators and survival analysis. This theory has a broad variety of applications in environmental sciences, social sciences, structure of material and image analysis. In this volume, the reader will find different approaches which foster the development of tools to modelling the spatial aspects of stochastic problems.
Computer Aided Continuous Time Stochastic Process Modelling
DEFF Research Database (Denmark)
Kristensen, N.R.; Madsen, Henrik; Jørgensen, Sten Bay
2001-01-01
A grey-box approach to process modelling that combines deterministic and stochastic modelling is advocated for identification of models for model-based control of batch and semi-batch processes. A computer-aided tool designed for supporting decision-making within the corresponding modelling cycle...
Topological superposition of abstractions of stochastic processes
Bujorianu, L.M.; Bujorianu, M.C.
2008-01-01
In this paper, we present a sound integration mechanism for Markov processes that are abstractions of stochastic hybrid systems (SHS). In a previous work, we have defined a very general model of SHS and we proved that the realization of an SHS is a Markov process. Moreover, we have developed a
Quantization by stochastic relaxation processes and supersymmetry
International Nuclear Information System (INIS)
Kirschner, R.
1984-01-01
We show the supersymmetry mechanism resposible for the quantization by stochastic relaxation processes and for the effective cancellation of the additional time dimension against the two Grassmann dimensions. We give a non-perturbative proof of the validity of this quantization procedure. (author)
ON REGRESSION REPRESENTATIONS OF STOCHASTIC-PROCESSES
RUSCHENDORF, L; DEVALK, [No Value
We construct a.s. nonlinear regression representations of general stochastic processes (X(n))n is-an-element-of N. As a consequence we obtain in particular special regression representations of Markov chains and of certain m-dependent sequences. For m-dependent sequences we obtain a constructive
Stochastic transport processes in discrete biological systems
Frehland, Eckart
1982-01-01
These notes are in part based on a course for advanced students in the applications of stochastic processes held in 1978 at the University of Konstanz. These notes contain the results of re cent studies on the stochastic description of ion transport through biological membranes. In particular, they serve as an introduction to an unified theory of fluctuations in complex biological transport systems. We emphasize that the subject of this volume is not to introduce the mathematics of stochastic processes but to present a field of theoretical biophysics in which stochastic methods are important. In the last years the study of membrane noise has become an important method in biophysics. Valuable information on the ion transport mechanisms in membranes can be obtained from noise analysis. A number of different processes such as the opening and closing of ion channels have been shown to be sources of the measured current or voltage fluctuations. Bio logical 'transport systems can be complex. For example, the tr...
Stationary stochastic processes theory and applications
Lindgren, Georg
2012-01-01
Some Probability and Process BackgroundSample space, sample function, and observablesRandom variables and stochastic processesStationary processes and fieldsGaussian processesFour historical landmarksSample Function PropertiesQuadratic mean propertiesSample function continuityDerivatives, tangents, and other characteristicsStochastic integrationAn ergodic resultExercisesSpectral RepresentationsComplex-valued stochastic processesBochner's theorem and the spectral distributionSpectral representation of a stationary processGaussian processesStationary counting processesExercisesLinear Filters - General PropertiesLinear time invariant filtersLinear filters and differential equationsWhite noise in linear systemsLong range dependence, non-integrable spectra, and unstable systemsThe ARMA-familyLinear Filters - Special TopicsThe Hilbert transform and the envelopeThe sampling theoremKarhunen-Loève expansionClassical Ergodic Theory and MixingThe basic ergodic theorem in L2Stationarity and transformationsThe ergodic th...
Probability of stochastic processes and spacetime geometry
International Nuclear Information System (INIS)
Canessa, E.
2007-01-01
We made a first attempt to associate a probabilistic description of stochastic processes like birth-death processes with spacetime geometry in the Schwarzschild metrics on distance scales from the macro- to the micro-domains. We idealize an ergodic system in which system states communicate through a curved path composed of transition arrows where each arrow corresponds to a positive, analogous birth or death rate. (author)
Stochastic Processes in Finance and Behavioral Finance
Steinbacher, Matjaz
2008-01-01
In the paper, we put some foundations for studying asset pricing and finance as a stochastic and behavioral process. In such process, preferences and psychology of agents represent the most important factor in the decision-making of people. Individuals have their own ways of acquiring the information they need, how to deal with them and how to make predictions and decisions. People usually also do not behave consistent in time, but learn. Therefore, in order to understand the behavior on the ...
Periodic linear differential stochastic processes
Kwakernaak, H.
1975-01-01
Periodic linear differential processes are defined and their properties are analyzed. Equivalent representations are discussed, and the solutions of related optimal estimation problems are given. An extension is presented of Kailath and Geesey’s [1] results concerning the innovations representation
Large scale stochastic spatio-temporal modelling with PCRaster
Karssenberg, D.J.; Drost, N.; Schmitz, O.; Jong, K. de; Bierkens, M.F.P.
2013-01-01
PCRaster is a software framework for building spatio-temporal models of land surface processes (http://www.pcraster.eu). Building blocks of models are spatial operations on raster maps, including a large suite of operations for water and sediment routing. These operations are available to model
Irreversible stochastic processes on lattices
International Nuclear Information System (INIS)
Nord, R.S.
1986-01-01
Models for irreversible random or cooperative filling of lattices are required to describe many processes in chemistry and physics. Since the filling is assumed to be irreversible, even the stationary, saturation state is not in equilibrium. The kinetics and statistics of these processes are described by recasting the master equations in infinite hierarchical form. Solutions can be obtained by implementing various techniques: refinements in these solution techniques are presented. Programs considered include random dimer, trimer, and tetramer filling of 2D lattices, random dimer filling of a cubic lattice, competitive filling of two or more species, and the effect of a random distribution of inactive sites on the filling. Also considered is monomer filling of a linear lattice with nearest neighbor cooperative effects and solve for the exact cluster-size distribution for cluster sizes up to the asymptotic regime. Additionally, a technique is developed to directly determine the asymptotic properties of the cluster size distribution. Finally cluster growth is considered via irreversible aggregation involving random walkers. In particular, explicit results are provided for the large-lattice-size asymptotic behavior of trapping probabilities and average walk lengths for a single walker on a lattice with multiple traps. Procedures for exact calculation of these quantities on finite lattices are also developed
Stochastic Simulation of Process Calculi for Biology
Directory of Open Access Journals (Sweden)
Andrew Phillips
2010-10-01
Full Text Available Biological systems typically involve large numbers of components with complex, highly parallel interactions and intrinsic stochasticity. To model this complexity, numerous programming languages based on process calculi have been developed, many of which are expressive enough to generate unbounded numbers of molecular species and reactions. As a result of this expressiveness, such calculi cannot rely on standard reaction-based simulation methods, which require fixed numbers of species and reactions. Rather than implementing custom stochastic simulation algorithms for each process calculus, we propose to use a generic abstract machine that can be instantiated to a range of process calculi and a range of reaction-based simulation algorithms. The abstract machine functions as a just-in-time compiler, which dynamically updates the set of possible reactions and chooses the next reaction in an iterative cycle. In this short paper we give a brief summary of the generic abstract machine, and show how it can be instantiated with the stochastic simulation algorithm known as Gillespie's Direct Method. We also discuss the wider implications of such an abstract machine, and outline how it can be used to simulate multiple calculi simultaneously within a common framework.
Modeling nanoparticle uptake and intracellular distribution using stochastic process algebras
Energy Technology Data Exchange (ETDEWEB)
Dobay, M. P. D., E-mail: maria.pamela.david@physik.uni-muenchen.de; Alberola, A. Piera; Mendoza, E. R.; Raedler, J. O., E-mail: joachim.raedler@physik.uni-muenchen.de [Ludwig-Maximilians University, Faculty of Physics, Center for NanoScience (Germany)
2012-03-15
Computational modeling is increasingly important to help understand the interaction and movement of nanoparticles (NPs) within living cells, and to come to terms with the wealth of data that microscopy imaging yields. A quantitative description of the spatio-temporal distribution of NPs inside cells; however, it is challenging due to the complexity of multiple compartments such as endosomes and nuclei, which themselves are dynamic and can undergo fusion and fission and exchange their content. Here, we show that stochastic pi calculus, a widely-used process algebra, is well suited for mapping surface and intracellular NP interactions and distributions. In stochastic pi calculus, each NP is represented as a process, which can adopt various states such as bound or aggregated, as well as be passed between processes representing location, as a function of predefined stochastic channels. We created a pi calculus model of gold NP uptake and intracellular movement and compared the evolution of surface-bound, cytosolic, endosomal, and nuclear NP densities with electron microscopy data. We demonstrate that the computational approach can be extended to include specific molecular binding and potential interaction with signaling cascades as characteristic for NP-cell interactions in a wide range of applications such as nanotoxicity, viral infection, and drug delivery.
Modeling nanoparticle uptake and intracellular distribution using stochastic process algebras
International Nuclear Information System (INIS)
Dobay, M. P. D.; Alberola, A. Piera; Mendoza, E. R.; Rädler, J. O.
2012-01-01
Computational modeling is increasingly important to help understand the interaction and movement of nanoparticles (NPs) within living cells, and to come to terms with the wealth of data that microscopy imaging yields. A quantitative description of the spatio-temporal distribution of NPs inside cells; however, it is challenging due to the complexity of multiple compartments such as endosomes and nuclei, which themselves are dynamic and can undergo fusion and fission and exchange their content. Here, we show that stochastic pi calculus, a widely-used process algebra, is well suited for mapping surface and intracellular NP interactions and distributions. In stochastic pi calculus, each NP is represented as a process, which can adopt various states such as bound or aggregated, as well as be passed between processes representing location, as a function of predefined stochastic channels. We created a pi calculus model of gold NP uptake and intracellular movement and compared the evolution of surface-bound, cytosolic, endosomal, and nuclear NP densities with electron microscopy data. We demonstrate that the computational approach can be extended to include specific molecular binding and potential interaction with signaling cascades as characteristic for NP-cell interactions in a wide range of applications such as nanotoxicity, viral infection, and drug delivery.
Modeling nanoparticle uptake and intracellular distribution using stochastic process algebras
Dobay, M. P. D.; Alberola, A. Piera; Mendoza, E. R.; Rädler, J. O.
2012-03-01
Computational modeling is increasingly important to help understand the interaction and movement of nanoparticles (NPs) within living cells, and to come to terms with the wealth of data that microscopy imaging yields. A quantitative description of the spatio-temporal distribution of NPs inside cells; however, it is challenging due to the complexity of multiple compartments such as endosomes and nuclei, which themselves are dynamic and can undergo fusion and fission and exchange their content. Here, we show that stochastic pi calculus, a widely-used process algebra, is well suited for mapping surface and intracellular NP interactions and distributions. In stochastic pi calculus, each NP is represented as a process, which can adopt various states such as bound or aggregated, as well as be passed between processes representing location, as a function of predefined stochastic channels. We created a pi calculus model of gold NP uptake and intracellular movement and compared the evolution of surface-bound, cytosolic, endosomal, and nuclear NP densities with electron microscopy data. We demonstrate that the computational approach can be extended to include specific molecular binding and potential interaction with signaling cascades as characteristic for NP-cell interactions in a wide range of applications such as nanotoxicity, viral infection, and drug delivery.
Minimum uncertainty and squeezing in diffusion processes and stochastic quantization
Demartino, S.; Desiena, S.; Illuminati, Fabrizo; Vitiello, Giuseppe
1994-01-01
We show that uncertainty relations, as well as minimum uncertainty coherent and squeezed states, are structural properties for diffusion processes. Through Nelson stochastic quantization we derive the stochastic image of the quantum mechanical coherent and squeezed states.
Doubly stochastic Poisson processes in artificial neural learning.
Card, H C
1998-01-01
This paper investigates neuron activation statistics in artificial neural networks employing stochastic arithmetic. It is shown that a doubly stochastic Poisson process is an appropriate model for the signals in these circuits.
A first course in stochastic processes
Karlin, Samuel
1975-01-01
The purpose, level, and style of this new edition conform to the tenets set forth in the original preface. The authors continue with their tack of developing simultaneously theory and applications, intertwined so that they refurbish and elucidate each other.The authors have made three main kinds of changes. First, they have enlarged on the topics treated in the first edition. Second, they have added many exercises and problems at the end of each chapter. Third, and most important, they have supplied, in new chapters, broad introductory discussions of several classes of stochastic processe
Stationary stochastic processes for scientists and engineers
Lindgren, Georg; Sandsten, Maria
2013-01-01
""This book is designed for a first course in stationary stochastic processes in science and engineering and does a very good job in introducing many concepts and ideas to students in these fields. … the book has probably been tested in the classroom many times, which also manifests itself in its virtual lack of typos. … Another great feature of the book is that it contains a wealth of worked example from many different fields. These help clarify concepts and theorems and I believe students will appreciate them-I certainly did. … The book is well suited for a one-semester course as it contains
XI Symposium on Probability and Stochastic Processes
Pardo, Juan; Rivero, Víctor; Bravo, Gerónimo
2015-01-01
This volume features lecture notes and a collection of contributed articles from the XI Symposium on Probability and Stochastic Processes, held at CIMAT Mexico in September 2013. Since the symposium was part of the activities organized in Mexico to celebrate the International Year of Statistics, the program included topics from the interface between statistics and stochastic processes. The book starts with notes from the mini-course given by Louigi Addario-Berry with an accessible description of some features of the multiplicative coalescent and its connection with random graphs and minimum spanning trees. It includes a number of exercises and a section on unanswered questions. Further contributions provide the reader with a broad perspective on the state-of-the art of active areas of research. Contributions by: Louigi Addario-Berry Octavio Arizmendi Fabrice Baudoin Jochen Blath Loïc Chaumont J. Armando Domínguez-Molina Bjarki Eldon Shui Feng Tulio Gaxiola Adrián González Casanova Evgueni Gordienko Daniel...
Nonparametric estimation of stochastic differential equations with sparse Gaussian processes.
García, Constantino A; Otero, Abraham; Félix, Paulo; Presedo, Jesús; Márquez, David G
2017-08-01
The application of stochastic differential equations (SDEs) to the analysis of temporal data has attracted increasing attention, due to their ability to describe complex dynamics with physically interpretable equations. In this paper, we introduce a nonparametric method for estimating the drift and diffusion terms of SDEs from a densely observed discrete time series. The use of Gaussian processes as priors permits working directly in a function-space view and thus the inference takes place directly in this space. To cope with the computational complexity that requires the use of Gaussian processes, a sparse Gaussian process approximation is provided. This approximation permits the efficient computation of predictions for the drift and diffusion terms by using a distribution over a small subset of pseudosamples. The proposed method has been validated using both simulated data and real data from economy and paleoclimatology. The application of the method to real data demonstrates its ability to capture the behavior of complex systems.
Temporal auditory processing in elders
Directory of Open Access Journals (Sweden)
Azzolini, Vanuza Conceição
2010-03-01
Full Text Available Introduction: In the trial of aging all the structures of the organism are modified, generating intercurrences in the quality of the hearing and of the comprehension. The hearing loss that occurs in consequence of this trial occasion a reduction of the communicative function, causing, also, a distance of the social relationship. Objective: Comparing the performance of the temporal auditory processing between elderly individuals with and without hearing loss. Method: The present study is characterized for to be a prospective, transversal and of diagnosis character field work. They were analyzed 21 elders (16 women and 5 men, with ages between 60 to 81 years divided in two groups, a group "without hearing loss"; (n = 13 with normal auditive thresholds or restricted hearing loss to the isolated frequencies and a group "with hearing loss" (n = 8 with neurosensory hearing loss of variable degree between light to moderately severe. Both the groups performed the tests of frequency (PPS and duration (DPS, for evaluate the ability of temporal sequencing, and the test Randon Gap Detection Test (RGDT, for evaluate the temporal resolution ability. Results: It had not difference statistically significant between the groups, evaluated by the tests DPS and RGDT. The ability of temporal sequencing was significantly major in the group without hearing loss, when evaluated by the test PPS in the condition "muttering". This result presented a growing one significant in parallel with the increase of the age group. Conclusion: It had not difference in the temporal auditory processing in the comparison between the groups.
Stochastic processes from physics to finance
Paul, Wolfgang
2013-01-01
This book introduces the theory of stochastic processes with applications taken from physics and finance. Fundamental concepts like the random walk or Brownian motion but also Levy-stable distributions are discussed. Applications are selected to show the interdisciplinary character of the concepts and methods. In the second edition of the book a discussion of extreme events ranging from their mathematical definition to their importance for financial crashes was included. The exposition of basic notions of probability theory and the Brownian motion problem as well as the relation between conservative diffusion processes and quantum mechanics is expanded. The second edition also enlarges the treatment of financial markets. Beyond a presentation of geometric Brownian motion and the Black-Scholes approach to option pricing as well as the econophysics analysis of the stylized facts of financial markets, an introduction to agent based modeling approaches is given.
An extension of clarke's model with stochastic amplitude flip processes
Hoel, Hakon
2014-07-01
Stochastic modeling is an essential tool for studying statistical properties of wireless channels. In multipath fading channel (MFC) models, the signal reception is modeled by a sum of wave path contributions, and Clarke\\'s model is an important example of such which has been widely accepted in many wireless applications. However, since Clarke\\'s model is temporally deterministic, Feng and Field noted that it does not model real wireless channels with time-varying randomness well. Here, we extend Clarke\\'s model to a novel time-varying stochastic MFC model with scatterers randomly flipping on and off. Statistical properties of the MFC model are analyzed and shown to fit well with real signal measurements, and a limit Gaussian process is derived from the model when the number of active wave paths tends to infinity. A second focus of this work is a comparison study of the error and computational cost of generating signal realizations from the MFC model and from its limit Gaussian process. By rigorous analysis and numerical studies, we show that in many settings, signal realizations are generated more efficiently by Gaussian process algorithms than by the MFC model\\'s algorithm. Numerical examples that strengthen these observations are also presented. © 2014 IEEE.
Applied probability and stochastic processes. 2. ed.
Energy Technology Data Exchange (ETDEWEB)
Feldman, Richard M. [Texas A and M Univ., College Station, TX (United States). Industrial and Systems Engineering Dept.; Valdez-Flores, Ciriaco [Sielken and Associates Consulting, Inc., Bryan, TX (United States)
2010-07-01
This book presents applied probability and stochastic processes in an elementary but mathematically precise manner, with numerous examples and exercises to illustrate the range of engineering and science applications of the concepts. The book is designed to give the reader an intuitive understanding of probabilistic reasoning, in addition to an understanding of mathematical concepts and principles. The initial chapters present a summary of probability and statistics and then Poisson processes, Markov chains, Markov processes and queuing processes are introduced. Advanced topics include simulation, inventory theory, replacement theory, Markov decision theory, and the use of matrix geometric procedures in the analysis of queues. Included in the second edition are appendices at the end of several chapters giving suggestions for the use of Excel in solving the problems of the chapter. Also new in this edition are an introductory chapter on statistics and a chapter on Poisson processes that includes some techniques used in risk assessment. The old chapter on queues has been expanded and broken into two new chapters: one for simple queuing processes and one for queuing networks. Support is provided through the web site http://apsp.tamu.edu where students will have the answers to odd numbered problems and instructors will have access to full solutions and Excel files for homework. (orig.)
An introduction to stochastic processes with applications to biology
Allen, Linda J S
2010-01-01
An Introduction to Stochastic Processes with Applications to Biology, Second Edition presents the basic theory of stochastic processes necessary in understanding and applying stochastic methods to biological problems in areas such as population growth and extinction, drug kinetics, two-species competition and predation, the spread of epidemics, and the genetics of inbreeding. Because of their rich structure, the text focuses on discrete and continuous time Markov chains and continuous time and state Markov processes.New to the Second EditionA new chapter on stochastic differential equations th
Mapping stochastic processes onto complex networks
International Nuclear Information System (INIS)
Shirazi, A H; Reza Jafari, G; Davoudi, J; Peinke, J; Reza Rahimi Tabar, M; Sahimi, Muhammad
2009-01-01
We introduce a method by which stochastic processes are mapped onto complex networks. As examples, we construct the networks for such time series as those for free-jet and low-temperature helium turbulence, the German stock market index (the DAX), and white noise. The networks are further studied by contrasting their geometrical properties, such as the mean length, diameter, clustering, and average number of connections per node. By comparing the network properties of the original time series investigated with those for the shuffled and surrogate series, we are able to quantify the effect of the long-range correlations and the fatness of the probability distribution functions of the series on the networks constructed. Most importantly, we demonstrate that the time series can be reconstructed with high precision by means of a simple random walk on their corresponding networks
Chemical kinetics, stochastic processes, and irreversible thermodynamics
Santillán, Moisés
2014-01-01
This book brings theories in nonlinear dynamics, stochastic processes, irreversible thermodynamics, physical chemistry, and biochemistry together in an introductory but formal and comprehensive manner. Coupled with examples, the theories are developed stepwise, starting with the simplest concepts and building upon them into a more general framework. Furthermore, each new mathematical derivation is immediately applied to one or more biological systems. The last chapters focus on applying mathematical and physical techniques to study systems such as: gene regulatory networks and ion channels. The target audience of this book are mainly final year undergraduate and graduate students with a solid mathematical background (physicists, mathematicians, and engineers), as well as with basic notions of biochemistry and cellular biology. This book can also be useful to students with a biological background who are interested in mathematical modeling, and have a working knowledge of calculus, differential equatio...
Reversibility in Quantum Models of Stochastic Processes
Gier, David; Crutchfield, James; Mahoney, John; James, Ryan
Natural phenomena such as time series of neural firing, orientation of layers in crystal stacking and successive measurements in spin-systems are inherently probabilistic. The provably minimal classical models of such stochastic processes are ɛ-machines, which consist of internal states, transition probabilities between states and output values. The topological properties of the ɛ-machine for a given process characterize the structure, memory and patterns of that process. However ɛ-machines are often not ideal because their statistical complexity (Cμ) is demonstrably greater than the excess entropy (E) of the processes they represent. Quantum models (q-machines) of the same processes can do better in that their statistical complexity (Cq) obeys the relation Cμ >= Cq >= E. q-machines can be constructed to consider longer lengths of strings, resulting in greater compression. With code-words of sufficiently long length, the statistical complexity becomes time-symmetric - a feature apparently novel to this quantum representation. This result has ramifications for compression of classical information in quantum computing and quantum communication technology.
Process theory for supervisory control of stochastic systems with data
Markovski, J.
2012-01-01
We propose a process theory for supervisory control of stochastic nondeterministic plants with data-based observations. The Markovian process theory with data relies on the notion of Markovian partial bisimulation to capture controllability of stochastic nondeterministic systems. It presents a
Stochastic processes and long range dependence
Samorodnitsky, Gennady
2016-01-01
This monograph is a gateway for researchers and graduate students to explore the profound, yet subtle, world of long-range dependence (also known as long memory). The text is organized around the probabilistic properties of stationary processes that are important for determining the presence or absence of long memory. The first few chapters serve as an overview of the general theory of stochastic processes which gives the reader sufficient background, language, and models for the subsequent discussion of long memory. The later chapters devoted to long memory begin with an introduction to the subject along with a brief history of its development, followed by a presentation of what is currently the best known approach, applicable to stationary processes with a finite second moment. The book concludes with a chapter devoted to the author’s own, less standard, point of view of long memory as a phase transition, and even includes some novel results. Most of the material in the book has not previously been publis...
Stochastic differential equations and diffusion processes
Ikeda, N
1989-01-01
Being a systematic treatment of the modern theory of stochastic integrals and stochastic differential equations, the theory is developed within the martingale framework, which was developed by J.L. Doob and which plays an indispensable role in the modern theory of stochastic analysis.A considerable number of corrections and improvements have been made for the second edition of this classic work. In particular, major and substantial changes are in Chapter III and Chapter V where the sections treating excursions of Brownian Motion and the Malliavin Calculus have been expanded and refined. Sectio
American option pricing with stochastic volatility processes
Directory of Open Access Journals (Sweden)
Ping LI
2017-12-01
Full Text Available In order to solve the problem of option pricing more perfectly, the option pricing problem with Heston stochastic volatility model is considered. The optimal implementation boundary of American option and the conditions for its early execution are analyzed and discussed. In view of the fact that there is no analytical American option pricing formula, through the space discretization parameters, the stochastic partial differential equation satisfied by American options with Heston stochastic volatility is transformed into the corresponding differential equations, and then using high order compact finite difference method, numerical solutions are obtained for the option price. The numerical experiments are carried out to verify the theoretical results and simulation. The two kinds of optimal exercise boundaries under the conditions of the constant volatility and the stochastic volatility are compared, and the results show that the optimal exercise boundary also has stochastic volatility. Under the setting of parameters, the behavior and the nature of volatility are analyzed, the volatility curve is simulated, the calculation results of high order compact difference method are compared, and the numerical option solution is obtained, so that the method is verified. The research result provides reference for solving the problems of option pricing under stochastic volatility such as multiple underlying asset option pricing and barrier option pricing.
Stochastic resonance during a polymer translocation process
International Nuclear Information System (INIS)
Mondal, Debasish; Muthukumar, M.
2016-01-01
We have studied the occurrence of stochastic resonance when a flexible polymer chain undergoes a single-file translocation through a nano-pore separating two spherical cavities, under a time-periodic external driving force. The translocation of the chain is controlled by a free energy barrier determined by chain length, pore length, pore-polymer interaction, and confinement inside the donor and receiver cavities. The external driving force is characterized by a frequency and amplitude. By combining the Fokker-Planck formalism for polymer translocation and a two-state model for stochastic resonance, we have derived analytical formulas for criteria for emergence of stochastic resonance during polymer translocation. We show that no stochastic resonance is possible if the free energy barrier for polymer translocation is purely entropic in nature. The polymer chain exhibits stochastic resonance only in the presence of an energy threshold in terms of polymer-pore interactions. Once stochastic resonance is feasible, the chain entropy controls the optimal synchronization conditions significantly.
Visualisation for Stochastic Process Algebras: The Graphic Truth
DEFF Research Database (Denmark)
Smith, Michael James Andrew; Gilmore, Stephen
2011-01-01
and stochastic activity networks provide an automaton-based view of the model, which may be easier to visualise, at the expense of portability. In this paper, we argue that we can achieve the benefits of both approaches by generating a graphical view of a stochastic process algebra model, which is synchronised...
Doubly stochastic Poisson process models for precipitation at fine time-scales
Ramesh, Nadarajah I.; Onof, Christian; Xie, Dichao
2012-09-01
This paper considers a class of stochastic point process models, based on doubly stochastic Poisson processes, in the modelling of rainfall. We examine the application of this class of models, a neglected alternative to the widely-known Poisson cluster models, in the analysis of fine time-scale rainfall intensity. These models are mainly used to analyse tipping-bucket raingauge data from a single site but an extension to multiple sites is illustrated which reveals the potential of this class of models to study the temporal and spatial variability of precipitation at fine time-scales.
100 years after Smoluchowski: stochastic processes in cell biology
International Nuclear Information System (INIS)
Holcman, D; Schuss, Z
2017-01-01
100 years after Smoluchowski introduced his approach to stochastic processes, they are now at the basis of mathematical and physical modeling in cellular biology: they are used for example to analyse and to extract features from a large number (tens of thousands) of single molecular trajectories or to study the diffusive motion of molecules, proteins or receptors. Stochastic modeling is a new step in large data analysis that serves extracting cell biology concepts. We review here Smoluchowski’s approach to stochastic processes and provide several applications for coarse-graining diffusion, studying polymer models for understanding nuclear organization and finally, we discuss the stochastic jump dynamics of telomeres across cell division and stochastic gene regulation. (topical review)
Introduction to probability and stochastic processes with applications
Castañ, Blanco; Arunachalam, Viswanathan; Dharmaraja, Selvamuthu
2012-01-01
An easily accessible, real-world approach to probability and stochastic processes Introduction to Probability and Stochastic Processes with Applications presents a clear, easy-to-understand treatment of probability and stochastic processes, providing readers with a solid foundation they can build upon throughout their careers. With an emphasis on applications in engineering, applied sciences, business and finance, statistics, mathematics, and operations research, the book features numerous real-world examples that illustrate how random phenomena occur in nature and how to use probabilistic t
Auditory temporal processing in patients with temporal lobe epilepsy.
Lavasani, Azam Navaei; Mohammadkhani, Ghassem; Motamedi, Mahmoud; Karimi, Leyla Jalilvand; Jalaei, Shohreh; Shojaei, Fereshteh Sadat; Danesh, Ali; Azimi, Hadi
2016-07-01
Auditory temporal processing is the main feature of speech processing ability. Patients with temporal lobe epilepsy, despite their normal hearing sensitivity, may present speech recognition disorders. The present study was carried out to evaluate the auditory temporal processing in patients with unilateral TLE. The present study was carried out on 25 patients with epilepsy: 11 patients with right temporal lobe epilepsy and 14 with left temporal lobe epilepsy with a mean age of 31.1years and 18 control participants with a mean age of 29.4years. The two experimental and control groups were evaluated via gap-in-noise and duration pattern sequence tests. One-way ANOVA was run to analyze the data. The mean of the threshold of the GIN test in the control group was observed to be better than that in participants with LTLE and RTLE. Also, it was observed that the percentage of correct responses on the DPS test in the control group and in participants with RTLE was better than that in participants with LTLE. Patients with TLE have difficulties in temporal processing. Difficulties are more significant in patients with LTLE, likely because the left temporal lobe is specialized for the processing of temporal information. Copyright © 2016 Elsevier Inc. All rights reserved.
Verification and Planning for Stochastic Processes with Asynchronous Events
National Research Council Canada - National Science Library
Younes, Hakan L
2005-01-01
.... The most common assumption is that of history-independence: the Markov assumption. In this thesis, the author considers the problems of verification and planning for stochastic processes with asynchronous events, without relying on the Markov assumption...
Bibliography on the stochastic processes in plasma and related problems
International Nuclear Information System (INIS)
Polovin, R.V.
1976-01-01
Stochastic processes in plasma and related matters. The bibliography contains 500 references and was compiled from the open literature only. Some references are annotated or completed with short abstracts. There are subject and authors indexes
Iacus, Stefano M
2018-01-01
The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stochastic differential equations driven by Wiener process, Lévy processes or fractional Brownian motion, as well as CARMA processes. The package performs various central statistical analyses such as quasi maximum likelihood estimation, adaptive Bayes estimation, structural change point analysis, hypotheses testing, asynchronous covariance estimation, lead-lag estimation, LASSO model selection, and so on. YUIMA also supports stochastic numerical analysis by fast computation of the expected value of functionals of stochastic processes through automatic asymptotic expansion by means of the Malliavin calculus. All models can be multidimensional, multiparametric or non parametric.The book explains briefly the underlying theory for simulation and inference of several classes of stochastic processes and then presents both simulation experiments and applications to real data. Although these ...
Bidirectional Classical Stochastic Processes with Measurements and Feedback
Hahne, G. E.
2005-01-01
A measurement on a quantum system is said to cause the "collapse" of the quantum state vector or density matrix. An analogous collapse occurs with measurements on a classical stochastic process. This paper addresses the question of describing the response of a classical stochastic process when there is feedback from the output of a measurement to the input, and is intended to give a model for quantum-mechanical processes that occur along a space-like reaction coordinate. The classical system can be thought of in physical terms as two counterflowing probability streams, which stochastically exchange probability currents in a way that the net probability current, and hence the overall probability, suitably interpreted, is conserved. The proposed formalism extends the . mathematics of those stochastic processes describable with linear, single-step, unidirectional transition probabilities, known as Markov chains and stochastic matrices. It is shown that a certain rearrangement and combination of the input and output of two stochastic matrices of the same order yields another matrix of the same type. Each measurement causes the partial collapse of the probability current distribution in the midst of such a process, giving rise to calculable, but non-Markov, values for the ensuing modification of the system's output probability distribution. The paper concludes with an analysis of a classical probabilistic version of the so-called grandfather paradox.
Stochastic Urban Pluvial Flood Hazard Maps Based upon a Spatial-Temporal Rainfall Generator
Directory of Open Access Journals (Sweden)
Nuno Eduardo Simões
2015-06-01
Full Text Available It is a common practice to assign the return period of a given storm event to the urban pluvial flood event that such storm generates. However, this approach may be inappropriate as rainfall events with the same return period can produce different urban pluvial flooding events, i.e., with different associated flood extent, water levels and return periods. This depends on the characteristics of the rainfall events, such as spatial variability, and on other characteristics of the sewer system and the catchment. To address this, the paper presents an innovative contribution to produce stochastic urban pluvial flood hazard maps. A stochastic rainfall generator for urban-scale applications was employed to generate an ensemble of spatially—and temporally—variable design storms with similar return period. These were used as input to the urban drainage model of a pilot urban catchment (~9 km2 located in London, UK. Stochastic flood hazard maps were generated through a frequency analysis of the flooding generated by the various storm events. The stochastic flood hazard maps obtained show that rainfall spatial-temporal variability is an important factor in the estimation of flood likelihood in urban areas. Moreover, as compared to the flood hazard maps obtained by using a single spatially-uniform storm event, the stochastic maps generated in this study provide a more comprehensive assessment of flood hazard which enables better informed flood risk management decisions.
Forecasting financial asset processes: stochastic dynamics via learning neural networks.
Giebel, S; Rainer, M
2010-01-01
Models for financial asset dynamics usually take into account their inherent unpredictable nature by including a suitable stochastic component into their process. Unknown (forward) values of financial assets (at a given time in the future) are usually estimated as expectations of the stochastic asset under a suitable risk-neutral measure. This estimation requires the stochastic model to be calibrated to some history of sufficient length in the past. Apart from inherent limitations, due to the stochastic nature of the process, the predictive power is also limited by the simplifying assumptions of the common calibration methods, such as maximum likelihood estimation and regression methods, performed often without weights on the historic time series, or with static weights only. Here we propose a novel method of "intelligent" calibration, using learning neural networks in order to dynamically adapt the parameters of the stochastic model. Hence we have a stochastic process with time dependent parameters, the dynamics of the parameters being themselves learned continuously by a neural network. The back propagation in training the previous weights is limited to a certain memory length (in the examples we consider 10 previous business days), which is similar to the maximal time lag of autoregressive processes. We demonstrate the learning efficiency of the new algorithm by tracking the next-day forecasts for the EURTRY and EUR-HUF exchange rates each.
Convergence of trajectories in fractal interpolation of stochastic processes
International Nuclear Information System (INIS)
MaIysz, Robert
2006-01-01
The notion of fractal interpolation functions (FIFs) can be applied to stochastic processes. Such construction is especially useful for the class of α-self-similar processes with stationary increments and for the class of α-fractional Brownian motions. For these classes, convergence of the Minkowski dimension of the graphs in fractal interpolation of the Hausdorff dimension of the graph of original process was studied in [Herburt I, MaIysz R. On convergence of box dimensions of fractal interpolation stochastic processes. Demonstratio Math 2000;4:873-88.], [MaIysz R. A generalization of fractal interpolation stochastic processes to higher dimension. Fractals 2001;9:415-28.], and [Herburt I. Box dimension of interpolations of self-similar processes with stationary increments. Probab Math Statist 2001;21:171-8.]. We prove that trajectories of fractal interpolation stochastic processes converge to the trajectory of the original process. We also show that convergence of the trajectories in fractal interpolation of stochastic processes is equivalent to the convergence of trajectories in linear interpolation
Stochastic Analysis of Gaussian Processes via Fredholm Representation
Directory of Open Access Journals (Sweden)
Tommi Sottinen
2016-01-01
Full Text Available We show that every separable Gaussian process with integrable variance function admits a Fredholm representation with respect to a Brownian motion. We extend the Fredholm representation to a transfer principle and develop stochastic analysis by using it. We show the convenience of the Fredholm representation by giving applications to equivalence in law, bridges, series expansions, stochastic differential equations, and maximum likelihood estimations.
Fast Quantum Algorithm for Predicting Descriptive Statistics of Stochastic Processes
Williams Colin P.
1999-01-01
Stochastic processes are used as a modeling tool in several sub-fields of physics, biology, and finance. Analytic understanding of the long term behavior of such processes is only tractable for very simple types of stochastic processes such as Markovian processes. However, in real world applications more complex stochastic processes often arise. In physics, the complicating factor might be nonlinearities; in biology it might be memory effects; and in finance is might be the non-random intentional behavior of participants in a market. In the absence of analytic insight, one is forced to understand these more complex stochastic processes via numerical simulation techniques. In this paper we present a quantum algorithm for performing such simulations. In particular, we show how a quantum algorithm can predict arbitrary descriptive statistics (moments) of N-step stochastic processes in just O(square root of N) time. That is, the quantum complexity is the square root of the classical complexity for performing such simulations. This is a significant speedup in comparison to the current state of the art.
Spatio-temporal and stochastic modelling of severe acute respiratory syndrome
Directory of Open Access Journals (Sweden)
Poh-Chin Lai
2013-11-01
Full Text Available This study describes the development of a spatio-temporal disease model based on the episodes of severe acute respiratory syndrome (SARS that took place in Hong Kong in 2003. In contrast to conventional, deterministic modelling approaches, the model described here is predominantly spatial. It incorporates stochastic processing of environmental and social variables that interact in space and time to affect the patterns of disease transmission in a community. The model was validated through a comparative assessment between actual and modelled distribution of diseased locations. Our study shows that the inclusion of location-specific characteristics satisfactorily replicates the spatial dynamics of an infectious disease. The Pearson’s correlation coefficients for five trials based on 3-day aggregation of disease counts for 1-3, 4-6 and 7-9 day forecasts were 0.57- 0.95, 0.54-0.86 and 0.57-0.82, respectively, while the correlation based on 5-day aggregation for the 1-5 day forecast was 0.55- 0.94 and 0.58-0.81 for the 6-10 day forecast. The significant and strong relationship between actual results and forecast is encouraging for the potential development of an early warning system for detecting this type of disease outbreaks.
Diffusive processes in a stochastic magnetic field
International Nuclear Information System (INIS)
Wang, H.; Vlad, M.; Vanden Eijnden, E.; Spineanu, F.; Misguich, J.H.; Balescu, R.
1995-01-01
The statistical representation of a fluctuating (stochastic) magnetic field configuration is studied in detail. The Eulerian correlation functions of the magnetic field are determined, taking into account all geometrical constraints: these objects form a nondiagonal matrix. The Lagrangian correlations, within the reasonable Corrsin approximation, are reduced to a single scalar function, determined by an integral equation. The mean square perpendicular deviation of a geometrical point moving along a perturbed field line is determined by a nonlinear second-order differential equation. The separation of neighboring field lines in a stochastic magnetic field is studied. We find exponentiation lengths of both signs describing, in particular, a decay (on the average) of any initial anisotropy. The vanishing sum of these exponentiation lengths ensures the existence of an invariant which was overlooked in previous works. Next, the separation of a particle's trajectory from the magnetic field line to which it was initially attached is studied by a similar method. Here too an initial phase of exponential separation appears. Assuming the existence of a final diffusive phase, anomalous diffusion coefficients are found for both weakly and strongly collisional limits. The latter is identical to the well known Rechester-Rosenbluth coefficient, which is obtained here by a more quantitative (though not entirely deductive) treatment than in earlier works
Stochastic project networks temporal analysis, scheduling and cost minimization
Neumann, Klaus
1990-01-01
Project planning, scheduling, and control are regularly used in business and the service sector of an economy to accomplish outcomes with limited resources under critical time constraints. To aid in solving these problems, network-based planning methods have been developed that now exist in a wide variety of forms, cf. Elmaghraby (1977) and Moder et al. (1983). The so-called "classical" project networks, which are used in the network techniques CPM and PERT and which represent acyclic weighted directed graphs, are able to describe only projects whose evolution in time is uniquely specified in advance. Here every event of the project is realized exactly once during a single project execution and it is not possible to return to activities previously carried out (that is, no feedback is permitted). Many practical projects, however, do not meet those conditions. Consider, for example, a production process where some parts produced by a machine may be poorly manufactured. If an inspection shows that a part does no...
Classical and spatial stochastic processes with applications to biology
Schinazi, Rinaldo B
2014-01-01
The revised and expanded edition of this textbook presents the concepts and applications of random processes with the same illuminating simplicity as its first edition, but with the notable addition of substantial modern material on biological modeling. While still treating many important problems in fields such as engineering and mathematical physics, the book also focuses on the highly relevant topics of cancerous mutations, influenza evolution, drug resistance, and immune response. The models used elegantly apply various classical stochastic models presented earlier in the text, and exercises are included throughout to reinforce essential concepts. The second edition of Classical and Spatial Stochastic Processes is suitable as a textbook for courses in stochastic processes at the advanced-undergraduate and graduate levels, or as a self-study resource for researchers and practitioners in mathematics, engineering, physics, and mathematical biology. Reviews of the first edition: An appetizing textbook for a f...
De Ridder, Simon; Vandermarliere, Benjamin; Ryckebusch, Jan
2016-11-01
A framework based on generalized hierarchical random graphs (GHRGs) for the detection of change points in the structure of temporal networks has recently been developed by Peel and Clauset (2015 Proc. 29th AAAI Conf. on Artificial Intelligence). We build on this methodology and extend it to also include the versatile stochastic block models (SBMs) as a parametric family for reconstructing the empirical networks. We use five different techniques for change point detection on prototypical temporal networks, including empirical and synthetic ones. We find that none of the considered methods can consistently outperform the others when it comes to detecting and locating the expected change points in empirical temporal networks. With respect to the precision and the recall of the results of the change points, we find that the method based on a degree-corrected SBM has better recall properties than other dedicated methods, especially for sparse networks and smaller sliding time window widths.
Analyzing Properties of Stochastic Business Processes By Model Checking
DEFF Research Database (Denmark)
Herbert, Luke Thomas; Sharp, Robin
2013-01-01
This chapter presents an approach to precise formal analysis of business processes with stochastic properties. The method presented here allows for both qualitative and quantitative properties to be individually analyzed at design time without requiring a full specification. This provides...... an effective means to explore possible designs for a business process and to debug any flaws....
? filtering for stochastic systems driven by Poisson processes
Song, Bo; Wu, Zheng-Guang; Park, Ju H.; Shi, Guodong; Zhang, Ya
2015-01-01
This paper investigates the ? filtering problem for stochastic systems driven by Poisson processes. By utilising the martingale theory such as the predictable projection operator and the dual predictable projection operator, this paper transforms the expectation of stochastic integral with respect to the Poisson process into the expectation of Lebesgue integral. Then, based on this, this paper designs an ? filter such that the filtering error system is mean-square asymptotically stable and satisfies a prescribed ? performance level. Finally, a simulation example is given to illustrate the effectiveness of the proposed filtering scheme.
Anomalous scaling of stochastic processes and the Moses effect.
Chen, Lijian; Bassler, Kevin E; McCauley, Joseph L; Gunaratne, Gemunu H
2017-04-01
The state of a stochastic process evolving over a time t is typically assumed to lie on a normal distribution whose width scales like t^{1/2}. However, processes in which the probability distribution is not normal and the scaling exponent differs from 1/2 are known. The search for possible origins of such "anomalous" scaling and approaches to quantify them are the motivations for the work reported here. In processes with stationary increments, where the stochastic process is time-independent, autocorrelations between increments and infinite variance of increments can cause anomalous scaling. These sources have been referred to as the Joseph effect and the Noah effect, respectively. If the increments are nonstationary, then scaling of increments with t can also lead to anomalous scaling, a mechanism we refer to as the Moses effect. Scaling exponents quantifying the three effects are defined and related to the Hurst exponent that characterizes the overall scaling of the stochastic process. Methods of time series analysis that enable accurate independent measurement of each exponent are presented. Simple stochastic processes are used to illustrate each effect. Intraday financial time series data are analyzed, revealing that their anomalous scaling is due only to the Moses effect. In the context of financial market data, we reiterate that the Joseph exponent, not the Hurst exponent, is the appropriate measure to test the efficient market hypothesis.
Anomalous scaling of stochastic processes and the Moses effect
Chen, Lijian; Bassler, Kevin E.; McCauley, Joseph L.; Gunaratne, Gemunu H.
2017-04-01
The state of a stochastic process evolving over a time t is typically assumed to lie on a normal distribution whose width scales like t1/2. However, processes in which the probability distribution is not normal and the scaling exponent differs from 1/2 are known. The search for possible origins of such "anomalous" scaling and approaches to quantify them are the motivations for the work reported here. In processes with stationary increments, where the stochastic process is time-independent, autocorrelations between increments and infinite variance of increments can cause anomalous scaling. These sources have been referred to as the Joseph effect and the Noah effect, respectively. If the increments are nonstationary, then scaling of increments with t can also lead to anomalous scaling, a mechanism we refer to as the Moses effect. Scaling exponents quantifying the three effects are defined and related to the Hurst exponent that characterizes the overall scaling of the stochastic process. Methods of time series analysis that enable accurate independent measurement of each exponent are presented. Simple stochastic processes are used to illustrate each effect. Intraday financial time series data are analyzed, revealing that their anomalous scaling is due only to the Moses effect. In the context of financial market data, we reiterate that the Joseph exponent, not the Hurst exponent, is the appropriate measure to test the efficient market hypothesis.
A Constructive Sharp Approach to Functional Quantization of Stochastic Processes
Junglen, Stefan; Luschgy, Harald
2010-01-01
We present a constructive approach to the functional quantization problem of stochastic processes, with an emphasis on Gaussian processes. The approach is constructive, since we reduce the infinite-dimensional functional quantization problem to a finite-dimensional quantization problem that can be solved numerically. Our approach achieves the sharp rate of the minimal quantization error and can be used to quantize the path space for Gaussian processes and also, for example, Lévy processes.
Using stochastic models to incorporate spatial and temporal variability [Exercise 14
Carolyn Hull Sieg; Rudy M. King; Fred Van Dyke
2003-01-01
To this point, our analysis of population processes and viability in the western prairie fringed orchid has used only deterministic models. In this exercise, we conduct a similar analysis, using a stochastic model instead. This distinction is of great importance to population biology in general and to conservation biology in particular. In deterministic models,...
Learning Theory Estimates with Observations from General Stationary Stochastic Processes.
Hang, Hanyuan; Feng, Yunlong; Steinwart, Ingo; Suykens, Johan A K
2016-12-01
This letter investigates the supervised learning problem with observations drawn from certain general stationary stochastic processes. Here by general, we mean that many stationary stochastic processes can be included. We show that when the stochastic processes satisfy a generalized Bernstein-type inequality, a unified treatment on analyzing the learning schemes with various mixing processes can be conducted and a sharp oracle inequality for generic regularized empirical risk minimization schemes can be established. The obtained oracle inequality is then applied to derive convergence rates for several learning schemes such as empirical risk minimization (ERM), least squares support vector machines (LS-SVMs) using given generic kernels, and SVMs using gaussian kernels for both least squares and quantile regression. It turns out that for independent and identically distributed (i.i.d.) processes, our learning rates for ERM recover the optimal rates. For non-i.i.d. processes, including geometrically [Formula: see text]-mixing Markov processes, geometrically [Formula: see text]-mixing processes with restricted decay, [Formula: see text]-mixing processes, and (time-reversed) geometrically [Formula: see text]-mixing processes, our learning rates for SVMs with gaussian kernels match, up to some arbitrarily small extra term in the exponent, the optimal rates. For the remaining cases, our rates are at least close to the optimal rates. As a by-product, the assumed generalized Bernstein-type inequality also provides an interpretation of the so-called effective number of observations for various mixing processes.
Stochastic analysis in production process and ecology under uncertainty
Bieda, Bogusław
2014-01-01
The monograph addresses a problem of stochastic analysis based on the uncertainty assessment by simulation and application of this method in ecology and steel industry under uncertainty. The first chapter defines the Monte Carlo (MC) method and random variables in stochastic models. Chapter two deals with the contamination transport in porous media. Stochastic approach for Municipal Solid Waste transit time contaminants modeling using MC simulation has been worked out. The third chapter describes the risk analysis of the waste to energy facility proposal for Konin city, including the financial aspects. Environmental impact assessment of the ArcelorMittal Steel Power Plant, in Kraków - in the chapter four - is given. Thus, four scenarios of the energy mix production processes were studied. Chapter five contains examples of using ecological Life Cycle Assessment (LCA) - a relatively new method of environmental impact assessment - which help in preparing pro-ecological strategy, and which can lead to reducing t...
Counting statistics of non-markovian quantum stochastic processes
DEFF Research Database (Denmark)
Flindt, Christian; Novotny, T.; Braggio, A.
2008-01-01
We derive a general expression for the cumulant generating function (CGF) of non-Markovian quantum stochastic transport processes. The long-time limit of the CGF is determined by a single dominating pole of the resolvent of the memory kernel from which we extract the zero-frequency cumulants...
Gene regulation and noise reduction by coupling of stochastic processes
Ramos, Alexandre F.; Hornos, José Eduardo M.; Reinitz, John
2015-02-01
Here we characterize the low-noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the two gene states depends on protein number. This fact has a very important implication: There exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of the genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction.
Gene regulation and noise reduction by coupling of stochastic processes.
Ramos, Alexandre F; Hornos, José Eduardo M; Reinitz, John
2015-02-01
Here we characterize the low-noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the two gene states depends on protein number. This fact has a very important implication: There exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of the genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction.
Conditional Stochastic Processes Applied to Wave Load Predictions
DEFF Research Database (Denmark)
Jensen, Jørgen Juncher
2015-01-01
The concept of conditional stochastic processes provides a powerful tool for evaluation and estimation of wave loads on ships and offshore structures. This article first considers conditional waves with a focus on critical wave episodes. Then the inherent uncertainty in the results is illustrated...
Stochastic evolution of the Universe: A possible dynamical process ...
Indian Academy of Sciences (India)
C Sivakumar
2017-12-11
Dec 11, 2017 ... https://doi.org/10.1007/s12043-017-1491-z. Stochastic evolution of the Universe: A possible dynamical process leading to fractal structures. C SIVAKUMAR. Department of Physics, Maharaja's College, Ernakulam 682 011, India. E-mail: thrisivc@yahoo.com. MS received 6 July 2016; revised 26 June 2017; ...
Uncertainty Reduction for Stochastic Processes on Complex Networks
Radicchi, Filippo; Castellano, Claudio
2018-05-01
Many real-world systems are characterized by stochastic dynamical rules where a complex network of interactions among individual elements probabilistically determines their state. Even with full knowledge of the network structure and of the stochastic rules, the ability to predict system configurations is generally characterized by a large uncertainty. Selecting a fraction of the nodes and observing their state may help to reduce the uncertainty about the unobserved nodes. However, choosing these points of observation in an optimal way is a highly nontrivial task, depending on the nature of the stochastic process and on the structure of the underlying interaction pattern. In this paper, we introduce a computationally efficient algorithm to determine quasioptimal solutions to the problem. The method leverages network sparsity to reduce computational complexity from exponential to almost quadratic, thus allowing the straightforward application of the method to mid-to-large-size systems. Although the method is exact only for equilibrium stochastic processes defined on trees, it turns out to be effective also for out-of-equilibrium processes on sparse loopy networks.
Stochastic processes and applications diffusion processes, the Fokker-Planck and Langevin equations
Pavliotis, Grigorios A
2014-01-01
This book presents various results and techniques from the theory of stochastic processes that are useful in the study of stochastic problems in the natural sciences. The main focus is analytical methods, although numerical methods and statistical inference methodologies for studying diffusion processes are also presented. The goal is the development of techniques that are applicable to a wide variety of stochastic models that appear in physics, chemistry and other natural sciences. Applications such as stochastic resonance, Brownian motion in periodic potentials and Brownian motors are studied and the connection between diffusion processes and time-dependent statistical mechanics is elucidated. The book contains a large number of illustrations, examples, and exercises. It will be useful for graduate-level courses on stochastic processes for students in applied mathematics, physics and engineering. Many of the topics covered in this book (reversible diffusions, convergence to eq...
Neural network connectivity and response latency modelled by stochastic processes
DEFF Research Database (Denmark)
Tamborrino, Massimiliano
is connected to thousands of other neurons. The rst question is: how to model neural networks through stochastic processes? A multivariate Ornstein-Uhlenbeck process, obtained as a diffusion approximation of a jump process, is the proposed answer. Obviously, dependencies between neurons imply dependencies......Stochastic processes and their rst passage times have been widely used to describe the membrane potential dynamics of single neurons and to reproduce neuronal spikes, respectively.However, cerebral cortex in human brains is estimated to contain 10-20 billions of neurons and each of them...... between their spike times. Therefore, the second question is: how to detect neural network connectivity from simultaneously recorded spike trains? Answering this question corresponds to investigate the joint distribution of sequences of rst passage times. A non-parametric method based on copulas...
Expectation propagation for continuous time stochastic processes
International Nuclear Information System (INIS)
Cseke, Botond; Schnoerr, David; Sanguinetti, Guido; Opper, Manfred
2016-01-01
We consider the inverse problem of reconstructing the posterior measure over the trajectories of a diffusion process from discrete time observations and continuous time constraints. We cast the problem in a Bayesian framework and derive approximations to the posterior distributions of single time marginals using variational approximate inference, giving rise to an expectation propagation type algorithm. For non-linear diffusion processes, this is achieved by leveraging moment closure approximations. We then show how the approximation can be extended to a wide class of discrete-state Markov jump processes by making use of the chemical Langevin equation. Our empirical results show that the proposed method is computationally efficient and provides good approximations for these classes of inverse problems. (paper)
Deterministic geologic processes and stochastic modeling
International Nuclear Information System (INIS)
Rautman, C.A.; Flint, A.L.
1992-01-01
This paper reports that recent outcrop sampling at Yucca Mountain, Nevada, has produced significant new information regarding the distribution of physical properties at the site of a potential high-level nuclear waste repository. consideration of the spatial variability indicates that her are a number of widespread deterministic geologic features at the site that have important implications for numerical modeling of such performance aspects as ground water flow and radionuclide transport. Because the geologic processes responsible for formation of Yucca Mountain are relatively well understood and operate on a more-or-less regional scale, understanding of these processes can be used in modeling the physical properties and performance of the site. Information reflecting these deterministic geologic processes may be incorporated into the modeling program explicitly using geostatistical concepts such as soft information, or implicitly, through the adoption of a particular approach to modeling
Option Pricing with Stochastic Volatility and Jump Diffusion Processes
Directory of Open Access Journals (Sweden)
Radu Lupu
2006-03-01
Full Text Available Option pricing by the use of Black Scholes Merton (BSM model is based on the assumption that asset prices have a lognormal distribution. In spite of the use of these models on a large scale, both by practioners and academics, the assumption of lognormality is rejected by the history of returns. The objective of this article is to present the methods that developed after the Black Scholes Merton environment and deals with the option pricing model adjustment to the empirical properties of asset returns. The main models that appeared after BSM allowed for special changes of the returns that materialized in jump-diffusion and stochastic volatility processes. The article presents the foundations of risk neutral options evaluation and the empirical evidence that fed the amendment of the lognormal assumption in the first part and shows the evaluation procedure under the assumption of stock prices following the jump-diffusion process and the stochastic volatility process.
Stochasticity in processes fundamentals and applications to chemistry and biology
Schuster, Peter
2016-01-01
This book has developed over the past fifteen years from a modern course on stochastic chemical kinetics for graduate students in physics, chemistry and biology. The first part presents a systematic collection of the mathematical background material needed to understand probability, statistics, and stochastic processes as a prerequisite for the increasingly challenging practical applications in chemistry and the life sciences examined in the second part. Recent advances in the development of new techniques and in the resolution of conventional experiments at nano-scales have been tremendous: today molecular spectroscopy can provide insights into processes down to scales at which current theories at the interface of physics, chemistry and the life sciences cannot be successful without a firm grasp of randomness and its sources. Routinely measured data is now sufficiently accurate to allow the direct recording of fluctuations. As a result, the sampling of data and the modeling of relevant processes are doomed t...
Stochastic Models in the Identification Process
Czech Academy of Sciences Publication Activity Database
Slovák, Dalibor; Zvárová, Jana
2011-01-01
Roč. 7, č. 1 (2011), s. 44-50 ISSN 1801-5603 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : identification process * weight-of evidence formula * coancestry coefficient * beta-binomial sampling formula * DNA mixtures Subject RIV: IN - Informatics, Computer Science http://www.ejbi.eu/images/2011-1/Slovak_en.pdf
5th Seminar on Stochastic Processes, Random Fields and Applications
Russo, Francesco; Dozzi, Marco
2008-01-01
This volume contains twenty-eight refereed research or review papers presented at the 5th Seminar on Stochastic Processes, Random Fields and Applications, which took place at the Centro Stefano Franscini (Monte Verità) in Ascona, Switzerland, from May 30 to June 3, 2005. The seminar focused mainly on stochastic partial differential equations, random dynamical systems, infinite-dimensional analysis, approximation problems, and financial engineering. The book will be a valuable resource for researchers in stochastic analysis and professionals interested in stochastic methods in finance. Contributors: Y. Asai, J.-P. Aubin, C. Becker, M. Benaïm, H. Bessaih, S. Biagini, S. Bonaccorsi, N. Bouleau, N. Champagnat, G. Da Prato, R. Ferrière, F. Flandoli, P. Guasoni, V.B. Hallulli, D. Khoshnevisan, T. Komorowski, R. Léandre, P. Lescot, H. Lisei, J.A. López-Mimbela, V. Mandrekar, S. Méléard, A. Millet, H. Nagai, A.D. Neate, V. Orlovius, M. Pratelli, N. Privault, O. Raimond, M. Röckner, B. Rüdiger, W.J. Runggaldi...
Stochastic processes dominate during boreal bryophyte community assembly.
Fenton, Nicole J; Bergeron, Yves
2013-09-01
Why are plant species found in certain locations and not in others? The study of community assembly rules has attempted to answer this question, and many studies articulate the historic dichotomy of deterministic (predictable niches) vs. stochastic (random or semi-random processes). The study of successional sequences to determine whether they converge, as would be expected by deterministic theory, or diverge, as stochastic theory would suggest, has been one method used to investigate this question. In this article we ask the question: Do similar boreal bryophyte communities develop in the similar habitat created by convergent succession after fires of different severities? Or do the stochastic processes generated by fires of different severity lead to different communities? Specifically we predict that deterministic structure will be more important for large forest-floor species than stochastic processes, and that the inverse will be true for small bryophyte species. We used multivariate regression trees and model selection to determine the relative weight of structure (forest structure, substrates, soil structure) and processes (fire severity) for two groups of bryophyte species sampled in 12 sites (seven high-severity and five low-severity fires). Contrary to our first hypothesis, processes were as important for large forest-floor bryophytes as for small pocket species. Fire severity, its interaction with the quality of available habitat, and its impact on the creation of biological legacies played dominant roles in determining community structure. In this study, sites with nearly identical forest structure, generated via convergent succession after high- and low-severity fire, were compared to see whether these sites supported similar bryophyte communities. While similar to some degree, both the large forest-floor species and the pocket species differed after high-severity fire compared to low-severity fire. This result suggests that the "how," or process of
Discrete stochastic processes and optimal filtering
Bertein, Jean-Claude
2012-01-01
Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. This book provides a comprehensive overview of this area, discussing random and Gaussian vectors, outlining the results necessary for the creation of Wiener and adaptive filters used for stationary signals, as well as examining Kalman filters which ar
Temporal Processing in Audition: Insights from Music.
Rajendran, Vani G; Teki, Sundeep; Schnupp, Jan W H
2017-11-03
Music is a curious example of a temporally patterned acoustic stimulus, and a compelling pan-cultural phenomenon. This review strives to bring some insights from decades of music psychology and sensorimotor synchronization (SMS) literature into the mainstream auditory domain, arguing that musical rhythm perception is shaped in important ways by temporal processing mechanisms in the brain. The feature that unites these disparate disciplines is an appreciation of the central importance of timing, sequencing, and anticipation. Perception of musical rhythms relies on an ability to form temporal predictions, a general feature of temporal processing that is equally relevant to auditory scene analysis, pattern detection, and speech perception. By bringing together findings from the music and auditory literature, we hope to inspire researchers to look beyond the conventions of their respective fields and consider the cross-disciplinary implications of studying auditory temporal sequence processing. We begin by highlighting music as an interesting sound stimulus that may provide clues to how temporal patterning in sound drives perception. Next, we review the SMS literature and discuss possible neural substrates for the perception of, and synchronization to, musical beat. We then move away from music to explore the perceptual effects of rhythmic timing in pattern detection, auditory scene analysis, and speech perception. Finally, we review the neurophysiology of general timing processes that may underlie aspects of the perception of rhythmic patterns. We conclude with a brief summary and outlook for future research. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Hermite-Hadamard type inequality for φ{sub h}-convex stochastic processes
Energy Technology Data Exchange (ETDEWEB)
Sarıkaya, Mehmet Zeki, E-mail: sarikayamz@gmail.com [Department of Mathematics, Faculty of Science and Arts, Düzce University, Düzce (Turkey); Kiriş, Mehmet Eyüp, E-mail: kiris@aku.edu.tr [Department of Mathematics, Institute of Science and Arts, Afyon Kocatepe University, Afyonkarahisar (Turkey); Çelik, Nuri, E-mail: ncelik@bartin.edu.tr [Department of Statistics, Faculty of Science, Bartın University, Bartın-Turkey (Turkey)
2016-04-18
The main aim of the present paper is to introduce φ{sub h}-convex stochastic processes and we investigate main properties of these mappings. Moreover, we prove the Hadamard-type inequalities for φ{sub h}-convex stochastic processes. We also give some new general inequalities for φ{sub h}-convex stochastic processes.
Simulation of anaerobic digestion processes using stochastic algorithm.
Palanichamy, Jegathambal; Palani, Sundarambal
2014-01-01
The Anaerobic Digestion (AD) processes involve numerous complex biological and chemical reactions occurring simultaneously. Appropriate and efficient models are to be developed for simulation of anaerobic digestion systems. Although several models have been developed, mostly they suffer from lack of knowledge on constants, complexity and weak generalization. The basis of the deterministic approach for modelling the physico and bio-chemical reactions occurring in the AD system is the law of mass action, which gives the simple relationship between the reaction rates and the species concentrations. The assumptions made in the deterministic models are not hold true for the reactions involving chemical species of low concentration. The stochastic behaviour of the physicochemical processes can be modeled at mesoscopic level by application of the stochastic algorithms. In this paper a stochastic algorithm (Gillespie Tau Leap Method) developed in MATLAB was applied to predict the concentration of glucose, acids and methane formation at different time intervals. By this the performance of the digester system can be controlled. The processes given by ADM1 (Anaerobic Digestion Model 1) were taken for verification of the model. The proposed model was verified by comparing the results of Gillespie's algorithms with the deterministic solution for conversion of glucose into methane through degraders. At higher value of 'τ' (timestep), the computational time required for reaching the steady state is more since the number of chosen reactions is less. When the simulation time step is reduced, the results are similar to ODE solver. It was concluded that the stochastic algorithm is a suitable approach for the simulation of complex anaerobic digestion processes. The accuracy of the results depends on the optimum selection of tau value.
Fast and robust estimation of spectro-temporal receptive fields using stochastic approximations.
Meyer, Arne F; Diepenbrock, Jan-Philipp; Ohl, Frank W; Anemüller, Jörn
2015-05-15
The receptive field (RF) represents the signal preferences of sensory neurons and is the primary analysis method for understanding sensory coding. While it is essential to estimate a neuron's RF, finding numerical solutions to increasingly complex RF models can become computationally intensive, in particular for high-dimensional stimuli or when many neurons are involved. Here we propose an optimization scheme based on stochastic approximations that facilitate this task. The basic idea is to derive solutions on a random subset rather than computing the full solution on the available data set. To test this, we applied different optimization schemes based on stochastic gradient descent (SGD) to both the generalized linear model (GLM) and a recently developed classification-based RF estimation approach. Using simulated and recorded responses, we demonstrate that RF parameter optimization based on state-of-the-art SGD algorithms produces robust estimates of the spectro-temporal receptive field (STRF). Results on recordings from the auditory midbrain demonstrate that stochastic approximations preserve both predictive power and tuning properties of STRFs. A correlation of 0.93 with the STRF derived from the full solution may be obtained in less than 10% of the full solution's estimation time. We also present an on-line algorithm that allows simultaneous monitoring of STRF properties of more than 30 neurons on a single computer. The proposed approach may not only prove helpful for large-scale recordings but also provides a more comprehensive characterization of neural tuning in experiments than standard tuning curves. Copyright © 2015 Elsevier B.V. All rights reserved.
Temporal Order Processing in Adult Dyslexics.
Maxwell, David L.; And Others
This study investigated the premise that disordered temporal order perception in retarded readers can be seen in the serial processing of both nonverbal auditory and visual information, and examined whether such information processing deficits relate to level of reading ability. The adult subjects included 20 in the dyslexic group, 12 in the…
Random migration processes between two stochastic epidemic centers.
Sazonov, Igor; Kelbert, Mark; Gravenor, Michael B
2016-04-01
We consider the epidemic dynamics in stochastic interacting population centers coupled by random migration. Both the epidemic and the migration processes are modeled by Markov chains. We derive explicit formulae for the probability distribution of the migration process, and explore the dependence of outbreak patterns on initial parameters, population sizes and coupling parameters, using analytical and numerical methods. We show the importance of considering the movement of resident and visitor individuals separately. The mean field approximation for a general migration process is derived and an approximate method that allows the computation of statistical moments for networks with highly populated centers is proposed and tested numerically. Copyright © 2016 Elsevier Inc. All rights reserved.
Quantitative Sociodynamics Stochastic Methods and Models of Social Interaction Processes
Helbing, Dirk
2010-01-01
This new edition of Quantitative Sociodynamics presents a general strategy for interdisciplinary model building and its application to a quantitative description of behavioral changes based on social interaction processes. Originally, the crucial methods for the modeling of complex systems (stochastic methods and nonlinear dynamics) were developed in physics and mathematics, but they have very often proven their explanatory power in chemistry, biology, economics and the social sciences as well. Quantitative Sociodynamics provides a unified and comprehensive overview of the different stochastic methods, their interrelations and properties. In addition, it introduces important concepts from nonlinear dynamics (e.g. synergetics, chaos theory). The applicability of these fascinating concepts to social phenomena is carefully discussed. By incorporating decision-theoretical approaches, a fundamental dynamic model is obtained, which opens new perspectives in the social sciences. It includes many established models a...
Quantitative sociodynamics stochastic methods and models of social interaction processes
Helbing, Dirk
1995-01-01
Quantitative Sociodynamics presents a general strategy for interdisciplinary model building and its application to a quantitative description of behavioural changes based on social interaction processes. Originally, the crucial methods for the modeling of complex systems (stochastic methods and nonlinear dynamics) were developed in physics but they have very often proved their explanatory power in chemistry, biology, economics and the social sciences. Quantitative Sociodynamics provides a unified and comprehensive overview of the different stochastic methods, their interrelations and properties. In addition, it introduces the most important concepts from nonlinear dynamics (synergetics, chaos theory). The applicability of these fascinating concepts to social phenomena is carefully discussed. By incorporating decision-theoretical approaches a very fundamental dynamic model is obtained which seems to open new perspectives in the social sciences. It includes many established models as special cases, e.g. the log...
Multiple-scale stochastic processes: Decimation, averaging and beyond
Energy Technology Data Exchange (ETDEWEB)
Bo, Stefano, E-mail: stefano.bo@nordita.org [Nordita, KTH Royal Institute of Technology and Stockholm University, Roslagstullsbacken 23, SE-106 91 Stockholm (Sweden); Celani, Antonio [Quantitative Life Sciences, The Abdus Salam International Centre for Theoretical Physics (ICTP), Strada Costiera 11, I-34151 - Trieste (Italy)
2017-02-07
The recent experimental progresses in handling microscopic systems have allowed to probe them at levels where fluctuations are prominent, calling for stochastic modeling in a large number of physical, chemical and biological phenomena. This has provided fruitful applications for established stochastic methods and motivated further developments. These systems often involve processes taking place on widely separated time scales. For an efficient modeling one usually focuses on the slower degrees of freedom and it is of great importance to accurately eliminate the fast variables in a controlled fashion, carefully accounting for their net effect on the slower dynamics. This procedure in general requires to perform two different operations: decimation and coarse-graining. We introduce the asymptotic methods that form the basis of this procedure and discuss their application to a series of physical, biological and chemical examples. We then turn our attention to functionals of the stochastic trajectories such as residence times, counting statistics, fluxes, entropy production, etc. which have been increasingly studied in recent years. For such functionals, the elimination of the fast degrees of freedom can present additional difficulties and naive procedures can lead to blatantly inconsistent results. Homogenization techniques for functionals are less covered in the literature and we will pedagogically present them here, as natural extensions of the ones employed for the trajectories. We will also discuss recent applications of these techniques to the thermodynamics of small systems and their interpretation in terms of information-theoretic concepts.
Temporal Gillespie Algorithm: Fast Simulation of Contagion Processes on Time-Varying Networks.
Vestergaard, Christian L; Génois, Mathieu
2015-10-01
Stochastic simulations are one of the cornerstones of the analysis of dynamical processes on complex networks, and are often the only accessible way to explore their behavior. The development of fast algorithms is paramount to allow large-scale simulations. The Gillespie algorithm can be used for fast simulation of stochastic processes, and variants of it have been applied to simulate dynamical processes on static networks. However, its adaptation to temporal networks remains non-trivial. We here present a temporal Gillespie algorithm that solves this problem. Our method is applicable to general Poisson (constant-rate) processes on temporal networks, stochastically exact, and up to multiple orders of magnitude faster than traditional simulation schemes based on rejection sampling. We also show how it can be extended to simulate non-Markovian processes. The algorithm is easily applicable in practice, and as an illustration we detail how to simulate both Poissonian and non-Markovian models of epidemic spreading. Namely, we provide pseudocode and its implementation in C++ for simulating the paradigmatic Susceptible-Infected-Susceptible and Susceptible-Infected-Recovered models and a Susceptible-Infected-Recovered model with non-constant recovery rates. For empirical networks, the temporal Gillespie algorithm is here typically from 10 to 100 times faster than rejection sampling.
DEFF Research Database (Denmark)
Finlay, Chris; Olsen, Nils; Gillet, Nicolas
We present a new ensemble of time-dependent magnetic field models constructed from satellite and observatory data spanning 1997-2013 that are compatible with prior information concerning the temporal spectrum of core field variations. These models allow sharper field changes compared to tradition...... physical hypotheses can be tested by asking questions of the entire ensemble of core field models, rather than by interpreting any single model.......We present a new ensemble of time-dependent magnetic field models constructed from satellite and observatory data spanning 1997-2013 that are compatible with prior information concerning the temporal spectrum of core field variations. These models allow sharper field changes compared to traditional...... regularization methods based on minimizing the square of second or third time derivative. We invert satellite and observatory data directly by adopting the external field and crustal field modelling framework of the CHAOS model, but apply the stochastic process method of Gillet et al. (2013) to the core field...
Population density equations for stochastic processes with memory kernels
Lai, Yi Ming; de Kamps, Marc
2017-06-01
We present a method for solving population density equations (PDEs)-a mean-field technique describing homogeneous populations of uncoupled neurons—where the populations can be subject to non-Markov noise for arbitrary distributions of jump sizes. The method combines recent developments in two different disciplines that traditionally have had limited interaction: computational neuroscience and the theory of random networks. The method uses a geometric binning scheme, based on the method of characteristics, to capture the deterministic neurodynamics of the population, separating the deterministic and stochastic process cleanly. We can independently vary the choice of the deterministic model and the model for the stochastic process, leading to a highly modular numerical solution strategy. We demonstrate this by replacing the master equation implicit in many formulations of the PDE formalism by a generalization called the generalized Montroll-Weiss equation—a recent result from random network theory—describing a random walker subject to transitions realized by a non-Markovian process. We demonstrate the method for leaky- and quadratic-integrate and fire neurons subject to spike trains with Poisson and gamma-distributed interspike intervals. We are able to model jump responses for both models accurately to both excitatory and inhibitory input under the assumption that all inputs are generated by one renewal process.
Simulation of Stochastic Processes by Coupled ODE-PDE
Zak, Michail
2008-01-01
A document discusses the emergence of randomness in solutions of coupled, fully deterministic ODE-PDE (ordinary differential equations-partial differential equations) due to failure of the Lipschitz condition as a new phenomenon. It is possible to exploit the special properties of ordinary differential equations (represented by an arbitrarily chosen, dynamical system) coupled with the corresponding Liouville equations (used to describe the evolution of initial uncertainties in terms of joint probability distribution) in order to simulate stochastic processes with the proscribed probability distributions. The important advantage of the proposed approach is that the simulation does not require a random-number generator.
A theoretically consistent stochastic cascade for temporal disaggregation of intermittent rainfall
Lombardo, F.; Volpi, E.; Koutsoyiannis, D.; Serinaldi, F.
2017-06-01
Generating fine-scale time series of intermittent rainfall that are fully consistent with any given coarse-scale totals is a key and open issue in many hydrological problems. We propose a stationary disaggregation method that simulates rainfall time series with given dependence structure, wet/dry probability, and marginal distribution at a target finer (lower-level) time scale, preserving full consistency with variables at a parent coarser (higher-level) time scale. We account for the intermittent character of rainfall at fine time scales by merging a discrete stochastic representation of intermittency and a continuous one of rainfall depths. This approach yields a unique and parsimonious mathematical framework providing general analytical formulations of mean, variance, and autocorrelation function (ACF) for a mixed-type stochastic process in terms of mean, variance, and ACFs of both continuous and discrete components, respectively. To achieve the full consistency between variables at finer and coarser time scales in terms of marginal distribution and coarse-scale totals, the generated lower-level series are adjusted according to a procedure that does not affect the stochastic structure implied by the original model. To assess model performance, we study rainfall process as intermittent with both independent and dependent occurrences, where dependence is quantified by the probability that two consecutive time intervals are dry. In either case, we provide analytical formulations of main statistics of our mixed-type disaggregation model and show their clear accordance with Monte Carlo simulations. An application to rainfall time series from real world is shown as a proof of concept.
Directory of Open Access Journals (Sweden)
Francisco Costa
2013-07-01
Full Text Available The full-fledged processing of temporal information presents specific challenges. These difficulties largely stem from the fact that the temporal meaning conveyed by grammatical means interacts with many extra-linguistic factors (world knowledge, causality, calendar systems, reasoning. This article proposes a novel approach to this problem, based on a hybrid strategy that explores the complementarity of the symbolic and probabilistic methods. A specialized temporal extraction system is combined with a deep linguistic processing grammar. The temporal extraction system extracts eventualities, times and dates mentioned in text, and also temporal relations between them, in line with the tasks of the recent TempEval challenges; and uses machine learning techniques to draw from different sources of information (grammatical and extra-grammatical even if it is not explicitly known how these combine to produce the final temporal meaning being expressed. In turn, the deep computational grammar delivers richer truth-conditional meaning representations of input sentences, which include a principled representation of temporal information, on which higher level tasks, including reasoning, can be based. These deep semantic representations are extended and improved according to the output of the aforementioned temporal extraction module. The prototype implemented shows performance results that increase the quality of the temporal meaning representations and are better than the performance of each of the two components in isolation.
MODELLING AND SIMULATION OF A NEUROPHYSIOLOGICAL EXPERIMENT BY SPATIO-TEMPORAL POINT PROCESSES
Directory of Open Access Journals (Sweden)
Viktor Beneš
2011-05-01
Full Text Available We present a stochastic model of an experimentmonitoring the spiking activity of a place cell of hippocampus of an experimental animal moving in an arena. Doubly stochastic spatio-temporal point process is used to model and quantify overdispersion. Stochastic intensity is modelled by a Lévy based random field while the animal path is simplified to a discrete random walk. In a simulation study first a method suggested previously is used. Then it is shown that a solution of the filtering problem yields the desired inference to the random intensity. Two approaches are suggested and the new one based on finite point process density is applied. Using Markov chain Monte Carlo we obtain numerical results from the simulated model. The methodology is discussed.
Gupta, Chinmaya; López, José Manuel; Azencott, Robert; Bennett, Matthew R; Josić, Krešimir; Ott, William
2014-05-28
Delay is an important and ubiquitous aspect of many biochemical processes. For example, delay plays a central role in the dynamics of genetic regulatory networks as it stems from the sequential assembly of first mRNA and then protein. Genetic regulatory networks are therefore frequently modeled as stochastic birth-death processes with delay. Here, we examine the relationship between delay birth-death processes and their appropriate approximating delay chemical Langevin equations. We prove a quantitative bound on the error between the pathwise realizations of these two processes. Our results hold for both fixed delay and distributed delay. Simulations demonstrate that the delay chemical Langevin approximation is accurate even at moderate system sizes. It captures dynamical features such as the oscillatory behavior in negative feedback circuits, cross-correlations between nodes in a network, and spatial and temporal information in two commonly studied motifs of metastability in biochemical systems. Overall, these results provide a foundation for using delay stochastic differential equations to approximate the dynamics of birth-death processes with delay.
Energy Technology Data Exchange (ETDEWEB)
Gupta, Chinmaya; López, José Manuel; Azencott, Robert; Ott, William [Department of Mathematics, University of Houston, Houston, Texas 77004 (United States); Bennett, Matthew R. [Department of Biochemistry and Cell Biology, Rice University, Houston, Texas 77204, USA and Institute of Biosciences and Bioengineering, Rice University, Houston, Texas 77005 (United States); Josić, Krešimir [Department of Mathematics, University of Houston, Houston, Texas 77004 (United States); Department of Biology and Biochemistry, University of Houston, Houston, Texas 77204 (United States)
2014-05-28
Delay is an important and ubiquitous aspect of many biochemical processes. For example, delay plays a central role in the dynamics of genetic regulatory networks as it stems from the sequential assembly of first mRNA and then protein. Genetic regulatory networks are therefore frequently modeled as stochastic birth-death processes with delay. Here, we examine the relationship between delay birth-death processes and their appropriate approximating delay chemical Langevin equations. We prove a quantitative bound on the error between the pathwise realizations of these two processes. Our results hold for both fixed delay and distributed delay. Simulations demonstrate that the delay chemical Langevin approximation is accurate even at moderate system sizes. It captures dynamical features such as the oscillatory behavior in negative feedback circuits, cross-correlations between nodes in a network, and spatial and temporal information in two commonly studied motifs of metastability in biochemical systems. Overall, these results provide a foundation for using delay stochastic differential equations to approximate the dynamics of birth-death processes with delay.
International Nuclear Information System (INIS)
Gupta, Chinmaya; López, José Manuel; Azencott, Robert; Ott, William; Bennett, Matthew R.; Josić, Krešimir
2014-01-01
Delay is an important and ubiquitous aspect of many biochemical processes. For example, delay plays a central role in the dynamics of genetic regulatory networks as it stems from the sequential assembly of first mRNA and then protein. Genetic regulatory networks are therefore frequently modeled as stochastic birth-death processes with delay. Here, we examine the relationship between delay birth-death processes and their appropriate approximating delay chemical Langevin equations. We prove a quantitative bound on the error between the pathwise realizations of these two processes. Our results hold for both fixed delay and distributed delay. Simulations demonstrate that the delay chemical Langevin approximation is accurate even at moderate system sizes. It captures dynamical features such as the oscillatory behavior in negative feedback circuits, cross-correlations between nodes in a network, and spatial and temporal information in two commonly studied motifs of metastability in biochemical systems. Overall, these results provide a foundation for using delay stochastic differential equations to approximate the dynamics of birth-death processes with delay
Time Series, Stochastic Processes and Completeness of Quantum Theory
International Nuclear Information System (INIS)
Kupczynski, Marian
2011-01-01
Most of physical experiments are usually described as repeated measurements of some random variables. Experimental data registered by on-line computers form time series of outcomes. The frequencies of different outcomes are compared with the probabilities provided by the algorithms of quantum theory (QT). In spite of statistical predictions of QT a claim was made that it provided the most complete description of the data and of the underlying physical phenomena. This claim could be easily rejected if some fine structures, averaged out in the standard descriptive statistical analysis, were found in time series of experimental data. To search for these structures one has to use more subtle statistical tools which were developed to study time series produced by various stochastic processes. In this talk we review some of these tools. As an example we show how the standard descriptive statistical analysis of the data is unable to reveal a fine structure in a simulated sample of AR (2) stochastic process. We emphasize once again that the violation of Bell inequalities gives no information on the completeness or the non locality of QT. The appropriate way to test the completeness of quantum theory is to search for fine structures in time series of the experimental data by means of the purity tests or by studying the autocorrelation and partial autocorrelation functions.
Evolution and mass extinctions as lognormal stochastic processes
Maccone, Claudio
2014-10-01
In a series of recent papers and in a book, this author put forward a mathematical model capable of embracing the search for extra-terrestrial intelligence (SETI), Darwinian Evolution and Human History into a single, unified statistical picture, concisely called Evo-SETI. The relevant mathematical tools are: (1) Geometric Brownian motion (GBM), the stochastic process representing evolution as the stochastic increase of the number of species living on Earth over the last 3.5 billion years. This GBM is well known in the mathematics of finances (Black-Sholes models). Its main features are that its probability density function (pdf) is a lognormal pdf, and its mean value is either an increasing or, more rarely, decreasing exponential function of the time. (2) The probability distributions known as b-lognormals, i.e. lognormals starting at a certain positive instant b>0 rather than at the origin. These b-lognormals were then forced by us to have their peak value located on the exponential mean-value curve of the GBM (Peak-Locus theorem). In the framework of Darwinian Evolution, the resulting mathematical construction was shown to be what evolutionary biologists call Cladistics. (3) The (Shannon) entropy of such b-lognormals is then seen to represent the `degree of progress' reached by each living organism or by each big set of living organisms, like historic human civilizations. Having understood this fact, human history may then be cast into the language of b-lognormals that are more and more organized in time (i.e. having smaller and smaller entropy, or smaller and smaller `chaos'), and have their peaks on the increasing GBM exponential. This exponential is thus the `trend of progress' in human history. (4) All these results also match with SETI in that the statistical Drake equation (generalization of the ordinary Drake equation to encompass statistics) leads just to the lognormal distribution as the probability distribution for the number of extra
Suprathreshold stochastic resonance in neural processing tuned by correlation.
Durrant, Simon; Kang, Yanmei; Stocks, Nigel; Feng, Jianfeng
2011-07-01
Suprathreshold stochastic resonance (SSR) is examined in the context of integrate-and-fire neurons, with an emphasis on the role of correlation in the neuronal firing. We employed a model based on a network of spiking neurons which received synaptic inputs modeled by Poisson processes stimulated by a stepped input signal. The smoothed ensemble firing rate provided an output signal, and the mutual information between this signal and the input was calculated for networks with different noise levels and different numbers of neurons. It was found that an SSR effect was present in this context. We then examined a more biophysically plausible scenario where the noise was not controlled directly, but instead was tuned by the correlation between the inputs. The SSR effect remained present in this scenario with nonzero noise providing improved information transmission, and it was found that negative correlation between the inputs was optimal. Finally, an examination of SSR in the context of this model revealed its connection with more traditional stochastic resonance and showed a trade-off between supratheshold and subthreshold components. We discuss these results in the context of existing empirical evidence concerning correlations in neuronal firing.
Stochastic investigation of precipitation process for climatic variability identification
Sotiriadou, Alexia; Petsiou, Amalia; Feloni, Elisavet; Kastis, Paris; Iliopoulou, Theano; Markonis, Yannis; Tyralis, Hristos; Dimitriadis, Panayiotis; Koutsoyiannis, Demetris
2016-04-01
The precipitation process is important not only to hydrometeorology but also to renewable energy resources management. We use a dataset consisting of daily and hourly records around the globe to identify statistical variability with emphasis on the last period. Specifically, we investigate the occurrence of mean, maximum and minimum values and we estimate statistical properties such as marginal probability distribution function and the type of decay of the climacogram (i.e., mean process variance vs. scale). Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.
Time-variant reliability assessment through equivalent stochastic process transformation
International Nuclear Information System (INIS)
Wang, Zequn; Chen, Wei
2016-01-01
Time-variant reliability measures the probability that an engineering system successfully performs intended functions over a certain period of time under various sources of uncertainty. In practice, it is computationally prohibitive to propagate uncertainty in time-variant reliability assessment based on expensive or complex numerical models. This paper presents an equivalent stochastic process transformation approach for cost-effective prediction of reliability deterioration over the life cycle of an engineering system. To reduce the high dimensionality, a time-independent reliability model is developed by translating random processes and time parameters into random parameters in order to equivalently cover all potential failures that may occur during the time interval of interest. With the time-independent reliability model, an instantaneous failure surface is attained by using a Kriging-based surrogate model to identify all potential failure events. To enhance the efficacy of failure surface identification, a maximum confidence enhancement method is utilized to update the Kriging model sequentially. Then, the time-variant reliability is approximated using Monte Carlo simulations of the Kriging model where system failures over a time interval are predicted by the instantaneous failure surface. The results of two case studies demonstrate that the proposed approach is able to accurately predict the time evolution of system reliability while requiring much less computational efforts compared with the existing analytical approach. - Highlights: • Developed a new approach for time-variant reliability analysis. • Proposed a novel stochastic process transformation procedure to reduce the dimensionality. • Employed Kriging models with confidence-based adaptive sampling scheme to enhance computational efficiency. • The approach is effective for handling random process in time-variant reliability analysis. • Two case studies are used to demonstrate the efficacy
Analysis of Stochastic Radio Channels with Temporal Birth-Death Dynamics
DEFF Research Database (Denmark)
Jakobsen, Morten Lomholt; Pedersen, Troels; Fleury, Bernard Henri
2014-01-01
). The proof of this result is a consequence of the point process perspective, in particular by circumventing enumeration issues arising from the use of integer-indexed path components in traditional channel modeling approaches. The practical importance of being able to analytically characterize the birth......, with the underlying stochastic birth-death mechanism governed by two facilitating assumptions. Well-known analytical properties of this class of channel models are reestablished by simple arguments and several new results are derived. The primary tool used to obtain these results is Campbell's Theorem which enables......-death channel models is clearly evidenced, e.g., by the fact that key parameters enter explicitly in measurable quantities such as the power-delay profile....
QUANTUM STOCHASTIC PROCESSES: BOSON AND FERMION BROWNIAN MOTION
Directory of Open Access Journals (Sweden)
A.E.Kobryn
2003-01-01
Full Text Available Dynamics of quantum systems which are stochastically perturbed by linear coupling to the reservoir can be studied in terms of quantum stochastic differential equations (for example, quantum stochastic Liouville equation and quantum Langevin equation. In order to work it out one needs to define the quantum Brownian motion. As far as only its boson version has been known until recently, in the present paper we present the definition which makes it possible to consider the fermion Brownian motion as well.
A measure theoretical approach to quantum stochastic processes
Energy Technology Data Exchange (ETDEWEB)
Waldenfels, Wilhelm von
2014-04-01
Authored by a leading researcher in the field. Self-contained presentation of the subject matter. Examines a number of worked examples in detail. This monograph takes as starting point that abstract quantum stochastic processes can be understood as a quantum field theory in one space and in one time coordinate. As a result it is appropriate to represent operators as power series of creation and annihilation operators in normal-ordered form, which can be achieved using classical measure theory. Considering in detail four basic examples (e.g. a two-level atom coupled to a heat bath of oscillators), in each case the Hamiltonian of the associated one-parameter strongly continuous group is determined and the spectral decomposition is explicitly calculated in the form of generalized eigen-vectors. Advanced topics include the theory of the Hudson-Parthasarathy equation and the amplified oscillator problem. To that end, a chapter on white noise calculus has also been included.
Stochastic calculus for fractional Brownian motion and related processes
Mishura, Yuliya S
2008-01-01
The theory of fractional Brownian motion and other long-memory processes are addressed in this volume. Interesting topics for PhD students and specialists in probability theory, stochastic analysis and financial mathematics demonstrate the modern level of this field. Among these are results about Levy characterization of fractional Brownian motion, maximal moment inequalities for Wiener integrals including the values 0
Kolmogorov's refined similarity hypotheses for turbulence and general stochastic processes
International Nuclear Information System (INIS)
Stolovitzky, G.; Sreenivasan, K.R.
1994-01-01
Kolmogorov's refined similarity hypotheses are shown to hold true for a variety of stochastic processes besides high-Reynolds-number turbulent flows, for which they were originally proposed. In particular, just as hypothesized for turbulence, there exists a variable V whose probability density function attains a universal form. Analytical expressions for the probability density function of V are obtained for Brownian motion as well as for the general case of fractional Brownian motion---the latter under some mild assumptions justified a posteriori. The properties of V for the case of antipersistent fractional Brownian motion with the Hurst exponent of 1/3 are similar in many details to those of high-Reynolds-number turbulence in atmospheric boundary layers a few meters above the ground. The one conspicuous difference between turbulence and the antipersistent fractional Brownian motion is that the latter does not possess the required skewness. Broad implications of these results are discussed
A measure theoretical approach to quantum stochastic processes
Von Waldenfels, Wilhelm
2014-01-01
This monograph takes as starting point that abstract quantum stochastic processes can be understood as a quantum field theory in one space and in one time coordinate. As a result it is appropriate to represent operators as power series of creation and annihilation operators in normal-ordered form, which can be achieved using classical measure theory. Considering in detail four basic examples (e.g. a two-level atom coupled to a heat bath of oscillators), in each case the Hamiltonian of the associated one-parameter strongly continuous group is determined and the spectral decomposition is explicitly calculated in the form of generalized eigen-vectors. Advanced topics include the theory of the Hudson-Parthasarathy equation and the amplified oscillator problem. To that end, a chapter on white noise calculus has also been included.
Díaz Fernández, Ester
2010-01-01
In this thesis, new models and methodologies are introduced for the analysis of dynamic processes characterized by image sequences with spatial temporal overlapping. The spatial temporal overlapping exists in many natural phenomena and should be addressed properly in several Science disciplines such as Microscopy, Material Sciences, Biology, Geostatistics or Communication Networks. This work is related to the Point Process and Random Closed Set theories, within Stochastic Ge...
SUPERPOSITION OF STOCHASTIC PROCESSES AND THE RESULTING PARTICLE DISTRIBUTIONS
International Nuclear Information System (INIS)
Schwadron, N. A.; Dayeh, M. A.; Desai, M.; Fahr, H.; Jokipii, J. R.; Lee, M. A.
2010-01-01
Many observations of suprathermal and energetic particles in the solar wind and the inner heliosheath show that distribution functions scale approximately with the inverse of particle speed (v) to the fifth power. Although there are exceptions to this behavior, there is a growing need to understand why this type of distribution function appears so frequently. This paper develops the concept that a superposition of exponential and Gaussian distributions with different characteristic speeds and temperatures show power-law tails. The particular type of distribution function, f ∝ v -5 , appears in a number of different ways: (1) a series of Poisson-like processes where entropy is maximized with the rates of individual processes inversely proportional to the characteristic exponential speed, (2) a series of Gaussian distributions where the entropy is maximized with the rates of individual processes inversely proportional to temperature and the density of individual Gaussian distributions proportional to temperature, and (3) a series of different diffusively accelerated energetic particle spectra with individual spectra derived from observations (1997-2002) of a multiplicity of different shocks. Thus, we develop a proof-of-concept for the superposition of stochastic processes that give rise to power-law distribution functions.
Stochastic process corrosion growth models for pipeline reliability
International Nuclear Information System (INIS)
Bazán, Felipe Alexander Vargas; Beck, André Teófilo
2013-01-01
Highlights: •Novel non-linear stochastic process corrosion growth model is proposed. •Corrosion rate modeled as random Poisson pulses. •Time to corrosion initiation and inherent time-variability properly represented. •Continuous corrosion growth histories obtained. •Model is shown to precisely fit actual corrosion data at two time points. -- Abstract: Linear random variable corrosion models are extensively employed in reliability analysis of pipelines. However, linear models grossly neglect well-known characteristics of the corrosion process. Herein, a non-linear model is proposed, where corrosion rate is represented as a Poisson square wave process. The resulting model represents inherent time-variability of corrosion growth, produces continuous growth and leads to mean growth at less-than-one power of time. Different corrosion models are adjusted to the same set of actual corrosion data for two inspections. The proposed non-linear random process corrosion growth model leads to the best fit to the data, while better representing problem physics
Profiles of the stochastic star formation process in spiral galaxies
International Nuclear Information System (INIS)
Comins, N.
1981-01-01
The formation of spiral arms in disc galaxies is generally attributed to the effects of spiral density waves. These relatively small (i.e. 5 per cent) non-axisymmetric perturbations of the interstellar medium cause spiral arms highlighted by O and B type stars to be created. In this paper another mechanism for spiral arm formation, the stochastic self-propagating star formation (SSPSF) process is examined. The SSPSF process combines the theory that shock waves from supernovae will compress the interstellar medium to create new stars, some of which will be massive enough to also supernova, with a disc galaxy's differential rotation to create spiral arms. The present work extends this process to the case where the probability of star formation from supernova shocks decreases with galactic radius. Where this work and previous investigations overlap (namely the uniform probability case), the agreement is very good, pretty spirals with various numbers of arms are generated. The decreasing probability cases, taken to vary as rsup(-j), still form spiral arms for 0 1.5 the spiral structure is essentially non-existent. (author)
Heterogeneous recurrence monitoring and control of nonlinear stochastic processes
Energy Technology Data Exchange (ETDEWEB)
Yang, Hui, E-mail: huiyang@usf.edu; Chen, Yun [Complex Systems Monitoring, Modeling and Analysis Laboratory, University of South Florida, Tampa, Florida 33620 (United States)
2014-03-15
Recurrence is one of the most common phenomena in natural and engineering systems. Process monitoring of dynamic transitions in nonlinear and nonstationary systems is more concerned with aperiodic recurrences and recurrence variations. However, little has been done to investigate the heterogeneous recurrence variations and link with the objectives of process monitoring and anomaly detection. Notably, nonlinear recurrence methodologies are based on homogeneous recurrences, which treat all recurrence states in the same way as black dots, and non-recurrence is white in recurrence plots. Heterogeneous recurrences are more concerned about the variations of recurrence states in terms of state properties (e.g., values and relative locations) and the evolving dynamics (e.g., sequential state transitions). This paper presents a novel approach of heterogeneous recurrence analysis that utilizes a new fractal representation to delineate heterogeneous recurrence states in multiple scales, including the recurrences of both single states and multi-state sequences. Further, we developed a new set of heterogeneous recurrence quantifiers that are extracted from fractal representation in the transformed space. To that end, we integrated multivariate statistical control charts with heterogeneous recurrence analysis to simultaneously monitor two or more related quantifiers. Experimental results on nonlinear stochastic processes show that the proposed approach not only captures heterogeneous recurrence patterns in the fractal representation but also effectively monitors the changes in the dynamics of a complex system.
Stochastic simulation of destruction processes in self-irradiated materials
Directory of Open Access Journals (Sweden)
T. Patsahan
2017-09-01
Full Text Available Self-irradiation damages resulting from fission processes are common phenomena observed in nuclear fuel containing (NFC materials. Numerous α-decays lead to local structure transformations in NFC materials. The damages appearing due to the impacts of heavy nuclear recoils in the subsurface layer can cause detachments of material particles. Such a behaviour is similar to sputtering processes observed during a bombardment of the material surface by a flux of energetic particles. However, in the NFC material, the impacts are initiated from the bulk. In this work we propose a two-dimensional mesoscopic model to perform a stochastic simulation of the destruction processes occurring in a subsurface region of NFC material. We describe the erosion of the material surface, the evolution of its roughness and predict the detachment of the material particles. Size distributions of the emitted particles are obtained in this study. The simulation results of the model are in a qualitative agreement with the size histogram of particles produced from the material containing lava-like fuel formed during the Chernobyl nuclear power plant disaster.
Stochastic model of template-directed elongation processes in biology.
Schilstra, Maria J; Nehaniv, Chrystopher L
2010-10-01
We present a novel modular, stochastic model for biological template-based linear chain elongation processes. In this model, elongation complexes (ECs; DNA polymerase, RNA polymerase, or ribosomes associated with nascent chains) that span a finite number of template units step along the template, one after another, with semaphore constructs preventing overtaking. The central elongation module is readily extended with modules that represent initiation and termination processes. The model was used to explore the effect of EC span on motor velocity and dispersion, and the effect of initiation activator and repressor binding kinetics on the overall elongation dynamics. The results demonstrate that (1) motors that move smoothly are able to travel at a greater velocity and closer together than motors that move more erratically, and (2) the rate at which completed chains are released is proportional to the occupancy or vacancy of activator or repressor binding sites only when initiation or activator/repressor dissociation is slow in comparison with elongation. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
Stochastic growth logistic model with aftereffect for batch fermentation process
Rosli, Norhayati; Ayoubi, Tawfiqullah; Bahar, Arifah; Rahman, Haliza Abdul; Salleh, Madihah Md
2014-06-01
In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits.
Stochastic growth logistic model with aftereffect for batch fermentation process
International Nuclear Information System (INIS)
Rosli, Norhayati; Ayoubi, Tawfiqullah; Bahar, Arifah; Rahman, Haliza Abdul; Salleh, Madihah Md
2014-01-01
In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits
Stochastic growth logistic model with aftereffect for batch fermentation process
Energy Technology Data Exchange (ETDEWEB)
Rosli, Norhayati; Ayoubi, Tawfiqullah [Faculty of Industrial Sciences and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300 Gambang, Pahang (Malaysia); Bahar, Arifah; Rahman, Haliza Abdul [Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor (Malaysia); Salleh, Madihah Md [Department of Biotechnology Industry, Faculty of Biosciences and Bioengineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor (Malaysia)
2014-06-19
In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits.
Stochastic Modelling, Analysis, and Simulations of the Solar Cycle Dynamic Process
Turner, Douglas C.; Ladde, Gangaram S.
2018-03-01
Analytical solutions, discretization schemes and simulation results are presented for the time delay deterministic differential equation model of the solar dynamo presented by Wilmot-Smith et al. In addition, this model is extended under stochastic Gaussian white noise parametric fluctuations. The introduction of stochastic fluctuations incorporates variables affecting the dynamo process in the solar interior, estimation error of parameters, and uncertainty of the α-effect mechanism. Simulation results are presented and analyzed to exhibit the effects of stochastic parametric volatility-dependent perturbations. The results generalize and extend the work of Hazra et al. In fact, some of these results exhibit the oscillatory dynamic behavior generated by the stochastic parametric additative perturbations in the absence of time delay. In addition, the simulation results of the modified stochastic models influence the change in behavior of the very recently developed stochastic model of Hazra et al.
Lei, Youming; Zheng, Fan
2016-12-01
Stochastic chaos induced by diffusion processes, with identical spectral density but different probability density functions (PDFs), is investigated in selected lightly damped Hamiltonian systems. The threshold amplitude of diffusion processes for the onset of chaos is derived by using the stochastic Melnikov method together with a mean-square criterion. Two quasi-Hamiltonian systems, namely, a damped single pendulum and damped Duffing oscillator perturbed by stochastic excitations, are used as illustrative examples. Four different cases of stochastic processes are taking as the driving excitations. It is shown that in such two systems the spectral density of diffusion processes completely determines the threshold amplitude for chaos, regardless of the shape of their PDFs, Gaussian or otherwise. Furthermore, the mean top Lyapunov exponent is employed to verify analytical results. The results obtained by numerical simulations are in accordance with the analytical results. This demonstrates that the stochastic Melnikov method is effective in predicting the onset of chaos in the quasi-Hamiltonian systems.
Stochastic volatility and stochastic leverage
DEFF Research Database (Denmark)
Veraart, Almut; Veraart, Luitgard A. M.
This paper proposes the new concept of stochastic leverage in stochastic volatility models. Stochastic leverage refers to a stochastic process which replaces the classical constant correlation parameter between the asset return and the stochastic volatility process. We provide a systematic...... treatment of stochastic leverage and propose to model the stochastic leverage effect explicitly, e.g. by means of a linear transformation of a Jacobi process. Such models are both analytically tractable and allow for a direct economic interpretation. In particular, we propose two new stochastic volatility...... models which allow for a stochastic leverage effect: the generalised Heston model and the generalised Barndorff-Nielsen & Shephard model. We investigate the impact of a stochastic leverage effect in the risk neutral world by focusing on implied volatilities generated by option prices derived from our new...
Stochastic Modelling of Shiroro River Stream flow Process
Musa, J. J
2013-01-01
Economists, social scientists and engineers provide insights into the drivers of anthropogenic climate change and the options for adaptation and mitigation, and yet other scientists, including geographers and biologists, study the impacts of climate change. This project concentrates mainly on the discharge from the Shiroro River. A stochastic approach is presented for modeling a time series by an Autoregressive Moving Average model (ARMA). The development and use of a stochastic stream flow m...
Simulating biological processes: stochastic physics from whole cells to colonies
Earnest, Tyler M.; Cole, John A.; Luthey-Schulten, Zaida
2018-05-01
The last few decades have revealed the living cell to be a crowded spatially heterogeneous space teeming with biomolecules whose concentrations and activities are governed by intrinsically random forces. It is from this randomness, however, that a vast array of precisely timed and intricately coordinated biological functions emerge that give rise to the complex forms and behaviors we see in the biosphere around us. This seemingly paradoxical nature of life has drawn the interest of an increasing number of physicists, and recent years have seen stochastic modeling grow into a major subdiscipline within biological physics. Here we review some of the major advances that have shaped our understanding of stochasticity in biology. We begin with some historical context, outlining a string of important experimental results that motivated the development of stochastic modeling. We then embark upon a fairly rigorous treatment of the simulation methods that are currently available for the treatment of stochastic biological models, with an eye toward comparing and contrasting their realms of applicability, and the care that must be taken when parameterizing them. Following that, we describe how stochasticity impacts several key biological functions, including transcription, translation, ribosome biogenesis, chromosome replication, and metabolism, before considering how the functions may be coupled into a comprehensive model of a ‘minimal cell’. Finally, we close with our expectation for the future of the field, focusing on how mesoscopic stochastic methods may be augmented with atomic-scale molecular modeling approaches in order to understand life across a range of length and time scales.
Weiss, Charles J.
2017-01-01
An introduction to digital stochastic simulations for modeling a variety of physical and chemical processes is presented. Despite the importance of stochastic simulations in chemistry, the prevalence of turn-key software solutions can impose a layer of abstraction between the user and the underlying approach obscuring the methodology being…
Kozachenko, Yuriy; Troshki, Viktor
2015-01-01
We consider a measurable stationary Gaussian stochastic process. A criterion for testing hypotheses about the covariance function of such a process using estimates for its norm in the space $L_p(\\mathbb {T}),\\,p\\geq1$, is constructed.
Modified stochastic fragmentation of an interval as an ageing process
Fortin, Jean-Yves
2018-02-01
We study a stochastic model based on modified fragmentation of a finite interval. The mechanism consists of cutting the interval at a random location and substituting a unique fragment on the right of the cut to regenerate and preserve the interval length. This leads to a set of segments of random sizes, with the accumulation of small fragments near the origin. This model is an example of record dynamics, with the presence of ‘quakes’ and slow dynamics. The fragment size distribution is a universal inverse power law with logarithmic corrections. The exact distribution for the fragment number as function of time is simply related to the unsigned Stirling numbers of the first kind. Two-time correlation functions are defined, and computed exactly. They satisfy scaling relations, and exhibit aging phenomena. In particular, the probability that the same number of fragments is found at two different times t>s is asymptotically equal to [4πlog(s)]-1/2 when s\\gg 1 and the ratio t/s is fixed, in agreement with the numerical simulations. The same process with a reset impedes the aging phenomenon-beyond a typical time scale defined by the reset parameter.
International Nuclear Information System (INIS)
Granita; Bahar, A.
2015-01-01
This paper discusses on linear birth and death with immigration and emigration (BIDE) process to stochastic differential equation (SDE) model. Forward Kolmogorov equation in continuous time Markov chain (CTMC) with a central-difference approximation was used to find Fokker-Planckequation corresponding to a diffusion process having the stochastic differential equation of BIDE process. The exact solution, mean and variance function of BIDE process was found
Energy Technology Data Exchange (ETDEWEB)
Granita, E-mail: granitafc@gmail.com [Dept. Mathematical Education, State Islamic University of Sultan Syarif Kasim Riau, 28293 Indonesia and Dept. of Mathematical Science, Universiti Teknologi Malaysia, 81310,Johor (Malaysia); Bahar, A. [Dept. of Mathematical Science, Universiti Teknologi Malaysia, 81310,Johor Malaysia and UTM Center for Industrial and Applied Mathematics (UTM-CIAM) (Malaysia)
2015-03-09
This paper discusses on linear birth and death with immigration and emigration (BIDE) process to stochastic differential equation (SDE) model. Forward Kolmogorov equation in continuous time Markov chain (CTMC) with a central-difference approximation was used to find Fokker-Planckequation corresponding to a diffusion process having the stochastic differential equation of BIDE process. The exact solution, mean and variance function of BIDE process was found.
Stochastic stability of mechanical systems under renewal jump process parametric excitation
DEFF Research Database (Denmark)
Iwankiewicz, R.; Nielsen, Søren R.K.; Larsen, Jesper Winther
2005-01-01
independent, negative exponential distributed variables; hence, the arrival process may be termed as a generalized Erlang renewal process. The excitation process is governed by the stochastic equation driven by two independent Poisson processes, with different parameters. If the response in a single mode...... is investigated, the problem is governed in the state space by two stochastic equations, because the stochastic equation for the excitation process is autonomic. However due to the parametric nature of the excitation, the nonlinear term appears at the right-hand sides of the equations. The equations become linear...... of the stochastic equation governing the natural logarithm of the hyperspherical amplitude process and using the modification of the method wherein the time averaging of the pertinent expressions is replaced by ensemble averaging. It is found that the direct simulation is more suitable and that the asymptotic mean...
Temporal processes involved in simultaneous reflection masking
DEFF Research Database (Denmark)
Buchholz, Jörg
2006-01-01
reflection delays and enhances the test reflection for large delays. Employing a 200-ms-long broadband noise burst as input signal, the critical delay separating these two binaural phenomena was found to be 7–10 ms. It was suggested that the critical delay refers to a temporal window that is employed......, resulting in a critical delay of about 2–3 ms for 20-ms-long stimuli. Hence, for very short stimuli the temporal window or critical delay exhibits values similar to the auditory temporal resolution as, for instance, observed in gap-detection tasks. It is suggested that the larger critical delay observed...
ARMA modeling of stochastic processes in nuclear reactor with significant detection noise
International Nuclear Information System (INIS)
Zavaljevski, N.
1992-01-01
The theoretical basis of ARMA modelling of stochastic processes in nuclear reactor was presented in a previous paper, neglecting observational noise. The identification of real reactor data indicated that in some experiments the detection noise is significant. Thus a more rigorous theoretical modelling of stochastic processes in nuclear reactor is performed. Starting from the fundamental stochastic differential equations of the Langevin type for the interaction of the detector with neutron field, a new theoretical ARMA model is developed. preliminary identification results confirm the theoretical expectations. (author)
Stochastic processes analysis in nuclear reactor using ARMA models
International Nuclear Information System (INIS)
Zavaljevski, N.
1990-01-01
The analysis of ARMA model derived from general stochastic state equations of nuclear reactor is given. The dependence of ARMA model parameters on the main physical characteristics of RB nuclear reactor in Vinca is presented. Preliminary identification results are presented, observed discrepancies between theory and experiment are explained and the possibilities of identification improvement are anticipated. (author)
Stochastic Modeling and Deterministic Limit of Catalytic Surface Processes
DEFF Research Database (Denmark)
Starke, Jens; Reichert, Christian; Eiswirth, Markus
2007-01-01
of stochastic origin can be observed in experiments. The models include a new approach to the platinum phase transition, which allows for a unification of existing models for Pt(100) and Pt(110). The rich nonlinear dynamical behavior of the macroscopic reaction kinetics is investigated and shows good agreement...
Stochastic process variation in deep-submicron CMOS circuits and algorithms
Zjajo, Amir
2014-01-01
One of the most notable features of nanometer scale CMOS technology is the increasing magnitude of variability of the key device parameters affecting performance of integrated circuits. The growth of variability can be attributed to multiple factors, including the difficulty of manufacturing control, the emergence of new systematic variation-generating mechanisms, and most importantly, the increase in atomic-scale randomness, where device operation must be described as a stochastic process. In addition to wide-sense stationary stochastic device variability and temperature variation, existence of non-stationary stochastic electrical noise associated with fundamental processes in integrated-circuit devices represents an elementary limit on the performance of electronic circuits. In an attempt to address these issues, Stochastic Process Variation in Deep-Submicron CMOS: Circuits and Algorithms offers unique combination of mathematical treatment of random process variation, electrical noise and temperature and ne...
Identification of AR(I)MA processes for modelling temporal correlations of GPS observations
Luo, X.; Mayer, M.; Heck, B.
2009-04-01
In many geodetic applications observations of the Global Positioning System (GPS) are routinely processed by means of the least-squares method. However, this algorithm delivers reliable estimates of unknown parameters und realistic accuracy measures only if both the functional and stochastic models are appropriately defined within GPS data processing. One deficiency of the stochastic model used in many GPS software products consists in neglecting temporal correlations of GPS observations. In practice the knowledge of the temporal stochastic behaviour of GPS observations can be improved by analysing time series of residuals resulting from the least-squares evaluation. This paper presents an approach based on the theory of autoregressive (integrated) moving average (AR(I)MA) processes to model temporal correlations of GPS observations using time series of observation residuals. A practicable integration of AR(I)MA models in GPS data processing requires the determination of the order parameters of AR(I)MA processes at first. In case of GPS, the identification of AR(I)MA processes could be affected by various factors impacting GPS positioning results, e.g. baseline length, multipath effects, observation weighting, or weather variations. The influences of these factors on AR(I)MA identification are empirically analysed based on a large amount of representative residual time series resulting from differential GPS post-processing using 1-Hz observation data collected within the permanent SAPOS® (Satellite Positioning Service of the German State Survey) network. Both short and long time series are modelled by means of AR(I)MA processes. The final order parameters are determined based on the whole residual database; the corresponding empirical distribution functions illustrate that multipath and weather variations seem to affect the identification of AR(I)MA processes much more significantly than baseline length and observation weighting. Additionally, the modelling
Directory of Open Access Journals (Sweden)
Rice Sean H
2008-09-01
Full Text Available Abstract Background Evolution involves both deterministic and random processes, both of which are known to contribute to directional evolutionary change. A number of studies have shown that when fitness is treated as a random variable, meaning that each individual has a distribution of possible fitness values, then both the mean and variance of individual fitness distributions contribute to directional evolution. Unfortunately the most general mathematical description of evolution that we have, the Price equation, is derived under the assumption that both fitness and offspring phenotype are fixed values that are known exactly. The Price equation is thus poorly equipped to study an important class of evolutionary processes. Results I present a general equation for directional evolutionary change that incorporates both deterministic and stochastic processes and applies to any evolving system. This is essentially a stochastic version of the Price equation, but it is derived independently and contains terms with no analog in Price's formulation. This equation shows that the effects of selection are actually amplified by random variation in fitness. It also generalizes the known tendency of populations to be pulled towards phenotypes with minimum variance in fitness, and shows that this is matched by a tendency to be pulled towards phenotypes with maximum positive asymmetry in fitness. This equation also contains a term, having no analog in the Price equation, that captures cases in which the fitness of parents has a direct effect on the phenotype of their offspring. Conclusion Directional evolution is influenced by the entire distribution of individual fitness, not just the mean and variance. Though all moments of individuals' fitness distributions contribute to evolutionary change, the ways that they do so follow some general rules. These rules are invisible to the Price equation because it describes evolution retrospectively. An equally general
Susceptibility of optimal train schedules to stochastic disturbances of process times
DEFF Research Database (Denmark)
Larsen, Rune; Pranzo, Marco; D’Ariano, Andrea
2013-01-01
study, an advanced branch and bound algorithm, on average, outperforms a First In First Out scheduling rule both in deterministic and stochastic traffic scenarios. However, the characteristic of the stochastic processes and the way a stochastic instance is handled turn out to have a serious impact...... and dwell times). In fact, the objective of railway traffic management is to reduce delay propagation and to increase disturbance robustness of train schedules at a network scale. We present a quantitative study of traffic disturbances and their effects on the schedules computed by simple and advanced...
Principles of Temporal Processing Across the Cortical Hierarchy.
Himberger, Kevin D; Chien, Hsiang-Yun; Honey, Christopher J
2018-05-02
The world is richly structured on multiple spatiotemporal scales. In order to represent spatial structure, many machine-learning models repeat a set of basic operations at each layer of a hierarchical architecture. These iterated spatial operations - including pooling, normalization and pattern completion - enable these systems to recognize and predict spatial structure, while robust to changes in the spatial scale, contrast and noisiness of the input signal. Because our brains also process temporal information that is rich and occurs across multiple time scales, might the brain employ an analogous set of operations for temporal information processing? Here we define a candidate set of temporal operations, and we review evidence that they are implemented in the mammalian cerebral cortex in a hierarchical manner. We conclude that multiple consecutive stages of cortical processing can be understood to perform temporal pooling, temporal normalization and temporal pattern completion. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.
Temporal Expectation and Information Processing: A Model-Based Analysis
Jepma, Marieke; Wagenmakers, Eric-Jan; Nieuwenhuis, Sander
2012-01-01
People are able to use temporal cues to anticipate the timing of an event, enabling them to process that event more efficiently. We conducted two experiments, using the fixed-foreperiod paradigm (Experiment 1) and the temporal-cueing paradigm (Experiment 2), to assess which components of information processing are speeded when subjects use such…
Capasso, Vincenzo
2015-01-01
This textbook, now in its third edition, offers a rigorous and self-contained introduction to the theory of continuous-time stochastic processes, stochastic integrals, and stochastic differential equations. Expertly balancing theory and applications, the work features concrete examples of modeling real-world problems from biology, medicine, industrial applications, finance, and insurance using stochastic methods. No previous knowledge of stochastic processes is required. Key topics include: * Markov processes * Stochastic differential equations * Arbitrage-free markets and financial derivatives * Insurance risk * Population dynamics, and epidemics * Agent-based models New to the Third Edition: * Infinitely divisible distributions * Random measures * Levy processes * Fractional Brownian motion * Ergodic theory * Karhunen-Loeve expansion * Additional applications * Additional exercises * Smoluchowski approximation of Langevin systems An Introduction to Continuous-Time Stochastic Processes, Third Editio...
Stochastic stability of mechanical systems under renewal jump process parametric excitation
DEFF Research Database (Denmark)
Iwankiewicz, R.; Nielsen, Søren R.K.; Larsen, Jesper Winther
2005-01-01
independent, negative exponential distributed variables; hence, the arrival process may be termed as a generalized Erlang renewal process. The excitation process is governed by the stochastic equation driven by two independent Poisson processes, with different parameters. If the response in a single mode...
DEFF Research Database (Denmark)
Sørup, Hjalte Jomo Danielsen; Christensen, O. B.; Arnbjerg-Nielsen, Karsten
gauges in the model area. The spatio-temporal performance of the model with respect to precipitation extremes is evaluated in the points of a 2x2 km regular grid covering the full model area. The model satisfactorily reproduces the extreme behaviour of the observed precipitation with respect to event...... intensity levels and unconditional spatial correlation when evaluated using an event based ranking approach at point scale and an advanced spatio-temporal coupling of extreme events. Prospectively the model can be used as a tool to evaluate the impact of climate change without relying onprecipitation output......Spatio-temporal rainfall is modelled for the North-Eastern part of Zealand (Denmark) using the Spatio-Temporal Neyman-Scott Rectangular Pulses model as implemented in the RainSim software. Hourly precipitation series for fitting the model are obtained from a dense network of tipping bucket rain...
Description of quantum-mechanical motion by using the formalism of non-Markov stochastic process
International Nuclear Information System (INIS)
Skorobogatov, G.A.; Svertilov, S.I.
1999-01-01
The principle possibilities of mathematical modeling of quantum mechanical motion by the theory of a real stochastic processes is considered. The set of equations corresponding to the simplest case of a two-level system undergoing transitions under the influence of electromagnetic field are obtained. It is shown that quantum-mechanical processes are purely discrete processes of non-Markovian type. They are continuous processes in the space of probability amplitudes and posses the properties of quantum Markovity. The formulation of quantum mechanics in terms of the theory of stochastic processes is necessary for its generalization on small space-time intervals [ru
Stochastic Modeling and Deterministic Limit of Catalytic Surface Processes
DEFF Research Database (Denmark)
Starke, Jens; Reichert, Christian; Eiswirth, Markus
2007-01-01
Three levels of modeling, microscopic, mesoscopic and macroscopic are discussed for the CO oxidation on low-index platinum single crystal surfaces. The introduced models on the microscopic and mesoscopic level are stochastic while the model on the macroscopic level is deterministic. It can......, such that in contrast to the microscopic model the spatial resolution is reduced. The derivation of deterministic limit equations is in correspondence with the successful description of experiments under low-pressure conditions by deterministic reaction-diffusion equations while for intermediate pressures phenomena...
ARMA modelling of neutron stochastic processes with large measurement noise
International Nuclear Information System (INIS)
Zavaljevski, N.; Kostic, Lj.; Pesic, M.
1994-01-01
An autoregressive moving average (ARMA) model of the neutron fluctuations with large measurement noise is derived from langevin stochastic equations and validated using time series data obtained during prompt neutron decay constant measurements at the zero power reactor RB in Vinca. Model parameters are estimated using the maximum likelihood (ML) off-line algorithm and an adaptive pole estimation algorithm based on the recursive prediction error method (RPE). The results show that subcriticality can be determined from real data with high measurement noise using much shorter statistical sample than in standard methods. (author)
Effect of multiplicative noise on stationary stochastic process
Kargovsky, A. V.; Chikishev, A. Yu.; Chichigina, O. A.
2018-03-01
An open system that can be analyzed using the Langevin equation with multiplicative noise is considered. The stationary state of the system results from a balance of deterministic damping and random pumping simulated as noise with controlled periodicity. The dependence of statistical moments of the variable that characterizes the system on parameters of the problem is studied. A nontrivial decrease in the mean value of the main variable with an increase in noise stochasticity is revealed. Applications of the results in several physical, chemical, biological, and technical problems of natural and humanitarian sciences are discussed.
Unifying three perspectives on information processing in stochastic thermodynamics.
Barato, A C; Seifert, U
2014-03-07
So far, feedback-driven systems have been discussed using (i) measurement and control, (ii) a tape interacting with a system, or (iii) by identifying an implicit Maxwell demon in steady-state transport. We derive the corresponding second laws from one master fluctuation theorem and discuss their relationship. In particular, we show that both the entropy production involving mutual information between system and controller and the one involving a Shannon entropy difference of an information reservoir like a tape carry an extra term different from the usual current times affinity. We, thus, generalize stochastic thermodynamics to the presence of an information reservoir.
Directory of Open Access Journals (Sweden)
Xuefeng Li
2014-04-01
Full Text Available Based on solving numerically the generalized nonlinear Langevin equation describing the nonlinear dynamics of stochastic resonance by Fourth-order Runge-Kutta method, an aperiodic stochastic resonance based on an optical bistable system is numerically investigated. The numerical results show that a parameter-tuning stochastic resonance system can be realized by choosing the appropriate optical bistable parameters, which performs well in reconstructing aperiodic signals from a very high level of noise background. The influences of optical bistable parameters on the stochastic resonance effect are numerically analyzed via cross-correlation, and a maximum cross-correlation gain of 8 is obtained by optimizing optical bistable parameters. This provides a prospective method for reconstructing noise-hidden weak signals in all-optical signal processing systems.
Consensus states of local majority rule in stochastic process
Energy Technology Data Exchange (ETDEWEB)
Luo, Yu-Pin [Department of Electronic Engineering, National Formosa University, Huwei, 63201, Taiwan (China); Tang, Chia-Wei; Xu, Hong-Yuan [Department of Physics, Chung-Yuan Christian University, Chungli, 32023, Taiwan (China); Wu, Jinn-Wen [Department of Applied Mathematics, Chung-Yuan Christian University, Chungli, 32023, Taiwan (China); Huang, Ming-Chang, E-mail: mchuang@cycu.edu.tw [Center for Theoretical Science and Department of Physics, Chung-Yuan Christian University, Chungli, 32023, Taiwan (China)
2015-04-03
A sufficient condition for a network system to reach a consensus state of the local majority rule is shown. The influence of interpersonal environment on the occurrence probability of consensus states for Watts–Strogatz and scale-free networks with random initial states is analyzed by numerical method. We also propose a stochastic local majority rule to study the mean first passage time from a random state to a consensus and the escape rate from a consensus state for systems in a noisy environment. Our numerical results show that there exists a window of fluctuation strengths for which the mean first passage time from a random to a consensus state reduces greatly, and the escape rate of consensus states obeys the Arrhenius equation in the window. - Highlights: • A sufficient condition for reaching a consensus. • The relation between the geometry of networks and the reachability of a consensus. • Stochastic local majority rule. • The mean first-passage time and the escape rate of consensus states.
Consensus states of local majority rule in stochastic process
International Nuclear Information System (INIS)
Luo, Yu-Pin; Tang, Chia-Wei; Xu, Hong-Yuan; Wu, Jinn-Wen; Huang, Ming-Chang
2015-01-01
A sufficient condition for a network system to reach a consensus state of the local majority rule is shown. The influence of interpersonal environment on the occurrence probability of consensus states for Watts–Strogatz and scale-free networks with random initial states is analyzed by numerical method. We also propose a stochastic local majority rule to study the mean first passage time from a random state to a consensus and the escape rate from a consensus state for systems in a noisy environment. Our numerical results show that there exists a window of fluctuation strengths for which the mean first passage time from a random to a consensus state reduces greatly, and the escape rate of consensus states obeys the Arrhenius equation in the window. - Highlights: • A sufficient condition for reaching a consensus. • The relation between the geometry of networks and the reachability of a consensus. • Stochastic local majority rule. • The mean first-passage time and the escape rate of consensus states
Optimal Liquidation under Stochastic Liquidity
Becherer, Dirk; Bilarev, Todor; Frentrup, Peter
2016-01-01
We solve explicitly a two-dimensional singular control problem of finite fuel type for infinite time horizon. The problem stems from the optimal liquidation of an asset position in a financial market with multiplicative and transient price impact. Liquidity is stochastic in that the volume effect process, which determines the inter-temporal resilience of the market in spirit of Predoiu, Shaikhet and Shreve (2011), is taken to be stochastic, being driven by own random noise. The optimal contro...
Temporal expectation and information processing: A model-based analysis
Jepma, M.; Wagenmakers, E.-J.; Nieuwenhuis, S.
2012-01-01
People are able to use temporal cues to anticipate the timing of an event, enabling them to process that event more efficiently. We conducted two experiments, using the fixed-foreperiod paradigm (Experiment 1) and the temporal-cueing paradigm (Experiment 2), to assess which components of information
It's about time: revisiting temporal processing deficits in dyslexia.
Casini, Laurence; Pech-Georgel, Catherine; Ziegler, Johannes C
2018-03-01
Temporal processing in French children with dyslexia was evaluated in three tasks: a word identification task requiring implicit temporal processing, and two explicit temporal bisection tasks, one in the auditory and one in the visual modality. Normally developing children matched on chronological age and reading level served as a control group. Children with dyslexia exhibited robust deficits in temporal tasks whether they were explicit or implicit and whether they involved the auditory or the visual modality. First, they presented larger perceptual variability when performing temporal tasks, whereas they showed no such difficulties when performing the same task on a non-temporal dimension (intensity). This dissociation suggests that their difficulties were specific to temporal processing and could not be attributed to lapses of attention, reduced alertness, faulty anchoring, or overall noisy processing. In the framework of cognitive models of time perception, these data point to a dysfunction of the 'internal clock' of dyslexic children. These results are broadly compatible with the recent temporal sampling theory of dyslexia. © 2017 John Wiley & Sons Ltd.
DEFF Research Database (Denmark)
Hansen, Benni Winding; Kesäniemi, Jenni E; Mustonen, Marina
2014-01-01
elegans, a poecilogonous polychaete with within-species variation in developmental mode. P. elegans produces either planktonic, benthic, or intermediate larvae, varying both among and within populations, providing a within-species test of the generality of a relationship between temporal genetic variation...
Role of temporal processing stages by inferior temporal neurons in facial recognition
Directory of Open Access Journals (Sweden)
Yasuko eSugase-Miyamoto
2011-06-01
Full Text Available In this review, we focus on the role of temporal stages of encoded facial information in the visual system, which might enable the efficient determination of species, identity, and expression. Facial recognition is an important function of our brain and is known to be processed in the ventral visual pathway, where visual signals are processed through areas V1, V2, V4, and the inferior temporal (IT cortex. In the IT cortex, neurons show selective responses to complex visual images such as faces, and at each stage along the pathway the stimulus selectivity of the neural responses becomes sharper, particularly in the later portion of the responses.In the IT cortex of the monkey, facial information is represented by different temporal stages of neural responses, as shown in our previous study: the initial transient response of face-responsive neurons represents information about global categories, i.e., human vs. monkey vs. simple shapes, whilst the later portion of these responses represents information about detailed facial categories, i.e., expression and/or identity. This suggests that the temporal stages of the neuronal firing pattern play an important role in the coding of visual stimuli, including faces. This type of coding may be a plausible mechanism underlying the temporal dynamics of recognition, including the process of detection/categorization followed by the identification of objects. Recent single-unit studies in monkeys have also provided evidence consistent with the important role of the temporal stages of encoded facial information. For example, view-invariant facial identity information is represented in the response at a later period within a region of face-selective neurons. Consistent with these findings, temporally modulated neural activity has also been observed in human studies. These results suggest a close correlation between the temporal processing stages of facial information by IT neurons and the temporal dynamics of
Neuhausler, R.; Robinson, M.; Bruna, M.
2017-12-01
Over the last 60 years we have seen an increased amount of ecological regime shifts in tropical coastal zones, from coral reefs to macroalgae dominated states, as a result of natural and anthropogenic stresses. However, these shifts are not always immediate- macroalgae are generally present in coral reefs, with their distribution regulated by herbivorous fish. This is especially true in Moorea, French Polynesia, where macroalgae are shown to flourish in spaces that provide refuge from roaming herbivores. While there are currently modeling efforts in projecting ecological regime shifts in Moorea, temporal deterministic models have been utilized, which fail to capture metastability between multiple steady states and can have issues when dealing with very small populations. To address these concerns, we build on these models to account for spatial variations and individual organisms, as well as stochasticity. Our model can project the percent cover of coral, macroalgae, and algae turf as a function of herbivorous grazers, water quality, and coral demographics. Grazers, included as individual fish (particles), evolve according to a kinetic model and interact with neighbouring benthic assemblages, represented as nodes. Water quality and coral demographics are input parameters that can vary over time, allowing our model to be run for temporally changing scenarios and to be adjusted for different reefs. We plan to engage with previous Moorea Reef Resilience Models through a comparative analysis of our models' outcomes and existing Moorea data. Coupling projective models with available data is useful for informing environmental policy and advancing the modeling field.
Effect of the Potential Shape on the Stochastic Resonance Processes
Kenmoé, G. Djuidjé; Ngouongo, Y. J. Wadop; Kofané, T. C.
2015-10-01
The stochastic resonance (SR) induced by periodic signal and white noises in a periodic nonsinusoidal potential is investigated. This phenomenon is studied as a function of the friction coefficient as well as the shape of the potential. It is done through an investigation of the hysteresis loop area which is equivalent to the input energy lost by the system to the environment per period of the external force. SR is evident in some range of the shape parameter of the potential, but cannot be observed in the other range. Specially, variation of the shape potential affects significantly and not trivially the heigh of the potential barrier in the Kramers rate as well as the occurrence of SR. The finding results show crucial dependence of the temperature of occurrence of SR on the shape of the potential. It is noted that the maximum of the input energy generally decreases when the friction coefficient is increased.
State estimation for temporal point processes
van Lieshout, Maria Nicolette Margaretha
2015-01-01
This paper is concerned with combined inference for point processes on the real line observed in a broken interval. For such processes, the classic history-based approach cannot be used. Instead, we adapt tools from sequential spatial point processes. For a range of models, the marginal and
Hwang, James Ho-Jin; Duran, Adam
2016-08-01
Most of the times pyrotechnic shock design and test requirements for space systems are provided in Shock Response Spectrum (SRS) without the input time history. Since the SRS does not describe the input or the environment, a decomposition method is used to obtain the source time history. The main objective of this paper is to develop a decomposition method producing input time histories that can satisfy the SRS requirement based on the pyrotechnic shock test data measured from a mechanical impact test apparatus. At the heart of this decomposition method is the statistical representation of the pyrotechnic shock test data measured from the MIT Lincoln Laboratory (LL) designed Universal Pyrotechnic Shock Simulator (UPSS). Each pyrotechnic shock test data measured at the interface of a test unit has been analyzed to produce the temporal peak acceleration, Root Mean Square (RMS) acceleration, and the phase lag at each band center frequency. Maximum SRS of each filtered time history has been calculated to produce a relationship between the input and the response. Two new definitions are proposed as a result. The Peak Ratio (PR) is defined as the ratio between the maximum SRS and the temporal peak acceleration at each band center frequency. The ratio between the maximum SRS and the RMS acceleration is defined as the Energy Ratio (ER) at each band center frequency. Phase lag is estimated based on the time delay between the temporal peak acceleration at each band center frequency and the peak acceleration at the lowest band center frequency. This stochastic process has been applied to more than one hundred pyrotechnic shock test data to produce probabilistic definitions of the PR, ER, and the phase lag. The SRS is decomposed at each band center frequency using damped sinusoids with the PR and the decays obtained by matching the ER of the damped sinusoids to the ER of the test data. The final step in this stochastic SRS decomposition process is the Monte Carlo (MC
Måren, Inger Elisabeth; Kapfer, Jutta; Aarrestad, Per Arild; Grytnes, John-Arvid; Vandvik, Vigdis
2018-01-01
Successional dynamics in plant community assembly may result from both deterministic and stochastic ecological processes. The relative importance of different ecological processes is expected to vary over the successional sequence, between different plant functional groups, and with the disturbance levels and land-use management regimes of the successional systems. We evaluate the relative importance of stochastic and deterministic processes in bryophyte and vascular plant community assembly after fire in grazed and ungrazed anthropogenic coastal heathlands in Northern Europe. A replicated series of post-fire successions (n = 12) were initiated under grazed and ungrazed conditions, and vegetation data were recorded in permanent plots over 13 years. We used redundancy analysis (RDA) to test for deterministic successional patterns in species composition repeated across the replicate successional series and analyses of co-occurrence to evaluate to what extent species respond synchronously along the successional gradient. Change in species co-occurrences over succession indicates stochastic successional dynamics at the species level (i.e., species equivalence), whereas constancy in co-occurrence indicates deterministic dynamics (successional niche differentiation). The RDA shows high and deterministic vascular plant community compositional change, especially early in succession. Co-occurrence analyses indicate stochastic species-level dynamics the first two years, which then give way to more deterministic replacements. Grazed and ungrazed successions are similar, but the early stage stochasticity is higher in ungrazed areas. Bryophyte communities in ungrazed successions resemble vascular plant communities. In contrast, bryophytes in grazed successions showed consistently high stochasticity and low determinism in both community composition and species co-occurrence. In conclusion, stochastic and individualistic species responses early in succession give way to more
Levy-Student processes for a stochastic model of beam halos
Energy Technology Data Exchange (ETDEWEB)
Petroni, N. Cufaro [Department of Mathematics, University of Bari, and INFN Sezione di Bari, via E. Orabona 4, 70125 Bari (Italy)]. E-mail: cufaro@ba.infn.it; De Martino, S. [Department of Physics, University of Salerno, and INFN Sezione di Napoli (gruppo di Salerno), Via S. Allende, I-84081 Baronissi (SA) (Italy); De Siena, S. [Department of Physics, University of Salerno, and INFN Sezione di Napoli (gruppo di Salerno), Via S. Allende, I-84081 Baronissi (SA) (Italy); Illuminati, F. [Department of Physics, University of Salerno, and INFN Sezione di Napoli (gruppo di Salerno), Via S. Allende, I-84081 Baronissi (SA) (Italy)
2006-06-01
We describe the transverse beam distribution in particle accelerators within the controlled, stochastic dynamical scheme of the stochastic mechanics which produces time reversal invariant diffusion processes. In this paper we analyze the consequences of introducing the generalized Student laws, namely non-Gaussian, Levy infinitely divisible (but not stable) distributions. We will analyze this idea from two different standpoints: (a) first by supposing that the stationary distribution of our (Wiener powered) stochastic model is a Student distribution; (b) by supposing that our model is based on a (non-Gaussian) Levy process whose increments are Student distributed. In the case (a) the longer tails of the power decay of the Student laws, and in the case (b) the discontinuities of the Levy-Student process can well account for the rare escape of particles from the beam core, and hence for the formation of a halo in intense beams.
Levy-Student processes for a stochastic model of beam halos
International Nuclear Information System (INIS)
Petroni, N. Cufaro; De Martino, S.; De Siena, S.; Illuminati, F.
2006-01-01
We describe the transverse beam distribution in particle accelerators within the controlled, stochastic dynamical scheme of the stochastic mechanics which produces time reversal invariant diffusion processes. In this paper we analyze the consequences of introducing the generalized Student laws, namely non-Gaussian, Levy infinitely divisible (but not stable) distributions. We will analyze this idea from two different standpoints: (a) first by supposing that the stationary distribution of our (Wiener powered) stochastic model is a Student distribution; (b) by supposing that our model is based on a (non-Gaussian) Levy process whose increments are Student distributed. In the case (a) the longer tails of the power decay of the Student laws, and in the case (b) the discontinuities of the Levy-Student process can well account for the rare escape of particles from the beam core, and hence for the formation of a halo in intense beams
Stochastic processes, multiscale modeling, and numerical methods for computational cellular biology
2017-01-01
This book focuses on the modeling and mathematical analysis of stochastic dynamical systems along with their simulations. The collected chapters will review fundamental and current topics and approaches to dynamical systems in cellular biology. This text aims to develop improved mathematical and computational methods with which to study biological processes. At the scale of a single cell, stochasticity becomes important due to low copy numbers of biological molecules, such as mRNA and proteins that take part in biochemical reactions driving cellular processes. When trying to describe such biological processes, the traditional deterministic models are often inadequate, precisely because of these low copy numbers. This book presents stochastic models, which are necessary to account for small particle numbers and extrinsic noise sources. The complexity of these models depend upon whether the biochemical reactions are diffusion-limited or reaction-limited. In the former case, one needs to adopt the framework of s...
The associations between multisensory temporal processing and symptoms of schizophrenia.
Stevenson, Ryan A; Park, Sohee; Cochran, Channing; McIntosh, Lindsey G; Noel, Jean-Paul; Barense, Morgan D; Ferber, Susanne; Wallace, Mark T
2017-01-01
Recent neurobiological accounts of schizophrenia have included an emphasis on changes in sensory processing. These sensory and perceptual deficits can have a cascading effect onto higher-level cognitive processes and clinical symptoms. One form of sensory dysfunction that has been consistently observed in schizophrenia is altered temporal processing. In this study, we investigated temporal processing within and across the auditory and visual modalities in individuals with schizophrenia (SCZ) and age-matched healthy controls. Individuals with SCZ showed auditory and visual temporal processing abnormalities, as well as multisensory temporal processing dysfunction that extended beyond that attributable to unisensory processing dysfunction. Most importantly, these multisensory temporal deficits were associated with the severity of hallucinations. This link between atypical multisensory temporal perception and clinical symptomatology suggests that clinical symptoms of schizophrenia may be at least partly a result of cascading effects from (multi)sensory disturbances. These results are discussed in terms of underlying neural bases and the possible implications for remediation. Copyright © 2016 Elsevier B.V. All rights reserved.
DEFF Research Database (Denmark)
Sørup, Hjalte Jomo Danielsen; Christensen, O. B.; Arnbjerg-Nielsen, Karsten
2017-01-01
Spatio-temporal rainfall is modelled for the North-Eastern part of Zealand (Denmark) using the Spatio-Temporal Neyman-Scott Rectangular Pulses model as implemented in the RainSim software. Hourly precipitation series for fitting the model are obtained from a dense network of tipping bucket rain...... gauges in the model area. The spatiotemporal performance of the model with respect to precipitation extremes is evaluated in the points of a 2x2 km regular grid covering the full model area. The model satisfactorily reproduces the extreme behaviour of the observed precipitation with respect to event...... intensity levels and unconditional spatial correlation when evaluated using an event based ranking approach at point scale and an advanced spatiotemporal coupling of extreme events. Prospectively the model can be used as a tool to evaluate the impact of climate change without relying on precipitation output...
Comments on the use of stochastic processes in the field of the ionizing radiations
International Nuclear Information System (INIS)
Alvarez Romero, Jose T.
2008-01-01
Stochastic process is the name given to a time dependent random process, unfortunately, its time dependence is not always clearly emphasized. In fact, such dependence is not unequivocally stated in the different disciplines of radiation physics, radiobiology or in radiation protection. This is the cause of some conceptual confusion when interpreting relationships between quantities is analyzed, e.g.: imparted energy vs. absorbed dose, stochastic vs. deterministic biological effects; or in radiation protection models, whether: linear or quadratic, relative or absolute. Most of these relationships are associated to stochastic phenomena, and they carry a time dependence that requires clarification. To mention some examples, in radiation physics: the absorbed dose is a non stochastic quantity resulting from averaging a stochastic one namely, the imparted energy, over a representative ensemble via an operation analogous to the Gibbs-Einstein algorithm. On the other hand stochastic quantities require specialized mathematical techniques of stochastic processes to handle them. These refinements are unfortunately ignored in the reports of ICRU 33 and 60. Essentially, a problem to be solved is to establish a clear relationship between micro or mesoscopic stochastic quantities and their macroscopic counterparts, these latter ones possibly being time dependent or not. This is the main objective of microdosimetry. Another problem is to describe phenomena such as electronic equilibrium which is nothing else than a stationary state thus exhibiting no time dependence. Still a different question is the interpretation of radioactive decay as a stochastic process of the Poisson and Markov type. In radiobiology a basic problem is the study of biological stochastic phenomena is to determine the characteristics and structure of those time dependent probabilistic functions allowing the quantification of macroscopic biological manifestations, such as carcinogenesis or genetic effects
International Nuclear Information System (INIS)
Frank, T D
2005-01-01
Stationary distributions of processes are derived that involve a time delay and are defined by a linear stochastic neutral delay differential equation. The distributions are Gaussian distributions. The variances of the Gaussian distributions are either monotonically increasing or decreasing functions of the time delays. The variances become infinite when fixed points of corresponding deterministic processes become unstable. (letter to the editor)
Dini-Andreote, Francisco; Stegen, James C.; van Elsas, Jan Dirk; Salles, Joana Falcao
2015-01-01
Ecological succession and the balance between stochastic and deterministic processes are two major themes within microbial ecology, but these conceptual domains have mostly developed independent of each other. Here we provide a framework that integrates shifts in community assembly processes with
A Family of Poisson Processes for Use in Stochastic Models of Precipitation
Penland, C.
2013-12-01
Both modified Poisson processes and compound Poisson processes can be relevant to stochastic parameterization of precipitation. This presentation compares the dynamical properties of these systems and discusses the physical situations in which each might be appropriate. If the parameters describing either class of systems originate in hydrodynamics, then proper consideration of stochastic calculus is required during numerical implementation of the parameterization. It is shown here that an improper numerical treatment can have severe implications for estimating rainfall distributions, particularly in the tails of the distributions and, thus, on the frequency of extreme events.
Continuous strong Markov processes in dimension one a stochastic calculus approach
Assing, Sigurd
1998-01-01
The book presents an in-depth study of arbitrary one-dimensional continuous strong Markov processes using methods of stochastic calculus. Departing from the classical approaches, a unified investigation of regular as well as arbitrary non-regular diffusions is provided. A general construction method for such processes, based on a generalization of the concept of a perfect additive functional, is developed. The intrinsic decomposition of a continuous strong Markov semimartingale is discovered. The book also investigates relations to stochastic differential equations and fundamental examples of irregular diffusions.
Entropy Measures for Stochastic Processes with Applications in Functional Anomaly Detection
Directory of Open Access Journals (Sweden)
Gabriel Martos
2018-01-01
Full Text Available We propose a definition of entropy for stochastic processes. We provide a reproducing kernel Hilbert space model to estimate entropy from a random sample of realizations of a stochastic process, namely functional data, and introduce two approaches to estimate minimum entropy sets. These sets are relevant to detect anomalous or outlier functional data. A numerical experiment illustrates the performance of the proposed method; in addition, we conduct an analysis of mortality rate curves as an interesting application in a real-data context to explore functional anomaly detection.
Warnke, Tom; Reinhardt, Oliver; Klabunde, Anna; Willekens, Frans; Uhrmacher, Adelinde M
2017-10-01
Individuals' decision processes play a central role in understanding modern migration phenomena and other demographic processes. Their integration into agent-based computational demography depends largely on suitable support by a modelling language. We are developing the Modelling Language for Linked Lives (ML3) to describe the diverse decision processes of linked lives succinctly in continuous time. The context of individuals is modelled by networks the individual is part of, such as family ties and other social networks. Central concepts, such as behaviour conditional on agent attributes, age-dependent behaviour, and stochastic waiting times, are tightly integrated in the language. Thereby, alternative decisions are modelled by concurrent processes that compete by stochastic race. Using a migration model, we demonstrate how this allows for compact description of complex decisions, here based on the Theory of Planned Behaviour. We describe the challenges for the simulation algorithm posed by stochastic race between multiple concurrent complex decisions.
Crisan, Dan
2011-01-01
"Stochastic Analysis" aims to provide mathematical tools to describe and model high dimensional random systems. Such tools arise in the study of Stochastic Differential Equations and Stochastic Partial Differential Equations, Infinite Dimensional Stochastic Geometry, Random Media and Interacting Particle Systems, Super-processes, Stochastic Filtering, Mathematical Finance, etc. Stochastic Analysis has emerged as a core area of late 20th century Mathematics and is currently undergoing a rapid scientific development. The special volume "Stochastic Analysis 2010" provides a sa
Temporal processing asymmetries between the cerebral hemispheres: evidence and implications.
Nicholls, M E
1996-07-01
This paper reviews a large body of research which has investigated the capacities of the cerebral hemispheres to process temporal information. This research includes clinical, non-clinical, and electrophysiological experimentation. On the whole, the research supports the notion of a left hemisphere advantage for temporal resolution. The existence of such an asymmetry demonstrates that cerebral lateralisation is not limited to the higher-order functions such as language. The capacity for the resolution of fine temporal events appears to play an important role in other left hemisphere functions which require a rapid sequential processor. The functions that are facilitated by such a processor include verbal, textual, and fine movement skills. The co-development of these functions with an efficient temporal processor can be accounted for with reference to a number of evolutionary scenarios. Physiological evidence favours a temporal processing mechanism located within the left temporal cortex. The function of this mechanism may be described in terms of intermittency or travelling moment models of temporal processing. The travelling moment model provides the most plausible account of the asymmetry.
Quan, Ji; Liu, Wei; Chu, Yuqing; Wang, Xianjia
2017-11-23
Traditional replication dynamic model and the corresponding concept of evolutionary stable strategy (ESS) only takes into account whether the system can return to the equilibrium after being subjected to a small disturbance. In the real world, due to continuous noise, the ESS of the system may not be stochastically stable. In this paper, a model of voluntary public goods game with punishment is studied in a stochastic situation. Unlike the existing model, we describe the evolutionary process of strategies in the population as a generalized quasi-birth-and-death process. And we investigate the stochastic stable equilibrium (SSE) instead. By numerical experiments, we get all possible SSEs of the system for any combination of parameters, and investigate the influence of parameters on the probabilities of the system to select different equilibriums. It is found that in the stochastic situation, the introduction of the punishment and non-participation strategies can change the evolutionary dynamics of the system and equilibrium of the game. There is a large range of parameters that the system selects the cooperative states as its SSE with a high probability. This result provides us an insight and control method for the evolution of cooperation in the public goods game in stochastic situations.
Kemper, A; Nishino, T; Schadschneider, A; Zittartz, J
2003-01-01
We develop a new variant of the recently introduced stochastic transfer matrix DMRG which we call stochastic light-cone corner-transfer-matrix DMRG (LCTMRG). It is a numerical method to compute dynamic properties of one-dimensional stochastic processes. As suggested by its name, the LCTMRG is a modification of the corner-transfer-matrix DMRG, adjusted by an additional causality argument. As an example, two reaction-diffusion models, the diffusion-annihilation process and the branch-fusion process are studied and compared with exact data and Monte Carlo simulations to estimate the capability and accuracy of the new method. The number of possible Trotter steps of more than 10 sup 5 shows a considerable improvement on the old stochastic TMRG algorithm.
Modelling on optimal portfolio with exchange rate based on discontinuous stochastic process
Yan, Wei; Chang, Yuwen
2016-12-01
Considering the stochastic exchange rate, this paper is concerned with the dynamic portfolio selection in financial market. The optimal investment problem is formulated as a continuous-time mathematical model under mean-variance criterion. These processes follow jump-diffusion processes (Weiner process and Poisson process). Then the corresponding Hamilton-Jacobi-Bellman(HJB) equation of the problem is presented and its efferent frontier is obtained. Moreover, the optimal strategy is also derived under safety-first criterion.
Altered organization of face processing networks in temporal lobe epilepsy
Riley, Jeffrey D.; Fling, Brett W.; Cramer, Steven C.; Lin, Jack J.
2015-01-01
SUMMARY Objective Deficits in social cognition are common and significant in people with temporal lobe epilepsy (TLE), but the functional and structural underpinnings remain unclear. The present study investigated how the side of seizure focus impacts face processing networks in temporal lobe epilepsy. Methods We used functional magnetic resonance imaging (fMRI) of a face processing paradigm to identify face responsive regions in 24 individuals with unilateral temporal lobe epilepsy (Left = 15; Right = 9) and 19 healthy controls. fMRI signals of face responsive regions ispilateral and contralateral to the side of seizure onset were delineated in TLE and compared to the healthy controls with right and left side combined. Diffusion tensor images were acquired to investigate structural connectivity between face regions that differed in fMRI signals between the two groups. Results In temporal lobe epilepsy, activation of the cortical face processing networks varied according to side of seizure onset. In temporal lobe epilepsy, the laterality of amygdala activation was shifted to the side contralateral to the seizure focus while controls showed no significant asymmetry. Furthermore, compared to controls, patients with TLE showed decreased activation of the occipital face responsive region in the ipsilateral side and an increased activity of the anterior temporal lobe in the contralateral side to the seizure focus. Probabilistic tractography revealed that the occipital face area and anterior temporal lobe are connected via the inferior longitudinal fasciculus, which in individuals with temporal lobe epilepsy showed reduced integrity. Significance Taken together, these findings suggest that brain function and white matter integrity of networks subserving face processing are impaired on the side of seizure onset, accompanied by altered responses on the side contralateral to the seizure. PMID:25823855
A simple stochastic rainstorm generator for simulating spatially and temporally varying rainfall
Singer, M. B.; Michaelides, K.; Nichols, M.; Nearing, M. A.
2016-12-01
In semi-arid to arid drainage basins, rainstorms often control both water supply and flood risk to marginal communities of people. They also govern the availability of water to vegetation and other ecological communities, as well as spatial patterns of sediment, nutrient, and contaminant transport and deposition on local to basin scales. All of these landscape responses are sensitive to changes in climate that are projected to occur throughout western North America. Thus, it is important to improve characterization of rainstorms in a manner that enables statistical assessment of rainfall at spatial scales below that of existing gauging networks and the prediction of plausible manifestations of climate change. Here we present a simple, stochastic rainstorm generator that was created using data from a rich and dense network of rain gauges at the Walnut Gulch Experimental Watershed (WGEW) in SE Arizona, but which is applicable anywhere. We describe our methods for assembling pdfs of relevant rainstorm characteristics including total annual rainfall, storm area, storm center location, and storm duration. We also generate five fitted intensity-duration curves and apply a spatial rainfall gradient to generate precipitation at spatial scales below gauge spacing. The model then runs by Monte Carlo simulation in which a total annual rainfall is selected before we generate rainstorms until the annual precipitation total is reached. The procedure continues for decadal simulations. Thus, we keep track of the hydrologic impact of individual storms and the integral of precipitation over multiple decades. We first test the model using ensemble predictions until we reach statistical similarity to the input data from WGEW. We then employ the model to assess decadal precipitation under simulations of climate change in which we separately vary the distribution of total annual rainfall (trend in moisture) and the intensity-duration curves used for simulation (trends in storminess). We
ℋ∞ constant gain state feedback stabilization of stochastic hybrid systems with Wiener process
Directory of Open Access Journals (Sweden)
E. K. Boukas
2004-01-01
Full Text Available This paper considers the stabilization problem of the class of continuous-time linear stochastic hybrid systems with Wiener process. The ℋ∞ state feedback stabilization problem is treated. A state feedback controller with constant gain that does not require access to the system mode is designed. LMI-based conditions are developed to design the state feedback controller with constant gain that stochastically stabilizes the studied class of systems and, at the same time, achieve the disturbance rejection of a desired level. The minimum disturbance rejection is also determined. Numerical examples are given to show the usefulness of the proposed results.
Stochastic processes and functional analysis a volume of recent advances in honor of M. M. Rao
Krinik, Alan C
2004-01-01
This extraordinary compilation is an expansion of the recent American Mathematical Society Special Session celebrating M. M. Rao's distinguished career and includes most of the presented papers as well as ancillary contributions from session invitees. This book shows the effectiveness of abstract analysis for solving fundamental problems of stochastic theory, specifically the use of functional analytic methods for elucidating stochastic processes, as made manifest in M. M. Rao's prolific research achievements. Featuring a biography of M. M. Rao, a complete bibliography of his published works,
Goychuk, I
2001-08-01
Stochastic resonance in a simple model of information transfer is studied for sensory neurons and ensembles of ion channels. An exact expression for the information gain is obtained for the Poisson process with the signal-modulated spiking rate. This result allows one to generalize the conventional stochastic resonance (SR) problem (with periodic input signal) to the arbitrary signals of finite duration (nonstationary SR). Moreover, in the case of a periodic signal, the rate of information gain is compared with the conventional signal-to-noise ratio. The paper establishes the general nonequivalence between both measures notwithstanding their apparent similarity in the limit of weak signals.
Strategy Complexity of Finite-Horizon Markov Decision Processes and Simple Stochastic Games
DEFF Research Database (Denmark)
Ibsen-Jensen, Rasmus; Chatterjee, Krishnendu
2012-01-01
Markov decision processes (MDPs) and simple stochastic games (SSGs) provide a rich mathematical framework to study many important problems related to probabilistic systems. MDPs and SSGs with finite-horizon objectives, where the goal is to maximize the probability to reach a target state in a given...
Using Max-Plus Algebra for the Evaluation of Stochastic Process Algebra Prefixes
Cloth, L.; de Alfaro, L.; Gilmore, S.; Bohnenkamp, H.C.; Haverkort, Boudewijn R.H.M.
2001-01-01
In this paper, the concept of complete finite prefixes for process algebra expressions is extended to stochastic models. Events are supposed to happen after a delay that is determined by random variables assigned to the preceding conditions. Max-plus algebra expressions are shown to provide an
Explicit calibration and simulation of stochastic fields by low-order ARMA processes
DEFF Research Database (Denmark)
Krenk, Steen
2011-01-01
A simple framework for autoregressive simulation of stochastic fields is presented. The autoregressive format leads to a simple exponential correlation structure in the time-dimension. In the case of scalar processes a more detailed correlation structure can be obtained by adding memory...... to the process via an extension to autoregressive moving average (ARMA) processes. The ARMA format incorporates a more detailed correlation structure by including previous values of the simulated process. Alternatively, a more detailed correlation structure can be obtained by including additional 'state......-space' variables in the simulation. For a scalar process this would imply an increase of the dimension of the process to be simulated. In the case of a stochastic field the correlation in the time-dimension is represented, although indirectly, in the simultaneous spatial correlation. The model with the shortest...
Kinetic theory of age-structured stochastic birth-death processes
Greenman, Chris D.; Chou, Tom
2016-01-01
Classical age-structured mass-action models such as the McKendrick-von Foerster equation have been extensively studied but are unable to describe stochastic fluctuations or population-size-dependent birth and death rates. Stochastic theories that treat semi-Markov age-dependent processes using, e.g., the Bellman-Harris equation do not resolve a population's age structure and are unable to quantify population-size dependencies. Conversely, current theories that include size-dependent population dynamics (e.g., mathematical models that include carrying capacity such as the logistic equation) cannot be easily extended to take into account age-dependent birth and death rates. In this paper, we present a systematic derivation of a new, fully stochastic kinetic theory for interacting age-structured populations. By defining multiparticle probability density functions, we derive a hierarchy of kinetic equations for the stochastic evolution of an aging population undergoing birth and death. We show that the fully stochastic age-dependent birth-death process precludes factorization of the corresponding probability densities, which then must be solved by using a Bogoliubov--Born--Green--Kirkwood--Yvon-like hierarchy. Explicit solutions are derived in three limits: no birth, no death, and steady state. These are then compared with their corresponding mean-field results. Our results generalize both deterministic models and existing master equation approaches by providing an intuitive and efficient way to simultaneously model age- and population-dependent stochastic dynamics applicable to the study of demography, stem cell dynamics, and disease evolution.
MODIS multi-temporal data retrieval and processing toolbox
Mattiuzzi, M.; Verbesselt, J.; Klisch, A.
2012-01-01
The package functionalities are focused for the download and processing of multi-temporal datasets from MODIS sensors. All standard MODIS grid data can be accessed and processed by the package routines. The package is still in alpha development and not all the functionalities are available for now.
On spatio-temporal Lévy based Cox processes
DEFF Research Database (Denmark)
Prokesova, Michaela; Hellmund, Gunnar; Jensen, Eva Bjørn Vedel
2006-01-01
The paper discusses a new class of models for spatio-temporal Cox point processes. In these models, the driving field is defined by means of an integral of a weight function with respect to a Lévy basis. The relations to other Cox process models studied previously are discussed and formulas for t...
Encoding model of temporal processing in human visual cortex.
Stigliani, Anthony; Jeska, Brianna; Grill-Spector, Kalanit
2017-12-19
How is temporal information processed in human visual cortex? Visual input is relayed to V1 through segregated transient and sustained channels in the retina and lateral geniculate nucleus (LGN). However, there is intense debate as to how sustained and transient temporal channels contribute to visual processing beyond V1. The prevailing view associates transient processing predominately with motion-sensitive regions and sustained processing with ventral stream regions, while the opposing view suggests that both temporal channels contribute to neural processing beyond V1. Using fMRI, we measured cortical responses to time-varying stimuli and then implemented a two temporal channel-encoding model to evaluate the contributions of each channel. Different from the general linear model of fMRI that predicts responses directly from the stimulus, the encoding approach first models neural responses to the stimulus from which fMRI responses are derived. This encoding approach not only predicts cortical responses to time-varying stimuli from milliseconds to seconds but also, reveals differential contributions of temporal channels across visual cortex. Consistent with the prevailing view, motion-sensitive regions and adjacent lateral occipitotemporal regions are dominated by transient responses. However, ventral occipitotemporal regions are driven by both sustained and transient channels, with transient responses exceeding the sustained. These findings propose a rethinking of temporal processing in the ventral stream and suggest that transient processing may contribute to rapid extraction of the content of the visual input. Importantly, our encoding approach has vast implications, because it can be applied with fMRI to decipher neural computations in millisecond resolution in any part of the brain. Copyright © 2017 the Author(s). Published by PNAS.
Cortical Correlates of Binaural Temporal Processing Deficits in Older Adults.
Eddins, Ann Clock; Eddins, David A
This study was designed to evaluate binaural temporal processing in young and older adults using a binaural masking level difference (BMLD) paradigm. Using behavioral and electrophysiological measures within the same listeners, a series of stimulus manipulations was used to evaluate the relative contribution of binaural temporal fine-structure and temporal envelope cues. We evaluated the hypotheses that age-related declines in the BMLD task would be more strongly associated with temporal fine-structure than envelope cues and that age-related declines in behavioral measures would be correlated with cortical auditory evoked potential (CAEP) measures. Thirty adults participated in the study, including 10 young normal-hearing, 10 older normal-hearing, and 10 older hearing-impaired adults with bilaterally symmetric, mild-to-moderate sensorineural hearing loss. Behavioral and CAEP thresholds were measured for diotic (So) and dichotic (Sπ) tonal signals presented in continuous diotic (No) narrowband noise (50-Hz wide) maskers. Temporal envelope cues were manipulated by using two different narrowband maskers; Gaussian noise (GN) with robust envelope fluctuations and low-noise noise (LNN) with minimal envelope fluctuations. The potential to use temporal fine-structure cues was controlled by varying the signal frequency (500 or 4000 Hz), thereby relying on the natural decline in phase-locking with increasing frequency. Behavioral and CAEP thresholds were similar across groups for diotic conditions, while the masking release in dichotic conditions was larger for younger than for older participants. Across all participants, BMLDs were larger for GN than LNN and for 500-Hz than for 4000-Hz conditions, where envelope and fine-structure cues were most salient, respectively. Specific age-related differences were demonstrated for 500-Hz dichotic conditions in GN and LNN, reflecting reduced binaural temporal fine-structure coding. No significant age effects were observed for 4000
An extension of clarke's model with stochastic amplitude flip processes
Hoel, Hakon; Nyberg, Henrik
2014-01-01
. By rigorous analysis and numerical studies, we show that in many settings, signal realizations are generated more efficiently by Gaussian process algorithms than by the MFC model's algorithm. Numerical examples that strengthen these observations are also
International Nuclear Information System (INIS)
Papiez, L.; Moskvin, V.; Tulovsky, V.
2001-01-01
The process of angular-spatial evolution of multiple scattering of charged particles can be described by a special case of Boltzmann integro-differential equation called Lewis equation. The underlying stochastic process for this evolution is the compound Poisson process on the surface of the unit sphere. The significant portion of events that constitute compound Poisson process that describes multiple scattering have diffusional character. This property allows to analyze the process of angular-spatial evolution of multiple scattering of charged particles as combination of soft and hard collision processes and compute appropriately its transition densities. These computations provide a method of the approximate solution to the Lewis equation. (orig.)
Raso , L.; Malaterre , P.O.; Bader , J.C.
2017-01-01
International audience; This article presents an innovative streamflow process model for use in reservoir operational rule design in stochastic dual dynamic programming (SDDP). Model features, which can be applied independently, are (1) a multiplicative process model for the forward phase and its linearized version for the backward phase; and (2) a nonuniform time-step length that is inversely proportional to seasonal variability. The advantages are (1) guaranteeing positive streamflow values...
Stochastic Analysis of a Queue Length Model Using a Graphics Processing Unit
Czech Academy of Sciences Publication Activity Database
Přikryl, Jan; Kocijan, J.
2012-01-01
Roč. 5, č. 2 (2012), s. 55-62 ISSN 1802-971X R&D Projects: GA MŠk(CZ) MEB091015 Institutional support: RVO:67985556 Keywords : graphics processing unit * GPU * Monte Carlo simulation * computer simulation * modeling Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/2012/AS/prikryl-stochastic analysis of a queue length model using a graphics processing unit.pdf
Modeling laser velocimeter signals as triply stochastic Poisson processes
Mayo, W. T., Jr.
1976-01-01
Previous models of laser Doppler velocimeter (LDV) systems have not adequately described dual-scatter signals in a manner useful for analysis and simulation of low-level photon-limited signals. At low photon rates, an LDV signal at the output of a photomultiplier tube is a compound nonhomogeneous filtered Poisson process, whose intensity function is another (slower) Poisson process with the nonstationary rate and frequency parameters controlled by a random flow (slowest) process. In the present paper, generalized Poisson shot noise models are developed for low-level LDV signals. Theoretical results useful in detection error analysis and simulation are presented, along with measurements of burst amplitude statistics. Computer generated simulations illustrate the difference between Gaussian and Poisson models of low-level signals.
Learning process mapping heuristics under stochastic sampling overheads
Ieumwananonthachai, Arthur; Wah, Benjamin W.
1991-01-01
A statistical method was developed previously for improving process mapping heuristics. The method systematically explores the space of possible heuristics under a specified time constraint. Its goal is to get the best possible heuristics while trading between the solution quality of the process mapping heuristics and their execution time. The statistical selection method is extended to take into consideration the variations in the amount of time used to evaluate heuristics on a problem instance. The improvement in performance is presented using the more realistic assumption along with some methods that alleviate the additional complexity.
Stochastic model of milk homogenization process using Markov's chain
Directory of Open Access Journals (Sweden)
A. A. Khvostov
2016-01-01
Full Text Available The process of development of a mathematical model of the process of homogenization of dairy products is considered in the work. The theory of Markov's chains was used in the development of the mathematical model, Markov's chain with discrete states and continuous parameter for which the homogenisation pressure is taken, being the basis for the model structure. Machine realization of the model is implemented in the medium of structural modeling MathWorks Simulink™. Identification of the model parameters was carried out by minimizing the standard deviation calculated from the experimental data for each fraction of dairy products fat phase. As the set of experimental data processing results of the micrographic images of fat globules of whole milk samples distribution which were subjected to homogenization at different pressures were used. Pattern Search method was used as optimization method with the Latin Hypercube search algorithm from Global Optimization Тoolbox library. The accuracy of calculations averaged over all fractions of 0.88% (the relative share of units, the maximum relative error was 3.7% with the homogenization pressure of 30 MPa, which may be due to the very abrupt change in properties from the original milk in the particle size distribution at the beginning of the homogenization process and the lack of experimental data at homogenization pressures of below the specified value. The mathematical model proposed allows to calculate the profile of volume and mass distribution of the fat phase (fat globules in the product, depending on the homogenization pressure and can be used in the laboratory and research of dairy products composition, as well as in the calculation, design and modeling of the process equipment of the dairy industry enterprises.
Mo Zhou; Joseph Buongiorno
2011-01-01
Most economic studies of forest decision making under risk assume a fixed interest rate. This paper investigated some implications of this stochastic nature of interest rates. Markov decision process (MDP) models, used previously to integrate stochastic stand growth and prices, can be extended to include variable interest rates as well. This method was applied to...
Stochastic behavior of cooling processes in hot nuclei
International Nuclear Information System (INIS)
de Oliveira, P.M.; Sa Martins, J.S.; Szanto de Toledo, A.
1997-01-01
The collapse of structure effects observed in hot nuclei is interpreted in terms of a dynamic lattice model which describes the process of nucleon (clusters) evaporation from a hot nucleus, predicting the final mass distribution. Results are compared with experimental data for the 10 B+ 9 Be and 10 B+ 10 B reactions, and indicate that the structures observed in the low-energy mass distributions in both simulation and experiment are a consequence of the competition between the residual interactions and the thermalization dissipative process. As a characteristic feature of complex evolving systems, this competition leads to long term memory during the dissipative path, the observables becoming thus insensitive to the actual microscopic interactions. copyright 1997 The American Physical Society
Pendar, Hodjat; Platini, Thierry; Kulkarni, Rahul V
2013-04-01
Stochasticity in gene expression gives rise to fluctuations in protein levels across a population of genetically identical cells. Such fluctuations can lead to phenotypic variation in clonal populations; hence, there is considerable interest in quantifying noise in gene expression using stochastic models. However, obtaining exact analytical results for protein distributions has been an intractable task for all but the simplest models. Here, we invoke the partitioning property of Poisson processes to develop a mapping that significantly simplifies the analysis of stochastic models of gene expression. The mapping leads to exact protein distributions using results for mRNA distributions in models with promoter-based regulation. Using this approach, we derive exact analytical results for steady-state and time-dependent distributions for the basic two-stage model of gene expression. Furthermore, we show how the mapping leads to exact protein distributions for extensions of the basic model that include the effects of posttranscriptional and posttranslational regulation. The approach developed in this work is widely applicable and can contribute to a quantitative understanding of stochasticity in gene expression and its regulation.
Pendar, Hodjat; Platini, Thierry; Kulkarni, Rahul V.
2013-04-01
Stochasticity in gene expression gives rise to fluctuations in protein levels across a population of genetically identical cells. Such fluctuations can lead to phenotypic variation in clonal populations; hence, there is considerable interest in quantifying noise in gene expression using stochastic models. However, obtaining exact analytical results for protein distributions has been an intractable task for all but the simplest models. Here, we invoke the partitioning property of Poisson processes to develop a mapping that significantly simplifies the analysis of stochastic models of gene expression. The mapping leads to exact protein distributions using results for mRNA distributions in models with promoter-based regulation. Using this approach, we derive exact analytical results for steady-state and time-dependent distributions for the basic two-stage model of gene expression. Furthermore, we show how the mapping leads to exact protein distributions for extensions of the basic model that include the effects of posttranscriptional and posttranslational regulation. The approach developed in this work is widely applicable and can contribute to a quantitative understanding of stochasticity in gene expression and its regulation.
Temporal order processing of syllables in the left parietal lobe.
Moser, Dana; Baker, Julie M; Sanchez, Carmen E; Rorden, Chris; Fridriksson, Julius
2009-10-07
Speech processing requires the temporal parsing of syllable order. Individuals suffering from posterior left hemisphere brain injury often exhibit temporal processing deficits as well as language deficits. Although the right posterior inferior parietal lobe has been implicated in temporal order judgments (TOJs) of visual information, there is limited evidence to support the role of the left inferior parietal lobe (IPL) in processing syllable order. The purpose of this study was to examine whether the left inferior parietal lobe is recruited during temporal order judgments of speech stimuli. Functional magnetic resonance imaging data were collected on 14 normal participants while they completed the following forced-choice tasks: (1) syllable order of multisyllabic pseudowords, (2) syllable identification of single syllables, and (3) gender identification of both multisyllabic and monosyllabic speech stimuli. Results revealed increased neural recruitment in the left inferior parietal lobe when participants made judgments about syllable order compared with both syllable identification and gender identification. These findings suggest that the left inferior parietal lobe plays an important role in processing syllable order and support the hypothesized role of this region as an interface between auditory speech and the articulatory code. Furthermore, a breakdown in this interface may explain some components of the speech deficits observed after posterior damage to the left hemisphere.
Spatio-temporal point process filtering methods with an application
Czech Academy of Sciences Publication Activity Database
Frcalová, B.; Beneš, V.; Klement, Daniel
2010-01-01
Roč. 21, 3-4 (2010), s. 240-252 ISSN 1180-4009 R&D Projects: GA AV ČR(CZ) IAA101120604 Institutional research plan: CEZ:AV0Z50110509 Keywords : cox point process * filtering * spatio-temporal modelling * spike Subject RIV: BA - General Mathematics Impact factor: 0.750, year: 2010
The gamma model : a new neural network for temporal processing
Vries, de B.
1992-01-01
In this paper we develop the gamma neural model, a new neural net architecture for processing of temporal patterns. Time varying patterns are normally segmented into a sequence of static patterns that are successively presented to a neural net. In the approach presented here segmentation is avoided.
Temporally selective processing of communication signals by auditory midbrain neurons
DEFF Research Database (Denmark)
Elliott, Taffeta M; Christensen-Dalsgaard, Jakob; Kelley, Darcy B
2011-01-01
click rates ranged from 4 to 50 Hz, the rate at which the clicks begin to overlap. Frequency selectivity and temporal processing were characterized using response-intensity curves, temporal-discharge patterns, and autocorrelations of reduplicated responses to click trains. Characteristic frequencies...... of the rate of clicks in calls. The majority of neurons (85%) were selective for click rates, and this selectivity remained unchanged over sound levels 10 to 20 dB above threshold. Selective neurons give phasic, tonic, or adapting responses to tone bursts and click trains. Some algorithms that could compute...
Reflection Positive Stochastic Processes Indexed by Lie Groups
Jorgensen, Palle E. T.; Neeb, Karl-Hermann; Ólafsson, Gestur
2016-06-01
Reflection positivity originates from one of the Osterwalder-Schrader axioms for constructive quantum field theory. It serves as a bridge between euclidean and relativistic quantum field theory. In mathematics, more specifically, in representation theory, it is related to the Cartan duality of symmetric Lie groups (Lie groups with an involution) and results in a transformation of a unitary representation of a symmetric Lie group to a unitary representation of its Cartan dual. In this article we continue our investigation of representation theoretic aspects of reflection positivity by discussing reflection positive Markov processes indexed by Lie groups, measures on path spaces, and invariant gaussian measures in spaces of distribution vectors. This provides new constructions of reflection positive unitary representations.
Tempered stable distributions stochastic models for multiscale processes
Grabchak, Michael
2015-01-01
This brief is concerned with tempered stable distributions and their associated Levy processes. It is a good text for researchers interested in learning about tempered stable distributions. A tempered stable distribution is one which takes a stable distribution and modifies its tails to make them lighter. The motivation for this class comes from the fact that infinite variance stable distributions appear to provide a good fit to data in a variety of situations, but the extremely heavy tails of these models are not realistic for most real world applications. The idea of using distributions that modify the tails of stable models to make them lighter seems to have originated in the influential paper of Mantegna and Stanley (1994). Since then, these distributions have been extended and generalized in a variety of ways. They have been applied to a wide variety of areas including mathematical finance, biostatistics,computer science, and physics.
International Nuclear Information System (INIS)
Sturm, R.
1991-01-01
Two aspects of performance are of main concern: plant availability and plant reliability (defined as the conditional probability of an unplanned shutdown). The goal of the research is a unified framework that combines behavioral models of optimizing agents with models of complex technical systems that take into account the dynamic and stochastic features of the system. In order to achieve this synthesis, two liens of work are necessary. One line requires a deeper understanding of complex production systems and the type of data they give rise to; the other line involves the specification and estimation of a rigorously specified behavioral model. Plant operations are modeled as a controlled stochastic process, and the sequence of up and downtime spells is analyzed during failure time and point process models. Similar to work on rational expectations and structural econometric models, the behavior model of how the plant process is controlled is formulated at the level of basic processes, i.e., the objective function of the plant manager, technical constraints, and stochastic disturbances
Katsoulakis, Markos A.; Vlachos, Dionisios G.
2003-11-01
We derive a hierarchy of successively coarse-grained stochastic processes and associated coarse-grained Monte Carlo (CGMC) algorithms directly from the microscopic processes as approximations in larger length scales for the case of diffusion of interacting particles on a lattice. This hierarchy of models spans length scales between microscopic and mesoscopic, satisfies a detailed balance, and gives self-consistent fluctuation mechanisms whose noise is asymptotically identical to the microscopic MC. Rigorous, detailed asymptotics justify and clarify these connections. Gradient continuous time microscopic MC and CGMC simulations are compared under far from equilibrium conditions to illustrate the validity of our theory and delineate the errors obtained by rigorous asymptotics. Information theory estimates are employed for the first time to provide rigorous error estimates between the solutions of microscopic MC and CGMC, describing the loss of information during the coarse-graining process. Simulations under periodic boundary conditions are used to verify the information theory error estimates. It is shown that coarse-graining in space leads also to coarse-graining in time by q2, where q is the level of coarse-graining, and overcomes in part the hydrodynamic slowdown. Operation counting and CGMC simulations demonstrate significant CPU savings in continuous time MC simulations that vary from q3 for short potentials to q4 for long potentials. Finally, connections of the new coarse-grained stochastic processes to stochastic mesoscopic and Cahn-Hilliard-Cook models are made.
Temporal processing deficit leads to impaired multisensory binding in schizophrenia.
Zvyagintsev, Mikhail; Parisi, Carmen; Mathiak, Klaus
2017-09-01
Schizophrenia has been characterised by neurodevelopmental dysconnectivity resulting in cognitive and perceptual dysmetria. Hence patients with schizophrenia may be impaired to detect the temporal relationship between stimuli in different sensory modalities. However, only a few studies described deficit in perception of temporally asynchronous multisensory stimuli in schizophrenia. We examined the perceptual bias and the processing time of synchronous and delayed sounds in the streaming-bouncing illusion in 16 patients with schizophrenia and a matched control group of 18 participants. Equal for patients and controls, the synchronous sound biased the percept of two moving squares towards bouncing as opposed to the more frequent streaming percept in the condition without sound. In healthy controls, a delay of the sound presentation significantly reduced the bias and led to prolonged processing time whereas patients with schizophrenia did not differentiate between this condition and the condition with synchronous sound. Schizophrenia leads to a prolonged window of simultaneity for audiovisual stimuli. Therefore, temporal processing deficit in schizophrenia can lead to hyperintegration of temporally unmatched multisensory stimuli.
An adaptive algorithm for simulation of stochastic reaction-diffusion processes
International Nuclear Information System (INIS)
Ferm, Lars; Hellander, Andreas; Loetstedt, Per
2010-01-01
We propose an adaptive hybrid method suitable for stochastic simulation of diffusion dominated reaction-diffusion processes. For such systems, simulation of the diffusion requires the predominant part of the computing time. In order to reduce the computational work, the diffusion in parts of the domain is treated macroscopically, in other parts with the tau-leap method and in the remaining parts with Gillespie's stochastic simulation algorithm (SSA) as implemented in the next subvolume method (NSM). The chemical reactions are handled by SSA everywhere in the computational domain. A trajectory of the process is advanced in time by an operator splitting technique and the timesteps are chosen adaptively. The spatial adaptation is based on estimates of the errors in the tau-leap method and the macroscopic diffusion. The accuracy and efficiency of the method are demonstrated in examples from molecular biology where the domain is discretized by unstructured meshes.
Reddy, V R; Reddy, T G; Reddy, P Y; Reddy, K R
2003-01-01
An AC modulation technique is described to convert stochastic signal variations into an amplitude variation and its retrieval through Fourier analysis. It is shown that this AC detection of signals of stochastic processes when processed through auto- and cross-correlation techniques improve the signal-to-noise ratio; the correlation techniques serve a similar purpose of frequency and phase filtering as that of phase-sensitive detection. A few model calculations applied to nuclear spectroscopy measurements such as Angular Correlations, Mossbauer spectroscopy and Pulse Height Analysis reveal considerable improvement in the sensitivity of signal detection. Experimental implementation of the technique is presented in terms of amplitude variations of harmonics representing the derivatives of normal spectra. Improved detection sensitivity to spectral variations is shown to be significant. These correlation techniques are general and can be made applicable to all the fields of particle counting where measurements ar...
Whole-field visual motion drives swimming in larval zebrafish via a stochastic process.
Portugues, Ruben; Haesemeyer, Martin; Blum, Mirella L; Engert, Florian
2015-05-01
Caudo-rostral whole-field visual motion elicits forward locomotion in many organisms, including larval zebrafish. Here, we investigate the dependence on the latency to initiate this forward swimming as a function of the speed of the visual motion. We show that latency is highly dependent on speed for slow speeds (1.5 s, which is much longer than neuronal transduction processes. What mechanisms underlie these long latencies? We propose two alternative, biologically inspired models that could account for this latency to initiate swimming: an integrate and fire model, which is history dependent, and a stochastic Poisson model, which has no history dependence. We use these models to predict the behavior of larvae when presented with whole-field motion of varying speed and find that the stochastic process shows better agreement with the experimental data. Finally, we discuss possible neuronal implementations of these models. © 2015. Published by The Company of Biologists Ltd.
Yang, Xin; Zeng, Zhenxiang; Wang, Ruidong; Sun, Xueshan
2016-01-01
This paper presents a novel method on the optimization of bi-objective Flexible Job-shop Scheduling Problem (FJSP) under stochastic processing times. The robust counterpart model and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) are used to solve the bi-objective FJSP with consideration of the completion time and the total energy consumption under stochastic processing times. The case study on GM Corporation verifies that the NSGA-II used in this paper is effective and has advantages to solve the proposed model comparing with HPSO and PSO+SA. The idea and method of the paper can be generalized widely in the manufacturing industry, because it can reduce the energy consumption of the energy-intensive manufacturing enterprise with less investment when the new approach is applied in existing systems.
Cerebro-cerebellar interactions underlying temporal information processing.
Aso, Kenji; Hanakawa, Takashi; Aso, Toshihiko; Fukuyama, Hidenao
2010-12-01
The neural basis of temporal information processing remains unclear, but it is proposed that the cerebellum plays an important role through its internal clock or feed-forward computation functions. In this study, fMRI was used to investigate the brain networks engaged in perceptual and motor aspects of subsecond temporal processing without accompanying coprocessing of spatial information. Direct comparison between perceptual and motor aspects of time processing was made with a categorical-design analysis. The right lateral cerebellum (lobule VI) was active during a time discrimination task, whereas the left cerebellar lobule VI was activated during a timed movement generation task. These findings were consistent with the idea that the cerebellum contributed to subsecond time processing in both perceptual and motor aspects. The feed-forward computational theory of the cerebellum predicted increased cerebro-cerebellar interactions during time information processing. In fact, a psychophysiological interaction analysis identified the supplementary motor and dorsal premotor areas, which had a significant functional connectivity with the right cerebellar region during a time discrimination task and with the left lateral cerebellum during a timed movement generation task. The involvement of cerebro-cerebellar interactions may provide supportive evidence that temporal information processing relies on the simulation of timing information through feed-forward computation in the cerebellum.
Stationary and related stochastic processes sample function properties and their applications
Cramér, Harald
2004-01-01
This graduate-level text offers a comprehensive account of the general theory of stationary processes, with special emphasis on the properties of sample functions. Assuming a familiarity with the basic features of modern probability theory, the text develops the foundations of the general theory of stochastic processes, examines processes with a continuous-time parameter, and applies the general theory to procedures key to the study of stationary processes. Additional topics include analytic properties of the sample functions and the problem of time distribution of the intersections between a
Anderson, David F; Yuan, Chaojie
2018-04-18
A number of coupling strategies are presented for stochastically modeled biochemical processes with time-dependent parameters. In particular, the stacked coupling is introduced and is shown via a number of examples to provide an exceptionally low variance between the generated paths. This coupling will be useful in the numerical computation of parametric sensitivities and the fast estimation of expectations via multilevel Monte Carlo methods. We provide the requisite estimators in both cases.
A decision dependent stochastic process model for repairable systems with applications
Directory of Open Access Journals (Sweden)
Paul F. Zantek
2015-12-01
This paper mathematically formalizes the notion of how management actions impact the functioning of a repairable system over time by developing a new stochastic process model for such systems. The proposed model is illustrated using both simulated and real data. The proposed model compares favorably to other models for well-known data on Boeing airplanes. The model is further illustrated and compared to other models on failure time and maintenance data stemming from the South Texas Project nuclear power plant.
Dini-Andreote, Francisco; Stegen, James C; van Elsas, Jan Dirk; Salles, Joana Falcão
2015-03-17
Ecological succession and the balance between stochastic and deterministic processes are two major themes within microbial ecology, but these conceptual domains have mostly developed independent of each other. Here we provide a framework that integrates shifts in community assembly processes with microbial primary succession to better understand mechanisms governing the stochastic/deterministic balance. Synthesizing previous work, we devised a conceptual model that links ecosystem development to alternative hypotheses related to shifts in ecological assembly processes. Conceptual model hypotheses were tested by coupling spatiotemporal data on soil bacterial communities with environmental conditions in a salt marsh chronosequence spanning 105 years of succession. Analyses within successional stages showed community composition to be initially governed by stochasticity, but as succession proceeded, there was a progressive increase in deterministic selection correlated with increasing sodium concentration. Analyses of community turnover among successional stages--which provide a larger spatiotemporal scale relative to within stage analyses--revealed that changes in the concentration of soil organic matter were the main predictor of the type and relative influence of determinism. Taken together, these results suggest scale-dependency in the mechanisms underlying selection. To better understand mechanisms governing these patterns, we developed an ecological simulation model that revealed how changes in selective environments cause shifts in the stochastic/deterministic balance. Finally, we propose an extended--and experimentally testable--conceptual model integrating ecological assembly processes with primary and secondary succession. This framework provides a priori hypotheses for future experiments, thereby facilitating a systematic approach to understand assembly and succession in microbial communities across ecosystems.
Model-free stochastic processes studied with q-wavelet-based informational tools
International Nuclear Information System (INIS)
Perez, D.G.; Zunino, L.; Martin, M.T.; Garavaglia, M.; Plastino, A.; Rosso, O.A.
2007-01-01
We undertake a model-free investigation of stochastic processes employing q-wavelet based quantifiers, that constitute a generalization of their Shannon counterparts. It is shown that (i) interesting physical information becomes accessible in such a way (ii) for special q values the quantifiers are more sensitive than the Shannon ones and (iii) there exist an implicit relationship between the Hurst parameter H and q within this wavelet framework
Stochastic Interest Model Based on Compound Poisson Process and Applications in Actuarial Science
Li, Shilong; Yin, Chuancun; Zhao, Xia; Dai, Hongshuai
2017-01-01
Considering stochastic behavior of interest rates in financial market, we construct a new class of interest models based on compound Poisson process. Different from the references, this paper describes the randomness of interest rates by modeling the force of interest with Poisson random jumps directly. To solve the problem in calculation of accumulated interest force function, one important integral technique is employed. And a conception called the critical value is introduced to investigat...
Stochastic processes, optimization, and control theory a volume in honor of Suresh Sethi
Yan, Houmin
2006-01-01
This edited volume contains 16 research articles. It presents recent and pressing issues in stochastic processes, control theory, differential games, optimization, and their applications in finance, manufacturing, queueing networks, and climate control. One of the salient features is that the book is highly multi-disciplinary. The book is dedicated to Professor Suresh Sethi on the occasion of his 60th birthday, in view of his distinguished career.
Spatio-Temporal Data Analysis at Scale Using Models Based on Gaussian Processes
Energy Technology Data Exchange (ETDEWEB)
Stein, Michael [Univ. of Chicago, IL (United States)
2017-03-13
Gaussian processes are the most commonly used statistical model for spatial and spatio-temporal processes that vary continuously. They are broadly applicable in the physical sciences and engineering and are also frequently used to approximate the output of complex computer models, deterministic or stochastic. We undertook research related to theory, computation, and applications of Gaussian processes as well as some work on estimating extremes of distributions for which a Gaussian process assumption might be inappropriate. Our theoretical contributions include the development of new classes of spatial-temporal covariance functions with desirable properties and new results showing that certain covariance models lead to predictions with undesirable properties. To understand how Gaussian process models behave when applied to deterministic computer models, we derived what we believe to be the first significant results on the large sample properties of estimators of parameters of Gaussian processes when the actual process is a simple deterministic function. Finally, we investigated some theoretical issues related to maxima of observations with varying upper bounds and found that, depending on the circumstances, standard large sample results for maxima may or may not hold. Our computational innovations include methods for analyzing large spatial datasets when observations fall on a partially observed grid and methods for estimating parameters of a Gaussian process model from observations taken by a polar-orbiting satellite. In our application of Gaussian process models to deterministic computer experiments, we carried out some matrix computations that would have been infeasible using even extended precision arithmetic by focusing on special cases in which all elements of the matrices under study are rational and using exact arithmetic. The applications we studied include total column ozone as measured from a polar-orbiting satellite, sea surface temperatures over the
Temporal texture of associative encoding modulates recall processes.
Tibon, Roni; Levy, Daniel A
2014-02-01
Binding aspects of an experience that are distributed over time is an important element of episodic memory. In the current study, we examined how the temporal complexity of an experience may govern the processes required for its retrieval. We recorded event-related potentials during episodic cued recall following pair associate learning of concurrently and sequentially presented object-picture pairs. Cued recall success effects over anterior and posterior areas were apparent in several time windows. In anterior locations, these recall success effects were similar for concurrently and sequentially encoded pairs. However, in posterior sites clustered over parietal scalp the effect was larger for the retrieval of sequentially encoded pairs. We suggest that anterior aspects of the mid-latency recall success effects may reflect working-with-memory operations or direct access recall processes, while more posterior aspects reflect recollective processes which are required for retrieval of episodes of greater temporal complexity. Copyright © 2013 Elsevier Inc. All rights reserved.
Temporal and Location Based RFID Event Data Management and Processing
Wang, Fusheng; Liu, Peiya
Advance of sensor and RFID technology provides significant new power for humans to sense, understand and manage the world. RFID provides fast data collection with precise identification of objects with unique IDs without line of sight, thus it can be used for identifying, locating, tracking and monitoring physical objects. Despite these benefits, RFID poses many challenges for data processing and management. RFID data are temporal and history oriented, multi-dimensional, and carrying implicit semantics. Moreover, RFID applications are heterogeneous. RFID data management or data warehouse systems need to support generic and expressive data modeling for tracking and monitoring physical objects, and provide automated data interpretation and processing. We develop a powerful temporal and location oriented data model for modeling and queryingRFID data, and a declarative event and rule based framework for automated complex RFID event processing. The approach is general and can be easily adapted for different RFID-enabled applications, thus significantly reduces the cost of RFID data integration.
Research on Process-oriented Spatio-temporal Data Model
Directory of Open Access Journals (Sweden)
XUE Cunjin
2016-02-01
Full Text Available According to the analysis of the present status and existing problems of spatio-temporal data models developed in last 20 years,this paper proposes a process-oriented spatio-temporal data model (POSTDM,aiming at representing,organizing and storing continuity and gradual geographical entities. The dynamic geographical entities are graded and abstracted into process objects series from their intrinsic characteristics,which are process objects,process stage objects,process sequence objects and process state objects. The logical relationships among process entities are further studied and the structure of UML models and storage are also designed. In addition,through the mechanisms of continuity and gradual changes impliedly recorded by process objects,and the modes of their procedure interfaces offered by the customized ObjcetStorageTable,the POSTDM can carry out process representation,storage and dynamic analysis of continuity and gradual geographic entities. Taking a process organization and storage of marine data as an example,a prototype system (consisting of an object-relational database and a functional analysis platform is developed for validating and evaluating the model's practicability.
Power Laws in Stochastic Processes for Social Phenomena: An Introductory Review
Kumamoto, Shin-Ichiro; Kamihigashi, Takashi
2018-03-01
Many phenomena with power laws have been observed in various fields of the natural and social sciences, and these power laws are often interpreted as the macro behaviors of systems that consist of micro units. In this paper, we review some basic mathematical mechanisms that are known to generate power laws. In particular, we focus on stochastic processes including the Yule process and the Simon process as well as some recent models. The main purpose of this paper is to explain the mathematical details of their mechanisms in a self-contained manner.
Dimension reduction of Karhunen-Loeve expansion for simulation of stochastic processes
Liu, Zhangjun; Liu, Zixin; Peng, Yongbo
2017-11-01
Conventional Karhunen-Loeve expansions for simulation of stochastic processes often encounter the challenge of dealing with hundreds of random variables. For breaking through the barrier, a random function embedded Karhunen-Loeve expansion method is proposed in this paper. The updated scheme has a similar form to the conventional Karhunen-Loeve expansion, both involving a summation of a series of deterministic orthonormal basis and uncorrelated random variables. While the difference from the updated scheme lies in the dimension reduction of Karhunen-Loeve expansion through introducing random functions as a conditional constraint upon uncorrelated random variables. The random function is expressed as a single-elementary-random-variable orthogonal function in polynomial format (non-Gaussian variables) or trigonometric format (non-Gaussian and Gaussian variables). For illustrative purposes, the simulation of seismic ground motion is carried out using the updated scheme. Numerical investigations reveal that the Karhunen-Loeve expansion with random functions could gain desirable simulation results in case of a moderate sample number, except the Hermite polynomials and the Laguerre polynomials. It has the sound applicability and efficiency in simulation of stochastic processes. Besides, the updated scheme has the benefit of integrating with probability density evolution method, readily for the stochastic analysis of nonlinear structures.
Nigsch, Annette; Costard, Solenne; Jones, Bryony A; Pfeiffer, Dirk U; Wieland, Barbara
2013-03-01
African swine fever (ASF) is a notifiable viral pig disease with high mortality and serious socio-economic consequences. Since ASF emerged in Georgia in 2007 the disease has spread to several neighbouring countries and cases have been detected in areas bordering the European Union (EU). It is uncertain how fast the virus would be able to spread within the unrestricted European trading area if it were introduced into the EU. This project therefore aimed to develop a model for the spread of ASF within and between the 27 Member States (MS) of the EU during the high risk period (HRP) and to identify MS during that period would most likely contribute to ASF spread ("super-spreaders") or MS that would most likely receive cases from other MS ("super-receivers"). A stochastic spatio-temporal state-transition model using simulated individual farm records was developed to assess silent ASF virus spread during different predefined HRPs of 10-60 days duration. Infection was seeded into farms of different pig production types in each of the 27 MS. Direct pig-to-pig transmission and indirect transmission routes (pig transport lorries and professional contacts) were considered the main pathways during the early stages of an epidemic. The model was parameterised using data collated from EUROSTAT, TRACES, a questionnaire sent to MS, and the scientific literature. Model outputs showed that virus circulation was generally limited to 1-2 infected premises per outbreak (95% IQR: 1-4; maximum: 10) with large breeder farms as index case resulting in most infected premises. Seven MS caused between-MS spread due to intra-Community trade during the first 10 days after seeding infection. For a HRP of 60 days from virus introduction, movements of infected pigs will originate at least once from 16 MS, with 6 MS spreading ASF in more than 10% of iterations. Two thirds of all intra-Community spread was linked to six trade links only. Denmark, the Netherlands, Lithuania and Latvia were identified
Hartman, Brian Davis
1995-01-01
A key drawback to estimating geodetic and geodynamic parameters over time based on satellite laser ranging (SLR) observations is the inability to accurately model all the forces acting on the satellite. Errors associated with the observations and the measurement model can detract from the estimates as well. These 'model errors' corrupt the solutions obtained from the satellite orbit determination process. Dynamical models for satellite motion utilize known geophysical parameters to mathematically detail the forces acting on the satellite. However, these parameters, while estimated as constants, vary over time. These temporal variations must be accounted for in some fashion to maintain meaningful solutions. The primary goal of this study is to analyze the feasibility of using a sequential process noise filter for estimating geodynamic parameters over time from the Laser Geodynamics Satellite (LAGEOS) SLR data. This evaluation is achieved by first simulating a sequence of realistic LAGEOS laser ranging observations. These observations are generated using models with known temporal variations in several geodynamic parameters (along track drag and the J(sub 2), J(sub 3), J(sub 4), and J(sub 5) geopotential coefficients). A standard (non-stochastic) filter and a stochastic process noise filter are then utilized to estimate the model parameters from the simulated observations. The standard non-stochastic filter estimates these parameters as constants over consecutive fixed time intervals. Thus, the resulting solutions contain constant estimates of parameters that vary in time which limits the temporal resolution and accuracy of the solution. The stochastic process noise filter estimates these parameters as correlated process noise variables. As a result, the stochastic process noise filter has the potential to estimate the temporal variations more accurately since the constraint of estimating the parameters as constants is eliminated. A comparison of the temporal
Contribution to the stochastically studies of space-time dependable hydrological processes
International Nuclear Information System (INIS)
Kjaevski, Ivancho
2002-12-01
One of the fundaments of today's planning and water economy is Science of Hydrology. Science of Hydrology through the history had followed the development of the water management systems. Water management systems, during the time from single-approach evolved to complex and multi purpose systems. The dynamic and development of the today's society contributed for increasing the demand of clean water, and in the same time, the resources of clean water in the nature are reduced. In this kind of conditions, water management systems should resolve problems that are more complicated during managing of water sources. Solving the problems in water management, enable development and applying new methods and technologies in planning and management with water resources and water management systems like: systematical analyses, operational research, hierarchy decisions, expert systems, computer technology etc. Planning and management of water sources needs historical measured data for hydro metrological processes. In our country there are data of hydro metrological processes in period of 50-70, but in some Europe countries there are data more than 100 years. Water economy trends follow the hydro metrological trend research. The basic statistic techniques like sampling, probability distribution function, correlation and regression, are used about one intended and simple water management problems. Solving new problems about water management needs using of space-time stochastic technique, modem mathematical and statistical techniques during simulation and optimization of complex water systems. We need tree phases of development of the techniques to get secure hydrological models: i) Estimate the quality of hydro meteorological data, analyzing of their consistency, and homogeneous; ii) Structural analyze of hydro meteorological processes; iii) Mathematical models for modeling hydro meteorological processes. Very often, the third phase is applied for analyzing and modeling of hydro
On a stochastic process associated to non-abelian gauge fields
International Nuclear Information System (INIS)
Vilela Mendes, R.
1989-01-01
A stochastic process is constructed from a ground state measure that generalizes to non-abelian fields the ground state of abelian (free) gauge fields without fermions. Using a latticized version one shows how the process leads to a well-defined quantum theory in the Schroedinger representation. An analysis of the qualitative behaviour of the theory seems to imply a quasi-free behaviour at short distances and a maximally disordered field strength configuration for the low-momentum component of the ground state. Scaling relations for the mass gap are inferred from the theory of small random perturbations of dynamical systems. (orig.)
On time-dependent diffusion coefficients arising from stochastic processes with memory
Carpio-Bernido, M. Victoria; Barredo, Wilson I.; Bernido, Christopher C.
2017-08-01
Time-dependent diffusion coefficients arise from anomalous diffusion encountered in many physical systems such as protein transport in cells. We compare these coefficients with those arising from analysis of stochastic processes with memory that go beyond fractional Brownian motion. Facilitated by the Hida white noise functional integral approach, diffusion propagators or probability density functions (pdf) are obtained and shown to be solutions of modified diffusion equations with time-dependent diffusion coefficients. This should be useful in the study of complex transport processes.
SDE decomposition and A-type stochastic interpretation in nonequilibrium processes
Yuan, Ruoshi; Tang, Ying; Ao, Ping
2017-12-01
An innovative theoretical framework for stochastic dynamics based on the decomposition of a stochastic differential equation (SDE) into a dissipative component, a detailed-balance-breaking component, and a dual-role potential landscape has been developed, which has fruitful applications in physics, engineering, chemistry, and biology. It introduces the A-type stochastic interpretation of the SDE beyond the traditional Ito or Stratonovich interpretation or even the α-type interpretation for multidimensional systems. The potential landscape serves as a Hamiltonian-like function in nonequilibrium processes without detailed balance, which extends this important concept from equilibrium statistical physics to the nonequilibrium region. A question on the uniqueness of the SDE decomposition was recently raised. Our review of both the mathematical and physical aspects shows that uniqueness is guaranteed. The demonstration leads to a better understanding of the robustness of the novel framework. In addition, we discuss related issues including the limitations of an approach to obtaining the potential function from a steady-state distribution.
International Nuclear Information System (INIS)
Nafidi, A.; Gutiérrez, R.; Gutiérrez-Sánchez, R.; Ramos-Ábalos, E.; El Hachimi, S.
2016-01-01
The aim of this study is to model electric power consumption during a period of economic crisis, characterised by declining gross domestic product. A novel aspect of this study is its use of a Gamma-type diffusion process for short and medium-term forecasting – other techniques that have been used to describe such consumption patterns are not valid in this situation. In this study, we consider a new extension of the stochastic Gamma diffusion process by introducing time functions (exogenous factors) that affect its trend. This extension is defined in terms of Kolmogorov backward and forward equations. After obtaining the transition probability density function and the moments (specifically, the trend function), the inference on the process parameters is obtained by discrete sampling of the sample paths. Finally, this stochastic process is applied to model total net electricity consumption in Spain, when affected by the following set of exogenous factors: Gross Domestic Product (GDP), Gross Fixed Capital Formation (GFCF) and Final Domestic Consumption (FDC). - Highlights: • The aim is modelling and predicting electricity consumption in Spain. • We propose a Gamma-type diffusion process for short and medium-term forecasting. • We compared the fit using diffusion processes with different exogenous factors.
Hidden symmetries and equilibrium properties of multiplicative white-noise stochastic processes
González Arenas, Zochil; Barci, Daniel G.
2012-12-01
Multiplicative white-noise stochastic processes continue to attract attention in a wide area of scientific research. The variety of prescriptions available for defining them makes the development of general tools for their characterization difficult. In this work, we study equilibrium properties of Markovian multiplicative white-noise processes. For this, we define the time reversal transformation for such processes, taking into account that the asymptotic stationary probability distribution depends on the prescription. Representing the stochastic process in a functional Grassmann formalism, we avoid the necessity of fixing a particular prescription. In this framework, we analyze equilibrium properties and study hidden symmetries of the process. We show that, using a careful definition of the equilibrium distribution and taking into account the appropriate time reversal transformation, usual equilibrium properties are satisfied for any prescription. Finally, we present a detailed deduction of a covariant supersymmetric formulation of a multiplicative Markovian white-noise process and study some of the constraints that it imposes on correlation functions using Ward-Takahashi identities.
Hidden symmetries and equilibrium properties of multiplicative white-noise stochastic processes
International Nuclear Information System (INIS)
Arenas, Zochil González; Barci, Daniel G
2012-01-01
Multiplicative white-noise stochastic processes continue to attract attention in a wide area of scientific research. The variety of prescriptions available for defining them makes the development of general tools for their characterization difficult. In this work, we study equilibrium properties of Markovian multiplicative white-noise processes. For this, we define the time reversal transformation for such processes, taking into account that the asymptotic stationary probability distribution depends on the prescription. Representing the stochastic process in a functional Grassmann formalism, we avoid the necessity of fixing a particular prescription. In this framework, we analyze equilibrium properties and study hidden symmetries of the process. We show that, using a careful definition of the equilibrium distribution and taking into account the appropriate time reversal transformation, usual equilibrium properties are satisfied for any prescription. Finally, we present a detailed deduction of a covariant supersymmetric formulation of a multiplicative Markovian white-noise process and study some of the constraints that it imposes on correlation functions using Ward–Takahashi identities. (paper)
Peccati, Giovanni
2016-01-01
Stochastic geometry is the branch of mathematics that studies geometric structures associated with random configurations, such as random graphs, tilings and mosaics. Due to its close ties with stereology and spatial statistics, the results in this area are relevant for a large number of important applications, e.g. to the mathematical modeling and statistical analysis of telecommunication networks, geostatistics and image analysis. In recent years – due mainly to the impetus of the authors and their collaborators – a powerful connection has been established between stochastic geometry and the Malliavin calculus of variations, which is a collection of probabilistic techniques based on the properties of infinite-dimensional differential operators. This has led in particular to the discovery of a large number of new quantitative limit theorems for high-dimensional geometric objects. This unique book presents an organic collection of authoritative surveys written by the principal actors in this rapidly evolvi...
Video game players show more precise multisensory temporal processing abilities.
Donohue, Sarah E; Woldorff, Marty G; Mitroff, Stephen R
2010-05-01
Recent research has demonstrated enhanced visual attention and visual perception in individuals with extensive experience playing action video games. These benefits manifest in several realms, but much remains unknown about the ways in which video game experience alters perception and cognition. In the present study, we examined whether video game players' benefits generalize beyond vision to multisensory processing by presenting auditory and visual stimuli within a short temporal window to video game players and non-video game players. Participants performed two discrimination tasks, both of which revealed benefits for video game players: In a simultaneity judgment task, video game players were better able to distinguish whether simple visual and auditory stimuli occurred at the same moment or slightly offset in time, and in a temporal-order judgment task, they revealed an enhanced ability to determine the temporal sequence of multisensory stimuli. These results suggest that people with extensive experience playing video games display benefits that extend beyond the visual modality to also impact multisensory processing.
Temporal factors affecting somatosensory-auditory interactions in speech processing
Directory of Open Access Journals (Sweden)
Takayuki eIto
2014-11-01
Full Text Available Speech perception is known to rely on both auditory and visual information. However, sound specific somatosensory input has been shown also to influence speech perceptual processing (Ito et al., 2009. In the present study we addressed further the relationship between somatosensory information and speech perceptual processing by addressing the hypothesis that the temporal relationship between orofacial movement and sound processing contributes to somatosensory-auditory interaction in speech perception. We examined the changes in event-related potentials in response to multisensory synchronous (simultaneous and asynchronous (90 ms lag and lead somatosensory and auditory stimulation compared to individual unisensory auditory and somatosensory stimulation alone. We used a robotic device to apply facial skin somatosensory deformations that were similar in timing and duration to those experienced in speech production. Following synchronous multisensory stimulation the amplitude of the event-related potential was reliably different from the two unisensory potentials. More importantly, the magnitude of the event-related potential difference varied as a function of the relative timing of the somatosensory-auditory stimulation. Event-related activity change due to stimulus timing was seen between 160-220 ms following somatosensory onset, mostly around the parietal area. The results demonstrate a dynamic modulation of somatosensory-auditory convergence and suggest the contribution of somatosensory information for speech processing process is dependent on the specific temporal order of sensory inputs in speech production.
Auditory temporal processing skills in musicians with dyslexia.
Bishop-Liebler, Paula; Welch, Graham; Huss, Martina; Thomson, Jennifer M; Goswami, Usha
2014-08-01
The core cognitive difficulty in developmental dyslexia involves phonological processing, but adults and children with dyslexia also have sensory impairments. Impairments in basic auditory processing show particular links with phonological impairments, and recent studies with dyslexic children across languages reveal a relationship between auditory temporal processing and sensitivity to rhythmic timing and speech rhythm. As rhythm is explicit in music, musical training might have a beneficial effect on the auditory perception of acoustic cues to rhythm in dyslexia. Here we took advantage of the presence of musicians with and without dyslexia in musical conservatoires, comparing their auditory temporal processing abilities with those of dyslexic non-musicians matched for cognitive ability. Musicians with dyslexia showed equivalent auditory sensitivity to musicians without dyslexia and also showed equivalent rhythm perception. The data support the view that extensive rhythmic experience initiated during childhood (here in the form of music training) can affect basic auditory processing skills which are found to be deficient in individuals with dyslexia. Copyright © 2014 John Wiley & Sons, Ltd.
Quantum learning of classical stochastic processes: The completely positive realization problem
Monràs, Alex; Winter, Andreas
2016-01-01
Among several tasks in Machine Learning, a specially important one is the problem of inferring the latent variables of a system and their causal relations with the observed behavior. A paradigmatic instance of this is the task of inferring the hidden Markov model underlying a given stochastic process. This is known as the positive realization problem (PRP), [L. Benvenuti and L. Farina, IEEE Trans. Autom. Control 49(5), 651-664 (2004)] and constitutes a central problem in machine learning. The PRP and its solutions have far-reaching consequences in many areas of systems and control theory, and is nowadays an important piece in the broad field of positive systems theory. We consider the scenario where the latent variables are quantum (i.e., quantum states of a finite-dimensional system) and the system dynamics is constrained only by physical transformations on the quantum system. The observable dynamics is then described by a quantum instrument, and the task is to determine which quantum instrument — if any — yields the process at hand by iterative application. We take as a starting point the theory of quasi-realizations, whence a description of the dynamics of the process is given in terms of linear maps on state vectors and probabilities are given by linear functionals on the state vectors. This description, despite its remarkable resemblance with the hidden Markov model, or the iterated quantum instrument, is however devoid of any stochastic or quantum mechanical interpretation, as said maps fail to satisfy any positivity conditions. The completely positive realization problem then consists in determining whether an equivalent quantum mechanical description of the same process exists. We generalize some key results of stochastic realization theory, and show that the problem has deep connections with operator systems theory, giving possible insight to the lifting problem in quotient operator systems. Our results have potential applications in quantum machine
Quantum learning of classical stochastic processes: The completely positive realization problem
Energy Technology Data Exchange (ETDEWEB)
Monràs, Alex [Física Teòrica: Informació i Fenòmens Quàntics, Universitat Autònoma de Barcelona, 08193 Bellaterra (Barcelona) (Spain); Centre for Quantum Technologies, National University of Singapore, 3 Science Drive 2, Singapore 117543 (Singapore); Winter, Andreas [Física Teòrica: Informació i Fenòmens Quàntics, Universitat Autònoma de Barcelona, 08193 Bellaterra (Barcelona) (Spain); Centre for Quantum Technologies, National University of Singapore, 3 Science Drive 2, Singapore 117543 (Singapore); ICREA—Institució Catalana de Recerca i Estudis Avançats, Pg. Lluis Companys, 23, 08010 Barcelona (Spain)
2016-01-15
Among several tasks in Machine Learning, a specially important one is the problem of inferring the latent variables of a system and their causal relations with the observed behavior. A paradigmatic instance of this is the task of inferring the hidden Markov model underlying a given stochastic process. This is known as the positive realization problem (PRP), [L. Benvenuti and L. Farina, IEEE Trans. Autom. Control 49(5), 651–664 (2004)] and constitutes a central problem in machine learning. The PRP and its solutions have far-reaching consequences in many areas of systems and control theory, and is nowadays an important piece in the broad field of positive systems theory. We consider the scenario where the latent variables are quantum (i.e., quantum states of a finite-dimensional system) and the system dynamics is constrained only by physical transformations on the quantum system. The observable dynamics is then described by a quantum instrument, and the task is to determine which quantum instrument — if any — yields the process at hand by iterative application. We take as a starting point the theory of quasi-realizations, whence a description of the dynamics of the process is given in terms of linear maps on state vectors and probabilities are given by linear functionals on the state vectors. This description, despite its remarkable resemblance with the hidden Markov model, or the iterated quantum instrument, is however devoid of any stochastic or quantum mechanical interpretation, as said maps fail to satisfy any positivity conditions. The completely positive realization problem then consists in determining whether an equivalent quantum mechanical description of the same process exists. We generalize some key results of stochastic realization theory, and show that the problem has deep connections with operator systems theory, giving possible insight to the lifting problem in quotient operator systems. Our results have potential applications in quantum machine
Quantum learning of classical stochastic processes: The completely positive realization problem
International Nuclear Information System (INIS)
Monràs, Alex; Winter, Andreas
2016-01-01
Among several tasks in Machine Learning, a specially important one is the problem of inferring the latent variables of a system and their causal relations with the observed behavior. A paradigmatic instance of this is the task of inferring the hidden Markov model underlying a given stochastic process. This is known as the positive realization problem (PRP), [L. Benvenuti and L. Farina, IEEE Trans. Autom. Control 49(5), 651–664 (2004)] and constitutes a central problem in machine learning. The PRP and its solutions have far-reaching consequences in many areas of systems and control theory, and is nowadays an important piece in the broad field of positive systems theory. We consider the scenario where the latent variables are quantum (i.e., quantum states of a finite-dimensional system) and the system dynamics is constrained only by physical transformations on the quantum system. The observable dynamics is then described by a quantum instrument, and the task is to determine which quantum instrument — if any — yields the process at hand by iterative application. We take as a starting point the theory of quasi-realizations, whence a description of the dynamics of the process is given in terms of linear maps on state vectors and probabilities are given by linear functionals on the state vectors. This description, despite its remarkable resemblance with the hidden Markov model, or the iterated quantum instrument, is however devoid of any stochastic or quantum mechanical interpretation, as said maps fail to satisfy any positivity conditions. The completely positive realization problem then consists in determining whether an equivalent quantum mechanical description of the same process exists. We generalize some key results of stochastic realization theory, and show that the problem has deep connections with operator systems theory, giving possible insight to the lifting problem in quotient operator systems. Our results have potential applications in quantum machine
Stochastic Processes and Queueing Theory used in Cloud Computer Performance Simulations
Directory of Open Access Journals (Sweden)
Florin-Catalin ENACHE
2015-10-01
Full Text Available The growing character of the cloud business has manifested exponentially in the last 5 years. The capacity managers need to concentrate on a practical way to simulate the random demands a cloud infrastructure could face, even if there are not too many mathematical tools to simulate such demands.This paper presents an introduction into the most important stochastic processes and queueing theory concepts used for modeling computer performance. Moreover, it shows the cases where such concepts are applicable and when not, using clear programming examples on how to simulate a queue, and how to use and validate a simulation, when there are no mathematical concepts to back it up.
The ‘hit’ phenomenon: a mathematical model of human dynamics interactions as a stochastic process
Ishii, Akira; Arakaki, Hisashi; Matsuda, Naoya; Umemura, Sanae; Urushidani, Tamiko; Yamagata, Naoya; Yoshida, Narihiko
2012-06-01
A mathematical model for the ‘hit’ phenomenon in entertainment within a society is presented as a stochastic process of human dynamics interactions. The model uses only the advertisement budget time distribution as an input, and word-of-mouth (WOM), represented by posts on social network systems, is used as data to make a comparison with the calculated results. The unit of time is days. The WOM distribution in time is found to be very close to the revenue distribution in time. Calculations for the Japanese motion picture market based on the mathematical model agree well with the actual revenue distribution in time.
Krylov, N. V.; Priola, E.
2017-09-01
We show, among other things, how knowing Schauder or Sobolev-space estimates for the one-dimensional heat equation allows one to derive their multidimensional analogs for equations with coefficients depending only on the time variable with the same constants as in the case of the one-dimensional heat equation. The method is quite general and is based on using the Poisson stochastic process. It also applies to equations involving non-local operators. It looks like no other methods are available at this time and it is a very challenging problem to find a purely analytical approach to proving such results.
International Nuclear Information System (INIS)
Vignes, J.
1986-01-01
Any result of algorithms provided by a computer always contains an error resulting from floating-point arithmetic round-off error propagation. Furthermore signal processing algorithms are also generally performed with data containing errors. The permutation-perturbation method, also known under the name CESTAC (controle et estimation stochastique d'arrondi de calcul) is a very efficient practical method for evaluating these errors and consequently for estimating the exact significant decimal figures of any result of algorithms performed on a computer. The stochastic approach of this method, its probabilistic proof, and the perfect agreement between the theoretical and practical aspects are described in this paper [fr
Temporal dynamics of biogeochemical processes at the Norman Landfill site
Arora, Bhavna; Mohanty, Binayak P.; McGuire, Jennifer T.; Cozzarelli, Isabelle M.
2013-01-01
The temporal variability observed in redox sensitive species in groundwater can be attributed to coupled hydrological, geochemical, and microbial processes. These controlling processes are typically nonstationary, and distributed across various time scales. Therefore, the purpose of this study is to investigate biogeochemical data sets from a municipal landfill site to identify the dominant modes of variation and determine the physical controls that become significant at different time scales. Data on hydraulic head, specific conductance, δ2H, chloride, sulfate, nitrate, and nonvolatile dissolved organic carbon were collected between 1998 and 2000 at three wells at the Norman Landfill site in Norman, OK. Wavelet analysis on this geochemical data set indicates that variations in concentrations of reactive and conservative solutes are strongly coupled to hydrologic variability (water table elevation and precipitation) at 8 month scales, and to individual eco-hydrogeologic framework (such as seasonality of vegetation, surface-groundwater dynamics) at 16 month scales. Apart from hydrologic variations, temporal variability in sulfate concentrations can be associated with different sources (FeS cycling, recharge events) and sinks (uptake by vegetation) depending on the well location and proximity to the leachate plume. Results suggest that nitrate concentrations show multiscale behavior across temporal scales for different well locations, and dominant variability in dissolved organic carbon for a closed municipal landfill can be larger than 2 years due to its decomposition and changing content. A conceptual framework that explains the variability in chemical concentrations at different time scales as a function of hydrologic processes, site-specific interactions, and/or coupled biogeochemical effects is also presented.
Analysis methods of stochastic transient electro–magnetic processes in electric traction system
Directory of Open Access Journals (Sweden)
T. M. Mishchenko
2013-04-01
Full Text Available Purpose. The essence and basic characteristics of calculation methods of transient electromagnetic processes in the elements and devices of non–linear dynamic electric traction systems taking into account the stochastic changes of voltages and currents in traction networks of power supply subsystem and power circuits of electric rolling stock are developed. Methodology. Classical methods and the methods of non–linear electric engineering, as well as probability theory method, especially the methods of stationary ergodic and non–stationary stochastic processes application are used in the research. Findings. Using the above-mentioned methods an equivalent circuit and the system of nonlinear integra–differential equations for electromagnetic condition of the double–track inter-substation zone of alternating current electric traction system are drawn up. Calculations allow obtaining electric traction current distribution in the areas of feeder zones. Originality. First of all the paper is interesting and important from scientific point of view due to the methods, which allow taking into account probabilistic character of change for traction voltages and electric traction system currents. On the second hand the researches develop the most efficient methods of nonlinear circuits’ analysis. Practical value. The practical value of the research is presented in application of the methods to the analysis of electromagnetic and electric energy processes in the traction power supply system in the case of high-speed train traffic.
Strategic WIP Inventory Positioning for Make-to-Order Production with Stochastic Processing Times
Directory of Open Access Journals (Sweden)
Jingjing Jiang
2017-01-01
Full Text Available It is vital for make-to-order manufacturers to shorten the lead time to meet the customers’ requirements. Holding work-in-process (WIP inventory at more stations can reduce the lead time, but it also brings about higher inventory holding cost. Therefore, it is important to seek out the optimal set of stations to hold WIP inventory to minimize the total inventory holding cost, while meeting the required due date for the final product at the same time. Since the problem with deterministic processing times at the stations has been addressed, as a natural extension, in this study, we address the problem with stochastic processing times, which is more realistic in the manufacturing environment. Assuming that the processing times follow normal distributions, we propose a solution procedure using genetic algorithm.
Elliott, Thomas J.; Gu, Mile
2018-03-01
Continuous-time stochastic processes pervade everyday experience, and the simulation of models of these processes is of great utility. Classical models of systems operating in continuous-time must typically track an unbounded amount of information about past behaviour, even for relatively simple models, enforcing limits on precision due to the finite memory of the machine. However, quantum machines can require less information about the past than even their optimal classical counterparts to simulate the future of discrete-time processes, and we demonstrate that this advantage extends to the continuous-time regime. Moreover, we show that this reduction in the memory requirement can be unboundedly large, allowing for arbitrary precision even with a finite quantum memory. We provide a systematic method for finding superior quantum constructions, and a protocol for analogue simulation of continuous-time renewal processes with a quantum machine.
Aspects of second-order analysis of structured inhomogeneous spatio-temporal processes
DEFF Research Database (Denmark)
Møller, Jesper; Ghorbani, Mohammad
2012-01-01
Statistical methodology for spatio-temporal point processes is in its infancy. We consider second-order analysis based on pair correlation functions and K-functions for general inhomogeneous spatio-temporal point processes and for inhomogeneous spatio-temporal Cox processes. Assuming spatio......-temporal separability of the intensity function, we clarify different meanings of second-order spatio-temporal separability. One is second-order spatio-temporal independence and relates to log-Gaussian Cox processes with an additive covariance structure of the underlying spatio-temporal Gaussian process. Another...... concerns shot-noise Cox processes with a separable spatio-temporal covariance density. We propose diagnostic procedures for checking hypotheses of second-order spatio-temporal separability, which we apply on simulated and real data....
Second-order analysis of structured inhomogeneous spatio-temporal point processes
DEFF Research Database (Denmark)
Møller, Jesper; Ghorbani, Mohammad
Statistical methodology for spatio-temporal point processes is in its infancy. We consider second-order analysis based on pair correlation functions and K-functions for first general inhomogeneous spatio-temporal point processes and second inhomogeneous spatio-temporal Cox processes. Assuming...... spatio-temporal separability of the intensity function, we clarify different meanings of second-order spatio-temporal separability. One is second-order spatio-temporal independence and relates e.g. to log-Gaussian Cox processes with an additive covariance structure of the underlying spatio......-temporal Gaussian process. Another concerns shot-noise Cox processes with a separable spatio-temporal covariance density. We propose diagnostic procedures for checking hypotheses of second-order spatio-temporal separability, which we apply on simulated and real data (the UK 2001 epidemic foot and mouth disease data)....
Drawert, Brian; Engblom, Stefan; Hellander, Andreas
2012-06-22
Experiments in silico using stochastic reaction-diffusion models have emerged as an important tool in molecular systems biology. Designing computational software for such applications poses several challenges. Firstly, realistic lattice-based modeling for biological applications requires a consistent way of handling complex geometries, including curved inner- and outer boundaries. Secondly, spatiotemporal stochastic simulations are computationally expensive due to the fast time scales of individual reaction- and diffusion events when compared to the biological phenomena of actual interest. We therefore argue that simulation software needs to be both computationally efficient, employing sophisticated algorithms, yet in the same time flexible in order to meet present and future needs of increasingly complex biological modeling. We have developed URDME, a flexible software framework for general stochastic reaction-transport modeling and simulation. URDME uses Unstructured triangular and tetrahedral meshes to resolve general geometries, and relies on the Reaction-Diffusion Master Equation formalism to model the processes under study. An interface to a mature geometry and mesh handling external software (Comsol Multiphysics) provides for a stable and interactive environment for model construction. The core simulation routines are logically separated from the model building interface and written in a low-level language for computational efficiency. The connection to the geometry handling software is realized via a Matlab interface which facilitates script computing, data management, and post-processing. For practitioners, the software therefore behaves much as an interactive Matlab toolbox. At the same time, it is possible to modify and extend URDME with newly developed simulation routines. Since the overall design effectively hides the complexity of managing the geometry and meshes, this means that newly developed methods may be tested in a realistic setting already at
Abas, Norzaida; Daud, Zalina M.; Yusof, Fadhilah
2014-11-01
A stochastic rainfall model is presented for the generation of hourly rainfall data in an urban area in Malaysia. In view of the high temporal and spatial variability of rainfall within the tropical rain belt, the Spatial-Temporal Neyman-Scott Rectangular Pulse model was used. The model, which is governed by the Neyman-Scott process, employs a reasonable number of parameters to represent the physical attributes of rainfall. A common approach is to attach each attribute to a mathematical distribution. With respect to rain cell intensity, this study proposes the use of a mixed exponential distribution. The performance of the proposed model was compared to a model that employs the Weibull distribution. Hourly and daily rainfall data from four stations in the Damansara River basin in Malaysia were used as input to the models, and simulations of hourly series were performed for an independent site within the basin. The performance of the models was assessed based on how closely the statistical characteristics of the simulated series resembled the statistics of the observed series. The findings obtained based on graphical representation revealed that the statistical characteristics of the simulated series for both models compared reasonably well with the observed series. However, a further assessment using the AIC, BIC and RMSE showed that the proposed model yields better results. The results of this study indicate that for tropical climates, the proposed model, using a mixed exponential distribution, is the best choice for generation of synthetic data for ungauged sites or for sites with insufficient data within the limit of the fitted region.
Stochastic and Deterministic Models for the Metastatic Emission Process: Formalisms and Crosslinks.
Gomez, Christophe; Hartung, Niklas
2018-01-01
Although the detection of metastases radically changes prognosis of and treatment decisions for a cancer patient, clinically undetectable micrometastases hamper a consistent classification into localized or metastatic disease. This chapter discusses mathematical modeling efforts that could help to estimate the metastatic risk in such a situation. We focus on two approaches: (1) a stochastic framework describing metastatic emission events at random times, formalized via Poisson processes, and (2) a deterministic framework describing the micrometastatic state through a size-structured density function in a partial differential equation model. Three aspects are addressed in this chapter. First, a motivation for the Poisson process framework is presented and modeling hypotheses and mechanisms are introduced. Second, we extend the Poisson model to account for secondary metastatic emission. Third, we highlight an inherent crosslink between the stochastic and deterministic frameworks and discuss its implications. For increased accessibility the chapter is split into an informal presentation of the results using a minimum of mathematical formalism and a rigorous mathematical treatment for more theoretically interested readers.
Liu, Zhangjun; Liu, Zenghui; Peng, Yongbo
2018-03-01
In view of the Fourier-Stieltjes integral formula of multivariate stationary stochastic processes, a unified formulation accommodating spectral representation method (SRM) and proper orthogonal decomposition (POD) is deduced. By introducing random functions as constraints correlating the orthogonal random variables involved in the unified formulation, the dimension-reduction spectral representation method (DR-SRM) and the dimension-reduction proper orthogonal decomposition (DR-POD) are addressed. The proposed schemes are capable of representing the multivariate stationary stochastic process with a few elementary random variables, bypassing the challenges of high-dimensional random variables inherent in the conventional Monte Carlo methods. In order to accelerate the numerical simulation, the technique of Fast Fourier Transform (FFT) is integrated with the proposed schemes. For illustrative purposes, the simulation of horizontal wind velocity field along the deck of a large-span bridge is proceeded using the proposed methods containing 2 and 3 elementary random variables. Numerical simulation reveals the usefulness of the dimension-reduction representation methods.
Directory of Open Access Journals (Sweden)
Huapu Lu
2017-01-01
Full Text Available This paper aims at introducing a new improved stochastic differential equation related to Gompertz curve for the projection of vehicle ownership growth. This diffusion model explains the relationship between vehicle ownership and GDP per capita, which has been studied as a Gompertz-like function before. The main innovations of the process lie in two parts: by modifying the deterministic part of the original Gompertz equation, the model can present the remaining slow increase when the S-shaped curve has reached its saturation level; by introducing the stochastic differential equation, the model can better fit the real data when there are fluctuations. Such comparisons are carried out based on data from US, UK, Japan, and Korea with a time span of 1960–2008. It turns out that the new process behaves better in fitting curves and predicting short term growth. Finally, a prediction of Chinese vehicle ownership up to 2025 is presented with the new model, as China is on the initial stage of motorization with much fluctuations in growth.
International Nuclear Information System (INIS)
Lee, Kwang Ho; Roh, Myung Sub
2013-01-01
There are so many different factors to consider when constructing a nuclear power plant successfully from planning to decommissioning. According to PMBOK, all projects have nine domains from a holistic project management perspective. They are equally important to all projects, however, this study focuses mostly on the processes required to manage timely completion of the project and conduct risk management. The overall objective of this study is to let you know what the risk analysis derived from scheduling of NPP project is, and understand how to implement the stochastic process modeling through risk management. Building the Nuclear Power Plant is required a great deal of time and fundamental knowledge related to all engineering. That means that integrated project scheduling management with so many activities is necessary and very important. Simulation techniques for scheduling of NPP project using Open Plan program, Crystal Ball program, and Minitab program can be useful tools for designing optimal schedule planning. Thus far, Open Plan and Monte Carlo programs have been used to calculate the critical path for scheduling network analysis. And also, Minitab program has been applied to monitor the scheduling risk. This approach to stochastic modeling through risk analysis of project activities is very useful for optimizing the schedules of activities using Critical Path Method and managing the scheduling control of NPP project. This study has shown new approach to optimal scheduling of NPP project, however, this does not consider the characteristic of activities according to the NPP site conditions. Hence, this study needs more research considering those factors
Energy Technology Data Exchange (ETDEWEB)
Lee, Kwang Ho; Roh, Myung Sub [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)
2013-10-15
There are so many different factors to consider when constructing a nuclear power plant successfully from planning to decommissioning. According to PMBOK, all projects have nine domains from a holistic project management perspective. They are equally important to all projects, however, this study focuses mostly on the processes required to manage timely completion of the project and conduct risk management. The overall objective of this study is to let you know what the risk analysis derived from scheduling of NPP project is, and understand how to implement the stochastic process modeling through risk management. Building the Nuclear Power Plant is required a great deal of time and fundamental knowledge related to all engineering. That means that integrated project scheduling management with so many activities is necessary and very important. Simulation techniques for scheduling of NPP project using Open Plan program, Crystal Ball program, and Minitab program can be useful tools for designing optimal schedule planning. Thus far, Open Plan and Monte Carlo programs have been used to calculate the critical path for scheduling network analysis. And also, Minitab program has been applied to monitor the scheduling risk. This approach to stochastic modeling through risk analysis of project activities is very useful for optimizing the schedules of activities using Critical Path Method and managing the scheduling control of NPP project. This study has shown new approach to optimal scheduling of NPP project, however, this does not consider the characteristic of activities according to the NPP site conditions. Hence, this study needs more research considering those factors.
Nonparametric Inference of Doubly Stochastic Poisson Process Data via the Kernel Method.
Zhang, Tingting; Kou, S C
2010-01-01
Doubly stochastic Poisson processes, also known as the Cox processes, frequently occur in various scientific fields. In this article, motivated primarily by analyzing Cox process data in biophysics, we propose a nonparametric kernel-based inference method. We conduct a detailed study, including an asymptotic analysis, of the proposed method, and provide guidelines for its practical use, introducing a fast and stable regression method for bandwidth selection. We apply our method to real photon arrival data from recent single-molecule biophysical experiments, investigating proteins' conformational dynamics. Our result shows that conformational fluctuation is widely present in protein systems, and that the fluctuation covers a broad range of time scales, highlighting the dynamic and complex nature of proteins' structure.
Producing a functional eukaryotic messenger RNA (mRNA) requires the coordinated activity of several large protein complexes to initiate transcription, elongate nascent transcripts, splice together exons, and cleave and polyadenylate the 3’ end. Kinetic competition between these various processes has been proposed to regulate mRNA maturation, but this model could lead to multiple, randomly determined, or stochastic, pathways or outcomes. Regulatory checkpoints have been suggested as a means of ensuring quality control. However, current methods have been unable to tease apart the contributions of these processes at a single gene or on a time scale that could provide mechanistic insight. To begin to investigate the kinetic relationship between transcription and splicing, Daniel Larson, Ph.D., of CCR’s Laboratory of Receptor Biology and Gene Expression, and his colleagues employed a single-molecule RNA imaging approach to monitor production and processing of a human β-globin reporter gene in living cells.
Monitoring and pollution control: A stochastic process approach to model oil spills
International Nuclear Information System (INIS)
Viladrich-Grau, M.
1991-01-01
The first chapter analyzes the behavior of a firm in an environment with pollution externalities and technological progress. It is assumed that firms may not purposely violate the pollution control regulations but nonetheless, generate some pollution due to negligence. The model allows firms two possible actions: either increase the level of treated waste or pay an expected penalty if illegal pollution is detected. The results of the first chapter show that in a world with pollution externalities, technological progress does not guarantee increases in the welfare level. The second chapter models the occurrence of an oil spill as a stochastic event. The stochastic model developed allows one to see how each step of the spilling process is affected by each policy measure and to compare the relative efficiency of different measures in reducing spills. The third chapter estimates the parameters that govern oil spill frequency and size distribution. The author models how these parameters depend on two pollution prevention measures: monitoring of transfer operations and assessment of penalties. He shows that these measures reduce the frequency of oil spills
Sulis, William H
2017-10-01
Walter Freeman III pioneered the application of nonlinear dynamical systems theories and methodologies in his work on mesoscopic brain dynamics.Sadly, mainstream psychology and psychiatry still cling to linear correlation based data analysis techniques, which threaten to subvert the process of experimentation and theory building. In order to progress, it is necessary to develop tools capable of managing the stochastic complexity of complex biopsychosocial systems, which includes multilevel feedback relationships, nonlinear interactions, chaotic dynamics and adaptability. In addition, however, these systems exhibit intrinsic randomness, non-Gaussian probability distributions, non-stationarity, contextuality, and non-Kolmogorov probabilities, as well as the absence of mean and/or variance and conditional probabilities. These properties and their implications for statistical analysis are discussed. An alternative approach, the Process Algebra approach, is described. It is a generative model, capable of generating non-Kolmogorov probabilities. It has proven useful in addressing fundamental problems in quantum mechanics and in the modeling of developing psychosocial systems.
DEFF Research Database (Denmark)
Schiøler, Henrik; Leth, John-Josef
2011-01-01
Results are given in [Yang et. al. 2009] regarding the overall stability of switched diffusion processes based on stability properties of separate processes combined through stochastic switching. This paper argues two main results to be empty, in that the presented hypotheses are logically...
1987-08-21
examples of so-called self-similar processes. 522 -°- °.. 0 * - -= uu~.~w- - v , LOCAL BEHAVIOUR OF SIMPLE STOCHASTIC MODELS by Rudolf Grfibel...theorem en- tails results on the growth of matchings, Steiner trees, traveling-salesman processes as well as triangulations in large areas. These
Frontal and superior temporal auditory processing abnormalities in schizophrenia.
Chen, Yu-Han; Edgar, J Christopher; Huang, Mingxiong; Hunter, Michael A; Epstein, Emerson; Howell, Breannan; Lu, Brett Y; Bustillo, Juan; Miller, Gregory A; Cañive, José M
2013-01-01
Although magnetoencephalography (MEG) studies show superior temporal gyrus (STG) auditory processing abnormalities in schizophrenia at 50 and 100 ms, EEG and corticography studies suggest involvement of additional brain areas (e.g., frontal areas) during this interval. Study goals were to identify 30 to 130 ms auditory encoding processes in schizophrenia (SZ) and healthy controls (HC) and group differences throughout the cortex. The standard paired-click task was administered to 19 SZ and 21 HC subjects during MEG recording. Vector-based Spatial-temporal Analysis using L1-minimum-norm (VESTAL) provided 4D maps of activity from 30 to 130 ms. Within-group t-tests compared post-stimulus 50 ms and 100 ms activity to baseline. Between-group t-tests examined 50 and 100 ms group differences. Bilateral 50 and 100 ms STG activity was observed in both groups. HC had stronger bilateral 50 and 100 ms STG activity than SZ. In addition to the STG group difference, non-STG activity was also observed in both groups. For example, whereas HC had stronger left and right inferior frontal gyrus activity than SZ, SZ had stronger right superior frontal gyrus and left supramarginal gyrus activity than HC. Less STG activity was observed in SZ than HC, indicating encoding problems in SZ. Yet auditory encoding abnormalities are not specific to STG, as group differences were observed in frontal and SMG areas. Thus, present findings indicate that individuals with SZ show abnormalities in multiple nodes of a concurrently activated auditory network.
International Nuclear Information System (INIS)
2005-01-01
Some specific stochastic, jumping processes have been studied. They are defined in terms of the jump size distribution and the waiting time distribution which are mutually dependent. For the simplest case (the kangaroo process), the corresponding master equation has been completely solved and simple asymptotic expressions for the time-dependent probability distributions have been derived. A generalized version of that process, which takes into account the memory effects, has been proposed and a connection to transport processes, namely to the Boltzmann kinetic theory and diffusion, has been demonstrated. The same process, but defined on the circle instead of the axis, can possess the power law autocorrelation function; a simple formula for this function has been derived. Therefore, the process can serve as a useful model for the colored noises, in particular for the 1/f noise. It has been applied as a model of the driving force in the generalized Langevin equation, an impossible task with the standard kangaroo process. The equation has been solved by means of the Monte Carlo simulations. The resulting velocity and energy distributions exhibit extremely long memory about the initial conditions, despite an apparent fast equilibration of their comprehensive shape. The tails of both distributions fall faster than in the Maxwellian case
Chang, Mou-Hsiung
2015-01-01
The classical probability theory initiated by Kolmogorov and its quantum counterpart, pioneered by von Neumann, were created at about the same time in the 1930s, but development of the quantum theory has trailed far behind. Although highly appealing, the quantum theory has a steep learning curve, requiring tools from both probability and analysis and a facility for combining the two viewpoints. This book is a systematic, self-contained account of the core of quantum probability and quantum stochastic processes for graduate students and researchers. The only assumed background is knowledge of the basic theory of Hilbert spaces, bounded linear operators, and classical Markov processes. From there, the book introduces additional tools from analysis, and then builds the quantum probability framework needed to support applications to quantum control and quantum information and communication. These include quantum noise, quantum stochastic calculus, stochastic quantum differential equations, quantum Markov semigrou...
Fayolle, G; Fayolle, Guy; Furtlehner, Cyril
2006-01-01
This report is the foreword of a series of stochastic deformations of curves. Problems are set in terms of exclusion processes, the ultimate goal being to derive hydrodynamic limits for these systems after proper scalings. In this study, solely the basic texts system on the torus is analyzed. The usual sequence of empirical measures, converges in probability to a deterministic measure, which is the unique weak solution of a Cauchy problem. The method presents some new features, letting hope for extensions to higher dimension. It relies on the analysis of a family of parabolic differential operators, involving variational calculus. Namely, the variables are the values of functions at given points, their number being possibly infinite.
Stochastic dynamical model of a growing citation network based on a self-exciting point process.
Golosovsky, Michael; Solomon, Sorin
2012-08-31
We put under experimental scrutiny the preferential attachment model that is commonly accepted as a generating mechanism of the scale-free complex networks. To this end we chose a citation network of physics papers and traced the citation history of 40,195 papers published in one year. Contrary to common belief, we find that the citation dynamics of the individual papers follows the superlinear preferential attachment, with the exponent α=1.25-1.3. Moreover, we show that the citation process cannot be described as a memoryless Markov chain since there is a substantial correlation between the present and recent citation rates of a paper. Based on our findings we construct a stochastic growth model of the citation network, perform numerical simulations based on this model and achieve an excellent agreement with the measured citation distributions.
Tucker, C. J.; Garratt, M. W.
1977-01-01
A stochastic leaf radiation model based upon physical and physiological properties of dicot leaves has been developed. The model accurately predicts the absorbed, reflected, and transmitted radiation of normal incidence as a function of wavelength resulting from the leaf-irradiance interaction over the spectral interval of 0.40-2.50 micron. The leaf optical system has been represented as Markov process with a unique transition matrix at each 0.01-micron increment between 0.40 micron and 2.50 micron. Probabilities are calculated at every wavelength interval from leaf thickness, structure, pigment composition, and water content. Simulation results indicate that this approach gives accurate estimations of actual measured values for dicot leaf absorption, reflection, and transmission as a function of wavelength.
Stochastic Interest Model Based on Compound Poisson Process and Applications in Actuarial Science
Directory of Open Access Journals (Sweden)
Shilong Li
2017-01-01
Full Text Available Considering stochastic behavior of interest rates in financial market, we construct a new class of interest models based on compound Poisson process. Different from the references, this paper describes the randomness of interest rates by modeling the force of interest with Poisson random jumps directly. To solve the problem in calculation of accumulated interest force function, one important integral technique is employed. And a conception called the critical value is introduced to investigate the validity condition of this new model. We also discuss actuarial present values of several life annuities under this new interest model. Simulations are done to illustrate the theoretical results and the effect of parameters in interest model on actuarial present values is also analyzed.
Stochastic modeling of stock price process induced from the conjugate heat equation
Paeng, Seong-Hun
2015-02-01
Currency can be considered as a ruler for values of commodities. Then the price is the measured value by the ruler. We can suppose that inflation and variation of exchange rate are caused by variation of the scale of the ruler. In geometry, variation of the scale means that the metric is time-dependent. The conjugate heat equation is the modified heat equation which satisfies the heat conservation law for the time-dependent metric space. We propose a new model of stock prices by using the stochastic process whose transition probability is determined by the kernel of the conjugate heat equation. Our model of stock prices shows how the volatility term is affected by inflation and exchange rate. This model modifies the Black-Scholes equation in light of inflation and exchange rate.
Energy Technology Data Exchange (ETDEWEB)
Araujo, Leonardo Rodrigues de [Instituto Federal do Espirito Santo, Vitoria, ES (Brazil)], E-mail: leoaraujo@ifes.edu.br; Donatelli, Joao Luiz Marcon [Universidade Federal do Espirito Santo (UFES), Vitoria, ES (Brazil)], E-mail: joaoluiz@npd.ufes.br; Silva, Edmar Alino da Cruz [Instituto Tecnologico de Aeronautica (ITA/CTA), Sao Jose dos Campos, SP (Brazil); Azevedo, Joao Luiz F. [Instituto de Aeronautica e Espaco (CTA/IAE/ALA), Sao Jose dos Campos, SP (Brazil)
2010-07-01
Thermal systems are essential in facilities such as thermoelectric plants, cogeneration plants, refrigeration systems and air conditioning, among others, in which much of the energy consumed by humanity is processed. In a world with finite natural sources of fuels and growing energy demand, issues related with thermal system design, such as cost estimative, design complexity, environmental protection and optimization are becoming increasingly important. Therefore the need to understand the mechanisms that degrade energy, improve energy sources use, reduce environmental impacts and also reduce project, operation and maintenance costs. In recent years, a consistent development of procedures and techniques for computational design of thermal systems has occurred. In this context, the fundamental objective of this study is a performance comparative analysis of structural and parametric optimization of a cogeneration system using stochastic methods: genetic algorithm and simulated annealing. This research work uses a superstructure, modelled in a process simulator, IPSEpro of SimTech, in which the appropriate design case studied options are included. Accordingly, the cogeneration system optimal configuration is determined as a consequence of the optimization process, restricted within the configuration options included in the superstructure. The optimization routines are written in MsExcel Visual Basic, in order to work perfectly coupled to the simulator process. At the end of the optimization process, the system optimal configuration, given the characteristics of each specific problem, should be defined. (author)
Humor drawings evoked temporal and spectral EEG processes
Kuo, Hsien-Chu; Chuang, Shang-Wen
2017-01-01
Abstract The study aimed to explore the humor processing elicited through the manipulation of artistic drawings. Using the Comprehension–Elaboration Theory of humor as the main research background, the experiment manipulated the head portraits of celebrities based on the independent variables of facial deformation (large/small) and addition of affective features (positive/negative). A 64-channel electroencephalography was recorded in 30 participants while viewing the incongruous drawings of celebrities. The electroencephalography temporal and spectral responses were measured during the three stages of humor which included incongruity detection, incongruity comprehension and elaboration of humor. Analysis of event-related potentials indicated that for humorous vs non-humorous drawings, facial deformation and the addition of affective features significantly affected the degree of humor elicited, specifically: large > small deformation; negative > positive affective features. The N170, N270, N400, N600-800 and N900-1200 components showed significant differences, particularly in the right prefrontal and frontal regions. Analysis of event-related spectral perturbation showed significant differences in the theta band evoked in the anterior cingulate cortex, parietal region and posterior cingulate cortex; and in the alpha and beta bands in the motor areas. These regions are involved in emotional processing, memory retrieval, and laughter and feelings of amusement induced by elaboration of the situation. PMID:28402573
Humor drawings evoked temporal and spectral EEG processes.
Wang, Regina W Y; Kuo, Hsien-Chu; Chuang, Shang-Wen
2017-08-01
The study aimed to explore the humor processing elicited through the manipulation of artistic drawings. Using the Comprehension-Elaboration Theory of humor as the main research background, the experiment manipulated the head portraits of celebrities based on the independent variables of facial deformation (large/small) and addition of affective features (positive/negative). A 64-channel electroencephalography was recorded in 30 participants while viewing the incongruous drawings of celebrities. The electroencephalography temporal and spectral responses were measured during the three stages of humor which included incongruity detection, incongruity comprehension and elaboration of humor. Analysis of event-related potentials indicated that for humorous vs non-humorous drawings, facial deformation and the addition of affective features significantly affected the degree of humor elicited, specifically: large > small deformation; negative > positive affective features. The N170, N270, N400, N600-800 and N900-1200 components showed significant differences, particularly in the right prefrontal and frontal regions. Analysis of event-related spectral perturbation showed significant differences in the theta band evoked in the anterior cingulate cortex, parietal region and posterior cingulate cortex; and in the alpha and beta bands in the motor areas. These regions are involved in emotional processing, memory retrieval, and laughter and feelings of amusement induced by elaboration of the situation. © The Author (2017). Published by Oxford University Press.
Moll, Kristina; Göbel, Silke M; Gooch, Debbie; Landerl, Karin; Snowling, Margaret J
2016-01-01
High comorbidity rates between reading disorder (RD) and mathematics disorder (MD) indicate that, although the cognitive core deficits underlying these disorders are distinct, additional domain-general risk factors might be shared between the disorders. Three domain-general cognitive abilities were investigated in children with RD and MD: processing speed, temporal processing, and working memory. Since attention problems frequently co-occur with learning disorders, the study examined whether these three factors, which are known to be associated with attention problems, account for the comorbidity between these disorders. The sample comprised 99 primary school children in four groups: children with RD, children with MD, children with both disorders (RD+MD), and typically developing children (TD controls). Measures of processing speed, temporal processing, and memory were analyzed in a series of ANCOVAs including attention ratings as covariate. All three risk factors were associated with poor attention. After controlling for attention, associations with RD and MD differed: Although deficits in verbal memory were associated with both RD and MD, reduced processing speed was related to RD, but not MD; and the association with RD was restricted to processing speed for familiar nameable symbols. In contrast, impairments in temporal processing and visuospatial memory were associated with MD, but not RD. © Hammill Institute on Disabilities 2014.
Energy Technology Data Exchange (ETDEWEB)
Van Kessel, L.B.M.
2003-06-11
with the on-line calorific value sensor from chapter 2 and a validated dynamic model of the process is available, the theory from stochastic processes can be applied to MSWC. This new application field of stochastics is discussed in chapter 4. The results obtained in chapter 2 will be used in this analysis. Also new linear transfer functions for thermal processes will be given and applied to MSWC. Finally, applications of the new developed tools will be discussed. As already mentioned, the validation experiments lead to the conclusion that the dynamics of the combustion process can change when the primary air temperature changes. This was a new result, which has never been reported in literature before. For that reason during the research it was decided to start an extensive study into the influence of the primary air temperature on the combustion process. This has been performed by using laboratory experiments. In chapter 5 the results from this search will be presented. The existing theory for combustion of solid fuels is extended with a qualitative as well as a quantitative description of the influence of primary preheating. The new theory is used to explain observations from real plants and the results from system identification. Furthermore, the value of laboratory experiments to simulate the real combustion process on a grate is discussed.
Lopopolo, Alessandro; Frank, Stefan L; van den Bosch, Antal; Willems, Roel M
2017-01-01
Language comprehension involves the simultaneous processing of information at the phonological, syntactic, and lexical level. We track these three distinct streams of information in the brain by using stochastic measures derived from computational language models to detect neural correlates of phoneme, part-of-speech, and word processing in an fMRI experiment. Probabilistic language models have proven to be useful tools for studying how language is processed as a sequence of symbols unfolding in time. Conditional probabilities between sequences of words are at the basis of probabilistic measures such as surprisal and perplexity which have been successfully used as predictors of several behavioural and neural correlates of sentence processing. Here we computed perplexity from sequences of words and their parts of speech, and their phonemic transcriptions. Brain activity time-locked to each word is regressed on the three model-derived measures. We observe that the brain keeps track of the statistical structure of lexical, syntactic and phonological information in distinct areas.
Modeling Aggregation Processes of Lennard-Jones particles Via Stochastic Networks
Forman, Yakir; Cameron, Maria
2017-07-01
We model an isothermal aggregation process of particles/atoms interacting according to the Lennard-Jones pair potential by mapping the energy landscapes of each cluster size N onto stochastic networks, computing transition probabilities from the network for an N-particle cluster to the one for N+1, and connecting these networks into a single joint network. The attachment rate is a control parameter. The resulting network representing the aggregation of up to 14 particles contains 6427 vertices. It is not only time-irreversible but also reducible. To analyze its transient dynamics, we introduce the sequence of the expected initial and pre-attachment distributions and compute them for a wide range of attachment rates and three values of temperature. As a result, we find the configurations most likely to be observed in the process of aggregation for each cluster size. We examine the attachment process and conduct a structural analysis of the sets of local energy minima for every cluster size. We show that both processes taking place in the network, attachment and relaxation, lead to the dominance of icosahedral packing in small (up to 14 atom) clusters.
Sedwards, Sean; Mazza, Tommaso
2007-10-15
Compartments and membranes are the basis of cell topology and more than 30% of the human genome codes for membrane proteins. While it is possible to represent compartments and membrane proteins in a nominal way with many mathematical formalisms used in systems biology, few, if any, explicitly model the topology of the membranes themselves. Discrete stochastic simulation potentially offers the most accurate representation of cell dynamics. Since the details of every molecular interaction in a pathway are often not known, the relationship between chemical species in not necessarily best described at the lowest level, i.e. by mass action. Simulation is a form of computer-aided analysis, relying on human interpretation to derive meaning. To improve efficiency and gain meaning in an automatic way, it is necessary to have a formalism based on a model which has decidable properties. We present Cyto-Sim, a stochastic simulator of membrane-enclosed hierarchies of biochemical processes, where the membranes comprise an inner, outer and integral layer. The underlying model is based on formal language theory and has been shown to have decidable properties (Cavaliere and Sedwards, 2006), allowing formal analysis in addition to simulation. The simulator provides variable levels of abstraction via arbitrary chemical kinetics which link to ordinary differential equations. In addition to its compact native syntax, Cyto-Sim currently supports models described as Petri nets, can import all versions of SBML and can export SBML and MATLAB m-files. Cyto-Sim is available free, either as an applet or a stand-alone Java program via the web page (http://www.cosbi.eu/Rpty_Soft_CytoSim.php). Other versions can be made available upon request.
Modelling and performance analysis of clinical pathways using the stochastic process algebra PEPA.
Yang, Xian; Han, Rui; Guo, Yike; Bradley, Jeremy; Cox, Benita; Dickinson, Robert; Kitney, Richard
2012-01-01
Hospitals nowadays have to serve numerous patients with limited medical staff and equipment while maintaining healthcare quality. Clinical pathway informatics is regarded as an efficient way to solve a series of hospital challenges. To date, conventional research lacks a mathematical model to describe clinical pathways. Existing vague descriptions cannot fully capture the complexities accurately in clinical pathways and hinders the effective management and further optimization of clinical pathways. Given this motivation, this paper presents a clinical pathway management platform, the Imperial Clinical Pathway Analyzer (ICPA). By extending the stochastic model performance evaluation process algebra (PEPA), ICPA introduces a clinical-pathway-specific model: clinical pathway PEPA (CPP). ICPA can simulate stochastic behaviours of a clinical pathway by extracting information from public clinical databases and other related documents using CPP. Thus, the performance of this clinical pathway, including its throughput, resource utilisation and passage time can be quantitatively analysed. A typical clinical pathway on stroke extracted from a UK hospital is used to illustrate the effectiveness of ICPA. Three application scenarios are tested using ICPA: 1) redundant resources are identified and removed, thus the number of patients being served is maintained with less cost; 2) the patient passage time is estimated, providing the likelihood that patients can leave hospital within a specific period; 3) the maximum number of input patients are found, helping hospitals to decide whether they can serve more patients with the existing resource allocation. ICPA is an effective platform for clinical pathway management: 1) ICPA can describe a variety of components (state, activity, resource and constraints) in a clinical pathway, thus facilitating the proper understanding of complexities involved in it; 2) ICPA supports the performance analysis of clinical pathway, thereby assisting
StochPy: A Comprehensive, User-Friendly Tool for Simulating Stochastic Biological Processes
T.R. Maarleveld (Timo); B.G. Olivier (Brett); F.J. Bruggeman (Frank)
2013-01-01
htmlabstractSingle-cell and single-molecule measurements indicate the importance of stochastic phenomena in cell biology. Stochasticity creates spontaneous differences in the copy numbers of key macromolecules and the timing of reaction events between genetically-identical cells. Mathematical models
Detection, information fusion, and temporal processing for intelligence in recognition
Energy Technology Data Exchange (ETDEWEB)
Casasent, D. [Carnegie Mellon Univ., Pittsburgh, PA (United States)
1996-12-31
The use of intelligence in vision recognition uses many different techniques or tools. This presentation discusses several of these techniques for recognition. The recognition process is generally separated into several steps or stages when implemented in hardware, e.g. detection, segmentation and enhancement, and recognition. Several new distortion-invariant filters, biologically-inspired Gabor wavelet filter techniques, and morphological operations that have been found very useful for detection and clutter rejection are discussed. These are all shift-invariant operations that allow multiple object regions of interest in a scene to be located in parallel. We also discuss new algorithm fusion concepts by which the results from different detection algorithms are combined to reduce detection false alarms; these fusion methods utilize hierarchical processing and fuzzy logic concepts. We have found this to be most necessary, since no single detection algorithm is best for all cases. For the final recognition stage, we describe a new method of representing all distorted versions of different classes of objects and determining the object class and pose that most closely matches that of a given input. Besides being efficient in terms of storage and on-line computations required, it overcomes many of the problems that other classifiers have in terms of the required training set size, poor generalization with many hidden layer neurons, etc. It is also attractive in its ability to reject input regions as clutter (non-objects) and to learn new object descriptions. We also discuss its use in processing a temporal sequence of input images of the contents of each local region of interest. We note how this leads to robust results in which estimation efforts in individual frames can be overcome. This seems very practical, since in many scenarios a decision need not be made after only one frame of data, since subsequent frames of data enter immediately in sequence.
Yu, Qian; Fang, Debin; Zhang, Xiaoling; Jin, Chen; Ren, Qiyu
2016-06-27
Stochasticity plays an important role in the evolutionary dynamic of cyclic dominance within a finite population. To investigate the stochastic evolution process of the behaviour of bounded rational individuals, we model the Rock-Scissors-Paper (RSP) game as a finite, state dependent Quasi Birth and Death (QBD) process. We assume that bounded rational players can adjust their strategies by imitating the successful strategy according to the payoffs of the last round of the game, and then analyse the limiting distribution of the QBD process for the game stochastic evolutionary dynamic. The numerical experiments results are exhibited as pseudo colour ternary heat maps. Comparisons of these diagrams shows that the convergence property of long run equilibrium of the RSP game in populations depends on population size and the parameter of the payoff matrix and noise factor. The long run equilibrium is asymptotically stable, neutrally stable and unstable respectively according to the normalised parameters in the payoff matrix. Moreover, the results show that the distribution probability becomes more concentrated with a larger population size. This indicates that increasing the population size also increases the convergence speed of the stochastic evolution process while simultaneously reducing the influence of the noise factor.
1987-08-01
ESTIMATION FOR STOCHASTIC PROCESSES by C. C. Heyde Australian National University Canberra, Australia ABSTRACT Optimality is a widely and loosely used...Case 240 S. Australia 1211 Geneva 24 Switzerland Christopher C. Heyde Dept. of Statistics, IAS Patricia Jacobs . Australian National University...Universitat Regensburg USA Postfach D-8400 Regensburg Anatole Joffe W. Germany Dept. of Mathematics & Statatistics Frank Kelly Universite de Montreal
Directory of Open Access Journals (Sweden)
Emil Bayramov
2016-05-01
Full Text Available The main goal of this research was to detect oil spills, to determine the oil spill frequencies and to approximate oil leak sources around the Oil Rocks Settlement, the Chilov and Pirallahi Islands in the Caspian Sea using 136 multi-temporal ENVISAT Advanced Synthetic Aperture Radar Wide Swath Medium Resolution images acquired during 2006–2010. The following oil spill frequencies were observed around the Oil Rocks Settlement, the Chilov and Pirallahi Islands: 2–10 (3471.04 sq km, 11–20 (971.66 sq km, 21–50 (692.44 sq km, 51–128 (191.38 sq km. The most critical oil leak sources with the frequency range of 41–128 were observed at the Oil Rocks Settlement. The exponential regression analysis between wind speeds and oil slick areas detected from 136 multi-temporal ENVISAT images revealed the regression coefficient equal to 63%. The regression model showed that larger oil spill areas were observed with decreasing wind speeds. The spatiotemporal patterns of currents in the Caspian Sea explained the multi-directional spatial distribution of oil spills around Oil Rocks Settlement, the Chilov and Pirallahi Islands. The linear regression analysis between detected oil spill frequencies and predicted oil contamination probability by the stochastic model showed the positive trend with the regression coefficient of 30%.
A customizable stochastic state point process filter (SSPPF) for neural spiking activity.
Xin, Yao; Li, Will X Y; Min, Biao; Han, Yan; Cheung, Ray C C
2013-01-01
Stochastic State Point Process Filter (SSPPF) is effective for adaptive signal processing. In particular, it has been successfully applied to neural signal coding/decoding in recent years. Recent work has proven its efficiency in non-parametric coefficients tracking in modeling of mammal nervous system. However, existing SSPPF has only been realized in commercial software platforms which limit their computational capability. In this paper, the first hardware architecture of SSPPF has been designed and successfully implemented on field-programmable gate array (FPGA), proving a more efficient means for coefficient tracking in a well-established generalized Laguerre-Volterra model for mammalian hippocampal spiking activity research. By exploring the intrinsic parallelism of the FPGA, the proposed architecture is able to process matrices or vectors with random size, and is efficiently scalable. Experimental result shows its superior performance comparing to the software implementation, while maintaining the numerical precision. This architecture can also be potentially utilized in the future hippocampal cognitive neural prosthesis design.
Deterministic flows of order-parameters in stochastic processes of quantum Monte Carlo method
International Nuclear Information System (INIS)
Inoue, Jun-ichi
2010-01-01
In terms of the stochastic process of quantum-mechanical version of Markov chain Monte Carlo method (the MCMC), we analytically derive macroscopically deterministic flow equations of order parameters such as spontaneous magnetization in infinite-range (d(= ∞)-dimensional) quantum spin systems. By means of the Trotter decomposition, we consider the transition probability of Glauber-type dynamics of microscopic states for the corresponding (d + 1)-dimensional classical system. Under the static approximation, differential equations with respect to macroscopic order parameters are explicitly obtained from the master equation that describes the microscopic-law. In the steady state, we show that the equations are identical to the saddle point equations for the equilibrium state of the same system. The equation for the dynamical Ising model is recovered in the classical limit. We also check the validity of the static approximation by making use of computer simulations for finite size systems and discuss several possible extensions of our approach to disordered spin systems for statistical-mechanical informatics. Especially, we shall use our procedure to evaluate the decoding process of Bayesian image restoration. With the assistance of the concept of dynamical replica theory (the DRT), we derive the zero-temperature flow equation of image restoration measure showing some 'non-monotonic' behaviour in its time evolution.
Stochastic production phase design for an open pit mining complex with multiple processing streams
Asad, Mohammad Waqar Ali; Dimitrakopoulos, Roussos; van Eldert, Jeroen
2014-08-01
In a mining complex, the mine is a source of supply of valuable material (ore) to a number of processes that convert the raw ore to a saleable product or a metal concentrate for production of the refined metal. In this context, expected variation in metal content throughout the extent of the orebody defines the inherent uncertainty in the supply of ore, which impacts the subsequent ore and metal production targets. Traditional optimization methods for designing production phases and ultimate pit limit of an open pit mine not only ignore the uncertainty in metal content, but, in addition, commonly assume that the mine delivers ore to a single processing facility. A stochastic network flow approach is proposed that jointly integrates uncertainty in supply of ore and multiple ore destinations into the development of production phase design and ultimate pit limit. An application at a copper mine demonstrates the intricacies of the new approach. The case study shows a 14% higher discounted cash flow when compared to the traditional approach.
Directory of Open Access Journals (Sweden)
Scott Ferrenberg
2016-10-01
Full Text Available Background Understanding patterns of biodiversity is a longstanding challenge in ecology. Similar to other biotic groups, arthropod community structure can be shaped by deterministic and stochastic processes, with limited understanding of what moderates the relative influence of these processes. Disturbances have been noted to alter the relative influence of deterministic and stochastic processes on community assembly in various study systems, implicating ecological disturbances as a potential moderator of these forces. Methods Using a disturbance gradient along a 5-year chronosequence of insect-induced tree mortality in a subalpine forest of the southern Rocky Mountains, Colorado, USA, we examined changes in community structure and relative influences of deterministic and stochastic processes in the assembly of aboveground (surface and litter-active species and belowground (species active in organic and mineral soil layers arthropod communities. Arthropods were sampled for all years of the chronosequence via pitfall traps (aboveground community and modified Winkler funnels (belowground community and sorted to morphospecies. Community structure of both communities were assessed via comparisons of morphospecies abundance, diversity, and composition. Assembly processes were inferred from a mixture of linear models and matrix correlations testing for community associations with environmental properties, and from null-deviation models comparing observed vs. expected levels of species turnover (Beta diversity among samples. Results Tree mortality altered community structure in both aboveground and belowground arthropod communities, but null models suggested that aboveground communities experienced greater relative influences of deterministic processes, while the relative influence of stochastic processes increased for belowground communities. Additionally, Mantel tests and linear regression models revealed significant associations between the
Martinez, Alexander S.; Faist, Akasha M.
2016-01-01
Background Understanding patterns of biodiversity is a longstanding challenge in ecology. Similar to other biotic groups, arthropod community structure can be shaped by deterministic and stochastic processes, with limited understanding of what moderates the relative influence of these processes. Disturbances have been noted to alter the relative influence of deterministic and stochastic processes on community assembly in various study systems, implicating ecological disturbances as a potential moderator of these forces. Methods Using a disturbance gradient along a 5-year chronosequence of insect-induced tree mortality in a subalpine forest of the southern Rocky Mountains, Colorado, USA, we examined changes in community structure and relative influences of deterministic and stochastic processes in the assembly of aboveground (surface and litter-active species) and belowground (species active in organic and mineral soil layers) arthropod communities. Arthropods were sampled for all years of the chronosequence via pitfall traps (aboveground community) and modified Winkler funnels (belowground community) and sorted to morphospecies. Community structure of both communities were assessed via comparisons of morphospecies abundance, diversity, and composition. Assembly processes were inferred from a mixture of linear models and matrix correlations testing for community associations with environmental properties, and from null-deviation models comparing observed vs. expected levels of species turnover (Beta diversity) among samples. Results Tree mortality altered community structure in both aboveground and belowground arthropod communities, but null models suggested that aboveground communities experienced greater relative influences of deterministic processes, while the relative influence of stochastic processes increased for belowground communities. Additionally, Mantel tests and linear regression models revealed significant associations between the aboveground arthropod
D'Onofrio, Giuseppe; Pirozzi, Enrica
2017-05-01
We consider a stochastic differential equation in a strip, with coefficients suitably chosen to describe the acto-myosin interaction subject to time-varying forces. By simulating trajectories of the stochastic dynamics via an Euler discretization-based algorithm, we fit experimental data and determine the values of involved parameters. The steps of the myosin are represented by the exit events from the strip. Motivated by these results, we propose a specific stochastic model based on the corresponding time-inhomogeneous Gauss-Markov and diffusion process evolving between two absorbing boundaries. We specify the mean and covariance functions of the stochastic modeling process taking into account time-dependent forces including the effect of an external load. We accurately determine the probability density function (pdf) of the first exit time (FET) from the strip by solving a system of two non singular second-type Volterra integral equations via a numerical quadrature. We provide numerical estimations of the mean of FET as approximations of the dwell-time of the proteins dynamics. The percentage of backward steps is given in agreement to experimental data. Numerical and simulation results are compared and discussed.
Tanaka, Shigenori
2016-03-07
A computational scheme to describe the temporal evolution of thermodynamic functions in stochastic nonequilibrium processes of isothermal classical systems is proposed on the basis of overdamped Langevin equation under given potential and temperature. In this scheme the associated Fokker-Planck-Smoluchowski equation for the probability density function is transformed into the imaginary-time Schrödinger equation with an effective Hamiltonian. The propagator for the time-dependent wave function is expressed in the framework of the path integral formalism, which can thus represent the dynamical behaviors of nonequilibrium molecular systems such as those conformational changes observed in protein folding and ligand docking. The present study then employs the diffusion Monte Carlo method to efficiently simulate the relaxation dynamics of wave function in terms of random walker distribution, which in the long-time limit reduces to the ground-state eigenfunction corresponding to the equilibrium Boltzmann distribution. Utilizing this classical-quantum correspondence, we can describe the relaxation processes of thermodynamic functions as an approach to the equilibrium state with the lowest free energy. Performing illustrative calculations for some prototypical model potentials, the temporal evolutions of enthalpy, entropy, and free energy of the classical systems are explicitly demonstrated. When the walkers initially start from a localized configuration in one- or two-dimensional harmonic or double well potential, the increase of entropy usually dominates the relaxation dynamics toward the equilibrium state. However, when they start from a broadened initial distribution or go into a steep valley of potential, the dynamics are driven by the decrease of enthalpy, thus causing the decrease of entropy associated with the spatial localization. In the cases of one- and two-dimensional asymmetric double well potentials with two minimal points and an energy barrier between them
Phenomenological and ratio bifurcations of a class of discrete time stochastic processes
Diks, C.G.H.; Wagener, F.O.O.
2011-01-01
Zeeman proposed a classification of stochastic dynamical systems based on the Morse classification of their invariant probability densities; the associated bifurcations are the ‘phenomenological bifurcations’ of L. Arnold. The classification is however not invariant under diffeomorphisms of the
Spatio-temporal statistical models with applications to atmospheric processes
International Nuclear Information System (INIS)
Wikle, C.K.
1996-01-01
This doctoral dissertation is presented as three self-contained papers. An introductory chapter considers traditional spatio-temporal statistical methods used in the atmospheric sciences from a statistical perspective. Although this section is primarily a review, many of the statistical issues considered have not been considered in the context of these methods and several open questions are posed. The first paper attempts to determine a means of characterizing the semiannual oscillation (SAO) spatial variation in the northern hemisphere extratropical height field. It was discovered that the midlatitude SAO in 500hPa geopotential height could be explained almost entirely as a result of spatial and temporal asymmetries in the annual variation of stationary eddies. It was concluded that the mechanism for the SAO in the northern hemisphere is a result of land-sea contrasts. The second paper examines the seasonal variability of mixed Rossby-gravity waves (MRGW) in lower stratospheric over the equatorial Pacific. Advanced cyclostationary time series techniques were used for analysis. It was found that there are significant twice-yearly peaks in MRGW activity. Analyses also suggested a convergence of horizontal momentum flux associated with these waves. In the third paper, a new spatio-temporal statistical model is proposed that attempts to consider the influence of both temporal and spatial variability. This method is mainly concerned with prediction in space and time, and provides a spatially descriptive and temporally dynamic model
Directory of Open Access Journals (Sweden)
Guoxi Shi
Full Text Available Both deterministic and stochastic processes are expected to drive the assemblages of arbuscular mycorrhizal (AM fungi, but little is known about the relative importance of these processes during the spreading of toxic plants. Here, the species composition and phylogenetic structure of AM fungal communities colonizing the roots of a toxic plant, Ligularia virgaurea, and its neighborhood plants, were analyzed in patches with different individual densities of L. virgaurea (represents the spreading degree. Community compositions of AM fungi in both root systems were changed significantly by the L. virgaurea spreading, and also these communities fitted the neutral model very well. AM fungal communities in patches with absence and presence of L. virgaurea were phylogenetically random and clustered, respectively, suggesting that the principal ecological process determining AM fungal assemblage shifted from stochastic process to environmental filtering when this toxic plant was present. Our results indicate that deterministic and stochastic processes together determine the assemblage of AM fungi, but the dominant process would be changed by the spreading of toxic plants, and suggest that the spreading of toxic plants in alpine meadow ecosystems might be involving the mycorrhizal symbionts.
Energy Technology Data Exchange (ETDEWEB)
Driver, Jeffrey H., E-mail: jeff@risksciences.net [risksciences.net, LLC, 10009 Wisakon Trail, Manassas, VA 20111 (United States); Price, Paul S. [The Dow Chemical Company, 1803 Building, Midland, MI 48674 (United States); Van Wesenbeeck, Ian [Dow AgroSciences, LLC, 9330 Zionsville Road, Indianapolis, IN 46268 (United States); Ross, John H. [risksciences.net, LLC, 5150 Fair Oaks Blvd., Ste. 101-370, Carmichael, CA 95608 (United States); Gehen, Sean [Dow AgroSciences, LLC, 9330 Zionsville Road, Indianapolis, IN 46268 (United States); Holden, Larry R. [Larry R. Holden, Statistical Consulting, 1403 Post Oak Circle, College Station, TX (United States); Landenberger, Bryce [The Dow Chemical Company, 1803 Building, Midland, MI 48674 (United States); Hastings, Kerry; Yan, Zhongyu; Rasoulpour, Reza [Dow AgroSciences, LLC, 9330 Zionsville Road, Indianapolis, IN 46268 (United States)
2016-11-15
Dow AgroSciences (DAS) markets and sells 1,3-Dichloropropene (1,3-D), the active ingredient in Telone®, which is used as a pre-plant soil fumigant nematicide in economically important crops in California. 1,3-D has been regulated as a “probable human carcinogen” and the California Department of Pesticide Regulation limits use of 1,3-D based on human health risk assessments for bystanders. This paper presents a risk characterization for bystanders based on advances in the assessment of both exposure and hazard. The revised bystander risk assessment incorporates significant advances: 1) new data on residency duration and mobility in communities where 1,3-D is in high demand; 2) new information on spatial and temporal concentrations of 1,3-D in air based on multi-year modeling using a validated model; and 3) a new stochastic spatial and temporal model of long-term exposures. Predicted distributions of long-term, chronic exposures indicate that current, and anticipated uses of 1,3-D would result in lifetime average daily doses lower than 0.002 mg/kg/d, a dose associated with theoretical lifetime excess cancer risk of < 10{sup −} {sup 5} to > 95% of the local population based on a non-threshold risk assessment approach. Additionally, examination of 1,3-D toxicity studies including new chronic toxicity data and mechanism of action supports the use of a non-linear, threshold based risk assessment approach. The estimated maximum annual average daily dose of < 0.0016 mg/kg/d derived from the updated exposure assessment was then compared with a threshold point of departure. The calculated margin of exposure is > 1000-fold, a clear indication of acceptable risk for human health. In summary, the best available science supports 1,3-D's threshold nature of hazard and the revised exposure assessment supports that current agricultural uses of 1,3-D are associated with reasonable certainty of no harm, i.e., estimated long-term exposures pose insignificant health risks
Directory of Open Access Journals (Sweden)
Akira Ikuta
2014-01-01
Full Text Available In real sound environment system, a specific signal shows various types of probability distribution, and the observation data are usually contaminated by external noise (e.g., background noise of non-Gaussian distribution type. Furthermore, there potentially exist various nonlinear correlations in addition to the linear correlation between input and output time series. Consequently, often the system input and output relationship in the real phenomenon cannot be represented by a simple model using only the linear correlation and lower order statistics. In this study, complex sound environment systems difficult to analyze by using usual structural method are considered. By introducing an estimation method of the system parameters reflecting correlation information for conditional probability distribution under existence of the external noise, a prediction method of output response probability for sound environment systems is theoretically proposed in a suitable form for the additive property of energy variable and the evaluation in decibel scale. The effectiveness of the proposed stochastic signal processing method is experimentally confirmed by applying it to the observed data in sound environment systems.
Energy Technology Data Exchange (ETDEWEB)
Angstmann, C.N.; Donnelly, I.C. [School of Mathematics and Statistics, UNSW Australia, Sydney NSW 2052 (Australia); Henry, B.I., E-mail: B.Henry@unsw.edu.au [School of Mathematics and Statistics, UNSW Australia, Sydney NSW 2052 (Australia); Jacobs, B.A. [School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, Private Bag 3, Wits 2050 (South Africa); DST–NRF Centre of Excellence in Mathematical and Statistical Sciences (CoE-MaSS) (South Africa); Langlands, T.A.M. [Department of Mathematics and Computing, University of Southern Queensland, Toowoomba QLD 4350 (Australia); Nichols, J.A. [School of Mathematics and Statistics, UNSW Australia, Sydney NSW 2052 (Australia)
2016-02-15
We have introduced a new explicit numerical method, based on a discrete stochastic process, for solving a class of fractional partial differential equations that model reaction subdiffusion. The scheme is derived from the master equations for the evolution of the probability density of a sum of discrete time random walks. We show that the diffusion limit of the master equations recovers the fractional partial differential equation of interest. This limiting procedure guarantees the consistency of the numerical scheme. The positivity of the solution and stability results are simply obtained, provided that the underlying process is well posed. We also show that the method can be applied to standard reaction–diffusion equations. This work highlights the broader applicability of using discrete stochastic processes to provide numerical schemes for partial differential equations, including fractional partial differential equations.
Stochastic goal-oriented error estimation with memory
Ackmann, Jan; Marotzke, Jochem; Korn, Peter
2017-11-01
We propose a stochastic dual-weighted error estimator for the viscous shallow-water equation with boundaries. For this purpose, previous work on memory-less stochastic dual-weighted error estimation is extended by incorporating memory effects. The memory is introduced by describing the local truncation error as a sum of time-correlated random variables. The random variables itself represent the temporal fluctuations in local truncation errors and are estimated from high-resolution information at near-initial times. The resulting error estimator is evaluated experimentally in two classical ocean-type experiments, the Munk gyre and the flow around an island. In these experiments, the stochastic process is adapted locally to the respective dynamical flow regime. Our stochastic dual-weighted error estimator is shown to provide meaningful error bounds for a range of physically relevant goals. We prove, as well as show numerically, that our approach can be interpreted as a linearized stochastic-physics ensemble.
Processing of natural temporal stimuli by macaque retinal ganglion cells
Hateren, J.H. van; Rüttiger, L.; Lee, B.B.
2002-01-01
This study quantifies the performance of primate retinal ganglion cells in response to natural stimuli. Stimuli were confined to the temporal and chromatic domains and were derived from two contrasting environments, one typically northern European and the other a flower show. The performance of the
Temporal Processing Development in Chinese Primary School-Aged Children with Dyslexia
Wang, Li-Chih; Yang, Hsien-Ming
2018-01-01
This study aimed to investigate the development of visual and auditory temporal processing among children with and without dyslexia and to examine the roles of temporal processing in reading and reading-related abilities. A total of 362 Chinese children in Grades 1-6 were recruited from Taiwan. Half of the children had dyslexia, and the other half…
The measurement problem on classical diffusion process: inverse method on stochastic processes
International Nuclear Information System (INIS)
Bigerelle, M.; Iost, A.
2004-01-01
In a high number of diffusive systems, measures are processed to calculate material parameters such as diffusion coefficients, or to verify the accuracy of mathematical models. However, the precision of the parameter determination or of the model relevance depends on the location of the measure itself. The aim of this paper is first to analyse, for a mono-dimensional system, the precision of the measure in relation with its location by an inverse problem algorithm and secondly to examine the physical meaning of the results. Statistical mechanic considerations show that, passing over a time-distance criterion, measurement becomes uncertain whatever the initial conditions. The criterion proves that this chaotic mode is related to the production of anti-entropy at a mesoscopique scale that is in violation to quantum theory about measurement
A stochastic post-processing method for solar irradiance forecasts derived from NWPs models
Lara-Fanego, V.; Pozo-Vazquez, D.; Ruiz-Arias, J. A.; Santos-Alamillos, F. J.; Tovar-Pescador, J.
2010-09-01
Solar irradiance forecast is an important area of research for the future of the solar-based renewable energy systems. Numerical Weather Prediction models (NWPs) have proved to be a valuable tool for solar irradiance forecasting with lead time up to a few days. Nevertheless, these models show low skill in forecasting the solar irradiance under cloudy conditions. Additionally, climatic (averaged over seasons) aerosol loading are usually considered in these models, leading to considerable errors for the Direct Normal Irradiance (DNI) forecasts during high aerosols load conditions. In this work we propose a post-processing method for the Global Irradiance (GHI) and DNI forecasts derived from NWPs. Particularly, the methods is based on the use of Autoregressive Moving Average with External Explanatory Variables (ARMAX) stochastic models. These models are applied to the residuals of the NWPs forecasts and uses as external variables the measured cloud fraction and aerosol loading of the day previous to the forecast. The method is evaluated for a set one-moth length three-days-ahead forecast of the GHI and DNI, obtained based on the WRF mesoscale atmospheric model, for several locations in Andalusia (Southern Spain). The Cloud fraction is derived from MSG satellite estimates and the aerosol loading from the MODIS platform estimates. Both sources of information are readily available at the time of the forecast. Results showed a considerable improvement of the forecasting skill of the WRF model using the proposed post-processing method. Particularly, relative improvement (in terms of the RMSE) for the DNI during summer is about 20%. A similar value is obtained for the GHI during the winter.
Leodori, Giorgio; Formica, Alessandra; Zhu, Xiaoying; Conte, Antonella; Belvisi, Daniele; Cruccu, Giorgio; Hallett, Mark; Berardelli, Alfredo
2017-10-01
The somatosensory temporal discrimination threshold (STDT) has been used in recent years to investigate time processing of sensory information, but little is known about the physiological correlates of somatosensory temporal discrimination. The objective of this study was to investigate whether the time interval required to discriminate between two stimuli varies according to the number of stimuli in the task. We used the third-stimulus temporal discrimination threshold (ThirdDT), defined as the shortest time interval at which an individual distinguishes a third stimulus following a pair of stimuli delivered at the STDT. The STDT and ThirdDT were assessed in 31 healthy subjects. In a subgroup of 10 subjects, we evaluated the effects of the stimuli intensity on the ThirdDT. In a subgroup of 16 subjects, we evaluated the effects of S1 continuous theta-burst stimulation (S1-cTBS) on the STDT and ThirdDT. Results show that ThirdDT is shorter than STDT. We found a positive correlation between STDT and ThirdDT values. As long as the stimulus intensity was within the perceivable and painless range, it did not affect ThirdDT values. S1-cTBS significantly affected both STDT and ThirdDT, although the latter was affected to a greater extent and for a longer period of time. We conclude that the interval needed to discriminate between time-separated tactile stimuli is related to the number of stimuli used in the task. STDT and ThirdDT are encoded in S1, probably by a shared tactile temporal encoding mechanism whose performance rapidly changes during the perception process. ThirdDT is a new method to measure somatosensory temporal discrimination. NEW & NOTEWORTHY To investigate whether the time interval required to discriminate between stimuli varies according to changes in the stimulation pattern, we used the third-stimulus temporal discrimination threshold (ThirdDT). We found that the somatosensory temporal discrimination acuity varies according to the number of stimuli in the
Gerhard, Felipe; Deger, Moritz; Truccolo, Wilson
2017-02-01
Point process generalized linear models (PP-GLMs) provide an important statistical framework for modeling spiking activity in single-neurons and neuronal networks. Stochastic stability is essential when sampling from these models, as done in computational neuroscience to analyze statistical properties of neuronal dynamics and in neuro-engineering to implement closed-loop applications. Here we show, however, that despite passing common goodness-of-fit tests, PP-GLMs estimated from data are often unstable, leading to divergent firing rates. The inclusion of absolute refractory periods is not a satisfactory solution since the activity then typically settles into unphysiological rates. To address these issues, we derive a framework for determining the existence and stability of fixed points of the expected conditional intensity function (CIF) for general PP-GLMs. Specifically, in nonlinear Hawkes PP-GLMs, the CIF is expressed as a function of the previous spike history and exogenous inputs. We use a mean-field quasi-renewal (QR) approximation that decomposes spike history effects into the contribution of the last spike and an average of the CIF over all spike histories prior to the last spike. Fixed points for stationary rates are derived as self-consistent solutions of integral equations. Bifurcation analysis and the number of fixed points predict that the original models can show stable, divergent, and metastable (fragile) dynamics. For fragile models, fluctuations of the single-neuron dynamics predict expected divergence times after which rates approach unphysiologically high values. This metric can be used to estimate the probability of rates to remain physiological for given time periods, e.g., for simulation purposes. We demonstrate the use of the stability framework using simulated single-neuron examples and neurophysiological recordings. Finally, we show how to adapt PP-GLM estimation procedures to guarantee model stability. Overall, our results provide a
Directory of Open Access Journals (Sweden)
Juliana Meneguello
2006-08-01
Full Text Available A epilepsia do lobo temporal ocasiona descargas elétricas excessivas onde a via auditiva tem sua estação final. É uma das formas mais comuns e de mais difícil controle da doença. O correto processamento dos estímulos auditivos necessita da integridade anatômica e funcional de todas as estruturas envolvidas na via auditiva. OBJETIVO: Verificar o Processamento Auditivo de pacientes portadores de epilepsia do lobo temporal quanto aos mecanismos de discriminação de sons em seqüência e de padrões tonais, discriminação da direção da fonte sonora e atenção seletiva para sons verbais e não-verbais. MÉTODO: Foram avaliados oito indivíduos com epilepsia do lobo temporal confirmada e com foco restrito a essa região, através dos testes auditivos especiais: Teste de Localização Sonora, Teste de Padrão de Duração, Teste Dicótico de Dígitos e Teste Dicótico Não-Verbal. O seu desempenho foi comparado ao de indivíduos sem alteração neurológica (estudo caso-controle. RESULTADO: Os sujeitos com epilepsia do lobo temporal apresentaram desempenho semelhante aos do grupo controle quanto ao mecanismo de discriminação da direção da fonte sonora e desempenho inferior quanto aos demais mecanismos avaliados. CONCLUSÃO: Indivíduos com epilepsia do lobo temporal apresentaram maior prejuízo no processamento auditivo que os sem danos corticais, de idades semelhantes.Temporal epilepsy, one of the most common presentation of this pathology, causes excessive electrical discharges in the area where we have the final station of the auditory pathway. Both the anatomical and functional integrity of the auditory pathway structures are essential for the correct processing of auditory stimuli. AIM: to check the Auditory Processing in patients with temporal lobe epilepsy regarding the auditory mechanisms of discrimination from sequential sounds and tone patterns, discrimination of the sound source direction and selective attention to verbal
Stochastic modeling of catalytic processes in nanoporous materials: Beyond mean-field approach
Energy Technology Data Exchange (ETDEWEB)
Garcia, Andres [Iowa State Univ., Ames, IA (United States)
2017-08-05
Transport and reaction in zeolites and other porous materials, such as mesoporous silica particles, has been a focus of interest in recent years. This is in part due to the possibility of anomalous transport effects (e.g. single-file diffusion) and its impact in the reaction yield in catalytic processes. Computational simulations are often used to study these complex nonequilibrium systems. Computer simulations using Molecular Dynamics (MD) techniques are prohibitive, so instead coarse grained one-dimensional models with the aid of Kinetic Monte Carlo (KMC) simulations are used. Both techniques can be computationally expensive, both time and resource wise. These coarse-grained systems can be exactly described by a set of coupled stochastic master equations, that describe the reaction-diffusion kinetics of the system. The equations can be written exactly, however, coupling between the equations and terms within the equations make it impossible to solve them exactly; approximations must be made. One of the most common methods to obtain approximate solutions is to use Mean Field (MF) theory. MF treatments yield reasonable results at high ratios of reaction rate k to hop rate h of the particles, but fail completely at low k=h due to the over-estimation of fluxes of particles within the pore. We develop a method to estimate fluxes and intrapore diffusivity in simple one- dimensional reaction-diffusion models at high and low k=h, where the pores are coupled to an equilibrated three-dimensional fluid. We thus successfully describe analytically these simple reaction-diffusion one-dimensional systems. Extensions to models considering behavior with long range steric interactions and wider pores require determination of multiple boundary conditions. We give a prescription to estimate the required parameters for these simulations. For one dimensional systems, if single-file diffusion is relaxed, additional parameters to describe particle exchange have to be introduced. We use
Directory of Open Access Journals (Sweden)
E. Chumak
2015-04-01
Full Text Available The author substantiates that only methodological training systems of mathematical disciplines with implementation of information and communication technologies (ICT can meet the requirements of modern educational paradigm and make possible to increase the educational efficiency. Due to this fact, the necessity of developing the methodology of theory of probability and stochastic processes computer-based learning for pre-service engineers is underlined in the paper. The results of the experimental study for analysis of the efficiency of methodological system of theory of probability and stochastic processes computer-based learning for pre-service engineers are shown. The analysis includes three main stages: ascertaining, searching and forming. The key criteria of the efficiency of designed methodological system are the level of probabilistic and stochastic skills of students and their learning motivation. The effect of implementing the methodological system of probability theory and stochastic processes computer-based learning on the level of students’ IT literacy is shown in the paper. The expanding of the range of objectives of ICT applying by students is described by author. The level of formation of students’ learning motivation on the ascertaining and forming stages of the experiment is analyzed. The level of intrinsic learning motivation for pre-service engineers is defined on these stages of the experiment. For this purpose, the methodology of testing the students’ learning motivation in the chosen specialty is presented in the paper. The increasing of intrinsic learning motivation of the experimental group students (E group against the control group students (C group is demonstrated.
Ding, Shaojie; Qian, Min; Qian, Hong; Zhang, Xuejuan
2016-12-01
The stochastic Hodgkin-Huxley model is one of the best-known examples of piecewise deterministic Markov processes (PDMPs), in which the electrical potential across a cell membrane, V(t), is coupled with a mesoscopic Markov jump process representing the stochastic opening and closing of ion channels embedded in the membrane. The rates of the channel kinetics, in turn, are voltage-dependent. Due to this interdependence, an accurate and efficient sampling of the time evolution of the hybrid stochastic systems has been challenging. The current exact simulation methods require solving a voltage-dependent hitting time problem for multiple path-dependent intensity functions with random thresholds. This paper proposes a simulation algorithm that approximates an alternative representation of the exact solution by fitting the log-survival function of the inter-jump dwell time, H(t), with a piecewise linear one. The latter uses interpolation points that are chosen according to the time evolution of the H(t), as the numerical solution to the coupled ordinary differential equations of V(t) and H(t). This computational method can be applied to all PDMPs. Pathwise convergence of the approximated sample trajectories to the exact solution is proven, and error estimates are provided. Comparison with a previous algorithm that is based on piecewise constant approximation is also presented.
Energy Technology Data Exchange (ETDEWEB)
Chechetkin, V.R.; Lutovinov, V.S.
1986-09-11
The continuous stochastic formalism for the description of systems with birth and death processes randomly distributed in space is developed with the use of local birth and death operators and local generalization of the corresponding Chapman-Kolmogorov equation. The functional stochastic equation for the evolution of the probability functional is derived and its modifications for evolution of the characteristic functional and the first passage time problem are given. The corresponding evolution equations for equal-time correlators are also derived. The results are generalized then on the exothermic and endothermic chemical reactions. As examples of the particular applications of the results the small fluctuations near stable equilibrium state and fluctuations in mono-molecular reactions, Lotka-Volterra model, Schloegl reaction and brusselator are considered. It is shown that the two-dimensional Lotka-Volterra model may exhibit synergetic phase transition analogous to the topological transition of the Kosterlitz-Thouless-Berezinskii type. At the end of the paper some general consequences from stochastic evolution of the birth and death processes are discussed and the arguments on their importance in evolution of populations, cellular dynamics and in applications to various chemical and biological problems are presented.
Audiovisual Temporal Processing and Synchrony Perception in the Rat.
Schormans, Ashley L; Scott, Kaela E; Vo, Albert M Q; Tyker, Anna; Typlt, Marei; Stolzberg, Daniel; Allman, Brian L
2016-01-01
Extensive research on humans has improved our understanding of how the brain integrates information from our different senses, and has begun to uncover the brain regions and large-scale neural activity that contributes to an observer's ability to perceive the relative timing of auditory and visual stimuli. In the present study, we developed the first behavioral tasks to assess the perception of audiovisual temporal synchrony in rats. Modeled after the parameters used in human studies, separate groups of rats were trained to perform: (1) a simultaneity judgment task in which they reported whether audiovisual stimuli at various stimulus onset asynchronies (SOAs) were presented simultaneously or not; and (2) a temporal order judgment task in which they reported whether they perceived the auditory or visual stimulus to have been presented first. Furthermore, using in vivo electrophysiological recordings in the lateral extrastriate visual (V2L) cortex of anesthetized rats, we performed the first investigation of how neurons in the rat multisensory cortex integrate audiovisual stimuli presented at different SOAs. As predicted, rats ( n = 7) trained to perform the simultaneity judgment task could accurately (~80%) identify synchronous vs. asynchronous (200 ms SOA) trials. Moreover, the rats judged trials at 10 ms SOA to be synchronous, whereas the majority (~70%) of trials at 100 ms SOA were perceived to be asynchronous. During the temporal order judgment task, rats ( n = 7) perceived the synchronous audiovisual stimuli to be "visual first" for ~52% of the trials, and calculation of the smallest timing interval between the auditory and visual stimuli that could be detected in each rat (i.e., the just noticeable difference (JND)) ranged from 77 ms to 122 ms. Neurons in the rat V2L cortex were sensitive to the timing of audiovisual stimuli, such that spiking activity was greatest during trials when the visual stimulus preceded the auditory by 20-40 ms. Ultimately, given
Walker, Martin; Hall, Andrew; Basáñez, María-Gloria
2010-10-01
The importance of the mode of acquisition of infectious stages of directly-transmitted parasitic helminths has been acknowledged in population dynamics models; hosts may acquire eggs/larvae singly in a "trickle" type manner or in "clumps". Such models have shown that the mode of acquisition influences the distribution and dynamics of parasite loads, the stability of host-parasite systems and the rate of emergence of anthelmintic resistance, yet very few field studies have allowed these questions to be explored with empirical data. We have analysed individual worm weight data for the parasitic roundworm of humans, Ascaris lumbricoides, collected from a three-round chemo-expulsion study in Dhaka, Bangladesh, with the aim of discerning whether a trickle or a clumped infection process predominates. We found that hosts tend to harbour female worms of a similar weight, indicative of a clumped infection process, but acknowledged that unmeasured host heterogeneities (random effects) could not be completely excluded as a cause. Here, we complement our previous statistical analyses using a stochastic infection model to simulate sizes of individual A. lumbricoides infecting a population of humans. We use the intraclass correlation coefficient (ICC) as a quantitative measure of similarity among simulated worm sizes and explore the behaviour of this statistic under assumptions corresponding to trickle or clumped infections and unmeasured host heterogeneities. We confirm that both mechanisms are capable of generating aggregates of similar-sized worms, but that the particular pattern of ICCs described pre- and post-anthelmintic treatment in the data is more consistent with aggregation generated by clumped infections than by host heterogeneities alone. This provides support to the notion that worms may be acquired in clumps. We discuss our results in terms of the population biology of A. lumbricoides and highlight the significance of our modelling approach for the study of the
A stochastic process model for life cycle cost analysis of nuclear power plant systems
Van der Weide, J.A.M.; Pandey, M.D.
2013-01-01
The paper presents a general stochastic model to analyze the life cycle cost of an engineering system that is affected by minor but repairable failures interrupting the operation and a major failure that would require the replacement or renewal of the failed system. It is commonly observed that the
Stochastic Greybox Modeling for Control of an Alternating Activated Sludge Process
DEFF Research Database (Denmark)
Halvgaard, Rasmus Fogtmann; Vezzaro, Luca; Grum, M.
We present a stochastic greybox model of a BioDenitro WWTP that can be used for short time horizon Model Predictive Control. The model is based on a simpliﬁed ASM1 model and takes model uncertainty in to account. It estimates unmeasured state variables in the system, e.g. the inlet concentration...
International Nuclear Information System (INIS)
Ziri, S.M.; Seefeldt, W.B.
1977-08-01
This analysis has demonstrated that a plant's temporal response to perturbation of feed isotope composition can be used to measure the in-process inventory, without suspending plant operations. The main advantages of the temporal response technique over the step-displacement method are (1) it (the temporal response method) obviates the need for large special feed batches, and (2) it obviates the requirement that all the in-process material have a uniform isotopic composition at the beginning of the measurement. The temporal response method holds promise for essentially continuous real-time determination of in-process SNM. However, the temporal response method requires the measurement of the isotopic composition of many samples, and it works best for a stationary random input time series of tracer perturbations. Both of these requirements appear amenable to satisfaction by practical equipment and procedures if the benefits are deemed sufficiently worthwhile
Oron, Anna; Szymaszek, Aneta; Szelag, Elzbieta
2015-01-01
Background: Temporal information processing (TIP) underlies many aspects of cognitive functions like language, motor control, learning, memory, attention, etc. Millisecond timing may be assessed by sequencing abilities, e.g. the perception of event order. It may be measured with auditory temporal-order-threshold (TOT), i.e. a minimum time gap…
Levels of Processing with Free and Cued Recall and Unilateral Temporal Lobe Epilepsy
Lespinet-Najib, Veronique; N'Kaoua, Bernard; Sauzeon, Helene; Bresson, Christel; Rougier, Alain; Claverie, Bernard
2004-01-01
This study investigates the role of the temporal lobes in levels-of-processing tasks (phonetic and semantic encoding) according to the nature of recall tasks (free and cued recall). These tasks were administered to 48 patients with unilateral temporal epilepsy (right ''RTLE''=24; left ''LTLE''=24) and a normal group (n=24). The results indicated…
The Role of Visual and Auditory Temporal Processing for Chinese Children with Developmental Dyslexia
Chung, Kevin K. H.; McBride-Chang, Catherine; Wong, Simpson W. L.; Cheung, Him; Penney, Trevor B.; Ho, Connie S. -H.
2008-01-01
This study examined temporal processing in relation to Chinese reading acquisition and impairment. The performances of 26 Chinese primary school children with developmental dyslexia on tasks of visual and auditory temporal order judgement, rapid naming, visual-orthographic knowledge, morphological, and phonological awareness were compared with…
Eichhorn, Ralf; Aurell, Erik
2014-04-01
theory for small deviations from equilibrium, in which a general framework is constructed from the analysis of non-equilibrium states close to equilibrium. In a next step, Prigogine and others developed linear irreversible thermodynamics, which establishes relations between transport coefficients and entropy production on a phenomenological level in terms of thermodynamic forces and fluxes. However, beyond the realm of linear response no general theoretical results were available for quite a long time. This situation has changed drastically over the last 20 years with the development of stochastic thermodynamics, revealing that the range of validity of thermodynamic statements can indeed be extended deep into the non-equilibrium regime. Early developments in that direction trace back to the observations of symmetry relations between the probabilities for entropy production and entropy annihilation in non-equilibrium steady states [5-8] (nowadays categorized in the class of so-called detailed fluctuation theorems), and the derivations of the Bochkov-Kuzovlev [9, 10] and Jarzynski relations [11] (which are now classified as so-called integral fluctuation theorems). Apart from its fundamental theoretical interest, the developments in stochastic thermodynamics have experienced an additional boost from the recent experimental progress in fabricating, manipulating, controlling and observing systems on the micro- and nano-scale. These advances are not only of formidable use for probing and monitoring biological processes on the cellular, sub-cellular and molecular level, but even include the realization of a microscopic thermodynamic heat engine [12] or the experimental verification of Landauer's principle in a colloidal system [13]. The scientific program Stochastic Thermodynamics held between 4 and 15 March 2013, and hosted by The Nordic Institute for Theoretical Physics (Nordita), was attended by more than 50 scientists from the Nordic countries and elsewhere, amongst them
Liu, Zhangjun; Liu, Zenghui
2018-06-01
This paper develops a hybrid approach of spectral representation and random function for simulating stationary stochastic vector processes. In the proposed approach, the high-dimensional random variables, included in the original spectral representation (OSR) formula, could be effectively reduced to only two elementary random variables by introducing the random functions that serve as random constraints. Based on this, a satisfactory simulation accuracy can be guaranteed by selecting a small representative point set of the elementary random variables. The probability information of the stochastic excitations can be fully emerged through just several hundred of sample functions generated by the proposed approach. Therefore, combined with the probability density evolution method (PDEM), it could be able to implement dynamic response analysis and reliability assessment of engineering structures. For illustrative purposes, a stochastic turbulence wind velocity field acting on a frame-shear-wall structure is simulated by constructing three types of random functions to demonstrate the accuracy and efficiency of the proposed approach. Careful and in-depth studies concerning the probability density evolution analysis of the wind-induced structure have been conducted so as to better illustrate the application prospects of the proposed approach. Numerical examples also show that the proposed approach possesses a good robustness.
Visual temporal processing in dyslexia and the magnocellular deficit theory: the need for speed?
McLean, Gregor M T; Stuart, Geoffrey W; Coltheart, Veronika; Castles, Anne
2011-12-01
A controversial question in reading research is whether dyslexia is associated with impairments in the magnocellular system and, if so, how these low-level visual impairments might affect reading acquisition. This study used a novel chromatic flicker perception task to specifically explore temporal aspects of magnocellular functioning in 40 children with dyslexia and 42 age-matched controls (aged 7-11). The relationship between magnocellular temporal resolution and higher-level aspects of visual temporal processing including inspection time, single and dual-target (attentional blink) RSVP performance, go/no-go reaction time, and rapid naming was also assessed. The Dyslexia group exhibited significant deficits in magnocellular temporal resolution compared with controls, but the two groups did not differ in parvocellular temporal resolution. Despite the significant group differences, associations between magnocellular temporal resolution and reading ability were relatively weak, and links between low-level temporal resolution and reading ability did not appear specific to the magnocellular system. Factor analyses revealed that a collective Perceptual Speed factor, involving both low-level and higher-level visual temporal processing measures, accounted for unique variance in reading ability independently of phonological processing, rapid naming, and general ability.
Driver, Jeffrey H; Price, Paul S; Van Wesenbeeck, Ian; Ross, John H; Gehen, Sean; Holden, Larry R; Landenberger, Bryce; Hastings, Kerry; Yan, Zhongyu June; Rasoulpour, Reza
2016-11-15
Dow AgroSciences (DAS) markets and sells 1,3-Dichloropropene (1,3-D), the active ingredient in Telone®, which is used as a pre-plant soil fumigant nematicide in economically important crops in California. 1,3-D has been regulated as a "probable human carcinogen" and the California Department of Pesticide Regulation limits use of 1,3-D based on human health risk assessments for bystanders. This paper presents a risk characterization for bystanders based on advances in the assessment of both exposure and hazard. The revised bystander risk assessment incorporates significant advances: 1) new data on residency duration and mobility in communities where 1,3-D is in high demand; 2) new information on spatial and temporal concentrations of 1,3-D in air based on multi-year modeling using a validated model; and 3) a new stochastic spatial and temporal model of long-term exposures. Predicted distributions of long-term, chronic exposures indicate that current, and anticipated uses of 1,3-D would result in lifetime average daily doses lower than 0.002mg/kg/d, a dose associated with theoretical lifetime excess cancer risk of 95% of the local population based on a non-threshold risk assessment approach. Additionally, examination of 1,3-D toxicity studies including new chronic toxicity data and mechanism of action supports the use of a non-linear, threshold based risk assessment approach. The estimated maximum annual average daily dose of 1000-fold, a clear indication of acceptable risk for human health. In summary, the best available science supports 1,3-D's threshold nature of hazard and the revised exposure assessment supports that current agricultural uses of 1,3-D are associated with reasonable certainty of no harm, i.e., estimated long-term exposures pose insignificant health risks to bystanders even when the non-threshold approach is assumed. Copyright © 2016 Elsevier B.V. All rights reserved.
Yuan, Yuan; Bachl, Fabian E.; Lindgren, Finn; Borchers, David L.; Illian, Janine B.; Buckland, Stephen T.; Rue, Haavard; Gerrodette, Tim
2017-01-01
Distance sampling is a widely used method for estimating wildlife population abundance. The fact that conventional distance sampling methods are partly design-based constrains the spatial resolution at which animal density can be estimated using these methods. Estimates are usually obtained at survey stratum level. For an endangered species such as the blue whale, it is desirable to estimate density and abundance at a finer spatial scale than stratum. Temporal variation in the spatial structure is also important. We formulate the process generating distance sampling data as a thinned spatial point process and propose model-based inference using a spatial log-Gaussian Cox process. The method adopts a flexible stochastic partial differential equation (SPDE) approach to model spatial structure in density that is not accounted for by explanatory variables, and integrated nested Laplace approximation (INLA) for Bayesian inference. It allows simultaneous fitting of detection and density models and permits prediction of density at an arbitrarily fine scale. We estimate blue whale density in the Eastern Tropical Pacific Ocean from thirteen shipboard surveys conducted over 22 years. We find that higher blue whale density is associated with colder sea surface temperatures in space, and although there is some positive association between density and mean annual temperature, our estimates are consistent with no trend in density across years. Our analysis also indicates that there is substantial spatially structured variation in density that is not explained by available covariates.
Yuan, Yuan
2017-12-28
Distance sampling is a widely used method for estimating wildlife population abundance. The fact that conventional distance sampling methods are partly design-based constrains the spatial resolution at which animal density can be estimated using these methods. Estimates are usually obtained at survey stratum level. For an endangered species such as the blue whale, it is desirable to estimate density and abundance at a finer spatial scale than stratum. Temporal variation in the spatial structure is also important. We formulate the process generating distance sampling data as a thinned spatial point process and propose model-based inference using a spatial log-Gaussian Cox process. The method adopts a flexible stochastic partial differential equation (SPDE) approach to model spatial structure in density that is not accounted for by explanatory variables, and integrated nested Laplace approximation (INLA) for Bayesian inference. It allows simultaneous fitting of detection and density models and permits prediction of density at an arbitrarily fine scale. We estimate blue whale density in the Eastern Tropical Pacific Ocean from thirteen shipboard surveys conducted over 22 years. We find that higher blue whale density is associated with colder sea surface temperatures in space, and although there is some positive association between density and mean annual temperature, our estimates are consistent with no trend in density across years. Our analysis also indicates that there is substantial spatially structured variation in density that is not explained by available covariates.
Influence of memory, attention, IQ and age on auditory temporal processing tests: preliminary study.
Murphy, Cristina Ferraz Borges; Zachi, Elaine Cristina; Roque, Daniela Tsubota; Ventura, Dora Selma Fix; Schochat, Eliane
2014-01-01
To investigate the existence of correlations between the performance of children in auditory temporal tests (Frequency Pattern and Gaps in Noise--GIN) and IQ, attention, memory and age measurements. Fifteen typically developing individuals between the ages of 7 to 12 years and normal hearing participated in the study. Auditory temporal processing tests (GIN and Frequency Pattern), as well as a Memory test (Digit Span), Attention tests (auditory and visual modality) and intelligence tests (RAVEN test of Progressive Matrices) were applied. Significant and positive correlation between the Frequency Pattern test and age variable were found, which was considered good (p<0.01, 75.6%). There were no significant correlations between the GIN test and the variables tested. Auditory temporal skills seem to be influenced by different factors: while the performance in temporal ordering skill seems to be influenced by maturational processes, the performance in temporal resolution was not influenced by any of the aspects investigated.
Moreno, Pablo; García, Marcelo
2016-01-01
The increase in energy consumption, especially in residential consumers, means that the electrical system should grow at pair, in infrastructure and installed capacity, the energy prices vary to meet these needs, so this paper uses the methodology of demand response using stochastic methods such as Markov, to optimize energy consumption of residential users. It is necessary to involve customers in the electrical system because in this way it can be verified the actual amount of electric charg...
Stochastic processes and the non-perturbative structure of the QCD vacuum
International Nuclear Information System (INIS)
Vilela Mendes, R.
1992-01-01
Based on a local Gaussian evaluation of the functional integral representation, a method is developed to obtain ground state functionals. The method is applied to the gluon sector of QCD. For the leading term in the ground state functional, stochastic techniques are used to check consistency of the quantum theory, finiteness of the mass gap and the scaling relation in the continuum limit. The functional also implies strong chromomagnetic fluctuations which constrain the propagators in the fermion sector. (orig.)
Iwata, Saeko; Tsukiura, Takashi
2017-11-01
Episodic memory is defined as memory for personally experienced events, and includes memory content and contextual information of time and space. Previous neuroimaging and neuropsychological studies have demonstrated three possible roles of the temporal context in episodic memory. First, temporal information contributes to the arrangement of temporal order for sequential events in episodic memory, and this process is involved in the lateral prefrontal cortex. The second possible role of temporal information in episodic memory is the segregation between memories of multiple events, which are segregated by cues of different time information. The role of segregation is associated with the orbitofrontal regions including the orbitofrontal cortex and basal forebrain region. Third, temporal information in episodic memory plays an important role in the integration of multiple components into a coherent episodic memory, in which episodic components in the different modalities are combined by temporal information as an index. The role of integration is mediated by the medial temporal lobe including the hippocampus and parahippocampal gyrus. Thus, temporal information in episodic memory could be represented in multiple stages, which are involved in a network of the lateral prefrontal, orbitofrontal, and medial temporal lobe regions.
Directory of Open Access Journals (Sweden)
Petras Rupšys
2015-01-01
Full Text Available A stochastic modeling approach based on the Bertalanffy law gained interest due to its ability to produce more accurate results than the deterministic approaches. We examine tree crown width dynamic with the Bertalanffy type stochastic differential equation (SDE and mixed-effects parameters. In this study, we demonstrate how this simple model can be used to calculate predictions of crown width. We propose a parameter estimation method and computational guidelines. The primary goal of the study was to estimate the parameters by considering discrete sampling of the diameter at breast height and crown width and by using maximum likelihood procedure. Performance statistics for the crown width equation include statistical indexes and analysis of residuals. We use data provided by the Lithuanian National Forest Inventory from Scots pine trees to illustrate issues of our modeling technique. Comparison of the predicted crown width values of mixed-effects parameters model with those obtained using fixed-effects parameters model demonstrates the predictive power of the stochastic differential equations model with mixed-effects parameters. All results were implemented in a symbolic algebra system MAPLE.
Spatio-Temporal Process Simulation of Dam-Break Flood Based on SPH
Wang, H.; Ye, F.; Ouyang, S.; Li, Z.
2018-04-01
On the basis of introducing the SPH (Smooth Particle Hydrodynamics) simulation method, the key research problems were given solutions in this paper, which ere the spatial scale and temporal scale adapting to the GIS(Geographical Information System) application, the boundary condition equations combined with the underlying surface, and the kernel function and parameters applicable to dam-break flood simulation. In this regards, a calculation method of spatio-temporal process emulation with elaborate particles for dam-break flood was proposed. Moreover the spatio-temporal process was dynamic simulated by using GIS modelling and visualization. The results show that the method gets more information, objectiveness and real situations.
ARIMA-Based Time Series Model of Stochastic Wind Power Generation
DEFF Research Database (Denmark)
Chen, Peiyuan; Pedersen, Troels; Bak-Jensen, Birgitte
2010-01-01
This paper proposes a stochastic wind power model based on an autoregressive integrated moving average (ARIMA) process. The model takes into account the nonstationarity and physical limits of stochastic wind power generation. The model is constructed based on wind power measurement of one year from...... the Nysted offshore wind farm in Denmark. The proposed limited-ARIMA (LARIMA) model introduces a limiter and characterizes the stochastic wind power generation by mean level, temporal correlation and driving noise. The model is validated against the measurement in terms of temporal correlation...... and probability distribution. The LARIMA model outperforms a first-order transition matrix based discrete Markov model in terms of temporal correlation, probability distribution and model parameter number. The proposed LARIMA model is further extended to include the monthly variation of the stochastic wind power...
International Nuclear Information System (INIS)
Zivi, S.M.; Seefeldt, W.B.
1976-01-01
This analysis demonstrated that a plant's temporal response to perturbations of feed isotope composition can be used to measure the in-process inventory, without suspending plant operations. The main advantage of the temporal response technique over the step-displacement method are (1) it obviates the need for large special feed batches and (2) it obviates the requirement that all the in-process material have a uniform isotopic composition at the beginning of the measurement. The temporal response method holds promise for essentially continuous real-time determination of in-process SNM. The main disadvantage or problem with the temporal response method is that it requires the measurement of the isotopic composition of a great many samples to moderately high accuracy. This requirement appears amenable to solution by a modest effort in instrument development
Instantaneous stochastic perturbation theory
International Nuclear Information System (INIS)
Lüscher, Martin
2015-01-01
A form of stochastic perturbation theory is described, where the representative stochastic fields are generated instantaneously rather than through a Markov process. The correctness of the procedure is established to all orders of the expansion and for a wide class of field theories that includes all common formulations of lattice QCD.
International Nuclear Information System (INIS)
Colombino, A.; Mosiello, R.; Norelli, F.; Jorio, V.M.; Pacilio, N.
1975-01-01
A nuclear system kinetics is formulated according to a stochastic approach. The detailed probability balance equations are written for the probability of finding the mixed population of neutrons and detected neutrons, i.e. detectrons, at a given level for a given instant of time. Equations are integrated in search of a probability profile: a series of cases is analyzed through a progressive criterium. It tends to take into account an increasing number of physical processes within the chosen model. The most important contribution is that solutions interpret analytically experimental conditions of equilibrium (moise analysis) and non equilibrium (pulsed neutron measurements, source drop technique, start up procedures)
Directory of Open Access Journals (Sweden)
Shuang Li
2014-01-01
Full Text Available We study the pricing of American options in an incomplete market in which the dynamics of the underlying risky asset is driven by a jump diffusion process with stochastic volatility. By employing a risk-minimization criterion, we obtain the Radon-Nikodym derivative for the minimal martingale measure and consequently a linear complementarity problem (LCP for American option price. An iterative method is then established to solve the LCP problem for American put option price. Our numerical results show that the model and numerical scheme are robust in capturing the feature of incomplete finance market, particularly the influence of market volatility on the price of American options.
The role of primary auditory and visual cortices in temporal processing: A tDCS approach.
Mioni, G; Grondin, S; Forgione, M; Fracasso, V; Mapelli, D; Stablum, F
2016-10-15
Many studies showed that visual stimuli are frequently experienced as shorter than equivalent auditory stimuli. These findings suggest that timing is distributed across many brain areas and that "different clocks" might be involved in temporal processing. The aim of this study is to investigate, with the application of tDCS over V1 and A1, the specific role of primary sensory cortices (either visual or auditory) in temporal processing. Forty-eight University students were included in the study. Twenty-four participants were stimulated over A1 and 24 participants were stimulated over V1. Participants performed time bisection tasks, in the visual and the auditory modalities, involving standard durations lasting 300ms (short) and 900ms (long). When tDCS was delivered over A1, no effect of stimulation was observed on perceived duration but we observed higher temporal variability under anodic stimulation compared to sham and higher variability in the visual compared to the auditory modality. When tDCS was delivered over V1, an under-estimation of perceived duration and higher variability was observed in the visual compared to the auditory modality. Our results showed more variability of visual temporal processing under tDCS stimulation. These results suggest a modality independent role of A1 in temporal processing and a modality specific role of V1 in the processing of temporal intervals in the visual modality. Copyright © 2016 Elsevier B.V. All rights reserved.
Multivariate moment closure techniques for stochastic kinetic models
International Nuclear Information System (INIS)
Lakatos, Eszter; Ale, Angelique; Kirk, Paul D. W.; Stumpf, Michael P. H.
2015-01-01
Stochastic effects dominate many chemical and biochemical processes. Their analysis, however, can be computationally prohibitively expensive and a range of approximation schemes have been proposed to lighten the computational burden. These, notably the increasingly popular linear noise approximation and the more general moment expansion methods, perform well for many dynamical regimes, especially linear systems. At higher levels of nonlinearity, it comes to an interplay between the nonlinearities and the stochastic dynamics, which is much harder to capture correctly by such approximations to the true stochastic processes. Moment-closure approaches promise to address this problem by capturing higher-order terms of the temporally evolving probability distribution. Here, we develop a set of multivariate moment-closures that allows us to describe the stochastic dynamics of nonlinear systems. Multivariate closure captures the way that correlations between different molecular species, induced by the reaction dynamics, interact with stochastic effects. We use multivariate Gaussian, gamma, and lognormal closure and illustrate their use in the context of two models that have proved challenging to the previous attempts at approximating stochastic dynamics: oscillations in p53 and Hes1. In addition, we consider a larger system, Erk-mediated mitogen-activated protein kinases signalling, where conventional stochastic simulation approaches incur unacceptably high computational costs
Multivariate moment closure techniques for stochastic kinetic models
Energy Technology Data Exchange (ETDEWEB)
Lakatos, Eszter, E-mail: e.lakatos13@imperial.ac.uk; Ale, Angelique; Kirk, Paul D. W.; Stumpf, Michael P. H., E-mail: m.stumpf@imperial.ac.uk [Department of Life Sciences, Centre for Integrative Systems Biology and Bioinformatics, Imperial College London, London SW7 2AZ (United Kingdom)
2015-09-07
Stochastic effects dominate many chemical and biochemical processes. Their analysis, however, can be computationally prohibitively expensive and a range of approximation schemes have been proposed to lighten the computational burden. These, notably the increasingly popular linear noise approximation and the more general moment expansion methods, perform well for many dynamical regimes, especially linear systems. At higher levels of nonlinearity, it comes to an interplay between the nonlinearities and the stochastic dynamics, which is much harder to capture correctly by such approximations to the true stochastic processes. Moment-closure approaches promise to address this problem by capturing higher-order terms of the temporally evolving probability distribution. Here, we develop a set of multivariate moment-closures that allows us to describe the stochastic dynamics of nonlinear systems. Multivariate closure captures the way that correlations between different molecular species, induced by the reaction dynamics, interact with stochastic effects. We use multivariate Gaussian, gamma, and lognormal closure and illustrate their use in the context of two models that have proved challenging to the previous attempts at approximating stochastic dynamics: oscillations in p53 and Hes1. In addition, we consider a larger system, Erk-mediated mitogen-activated protein kinases signalling, where conventional stochastic simulation approaches incur unacceptably high computational costs.
Effluent trading in river systems through stochastic decision-making process: a case study.
Zolfagharipoor, Mohammad Amin; Ahmadi, Azadeh
2017-09-01
The objective of this paper is to provide an efficient framework for effluent trading in river systems. The proposed framework consists of two pessimistic and optimistic decision-making models to increase the executability of river water quality trading programs. The models used for this purpose are (1) stochastic fallback bargaining (SFB) to reach an agreement among wastewater dischargers and (2) stochastic multi-criteria decision-making (SMCDM) to determine the optimal treatment strategy. The Monte-Carlo simulation method is used to incorporate the uncertainty into analysis. This uncertainty arises from stochastic nature and the errors in the calculation of wastewater treatment costs. The results of river water quality simulation model are used as the inputs of models. The proposed models are used in a case study on the Zarjoub River in northern Iran to determine the best solution for the pollution load allocation. The best treatment alternatives selected by each model are imported, as the initial pollution discharge permits, into an optimization model developed for trading of pollution discharge permits among pollutant sources. The results show that the SFB-based water pollution trading approach reduces the costs by US$ 14,834 while providing a relative consensus among pollutant sources. Meanwhile, the SMCDM-based water pollution trading approach reduces the costs by US$ 218,852, but it is less acceptable by pollutant sources. Therefore, it appears that giving due attention to stability, or in other words acceptability of pollution trading programs for all pollutant sources, is an essential element of their success.
Willigenburg, van L.G.; Koning, de W.L.
2013-01-01
Two different descriptions are used in the literature to formulate the optimal dynamic output feedback control problem for linear dynamical systems with white stochastic parameters and quadratic criteria, called the optimal compensation problem. One describes the matrix valued white stochastic
Parkinson’s disease motor disorganization and temporal processing
Florio, Tiziana M.
2017-01-01
Motor control is essential for everyday life and highly contributes to the development and organisation of higher cognitive functions. Embodied cognition endemically approaches cognitive activities, grounding on sensory-motor processes and the ability to switch from each other in response to specific context and situations. In this view, it is possible to deliberate higher functions such as “expertise” and “decision making” as the ability to reactivate, deconstruct and reconstruct different m...
Video Game Players Show More Precise Multisensory Temporal Processing Abilities
Donohue, Sarah E.; Woldorff, Marty G.; Mitroff, Stephen R.
2010-01-01
Recent research has demonstrated enhanced visual attention and visual perception in individuals with extensive experience playing action video games. These benefits manifest in several realms, but much remains unknown about the ways in which video game experience alters perception and cognition. The current study examined whether video game players’ benefits generalize beyond vision to multisensory processing by presenting video game players and non-video game players auditory and visual stim...
Stochastic Wake Modelling Based on POD Analysis
Directory of Open Access Journals (Sweden)
David Bastine
2018-03-01
Full Text Available In this work, large eddy simulation data is analysed to investigate a new stochastic modeling approach for the wake of a wind turbine. The data is generated by the large eddy simulation (LES model PALM combined with an actuator disk with rotation representing the turbine. After applying a proper orthogonal decomposition (POD, three different stochastic models for the weighting coefficients of the POD modes are deduced resulting in three different wake models. Their performance is investigated mainly on the basis of aeroelastic simulations of a wind turbine in the wake. Three different load cases and their statistical characteristics are compared for the original LES, truncated PODs and the stochastic wake models including different numbers of POD modes. It is shown that approximately six POD modes are enough to capture the load dynamics on large temporal scales. Modeling the weighting coefficients as independent stochastic processes leads to similar load characteristics as in the case of the truncated POD. To complete this simplified wake description, we show evidence that the small-scale dynamics can be captured by adding to our model a homogeneous turbulent field. In this way, we present a procedure to derive stochastic wake models from costly computational fluid dynamics (CFD calculations or elaborated experimental investigations. These numerically efficient models provide the added value of possible long-term studies. Depending on the aspects of interest, different minimalized models may be obtained.
Influence of memory, attention, IQ and age on auditory temporal processing tests: preliminary study
Murphy, Cristina Ferraz Borges; Zachi, Elaine Cristina; Roque, Daniela Tsubota; Ventura, Dora Selma Fix; Schochat, Eliane
2014-01-01
PURPOSE: To investigate the existence of correlations between the performance of children in auditory temporal tests (Frequency Pattern and Gaps in Noise - GIN) and IQ, attention, memory and age measurements. METHOD: Fifteen typically developing individuals between the ages of 7 to 12 years and normal hearing participated in the study. Auditory temporal processing tests (GIN and Frequency Pattern), as well as a Memory test (Digit Span), Attention tests (auditory and visual modality) and ...
International Nuclear Information System (INIS)
Zwingelstein, Gilles; Thabet, Gabriel.
1977-01-01
Control algorithms for components of nuclear power plants are currently based on external diagnostic methods. Modeling and identification techniques for autoregressive moving average models (ARMA) for stochastic processes are described. The identified models provide a means of estimating the power spectral density with improved accuracy and computer time compared with the classical methods. They are particularly will suited for on-line estimation of the power spectral density. The observable stochastic process y (t) is modeled assuming that it is the output of a linear filter driven by Gaussian while noise w (t). Two identification schemes were tested to find the orders m and n of the ARMA (m,n) models and to estimate the parameters of the recursion equation relating the input and output signals. The first scheme consists in transforming the ARMA model to an autoregressive model. The parameters of this AR model are obtained using least squares estimation techniques. The second scheme consists in finding the parameters of the ARMA by nonlinear programming techniques. The power spectral density of y(t) is instantaneously deduced from these ARMA models [fr
International Nuclear Information System (INIS)
Do, Duy Minh; Gao, Wei; Song, Chongmin; Tangaramvong, Sawekchai
2014-01-01
This paper presents the non-deterministic dynamic analysis and reliability assessment of structures with uncertain-but-bounded parameters under stochastic process excitations. Random ground acceleration from earthquake motion is adopted to illustrate the stochastic process force. The exact change ranges of natural frequencies, random vibration displacement and stress responses of structures are investigated under the interval analysis framework. Formulations for structural reliability are developed considering the safe boundary and structural random vibration responses as interval parameters. An improved particle swarm optimization algorithm, namely randomised lower sequence initialized high-order nonlinear particle swarm optimization algorithm, is employed to capture the better bounds of structural dynamic characteristics, random vibration responses and reliability. Three numerical examples are used to demonstrate the presented method for interval random vibration analysis and reliability assessment of structures. The accuracy of the results obtained by the presented method is verified by the randomised Quasi-Monte Carlo simulation method (QMCSM) and direct Monte Carlo simulation method (MCSM). - Highlights: • Interval uncertainty is introduced into structural random vibration responses. • Interval dynamic reliability assessments of structures are implemented. • Boundaries of structural dynamic response and reliability are achieved
Human processing of short temporal intervals as revealed by an ERP waveform analysis
Directory of Open Access Journals (Sweden)
Yoshitaka eNakajima
2011-12-01
Full Text Available To clarify the time course over which the human brain processes information about durations up to ~300 ms, we reanalyzed the data that were previously reported by Mitsudo et al. (2009 using a multivariate analysis method. Event-related potentials were recorded from 19 scalp electrodes on 11 (9 original and 2 additional participants while they judged whether two neighboring empty time intervals—called t1 and t2 and marked by three tone bursts—had equal durations. There was also a control condition in which the participants were presented the same temporal patterns but without a judgment task. In the present reanalysis, we sought to visualize how the temporal patterns were represented in the brain over time. A correlation matrix across channels was calculated for each temporal pattern. Geometric separations between the correlation matrices were calculated, and subjected to multidimensional scaling. We performed such analyses for a moving 100-ms time window after the t1 presentations. In the windows centered at < 100 ms after the t2 presentation, the analyses revealed the local maxima of categorical separation between temporal patterns of perceptually equal durations versus perceptually unequal durations, both in the judgment condition and in the control condition. Such categorization of the temporal patterns was prominent only in narrow temporal regions. The analysis indicated that the participants determined whether the two neighboring time intervals were of equal duration mostly within 100 ms after the presentation of the temporal patterns. A very fast brain activity was related to the perception of elementary temporal patterns without explicit judgments. This is consistent with the findings of Mitsudo et al., and it is in line with the processing time hypothesis proposed by Nakajima et al. (2004. The validity of the correlation matrix analyses turned out to be an effective tool to grasp the overall responses of the brain to temporal
Liss, Alexander
Extreme weather events, such as heat waves and cold spells, cause substantial excess mortality and morbidity in the vulnerable elderly population, and cost billions of dollars. The accurate and reliable assessment of adverse effects of extreme weather events on human health is crucial for environmental scientists, economists, and public health officials to ensure proper protection of vulnerable populations and efficient allocation of scarce resources. However, the methodology for the analysis of large national databases is yet to be developed. The overarching objective of this dissertation is to examine the effect of extreme weather on the elderly population of the Conterminous US (ConUS) with respect to seasonality in temperature in different climatic regions by utilizing heterogeneous high frequency and spatio-temporal resolution data. To achieve these goals the author: 1) incorporated dissimilar stochastic high frequency big data streams and distinct data types into the integrated data base for use in analytical and decision support frameworks; 2) created an automated climate regionalization system based on remote sensing and machine learning to define climate regions for the Conterminous US; 3) systematically surveyed the current state of the art and identified existing gaps in the scientific knowledge; 4) assessed the dose-response relationship of exposure to temperature extremes on human health in relatively homogeneous climate regions using different statistical models, such as parametric and non-parametric, contemporaneous and asynchronous, applied to the same data; 5) assessed seasonal peak timing and synchronization delay of the exposure and the disease within the framework of contemporaneous high frequency harmonic time series analysis and modification of the effect by the regional climate; 6) modeled using hyperbolic functional form non-linear properties of the effect of exposure to extreme temperature on human health. The proposed climate
Levels of word processing and incidental memory: dissociable mechanisms in the temporal lobe.
Castillo, E M; Simos, P G; Davis, R N; Breier, J; Fitzgerald, M E; Papanicolaou, A C
2001-11-16
Word recall is facilitated when deep (e.g. semantic) processing is applied during encoding. This fact raises the question of the existence of specific brain mechanisms supporting different levels of information processing that can modulate incidental memory performance. In this study we obtained spatiotemporal brain activation profiles, using magnetic source imaging, from 10 adult volunteers as they performed a shallow (phonological) processing task and a deep (semantic) processing task. When phonological analysis of the word stimuli into their constituent phonemes was required, activation was largely restricted to the posterior portion of the left superior temporal gyrus (area 22). Conversely, when access to lexical/semantic representations was required, activation was found predominantly in the left middle temporal gyrus and medial temporal cortex. The differential engagement of each mechanism during word encoding was associated with dramatic changes in subsequent incidental memory performance.
Musical intervention enhances infants' neural processing of temporal structure in music and speech.
Zhao, T Christina; Kuhl, Patricia K
2016-05-10
Individuals with music training in early childhood show enhanced processing of musical sounds, an effect that generalizes to speech processing. However, the conclusions drawn from previous studies are limited due to the possible confounds of predisposition and other factors affecting musicians and nonmusicians. We used a randomized design to test the effects of a laboratory-controlled music intervention on young infants' neural processing of music and speech. Nine-month-old infants were randomly assigned to music (intervention) or play (control) activities for 12 sessions. The intervention targeted temporal structure learning using triple meter in music (e.g., waltz), which is difficult for infants, and it incorporated key characteristics of typical infant music classes to maximize learning (e.g., multimodal, social, and repetitive experiences). Controls had similar multimodal, social, repetitive play, but without music. Upon completion, infants' neural processing of temporal structure was tested in both music (tones in triple meter) and speech (foreign syllable structure). Infants' neural processing was quantified by the mismatch response (MMR) measured with a traditional oddball paradigm using magnetoencephalography (MEG). The intervention group exhibited significantly larger MMRs in response to music temporal structure violations in both auditory and prefrontal cortical regions. Identical results were obtained for temporal structure changes in speech. The intervention thus enhanced temporal structure processing not only in music, but also in speech, at 9 mo of age. We argue that the intervention enhanced infants' ability to extract temporal structure information and to predict future events in time, a skill affecting both music and speech processing.
Dynamic spatial organization of the occipito-temporal word form area for second language processing.
Gao, Yue; Sun, Yafeng; Lu, Chunming; Ding, Guosheng; Guo, Taomei; Malins, Jeffrey G; Booth, James R; Peng, Danling; Liu, Li
2017-08-01
Despite the left occipito-temporal region having shown consistent activation in visual word form processing across numerous studies in different languages, the mechanisms by which word forms of second languages are processed in this region remain unclear. To examine this more closely, 16 Chinese-English and 14 English-Chinese late bilinguals were recruited to perform lexical decision tasks to visually presented words in both their native and second languages (L1 and L2) during functional magnetic resonance imaging scanning. Here we demonstrate that visual word form processing for L1 versus L2 engaged different spatial areas of the left occipito-temporal region. Namely, the spatial organization of the visual word form processing in the left occipito-temporal region is more medial and posterior for L2 than L1 processing in Chinese-English bilinguals, whereas activation is more lateral and anterior for L2 in English-Chinese bilinguals. In addition, for Chinese-English bilinguals, more lateral recruitment of the occipito-temporal region was correlated with higher L2 proficiency, suggesting higher L2 proficiency is associated with greater involvement of L1-preferred mechanisms. For English-Chinese bilinguals, higher L2 proficiency was correlated with more lateral and anterior activation of the occipito-temporal region, suggesting higher L2 proficiency is associated with greater involvement of L2-preferred mechanisms. Taken together, our results indicate that L1 and L2 recruit spatially different areas of the occipito-temporal region in visual word processing when the two scripts belong to different writing systems, and that the spatial organization of this region for L2 visual word processing is dynamically modulated by L2 proficiency. Specifically, proficiency in L2 in Chinese-English is associated with assimilation to the native language mechanisms, whereas L2 in English-Chinese is associated with accommodation to second language mechanisms. Copyright © 2017
Stochastic quantization and gravity
International Nuclear Information System (INIS)
Rumpf, H.
1984-01-01
We give a preliminary account of the application of stochastic quantization to the gravitational field. We start in Section I from Nelson's formulation of quantum mechanics as Newtonian stochastic mechanics and only then introduce the Parisi-Wu stochastic quantization scheme on which all the later discussion will be based. In Section II we present a generalization of the scheme that is applicable to fields in physical (i.e. Lorentzian) space-time and treat the free linearized gravitational field in this manner. The most remarkable result of this is the noncausal propagation of conformal gravitons. Moreover the concept of stochastic gauge-fixing is introduced and a complete discussion of all the covariant gauges is given. A special symmetry relating two classes of covariant gauges is exhibited. Finally Section III contains some preliminary remarks on full nonlinear gravity. In particular we argue that in contrast to gauge fields the stochastic gravitational field cannot be transformed to a Gaussian process. (Author)
Lanchier, Nicolas
2017-01-01
Three coherent parts form the material covered in this text, portions of which have not been widely covered in traditional textbooks. In this coverage the reader is quickly introduced to several different topics enriched with 175 exercises which focus on real-world problems. Exercises range from the classics of probability theory to more exotic research-oriented problems based on numerical simulations. Intended for graduate students in mathematics and applied sciences, the text provides the tools and training needed to write and use programs for research purposes. The first part of the text begins with a brief review of measure theory and revisits the main concepts of probability theory, from random variables to the standard limit theorems. The second part covers traditional material on stochastic processes, including martingales, discrete-time Markov chains, Poisson processes, and continuous-time Markov chains. The theory developed is illustrated by a variety of examples surrounding applications such as the ...
Directory of Open Access Journals (Sweden)
Shilong Li
2018-03-01
Full Text Available In this paper, we introduce a class of stochastic interest model driven by a compoundPoisson process and a Brownian motion, in which the jumping times of force of interest obeyscompound Poisson process and the continuous tiny fluctuations are described by Brownian motion, andthe adjustment in each jump of interest force is assumed to be random. Based on the proposed interestmodel, we discuss the expected discounted function, the validity of the model and actuarial presentvalues of life annuities and life insurances under different parameters and distribution settings. Ournumerical results show actuarial values could be sensitive to the parameters and distribution settings,which shows the importance of introducing this kind interest model.
Campo, M. A.; Lopez, J. J.; Rebole, J. P.
2012-04-01
This work was carried out in north of Spain. San Sebastian A meteorological station, where there are available precipitation records every ten minutes was selected. Precipitation data covers from October of 1927 to September of 1997. Pulse models describe the temporal process of rainfall as a succession of rainy cells, main storm, whose origins are distributed in time according to a Poisson process and a secondary process that generates a random number of cells of rain within each storm. Among different pulse models, the Bartlett-Lewis was used. On the other hand, alternative renewal processes and Markov chains describe the way in which the process will evolve in the future depending only on the current state. Therefore they are nor dependant on past events. Two basic processes are considered when describing the occurrence of rain: the alternation of wet and dry periods and temporal distribution of rainfall in each rain event, which determines the rainwater collected in each of the intervals that make up the rain. This allows the introduction of alternative renewal processes and Markov chains of three states, where interstorm time is given by either of the two dry states, short or long. Thus, the stochastic model of Markov chains tries to reproduce the basis of pulse models: the succession of storms, each one composed for a series of rain, separated by a short interval of time without theoretical complexity of these. In a first step, we analyzed all variables involved in the sequential process of the rain: rain event duration, event duration of non-rain, average rainfall intensity in rain events, and finally, temporal distribution of rainfall within the rain event. Additionally, for pulse Bartlett-Lewis model calibration, main descriptive statistics were calculated for each month, considering the process of seasonal rainfall in each month. In a second step, both models were calibrated. Finally, synthetic series were simulated with calibration parameters; series
Temporal and speech processing skills in normal hearing individuals exposed to occupational noise.
Kumar, U Ajith; Ameenudin, Syed; Sangamanatha, A V
2012-01-01
Prolonged exposure to high levels of occupational noise can cause damage to hair cells in the cochlea and result in permanent noise-induced cochlear hearing loss. Consequences of cochlear hearing loss on speech perception and psychophysical abilities have been well documented. Primary goal of this research was to explore temporal processing and speech perception Skills in individuals who are exposed to occupational noise of more than 80 dBA and not yet incurred clinically significant threshold shifts. Contribution of temporal processing skills to speech perception in adverse listening situation was also evaluated. A total of 118 participants took part in this research. Participants comprised three groups of train drivers in the age range of 30-40 (n= 13), 41 50 ( = 13), 41-50 (n = 9), and 51-60 (n = 6) years and their non-noise-exposed counterparts (n = 30 in each age group). Participants of all the groups including the train drivers had hearing sensitivity within 25 dB HL in the octave frequencies between 250 and 8 kHz. Temporal processing was evaluated using gap detection, modulation detection, and duration pattern tests. Speech recognition was tested in presence multi-talker babble at -5dB SNR. Differences between experimental and control groups were analyzed using ANOVA and independent sample t-tests. Results showed a trend of reduced temporal processing skills in individuals with noise exposure. These deficits were observed despite normal peripheral hearing sensitivity. Speech recognition scores in the presence of noise were also significantly poor in noise-exposed group. Furthermore, poor temporal processing skills partially accounted for the speech recognition difficulties exhibited by the noise-exposed individuals. These results suggest that noise can cause significant distortions in the processing of suprathreshold temporal cues which may add to difficulties in hearing in adverse listening conditions.
Temporal and speech processing skills in normal hearing individuals exposed to occupational noise
Directory of Open Access Journals (Sweden)
U Ajith Kumar
2012-01-01
Full Text Available Prolonged exposure to high levels of occupational noise can cause damage to hair cells in the cochlea and result in permanent noise-induced cochlear hearing loss. Consequences of cochlear hearing loss on speech perception and psychophysical abilities have been well documented. Primary goal of this research was to explore temporal processing and speech perception Skills in individuals who are exposed to occupational noise of more than 80 dBA and not yet incurred clinically significant threshold shifts. Contribution of temporal processing skills to speech perception in adverse listening situation was also evaluated. A total of 118 participants took part in this research. Participants comprised three groups of train drivers in the age range of 30-40 (n= 13, 41 50 ( = 13, 41-50 (n = 9, and 51-60 (n = 6 years and their non-noise-exposed counterparts (n = 30 in each age group. Participants of all the groups including the train drivers had hearing sensitivity within 25 dB HL in the octave frequencies between 250 and 8 kHz. Temporal processing was evaluated using gap detection, modulation detection, and duration pattern tests. Speech recognition was tested in presence multi-talker babble at -5dB SNR. Differences between experimental and control groups were analyzed using ANOVA and independent sample t-tests. Results showed a trend of reduced temporal processing skills in individuals with noise exposure. These deficits were observed despite normal peripheral hearing sensitivity. Speech recognition scores in the presence of noise were also significantly poor in noise-exposed group. Furthermore, poor temporal processing skills partially accounted for the speech recognition difficulties exhibited by the noise-exposed individuals. These results suggest that noise can cause significant distortions in the processing of suprathreshold temporal cues which may add to difficulties in hearing in adverse listening conditions.
Ahmet, Kara
2015-01-01
This paper presents a simple model of the provision of higher educational services that considers and exemplifies nonlinear, stochastic, and potentially chaotic processes. I use the methods of system dynamics to simulate these processes in the context of a particular sociologically interesting case, namely that of the Turkish higher education…
Temporal information processing in short- and long-term memory of patients with schizophrenia.
Landgraf, Steffen; Steingen, Joerg; Eppert, Yvonne; Niedermeyer, Ulrich; van der Meer, Elke; Krueger, Frank
2011-01-01
Cognitive deficits of patients with schizophrenia have been largely recognized as core symptoms of the disorder. One neglected factor that contributes to these deficits is the comprehension of time. In the present study, we assessed temporal information processing and manipulation from short- and long-term memory in 34 patients with chronic schizophrenia and 34 matched healthy controls. On the short-term memory temporal-order reconstruction task, an incidental or intentional learning strategy was deployed. Patients showed worse overall performance than healthy controls. The intentional learning strategy led to dissociable performance improvement in both groups. Whereas healthy controls improved on a performance measure (serial organization), patients improved on an error measure (inappropriate semantic clustering) when using the intentional instead of the incidental learning strategy. On the long-term memory script-generation task, routine and non-routine events of everyday activities (e.g., buying groceries) had to be generated in either chronological or inverted temporal order. Patients were slower than controls at generating events in the chronological routine condition only. They also committed more sequencing and boundary errors in the inverted conditions. The number of irrelevant events was higher in patients in the chronological, non-routine condition. These results suggest that patients with schizophrenia imprecisely access temporal information from short- and long-term memory. In short-term memory, processing of temporal information led to a reduction in errors rather than, as was the case in healthy controls, to an improvement in temporal-order recall. When accessing temporal information from long-term memory, patients were slower and committed more sequencing, boundary, and intrusion errors. Together, these results suggest that time information can be accessed and processed only imprecisely by patients who provide evidence for impaired time comprehension
Spatio-temporal models of mental processes from fMRI.
Janoos, Firdaus; Machiraju, Raghu; Singh, Shantanu; Morocz, Istvan Ákos
2011-07-15
Understanding the highly complex, spatially distributed and temporally organized phenomena entailed by mental processes using functional MRI is an important research problem in cognitive and clinical neuroscience. Conventional analysis methods focus on the spatial dimension of the data discarding the information about brain function contained in the temporal dimension. This paper presents a fully spatio-temporal multivariate analysis method using a state-space model (SSM) for brain function that yields not only spatial maps of activity but also its temporal structure along with spatially varying estimates of the hemodynamic response. Efficient algorithms for estimating the parameters along with quantitative validations are given. A novel low-dimensional feature-space for representing the data, based on a formal definition of functional similarity, is derived. Quantitative validation of the model and the estimation algorithms is provided with a simulation study. Using a real fMRI study for mental arithmetic, the ability of this neurophysiologically inspired model to represent the spatio-temporal information corresponding to mental processes is demonstrated. Moreover, by comparing the models across multiple subjects, natural patterns in mental processes organized according to different mental abilities are revealed. Copyright © 2011 Elsevier Inc. All rights reserved.
Research of Cadastral Data Modelling and Database Updating Based on Spatio-temporal Process
Directory of Open Access Journals (Sweden)
ZHANG Feng
2016-02-01
Full Text Available The core of modern cadastre management is to renew the cadastre database and keep its currentness,topology consistency and integrity.This paper analyzed the changes and their linkage of various cadastral objects in the update process.Combined object-oriented modeling technique with spatio-temporal objects' evolution express,the paper proposed a cadastral data updating model based on the spatio-temporal process according to people's thought.Change rules based on the spatio-temporal topological relations of evolution cadastral spatio-temporal objects are drafted and further more cascade updating and history back trace of cadastral features,land use and buildings are realized.This model implemented in cadastral management system-ReGIS.Achieved cascade changes are triggered by the direct driving force or perceived external events.The system records spatio-temporal objects' evolution process to facilitate the reconstruction of history,change tracking,analysis and forecasting future changes.
Bedoin, Nathalie; Brisseau, Lucie; Molinier, Pauline; Roch, Didier; Tillmann, Barbara
2016-01-01
Children with developmental language disorders have been shown to be also impaired in rhythm and meter perception. Temporal processing and its link to language processing can be understood within the dynamic attending theory. An external stimulus can stimulate internal oscillators, which orient attention over time and drive speech signal segmentation to provide benefits for syntax processing, which is impaired in various patient populations. For children with Specific Language Impairment (SLI) and dyslexia, previous research has shown the influence of an external rhythmic stimulation on subsequent language processing by comparing the influence of a temporally regular musical prime to that of a temporally irregular prime. Here we tested whether the observed rhythmic stimulation effect is indeed due to a benefit provided by the regular musical prime (rather than a cost subsequent to the temporally irregular prime). Sixteen children with SLI and 16 age-matched controls listened to either a regular musical prime sequence or an environmental sound scene (without temporal regularities in event occurrence; i.e., referred to as "baseline condition") followed by grammatically correct and incorrect sentences. They were required to perform grammaticality judgments for each auditorily presented sentence. Results revealed that performance for the grammaticality judgments was better after the regular prime sequences than after the baseline sequences. Our findings are interpreted in the theoretical framework of the dynamic attending theory (Jones, 1976) and the temporal sampling (oscillatory) framework for developmental language disorders (Goswami, 2011). Furthermore, they encourage the use of rhythmic structures (even in non-verbal materials) to boost linguistic structure processing and outline perspectives for rehabilitation.
International Nuclear Information System (INIS)
Biyajima, M.
1984-01-01
Stochastic backgrounds of the KNO scaling functions given by Buras and Koba and by Barshay and Yamaguchi are investigated. It is found that they are connected with the stochastic Rayleigh process, and the (1+2)- and (1+4)-dimensional Ornstein-Uhlenbeck process. Moreover those KNO scaling functions are transformed into the KNO scaling functions given by the Perina-McGill formula in terms of a nonlinear transformation. Analyses of data by means of them are made. Probability distributions of the former KNO scaling functions are also calculated by the Poisson transformation. (orig.)
Adepeju, M.; Rosser, G.; Cheng, T.
2016-01-01
Many physical and sociological processes are represented as discrete events in time and space. These spatio-temporal point processes are often sparse, meaning that they cannot be aggregated and treated with conventional regression models. Models based on the point process framework may be employed instead for prediction purposes. Evaluating the predictive performance of these models poses a unique challenge, as the same sparseness prevents the use of popular measures such as the root mean squ...
Modeling bias and variation in the stochastic processes of small RNA sequencing.
Argyropoulos, Christos; Etheridge, Alton; Sakhanenko, Nikita; Galas, David
2017-06-20
The use of RNA-seq as the preferred method for the discovery and validation of small RNA biomarkers has been hindered by high quantitative variability and biased sequence counts. In this paper we develop a statistical model for sequence counts that accounts for ligase bias and stochastic variation in sequence counts. This model implies a linear quadratic relation between the mean and variance of sequence counts. Using a large number of sequencing datasets, we demonstrate how one can use the generalized additive models for location, scale and shape (GAMLSS) distributional regression framework to calculate and apply empirical correction factors for ligase bias. Bias correction could remove more than 40% of the bias for miRNAs. Empirical bias correction factors appear to be nearly constant over at least one and up to four orders of magnitude of total RNA input and independent of sample composition. Using synthetic mixes of known composition, we show that the GAMLSS approach can analyze differential expression with greater accuracy, higher sensitivity and specificity than six existing algorithms (DESeq2, edgeR, EBSeq, limma, DSS, voom) for the analysis of small RNA-seq data. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
Syahidatul Ayuni Mazlan, Mazma; Rosli, Norhayati; Jauhari Arief Ichwan, Solachuddin; Suhaity Azmi, Nina
2017-09-01
A stochastic model is introduced to describe the growth of cancer affected by anti-cancer therapeutics of Chondroitin Sulfate (CS). The parameters values of the stochastic model are estimated via maximum likelihood function. The numerical method of Euler-Maruyama will be employed to solve the model numerically. The efficiency of the stochastic model is measured by comparing the simulated result with the experimental data.
Kuwahara, Jun; Miyata, Hajime; Konno, Hidetoshi
2017-09-01
Recently, complex dynamics of globally coupled oscillators have been attracting many researcher's attentions. In spite of their numerous studies, their features of nonlinear oscillator systems with global and local couplings in two-dimension (2D) are not understood fully. The paper focuses on 2D states of coherent, clustered and chaotic oscillation especially under the effect of negative global coupling (NGC) in 2D Alief-Panfilov model. It is found that the tuning NGC can cause various new coupling-parameter dependency on the features of oscillations. Then quantitative characterization of various states of oscillations (so called spiral wave turbulence) is examined by using the pragmatic information (PI) which have been utilized in analyzing multimode laser, solar activity and neuronal systems. It is demonstrated that the dynamics of the PI for various oscillations can be characterized successfully by the Hyper-Gamma stochastic process.
Kaulakys, B.; Alaburda, M.; Ruseckas, J.
2016-05-01
A well-known fact in the financial markets is the so-called ‘inverse cubic law’ of the cumulative distributions of the long-range memory fluctuations of market indicators such as a number of events of trades, trading volume and the logarithmic price change. We propose the nonlinear stochastic differential equation (SDE) giving both the power-law behavior of the power spectral density and the long-range dependent inverse cubic law of the cumulative distribution. This is achieved using the suggestion that when the market evolves from calm to violent behavior there is a decrease of the delay time of multiplicative feedback of the system in comparison to the driving noise correlation time. This results in a transition from the Itô to the Stratonovich sense of the SDE and yields a long-range memory process.
Sequential stochastic optimization
Cairoli, Renzo
1996-01-01
Sequential Stochastic Optimization provides mathematicians and applied researchers with a well-developed framework in which stochastic optimization problems can be formulated and solved. Offering much material that is either new or has never before appeared in book form, it lucidly presents a unified theory of optimal stopping and optimal sequential control of stochastic processes. This book has been carefully organized so that little prior knowledge of the subject is assumed; its only prerequisites are a standard graduate course in probability theory and some familiarity with discrete-paramet
Stochastic resonance and coherence resonance in groundwater-dependent plant ecosystems.
Borgogno, Fabio; D'Odorico, Paolo; Laio, Francesco; Ridolfi, Luca
2012-01-21
Several studies have shown that non-linear deterministic dynamical systems forced by external random components can give rise to unexpectedly regular temporal behaviors. Stochastic resonance and coherence resonance, the two best known processes of this type, have been studied in a number of physical and chemical systems. Here, we explore their possible occurrence in the dynamics of groundwater-dependent plant ecosystems. To this end, we develop two eco-hydrological models, which allow us to demonstrate that stochastic and coherence resonance may emerge in the dynamics of phreatophyte vegetation, depending on their deterministic properties and the intensity of external stochastic drivers. Copyright © 2011 Elsevier Ltd. All rights reserved.
Temporally selective attention supports speech processing in 3- to 5-year-old children.
Astheimer, Lori B; Sanders, Lisa D
2012-01-01
Recent event-related potential (ERP) evidence demonstrates that adults employ temporally selective attention to preferentially process the initial portions of words in continuous speech. Doing so is an effective listening strategy since word-initial segments are highly informative. Although the development of this process remains unexplored, directing attention to word onsets may be important for speech processing in young children who would otherwise be overwhelmed by the rapidly changing acoustic signals that constitute speech. We examined the use of temporally selective attention in 3- to 5-year-old children listening to stories by comparing ERPs elicited by attention probes presented at four acoustically matched times relative to word onsets: concurrently with a word onset, 100 ms before, 100 ms after, and at random control times. By 80 ms, probes presented at and after word onsets elicited a larger negativity than probes presented before word onsets or at control times. The latency and distribution of this effect is similar to temporally and spatially selective attention effects measured in adults and, despite differences in polarity, spatially selective attention effects measured in children. These results indicate that, like adults, preschool aged children modulate temporally selective attention to preferentially process the initial portions of words in continuous speech. Copyright © 2011 Elsevier Ltd. All rights reserved.
The neural basis of temporal order processing in past and future thought.
D'Argembeau, Arnaud; Jeunehomme, Olivier; Majerus, Steve; Bastin, Christine; Salmon, Eric
2015-01-01
Although growing evidence has shown that remembering the past and imagining the future recruit a common core network of frontal-parietal-temporal regions, the extent to which these regions contribute to the temporal dimension of autobiographical thought remains unclear. In this fMRI study, we focused on the event-sequencing aspect of time and examined whether ordering past and future events involve common neural substrates. Participants had to determine which of two past (or future) events occurred (or would occur) before the other, and these order judgments were compared with a task requiring to think about the content of the same past or future events. For both past and future events, we found that the left posterior hippocampus was more activated when establishing the order of events, whereas the anterior hippocampus was more activated when representing their content. Aside from the hippocampus, most of the brain regions that were activated when thinking about temporal order (notably the intraparietal sulcus, dorsolateral pFC, dorsal anterior cingulate, and visual cortex) lied outside the core network and may reflect the involvement of controlled processes and visuospatial imagery to locate events in time. Collectively, these findings suggest (a) that the same processing operations are engaged for ordering past events and planned future events in time, (b) that anterior and posterior portions of the hippocampus are involved in processing different aspects of autobiographical thought, and (c) that temporal order is not necessarily an intrinsic property of memory or future thought but instead requires additional, controlled processes.
Auditory Temporal Processing and Working Memory: Two Independent Deficits for Dyslexia
Fostick, Leah; Bar-El, Sharona; Ram-Tsur, Ronit
2012-01-01
Dyslexia is a neuro-cognitive disorder with a strong genetic basis, characterized by a difficulty in acquiring reading skills. Several hypotheses have been suggested in an attempt to explain the origin of dyslexia, among which some have suggested that dyslexic readers might have a deficit in auditory temporal processing, while others hypothesized…
Face processing regions are sensitive to distinct aspects of temporal sequence in facial dynamics.
Reinl, Maren; Bartels, Andreas
2014-11-15
Facial movement conveys important information for social interactions, yet its neural processing is poorly understood. Computational models propose that shape- and temporal sequence sensitive mechanisms interact in processing dynamic faces. While face processing regions are known to respond to facial movement, their sensitivity to particular temporal sequences has barely been studied. Here we used fMRI to examine the sensitivity of human face-processing regions to two aspects of directionality in facial movement trajectories. We presented genuine movie recordings of increasing and decreasing fear expressions, each of which were played in natural or reversed frame order. This two-by-two factorial design matched low-level visual properties, static content and motion energy within each factor, emotion-direction (increasing or decreasing emotion) and timeline (natural versus artificial). The results showed sensitivity for emotion-direction in FFA, which was timeline-dependent as it only occurred within the natural frame order, and sensitivity to timeline in the STS, which was emotion-direction-dependent as it only occurred for decreased fear. The occipital face area (OFA) was sensitive to the factor timeline. These findings reveal interacting temporal sequence sensitive mechanisms that are responsive to both ecological meaning and to prototypical unfolding of facial dynamics. These mechanisms are temporally directional, provide socially relevant information regarding emotional state or naturalness of behavior, and agree with predictions from modeling and predictive coding theory. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
DEFF Research Database (Denmark)
Møller, Jesper; Diaz-Avalos, Carlos
Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable fo...... dataset consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent....
Aggressive osteoblastoma in mastoid process of temporal bone with facial palsy
Directory of Open Access Journals (Sweden)
Manoj Jain
2013-01-01
Full Text Available Osteoblastoma is an uncommon primary bone tumor with a predilection for posterior elements of spine. Its occurrence in temporal bone and middle ear is extremely rare. Clinical symptoms are non-specific and cranial nerve involvement is uncommon. The cytomorphological features of osteoblastoma are not very well defined and the experience is limited to only few reports. We report an interesting and rare case of aggressive osteoblastoma, with progressive hearing loss and facial palsy, involving the mastoid process of temporal bone and middle ear along with the description of cyto-morphological features.
Musical intervention enhances infants’ neural processing of temporal structure in music and speech
Zhao, T. Christina; Kuhl, Patricia K.
2016-01-01
Musicians show enhanced musical pitch and meter processing, effects that generalize to speech. Yet potential differences between musicians and nonmusicians limit conclusions. We examined the effects of a randomized laboratory-controlled music intervention on music and speech processing in 9-mo-old infants. The Intervention exposed infants to music in triple meter (the waltz) in a social environment. Controls engaged in similar social play without music. After 12 sessions, infants’ temporal in...
Asghari, Mohammad H; Park, Yongwoo; Azaña, José
2011-01-17
We propose and experimentally prove a novel design for implementing photonic temporal integrators simultaneously offering a high processing bandwidth and a long operation time window, namely a large time-bandwidth product. The proposed scheme is based on concatenating in series a time-limited ultrafast photonic temporal integrator, e.g. implemented using a fiber Bragg grating (FBG), with a discrete-time (bandwidth limited) optical integrator, e.g. implemented using an optical resonant cavity. This design combines the advantages of these two previously demonstrated photonic integrator solutions, providing a processing speed as high as that of the time-limited ultrafast integrator and an operation time window fixed by the discrete-time integrator. Proof-of-concept experiments are reported using a uniform fiber Bragg grating (as the original time-limited integrator) connected in series with a bulk-optics coherent interferometers' system (as a passive 4-points discrete-time photonic temporal integrator). Using this setup, we demonstrate accurate temporal integration of complex-field optical signals with time-features as fast as ~6 ps, only limited by the processing bandwidth of the FBG integrator, over time durations as long as ~200 ps, which represents a 4-fold improvement over the operation time window (~50 ps) of the original FBG integrator.
The right hemisphere's contribution to discourse processing: A study in temporal lobe epilepsy.
Lomlomdjian, Carolina; Múnera, Claudia P; Low, Daniel M; Terpiluk, Verónica; Solís, Patricia; Abusamra, Valeria; Kochen, Silvia
2017-08-01
Discourse skills - in which the right hemisphere has an important role - enables verbal communication by selecting contextually relevant information and integrating it coherently to infer the correct meaning. However, language research in epilepsy has focused on single word analysis related mainly to left hemisphere processing. The purpose of this study was to investigate discourse abilities in patients with right lateralized medial temporal lobe epilepsy (RTLE) by comparing their performance to that of patients with left temporal lobe epilepsy (LTLE). 74 pharmacoresistant temporal lobe epilepsy (TLE) patients were evaluated: 34 with RTLE and 40 with LTLE. Subjects underwent a battery of tests that measure comprehension and production of conversational and narrative discourse. Disease related variables and general neuropsychological data were evaluated. The RTLE group presented deficits in interictal conversational and narrative discourse, with a disintegrated speech, lack of categorization and misinterpretation of social meaning. LTLE group, on the other hand, showed a tendency to lower performance in logical-temporal sequencing. RTLE patients showed discourse deficits which have been described in right hemisphere damaged patients due to other etiologies. Medial and anterior temporal lobe structures appear to link semantic, world knowledge, and social cognition associated areas to construct a contextually related coherent meaning. Copyright © 2017 Elsevier Inc. All rights reserved.
Ramseyer, Fabian; Kupper, Zeno; Caspar, Franz; Znoj, Hansjörg; Tschacher, Wolfgang
2014-10-01
Processes occurring in the course of psychotherapy are characterized by the simple fact that they unfold in time and that the multiple factors engaged in change processes vary highly between individuals (idiographic phenomena). Previous research, however, has neglected the temporal perspective by its traditional focus on static phenomena, which were mainly assessed at the group level (nomothetic phenomena). To support a temporal approach, the authors introduce time-series panel analysis (TSPA), a statistical methodology explicitly focusing on the quantification of temporal, session-to-session aspects of change in psychotherapy. TSPA-models are initially built at the level of individuals and are subsequently aggregated at the group level, thus allowing the exploration of prototypical models. TSPA is based on vector auto-regression (VAR), an extension of univariate auto-regression models to multivariate time-series data. The application of TSPA is demonstrated in a sample of 87 outpatient psychotherapy patients who were monitored by postsession questionnaires. Prototypical mechanisms of change were derived from the aggregation of individual multivariate models of psychotherapy process. In a 2nd step, the associations between mechanisms of change (TSPA) and pre- to postsymptom change were explored. TSPA allowed a prototypical process pattern to be identified, where patient's alliance and self-efficacy were linked by a temporal feedback-loop. Furthermore, therapist's stability over time in both mastery and clarification interventions was positively associated with better outcomes. TSPA is a statistical tool that sheds new light on temporal mechanisms of change. Through this approach, clinicians may gain insight into prototypical patterns of change in psychotherapy. PsycINFO Database Record (c) 2014 APA, all rights reserved.
Stochastic reaction-diffusion algorithms for macromolecular crowding
Sturrock, Marc
2016-06-01
Compartment-based (lattice-based) reaction-diffusion algorithms are often used for studying complex stochastic spatio-temporal processes inside cells. In this paper the influence of macromolecular crowding on stochastic reaction-diffusion simulations is investigated. Reaction-diffusion processes are considered on two different kinds of compartmental lattice, a cubic lattice and a hexagonal close packed lattice, and solved using two different algorithms, the stochastic simulation algorithm and the spatiocyte algorithm (Arjunan and Tomita 2010 Syst. Synth. Biol. 4, 35-53). Obstacles (modelling macromolecular crowding) are shown to have substantial effects on the mean squared displacement and average number of molecules in the domain but the nature of these effects is dependent on the choice of lattice, with the cubic lattice being more susceptible to the effects of the obstacles. Finally, improvements for both algorithms are presented.
Bouchaud, Jean-Philippe; Sornette, Didier
1994-06-01
The ability to price risks and devise optimal investment strategies in thé présence of an uncertain "random" market is thé cornerstone of modern finance theory. We first consider thé simplest such problem of a so-called "European call option" initially solved by Black and Scholes using Ito stochastic calculus for markets modelled by a log-Brownien stochastic process. A simple and powerful formalism is presented which allows us to generalize thé analysis to a large class of stochastic processes, such as ARCH, jump or Lévy processes. We also address thé case of correlated Gaussian processes, which is shown to be a good description of three différent market indices (MATIF, CAC40, FTSE100). Our main result is thé introduction of thé concept of an optimal strategy in the sense of (functional) minimization of the risk with respect to the portfolio. If the risk may be made to vanish for particular continuous uncorrelated 'quasiGaussian' stochastic processes (including Black and Scholes model), this is no longer the case for more general stochastic processes. The value of the residual risk is obtained and suggests the concept of risk-corrected option prices. In the presence of very large deviations such as in Lévy processes, new criteria for rational fixing of the option prices are discussed. We also apply our method to other types of options, `Asian', `American', and discuss new possibilities (`doubledecker'...). The inclusion of transaction costs leads to the appearance of a natural characteristic trading time scale. L'aptitude à quantifier le coût du risque et à définir une stratégie optimale de gestion de portefeuille dans un marché aléatoire constitue la base de la théorie moderne de la finance. Nous considérons d'abord le problème le plus simple de ce type, à savoir celui de l'option d'achat `européenne', qui a été résolu par Black et Scholes à l'aide du calcul stochastique d'Ito appliqué aux marchés modélisés par un processus Log
Segregation of Brain Structural Networks Supports Spatio-Temporal Predictive Processing
Directory of Open Access Journals (Sweden)
Valentina Ciullo
2018-05-01
explicit and implicit temporal orienting processes was considered at the long interval, we found that explicit processes were related to centrality measures of the bilateral inferior parietal lobule. Degree centrality of the same region in the left hemisphere covaried with behavioral measures indexing the process of attentional re-orienting. These results represent a crucial step forward the ordinary predictive processing description, as we identified the patterns of connectivity characterizing the brain organization associated with the ability to generate and update temporal expectancies in case of contextual violations.
Segregation of Brain Structural Networks Supports Spatio-Temporal Predictive Processing.
Ciullo, Valentina; Vecchio, Daniela; Gili, Tommaso; Spalletta, Gianfranco; Piras, Federica
2018-01-01
implicit temporal orienting processes was considered at the long interval, we found that explicit processes were related to centrality measures of the bilateral inferior parietal lobule. Degree centrality of the same region in the left hemisphere covaried with behavioral measures indexing the process of attentional re-orienting. These results represent a crucial step forward the ordinary predictive processing description, as we identified the patterns of connectivity characterizing the brain organization associated with the ability to generate and update temporal expectancies in case of contextual violations.
Auditory temporal-order processing of vowel sequences by young and elderly listeners.
Fogerty, Daniel; Humes, Larry E; Kewley-Port, Diane
2010-04-01
This project focused on the individual differences underlying observed variability in temporal processing among older listeners. Four measures of vowel temporal-order identification were completed by young (N=35; 18-31 years) and older (N=151; 60-88 years) listeners. Experiments used forced-choice, constant-stimuli methods to determine the smallest stimulus onset asynchrony (SOA) between brief (40 or 70 ms) vowels that enabled identification of a stimulus sequence. Four words (pit, pet, pot, and put) spoken by a male talker were processed to serve as vowel stimuli. All listeners identified the vowels in isolation with better than 90% accuracy. Vowel temporal-order tasks included the following: (1) monaural two-item identification, (2) monaural four-item identification, (3) dichotic two-item vowel identification, and (4) dichotic two-item ear identification. Results indicated that older listeners had more variability and performed poorer than young listeners on vowel-identification tasks, although a large overlap in distributions was observed. Both age groups performed similarly on the dichotic ear-identification task. For both groups, the monaural four-item and dichotic two-item tasks were significantly harder than the monaural two-item task. Older listeners' SOA thresholds improved with additional stimulus exposure and shorter dichotic stimulus durations. Individual differences of temporal-order performance among the older listeners demonstrated the influence of cognitive measures, but not audibility or age.
Temporal processing and long-latency auditory evoked potential in stutterers.
Prestes, Raquel; de Andrade, Adriana Neves; Santos, Renata Beatriz Fernandes; Marangoni, Andrea Tortosa; Schiefer, Ana Maria; Gil, Daniela
Stuttering is a speech fluency disorder, and may be associated with neuroaudiological factors linked to central auditory processing, including changes in auditory processing skills and temporal resolution. To characterize the temporal processing and long-latency auditory evoked potential in stutterers and to compare them with non-stutterers. The study included 41 right-handed subjects, aged 18-46 years, divided into two groups: stutterers (n=20) and non-stutters (n=21), compared according to age, education, and sex. All subjects were submitted to the duration pattern tests, random gap detection test, and long-latency auditory evoked potential. Individuals who stutter showed poorer performance on Duration Pattern and Random Gap Detection tests when compared with fluent individuals. In the long-latency auditory evoked potential, there was a difference in the latency of N2 and P3 components; stutterers had higher latency values. Stutterers have poor performance in temporal processing and higher latency values for N2 and P3 components. Copyright © 2017 Associação Brasileira de Otorrinolaringologia e Cirurgia Cérvico-Facial. Published by Elsevier Editora Ltda. All rights reserved.
Temporal processing and long-latency auditory evoked potential in stutterers
Directory of Open Access Journals (Sweden)
Raquel Prestes
Full Text Available Abstract Introduction: Stuttering is a speech fluency disorder, and may be associated with neuroaudiological factors linked to central auditory processing, including changes in auditory processing skills and temporal resolution. Objective: To characterize the temporal processing and long-latency auditory evoked potential in stutterers and to compare them with non-stutterers. Methods: The study included 41 right-handed subjects, aged 18-46 years, divided into two groups: stutterers (n = 20 and non-stutters (n = 21, compared according to age, education, and sex. All subjects were submitted to the duration pattern tests, random gap detection test, and long-latency auditory evoked potential. Results: Individuals who stutter showed poorer performance on Duration Pattern and Random Gap Detection tests when compared with fluent individuals. In the long-latency auditory evoked potential, there was a difference in the latency of N2 and P3 components; stutterers had higher latency values. Conclusion: Stutterers have poor performance in temporal processing and higher latency values for N2 and P3 components.
Papalexiou, Simon Michael
2018-05-01
Hydroclimatic processes come in all "shapes and sizes". They are characterized by different spatiotemporal correlation structures and probability distributions that can be continuous, mixed-type, discrete or even binary. Simulating such processes by reproducing precisely their marginal distribution and linear correlation structure, including features like intermittency, can greatly improve hydrological analysis and design. Traditionally, modelling schemes are case specific and typically attempt to preserve few statistical moments providing inadequate and potentially risky distribution approximations. Here, a single framework is proposed that unifies, extends, and improves a general-purpose modelling strategy, based on the assumption that any process can emerge by transforming a specific "parent" Gaussian process. A novel mathematical representation of this scheme, introducing parametric correlation transformation functions, enables straightforward estimation of the parent-Gaussian process yielding the target process after the marginal back transformation, while it provides a general description that supersedes previous specific parameterizations, offering a simple, fast and efficient simulation procedure for every stationary process at any spatiotemporal scale. This framework, also applicable for cyclostationary and multivariate modelling, is augmented with flexible parametric correlation structures that parsimoniously describe observed correlations. Real-world simulations of various hydroclimatic processes with different correlation structures and marginals, such as precipitation, river discharge, wind speed, humidity, extreme events per year, etc., as well as a multivariate example, highlight the flexibility, advantages, and complete generality of the method.
A software framework for process flow execution of stochastic multi-scale integrated models
Schmitz, Oliver; de Kok, Jean Luc; Karssenberg, Derek
2016-01-01
Dynamic environmental models use a state transition function, external inputs and parameters to simulate the change of real-world processes over time. Modellers specify the state transition function and the external inputs required in the process calculation of each time step in a component model, a
DEFF Research Database (Denmark)
E. Barndorff-Nielsen, Ole; Benth, Fred Espen; Szozda, Benedykt
This paper generalizes the integration theory for volatility modulated Brownian-driven Volterra processes onto the space G* of Potthoff-Timpel distributions. Sufficient conditions for integrability of generalized processes are given, regularity results and properties of the integral are discussed...
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole E.; Benth, Fred Espen; Szozda, Benedykt
This paper generalizes the integration theory for volatility modulated Brownian-driven Volterra processes onto the space G∗ of Potthoff--Timpel distributions. Sufficient conditions for integrability of generalized processes are given, regularity results and properties of the integral are discusse...
Directory of Open Access Journals (Sweden)
Svetlana Strbac Savic
2015-01-01
Full Text Available Forecasting the operational efficiency of an existing underground mine plays an important role in strategic planning of production. Degree of Operating Leverage (DOL is used to express the operational efficiency of production. The forecasting model should be able to involve common time horizon, taking the characteristics of the input variables that directly affect the value of DOL. Changes in the magnitude of any input variable change the value of DOL. To establish the relationship describing the way of changing we applied multivariable grey modeling. Established time sequence multivariable response formula is also used to forecast the future values of operating leverage. Operational efficiency of production is often associated with diverse sources of uncertainties. Incorporation of these uncertainties into multivariable forecasting model enables mining company to survive in today’s competitive environment. Simulation of mean reversion process and geometric Brownian motion is used to describe the stochastic diffusion nature of metal price, as a key element of revenues, and production costs, respectively. By simulating a forecasting model, we imitate its action in order to measure its response to different inputs. The final result of simulation process is the expected value of DOL for every year of defined time horizon.
Processing of Words and Faces by Patients with Left and Right Temporal Lobe Epilepsy
Directory of Open Access Journals (Sweden)
Andrew W. Ellis
1991-01-01
Full Text Available Tests of word and face processing were given to patients with complex partial epilepsy focussed on the left or right temporal lobe, and to non-epileptic control subjects. The left TLE group showed the greatest impairment on object naming and on reading tests, but the right TLE group also showed a lesser impairment relative to the normal control subjects on both tests. The right TLE group was selectively impaired on distinguishing famous from non-famous faces while the left TLE group was impaired at naming famous faces they had successfully recognized as familiar. There was no significant difference between the three groups on recognition memory for words. The implications of the results for theories of the role of the temporal lobes in word and face processing, and the possible neural mechanisms responsible for the deficits in TLE patients, are discussed.
Thermal mixtures in stochastic mechanics
Energy Technology Data Exchange (ETDEWEB)
Guerra, F [Rome Univ. (Italy). Ist. di Matematica; Loffredo, M I [Salerno Univ. (Italy). Ist. di Fisica
1981-01-17
Stochastic mechanics is extended to systems in thermal equilibrium. The resulting stochastic processes are mixtures of Nelson processes. Their Markov property is investigated in some simple cases. It is found that in order to inforce Markov property the algebra of observable associated to the present must be suitably enlarged.
Stochastic Pi-calculus Revisited
DEFF Research Database (Denmark)
Cardelli, Luca; Mardare, Radu Iulian
2013-01-01
We develop a version of stochastic Pi-calculus with a semantics based on measure theory. We dene the behaviour of a process in a rate environment using measures over the measurable space of processes induced by structural congruence. We extend the stochastic bisimulation to include the concept of...
Tournaire, O.; Paparoditis, N.
Road detection has been a topic of great interest in the photogrammetric and remote sensing communities since the end of the 70s. Many approaches dealing with various sensor resolutions, the nature of the scene or the wished accuracy of the extracted objects have been presented. This topic remains challenging today as the need for accurate and up-to-date data is becoming more and more important. Based on this context, we will study in this paper the road network from a particular point of view, focusing on road marks, and in particular dashed lines. Indeed, they are very useful clues, for evidence of a road, but also for tasks of a higher level. For instance, they can be used to enhance quality and to improve road databases. It is also possible to delineate the different circulation lanes, their width and functionality (speed limit, special lanes for buses or bicycles...). In this paper, we propose a new robust and accurate top-down approach for dashed line detection based on stochastic geometry. Our approach is automatic in the sense that no intervention from a human operator is necessary to initialise the algorithm or to track errors during the process. The core of our approach relies on defining geometric, radiometric and relational models for dashed lines objects. The model also has to deal with the interactions between the different objects making up a line, meaning that it introduces external knowledge taken from specifications. Our strategy is based on a stochastic method, and in particular marked point processes. Our goal is to find the objects configuration minimising an energy function made-up of a data attachment term measuring the consistency of the image with respect to the objects and a regularising term managing the relationship between neighbouring objects. To sample the energy function, we use Green algorithm's; coupled with a simulated annealing to find its minimum. Results from aerial images at various resolutions are presented showing that our
Wutz, Andreas; Weisz, Nathan; Braun, Christoph; Melcher, David
2014-01-22
Dynamic vision requires both stability of the current perceptual representation and sensitivity to the accumulation of sensory evidence over time. Here we study the electrophysiological signatures of this intricate balance between temporal segregation and integration in vision. Within a forward masking paradigm with short and long stimulus onset asynchronies (SOA), we manipulated the temporal overlap of the visual persistence of two successive transients. Human observers enumerated the items presented in the second target display as a measure of the informational capacity read-out from this partly temporally integrated visual percept. We observed higher β-power immediately before mask display onset in incorrect trials, in which enumeration failed due to stronger integration of mask and target visual information. This effect was timescale specific, distinguishing between segregation and integration of visual transients that were distant in time (long SOA). Conversely, for short SOA trials, mask onset evoked a stronger visual response when mask and targets were correctly segregated in time. Examination of the target-related response profile revealed the importance of an evoked α-phase reset for the segregation of those rapid visual transients. Investigating this precise mapping of the temporal relationships of visual signals onto electrophysiological responses highlights how the stream of visual information is carved up into discrete temporal windows that mediate between segregated and integrated percepts. Fragmenting the stream of visual information provides a means to stabilize perceptual events within one instant in time.
International Nuclear Information System (INIS)
Kuhn, W.L.; Westsik, J.H. Jr.
1989-01-01
Processing steps during the conversion of high-level nuclear waste into borosilicate glass in the Hanford Waste Vitrification Plant are being simulated on a computer by addressing transient mass balances. The results are being used to address the US Department of Energy's Waste Form Qualification requirements. The simulated addresses discontinuous (batch) operations and perturbations in the transient behavior of the process caused by errors in measurements and control actions. A collection of tests, based on process measurements, is continually checked and used to halt the simulated process when specified conditions are met. An associated set of control actions is then implemented in the simulation. The results for an example simulation are shown. 8 refs
Spatio-temporal pattern of vestibular information processing after brief caloric stimulation
International Nuclear Information System (INIS)
Marcelli, Vincenzo; Esposito, Fabrizio; Aragri, Adriana; Furia, Teresa; Riccardi, Pasquale; Tosetti, Michela; Biagi, Laura; Marciano, Elio; Di Salle, Francesco
2009-01-01
Processing of vestibular information at the cortical and subcortical level is essential for head and body orientation in space and self-motion perception, but little is known about the neural dynamics of the brain regions of the vestibular system involved in this task. Neuroimaging studies using both galvanic and caloric stimulation have shown that several distinct cortical and subcortical structures can be activated during vestibular information processing. The insular cortex has been often targeted and presented as the central hub of the vestibular cortical system. Since very short pulses of cold water ear irrigation can generate a strong and prolonged vestibular response and a nystagmus, we explored the effects of this type of caloric stimulation for assessing the blood-oxygen-level-dependent (BOLD) dynamics of neural vestibular processing in a whole-brain event-related functional magnetic resonance imaging (fMRI) experiment. We evaluated the spatial layout and the temporal dynamics of the activated cortical and subcortical regions in time-locking with the instant of injection and were able to extract a robust pattern of neural activity involving the contra-lateral insular cortex, the thalamus, the brainstem and the cerebellum. No significant correlation with the temporal envelope of the nystagmus was found. The temporal analysis of the activation profiles highlighted a significantly longer duration of the evoked BOLD activity in the brainstem compared to the insular cortex suggesting a functional de-coupling between cortical and subcortical activity during the vestibular response.
Directory of Open Access Journals (Sweden)
Yao Lu
Full Text Available Numerous studies have demonstrated that the structural and functional differences between professional musicians and non-musicians are not only found within a single modality, but also with regard to multisensory integration. In this study we have combined psychophysical with neurophysiological measurements investigating the processing of non-musical, synchronous or various levels of asynchronous audiovisual events. We hypothesize that long-term multisensory experience alters temporal audiovisual processing already at a non-musical stage. Behaviorally, musicians scored significantly better than non-musicians in judging whether the auditory and visual stimuli were synchronous or asynchronous. At the neural level, the statistical analysis for the audiovisual asynchronous response revealed three clusters of activations including the ACC and the SFG and two bilaterally located activations in IFG and STG in both groups. Musicians, in comparison to the non-musicians, responded to synchronous audiovisual events with enhanced neuronal activity in a broad left posterior temporal region that covers the STG, the insula and the Postcentral Gyrus. Musicians also showed significantly greater activation in the left Cerebellum, when confronted with an audiovisual asynchrony. Taken together, our MEG results form a strong indication that long-term musical training alters the basic audiovisual temporal processing already in an early stage (direct after the auditory N1 wave, while the psychophysical results indicate that musical training may also provide behavioral benefits in the accuracy of the estimates regarding the timing of audiovisual events.
Lu, Yao; Paraskevopoulos, Evangelos; Herholz, Sibylle C; Kuchenbuch, Anja; Pantev, Christo
2014-01-01
Numerous studies have demonstrated that the structural and functional differences between professional musicians and non-musicians are not only found within a single modality, but also with regard to multisensory integration. In this study we have combined psychophysical with neurophysiological measurements investigating the processing of non-musical, synchronous or various levels of asynchronous audiovisual events. We hypothesize that long-term multisensory experience alters temporal audiovisual processing already at a non-musical stage. Behaviorally, musicians scored significantly better than non-musicians in judging whether the auditory and visual stimuli were synchronous or asynchronous. At the neural level, the statistical analysis for the audiovisual asynchronous response revealed three clusters of activations including the ACC and the SFG and two bilaterally located activations in IFG and STG in both groups. Musicians, in comparison to the non-musicians, responded to synchronous audiovisual events with enhanced neuronal activity in a broad left posterior temporal region that covers the STG, the insula and the Postcentral Gyrus. Musicians also showed significantly greater activation in the left Cerebellum, when confronted with an audiovisual asynchrony. Taken together, our MEG results form a strong indication that long-term musical training alters the basic audiovisual temporal processing already in an early stage (direct after the auditory N1 wave), while the psychophysical results indicate that musical training may also provide behavioral benefits in the accuracy of the estimates regarding the timing of audiovisual events.
Warnke, T.; Reinhardt, O.; Klabunde, A.; Willekens, F.J.; Uhrmacher, A.
2017-01-01
Individuals’ decision processes play a central role in understanding modern migration phenomena and other demographic processes. Their integration into agent-based computational demography depends largely on suitable support by a modelling language. We are developing the Modelling Language for
International Nuclear Information System (INIS)
Klauder, J.R.
1983-01-01
The author provides an introductory survey to stochastic quantization in which he outlines this new approach for scalar fields, gauge fields, fermion fields, and condensed matter problems such as electrons in solids and the statistical mechanics of quantum spins. (Auth.)
Simiu, Emil
2002-01-01
The classical Melnikov method provides information on the behavior of deterministic planar systems that may exhibit transitions, i.e. escapes from and captures into preferred regions of phase space. This book develops a unified treatment of deterministic and stochastic systems that extends the applicability of the Melnikov method to physically realizable stochastic planar systems with additive, state-dependent, white, colored, or dichotomous noise. The extended Melnikov method yields the novel result that motions with transitions are chaotic regardless of whether the excitation is deterministic or stochastic. It explains the role in the occurrence of transitions of the characteristics of the system and its deterministic or stochastic excitation, and is a powerful modeling and identification tool. The book is designed primarily for readers interested in applications. The level of preparation required corresponds to the equivalent of a first-year graduate course in applied mathematics. No previous exposure to d...
International Nuclear Information System (INIS)
Wehner, M.F.
1983-01-01
A path-integral solution is derived for processes described by nonlinear Fokker-Plank equations together with externally imposed boundary conditions. This path-integral solution is written in the form of a path sum for small time steps and contains, in addition to the conventional volume integral, a surface integral which incorporates the boundary conditions. A previously developed numerical method, based on a histogram representation of the probability distribution, is extended to a trapezoidal representation. This improved numerical approach is combined with the present path-integral formalism for restricted processes and is show t give accurate results. 35 refs., 5 figs
Stochastic stability of mechanical systems under renewal jump process parametric excitation
DEFF Research Database (Denmark)
Iwankiewicz, R.; Nielsen, Søren R.K.; Larsen, Jesper Winther
2005-01-01
A dynamic system under parametric excitation in the form of a non-Erlang renewal jump process is considered. The excitation is a random train of nonoverlapping rectangular pulses with equal, deterministic heights. The time intervals between two consecutive jumps up (or down), are the sum of two...
Analysis of the stochastic channel model by Saleh & Valenzuela via the theory of point processes
DEFF Research Database (Denmark)
Jakobsen, Morten Lomholt; Pedersen, Troels; Fleury, Bernard Henri
2012-01-01
and underlying features, like the intensity function of the component delays and the delaypower intensity. The flexibility and clarity of the mathematical instruments utilized to obtain these results lead us to conjecture that the theory of spatial point processes provides a unifying mathematical framework...
International Nuclear Information System (INIS)
Brenner, H.
1991-01-01
Macrotransport processes (generalized Taylor dispersion phenomena) constitute coarse-grained descriptions of comparable convective diffusive-reactive microtransport processes, the latter supposed governed by microscale linear constitutive equations and boundary conditions, but characterized by spatially nonuniform phenomenological coefficients. Following a brief review of existing applications of the theory, the author focuses - by way of background information-upon the original (and now classical) Taylor - Aris dispersion problem, involving the combined convective and molecular diffusive transport of a point-size Brownian solute molecule (tracer) suspended in a Poiseuille solvent flow within a circular tube. A series of elementary generalizations of this prototype problem to chromatographic-like solute transport processes in tubes is used to illustrate some novel statistical-physical features. These examples emphasize the fact that a solute molecule may, on average, move axially down the tube at a different mean velocity (either larger or smaller) than that of a solvent molecule. Moreover, this solute molecule may suffer axial dispersion about its mean velocity at a rate greatly exceeding that attributable to its axial molecular diffusion alone. Such chromatographic anomalies represent novel macroscale non-linearities originating from physicochemical interactions between spatially inhomogeneous convective-diffusive-reactive microtransport processes
Non-homogeneous stochastic birth and death processes with applications to epidemic outbreak data
van den Broek, J.
2012-01-01
The subject of this thesis is the non-homogeneous birth-death process with some of its special cases and its use in modeling epidemic data. This model describes changes in the size of a population. New population members can appear with a rate, called the birth rate or the reproductive power, and
DEFF Research Database (Denmark)
Møller, Jesper; Ghorbani, Mohammad; Rubak, Ege Holger
We show how a spatial point process, where to each point there is associated a random quantitative mark, can be identified with a spatio-temporal point process specified by a conditional intensity function. For instance, the points can be tree locations, the marks can express the size of trees......, and the conditional intensity function can describe the distribution of a tree (i.e., its location and size) conditionally on the larger trees. This enable us to construct parametric statistical models which are easily interpretable and where likelihood-based inference is tractable. In particular, we consider maximum...
Davey, James; Thompson, Hannah E; Hallam, Glyn; Karapanagiotidis, Theodoros; Murphy, Charlotte; De Caso, Irene; Krieger-Redwood, Katya; Bernhardt, Boris C; Smallwood, Jonathan; Jefferies, Elizabeth
2016-08-15
Making sense of the world around us depends upon selectively retrieving information relevant to our current goal or context. However, it is unclear whether selective semantic retrieval relies exclusively on general control mechanisms recruited in demanding non-semantic tasks, or instead on systems specialised for the control of meaning. One hypothesis is that the left posterior middle temporal gyrus (pMTG) is important in the controlled retrieval of semantic (not non-semantic) information; however this view remains controversial since a parallel literature links this site to event and relational semantics. In a functional neuroimaging study, we demonstrated that an area of pMTG implicated in semantic control by a recent meta-analysis was activated in a conjunction of (i) semantic association over size judgements and (ii) action over colour feature matching. Under these circumstances the same region showed functional coupling with the inferior frontal gyrus - another crucial site for semantic control. Structural and functional connectivity analyses demonstrated that this site is at the nexus of networks recruited in automatic semantic processing (the default mode network) and executively demanding tasks (the multiple-demand network). Moreover, in both task and task-free contexts, pMTG exhibited functional properties that were more similar to ventral parts of inferior frontal cortex, implicated in controlled semantic retrieval, than more dorsal inferior frontal sulcus, implicated in domain-general control. Finally, the pMTG region was functionally correlated at rest with other regions implicated in control-demanding semantic tasks, including inferior frontal gyrus and intraparietal sulcus. We suggest that pMTG may play a crucial role within a large-scale network that allows the integration of automatic retrieval in the default mode network with executively-demanding goal-oriented cognition, and that this could support our ability to understand actions and non
A Fractionally Integrated Wishart Stochastic Volatility Model
M. Asai (Manabu); M.J. McAleer (Michael)
2013-01-01
textabstractThere has recently been growing interest in modeling and estimating alternative continuous time multivariate stochastic volatility models. We propose a continuous time fractionally integrated Wishart stochastic volatility (FIWSV) process. We derive the conditional Laplace transform of
Transport properties of stochastic Lorentz models
Beijeren, H. van
Diffusion processes are considered for one-dimensional stochastic Lorentz models, consisting of randomly distributed fixed scatterers and one moving light particle. In waiting time Lorentz models the light particle makes instantaneous jumps between scatterers after a stochastically distributed
Environmental vs Demographic Stochasticity in Population Growth
Braumann, C. A.
2010-01-01
Compares the effect on population growth of envinonmental stochasticity (random environmental variations described by stochastic differential equations) with demographic stochasticity (random variations in births and deaths described by branching processes and birth-and-death processes), in the density-independent and the density-dependent cases.
Stochastic modeling for neural spiking events based on fractional superstatistical Poisson process
Directory of Open Access Journals (Sweden)
Hidetoshi Konno
2018-01-01
Full Text Available In neural spike counting experiments, it is known that there are two main features: (i the counting number has a fractional power-law growth with time and (ii the waiting time (i.e., the inter-spike-interval distribution has a heavy tail. The method of superstatistical Poisson processes (SSPPs is examined whether these main features are properly modeled. Although various mixed/compound Poisson processes are generated with selecting a suitable distribution of the birth-rate of spiking neurons, only the second feature (ii can be modeled by the method of SSPPs. Namely, the first one (i associated with the effect of long-memory cannot be modeled properly. Then, it is shown that the two main features can be modeled successfully by a class of fractional SSPP (FSSPP.
Stochastic processes crossing from ballistic to fractional diffusion with memory: exact results
Directory of Open Access Journals (Sweden)
V. Ilyin
2010-01-01
Full Text Available We address the now classical problem of a diffusion process that crosses over from a ballistic behavior at short times to a fractional diffusion (sub- or super-diffusion at longer times. Using the standard non-Markovian diffusion equation we demonstrate how to choose the memory kernel to exactly respect the two different asymptotics of the diffusion process. Having done so we solve for the probability distribution function as a continuous function which evolves inside a ballistically expanding domain. This general solution agrees for long times with the probability distribution function obtained within the continuous random walk approach but it is much superior to this solution at shorter times where the effect of the ballistic regime is crucial.
Stochastic modeling for neural spiking events based on fractional superstatistical Poisson process
Konno, Hidetoshi; Tamura, Yoshiyasu
2018-01-01
In neural spike counting experiments, it is known that there are two main features: (i) the counting number has a fractional power-law growth with time and (ii) the waiting time (i.e., the inter-spike-interval) distribution has a heavy tail. The method of superstatistical Poisson processes (SSPPs) is examined whether these main features are properly modeled. Although various mixed/compound Poisson processes are generated with selecting a suitable distribution of the birth-rate of spiking neurons, only the second feature (ii) can be modeled by the method of SSPPs. Namely, the first one (i) associated with the effect of long-memory cannot be modeled properly. Then, it is shown that the two main features can be modeled successfully by a class of fractional SSPP (FSSPP).
ADAPTIVE PARAMETER ESTIMATION OF PERSON RECOGNITION MODEL IN A STOCHASTIC HUMAN TRACKING PROCESS
W. Nakanishi; T. Fuse; T. Ishikawa
2015-01-01
This paper aims at an estimation of parameters of person recognition models using a sequential Bayesian filtering method. In many human tracking method, any parameters of models used for recognize the same person in successive frames are usually set in advance of human tracking process. In real situation these parameters may change according to situation of observation and difficulty level of human position prediction. Thus in this paper we formulate an adaptive parameter estimation ...
Brownian motion and stochastic calculus
Karatzas, Ioannis
1998-01-01
This book is designed as a text for graduate courses in stochastic processes. It is written for readers familiar with measure-theoretic probability and discrete-time processes who wish to explore stochastic processes in continuous time. The vehicle chosen for this exposition is Brownian motion, which is presented as the canonical example of both a martingale and a Markov process with continuous paths. In this context, the theory of stochastic integration and stochastic calculus is developed. The power of this calculus is illustrated by results concerning representations of martingales and change of measure on Wiener space, and these in turn permit a presentation of recent advances in financial economics (option pricing and consumption/investment optimization). This book contains a detailed discussion of weak and strong solutions of stochastic differential equations and a study of local time for semimartingales, with special emphasis on the theory of Brownian local time. The text is complemented by a large num...
Hu, Weigang; Zhang, Qi; Tian, Tian; Li, Dingyao; Cheng, Gang; Mu, Jing; Wu, Qingbai; Niu, Fujun; Stegen, James C; An, Lizhe; Feng, Huyuan
2015-01-01
Understanding the processes that influence the structure of biotic communities is one of the major ecological topics, and both stochastic and deterministic processes are expected to be at work simultaneously in most communities. Here, we investigated the vertical distribution patterns of bacterial communities in a 10-m-long soil core taken within permafrost of the Qinghai-Tibet Plateau. To get a better understanding of the forces that govern these patterns, we examined the diversity and structure of bacterial communities, and the change in community composition along the vertical distance (spatial turnover) from both taxonomic and phylogenetic perspectives. Measures of taxonomic and phylogenetic beta diversity revealed that bacterial community composition changed continuously along the soil core, and showed a vertical distance-decay relationship. Multiple stepwise regression analysis suggested that bacterial alpha diversity and phylogenetic structure were strongly correlated with soil conductivity and pH but weakly correlated with depth. There was evidence that deterministic and stochastic processes collectively drived bacterial vertically-structured pattern. Bacterial communities in five soil horizons (two originated from the active layer and three from permafrost) of the permafrost core were phylogenetically random, indicator of stochastic processes. However, we found a stronger effect of deterministic processes related to soil pH, conductivity, and organic carbon content that were structuring the bacterial communities. We therefore conclude that the vertical distribution of bacterial communities was governed primarily by deterministic ecological selection, although stochastic processes were also at work. Furthermore, the strong impact of environmental conditions (for example, soil physicochemical parameters and seasonal freeze-thaw cycles) on these communities underlines the sensitivity of permafrost microorganisms to climate change and potentially subsequent
Quantification of annual wildfire risk; A spatio-temporal point process approach.
Directory of Open Access Journals (Sweden)
Paula Pereira
2013-10-01
Full Text Available Policy responses for local and global firemanagement depend heavily on the proper understanding of the fire extent as well as its spatio-temporal variation across any given study area. Annual fire risk maps are important tools for such policy responses, supporting strategic decisions such as location-allocation of equipment and human resources. Here, we define risk of fire in the narrow sense as the probability of its occurrence without addressing the loss component. In this paper, we study the spatio-temporal point patterns of wildfires and model them by a log Gaussian Cox processes. Themean of predictive distribution of randomintensity function is used in the narrow sense, as the annual fire risk map for next year.
Reversal of interlaminar signal between sensory and memory processing in monkey temporal cortex.
Takeuchi, Daigo; Hirabayashi, Toshiyuki; Tamura, Keita; Miyashita, Yasushi
2011-03-18
The primate temporal cortex implements visual long-term memory. However, how its interlaminar circuitry executes cognitive computations is poorly understood. Using linear-array multicontact electrodes, we simultaneously recorded unit activities across cortical layers in the perirhinal cortex of macaques performing a pair-association memory task. Cortical layers were estimated on the basis of current source density profiles with histological verifications, and the interlaminar signal flow was determined with cross-correlation analysis between spike trains. During the cue period, canonical "feed-forward" signals flowed from granular to supragranular layers and from supragranular to infragranular layers. During the delay period, however, the signal flow reversed to the "feed-back" direction: from infragranular to supragranular layers. This reversal of signal flow highlights how the temporal cortex differentially recruits its laminar circuits for sensory and mnemonic processing.
Deep processing activates the medial temporal lobe in young but not in old adults.
Daselaar, Sander M; Veltman, Dick J; Rombouts, Serge A R B; Raaijmakers, Jeroen G W; Jonker, Cees
2003-11-01
Age-related impairments in episodic memory have been related to a deficiency in semantic processing, based on the finding that elderly adults typically benefit less than young adults from deep, semantic as opposed to shallow, nonsemantic processing of study items. In the present study, we tested the hypothesis that elderly adults are not able to perform certain cognitive operations under deep processing conditions. We further hypothesised that this inability does not involve regions commonly associated with lexical/semantic retrieval processes, but rather involves a dysfunction of the medial temporal lobe (MTL) memory system. To this end, we used functional MRI on rather extensive groups of young and elderly adults to compare brain activity patterns obtained during a deep (living/nonliving) and a shallow (uppercase/lowercase) classification task. Common activity in relation to semantic classification was observed in regions that have been previously related to semantic retrieval, including mainly left-lateralised activity in the inferior prefrontal, middle temporal, and middle frontal/anterior cingulate gyrus. Although the young adults showed more activity in some of these areas, the finding of mainly overlapping activation patterns during semantic classification supports the idea that lexical/semantic retrieval processes are still intact in elderly adults. This received further support by the finding that both groups showed similar behavioural performances as well on the deep and shallow classification tasks. Importantly, though, the young revealed significantly more activity than the elderly adults in the left anterior hippocampus during deep relative to shallow classification. This finding is in line with the idea that age-related impairments in episodic encoding are, at least partly, due to an under-recruitment of the medial temporal lobe memory system.
STOCHASTIC ASSESSMENT OF NIGERIAN STOCHASTIC ...
African Journals Online (AJOL)
eobe
STOCHASTIC ASSESSMENT OF NIGERIAN WOOD FOR BRIDGE DECKS ... abandoned bridges with defects only in their decks in both rural and urban locations can be effectively .... which can be seen as the detection of rare physical.
Directory of Open Access Journals (Sweden)
Fabio Rodrigo Siqueira Batista
2013-12-01
Full Text Available The objective of this paper is to verify the robustness of the Least Square Monte Carlo and Grant, Vora & Weeks methods when used to determine the incremental payoff of the carbon market for renewable electricity generation projects, considering that the behavior of the price of Certified Emission Reductions, otherwise known as Carbon Credits, may be modeled using a jump-diffusion process. In addition, this paper analyses particular characteristics, such as absence of monotonicity, found in trigger curves obtained through use of the Grant, Vora & Weeks method to valuate these types of project.
Directory of Open Access Journals (Sweden)
Chad Edward Forbes
2012-11-01
Full Text Available The Implicit Association Test (IAT is a popular behavioral measure that assesses the associative strength between outgroup members and stereotypical and counterstereotypical traits. Less is known, however, about the degree to which the IAT reflects automatic processing. Two studies examined automatic processing contributions to a gender-IAT using a data driven, social neuroscience approach. Performance on congruent (e.g., categorizing male names with synonyms of strength and incongruent (e.g., categorizing female names with synonyms of strength IAT blocks were separately analyzed using EEG (event-related potentials, or ERPs, and coherence; Study 1 and lesion (Study 2 methodologies. Compared to incongruent blocks, performance on congruent IAT blocks was associated with more positive ERPs that manifested in frontal and occipital regions at automatic processing speeds, occipital regions at more controlled processing speeds and was compromised by volume loss in the anterior temporal lobe, insula and medial PFC. Performance on incongruent blocks was associated with volume loss in supplementary motor areas, cingulate gyrus and a region in medial PFC similar to that found for congruent blocks. Greater coherence was found between frontal and occipital regions to the extent individuals exhibited more bias. This suggests there are separable neural contributions to congruent and incongruent blocks of the IAT but there is also a surprising amount of overlap. Given the temporal and regional neural distinctions, these results provide converging evidence that stereotypic associative strength assessed by the IAT indexes automatic processing to a degree.
Altered Medial Frontal and Superior Temporal Response to Implicit Processing of Emotions in Autism.
Kana, Rajesh K; Patriquin, Michelle A; Black, Briley S; Channell, Marie M; Wicker, Bruno
2016-01-01
Interpreting emotional expressions appropriately poses a challenge for individuals with autism spectrum disorder (ASD). In particular, difficulties with emotional processing in ASD are more pronounced in contexts where emotional expressions are subtle, automatic, and reflexive-that is, implicit. In contrast, explicit emotional processing, which requires the cognitive evaluation of an emotional experience, appears to be relatively intact in individuals with ASD. In the present study, we examined the brain activation and functional connectivity differences underlying explicit and implicit emotional processing in age- and IQ-matched adults with (n = 17) and without (n = 15) ASD. Results indicated: (1) significantly reduced levels of brain activation in participants with ASD in medial prefrontal cortex (MPFC) and superior temporal gyrus (STG) during implicit emotion processing; (2) significantly weaker functional connectivity in the ASD group in connections of the MPFC with the amygdala, temporal lobe, parietal lobe, and fusiform gyrus; (3) No group difference in performance accuracy or reaction time; and (4) Significant positive relationship between empathizing ability and STG activity in ASD but not in typically developing participants. These findings suggest that the neural mechanisms underlying implicit, but not explicit, emotion processing may be altered at multiple levels in individuals with ASD. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.
Stochastic modeling and analysis of telecoms networks
Decreusefond, Laurent
2012-01-01
This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an
Dhivert, E; Grosbois, C; Rodrigues, S; Desmet, M
2015-02-01
Floodplains are often cored to build long-term pollutant trends at the basin scale. To highlight the influences of depositional environments on archiving processes, aggradation rates, archived trace element signals and vertical redistribution processes, two floodplain cores were sampled near in two different environments of the Upper Loire River (France): (i) a river bank ridge and (ii) a paleochannel connected by its downstream end. The base of the river bank core is composed of sandy sediments from the end of the Little Ice Age (late 18th century). This composition corresponds to a proximal floodplain aggradation (sediments that settled in the distal floodplain. In this distal floodplain environment, the aggradation rate depends on the topography and connection degree to the river channel. The temporal dynamics of anthropogenic trace element enrichments recorded in the distal floodplain are initially synchronous and present similar levels. Although the river bank core shows general temporal trends, the paleochannel core has a better resolution for short-time variations of trace element signals. After local water depth regulation began in the early 1930s, differences of connection degree were enhanced between the two cores. Therefore, large trace element signal divergences are recorded across the floodplain. The paleochannel core shows important temporal variations of enrichment levels from the 1930s to the coring date. However, the river bank core has no significant temporal variations of trace element enrichments and lower contamination levels because of a lower deposition of contaminated sediments and a pedogenetic trace elements redistribution. Copyright © 2014 Elsevier B.V. All rights reserved.
Stochastic Games for Continuous-Time Jump Processes Under Finite-Horizon Payoff Criterion
Energy Technology Data Exchange (ETDEWEB)
Wei, Qingda, E-mail: weiqd@hqu.edu.cn [Huaqiao University, School of Economics and Finance (China); Chen, Xian, E-mail: chenxian@amss.ac.cn [Peking University, School of Mathematical Sciences (China)
2016-10-15
In this paper we study two-person nonzero-sum games for continuous-time jump processes with the randomized history-dependent strategies under the finite-horizon payoff criterion. The state space is countable, and the transition rates and payoff functions are allowed to be unbounded from above and from below. Under the suitable conditions, we introduce a new topology for the set of all randomized Markov multi-strategies and establish its compactness and metrizability. Then by constructing the approximating sequences of the transition rates and payoff functions, we show that the optimal value function for each player is a unique solution to the corresponding optimality equation and obtain the existence of a randomized Markov Nash equilibrium. Furthermore, we illustrate the applications of our main results with a controlled birth and death system.
On discrete stochastic processes with long-lasting time dependence in the variance
Queirós, S. M. D.
2008-11-01
In this manuscript, we analytically and numerically study statistical properties of an heteroskedastic process based on the celebrated ARCH generator of random variables whose variance is defined by a memory of qm-exponencial, form (eqm=1 x=ex). Specifically, we inspect the self-correlation function of squared random variables as well as the kurtosis. In addition, by numerical procedures, we infer the stationary probability density function of both of the heteroskedastic random variables and the variance, the multiscaling properties, the first-passage times distribution, and the dependence degree. Finally, we introduce an asymmetric variance version of the model that enables us to reproduce the so-called leverage effect in financial markets.
Stochastic Games for Continuous-Time Jump Processes Under Finite-Horizon Payoff Criterion
International Nuclear Information System (INIS)
Wei, Qingda; Chen, Xian
2016-01-01
In this paper we study two-person nonzero-sum games for continuous-time jump processes with the randomized history-dependent strategies under the finite-horizon payoff criterion. The state space is countable, and the transition rates and payoff functions are allowed to be unbounded from above and from below. Under the suitable conditions, we introduce a new topology for the set of all randomized Markov multi-strategies and establish its compactness and metrizability. Then by constructing the approximating sequences of the transition rates and payoff functions, we show that the optimal value function for each player is a unique solution to the corresponding optimality equation and obtain the existence of a randomized Markov Nash equilibrium. Furthermore, we illustrate the applications of our main results with a controlled birth and death system.
Digital simulation of an arbitrary stationary stochastic process by spectral representation.
Yura, Harold T; Hanson, Steen G
2011-04-01
In this paper we present a straightforward, efficient, and computationally fast method for creating a large number of discrete samples with an arbitrary given probability density function and a specified spectral content. The method relies on initially transforming a white noise sample set of random Gaussian distributed numbers into a corresponding set with the desired spectral distribution, after which this colored Gaussian probability distribution is transformed via an inverse transform into the desired probability distribution. In contrast to previous work, where the analyses were limited to auto regressive and or iterative techniques to obtain satisfactory results, we find that a single application of the inverse transform method yields satisfactory results for a wide class of arbitrary probability distributions. Although a single application of the inverse transform technique does not conserve the power spectra exactly, it yields highly accurate numerical results for a wide range of probability distributions and target power spectra that are sufficient for system simulation purposes and can thus be regarded as an accurate engineering approximation, which can be used for wide range of practical applications. A sufficiency condition is presented regarding the range of parameter values where a single application of the inverse transform method yields satisfactory agreement between the simulated and target power spectra, and a series of examples relevant for the optics community are presented and discussed. Outside this parameter range the agreement gracefully degrades but does not distort in shape. Although we demonstrate the method here focusing on stationary random processes, we see no reason why the method could not be extended to simulate non-stationary random processes. © 2011 Optical Society of America
Wang, Dong-Yuan Debbie; Richard, F Dan; Ray, Brittany
2016-01-01
The stimulus-response correspondence (SRC) effect refers to advantages in performance when stimulus and response correspond in dimensions or features, even if the common features are irrelevant to the task. Previous research indicated that the SRC effect depends on the temporal course of stimulus information processing. The current study investigated how the temporal overlap between relevant and irrelevant stimulus processing influences the SRC effect. In this experiment, the irrelevant stimulus (a previously associated tone) preceded the relevant stimulus (a coloured rectangle). The irrelevant and relevant stimuli onset asynchrony was varied to manipulate the temporal overlap between the irrelevant and relevant stimuli processing. Results indicated that the SRC effect size varied as a quadratic function of the temporal overlap between the relevant stimulus and irrelevant stimulus. This finding extends previous experimental observations that the SRC effect size varies in an increasing or decreasing function with reaction time. The current study demonstrated a quadratic function between effect size and the temporal overlap.
International Nuclear Information System (INIS)
Lee, Youn Myoung
1995-02-01
As a newly approaching model, a stochastic model using continuous time Markov process for nuclide decay chain transport of arbitrary length in the fractured porous rock medium has been proposed, by which the need for solving a set of partial differential equations corresponding to various sets of side conditions can be avoided. Once the single planar fracture in the rock matrix is represented by a series of finite number of compartments having region wise constant parameter values in them, the medium is continuous in view of various processes associated with nuclide transport but discrete in medium space and such geologic system is assumed to have Markov property, since the Markov process requires that only the present value of the time dependent random variable be known to determine the future value of random variable, nuclide transport in the medium can then be modeled as a continuous time Markov process. Processes that are involved in nuclide transport are advective transport due to groundwater flow, diffusion into the rock matrix, adsorption onto the wall of the fracture and within the pores in the rock matrix, and radioactive decay chain. The transition probabilities for nuclide from the transition intensities between and out of the compartments are represented utilizing Chapman-Kolmogorov equation, through which the expectation and the variance of nuclide distribution for each compartment or the fractured rock medium can be obtained. Some comparisons between Markov process model developed in this work and available analytical solutions for one-dimensional layered porous medium, fractured medium with rock matrix diffusion, and porous medium considering three member nuclide decay chain without rock matrix diffusion have been made showing comparatively good agreement for all cases. To verify the model developed in this work another comparative study was also made by fitting the experimental data obtained with NaLS and uranine running in the artificial fractured
Directory of Open Access Journals (Sweden)
Petrică Andreea-Cristina
2017-07-01
Full Text Available Modeling exchange rate volatility became an important topic for research debate starting with 1973, when many countries switched to floating exchange rate system. In this paper, we focus on the EUR/RON exchange rate both as an economic measure and present the implied economic links, and also as a financial investment and analyze its movements and fluctuations through two volatility stochastic processes: the Standard Generalized Autoregressive Conditionally Heteroscedastic Model (GARCH and the Exponential Generalized Autoregressive Conditionally Heteroscedastic Model (EGARCH. The objective of the conditional variance processes is to capture dependency in the return series of the EUR/RON exchange rate. On this account, analyzing exchange rates could be seen as the input for economic decisions regarding Romanian macroeconomics - the exchange rates being influenced by many factors such as: interest rates, inflation, trading relationships with other countries (imports and exports, or investments - portfolio optimization, risk management, asset pricing. Therefore, we talk about political stability and economic performance of a country that represents a link between the two types of inputs mentioned above and influences both the macroeconomics and the investments. Based on time-varying volatility, we examine implied volatility of daily returns of EUR/RON exchange rate using the standard GARCH model and the asymmetric EGARCH model, whose parameters are estimated through the maximum likelihood method and the error terms follow two distributions (Normal and Student’s t. The empirical results show EGARCH(2,1 with Asymmetric order 2 and Student’s t error terms distribution performs better than all the estimated standard GARCH models (GARCH(1,1, GARCH(1,2, GARCH(2,1 and GARCH(2,2. This conclusion is supported by the major advantage of the EGARCH model compared to the GARCH model which consists in allowing good and bad news having different impact on the
Tünnermann, Jan; Scharlau, Ingrid
2016-01-01
Peripheral visual cues lead to large shifts in psychometric distributions of temporal-order judgments. In one view, such shifts are attributed to attention speeding up processing of the cued stimulus, so-called prior entry. However, sometimes these shifts are so large that it is unlikely that they are caused by attention alone. Here we tested the prevalent alternative explanation that the cue is sometimes confused with the target on a perceptual level, bolstering the shift of the psychometric function. We applied a novel model of cued temporal-order judgments, derived from Bundesen's Theory of Visual Attention. We found that cue-target confusions indeed contribute to shifting psychometric functions. However, cue-induced changes in the processing rates of the target stimuli play an important role, too. At smaller cueing intervals, the cue increased the processing speed of the target. At larger intervals, inhibition of return was predominant. Earlier studies of cued TOJs were insensitive to these effects because in psychometric distributions they are concealed by the conjoint effects of cue-target confusions and processing rate changes.
Detecting change in stochastic sound sequences.
Directory of Open Access Journals (Sweden)
Benjamin Skerritt-Davis
2018-05-01
Full Text Available Our ability to parse our acoustic environment relies on the brain's capacity to extract statistical regularities from surrounding sounds. Previous work in regularity extraction has predominantly focused on the brain's sensitivity to predictable patterns in sound sequences. However, natural sound environments are rarely completely predictable, often containing some level of randomness, yet the brain is able to effectively interpret its surroundings by extracting useful information from stochastic sounds. It has been previously shown that the brain is sensitive to the marginal lower-order statistics of sound sequences (i.e., mean and variance. In this work, we investigate the brain's sensitivity to higher-order statistics describing temporal dependencies between sound events through a series of change detection experiments, where listeners are asked to detect changes in randomness in the pitch of tone sequences. Behavioral data indicate listeners collect statistical estimates to process incoming sounds, and a perceptual model based on Bayesian inference shows a capacity in the brain to track higher-order statistics. Further analysis of individual subjects' behavior indicates an important role of perceptual constraints in listeners' ability to track these sensory statistics with high fidelity. In addition, the inference model facilitates analysis of neural electroencephalography (EEG responses, anchoring the analysis relative to the statistics of each stochastic stimulus. This reveals both a deviance response and a change-related disruption in phase of the stimulus-locked response that follow the higher-order statistics. These results shed light on the brain's ability to process stochastic sound sequences.
Adaptive Parameter Estimation of Person Recognition Model in a Stochastic Human Tracking Process
Nakanishi, W.; Fuse, T.; Ishikawa, T.
2015-05-01
This paper aims at an estimation of parameters of person recognition models using a sequential Bayesian filtering method. In many human tracking method, any parameters of models used for recognize the same person in successive frames are usually set in advance of human tracking process. In real situation these parameters may change according to situation of observation and difficulty level of human position prediction. Thus in this paper we formulate an adaptive parameter estimation using general state space model. Firstly we explain the way to formulate human tracking in general state space model with their components. Then referring to previous researches, we use Bhattacharyya coefficient to formulate observation model of general state space model, which is corresponding to person recognition model. The observation model in this paper is a function of Bhattacharyya coefficient with one unknown parameter. At last we sequentially estimate this parameter in real dataset with some settings. Results showed that sequential parameter estimation was succeeded and were consistent with observation situations such as occlusions.
Peter, Varghese; Wong, Kogo; Narne, Vijaya Kumar; Sharma, Mridula; Purdy, Suzanne C; McMahon, Catherine
2014-02-01
There are many clinically available tests for the assessment of auditory processing skills in children and adults. However, there is limited data available on the maturational effects on the performance on these tests. The current study investigated maturational effects on auditory processing abilities using three psychophysical measures: temporal modulation transfer function (TMTF), iterated ripple noise (IRN) perception, and spectral ripple discrimination (SRD). A cross-sectional study. Three groups of subjects were tested: 10 adults (18-30 yr), 10 older children (12-18 yr), and 10 young children (8-11 yr) Temporal envelope processing was measured by obtaining thresholds for amplitude modulation detection as a function of modulation frequency (TMTF; 4, 8, 16, 32, 64, and 128 Hz). Temporal fine structure processing was measured using IRN, and spectral processing was measured using SRD. The results showed that young children had significantly higher modulation thresholds at 4 Hz (TMTF) compared to the other two groups and poorer SRD scores compared to adults. The results on IRN did not differ across groups. The results suggest that different aspects of auditory processing mature at different age periods and these maturational effects need to be considered while assessing auditory processing in children. American Academy of Audiology.
Stochastic dynamics and irreversibility
Tomé, Tânia
2015-01-01
This textbook presents an exposition of stochastic dynamics and irreversibility. It comprises the principles of probability theory and the stochastic dynamics in continuous spaces, described by Langevin and Fokker-Planck equations, and in discrete spaces, described by Markov chains and master equations. Special concern is given to the study of irreversibility, both in systems that evolve to equilibrium and in nonequilibrium stationary states. Attention is also given to the study of models displaying phase transitions and critical phenomema both in thermodynamic equilibrium and out of equilibrium. These models include the linear Glauber model, the Glauber-Ising model, lattice models with absorbing states such as the contact process and those used in population dynamic and spreading of epidemic, probabilistic cellular automata, reaction-diffusion processes, random sequential adsorption and dynamic percolation. A stochastic approach to chemical reaction is also presented.The textbook is intended for students of ...
Stochastic ice stream dynamics.
Mantelli, Elisa; Bertagni, Matteo Bernard; Ridolfi, Luca
2016-08-09
Ice streams are narrow corridors of fast-flowing ice that constitute the arterial drainage network of ice sheets. Therefore, changes in ice stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of ice sheets during deglaciation. The dynamics of ice flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and ice stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive ice stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of ice sheets, as well as to predicting their future evolution.
DEFF Research Database (Denmark)
Møller, Jesper; Diaz-Avalos, Carlos
2010-01-01
Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable fo...... data set consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent....
Constraining Stochastic Parametrisation Schemes Using High-Resolution Model Simulations
Christensen, H. M.; Dawson, A.; Palmer, T.
2017-12-01
Stochastic parametrisations are used in weather and climate models as a physically motivated way to represent model error due to unresolved processes. Designing new stochastic schemes has been the target of much innovative research over the last decade. While a focus has been on developing physically motivated approaches, many successful stochastic parametrisation schemes are very simple, such as the European Centre for Medium-Range Weather Forecasts (ECMWF) multiplicative scheme `Stochastically Perturbed Parametrisation Tendencies' (SPPT). The SPPT scheme improves the skill of probabilistic weather and seasonal forecasts, and so is widely used. However, little work has focused on assessing the physical basis of the SPPT scheme. We address this matter by using high-resolution model simulations to explicitly measure the `error' in the parametrised tendency that SPPT seeks to represent. The high resolution simulations are first coarse-grained to the desired forecast model resolution before they are used to produce initial conditions and forcing data needed to drive the ECMWF Single Column Model (SCM). By comparing SCM forecast tendencies with the evolution of the high resolution model, we can measure the `error' in the forecast tendencies. In this way, we provide justification for the multiplicative nature of SPPT, and for the temporal and spatial scales of the stochastic perturbations. However, we also identify issues with the SPPT scheme. It is therefore hoped these measurements will improve both holistic and process based approaches to stochastic parametrisation. Figure caption: Instantaneous snapshot of the optimal SPPT stochastic perturbation, derived by comparing high-resolution simulations with a low resolution forecast model.
Multimodal imaging of temporal processing in typical and atypical language development.
Kovelman, Ioulia; Wagley, Neelima; Hay, Jessica S F; Ugolini, Margaret; Bowyer, Susan M; Lajiness-O'Neill, Renee; Brennan, Jonathan
2015-03-01
New approaches to understanding language and reading acquisition propose that the human brain's ability to synchronize its neural firing rate to syllable-length linguistic units may be important to children's ability to acquire human language. Yet, little evidence from brain imaging studies has been available to support this proposal. Here, we summarize three recent brain imaging (functional near-infrared spectroscopy (fNIRS), functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG)) studies from our laboratories with young English-speaking children (aged 6-12 years). In the first study (fNIRS), we used an auditory beat perception task to show that, in children, the left superior temporal gyrus (STG) responds preferentially to rhythmic beats at 1.5 Hz. In the second study (fMRI), we found correlations between children's amplitude rise-time sensitivity, phonological awareness, and brain activation in the left STG. In the third study (MEG), typically developing children outperformed children with autism spectrum disorder in extracting words from rhythmically rich foreign speech and displayed different brain activation during the learning phase. The overall findings suggest that the efficiency with which left temporal regions process slow temporal (rhythmic) information may be important for gains in language and reading proficiency. These findings carry implications for better understanding of the brain's mechanisms that support language and reading acquisition during both typical and atypical development. © 2014 New York Academy of Sciences.
Directory of Open Access Journals (Sweden)
Tristan Guillaume
2016-01-01
Full Text Available This paper shows how to value multiasset options analytically in a modeling framework that combines both continuous and discontinuous variations in the underlying equity or foreign exchange processes and a stochastic, two-factor yield curve. All correlations are taken into account, between the factors driving the yield curve, between fixed income and equity as asset classes, and between the individual equity assets themselves. The valuation method is applied to three of the most popular two-asset options.
Big Data GPU-Driven Parallel Processing Spatial and Spatio-Temporal Clustering Algorithms
Konstantaras, Antonios; Skounakis, Emmanouil; Kilty, James-Alexander; Frantzeskakis, Theofanis; Maravelakis, Emmanuel
2016-04-01
Advances in graphics processing units' technology towards encompassing parallel architectures [1], comprised of thousands of cores and multiples of parallel threads, provide the foundation in terms of hardware for the rapid processing of various parallel applications regarding seismic big data analysis. Seismic data are normally stored as collections of vectors in massive matrices, growing rapidly in size as wider areas are covered, denser recording networks are being established and decades of data are being compiled together [2]. Yet, many processes regarding seismic data analysis are performed on each seismic event independently or as distinct tiles [3] of specific grouped seismic events within a much larger data set. Such processes, independent of one another can be performed in parallel narrowing down processing times drastically [1,3]. This research work presents the development and implementation of three parallel processing algorithms using Cuda C [4] for the investigation of potentially distinct seismic regions [5,6] present in the vicinity of the southern Hellenic seismic arc. The algorithms, programmed and executed in parallel comparatively, are the: fuzzy k-means clustering with expert knowledge [7] in assigning overall clusters' number; density-based clustering [8]; and a selves-developed spatio-temporal clustering algorithm encompassing expert [9] and empirical knowledge [10] for the specific area under investigation. Indexing terms: GPU parallel programming, Cuda C, heterogeneous processing, distinct seismic regions, parallel clustering algorithms, spatio-temporal clustering References [1] Kirk, D. and Hwu, W.: 'Programming massively parallel processors - A hands-on approach', 2nd Edition, Morgan Kaufman Publisher, 2013 [2] Konstantaras, A., Valianatos, F., Varley, M.R. and Makris, J.P.: 'Soft-Computing Modelling of Seismicity in the Southern Hellenic Arc', Geoscience and Remote Sensing Letters, vol. 5 (3), pp. 323-327, 2008 [3] Papadakis, S. and
Gourévitch, Boris; Le Bouquin Jeannès, Régine; Faucon, Gérard; Liégeois-Chauvel, Catherine
2008-03-01
Temporal envelope processing in the human auditory cortex has an important role in language analysis. In this paper, depth recordings of local field potentials in response to amplitude modulated white noises were used to design maps of activation in primary, secondary and associative auditory areas and to study the propagation of the cortical activity between them. The comparison of activations between auditory areas was based on a signal-to-noise ratio associated with the response to amplitude modulation (AM). The functional connectivity between cortical areas was quantified by the directed coherence (DCOH) applied to auditory evoked potentials. This study shows the following reproducible results on twenty subjects: (1) the primary auditory cortex (PAC), the secondary cortices (secondary auditory cortex (SAC) and planum temporale (PT)), the insular gyrus, the Brodmann area (BA) 22 and the posterior part of T1 gyrus (T1Post) respond to AM in both hemispheres. (2) A stronger response to AM was observed in SAC and T1Post of the left hemisphere independent of the modulation frequency (MF), and in the left BA22 for MFs 8 and 16Hz, compared to those in the right. (3) The activation and propagation features emphasized at least four different types of temporal processing. (4) A sequential activation of PAC, SAC and BA22 areas was clearly visible at all MFs, while other auditory areas may be more involved in parallel processing upon a stream originating from primary auditory area, which thus acts as a distribution hub. These results suggest that different psychological information is carried by the temporal envelope of sounds relative to the rate of amplitude modulation.
Gens, R.
2017-12-01
With increasing number of experimental and operational satellites in orbit, remote sensing based mapping and monitoring of the dynamic Earth has entered into the realm of `big data'. Just the Landsat series of satellites provide a near continuous archive of 45 years of data. The availability of such spatio-temporal datasets has created opportunities for long-term monitoring diverse features and processes operating on the Earth's terrestrial and aquatic systems. Processes such as erosion, deposition, subsidence, uplift, evapotranspiration, urbanization, land-cover regime shifts can not only be monitored and change can be quantified using time-series data analysis. This unique opportunity comes with new challenges in management, analysis, and visualization of spatio-temporal datasets. Data need to be stored in a user-friendly format, and relevant metadata needs to be recorded, to allow maximum flexibility for data exchange and use. Specific data processing workflows need to be defined to support time-series analysis for specific applications. Value-added data products need to be generated keeping in mind the needs of the end-users, and using best practices in complex data visualization. This presentation systematically highlights the various steps for preparing spatio-temporal remote sensing data for time series analysis. It showcases a prototype workflow for remote sensing based change detection that can be generically applied while preserving the application-specific fidelity of the datasets. The prototype includes strategies for visualizing change over time. This has been exemplified using a time-series of optical and SAR images for visualizing the changing glacial, coastal, and wetland landscapes in parts of Alaska.
A spatio-temporal process data model for characterizing marine disasters
International Nuclear Information System (INIS)
Jiang, B; Gao, T; Zhang, X; Huang, X
2014-01-01
Marine disasters are a more prevalent problem in China than in many other countries. Based on the development of a status quo of China's marine disaster the space-time process model is used. The model uses the ocean's temperature field, salinity field, water density field, surface wind field, wave field and other four-dimensional spatio-temporal quantities. This paper studies that model in detail. This study aims at using the theory to provide support during marine disasters in an effort to prevent or decrease their frequency in the future
Spectro-temporal processing of speech – An information-theoretic framework
DEFF Research Database (Denmark)
Christiansen, Thomas Ulrich; Dau, Torsten; Greenberg, Steven
2007-01-01
Hearing – From Sensory Processing to Perception presents the papers of the latest "International Symposium on Hearing," a meeting held every three years focusing on psychoacoustics and the research of the physiological mechanisms underlying auditory perception. The proceedings provide an up......-to-date report on the status of the field of research into hearing and auditory functions. The 59 chapters treat topics such as: the physiological representation of temporal and spectral stimulus properties as a basis for the perception of modulation patterns, pitch and signal intensity; spatial hearing...
Recovery process of wall condition in KSTAR vacuum vessel after temporal machine-vent for repair
Energy Technology Data Exchange (ETDEWEB)
Kim, Kwang Pyo, E-mail: kpkim@nfri.er.ke; Hong, Suk-Ho; Lee, Hyunmyung; Song, Jae-in; Jung, Nam-Yong; Lee, Kunsu; Chu, Yong; Kim, Hakkun; Park, Kaprai; Oh, Yeong-Kook
2015-10-15
Highlights: • Efforts have been made to obtain vacuum condition that is essential for the plasma experiments. • For example, the vacuum vessel should be vented to repair in-vessel components such as diagnostic shutter, and PFC damaged by high energy plasma. • Here, we present the recovery process of wall condition in KSTAR after temporal machine-vent for repair. • It is found that an acceptable vacuum condition has been achieved only by plasma based wall conditioning techniques such as baking, GDC, and boronization. • This study was that the proper recovering method of the vacuum condition should be developed according to the severity of the accident. - Abstract: Efforts have been made to obtain vacuum condition that is essential for the plasma experiments. Under certain situations, for example, the vacuum vessel should be vented to repair in-vessel components such as diagnostic shutter, exchange of window for diagnostic equipment, and PFC damaged by high energy plasma. For the quick restart of the campaign, a recovery process was established to make the vacuum condition acceptable for the plasma experiment. In this paper, we present the recovery process of wall condition in KSTAR after temporal machine-vent for repair. It is found that an acceptable vacuum condition has been achieved only by plasma based wall conditioning techniques such as baking, GDC, and boronization. This study was that the proper recovering method of the vacuum condition should be developed according to the severity of the accident.
Siebeneck, Laura K; Cova, Thomas J
2012-09-01
Developing effective evacuation and return-entry plans requires understanding the spatial and temporal dimensions of risk perception experienced by evacuees throughout a disaster event. Using data gathered from the 2008 Cedar Rapids, Iowa Flood, this article explores how risk perception and location influence evacuee behavior during the evacuation and return-entry process. Three themes are discussed: (1) the spatial and temporal characteristics of risk perception throughout the evacuation and return-entry process, (2) the relationship between risk perception and household compliance with return-entry orders, and (3) the role social influences have on the timing of the return by households. The results indicate that geographic location and spatial variation of risk influenced household risk perception and compliance with return-entry plans. In addition, sociodemographic characteristics influenced the timing and characteristics of the return groups. The findings of this study advance knowledge of evacuee behavior throughout a disaster and can inform strategies used by emergency managers throughout the evacuation and return-entry process. © 2012 Society for Risk Analysis.
Temporal Information Processing and Stability Analysis of the MHSN Neuron Model in DDF
Directory of Open Access Journals (Sweden)
Saket Kumar Choudhary
2016-12-01
Full Text Available Implementation of a neuron like information processing structure at hardware level is a burning research problem. In this article, we analyze the modified hybrid spiking neuron model (the MHSN model in distributed delay framework (DDF for hardware level implementation point of view. We investigate its temporal information processing capability in term of inter-spike-interval (ISI distribution. We also perform the stability analysis of the MHSN model, in which, we compute nullclines, steady state solution, eigenvalues corresponding the MHSN model. During phase plane analysis, we notice that the MHSN model generates limit cycle oscillations which is an important phenomenon in many biological processes. Qualitative behavior of these limit cycle does not changes due to the variation in applied input stimulus, however, delay effect the spiking activity and duration of cycle get altered.
McElree, Brian; Carrasco, Marisa
2012-01-01
Feature and conjunction searches have been argued to delineate parallel and serial operations in visual processing. The authors evaluated this claim by examining the temporal dynamics of the detection of features and conjunctions. The 1st experiment used a reaction time (RT) task to replicate standard mean RT patterns and to examine the shapes of the RT distributions. The 2nd experiment used the response-signal speed–accuracy trade-off (SAT) procedure to measure discrimination (asymptotic detection accuracy) and detection speed (processing dynamics). Set size affected discrimination in both feature and conjunction searches but affected detection speed only in the latter. Fits of models to the SAT data that included a serial component overpredicted the magnitude of the observed dynamics differences. The authors concluded that both features and conjunctions are detected in parallel. Implications for the role of attention in visual processing are discussed. PMID:10641310
Hourly temporal distribution of wind
Deligiannis, Ilias; Dimitriadis, Panayiotis; Koutsoyiannis, Demetris
2016-04-01
The wind process is essential for hydrometeorology and additionally, is one of the basic renewable energy resources. Most stochastic forecast models are limited up to daily scales disregarding the hourly scale which is significant for renewable energy management. Here, we analyze hourly wind timeseries giving emphasis on the temporal distribution of wind within the day. We finally present a periodic model based on statistical as well as hydrometeorological reasoning that shows good agreement with data. Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.
Stochastic processes an introduction
Jones, Peter Watts
2009-01-01
Some Background on ProbabilityIntroduction Probability Conditional probability and independence Discrete random variables Continuous random variables Mean and variance Some standard discrete probability distributions Some standard continuous probability distributions Generating functions Conditional expectationSome Gambling ProblemsGambler's ruin Probability of ruin Some numerical simulations Duration of the game Some variations of gambler's ruinRandom WalksIntroduction Unrestricted random walks The probability distribution after n steps First returns of the symmetric random walkMarkov ChainsS
Schillinger, Dominik
2013-07-01
The method of separation can be used as a non-parametric estimation technique, especially suitable for evolutionary spectral density functions of uniformly modulated and strongly narrow-band stochastic processes. The paper at hand provides a consistent derivation of method of separation based spectrum estimation for the general multi-variate and multi-dimensional case. The validity of the method is demonstrated by benchmark tests with uniformly modulated spectra, for which convergence to the analytical solution is demonstrated. The key advantage of the method of separation is the minimization of spectral dispersion due to optimum time- or space-frequency localization. This is illustrated by the calibration of multi-dimensional and multi-variate geometric imperfection models from strongly narrow-band measurements in I-beams and cylindrical shells. Finally, the application of the method of separation based estimates for the stochastic buckling analysis of the example structures is briefly discussed. © 2013 Elsevier Ltd.