Bivariate discrete Linnik distribution
Directory of Open Access Journals (Sweden)
Davis Antony Mundassery
2014-10-01
Full Text Available Christoph and Schreiber (1998a studied the discrete analogue of positive Linnik distribution and obtained its characterizations using survival function. In this paper, we introduce a bivariate form of the discrete Linnik distribution and study its distributional properties. Characterizations of the bivariate distribution are obtained using compounding schemes. Autoregressive processes are developed with marginals follow the bivariate discrete Linnik distribution.
The compaction of a random distribution of metal cylinders by the discrete element method
DEFF Research Database (Denmark)
Redanz, Pia; Fleck, N. A.
2001-01-01
The cold compaction of a 2D random distribution of metal circular cylinders has been investigated numerically by the discrete element method. Each cylindrical particle is located by a node at its centre and the plastic indentation of the contacts between neighbouring particles is represented by non...... takes place. leading to yield surfaces of similar shape but about half the size of that found for affine motion, as reported in [J. Mech. Phys. Solids 40 (1992) 1139 43 (1995) 1409; 47 (1999) 785]. An increase in the level of inter-particle friction leads to a reduction in the degree of local particle...... rearrangement: the relative displacement of particle centres in the network is more closely represented by affine motion for the case of sticking contacts than frictionless contacts. The discrete element calculations suggest that the yield surfaces for sticking contacts are similar in shape to those...
A discrete fractional random transform
Liu, Zhengjun; Zhao, Haifa; Liu, Shutian
2006-01-01
We propose a discrete fractional random transform based on a generalization of the discrete fractional Fourier transform with an intrinsic randomness. Such discrete fractional random transform inheres excellent mathematical properties of the fractional Fourier transform along with some fantastic features of its own. As a primary application, the discrete fractional random transform has been used for image encryption and decryption.
Discrete Pearson distributions
Energy Technology Data Exchange (ETDEWEB)
Bowman, K.O. [Oak Ridge National Lab., TN (United States); Shenton, L.R. [Georgia Univ., Athens, GA (United States); Kastenbaum, M.A. [Kastenbaum (M.A.), Basye, VA (United States)
1991-11-01
These distributions are generated by a first order recursive scheme which equates the ratio of successive probabilities to the ratio of two corresponding quadratics. The use of a linearized form of this model will produce equations in the unknowns matched by an appropriate set of moments (assumed to exist). Given the moments we may find valid solutions. These are two cases; (1) distributions defined on the non-negative integers (finite or infinite) and (2) distributions defined on negative integers as well. For (1), given the first four moments, it is possible to set this up as equations of finite or infinite degree in the probability of a zero occurrence, the sth component being a product of s ratios of linear forms in this probability in general. For (2) the equation for the zero probability is purely linear but may involve slowly converging series; here a particular case is the discrete normal. Regions of validity are being studied. 11 refs.
Zhu, P. Y.
1991-01-01
The effective-medium approximation is applied to investigate scattering from a half-space of randomly and densely distributed discrete scatterers. Starting from vector wave equations, an approximation, called effective-medium Born approximation, a particular way, treating Green's functions, and special coordinates, of which the origin is set at the field point, are used to calculate the bistatic- and back-scatterings. An analytic solution of backscattering with closed form is obtained and it shows a depolarization effect. The theoretical results are in good agreement with the experimental measurements in the cases of snow, multi- and first-year sea-ice. The root product ratio of polarization to depolarization in backscattering is equal to 8; this result constitutes a law about polarized scattering phenomena in the nature.
Fast Generation of Discrete Random Variables
Directory of Open Access Journals (Sweden)
George Marsaglia
2004-07-01
Full Text Available We describe two methods and provide C programs for generating discrete random variables with functions that are simple and fast, averaging ten times as fast as published methods and more than five times as fast as the fastest of those. We provide general procedures for implementing the two methods, as well as specific procedures for three of the most important discrete distributions: Poisson, binomial and hypergeometric.
Exponential-modified discrete Lindley distribution.
Yilmaz, Mehmet; Hameldarbandi, Monireh; Acik Kemaloglu, Sibel
2016-01-01
In this study, we have considered a series system composed of stochastically independent M-component where M is a random variable having the zero truncated modified discrete Lindley distribution. This distribution is newly introduced by transforming on original parameter. The properties of the distribution of the lifetime of above system have been examined under the given circumstances and also parameters of this new lifetime distribution are estimated by using moments, maximum likelihood and EM-algorithm.
NAFASS: Discrete spectroscopy of random signals
Energy Technology Data Exchange (ETDEWEB)
Nigmatullin, R.R., E-mail: nigmat@knet.r [Institute of Physics, Kazan (Volga Region) Federal University, Kremlevskaya str.18, Kazan, Tatarstan 420008 (Russian Federation); Osokin, S.I. [Institute of Physics, Kazan (Volga Region) Federal University, Kremlevskaya str.18, Kazan, Tatarstan 420008 (Russian Federation); Toboev, V.A. [Department of Mathematics, Chuvash State University, Moskovskiy pr., 15, Cheboksary 428015 (Russian Federation)
2011-04-15
Research highlights: The successful solution of the Prony's problem has been obtained. It means that for any random signal its amplitude-frequency response can be found. This solution opens quite new possibilities in creation of new discrete spectroscopy in analysis of different nanoscopic and intermolecular signals. Real NIR spectra and biological data were considered and analyzed as examples. The conception of the pseudo-ergodic noise is introduced. It helps to fit the auto-correlation function that is related to remnant function. The three basic principles of the fluctuation metrology are formulated. - Abstract: In this paper we suggest a new discrete spectroscopy for analysis of random signals and fluctuations. This discrete spectroscopy is based on successful solution of the modified Prony's problem for the strongly-correlated random sequences. As opposed to the general Prony's problem where the set of frequencies is supposed to be unknown in the new approach suggested the distribution of the unknown frequencies can be found for the strongly-correlated random sequences. Preliminary information about the frequency distribution facilitates the calculations and attaches an additional stability in the presence of a noise. This spectroscopy uses only the informative-significant frequency band that helps to fit the given signal with high accuracy. It means that any random signal measured in t-domain can be 'read' in terms of its amplitude-frequency response (AFR) without model assumptions related to the behavior of this signal in the frequency region. The method overcomes some essential drawbacks of the conventional Prony's method and can be determined as the non-orthogonal amplitude frequency analysis of the smoothed sequences (NAFASS). In this paper we outline the basic principles of the NAFASS procedure and show its high potential possibilities based on analysis of some actual NIR data. The AFR obtained serves as a specific
Succinct Sampling from Discrete Distributions
DEFF Research Database (Denmark)
Bringmann, Karl; Larsen, Kasper Green
2013-01-01
We revisit the classic problem of sampling from a discrete distribution: Given n non-negative w-bit integers x_1,...,x_n, the task is to build a data structure that allows sampling i with probability proportional to x_i. The classic solution is Walker's alias method that takes, when implemented...... requirement of the classic solution for a fundamental sampling problem, on the other hand, they provide the strongest known separation between the systematic and non-systematic case for any data structure problem. Finally, we also believe our upper bounds are practically efficient and simpler than Walker...... on a Word RAM, O(n) preprocessing time, O(1) expected query time for one sample, and n(w+2 lg n+o(1)) bits of space. Using the terminology of succinct data structures, this solution has redundancy 2n lg n+o(n) bits, i.e., it uses 2n lg n+o(n) bits in addition to the information theoretic minimum required...
Rights, Jason D; Sterba, Sonya K
2016-11-01
Multilevel data structures are common in the social sciences. Often, such nested data are analysed with multilevel models (MLMs) in which heterogeneity between clusters is modelled by continuously distributed random intercepts and/or slopes. Alternatively, the non-parametric multilevel regression mixture model (NPMM) can accommodate the same nested data structures through discrete latent class variation. The purpose of this article is to delineate analytic relationships between NPMM and MLM parameters that are useful for understanding the indirect interpretation of the NPMM as a non-parametric approximation of the MLM, with relaxed distributional assumptions. We define how seven standard and non-standard MLM specifications can be indirectly approximated by particular NPMM specifications. We provide formulas showing how the NPMM can serve as an approximation of the MLM in terms of intraclass correlation, random coefficient means and (co)variances, heteroscedasticity of residuals at level 1, and heteroscedasticity of residuals at level 2. Further, we discuss how these relationships can be useful in practice. The specific relationships are illustrated with simulated graphical demonstrations, and direct and indirect interpretations of NPMM classes are contrasted. We provide an R function to aid in implementing and visualizing an indirect interpretation of NPMM classes. An empirical example is presented and future directions are discussed. © 2016 The British Psychological Society.
Discrete Painlev\\'e equations and random matrix averages
Forrester, P. J.; Witte, N. S.
2003-01-01
The $\\tau$-function theory of Painlev\\'e systems is used to derive recurrences in the rank $n$ of certain random matrix averages over U(n). These recurrences involve auxilary quantities which satisfy discrete Painlev\\'e equations. The random matrix averages include cases which can be interpreted as eigenvalue distributions at the hard edge and in the bulk of matrix ensembles with unitary symmetry. The recurrences are illustrated by computing the value of a sequence of these distributions as $...
Discrete optimization problems with random cost elements
Ghosh, D.; Das, S.
2000-01-01
In a general class of discrete optimization problems, some of the elements mayhave random costs associated with them. In such a situation, the notion of optimalityneeds to be suitably modified. In this work we define an optimal solutionto be a feasible solution with the minimum risk. We focus on the
Entropy power inequality for a family of discrete random variables
Sharma, Naresh; Muthukrishnan, Siddharth
2010-01-01
It is known that the Entropy Power Inequality (EPI) always holds if the random variables have density. Not much work has been done to identify discrete distributions for which the inequality holds with the differential entropy replaced by the discrete entropy. Harremo\\"{e}s and Vignat showed that it holds for the pair (B(m,p), B(n,p)), m,n \\in \\mathbb{N}, (where B(n,p) is a Binomial distribution with n trials each with success probability p) for p = 0.5. In this paper, we considerably expand the set of Binomial distributions for which the inequality holds and, in particular, identify n_0(p) such that for all m,n \\geq n_0(p), the EPI holds for (B(m,p), B(n,p)). We further show that the EPI holds for the discrete random variables that can be expressed as the sum of n independent identical distributed (IID) discrete random variables for large n.
Energy Technology Data Exchange (ETDEWEB)
Mishchenko, Michael I., E-mail: michael.i.mishchenko@nasa.gov [NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY 10025 (United States); Dlugach, Janna M. [Main Astronomical Observatory of the National Academy of Sciences of Ukraine, 27 Zabolotny Str., 03680, Kyiv (Ukraine); Yurkin, Maxim A. [Voevodsky Institute of Chemical Kinetics and Combustion, SB RAS, Institutskaya str. 3, 630090 Novosibirsk (Russian Federation); Novosibirsk State University, Pirogova 2, 630090 Novosibirsk (Russian Federation); Bi, Lei [Department of Atmospheric Sciences, Texas A& M University, College Station, TX 77843 (United States); Cairns, Brian [NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY 10025 (United States); Liu, Li [NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY 10025 (United States); Columbia University, 2880 Broadway, New York, NY 10025 (United States); Panetta, R. Lee [Department of Atmospheric Sciences, Texas A& M University, College Station, TX 77843 (United States); Travis, Larry D. [NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY 10025 (United States); Yang, Ping [Department of Atmospheric Sciences, Texas A& M University, College Station, TX 77843 (United States); Zakharova, Nadezhda T. [Trinnovim LLC, 2880 Broadway, New York, NY 10025 (United States)
2016-05-16
A discrete random medium is an object in the form of a finite volume of a vacuum or a homogeneous material medium filled with quasi-randomly and quasi-uniformly distributed discrete macroscopic impurities called small particles. Such objects are ubiquitous in natural and artificial environments. They are often characterized by analyzing theoretically the results of laboratory, in situ, or remote-sensing measurements of the scattering of light and other electromagnetic radiation. Electromagnetic scattering and absorption by particles can also affect the energy budget of a discrete random medium and hence various ambient physical and chemical processes. In either case electromagnetic scattering must be modeled in terms of appropriate optical observables, i.e., quadratic or bilinear forms in the field that quantify the reading of a relevant optical instrument or the electromagnetic energy budget. It is generally believed that time-harmonic Maxwell’s equations can accurately describe elastic electromagnetic scattering by macroscopic particulate media that change in time much more slowly than the incident electromagnetic field. However, direct solutions of these equations for discrete random media had been impracticable until quite recently. This has led to a widespread use of various phenomenological approaches in situations when their very applicability can be questioned. Recently, however, a new branch of physical optics has emerged wherein electromagnetic scattering by discrete and discretely heterogeneous random media is modeled directly by using analytical or numerically exact computer solutions of the Maxwell equations. Therefore, the main objective of this Report is to formulate the general theoretical framework of electromagnetic scattering by discrete random media rooted in the Maxwell–Lorentz electromagnetics and discuss its immediate analytical and numerical consequences. Starting from the microscopic Maxwell–Lorentz equations, we trace the development
Random discrete Schroedinger operators from random matrix theory
Energy Technology Data Exchange (ETDEWEB)
Breuer, Jonathan [Institute of Mathematics, Hebrew University of Jerusalem, Jerusalem 91904 (Israel); Forrester, Peter J [Department of Mathematics and Statistics, University of Melbourne, Parkville, Vic 3010 (Australia); Smilansky, Uzy [Department of Physics of Complex Systems, Weizmann Institute, Rehovot 76100 (Israel)
2007-02-02
We investigate random, discrete Schroedinger operators which arise naturally in the theory of random matrices, and depend parametrically on Dyson's Coulomb gas inverse temperature {beta}. They are similar to the class of 'critical' random Schroedinger operators with random potentials which diminish as vertical bar x vertical bar{sup -1/2}. We show that as a function of {beta} they undergo a transition from a regime of (power-law) localized eigenstates with a pure point spectrum for {beta} < 2 to a regime of extended states with a singular continuous spectrum for {beta} {>=} 2. (fast track communication)
Semiparametric Bayesian Estimation of Random Coefficients Discrete Choice Models
Tchumtchoua, Sylvie; Dey, Dipak
2007-01-01
Heterogeneity in choice models is typically assumed to have a normal distribution in both Bayesian and classical setups. In this paper, we propose a semiparametric Bayesian framework for the analysis of random coefficients discrete choice models that can be applied to both individual as well as aggregate data. Heterogeneity is modeled using a Dirichlet process prior which varies with consumers characteristics through covariates. We develop a Markov chain Monte Carlo algorithm for fitting such...
Generation and monitoring of a discrete stable random process
Hopcraft, K I; Matthews, J O
2002-01-01
A discrete stochastic process with stationary power law distribution is obtained from a death-multiple immigration population model. Emigrations from the population form a random series of events which are monitored by a counting process with finite-dynamic range and response time. It is shown that the power law behaviour of the population is manifested in the intermittent behaviour of the series of events. (letter to the editor)
A Novel Method for Increasing the Entropy of a Sequence of Independent, Discrete Random Variables
Directory of Open Access Journals (Sweden)
Mieczyslaw Jessa
2015-10-01
Full Text Available In this paper, we propose a novel method for increasing the entropy of a sequence of independent, discrete random variables with arbitrary distributions. The method uses an auxiliary table and a novel theorem that concerns the entropy of a sequence in which the elements are a bitwise exclusive-or sum of independent discrete random variables.
A note on inconsistent families of discrete multivariate distributions
Ghosh, Sugata
2017-07-05
We construct a d-dimensional discrete multivariate distribution for which any proper subset of its components belongs to a specific family of distributions. However, the joint d-dimensional distribution fails to belong to that family and in other words, it is ‘inconsistent’ with the distribution of these subsets. We also address preservation of this ‘inconsistency’ property for the symmetric Binomial distribution, and some discrete distributions arising from the multivariate discrete normal distribution.
Distributed discrete event simulation. Final report
Energy Technology Data Exchange (ETDEWEB)
De Vries, R.C. [Univ. of New Mexico, Albuquerque, NM (United States). EECE Dept.
1988-02-01
The presentation given here is restricted to discrete event simulation. The complexity of and time required for many present and potential discrete simulations exceeds the reasonable capacity of most present serial computers. The desire, then, is to implement the simulations on a parallel machine. However, certain problems arise in an effort to program the simulation on a parallel machine. In one category of methods deadlock care arise and some method is required to either detect deadlock and recover from it or to avoid deadlock through information passing. In the second category of methods, potentially incorrect simulations are allowed to proceed. If the situation is later determined to be incorrect, recovery from the error must be initiated. In either case, computation and information passing are required which would not be required in a serial implementation. The net effect is that the parallel simulation may not be much better than a serial simulation. In an effort to determine alternate approaches, important papers in the area were reviewed. As a part of that review process, each of the papers was summarized. The summary of each paper is presented in this report in the hopes that those doing future work in the area will be able to gain insight that might not otherwise be available, and to aid in deciding which papers would be most beneficial to pursue in more detail. The papers are broken down into categories and then by author. Conclusions reached after examining the papers and other material, such as direct talks with an author, are presented in the last section. Also presented there are some ideas that surfaced late in the research effort. These promise to be of some benefit in limiting information which must be passed between processes and in better understanding the structure of a distributed simulation. Pursuit of these ideas seems appropriate.
A discrete random walk on the hypercube
Zhang, Jingyuan; Xiang, Yonghong; Sun, Weigang
2018-03-01
In this paper, we study the scaling for mean first-passage time (MFPT) of random walks on the hypercube and obtain a closed-form formula for the MFPT over all node pairs. We also determine the exponent of scaling efficiency characterizing the random walks and compare it with those of the existing networks. Finally we study the random walks on the hypercube with a located trap and provide a solution of the Kirchhoff index of the hypercube.
Discrete random signal processing and filtering primer with Matlab
Poularikas, Alexander D
2013-01-01
Engineers in all fields will appreciate a practical guide that combines several new effective MATLAB® problem-solving approaches and the very latest in discrete random signal processing and filtering.Numerous Useful Examples, Problems, and Solutions - An Extensive and Powerful ReviewWritten for practicing engineers seeking to strengthen their practical grasp of random signal processing, Discrete Random Signal Processing and Filtering Primer with MATLAB provides the opportunity to doubly enhance their skills. The author, a leading expert in the field of electrical and computer engineering, offe
Random discrete Morse theory and a new library of triangulations
DEFF Research Database (Denmark)
Benedetti, Bruno; Lutz, Frank Hagen
2014-01-01
We introduce random discrete Morse theory as a computational scheme to measure the complexity of a triangulation. The idea is to try to quantify the frequency of discrete Morse matchings with few critical cells. Our measure will depend on the topology of the space, but also on how nicely the space...... is triangulated. The scheme we propose looks for optimal discrete Morse functions with an elementary random heuristic. Despite its naiveté, this approach turns out to be very successful even in the case of huge inputs. In our view, the existing libraries of examples in computational topology are “too easy......” for testing algorithms based on discrete Morse theory. We propose a new library containing more complicated (and thus more meaningful) test examples....
Nobile, Fabio
2015-01-07
We consider a general problem F(u, y) = 0 where u is the unknown solution, possibly Hilbert space valued, and y a set of uncertain parameters. We specifically address the situation in which the parameterto-solution map u(y) is smooth, however y could be very high (or even infinite) dimensional. In particular, we are interested in cases in which F is a differential operator, u a Hilbert space valued function and y a distributed, space and/or time varying, random field. We aim at reconstructing the parameter-to-solution map u(y) from random noise-free or noisy observations in random points by discrete least squares on polynomial spaces. The noise-free case is relevant whenever the technique is used to construct metamodels, based on polynomial expansions, for the output of computer experiments. In the case of PDEs with random parameters, the metamodel is then used to approximate statistics of the output quantity. We discuss the stability of discrete least squares on random points show convergence estimates both in expectation and probability. We also present possible strategies to select, either a-priori or by adaptive algorithms, sequences of approximating polynomial spaces that allow to reduce, and in some cases break, the curse of dimensionality
A discrete random effects probit model with application to the demand for preventive care.
Deb, P
2001-07-01
I have developed a random effects probit model in which the distribution of the random intercept is approximated by a discrete density. Monte Carlo results show that only three to four points of support are required for the discrete density to closely mimic normal and chi-squared densities and provide unbiased estimates of the structural parameters and the variance of the random intercept. The empirical application shows that both observed family characteristics and unobserved family-level heterogeneity are important determinants of the demand for preventive care. Copyright 2001 John Wiley & Sons, Ltd.
A practical test for the choice of mixing distribution in discrete choice models
DEFF Research Database (Denmark)
Fosgerau, Mogens; Bierlaire, Michel
2007-01-01
The choice of a specific distribution for random parameters of discrete choice models is a critical issue in transportation analysis. Indeed, various pieces of research have demonstrated that an inappropriate choice of the distribution may lead to serious bias in model forecast and in the estimated...
Angular Distributions of Discrete Mesoscale Mapping Functions
Kroszczyński, Krzysztof
2015-08-01
The paper presents the results of analyses of numerical experiments concerning GPS signal propagation delays in the atmosphere and the discrete mapping functions defined on their basis. The delays were determined using data from the mesoscale non-hydrostatic weather model operated in the Centre of Applied Geomatics, Military University of Technology. A special attention was paid to investigating angular characteristics of GPS slant delays for low angles of elevation. The investigation proved that the temporal and spatial variability of the slant delays depends to a large extent on current weather conditions.
Decomposing a Utility Function Based on Discrete Distribution Independence
DEFF Research Database (Denmark)
He, Ying; Dyer, James; Butler, John
2014-01-01
For two-attribute decision-making problems, the multilinear utility model cannot be applied when the risk aversion on one attribute depends on the level of the other attribute. We propose a family of general preference conditions called nth-degree discrete distribution independence that can accom...
A Discrete Model for HIV Infection with Distributed Delay
Directory of Open Access Journals (Sweden)
Brahim EL Boukari
2014-01-01
Full Text Available We give a consistent discretization of a continuous model of HIV infection, with distributed time delays to express the lag between the times when the virus enters a cell and when the cell becomes infected. The global stability of the steady states of the model is determined and numerical simulations are presented to illustrate our theoretical results.
On the Discrete-Time Geo/G/1 Queue with Vacations in Random Environment
Directory of Open Access Journals (Sweden)
Jianjun Li
2016-01-01
Full Text Available A discrete-time Geo/G/1 queue with vacations in random environment is analyzed. Using the method of supplementary variable, we give the probability generating function (PGF of the stationary queue length distribution at arbitrary epoch. The PGF of the stationary sojourn time distribution is also derived. And we present the various performance measures such as mean number of customers in the system, mean length of the type-i cycle, and mean time that the system resides in phase 0. In addition, we show that the M/G/1 queue with vacations in random environment can be approximated by its discrete-time counterpart. Finally, we present some special cases of the model and numerical examples.
Miller, B.; Blin, A. H.; Dworzecka, M.; Griffin, J. J.
1984-08-01
The correspondence between a random walk process, comprising discrete steps on the integer values of ( N, Z) and the Markovian discrete master equation which it uniquely specifies is reviewed. Differences between the random walk distribution calculated at integral values of the step count q and that of its Markovian master equation at corresponding values of the (continuous) time parameter ( are studied for a certain soluble two-dimensional example. The mean values of N and Z calculated from the random walk and Markovian master equation agree precisely. The second and higher moments which are also linear in the distribution function agree in leading order. But in this case, the N, Z correlation width vanishes identically for the master equation, and is finite in general for the random walk, while the widths of the distributions (which are bilinear in the distribution function) may differ even in leading order. The relevance of these differences to data measured against some independent variable (e.g. total kinetic energy loss in a heavyion collision), which is in fact uniquely related neither to q nor to t, is discussed. Since both random walk and master equations are currently used to analyze the phenomenology of nuclear heavy-ion collisions, the fact that they offer different predictions, and that depending upon the physical circumstances either (or neither) may be the correct description, recommends the development of a more rational basis for choosing between them.
Electromagnetic scattering by spheroidal volumes of discrete random medium
Mishchenko, Michael I.; Dlugach, Janna M.
2017-10-01
We use the superposition T-matrix method to compare the far-field scattering matrices generated by spheroidal and spherical volumes of discrete random medium having the same volume and populated by identical spherical particles. Our results fully confirm the robustness of the previously identified coherent and diffuse scattering regimes and associated optical phenomena exhibited by spherical particulate volumes and support their explanation in terms of the interference phenomenon coupled with the order-of-scattering expansion of the far-field Foldy equations. We also show that increasing nonsphericity of particulate volumes causes discernible (albeit less pronounced) optical effects in forward and backscattering directions and explain them in terms of the same interference/multiple-scattering phenomenon.
Interacting discrete Markov processes with power-law probability distributions
Ridley, Kevin D.; Jakeman, Eric
2017-09-01
During recent years there has been growing interest in the occurrence of long-tailed distributions, also known as heavy-tailed or fat-tailed distributions, which can exhibit power-law behaviour and often characterise physical systems that undergo very large fluctuations. In this paper we show that the interaction between two discrete Markov processes naturally generates a time-series characterised by such a distribution. This possibility is first demonstrated by numerical simulation and then confirmed by a mathematical analysis that enables the parameter range over which the power-law occurs to be quantified. The results are supported by comparison of numerical results with theoretical predictions and general conclusions are drawn regarding mechanisms that can cause this behaviour.
Discrete population balance models of random agglomeration and cleavage in polymer pyrolysis
Directory of Open Access Journals (Sweden)
John E. J. Staggs
2017-05-01
Full Text Available The processes of random agglomeration and cleavage (both of which are important for the development of new models of polymer combustion, but are also applicable in a wide range of fields including atmospheric physics, radiation modelling and astrophysics are analysed using population balance methods. The evolution of a discrete distribution of particles is considered within this framework, resulting in a set of ordinary differential equations for the individual particle concentrations. Exact solutions for these equations are derived, together with moment generating functions. Application of the discrete Laplace transform (analogous to the Z-transform is found to be effective in these problems, providing both exact solutions for particle concentrations and moment generating functions. The combined agglomeration-cleavage problem is also considered. Unfortunately, it has been impossible to find an exact solution for the full problem, but a stable steady state has been identified and computed.
Directory of Open Access Journals (Sweden)
Dongyan Chen
2015-01-01
Full Text Available This paper is concerned with the optimal Kalman filtering problem for a class of discrete stochastic systems with multiplicative noises and random two-step sensor delays. Three Bernoulli distributed random variables with known conditional probabilities are introduced to characterize the phenomena of the random two-step sensor delays which may happen during the data transmission. By using the state augmentation approach and innovation analysis technique, an optimal Kalman filter is constructed for the augmented system in the sense of the minimum mean square error (MMSE. Subsequently, the optimal Kalman filtering is derived for corresponding augmented system in initial instants. Finally, a simulation example is provided to demonstrate the feasibility and effectiveness of the proposed filtering method.
Multi-threaded, discrete event simulation of distributed computing systems
Legrand, Iosif; MONARC Collaboration
2001-10-01
The LHC experiments have envisaged computing systems of unprecedented complexity, for which is necessary to provide a realistic description and modeling of data access patterns, and of many jobs running concurrently on large scale distributed systems and exchanging very large amounts of data. A process oriented approach for discrete event simulation is well suited to describe various activities running concurrently, as well the stochastic arrival patterns specific for such type of simulation. Threaded objects or "Active Objects" can provide a natural way to map the specific behaviour of distributed data processing into the simulation program. The simulation tool developed within MONARC is based on Java (TM) technology which provides adequate tools for developing a flexible and distributed process oriented simulation. Proper graphics tools, and ways to analyze data interactively, are essential in any simulation project. The design elements, status and features of the MONARC simulation tool are presented. The program allows realistic modeling of complex data access patterns by multiple concurrent users in large scale computing systems in a wide range of possible architectures, from centralized to highly distributed. Comparison between queuing theory and realistic client-server measurements is also presented.
Process of random distributions : classification and prediction ...
African Journals Online (AJOL)
Dirichlet random distribution. The parameter of this process can be the distribution of any usual such as the (multifractional) Brownian motion. We also extend Kraft random distribution to the continuous time case. We give an application in ...
A Discrete Group Search Optimizer for Hybrid Flowshop Scheduling Problem with Random Breakdown
National Research Council Canada - National Science Library
Cui, Zhe; Gu, Xingsheng
2014-01-01
...) together with a discrete group search optimizer algorithm (DGSO). In particular, two different working cases, preempt-resume case, and preempt-repeat case are considered under random breakdown...
Migliorati, G.
2013-05-30
In this work we consider the random discrete L^2 projection on polynomial spaces (hereafter RDP) for the approximation of scalar quantities of interest (QOIs) related to the solution of a partial differential equation model with random input parameters. In the RDP technique the QOI is first computed for independent samples of the random input parameters, as in a standard Monte Carlo approach, and then the QOI is approximated by a multivariate polynomial function of the input parameters using a discrete least squares approach. We consider several examples including the Darcy equations with random permeability, the linear elasticity equations with random elastic coefficient, and the Navier--Stokes equations in random geometries and with random fluid viscosity. We show that the RDP technique is well suited to QOIs that depend smoothly on a moderate number of random parameters. Our numerical tests confirm the theoretical findings in [G. Migliorati, F. Nobile, E. von Schwerin, and R. Tempone, Analysis of the Discrete $L^2$ Projection on Polynomial Spaces with Random Evaluations, MOX report 46-2011, Politecnico di Milano, Milano, Italy, submitted], which have shown that, in the case of a single uniformly distributed random parameter, the RDP technique is stable and optimally convergent if the number of sampling points is proportional to the square of the dimension of the polynomial space. Here optimality means that the weighted $L^2$ norm of the RDP error is bounded from above by the best $L^\\\\infty$ error achievable in the given polynomial space, up to logarithmic factors. In the case of several random input parameters, the numerical evidence indicates that the condition on quadratic growth of the number of sampling points could be relaxed to a linear growth and still achieve stable and optimal convergence. This makes the RDP technique very promising for moderately high dimensional uncertainty quantification.
Mandal, Pranab K.; Ghosh, D.; Das, S
2005-01-01
In this paper we attempt to find least risk solutions for stochastic discrete optimization problems (SDOP) with multiple random elements, where the feasibility of a solution does not depend on the particular values the random elements in the problem take. While the optimal solution, for a linear
Fuzzy random variables — II. Algorithms and examples for the discrete case
Kwakernaak, H.
1979-01-01
The results obtained in part I of the paper are specialized to the case of discrete fuzzy random variables. A more intuitive interpretation is given of the notion of fuzzy random variables. Algorithms are derived for determining expectations, fuzzy probabilities, fuzzy conditional expectations and
Erin L. Landguth; Michael K. Schwartz
2014-01-01
One of the most pressing issues in spatial genetics concerns sampling. Traditionally, substructure and gene flow are estimated for individuals sampled within discrete populations. Because many species may be continuously distributed across a landscape without discrete boundaries, understanding sampling issues becomes paramount. Given large-scale, geographically broad...
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Hideki Katagiri
2017-10-01
Full Text Available This paper considers linear programming problems (LPPs where the objective functions involve discrete fuzzy random variables (fuzzy set-valued discrete random variables. New decision making models, which are useful in fuzzy stochastic environments, are proposed based on both possibility theory and probability theory. In multi-objective cases, Pareto optimal solutions of the proposed models are newly defined. Computational algorithms for obtaining the Pareto optimal solutions of the proposed models are provided. It is shown that problems involving discrete fuzzy random variables can be transformed into deterministic nonlinear mathematical programming problems which can be solved through a conventional mathematical programming solver under practically reasonable assumptions. A numerical example of agriculture production problems is given to demonstrate the applicability of the proposed models to real-world problems in fuzzy stochastic environments.
Analysis of hybrid Petri nets with random discrete events
Ghasemieh, Hamed
2017-01-01
More and more, our society and economy rely on the correct operation of, often hidden, critical infrastructures. These infrastructures such as the power grid and water and gas distribution networks, play an important role in our everyday life. Continuous supply of services from these assets is
Dlugach, Janna M.; Mishchenko, Michael I.
2017-01-01
In this paper, we discuss some aspects of numerical modeling of electromagnetic scattering by discrete random medium by using numerically exact solutions of the macroscopic Maxwell equations. Typical examples of such media are clouds of interstellar dust, clouds of interplanetary dust in the Solar system, dusty atmospheres of comets, particulate planetary rings, clouds in planetary atmospheres, aerosol particles with numerous inclusions and so on. Our study is based on the results of extensive computations of different characteristics of electromagnetic scattering obtained by using the superposition T-matrix method which represents a direct computer solver of the macroscopic Maxwell equations for an arbitrary multisphere configuration. As a result, in particular, we clarify the range of applicability of the low-density theories of radiative transfer and coherent backscattering as well as of widely used effective-medium approximations.
Modelling a reliability system governed by discrete phase-type distributions
Energy Technology Data Exchange (ETDEWEB)
Ruiz-Castro, Juan Eloy [Departamento de Estadistica e Investigacion Operativa, Universidad de Granada, 18071 Granada (Spain)], E-mail: jeloy@ugr.es; Perez-Ocon, Rafael [Departamento de Estadistica e Investigacion Operativa, Universidad de Granada, 18071 Granada (Spain)], E-mail: rperezo@ugr.es; Fernandez-Villodre, Gemma [Departamento de Estadistica e Investigacion Operativa, Universidad de Granada, 18071 Granada (Spain)
2008-11-15
We present an n-system with one online unit and the others in cold standby. There is a repairman. When the online fails it goes to repair, and instantaneously a standby unit becomes the online one. The operational and repair times follow discrete phase-type distributions. Given that any discrete distribution defined on the positive integers is a discrete phase-type distribution, the system can be considered a general one. A model with unlimited number of units is considered for approximating a system with a great number of units. We show that the process that governs the system is a quasi-birth-and-death process. For this system, performance reliability measures; the up and down periods, and the involved costs are calculated in a matrix and algorithmic form. We show that the discrete case is not a trivial case of the continuous one. The results given in this paper have been implemented computationally with Matlab.
On solving discrete optimization problems with one random element under general regret functions
Ghosh, D.; Mandal, Pranab K.; Das, S
2005-01-01
In this paper we consider the class of stochastic discrete optimization problems in which the feasibility of a solution does not depend on the particular values the random elements in the problem take. Given a regret function, we introduce the concept of the risk associated with a solution, and
A comparison of methods for representing random taste heterogeneity in discrete choice models
DEFF Research Database (Denmark)
Fosgerau, Mogens; Hess, Stephane
2009-01-01
This paper reports the findings of a systematic study using Monte Carlo experiments and a real dataset aimed at comparing the performance of various ways of specifying random taste heterogeneity in a discrete choice model. Specifically, the analysis compares the performance of two recent advanced...
Random matrix theory and discrete moments of the Riemann zeta function
Energy Technology Data Exchange (ETDEWEB)
Hughes, C P [Raymond and Beverly Sackler School of Mathematical Sciences, Tel Aviv University, Tel Aviv 69978 (Israel)
2003-03-28
We calculate the discrete moments of the characteristic polynomial of a random unitary matrix, evaluated a small distance away from an eigenangle. Such results allow us to make conjectures about similar moments for the Riemann zeta function, and provide a uniform approach to understanding moments of the zeta function and its derivative.
Bao, Yan; Yang, Taoxi; Lin, Xiaoxiong; Pöppel, Ernst
2016-09-01
Differences of reaction times to specific stimulus configurations are used as indicators of cognitive processing stages. In this classical experimental paradigm, continuous temporal processing is implicitly assumed. Multimodal response distributions indicate, however, discrete time sampling, which is often masked by experimental conditions. Differences in reaction times reflect discrete temporal mechanisms that are pre-semantically implemented and suggested to be based on entrained neural oscillations. © 2016 The Institute of Psychology, Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.
Distributed Submodular Minimization And Motion Coordination Over Discrete State Space
Jaleel, Hassan
2017-09-21
Submodular set-functions are extensively used in large-scale combinatorial optimization problems arising in complex networks and machine learning. While there has been significant interest in distributed formulations of convex optimization, distributed minimization of submodular functions has not received significant attention. Thus, our main contribution is a framework for minimizing submodular functions in a distributed manner. The proposed framework is based on the ideas of Lovasz extension of submodular functions and distributed optimization of convex functions. The framework exploits a fundamental property of submodularity that the Lovasz extension of a submodular function is a convex function and can be computed efficiently. Moreover, a minimizer of a submodular function can be computed by computing the minimizer of its Lovasz extension. In the proposed framework, we employ a consensus based distributed optimization algorithm to minimize set-valued submodular functions as well as general submodular functions defined over set products. We also identify distributed motion coordination in multiagent systems as a new application domain for submodular function minimization. For demonstrating key ideas of the proposed framework, we select a complex setup of the capture the flag game, which offers a variety of challenges relevant to multiagent system. We formulate the problem as a submodular minimization problem and verify through extensive simulations that the proposed framework results in feasible policies for the agents.
Modelling road accident blackspots data with the discrete generalized Pareto distribution.
Prieto, Faustino; Gómez-Déniz, Emilio; Sarabia, José María
2014-10-01
This study shows how road traffic networks events, in particular road accidents on blackspots, can be modelled with simple probabilistic distributions. We considered the number of crashes and the number of fatalities on Spanish blackspots in the period 2003-2007, from Spanish General Directorate of Traffic (DGT). We modelled those datasets, respectively, with the discrete generalized Pareto distribution (a discrete parametric model with three parameters) and with the discrete Lomax distribution (a discrete parametric model with two parameters, and particular case of the previous model). For that, we analyzed the basic properties of both parametric models: cumulative distribution, survival, probability mass, quantile and hazard functions, genesis and rth-order moments; applied two estimation methods of their parameters: the μ and (μ+1) frequency method and the maximum likelihood method; used two goodness-of-fit tests: Chi-square test and discrete Kolmogorov-Smirnov test based on bootstrap resampling; and compared them with the classical negative binomial distribution in terms of absolute probabilities and in models including covariates. We found that those probabilistic models can be useful to describe the road accident blackspots datasets analyzed. Copyright © 2014 Elsevier Ltd. All rights reserved.
A Discrete Group Search Optimizer for Hybrid Flowshop Scheduling Problem with Random Breakdown
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Zhe Cui
2014-01-01
Full Text Available The scheduling problems have been discussed in the literature extensively under the assumption that the machines are permanently available without any breakdown. However, in the real manufacturing environments, the machines could be unavailable inevitably for many reasons. In this paper, the authors introduce the hybrid flowshop scheduling problem with random breakdown (RBHFS together with a discrete group search optimizer algorithm (DGSO. In particular, two different working cases, preempt-resume case, and preempt-repeat case are considered under random breakdown. The proposed DGSO algorithm adopts the vector representation and several discrete operators, such as insert, swap, differential evolution, destruction, and construction in the producers, scroungers, and rangers phases. In addition, an orthogonal test is applied to configure the adjustable parameters in the DGSO algorithm. The computational results in both cases indicate that the proposed algorithm significantly improves the performances compared with other high performing algorithms in the literature.
Bayes Estimation of Change Point in Discrete Maxwell Distribution
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Mayuri Pandya
2011-01-01
Full Text Available A sequence of independent lifetimes X1,…,Xm,Xm+1,…,Xn was observed from Maxwell distribution with reliability r1(t at time t but later, it was found that there was a change in the system at some point of time m and it is reflected in the sequence after Xm by change in reliability r2(t at time t. The Bayes estimators of m, θ1, θ2 are derived under different asymmetric loss functions. The effects of correct and wrong prior information on the Bayes estimates are studied.
Oscillatory Behavior on a Three-Node Neural Network Model with Discrete and Distributed Delays
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Chunhua Feng
2014-01-01
Full Text Available This paper investigates the oscillatory behavior of the solutions for a three-node neural network with discrete and distributed delays. Two theorems are provided to determine the conditions for oscillating solutions of the model. The criteria for selecting the parameters in this network are derived. Some simulation examples are presented to illustrate the effectiveness of the results.
Validity of the formal Edgeworth expansion when the underlying distribution is partly discrete
DEFF Research Database (Denmark)
Jensen, J.L.
1989-01-01
Validity of the formal Edgeworth expansion for the distribution of the statistic √ng(Xn/n, Yn/n) is considered. Here Xn is a continuous variate and Yn is a discrete variate. In general if (Xn, Yn) resemble the sum of i.i.d. variables and the partial derivative of g with respect to the first...
On a random area variable arising in discrete-time queues and compact directed percolation
Kearney, Michael J.
2004-09-01
A well-known discrete-time, single-server queueing system with mean arrival rate lgr and mean departure rate mgr is considered from the perspective of the area, A, swept out by the queue occupation process during a busy period. We determine the exact form of the tail of the distribution, Pr(A > x); in particular, we show that Pr(A > x) ~ Cx-1/4 exp(-Dx1/2) for all rgr \
Energy Technology Data Exchange (ETDEWEB)
Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhou, Xinyang [University of Colorado; Liu, Zhiyuan [University of Colorado; Chen, Lijun [University of Colorado
2017-10-03
This paper considers distribution networks with distributed energy resources and discrete-rate loads, and designs an incentive-based algorithm that allows the network operator and the customers to pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. Four major challenges include: (1) the non-convexity from discrete decision variables, (2) the non-convexity due to a Stackelberg game structure, (3) unavailable private information from customers, and (4) different update frequency from two types of devices. In this paper, we first make convex relaxation for discrete variables, then reformulate the non-convex structure into a convex optimization problem together with pricing/reward signal design, and propose a distributed stochastic dual algorithm for solving the reformulated problem while restoring feasible power rates for discrete devices. By doing so, we are able to statistically achieve the solution of the reformulated problem without exposure of any private information from customers. Stability of the proposed schemes is analytically established and numerically corroborated.
Žukovič, Milan; Hristopulos, Dionissios T.
2009-02-01
A current problem of practical significance is how to analyze large, spatially distributed, environmental data sets. The problem is more challenging for variables that follow non-Gaussian distributions. We show by means of numerical simulations that the spatial correlations between variables can be captured by interactions between 'spins'. The spins represent multilevel discretizations of environmental variables with respect to a number of pre-defined thresholds. The spatial dependence between the 'spins' is imposed by means of short-range interactions. We present two approaches, inspired by the Ising and Potts models, that generate conditional simulations of spatially distributed variables from samples with missing data. Currently, the sampling and simulation points are assumed to be at the nodes of a regular grid. The conditional simulations of the 'spin system' are forced to respect locally the sample values and the system statistics globally. The second constraint is enforced by minimizing a cost function representing the deviation between normalized correlation energies of the simulated and the sample distributions. In the approach based on the Nc-state Potts model, each point is assigned to one of Nc classes. The interactions involve all the points simultaneously. In the Ising model approach, a sequential simulation scheme is used: the discretization at each simulation level is binomial (i.e., ± 1). Information propagates from lower to higher levels as the simulation proceeds. We compare the two approaches in terms of their ability to reproduce the target statistics (e.g., the histogram and the variogram of the sample distribution), to predict data at unsampled locations, as well as in terms of their computational complexity. The comparison is based on a non-Gaussian data set (derived from a digital elevation model of the Walker Lake area, Nevada, USA). We discuss the impact of relevant simulation parameters, such as the domain size, the number of
Directory of Open Access Journals (Sweden)
A. Klemm
1999-01-01
Full Text Available Distributions of basic characteristics of random mappings with a single absorbing center are calculated. Results explain some phenomena occurring in computer simulations of the logistic mapping.
Supervisor Localization: A Top-Down Approach to Distributed Control of Discrete-Event Systems
Cai, K.; Wonham, W. M.
2009-03-01
A purely distributed control paradigm is proposed for discrete-event systems (DES). In contrast to control by one or more external supervisors, distributed control aims to design built-in strategies for individual agents. First a distributed optimal nonblocking control problem is formulated. To solve it, a top-down localization procedure is developed which systematically decomposes an external supervisor into local controllers while preserving optimality and nonblockingness. An efficient localization algorithm is provided to carry out the computation, and an automated guided vehicles (AGV) example presented for illustration. Finally, the 'easiest' and 'hardest' boundary cases of localization are discussed.
Wang, Qingzhu; Chen, Xiaoming; Zhu, Yihai
2017-09-01
Existing image compression and encryption methods have several shortcomings: they have low reconstruction accuracy and are unsuitable for three-dimensional (3D) images. To overcome these limitations, this paper proposes a tensor-based approach adopting tensor compressive sensing and tensor discrete fractional random transform (TDFRT). The source video images are measured by three key-controlled sensing matrices. Subsequently, the resulting tensor image is further encrypted using 3D cat map and the proposed TDFRT, which is based on higher-order singular value decomposition. A multiway projection algorithm is designed to reconstruct the video images. The proposed algorithm can greatly reduce the data volume and improve the efficiency of the data transmission and key distribution. The simulation results validate the good compression performance, efficiency, and security of the proposed algorithm.
Analysis of Discrete L2 Projection on Polynomial Spaces with Random Evaluations
Migliorati, Giovanni
2014-03-05
We analyze the problem of approximating a multivariate function by discrete least-squares projection on a polynomial space starting from random, noise-free observations. An area of possible application of such technique is uncertainty quantification for computational models. We prove an optimal convergence estimate, up to a logarithmic factor, in the univariate case, when the observation points are sampled in a bounded domain from a probability density function bounded away from zero and bounded from above, provided the number of samples scales quadratically with the dimension of the polynomial space. Optimality is meant in the sense that the weighted L2 norm of the error committed by the random discrete projection is bounded with high probability from above by the best L∞ error achievable in the given polynomial space, up to logarithmic factors. Several numerical tests are presented in both the univariate and multivariate cases, confirming our theoretical estimates. The numerical tests also clarify how the convergence rate depends on the number of sampling points, on the polynomial degree, and on the smoothness of the target function. © 2014 SFoCM.
B.M. Craig (Benjamin); J.J. van Busschbach (Jan)
2009-01-01
textabstractABSTRACT: BACKGROUND: To present an episodic random utility model that unifies time trade-off and discrete choice approaches in health state valuation. METHODS: First, we introduce two alternative random utility models (RUMs) for health preferences: the episodic RUM and the more common
Jin, Y. Q.; Kong, J. A.
1984-01-01
The strong fluctuation theory is applied to the study of electromagnetic wave scattering from a layer of random discrete scatterers. The singularity of the dyadic Green's function is taken into account in the calculation of the effective permittivity functions. The correlation functions for the random medium with different scatterer constituents and size distributions are derived. Applying the dyadic Green's function for a two-layer medium and using the bilocal and distorted Born approximations, the first and the second moments of the fields are then calculated. Both the backscattering and bistatic scattering coefficients are obtained, and the former is shown to match favorably with experimental data obtained from snow fields.
Zhang, X; Wu, Z; Zhou, T
2016-01-01
A predator-prey discrete-time model with Holling-IV functional response and distributed delays is investigated in this paper. By using the comparison theorem of the difference equation and some analysis technique, some sufficient conditions are obtained for the permanence of the discrete predator-prey system. Two examples are given to illustrate the feasibility of the obtained result.
Zhou, Bingliang; Zhou, Jianbin; Zhang, Qisheng
2017-10-01
This study aims at investigating the pyrolysis behavior of Camellia sinensis branches by the Discrete Distributed Activation Energy Model (DAEM) and thermogravimetric experiments. Then the Discrete DAEM method is used to describe pyrolysis process of Camellia sinensis branches dominated by 12 characterized reactions. The decomposition mechanism of Camellia sinensis branches and interaction with components are observed. And the reaction at 350.77°C is a significant boundary of the first and second reaction range. The pyrolysis process of Camellia sinensis branches at the heating rate of 10,000°C/min is predicted and provides valuable references for gasification or combustion. The relationship and function between four typical indexes and heating rates from 10 to 10,000°C/min are revealed. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Bindu Abraham
2014-05-01
Full Text Available In this paper we analyze DAR(1/D/s Queue with Discrete Mittag-Leffler [DML(α] as marginal distribution. Simulation study of the sample path of the arrival process is conducted. For this queueing system, the stationary distribution of the system size and the waiting time distribution of an arbitrary packet is obtained with the help of matrix analytic methods and Markov regenerative theory. The quantitative effect of the stationary distribution on system size, waiting time and the autocorrelation function as well as the parameters of the input traffic is illustrated empirically. The model is applied to a real data on the passenger arrivals at a subway bus terminal in Santiago de Chile and is established that the model well suits this data.
Panchuk, Derek; Spittle, Michael; Johnston, Natillie; Spittle, Sharna
2013-06-01
This study examined how practice distribution influenced performance and learning of a discrete sport skill, the Australian Football (AF) handball pass. A secondary aim was to assess whether previous experience playing competitive Australian Football influenced learning. Participants performed the handball 50 times (5 blocks x 10 repetitions) using either a massed (1 sec. between repetitions or distributed (30 sec. between repetitions) practice schedule. Testing consisted of pre-test, acquisition, immediate retention (10 min.), and delayed retention (2 weeks) sessions. Performance accuracy scores improved in the massed practice condition from pre-test to immediate retention and from pre-test to delayed retention. Likewise, performance improved in the distributed practice group from pretest to immediate retention, but scores were not different from pre-test to delayed retention, and decreased from immediate retention to delayed retention. While students with previous AF experience performed better overall, there were no differences between the massed and distributed groups based on experience. Results suggested that, regardless of previous related skill, massed practice of a discrete sport skill may lead to better retention of learning over a two-week period.
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Guitao Zhang
2014-01-01
Full Text Available The advertisement can increase the consumers demand; therefore it is one of the most important marketing strategies in the operations management of enterprises. This paper aims to analyze the impact of advertising investment on a discrete dynamic supply chain network which consists of suppliers, manufactures, retailers, and demand markets associated at different tiers under random demand. The impact of advertising investment will last several planning periods besides the current period due to delay effect. Based on noncooperative game theory, variational inequality, and Lagrange dual theory, the optimal economic behaviors of the suppliers, the manufactures, the retailers, and the consumers in the demand markets are modeled. In turn, the supply chain network equilibrium model is proposed and computed by modified project contraction algorithm with fixed step. The effectiveness of the model is illustrated by numerical examples, and managerial insights are obtained through the analysis of advertising investment in multiple periods and advertising delay effect among different periods.
Le Douget, J E; Fouad, A; Maskani Filali, M; Pyrzowski, J; Le Van Quyen, M
2017-07-01
Epilepsy is a neurological disorder for which the electroencephalogram (EEG) is the most important diagnostic tool. In particular, this diagnosis heavily depends on the detection of interictal (between seizures) paroxysmal epileptic discharges (IPED) in the EEG. This is a time-consuming task requiring significant training and experience. Automatic detection of these EEG patterns would greatly assist visual inspections of human readers. We present a new method, which allows automatic detection of IPED based on discrete wavelet decomposition and a random forest classifier. The algorithm was trained and cross validated using 17 subjects with scalp EEG and 10 subjects with intracranial EEG. The performance of this method reached 62% recall and 26% precision for surface EEG subjects and 63% recall and 53% precision for intracranial EEG subjects. Thus, the method hereby proposed has great potential for diagnosis support in clinical environments.
Raney Distributions and Random Matrix Theory
Forrester, Peter J.; Liu, Dang-Zheng
2015-03-01
Recent works have shown that the family of probability distributions with moments given by the Fuss-Catalan numbers permit a simple parameterized form for their density. We extend this result to the Raney distribution which by definition has its moments given by a generalization of the Fuss-Catalan numbers. Such computations begin with an algebraic equation satisfied by the Stieltjes transform, which we show can be derived from the linear differential equation satisfied by the characteristic polynomial of random matrix realizations of the Raney distribution. For the Fuss-Catalan distribution, an equilibrium problem characterizing the density is identified. The Stieltjes transform for the limiting spectral density of the singular values squared of the matrix product formed from inverse standard Gaussian matrices, and standard Gaussian matrices, is shown to satisfy a variant of the algebraic equation relating to the Raney distribution. Supported on , we show that it too permits a simple functional form upon the introduction of an appropriate choice of parameterization. As an application, the leading asymptotic form of the density as the endpoints of the support are approached is computed, and is shown to have some universal features.
Discrete epidemic models with arbitrary stage distributions and applications to disease control
Hernandez-Ceron, Nancy; Feng, Zhilan; Castillo-Chavez, Carlos
2014-01-01
W. O. Kermack and A. G. McKendrick introduced in their fundamental paper, A Contribution to the Mathematical Theory of Epidemics, published in 1927, a simple deterministic model that captured the qualitative dynamic behavior of single infectious disease outbreaks. A Kermack-McKendrick discrete-time general framework, motivated by the emergence of a multitude of models used to forecast the dynamics of SARS and influenza outbreaks, is introduced in this manuscript. Results that allow us to measure quantitatively the role of classical and general distributions on disease dynamics are presented. The case of the geometric distribution is used to evaluate the impact of waiting-time distributions on epidemiological processes or public health interventions. In short, the geometric distribution is used to set up the baseline or null epidemiological model used to test the relevance of realistic stage-period distribution on the dynamics of single epidemic outbreaks. A final size relationship involving the control reproduction number, a function of transmission parameters and the means of distributions used to model disease or intervention control measures, is computed. Model results and simulations highlight the inconsistencies in forecasting that emerge from the use of specific parametric distributions. Examples, using the geometric, Poisson and binomial distributions, are used to highlight the impact of the choices made in quantifying the risk posed by single outbreaks and the relative importance of various control measures. PMID:23797790
Discrete epidemic models with arbitrary stage distributions and applications to disease control.
Hernandez-Ceron, Nancy; Feng, Zhilan; Castillo-Chavez, Carlos
2013-10-01
W.O. Kermack and A.G. McKendrick introduced in their fundamental paper, A Contribution to the Mathematical Theory of Epidemics, published in 1927, a deterministic model that captured the qualitative dynamic behavior of single infectious disease outbreaks. A Kermack–McKendrick discrete-time general framework, motivated by the emergence of a multitude of models used to forecast the dynamics of epidemics, is introduced in this manuscript. Results that allow us to measure quantitatively the role of classical and general distributions on disease dynamics are presented. The case of the geometric distribution is used to evaluate the impact of waiting-time distributions on epidemiological processes or public health interventions. In short, the geometric distribution is used to set up the baseline or null epidemiological model used to test the relevance of realistic stage-period distribution on the dynamics of single epidemic outbreaks. A final size relationship involving the control reproduction number, a function of transmission parameters and the means of distributions used to model disease or intervention control measures, is computed. Model results and simulations highlight the inconsistencies in forecasting that emerge from the use of specific parametric distributions. Examples, using the geometric, Poisson and binomial distributions, are used to highlight the impact of the choices made in quantifying the risk posed by single outbreaks and the relative importance of various control measures.
Modelling of LPG Ship Distribution in Western of Indonesia using Discrete Simulation Method
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Trika Pitana
2017-06-01
Full Text Available The result of data from the Energy Outlook Indonesia issued by the National Energy Board, mentioned the demand of LPG every year continues to rise, and there is a regions has high increased still at western part of Indonesia, precisely in the Sumatra and Java Island. Because of that, so effort to necessary anassesment for remake case study on the distribution pattern of vesseles with the thechincal data on the loading port and discharging port. The data has affecting distribution pattern of vessels, will be used to replicate previously existing transport system currently operated by using discrete simulation method, evaluated, and scenario building improvements to variations number and size of the capacity of vessels to get distribution pattern of effective and efficient. The result of this research obtained scenario capable to meet the demands of each destination terminal port with a case study during the next 5 years and also which has a vesseles operating expenses are the most economical
Supervisor localization a top-down approach to distributed control of discrete-event systems
Cai, Kai
2016-01-01
This monograph presents a systematic top-down approach to distributed control synthesis of discrete-event systems (DES). The approach is called supervisor localization; its essence is the allocation of external supervisory control action to individual component agents as their internal control strategies. The procedure is: first synthesize a monolithic supervisor, to achieve globally optimal and nonblocking controlled behavior, then decompose the monolithic supervisor into local controllers, one for each agent. The collective behavior of the resulting local controllers is identical to that achieved by the monolithic supervisor. The basic localization theory is first presented in the Ramadge–Wonham language-based supervisory control framework, then demonstrated with distributed control examples of multi-robot formations, manufacturing systems, and distributed algorithms. An architectural approach is adopted to apply localization to large-scale DES; this yields a heterarchical localization procedure, which is...
Sheeley, N. R., Jr.; Harvey, J. W.
1975-01-01
This paper presents particularly simple mathematical formulas for the calculation of force-free fields of constant alpha from the distribution of discrete sources on a flat surface. The advantage of these formulas lies in their physical simplicity and the fact that they can be easily used in practice to calculate the fields. The disadvantage is that they are limited to fields of 'sufficiently small alpha'. These formulas may be useful in the study of chromospheric magnetic fields by the comparison of high-resolution H-alpha photographs and photospheric magnetograms.
Distributions on unbounded moment spaces and random moment sequences
Dette, Holger; Nagel, Jan
2012-01-01
In this paper we define distributions on moment spaces corresponding to measures on the real line with an unbounded support. We identify these distributions as limiting distributions of random moment vectors defined on compact moment spaces and as distributions corresponding to random spectral measures associated with the Jacobi, Laguerre and Hermite ensemble from random matrix theory. For random vectors on the unbounded moment spaces we prove a central limit theorem where the centering vecto...
Direct Simulation of Multiple Scattering by Discrete Random Media Illuminated by Gaussian Beams
Mackowski, Daniel W.; Mishchenko, Michael I.
2011-01-01
The conventional orientation-averaging procedure developed in the framework of the superposition T-matrix approach is generalized to include the case of illumination by a Gaussian beam (GB). The resulting computer code is parallelized and used to perform extensive numerically exact calculations of electromagnetic scattering by volumes of discrete random medium consisting of monodisperse spherical particles. The size parameters of the scattering volumes are 40, 50, and 60, while their packing density is fixed at 5%. We demonstrate that all scattering patterns observed in the far-field zone of a random multisphere target and their evolution with decreasing width of the incident GB can be interpreted in terms of idealized theoretical concepts such as forward-scattering interference, coherent backscattering (CB), and diffuse multiple scattering. It is shown that the increasing violation of electromagnetic reciprocity with decreasing GB width suppresses and eventually eradicates all observable manifestations of CB. This result supplements the previous demonstration of the effects of broken reciprocity in the case of magneto-optically active particles subjected to an external magnetic field.
Probability Distributions for Random Quantum Operations
Schultz, Kevin
Motivated by uncertainty quantification and inference of quantum information systems, in this work we draw connections between the notions of random quantum states and operations in quantum information with probability distributions commonly encountered in the field of orientation statistics. This approach identifies natural sample spaces and probability distributions upon these spaces that can be used in the analysis, simulation, and inference of quantum information systems. The theory of exponential families on Stiefel manifolds provides the appropriate generalization to the classical case. Furthermore, this viewpoint motivates a number of additional questions into the convex geometry of quantum operations relative to both the differential geometry of Stiefel manifolds as well as the information geometry of exponential families defined upon them. In particular, we draw on results from convex geometry to characterize which quantum operations can be represented as the average of a random quantum operation. This project was supported by the Intelligence Advanced Research Projects Activity via Department of Interior National Business Center Contract Number 2012-12050800010.
Biham, O; Lévy, M; Solomon, S; Biham, Ofer; Malcai, Ofer; Levy, Moshe; Solomon, Sorin
1998-01-01
The dynamics of generic stochastic Lotka-Volterra (discrete logistic) systems of the form \\cite{Solomon96a} $w_i (t+1) = \\lambda(t) w_i (t) + a {\\bar w (t)} - b w_i (t) {\\bar w(t)}$ is studied by computer simulations. The variables $w_i$, $i=1,...N$, are the individual system components and ${\\bar w (t)} = {1\\over N} \\sum_i w_i (t)$ is their average. The parameters $a$ and $b$ are constants, while $\\lambda(t)$ is randomly chosen at each time step from a given distribution. Models of this type describe the temporal evolution of a large variety of systems such as stock markets and city populations. These systems are characterized by a large number of interacting objects and the dynamics is dominated by multiplicative processes. The instantaneous probability distribution $P(w,t)$ of the system components $w_i$, turns out to fulfill a (truncated) Pareto power-law $P(w,t) \\sim w^{-1-\\alpha}$. The time evolution of ${\\bar w (t)} $ presents intermittent fluctuations parametrized by a truncated distribution of the $w...
Epileptic seizure detection using probability distribution based on equal frequency discretization.
Orhan, Umut; Hekim, Mahmut; Ozer, Mahmut
2012-08-01
In this study, we offered a new feature extraction approach called probability distribution based on equal frequency discretization (EFD) to be used in the detection of epileptic seizure from electroencephalogram (EEG) signals. Here, after EEG signals were discretized by using EFD method, the probability densities of the signals were computed according to the number of data points in each interval. Two different probability density functions were defined by means of the polynomial curve fitting for the subjects without epileptic seizure and the subjects with epileptic seizure, and then when using the mean square error criterion for these two functions, the success of epileptic seizure detection was 96.72%. In addition, when the probability densities of EEG segments were used as the inputs of a multilayer perceptron neural network (MLPNN) model, the success of epileptic seizure detection was 99.23%. This results show that non-linear classifiers can easily detect the epileptic seizures from EEG signals by means of probability distribution based on EFD.
Decentralized Observer with a Consensus Filter for Distributed Discrete-Time Linear Systems
Acikmese, Behcet; Mandic, Milan
2011-01-01
This paper presents a decentralized observer with a consensus filter for the state observation of a discrete-time linear distributed systems. In this setup, each agent in the distributed system has an observer with a model of the plant that utilizes the set of locally available measurements, which may not make the full plant state detectable. This lack of detectability is overcome by utilizing a consensus filter that blends the state estimate of each agent with its neighbors' estimates. We assume that the communication graph is connected for all times as well as the sensing graph. It is proven that the state estimates of the proposed observer asymptotically converge to the actual plant states under arbitrarily changing, but connected, communication and sensing topologies. As a byproduct of this research, we also obtained a result on the location of eigenvalues, the spectrum, of the Laplacian for a family of graphs with self-loops.
Random regret-based discrete-choice modelling: an application to healthcare.
de Bekker-Grob, Esther W; Chorus, Caspar G
2013-07-01
A new modelling approach for analysing data from discrete-choice experiments (DCEs) has been recently developed in transport economics based on the notion of regret minimization-driven choice behaviour. This so-called Random Regret Minimization (RRM) approach forms an alternative to the dominant Random Utility Maximization (RUM) approach. The RRM approach is able to model semi-compensatory choice behaviour and compromise effects, while being as parsimonious and formally tractable as the RUM approach. Our objectives were to introduce the RRM modelling approach to healthcare-related decisions, and to investigate its usefulness in this domain. Using data from DCEs aimed at determining valuations of attributes of osteoporosis drug treatments and human papillomavirus (HPV) vaccinations, we empirically compared RRM models, RUM models and Hybrid RUM-RRM models in terms of goodness of fit, parameter ratios and predicted choice probabilities. In terms of model fit, the RRM model did not outperform the RUM model significantly in the case of the osteoporosis DCE data (p = 0.21), whereas in the case of the HPV DCE data, the Hybrid RUM-RRM model outperformed the RUM model (p < 0.05). Differences in predicted choice probabilities between RUM models and (Hybrid RUM-) RRM models were small. Derived parameter ratios did not differ significantly between model types, but trade-offs between attributes implied by the two models can vary substantially. Differences in model fit between RUM, RRM and Hybrid RUM-RRM were found to be small. Although our study did not show significant differences in parameter ratios, the RRM and Hybrid RUM-RRM models did feature considerable differences in terms of the trade-offs implied by these ratios. In combination, our results suggest that RRM and Hybrid RUM-RRM modelling approach hold the potential of offering new and policy-relevant insights for health researchers and policy makers.
Migliorati, Giovanni
2015-08-28
We study the accuracy of the discrete least-squares approximation on a finite dimensional space of a real-valued target function from noisy pointwise evaluations at independent random points distributed according to a given sampling probability measure. The convergence estimates are given in mean-square sense with respect to the sampling measure. The noise may be correlated with the location of the evaluation and may have nonzero mean (offset). We consider both cases of bounded or square-integrable noise / offset. We prove conditions between the number of sampling points and the dimension of the underlying approximation space that ensure a stable and accurate approximation. Particular focus is on deriving estimates in probability within a given confidence level. We analyze how the best approximation error and the noise terms affect the convergence rate and the overall confidence level achieved by the convergence estimate. The proofs of our convergence estimates in probability use arguments from the theory of large deviations to bound the noise term. Finally we address the particular case of multivariate polynomial approximation spaces with any density in the beta family, including uniform and Chebyshev.
Fitting traffic traces with discrete canonical phase type distributions and Markov arrival processes
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Meszáros András
2014-09-01
Full Text Available Recent developments of matrix analytic methods make phase type distributions (PHs and Markov Arrival Processes (MAPs promising stochastic model candidates for capturing traffic trace behaviour and for efficient usage in queueing analysis. After introducing basics of these sets of stochastic models, the paper discusses the following subjects in detail: (i PHs and MAPs have different representations. For efficient use of these models, sparse (defined by a minimal number of parameters and unique representations of discrete time PHs and MAPs are needed, which are commonly referred to as canonical representations. The paper presents new results on the canonical representation of discrete PHs and MAPs. (ii The canonical representation allows a direct mapping between experimental moments and the stochastic models, referred to as moment matching. Explicit procedures are provided for this mapping. (iii Moment matching is not always the best way to model the behavior of traffic traces. Model fitting based on appropriately chosen distance measures might result in better performing stochastic models. We also demonstrate the efficiency of fitting procedures with experimental results
Robust stability analysis of generalized neural networks with discrete and distributed time delays
Energy Technology Data Exchange (ETDEWEB)
Wang Zidong [Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex, UB8 3PH (United Kingdom) and School of Information Sciences and Technology, Donghua University, Shanghai 200051 (China)]. E-mail: zidong.wang@brunel.ac.uk; Shu Huisheng [School of Sciences, Donghua University, Shanghai 200051 (China)]. E-mail: hsshu@dhu.edu.cn; Liu Yurong [Department of Mathematics, Yangzhou University, Yangzhou 225002 (China); Ho, Daniel W.C. [Department of Mathematics, City University of Hong Kong (Hong Kong); Liu Xiaohui [Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex, UB8 3PH (United Kingdom)
2006-11-15
This paper is concerned with the problem of robust global stability analysis for generalized neural networks (GNNs) with both discrete and distributed delays. The parameter uncertainties are assumed to be time-invariant and bounded, and belong to given compact sets. The existence of the equilibrium point is first proved under mild conditions, assuming neither differentiability nor strict monotonicity for the activation function. Then, by employing a Lyapunov-Krasovskii functional, the addressed stability analysis problem is converted into a convex optimization problem, and a linear matrix inequality (LMI) approach is utilized to establish the sufficient conditions for the globally robust stability for the GNNs, with and without parameter uncertainties. These conditions can be readily checked by utilizing the Matlab LMI toolbox. A numerical example is provided to demonstrate the usefulness of the proposed global stability condition.
Numerical assessment and optimization of discrete-variable time-frequency quantum key distribution
Rödiger, Jasper; Perlot, Nicolas; Mottola, Roberto; Elschner, Robert; Weinert, Carl-Michael; Benson, Oliver; Freund, Ronald
2017-05-01
The discrete-variables (DV) time-frequency (TF) quantum key distribution (QKD) protocol is a BB84-like protocol, which utilizes time and frequency as complementary bases. As orthogonal modulations, pulse position modulation (PPM) and frequency shift keying (FSK) are capable of transmitting several bits per symbol, i.e., per photon. However, unlike traditional binary polarization shift keying, PPM and FSK do not allow perfectly complementary bases. So information is not completely deleted when the wrong-basis filters are applied. Since a general security proof does not yet exist, we numerically assess DV-TF-QKD. We show that the secret key rate increases with a higher number of symbols per basis. Further we identify the optimal pulse relations in the two bases in terms of key rate and resistance against eavesdropping attacks.
Implementation of continuous-variable quantum key distribution with discrete modulation
Hirano, Takuya; Ichikawa, Tsubasa; Matsubara, Takuto; Ono, Motoharu; Oguri, Yusuke; Namiki, Ryo; Kasai, Kenta; Matsumoto, Ryutaroh; Tsurumaru, Toyohiro
2017-06-01
We have developed a continuous-variable quantum key distribution (CV-QKD) system that employs discrete quadrature-amplitude modulation and homodyne detection of coherent states of light. We experimentally demonstrated automated secure key generation with a rate of 50 kbps when a quantum channel is a 10 km optical fibre. The CV-QKD system utilises a four-state and post-selection protocol and generates a secure key against the entangling cloner attack. We used a pulsed light source of 1550 nm wavelength with a repetition rate of 10 MHz. A commercially available balanced receiver is used to realise shot-noise-limited pulsed homodyne detection. We used a non-binary LDPC code for error correction (reverse reconciliation) and the Toeplitz matrix multiplication for privacy amplification. A graphical processing unit card is used to accelerate the software-based post-processing.
On the Steady-State System Size Distribution for a Discrete-Time Geo/G/1 Repairable Queue
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Renbin Liu
2014-01-01
Full Text Available This paper studies a discrete-time N-policy Geo/G/1 queueing system with feedback and repairable server. With a probabilistic analysis method and renewal process theory, the steady-state system size distribution is derived. Further, the steady-state system size distribution derived in this work is extremely suitable for numerical calculations. Numerical example illustrates the important application of steady-state system size distribution in system capacity design for a network access proxy system.
Event-Triggered Discrete-Time Distributed Consensus Optimization over Time-Varying Graphs
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Qingguo Lü
2017-01-01
Full Text Available This paper focuses on a class of event-triggered discrete-time distributed consensus optimization algorithms, with a set of agents whose communication topology is depicted by a sequence of time-varying networks. The communication process is steered by independent trigger conditions observed by agents and is decentralized and just rests with each agent’s own state. At each time, each agent only has access to its privately local Lipschitz convex objective function. At the next time step, every agent updates its state by applying its own objective function and the information sent from its neighboring agents. Under the assumption that the network topology is uniformly strongly connected and weight-balanced, the novel event-triggered distributed subgradient algorithm is capable of steering the whole network of agents asymptotically converging to an optimal solution of the convex optimization problem. Finally, a simulation example is given to validate effectiveness of the introduced algorithm and demonstrate feasibility of the theoretical analysis.
A Review of Discrete Element Method (DEM) Particle Shapes and Size Distributions for Lunar Soil
Lane, John E.; Metzger, Philip T.; Wilkinson, R. Allen
2010-01-01
As part of ongoing efforts to develop models of lunar soil mechanics, this report reviews two topics that are important to discrete element method (DEM) modeling the behavior of soils (such as lunar soils): (1) methods of modeling particle shapes and (2) analytical representations of particle size distribution. The choice of particle shape complexity is driven primarily by opposing tradeoffs with total number of particles, computer memory, and total simulation computer processing time. The choice is also dependent on available DEM software capabilities. For example, PFC2D/PFC3D and EDEM support clustering of spheres; MIMES incorporates superquadric particle shapes; and BLOKS3D provides polyhedra shapes. Most commercial and custom DEM software supports some type of complex particle shape beyond the standard sphere. Convex polyhedra, clusters of spheres and single parametric particle shapes such as the ellipsoid, polyellipsoid, and superquadric, are all motivated by the desire to introduce asymmetry into the particle shape, as well as edges and corners, in order to better simulate actual granular particle shapes and behavior. An empirical particle size distribution (PSD) formula is shown to fit desert sand data from Bagnold. Particle size data of JSC-1a obtained from a fine particle analyzer at the NASA Kennedy Space Center is also fitted to a similar empirical PSD function.
Schmidt, Lukas; Holzner, Markus
2016-01-01
This work considers the distribution of inertial particles in turbulence using the point-particle approximation. We demonstrate that the random point process formed by the positions of particles in space is a Poisson point process with log-normal random intensity ("log Gaussian Cox process" or LGCP). The probability of having a finite number of particles in a small volume is given in terms of the characteristic function of a log-normal distribution. Corrections due to discreteness of the number of particles to the previously derived statistics of particle concentration in the continuum limit are provided. These are relevant for dealing with experimental or numerical data. The probability of having regions without particles, i.e. voids, is larger for inertial particles than for tracer particles where voids are distributed according to Poisson processes. Further, the probability of having large voids decays only log-normally with size. This shows that particles cluster, leaving voids behind. At scales where the...
Generating Discrete Power-Law Distributions from a Death- Multiple Immigration Population Process
Matthews, J. O.; Jakeman, E.; Hopcraft, K. I.
2003-04-01
We consider the evolution of a simple population process governed by deaths and multiple immigrations that arrive with rates particular to their order. For a particular choice of rates, the equilibrium solution has a discrete power-law form. The model is a generalization of a process investigated previously where immigrants arrived in pairs [1]. The general properties of this model are discussed in a companion paper. The population is initiated with precisely M individuals present and evolves to an equilibrium distribution with a power-law tail. However the power-law tails of the equilibrium distribution are established immediately, so that moments and correlation properties of the population are undefined for any non-zero time. The technique we develop to characterize this process utilizes external monitoring that counts the emigrants leaving the population in specified time intervals. This counting distribution also possesses a power-law tail for all sampling times and the resulting time series exhibits two features worthy of note, a large variation in the strength of the signal, reflecting the power-law PDF; and secondly, intermittency of the emissions. We show that counting with a detector of finite dynamic range regularizes naturally the fluctuations, in effect `clipping' the events. All previously undefined characteristics such as the mean, autocorrelation and probabilities to the first event and time between events are well defined and derived. These properties, although obtained by discarding much data, nevertheless possess embedded power-law regimes that characterize the population in a way that is analogous to box averaging determination of fractal-dimension.
Distributed event-triggered scheme for discrete-time second-order multi-agent systems
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Liu Quansheng
2017-03-01
Full Text Available In order to achieve the consistency of multi-agent systems, each agent needs to communicate with its adjacent agents, which will consume energy of sensors embedded on the agents and occupy network bandwidth of multi-agent systems. Both resources are limited. To solve the above problem, a novel distributed event-triggered scheme of discrete-time second-order multi-agent systems are proposed in this article. The characteristics of the scheme have two aspects. Firstly, the event-triggered conditions are considered for the state and the velocity separately. Secondly, when the event is triggered on an agent, the agent only communicates with its local neighbors. Then, the agent and its local neighbors update their controls while the other agents' controllers remain unchanged. So the scheme can maximize reduction of the sensor energy consuming and communication burden in the multi-agent network. Based on the Lyapunov functional method, a sufficient condition is obtained to achieve the stability of the second-order multi-agent systems in terms of linear matrix inequality. Finally, numerical examples are presented to validate the proposed event-triggered consensus control.
Liang, Hongjing; Zhang, Huaguang; Wang, Zhanshan
2015-11-01
This paper considers output synchronization of discrete-time multi-agent systems with directed communication topologies. The directed communication graph contains a spanning tree and the exosystem as its root. Distributed observer-based consensus protocols are proposed, based on the relative outputs of neighboring agents. A multi-step algorithm is presented to construct the observer-based protocols. In light of the discrete-time algebraic Riccati equation and internal model principle, synchronization problem is completed. At last, numerical simulation is provided to verify the effectiveness of the theoretical results. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Yu, Jinchen; Peng, Mingshu
2016-10-01
In this paper, a Kaldor-Kalecki model of business cycle with both discrete and distributed delays is considered. With the corresponding characteristic equation analyzed, the local stability of the positive equilibrium is investigated. It is found that there exist Hopf bifurcations when the discrete time delay passes a sequence of critical values. By applying the method of multiple scales, the explicit formulae which determine the direction of Hopf bifurcation and the stability of bifurcating periodic solutions are derived. Finally, numerical simulations are carried out to illustrate our main results.
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Nieves Velez de Mendizabal
Full Text Available Relapsing-remitting dynamics are a hallmark of autoimmune diseases such as Multiple Sclerosis (MS. A clinical relapse in MS reflects an acute focal inflammatory event in the central nervous system that affects signal conduction by damaging myelinated axons. Those events are evident in T1-weighted post-contrast magnetic resonance imaging (MRI as contrast enhancing lesions (CEL. CEL dynamics are considered unpredictable and are characterized by high intra- and inter-patient variability. Here, a population approach (nonlinear mixed-effects models was applied to analyse of CEL progression, aiming to propose a model that adequately captures CEL dynamics.We explored several discrete distribution models to CEL counts observed in nine MS patients undergoing a monthly MRI for 48 months. All patients were enrolled in the study free of immunosuppressive drugs, except for intravenous methylprednisolone or oral prednisone taper for a clinical relapse. Analyses were performed with the nonlinear mixed-effect modelling software NONMEM 7.2. Although several models were able to adequately characterize the observed CEL dynamics, the negative binomial distribution model had the best predictive ability. Significant improvements in fitting were observed when the CEL counts from previous months were incorporated to predict the current month's CEL count. The predictive capacity of the model was validated using a second cohort of fourteen patients who underwent monthly MRIs during 6-months. This analysis also identified and quantified the effect of steroids for the relapse treatment.The model was able to characterize the observed relapsing-remitting CEL dynamic and to quantify the inter-patient variability. Moreover, the nature of the effect of steroid treatment suggested that this therapy helps resolve older CELs yet does not affect newly appearing active lesions in that month. This model could be used for design of future longitudinal studies and clinical trials, as
Time Dependent Discrete Ordinates Neutron Transport Using Distribution Iteration in XYZ Geometry
2007-09-01
of applications, one example being the determination of activation products in a fast-flux reactor . All current discrete ordi- nates implementations...ψj+1 that is accurate to (∆t′)2 term. Thus, this method will yield second-order local truncation error only with the extrap - olated fluxes and not...D. Computing Methods in Reactor Physics . Gordon and Breach, 1968. 9. Carlson B. G. and Lathrop K. D. The Method of Discrete Ordinates . Technical
Gong, Xue; Li, Guangwu; Wu, Yang; Zhang, Jicheng; Feng, Shiyu; Liu, Yahui; Li, Cuihong; Ma, Wei; Bo, Zhishan
2017-07-19
Conjugated polymers with three components, P1-1 and P1-2, were prepared by one-pot Stille polymerization. The two-component polymer P1-0 is only composed of a 5-fluoro-6-alkyloxybenzothiadiazole (AFBT) acceptor unit and a thiophene donor unit, while the three-component polymers P1-1 and P1-2 contain 10% and 20% 5,6-difluorobenzothiadiazole (DFBT), respectively, as the third component. The incorporation of the third component, 5,6-difluorobenzothiadiazole, makes the side chains discretely distributed in the polymer backbones, which can enhance the π-π stacking of polymers in film, markedly increase the hole mobility of active layers, and improve the power-conversion efficiency (PCE) of devices. Influence of the third component on the morphology of active layer was also studied by X-ray diffraction (XRD), resonant soft X-ray scattering (R-SoXS), and transmission electron microscopy (TEM) experiments. P1-1/PC71BM-based PSCs gave a high PCE up to 7.25%, whereas similarly fabricated devices for P1-0/PC71BM only showed a PCE of 3.46%. The PCE of P1-1/PC71BM-based device was further enhanced to 8.79% after the use of 1,8-diiodooctane (DIO) as the solvent additive. Most importantly, after the incorporation of 10% 5,6-difluorobenzothiadiazole unit, P1-1 exhibited a marked tolerance to the blend film thickness. Devices with a thickness of 265 nm still showed a PCE above 8%, indicating that P1-1 is promising for future applications.
Hung, Tran Loc; Giang, Le Truong
2016-01-01
Using the Stein-Chen method some upper bounds in Poisson approximation for distributions of row-wise triangular arrays of independent negative-binomial distributed random variables are established in this note.
Hybrid computer technique yields random signal probability distributions
Cameron, W. D.
1965-01-01
Hybrid computer determines the probability distributions of instantaneous and peak amplitudes of random signals. This combined digital and analog computer system reduces the errors and delays of manual data analysis.
Directory of Open Access Journals (Sweden)
Eugenia BABILONI
2012-01-01
Full Text Available The fill rate is usually computed by using the traditional approach, which calculates it as the complement of the quotient between the expected unfulfilled demand and the expected demand per replenishment cycle, instead of directly the expected fraction of fulfilled demand. Furthermore the available methods to estimate the fill rate apply only under specific demand conditions. This paper shows the research gap regarding the estimation procedures to compute the fill rate and suggests: (i a new exact procedure to compute the traditional approximation for any discrete demand distribution; and (ii a new method to compute the fill rate directly as the fraction of fulfilled demand for any discrete demand distribution. Simulation results show that the latter methods outperform the traditional approach, which underestimates the simulated fill rate, over different demand patterns. This paper focuses on the traditional periodic review, base stock system when backlogged demands are allowed.
Randomized distributed access to mutually exclusive resources
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Moshe Dror
2005-01-01
they generally suffer from the need for extensive interagent communication. In this paper, we develop a randomized approach to make multiagent resource-allocation decisions with the objective of maximizing expected concurrency measured by the number of the active agents. This approach does not assume a centralized mechanism and has no need for interagent communication. Compared to existing autonomous-decentralized-decision-making (ADDM-based approaches for resource-allocation, our work emphasizes achieving the highest degree of agent autonomy and is able to handle more general resource requirements.
Use of log-skew-normal distribution in analysis of continuous data with a discrete component at zero
Chai, High Seng; Bailey, Kent R.
2008-01-01
The problem of analyzing a continuous variable with a discrete component is addressed within the frame-work of the mixture model proposed by Moulton and Halsey. The model can be generalized by the introduction of the log-skew-normal distribution for the continuous component, and the fit can be significantly improved by its use, while retaining the interpretation of regression parameter estimates. Simulation studies and application to a real data set are used for demonstration.
Characterizations of Distributions of Ratios of Certain Independent Random Variables
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Hamedani G.G.
2013-05-01
Full Text Available Various characterizations of the distributions of the ratio of two independent gamma and exponential random variables as well as that of two independent Weibull random variables are presented. These characterizations are based, on a simple relationship between two truncated moments ; on hazard function ; and on functions of order statistics.
On Distributed Computation in Noisy Random Planar Networks
Kanoria, Y.; Manjunath, D.
2007-01-01
We consider distributed computation of functions of distributed data in random planar networks with noisy wireless links. We present a new algorithm for computation of the maximum value which is order optimal in the number of transmissions and computation time.We also adapt the histogram computation algorithm of Ying et al to make the histogram computation time optimal.
Asymptotic distribution of products of sums of independent random ...
Indian Academy of Sciences (India)
453007 Henan, China. E-mail: bigduckwyl@163.com; duhongxia24@gmail.com. MS received 7 April 2012; revised 10 October 2012. Abstract. In the paper we consider the asymptotic distribution of products of weighted sums of independent random variables. Keywords. Asymptotic distribution; products of sums. 1.
Fan, Xiaozheng; Wang, Yan; Hu, Manfeng
2016-01-01
In this paper, the fuzzy [Formula: see text] output-feedback control problem is investigated for a class of discrete-time T-S fuzzy systems with channel fadings, sector nonlinearities, randomly occurring interval delays (ROIDs) and randomly occurring nonlinearities (RONs). A series of variables of the randomly occurring phenomena obeying the Bernoulli distribution is used to govern ROIDs and RONs. Meanwhile, the measurement outputs are subject to the sector nonlinearities (i.e. the sensor saturations) and we assume the system output is [Formula: see text], [Formula: see text]. The Lth-order Rice model is utilized to describe the phenomenon of channel fadings by setting different values of the channel coefficients. The aim of this work is to deal with the problem of designing a full-order dynamic fuzzy [Formula: see text] output-feedback controller such that the fuzzy closed-loop system is exponentially mean-square stable and the [Formula: see text] performance constraint is satisfied, by means of a combination of Lyapunov stability theory and stochastic analysis along with LMI methods. The proposed fuzzy controller parameters are derived by solving a convex optimization problem via the semidefinite programming technique. Finally, a numerical simulation is given to illustrate the feasibility and effectiveness of the proposed design technique.
Continuous Time Random Walks with memory and financial distributions
Montero, Miquel; Masoliver, Jaume
2017-11-01
We study financial distributions from the perspective of Continuous Time Random Walks with memory. We review some of our previous developments and apply them to financial problems. We also present some new models with memory that can be useful in characterizing tendency effects which are inherent in most markets. We also briefly study the effect on return distributions of fractional behaviors in the distribution of pausing times between successive transactions.
Fully-distributed randomized cooperation in wireless sensor networks
Bader, Ahmed
2015-01-07
When marrying randomized distributed space-time coding (RDSTC) to geographical routing, new performance horizons can be created. In order to reach those horizons however, routing protocols must evolve to operate in a fully distributed fashion. In this letter, we expose a technique to construct a fully distributed geographical routing scheme in conjunction with RDSTC. We then demonstrate the performance gains of this novel scheme by comparing it to one of the prominent classical schemes.
Craig, Benjamin M; Busschbach, Jan Jv
2009-01-13
To present an episodic random utility model that unifies time trade-off and discrete choice approaches in health state valuation. First, we introduce two alternative random utility models (RUMs) for health preferences: the episodic RUM and the more common instant RUM. For the interpretation of time trade-off (TTO) responses, we show that the episodic model implies a coefficient estimator, and the instant model implies a mean slope estimator. Secondly, we demonstrate these estimators and the differences between the estimates for 42 health states using TTO responses from the seminal Measurement and Valuation in Health (MVH) study conducted in the United Kingdom. Mean slopes are estimates with and without Dolan's transformation of worse-than-death (WTD) responses. Finally, we demonstrate an exploded probit estimator, an extension of the coefficient estimator for discrete choice data that accommodates both TTO and rank responses. By construction, mean slopes are less than or equal to coefficients, because slopes are fractions and, therefore, magnify downward errors in WTD responses. The Dolan transformation of WTD responses causes mean slopes to increase in similarity to coefficient estimates, yet they are not equivalent (i.e., absolute mean difference = 0.179). Unlike mean slopes, coefficient estimates demonstrate strong concordance with rank-based predictions (Lin's rho = 0.91). Combining TTO and rank responses under the exploded probit model improves the identification of health state values, decreasing the average width of confidence intervals from 0.057 to 0.041 compared to TTO only results. The episodic RUM expands upon the theoretical framework underlying health state valuation and contributes to health econometrics by motivating the selection of coefficient and exploded probit estimators for the analysis of TTO and rank responses. In future MVH surveys, sample size requirements may be reduced through the incorporation of multiple responses under a single
Maximum Likelihood and Bayes Estimation in Randomly Censored Geometric Distribution
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Hare Krishna
2017-01-01
Full Text Available In this article, we study the geometric distribution under randomly censored data. Maximum likelihood estimators and confidence intervals based on Fisher information matrix are derived for the unknown parameters with randomly censored data. Bayes estimators are also developed using beta priors under generalized entropy and LINEX loss functions. Also, Bayesian credible and highest posterior density (HPD credible intervals are obtained for the parameters. Expected time on test and reliability characteristics are also analyzed in this article. To compare various estimates developed in the article, a Monte Carlo simulation study is carried out. Finally, for illustration purpose, a randomly censored real data set is discussed.
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Rahmawan D. Arry
2017-01-01
Full Text Available FMCG is considered as one of the industry with the highest competition in the world. To win this industry, customer satisfaction becomes the main thing. In this paper, authors will simulate a system of distribution of goods from PT X TBK which has 3 categories, namely M1 (biscuit, M2 (powder and M3 (liquid. The distribution system has a problem on time delivery of goods which have a wide variety of obstacles, mainly on routing. There are 8 trucks with different routes and different utilization. There's trucks with over hour work and trucks with long idle time. The routing also causes problem for unused truck weight and volume capacity, where cost could possibly be reduced. Through Discrete event simulation and sweeping method, authors try to solve the problem by modelling the existing system and then find the solution to improve the distribution system and reaching the model objective.
Structure and Randomness of Continuous-Time, Discrete-Event Processes
Marzen, Sarah E.; Crutchfield, James P.
2017-10-01
Loosely speaking, the Shannon entropy rate is used to gauge a stochastic process' intrinsic randomness; the statistical complexity gives the cost of predicting the process. We calculate, for the first time, the entropy rate and statistical complexity of stochastic processes generated by finite unifilar hidden semi-Markov models—memoryful, state-dependent versions of renewal processes. Calculating these quantities requires introducing novel mathematical objects (ɛ -machines of hidden semi-Markov processes) and new information-theoretic methods to stochastic processes.
Chai, High Seng; Bailey, Kent R
2008-08-15
The problem of analyzing a continuous variable with a discrete component is addressed within the framework of the mixture model proposed by Moulton and Halsey (Biometrics 1995; 51:1570-1578). The model can be generalized by the introduction of the log-skew-normal distribution for the continuous component, and the fit can be significantly improved by its use, while retaining the interpretation of regression parameter estimates. Simulation studies and application to a real data set are used for demonstration. 2008 John Wiley & Sons, Ltd
A simple consensus algorithm for distributed averaging in random ...
Indian Academy of Sciences (India)
guaranteed convergence with this simple algorithm. Keywords. Sensor networks; random geographical networks; distributed averaging; consensus algorithms. PACS Nos 89.75.Hc; 89.75.Fb; 89.20.Ff. 1. Introduction. Wireless sensor networks are increasingly used in many applications ranging from envi- ronmental to ...
Random graphs with arbitrary degree distributions and their applications
Newman, M. E. J.; Strogatz, S. H.; Watts, D. J.
2001-08-01
Recent work on the structure of social networks and the internet has focused attention on graphs with distributions of vertex degree that are significantly different from the Poisson degree distributions that have been widely studied in the past. In this paper we develop in detail the theory of random graphs with arbitrary degree distributions. In addition to simple undirected, unipartite graphs, we examine the properties of directed and bipartite graphs. Among other results, we derive exact expressions for the position of the phase transition at which a giant component first forms, the mean component size, the size of the giant component if there is one, the mean number of vertices a certain distance away from a randomly chosen vertex, and the average vertex-vertex distance within a graph. We apply our theory to some real-world graphs, including the world-wide web and collaboration graphs of scientists and Fortune 1000 company directors. We demonstrate that in some cases random graphs with appropriate distributions of vertex degree predict with surprising accuracy the behavior of the real world, while in others there is a measurable discrepancy between theory and reality, perhaps indicating the presence of additional social structure in the network that is not captured by the random graph.
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Wangyan Li
2013-01-01
based on the time-varying Bernoulli distribution with measurable probability in real time. The aim of the paper is to design a nonfragile gain-scheduled controller with probability-dependent gains which can be achieved by solving a convex optimization problem via semidefinite programming method. Subsequently, a new kind of probability-dependent Lyapunov functional is proposed in order to derive the controller with less conservatism. Finally, an illustrative example will demonstrate the effectiveness of our designed procedures.
Ultrathin wide bandwidth metamaterial absorber using randomly distributed scatterers
Ahmadi, Farzad; Ida, Nathan
2017-02-01
In this paper, a broadband, ultrathin metamaterial absorber (MA) using randomly distributed scatterers is presented. Each scattering element consists of two parallel strips. These elements can either be isolated or they may overlap with nearby elements. Three different randomly positioned structures are investigated for normal incident angle as well as oblique incident angles showing that these MAs can provide broadband absorption for all cases. The results presented here coincide with some previous works. Each structure obviously has different absorption spectrum and FWHM since the coupling between the randomly positioned scatterers is different in each case. The coupling between neighboring isolated and clustered scatterers form many resonating modes resulting in broadband absorption. The distribution of the electromagnetic fields are analyzed to obtain the physical behavior of the absorber. This shows that promising results can still be obtained for MAs when there is a significant tolerance distance between scatterers due to fabrication errors in micro and nanoscale metadevices.
Nonparametric Estimation of Distributions in Random Effects Models
Hart, Jeffrey D.
2011-01-01
We propose using minimum distance to obtain nonparametric estimates of the distributions of components in random effects models. A main setting considered is equivalent to having a large number of small datasets whose locations, and perhaps scales, vary randomly, but which otherwise have a common distribution. Interest focuses on estimating the distribution that is common to all datasets, knowledge of which is crucial in multiple testing problems where a location/scale invariant test is applied to every small dataset. A detailed algorithm for computing minimum distance estimates is proposed, and the usefulness of our methodology is illustrated by a simulation study and an analysis of microarray data. Supplemental materials for the article, including R-code and a dataset, are available online. © 2011 American Statistical Association.
Modeling Slotted Aloha as a Stochastic Game with Random Discrete Power Selection Algorithms
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Rachid El-Azouzi
2009-01-01
Full Text Available We consider the uplink case of a cellular system where bufferless mobiles transmit over a common channel to a base station, using the slotted aloha medium access protocol. We study the performance of this system under several power differentiation schemes. Indeed, we consider a random set of selectable transmission powers and further study the impact of priorities given either to new arrival packets or to the backlogged ones. Later, we address a general capture model where a mobile transmits successfully a packet if its instantaneous SINR (signal to interferences plus noise ratio is lager than some fixed threshold. Under this capture model, we analyze both the cooperative team in which a common goal is jointly optimized as well as the noncooperative game problem where mobiles reach to optimize their own objectives. Furthermore, we derive the throughput and the expected delay and use them as the objectives to optimize and provide a stability analysis as alternative study. Exhaustive performance evaluations were carried out, we show that schemes with power differentiation improve significantly the individual as well as global performances, and could eliminate in some cases the bi-stable nature of slotted aloha.
Chkifa, Abdellah
2015-04-08
Motivated by the numerical treatment of parametric and stochastic PDEs, we analyze the least-squares method for polynomial approximation of multivariate functions based on random sampling according to a given probability measure. Recent work has shown that in the univariate case, the least-squares method is quasi-optimal in expectation in [A. Cohen, M A. Davenport and D. Leviatan. Found. Comput. Math. 13 (2013) 819–834] and in probability in [G. Migliorati, F. Nobile, E. von Schwerin, R. Tempone, Found. Comput. Math. 14 (2014) 419–456], under suitable conditions that relate the number of samples with respect to the dimension of the polynomial space. Here “quasi-optimal” means that the accuracy of the least-squares approximation is comparable with that of the best approximation in the given polynomial space. In this paper, we discuss the quasi-optimality of the polynomial least-squares method in arbitrary dimension. Our analysis applies to any arbitrary multivariate polynomial space (including tensor product, total degree or hyperbolic crosses), under the minimal requirement that its associated index set is downward closed. The optimality criterion only involves the relation between the number of samples and the dimension of the polynomial space, independently of the anisotropic shape and of the number of variables. We extend our results to the approximation of Hilbert space-valued functions in order to apply them to the approximation of parametric and stochastic elliptic PDEs. As a particular case, we discuss “inclusion type” elliptic PDE models, and derive an exponential convergence estimate for the least-squares method. Numerical results confirm our estimate, yet pointing out a gap between the condition necessary to achieve optimality in the theory, and the condition that in practice yields the optimal convergence rate.
Randomized Algorithms for Tracking Distributed Count, Frequencies, and Ranks
DEFF Research Database (Denmark)
Huang, Zengfeng; Yi, Ke; Zhang, Qin
2011-01-01
$-approximation of their sum $n=\\sum_i n_i$ continuously at all times, using minimum communication. While the deterministic communication complexity of the problem is $\\Theta(k/\\eps \\cdot \\log N)$, where $N$ is the final value of $n$ when the tracking finishes, we show that with randomization, the communication cost can......We show that randomization can lead to significant improvements for a few fundamental problems in distributed tracking. Our basis is the {\\em count-tracking} problem, where there are $k$ players, each holding a counter $n_i$ that gets incremented over time, and the goal is to track an $\\eps...
Randomized algorithms for tracking distributed count, frequencies, and ranks
DEFF Research Database (Denmark)
Zengfeng, Huang; Ke, Yi; Zhang, Qin
2012-01-01
of their sum n=∑ini continuously at all times, using minimum communication. While the deterministic communication complexity of the problem is θ(k/ε • log N), where N is the final value of n when the tracking finishes, we show that with randomization, the communication cost can be reduced to θ(√k/ε • log N......We show that randomization can lead to significant improvements for a few fundamental problems in distributed tracking. Our basis is the count-tracking problem, where there are k players, each holding a counter ni that gets incremented over time, and the goal is to track an ∑-approximation...
The remarkable discreteness of being
Houchmandzadeh, Bahram
2013-01-01
Life is a discrete, stochastic phenomena : for a biological organism, the time of the two most important events of its life (reproduction and death) is random and these events change the number of individuals of the species by single units. These facts can have surprising, counter-intuitive consequences. I review here three examples where these facts play, or could play, important roles : the spatial distribution of species, the biodiversity and the (Darwinian) evolution of altruistic behavior.
Exact Kolmogorov and total variation distances between some familiar discrete distributions
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Adell José A
2006-01-01
Full Text Available We give exact closed-form expressions for the Kolmogorov and the total variation distances between Poisson, binomial, and negative binomial distributions with different parameters. In the Poisson case, such expressions are related with the Lambert function.
DIVE in the cosmic web: voids with Delaunay triangulation from discrete matter tracer distributions
Zhao, Cheng; Tao, Charling; Liang, Yu; Kitaura, Francisco-Shu; Chuang, Chia-Hsun
2016-07-01
We present a novel parameter-free cosmological void finder (DIVE, Delaunay TrIangulation Void findEr) based on Delaunay Triangulation (DT), which efficiently computes the empty spheres constrained by a discrete set of tracers. We define the spheres as DT voids, and describe their properties, including a universal density profile together with an intrinsic scatter. We apply this technique on 100 halo catalogues with volumes of 2.5 h-1Gpc side each, with a bias and number density similar to the Baryon Oscillation Spectroscopic Survey CMASS luminous red galaxies, performed with the PATCHY code. Our results show that there are two main species of DT voids, which can be characterized by the radius: they have different responses to halo redshift space distortions, to number density of tracers, and reside in different dark matter environments. Based on dynamical arguments using the tidal field tensor, we demonstrate that large DT voids are hosted in expanding regions, whereas the haloes used to construct them reside in collapsing ones. Our approach is therefore able to efficiently determine the troughs of the density field from galaxy surveys, and can be used to study their clustering. We further study the power spectra of DT voids, and find that the bias of the two populations are different, demonstrating that the small DT voids are essentially tracers of groups of haloes.
Robyn, Paul Jacob; Shroff, Zubin; Zang, Omer Ramses; Kingue, Samuel; Djienouassi, Sebastien; Kouontchou, Christian; Sorgho, Gaston
2015-03-01
Nearly every nation in the world faces shortages of health workers in remote areas. Cameroon is no exception to this. The Ministry of Public Health (MoPH) is currently considering several rural retention strategies to motivate qualified health personnel to practice in remote rural areas. To better calibrate these mechanisms and to develop evidence-based retention strategies that are attractive and motivating to health workers, a Discrete Choice Experiment (DCE) was conducted to examine what job attributes are most attractive and important to health workers when considering postings in remote areas. The study was carried out between July and August 2012 among 351 medical students, nursing students and health workers in Cameroon. Mixed logit models were used to analyze the data. Among medical and nursing students a rural retention bonus of 75% of base salary (aOR= 8.27, 95% CI: 5.28-12.96, Pworker cadre for all the attributes. Preference impact measurements were also estimated to identify combination of incentives that health workers would find most attractive. Based on these findings, the study recommends the introduction of a system of substantial monetary bonuses for rural service along with ensuring adequate and functional equipment and uninterrupted supplies. By focusing on the analysis of locally relevant, actionable incentives, generated through the involvement of policy-makers at the design stage, this study provides an example of research directly linked to policy action to address a vitally important issue in global health.
Computer routines for probability distributions, random numbers, and related functions
Kirby, W.
1983-01-01
Use of previously coded and tested subroutines simplifies and speeds up program development and testing. This report presents routines that can be used to calculate various probability distributions and other functions of importance in statistical hydrology. The routines are designed as general-purpose Fortran subroutines and functions to be called from user-written main progress. The probability distributions provided include the beta, chi-square, gamma, Gaussian (normal), Pearson Type III (tables and approximation), and Weibull. Also provided are the distributions of the Grubbs-Beck outlier test, Kolmogorov 's and Smirnov 's D, Student 's t, noncentral t (approximate), and Snedecor F. Other mathematical functions include the Bessel function, I sub o, gamma and log-gamma functions, error functions, and exponential integral. Auxiliary services include sorting and printer-plotting. Random number generators for uniform and normal numbers are provided and may be used with some of the above routines to generate numbers from other distributions. (USGS)
Peer-Assisted Content Distribution with Random Linear Network Coding
DEFF Research Database (Denmark)
Hundebøll, Martin; Ledet-Pedersen, Jeppe; Sluyterman, Georg
2014-01-01
Peer-to-peer networks constitute a widely used, cost-effective and scalable technology to distribute bandwidth-intensive content. The technology forms a great platform to build distributed cloud storage without the need of a central provider. However, the majority of todays peer-to-peer systems...... require complex algorithms to schedule what parts of obtained content to forward to other peers. Random Linear Network Coding can greatly simplify these algorithm by removing the need for coordination between the distributing nodes. In this paper we propose and evaluate the structure of the BRONCO peer-to-peer....... Furthermore, we evaluate the performance of different parameters and suggest a suitable trade-off between CPU utilization and network overhead. Within the limitations of the used test environment, we have shown that networkc coding is usable in peer-assisted content distribution and we suggest further...
Directory of Open Access Journals (Sweden)
Eric S Walsh
Full Text Available Modeling the magnitude and distribution of sediment-bound pollutants in estuaries is often limited by incomplete knowledge of the site and inadequate sample density. To address these modeling limitations, a decision-support tool framework was conceived that predicts sediment contamination from the sub-estuary to broader estuary extent. For this study, a Random Forest (RF model was implemented to predict the distribution of a model contaminant, triclosan (5-chloro-2-(2,4-dichlorophenoxyphenol (TCS, in Narragansett Bay, Rhode Island, USA. TCS is an unregulated contaminant used in many personal care products. The RF explanatory variables were associated with TCS transport and fate (proxies and direct and indirect environmental entry. The continuous RF TCS concentration predictions were discretized into three levels of contamination (low, medium, and high for three different quantile thresholds. The RF model explained 63% of the variance with a minimum number of variables. Total organic carbon (TOC (transport and fate proxy was a strong predictor of TCS contamination causing a mean squared error increase of 59% when compared to permutations of randomized values of TOC. Additionally, combined sewer overflow discharge (environmental entry and sand (transport and fate proxy were strong predictors. The discretization models identified a TCS area of greatest concern in the northern reach of Narragansett Bay (Providence River sub-estuary, which was validated with independent test samples. This decision-support tool performed well at the sub-estuary extent and provided the means to identify areas of concern and prioritize bay-wide sampling.
Karvinkoppa, M. V.; Hotta, T. K.
2017-11-01
The paper deals with the numerical investigation of natural and mixed convection heat transfer on optimal distribution of five non-identical protruding discrete heat sources (Aluminium) mounted on a substrate (Bakelite) board. The heat sources are subjected to a uniform heat flux of 2000 W/m2. The temperature of heat sources along with the effect of thermal interaction between them is predicted by carrying out numerical simulations using ANSYS Icepak, and the results are validated with the existing experimental findings. The results suggest that mixed convection is a better method for cooling of discrete heat source modules. Also, the temperature of heat sources is a strong function of their shape, size, and positioning on the substrate. Effect of radiation is studied by painting the surface of heat sources by black paint. The results conclude that, under natural convection heat transfer, the temperature of heat sources drops by 6-13% from polished to black painted surface, while mixed convection results in the drop by 3-15%. The numerical predictions are in strong agreement with experimental results.
Yu, Han
2014-06-11
On the basis of unsaturated Darcy\\'s law, the Talbot-Ogden method provides a fast unconditional mass conservative algorithm to simulate groundwater infiltration in various unsaturated soil textures. Unlike advanced reservoir modelling methods that compute unsaturated flow in space, it only discretizes the moisture content domain into a suitable number of bins so that the vertical water movement is estimated piecewise in each bin. The dimensionality of the moisture content domain is extended from one dimensional to two dimensional in this study, which allows us to distinguish pore shapes within the same moisture content range. The vertical movement of water in the extended model imitates the infiltration phase in the Talbot-Ogden method. However, the difference in this extension is the directional redistribution, which represents the horizontal inter-bin flow and causes the water content distribution to have an effect on infiltration. Using this extension, we mathematically analyse the general relationship between infiltration and the moisture content distribution associated with wetting front depths in different bins. We show that a more negatively skewed moisture content distribution can produce a longer ponding time, whereas a higher overall flux cannot be guaranteed in this situation. It is proven on the basis of the water content probability distribution independent of soil textures. To illustrate this analysis, we also present numerical examples for both fine and coarse soil textures.
Directory of Open Access Journals (Sweden)
Debesh Jha
2017-01-01
Full Text Available Accurate diagnosis of pathological brain images is important for patient care, particularly in the early phase of the disease. Although numerous studies have used machine-learning techniques for the computer-aided diagnosis (CAD of pathological brain, previous methods encountered challenges in terms of the diagnostic efficiency owing to deficiencies in the choice of proper filtering techniques, neuroimaging biomarkers, and limited learning models. Magnetic resonance imaging (MRI is capable of providing enhanced information regarding the soft tissues, and therefore MR images are included in the proposed approach. In this study, we propose a new model that includes Wiener filtering for noise reduction, 2D-discrete wavelet transform (2D-DWT for feature extraction, probabilistic principal component analysis (PPCA for dimensionality reduction, and a random subspace ensemble (RSE classifier along with the K-nearest neighbors (KNN algorithm as a base classifier to classify brain images as pathological or normal ones. The proposed methods provide a significant improvement in classification results when compared to other studies. Based on 5×5 cross-validation (CV, the proposed method outperforms 21 state-of-the-art algorithms in terms of classification accuracy, sensitivity, and specificity for all four datasets used in the study.
Graphene materials having randomly distributed two-dimensional structural defects
Kung, Harold H; Zhao, Xin; Hayner, Cary M; Kung, Mayfair C
2013-10-08
Graphene-based storage materials for high-power battery applications are provided. The storage materials are composed of vertical stacks of graphene sheets and have reduced resistance for Li ion transport. This reduced resistance is achieved by incorporating a random distribution of structural defects into the stacked graphene sheets, whereby the structural defects facilitate the diffusion of Li ions into the interior of the storage materials.
Random generation of RNA secondary structures according to native distributions
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Nebel Markus E
2011-10-01
Full Text Available Abstract Background Random biological sequences are a topic of great interest in genome analysis since, according to a powerful paradigm, they represent the background noise from which the actual biological information must differentiate. Accordingly, the generation of random sequences has been investigated for a long time. Similarly, random object of a more complicated structure like RNA molecules or proteins are of interest. Results In this article, we present a new general framework for deriving algorithms for the non-uniform random generation of combinatorial objects according to the encoding and probability distribution implied by a stochastic context-free grammar. Briefly, the framework extends on the well-known recursive method for (uniform random generation and uses the popular framework of admissible specifications of combinatorial classes, introducing weighted combinatorial classes to allow for the non-uniform generation by means of unranking. This framework is used to derive an algorithm for the generation of RNA secondary structures of a given fixed size. We address the random generation of these structures according to a realistic distribution obtained from real-life data by using a very detailed context-free grammar (that models the class of RNA secondary structures by distinguishing between all known motifs in RNA structure. Compared to well-known sampling approaches used in several structure prediction tools (such as SFold ours has two major advantages: Firstly, after a preprocessing step in time O(n2 for the computation of all weighted class sizes needed, with our approach a set of m random secondary structures of a given structure size n can be computed in worst-case time complexity Om⋅n⋅ log(n while other algorithms typically have a runtime in O(m⋅n2. Secondly, our approach works with integer arithmetic only which is faster and saves us from all the discomforting details of using floating point arithmetic with
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Syed Asif AliShah
2011-10-01
Full Text Available Load balancing is an efficient technique used to maximize throughput, optimal resource utilization, minimized response time and avoiding congestion. This can be achieved by distributing the workload evenly across two or more network stations, nodes or buffers, links, central processing units, hard drives, or other resources. In this paper, we have modeled and developed a load balancing approach in a discrete-time domain to analyze and evaluate the system of finite network buffers using an early arrival system. Our approach of modeling such a system consists of two steps. The first step is the determination of all system-state stages and their corresponding transition probabilities. Next, we compute various performance measures by utilizing the system state transition probabilities for its steady-state behavior.
Directory of Open Access Journals (Sweden)
Syed Asif Ali Shah
2012-01-01
Full Text Available Flow time analysis is a powerful concept to analyze the flow time of any arriving customer in any system at any instant. A load management mechanism can be employed very effectively in any queueing system by utilizing a system which provides probability of dual service rate. In this paper, we develop and demonstrate the flow and service processes transition diagram to determine the flow time of a customer in a load management late arrival state dependent finite discrete time queueing system with dual service rate where customers are hypogeometrically distributed. We compute the probability mass function of each starting state and total probability mass function. The obtained analytical results are validated with simulation results for varying values of arrival and service probabilities.
An empirical investigation of sparse distributed memory using discrete speech recognition
Danforth, Douglas G.
1990-01-01
Presented here is a step by step analysis of how the basic Sparse Distributed Memory (SDM) model can be modified to enhance its generalization capabilities for classification tasks. Data is taken from speech generated by a single talker. Experiments are used to investigate the theory of associative memories and the question of generalization from specific instances.
Ho, Andrew D.; Yu, Carol C.
2015-01-01
Many statistical analyses benefit from the assumption that unconditional or conditional distributions are continuous and normal. More than 50 years ago in this journal, Lord and Cook chronicled departures from normality in educational tests, and Micerri similarly showed that the normality assumption is met rarely in educational and psychological…
Konopka, Ladislav; Kosek, Juraj
2015-10-01
Polyethylene particles of various sizes are present in industrial gas-dispersion reactors and downstream processing units. The contact of the particles with a device wall as well as the mutual particle collisions cause electrons on the particle surface to redistribute in the system. The undesirable triboelectric charging results in several operational problems and safety risks in industrial systems, for example in the fluidized-bed polymerization reactor. We studied the charging of polyethylene particles caused by the particle-particle interactions in gas. Our model employs the Discrete Element Method (DEM) describing the particle dynamics and incorporates the ‘Trapped Electron Approach’ as the physical basis for the considered charging mechanism. The model predicts the particle charge distribution for systems with various particle size distributions and various level of segregation. Simulation results are in a qualitative agreement with experimental observations of similar particulate systems specifically in two aspects: 1) Big particles tend to gain positive charge and small particles the negative one. 2) The wider the particle size distribution is, the more pronounced is the charging process. Our results suggest that not only the size distribution, but also the effect of the spatial segregation of the polyethylene particles significantly influence the resulting charge distribution ‘generated’ in the system. The level of particle segregation as well as the particle size distribution of polyethylene particles can be in practice adjusted by the choice of supported catalysts, by the conditions in the fluidized-bed polymerization reactor and by the fluid dynamics. We also attempt to predict how the reactor temperature affects the triboelectric charging of particles.
Directory of Open Access Journals (Sweden)
Paul Jacob Robyn
2015-03-01
Full Text Available Background Nearly every nation in the world faces shortages of health workers in remote areas. Cameroon is no exception to this. The Ministry of Public Health (MoPH is currently considering several rural retention strategies to motivate qualified health personnel to practice in remote rural areas. Methods To better calibrate these mechanisms and to develop evidence-based retention strategies that are attractive and motivating to health workers, a Discrete Choice Experiment (DCE was conducted to examine what job attributes are most attractive and important to health workers when considering postings in remote areas. The study was carried out between July and August 2012 among 351 medical students, nursing students and health workers in Cameroon. Mixed logit models were used to analyze the data. Results Among medical and nursing students a rural retention bonus of 75% of base salary (aOR= 8.27, 95% CI: 5.28-12.96, P< 0.001 and improved health facility infrastructure (aOR= 3.54, 95% CI: 2.73-4.58 respectively were the attributes with the largest effect sizes. Among medical doctors and nurse aides, a rural retention bonus of 75% of base salary was the attribute with the largest effect size (medical doctors aOR= 5.60, 95% CI: 4.12-7.61, P< 0.001; nurse aides aOR= 4.29, 95% CI: 3.11-5.93, P< 0.001. On the other hand, improved health facility infrastructure (aOR= 3.56, 95% CI: 2.75-4.60, P< 0.001, was the attribute with the largest effect size among the state registered nurses surveyed. Willingness-to-Pay (WTP estimates were generated for each health worker cadre for all the attributes. Preference impact measurements were also estimated to identify combination of incentives that health workers would find most attractive. Conclusion Based on these findings, the study recommends the introduction of a system of substantial monetary bonuses for rural service along with ensuring adequate and functional equipment and uninterrupted supplies. By focusing on
Schmidt, Lukas; Fouxon, Itzhak; Holzner, Markus
2017-07-01
This work considers the distribution of discrete inertial particles in turbulence. We demonstrate that even for weak inertia the distribution can be strongly different from the Poisson distribution that holds for tracers. We study the cases of weak inertia or strong gravity where single-valued particle flow holds in space. In these cases, the particles distribute over a random multifractal attractor in space. This attractor is characterized by fractal dimensions describing scaling exponents of moments of number of particles inside a ball with size much smaller than the viscous scale of turbulence. Previous studies used a continuum approach to the moments which requires having a large number of particles below the viscous scale. This condition often does not hold in practice; for instance, for water droplets in clouds there is typically one droplet per viscous scale. This condition is also hard to realize in numerical simulations. In this work, we overcome this difficulty by deriving the probability pl(k ) of having k particles in a ball of small radius l for which the continuum approximation may not hold. We demonstrate that the random point process formed by positions of particles' centers in space is a Poisson point process with log-normal random intensity (the so-called log Gaussian Cox process or LGCP). This gives pl(k ) in terms of the characteristic function of a log-normal distribution from which the moments are derived. This allows finding the correlation dimension relevant for statistics of particles' collisions. The case of zero number of particles provides the statistics of the size of voids—regions without particles—that were not studied previously. The probability of voids is increased compared to a random distribution of particles because preferential concentration of inertial particles implies voids in the deserted regions. Thus voids and preferential concentration are different reflections of the same phenomena. In the limit of tracers with zero
Discrete coherent states and probability distributions in finite-dimensional spaces
Energy Technology Data Exchange (ETDEWEB)
Galetti, D.; Marchiolli, M.A.
1995-06-01
Operator bases are discussed in connection with the construction of phase space representatives of operators in finite-dimensional spaces and their properties are presented. It is also shown how these operator bases allow for the construction of a finite harmonic oscillator-like coherent state. Creation and annihilation operators for the Fock finite-dimensional space are discussed and their expressions in terms of the operator bases are explicitly written. The relevant finite-dimensional probability distributions are obtained and their limiting behavior for an infinite-dimensional space are calculated which agree with the well know results. (author). 20 refs, 2 figs.
Aichinger, Ida; Kersevan, Roberto
The underlying thesis on mathematical simulation methods in application and theory is structured into three parts. The first part sets up a mathematical model capable of predicting the performance and operation of an accelerator’s vacuum system based on analytical methods. A coupled species-balance equation system describes the distribution of the gas dynamics in an ultra-high vacuum system considering impacts of conductance limitations, beam induced effects (ion-, electron-, and photon-induced de- sorption), thermal outgassing and sticking probabilities of the chamber materials. A new solving algorithm based on sparse matrix representations, is introduced and presents a closed form solution of the equation system. The model is implemented in a Python environment, named PyVasco, and is supported by a graphical user interface to make it easy available for everyone. A sensitivity analysis, a cross-check with the Test-Particle Monte Carlo simulation program Molflow+ and a comparison of the simulation results t...
Gauran, Iris Ivy M; Park, Junyong; Lim, Johan; Park, DoHwan; Zylstra, John; Peterson, Thomas; Kann, Maricel; Spouge, John L
2017-09-22
In recent mutation studies, analyses based on protein domain positions are gaining popularity over gene-centric approaches since the latter have limitations in considering the functional context that the position of the mutation provides. This presents a large-scale simultaneous inference problem, with hundreds of hypothesis tests to consider at the same time. This article aims to select significant mutation counts while controlling a given level of Type I error via False Discovery Rate (FDR) procedures. One main assumption is that the mutation counts follow a zero-inflated model in order to account for the true zeros in the count model and the excess zeros. The class of models considered is the Zero-inflated Generalized Poisson (ZIGP) distribution. Furthermore, we assumed that there exists a cut-off value such that smaller counts than this value are generated from the null distribution. We present several data-dependent methods to determine the cut-off value. We also consider a two-stage procedure based on screening process so that the number of mutations exceeding a certain value should be considered as significant mutations. Simulated and protein domain data sets are used to illustrate this procedure in estimation of the empirical null using a mixture of discrete distributions. Overall, while maintaining control of the FDR, the proposed two-stage testing procedure has superior empirical power. 2017 The Authors. Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Random matrix approach to the distribution of genomic distance.
Alexeev, Nikita; Zograf, Peter
2014-08-01
The cycle graph introduced by Bafna and Pevzner is an important tool for evaluating the distance between two genomes, that is, the minimal number of rearrangements needed to transform one genome into another. We interpret this distance in topological terms and relate it to the random matrix theory. Namely, the number of genomes at a given 2-break distance from a fixed one (the Hultman number) is represented by a coefficient in the genus expansion of a matrix integral over the space of complex matrices with the Gaussian measure. We study generating functions for the Hultman numbers and prove that the two-break distance distribution is asymptotically normal.
Runoff production on a slope with randomly distributed infiltrabilities
Mouche, E.; Harel, M.
2013-12-01
Runoff generated on one- and two-dimensional slopes with randomly distributed infiltrability is studied in the queuing theory and connectivity frameworks. The equivalence between the runoff-runon equation and the customers waiting time in a single server queue provides a theoretical link between the statistical descriptions of infiltrability and that of runoff flow rate. Different distributions of infiltrability, representing soil heterogeneities at different scales, are considered. Numerical simulations validate these results and improve our understanding of runoff-runon process. All of the quantities describing the generation of runoff (runoff one-point statistics) and its organization into patterns (patterns statistics and connectivity) are studied as functions of rainfall rate and runoff dimensionality.
Smith, D J; Gaffney, E A; Blake, J R
2007-07-01
We discuss in detail techniques for modelling flows due to finite and infinite arrays of beating cilia. An efficient technique, based on concepts from previous 'singularity models' is described, that is accurate in both near and far-fields. Cilia are modelled as curved slender ellipsoidal bodies by distributing Stokeslet and potential source dipole singularities along their centrelines, leading to an integral equation that can be solved using a simple and efficient discretisation. The computed velocity on the cilium surface is found to compare favourably with the boundary condition. We then present results for two topics of current interest in biology. 1) We present the first theoretical results showing the mechanism by which rotating embryonic nodal cilia produce a leftward flow by a 'posterior tilt,' and track particle motion in an array of three simulated nodal cilia. We find that, contrary to recent suggestions, there is no continuous layer of negative fluid transport close to the ciliated boundary. The mean leftward particle transport is found to be just over 1 mum/s, within experimentally measured ranges. We also discuss the accuracy of models that represent the action of cilia by steady rotlet arrays, in particular, confirming the importance of image systems in the boundary in establishing the far-field fluid transport. Future modelling may lead to understanding of the mechanisms by which morphogen gradients or mechanosensing cilia convert a directional flow to asymmetric gene expression. 2) We develop a more complex and detailed model of flow patterns in the periciliary layer of the airway surface liquid. Our results confirm that shear flow of the mucous layer drives a significant volume of periciliary liquid in the direction of mucus transport even during the recovery stroke of the cilia. Finally, we discuss the advantages and disadvantages of the singularity technique and outline future theoretical and experimental developments required to apply this
Weight Distributions for Turbo Codes Using Random and Nonrandom Permutations
Dolinar, S.; Divsalar, D.
1995-04-01
This article takes a preliminary look at the weight distributions achievable for turbo codes using random, nonrandom, and semirandom permutations. Due to the recursiveness of the encoders, it is important to distinguish between self-terminating and non-self-terminating input sequences. The non-self-terminating sequences have little effect on decoder performance, because they accumulate high encoded weight until they are artificially terminated at the end of the block. From probabilistic arguments based on selecting the permutations randomly, it is concluded that the self-terminating weight-2 data sequences are the most important consideration in the design of the constituent codes; higher-weight self-terminating sequences have successively decreasing importance. Also, increasing the number of codes and, correspondingly, the number of permutations makes it more and more likely that the bad input sequences will be broken up by one or more of the permuters. It is possible to design nonrandom permutations that ensure that the minimum distance due to weight-2 input sequences grows roughly as p 2N, where N is the block length. However, these nonrandom permutations amplify the bad effects of higher-weight inputs, and as a result they are inferior in performance to randomly selected permutations. But there are "semirandom" permutations that perform nearly as well as the designed nonrandom permutations with respect to weight-2 input sequences and are not as susceptible to being foiled by higher-weight inputs.
Optimization and Discrete Mathematics
2012-03-06
Manager AFOSR/RSL Air Force Research Laboratory Optimization and Discrete Mathematics 6 Mar 2012 Report Documentation Page Form ApprovedOMB No...00-2012 to 00-00-2012 4. TITLE AND SUBTITLE Optimization and Discrete Mathematics 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT...distribution is unlimited.. Optimization and Discrete Mathematics PM: Don Hearn BRIEF DESCRIPTION OF PORTFOLIO: Development of
Fitting and Analyzing Randomly Censored Geometric Extreme Exponential Distribution
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Muhammad Yameen Danish
2016-06-01
Full Text Available The paper presents the Bayesian analysis of two-parameter geometric extreme exponential distribution with randomly censored data. The continuous conjugate prior of the scale and shape parameters of the model does not exist while computing the Bayes estimates, it is assumed that the scale and shape parameters have independent gamma priors. It is seen that the closed-form expressions for the Bayes estimators are not possible; we suggest the Lindley’s approximation to obtain the Bayes estimates. However, the Bayesian credible intervals cannot be constructed while using this method, we propose Gibbs sampling to obtain the Bayes estimates and also to construct the Bayesian credible intervals. Monte Carlo simulation study is carried out to observe the behavior of the Bayes estimators and also to compare with the maximum likelihood estimators. One real data analysis is performed for illustration.
The rising power of random distributed feedback fiber laser
Zhou, Pu; Ye, Jun; Xu, Jiangming; Zhang, Hanwei; Huang, Long; Wu, Jian; Xiao, Hu; Leng, Jinyong
2018-01-01
Random distributed feedback fiber lasers (RDFFL) are now attracting more and more attentions for their unique cavity-free, mode-free and structural simplicity features and broadband application potentials in many fields, such as long distance sensing, speck free imaging, nonlinear frequency conversion as well as new pump source. In this talk, we will review the recent research progresses on high power RDFFLs. We have achieved (1) More than 400 W RDFFL with nearly Gaussian beam profile based on crucial employment of fiber mismatching architecture. (2) High power RDFFL with specialized optical property that include: high power narrow-band RDFFL, hundred-watt level linearly-polarized RDFFL, hundred-watt level high-order RDFFL. (3) Power enhancements of RDFFL to record kilowatt level are demonstrated with the aid of fiber master oscillator power amplifier (MOPA) with different pump schemes.
The distribution of first hitting times of non-backtracking random walks on Erdős-Rényi networks
Tishby, Ido; Biham, Ofer; Katzav, Eytan
2017-05-01
We present analytical results for the distribution of first hitting times of non-backtracking random walks on finite Erdős-Rényi networks of N nodes. The walkers hop randomly between adjacent nodes on the network, without stepping back to the previous node, until they hit a node which they have already visited before or get trapped in a dead-end node. At this point, the path is terminated. The length, d, of the resulting path, is called the first hitting time. Using recursion equations, we obtain analytical results for the tail distribution of first hitting times, P(d > \\ell) , \\ell=0, 1, 2, \\dots , of non-backtracking random walks starting from a random initial node. It turns out that the distribution P(d > \\ell) is given by a product of a discrete Rayleigh distribution and an exponential distribution. We obtain analytical expressions for central measures (mean and median) and a dispersion measure (standard deviation) of this distribution. It is found that the paths of non-backtracking random walks, up to their termination at the first hitting time, are longer, on average, than those of the corresponding simple random walks. However, they are shorter than those of self avoiding walks on the same network, which terminate at the last hitting time. We obtain analytical results for the probabilities, p ret and p trap, that a path will terminate by retracing, namely stepping into an already visited node, or by trapping, namely entering a node of degree k = 1, which has no exit link, respectively. It is shown that in dilute networks the dominant termination scenario is trapping while in dense networks most paths terminate by retracing. We obtain expressions for the conditional tail distributions of path lengths, P(d> \\ell \\vert ret) and P(d> \\ell \\vert {trap}) , for those paths which terminate by retracing or by trapping, respectively. We also study a class of generalized non-backtracking random walk models which not only avoid the backtracking step
DEFF Research Database (Denmark)
Sørensen, John Aasted
2011-01-01
; construct a finite state machine for a given application. Apply these concepts to new problems. The teaching in Discrete Mathematics is a combination of sessions with lectures and students solving problems, either manually or by using Matlab. Furthermore a selection of projects must be solved and handed......The objectives of Discrete Mathematics (IDISM2) are: The introduction of the mathematics needed for analysis, design and verification of discrete systems, including the application within programming languages for computer systems. Having passed the IDISM2 course, the student will be able...... to accomplish the following: -Understand and apply formal representations in discrete mathematics. -Understand and apply formal representations in problems within discrete mathematics. -Understand methods for solving problems in discrete mathematics. -Apply methods for solving problems in discrete mathematics...
DEFF Research Database (Denmark)
Sørensen, John Aasted
2011-01-01
The objectives of Discrete Mathematics (IDISM2) are: The introduction of the mathematics needed for analysis, design and verification of discrete systems, including the application within programming languages for computer systems. Having passed the IDISM2 course, the student will be able...... to accomplish the following: -Understand and apply formal representations in discrete mathematics. -Understand and apply formal representations in problems within discrete mathematics. -Understand methods for solving problems in discrete mathematics. -Apply methods for solving problems in discrete mathematics......; construct a finite state machine for a given application. Apply these concepts to new problems. The teaching in Discrete Mathematics is a combination of sessions with lectures and students solving problems, either manually or by using Matlab. Furthermore a selection of projects must be solved and handed...
DEFF Research Database (Denmark)
Mikosch, Thomas Valentin; Rackauskas, Alfredas
2010-01-01
In this paper, we deal with the asymptotic distribution of the maximum increment of a random walk with a regularly varying jump size distribution. This problem is motivated by a long-standing problem on change point detection for epidemic alternatives. It turns out that the limit distribution...... of the maximum increment of the random walk is one of the classical extreme value distributions, the Fréchet distribution. We prove the results in the general framework of point processes and for jump sizes taking values in a separable Banach space...
Distribution of breakage events in random packings of rodlike particles.
Grof, Zdeněk; Štěpánek, František
2013-07-01
Uniaxial compaction and breakage of rodlike particle packing has been studied using a discrete element method simulation. A scaling relationship between the applied stress, the number of breakage events, and the number-mean particle length has been derived and compared with computational experiments. Based on results for a wide range of intrinsic particle strengths and initial particle lengths, it seems that a single universal relation can be used to describe the incidence of breakage events during compaction of rodlike particle layers.
Directory of Open Access Journals (Sweden)
Sung Soo Kim
2016-02-01
Full Text Available We consider a discrete-time dependent Sparre Andersen risk model which incorporates multiple threshold levels characterizing an insurer’s minimal capital requirement, dividend paying situations, and external financial activities. We focus on the development of a recursive computational procedure to calculate the finite-time ruin probabilities and expected total discounted dividends paid prior to ruin associated with this model. We investigate several numerical examples and make some observations concerning the impact our threshold levels have on the finite-time ruin probabilities and expected total discounted dividends paid prior to ruin.
The random field model of the spatial distribution of heavy vehicle loads on long-span bridges
Chen, Zhicheng; Bao, Yuequan; Li, Hui
2016-04-01
A stochastic model based on Markov random field is proposed to model the spatial distribution of vehicle loads on longspan bridges. The bridge deck is divided into a finite set of discrete grid cells, each cell has two states according to whether the cell is occupied by the heavy vehicle load or not, then a four-neighbor lattice-structured undirected graphical model with each node corresponding to a cell state variable is proposed to model the location distribution of heavy vehicle loads on the bridge deck. The node potential is defined to quantitatively describe the randomness of node state, and the edge potential is defined to quantitatively describe the correlation of the connected node pair. The junction tree algorithm is employed to obtain the systematic solutions of inference problems of the graphical model. A marked random variable is assigned to each node to represent the amplitude of the total weight of vehicle applied on the corresponding cell of the bridge deck. The rationality of the model is validated by a Monte Carlo simulation of a learned model based on monitored data of a cable-stayed bridge.
CSIR Research Space (South Africa)
Van Aardt, JAN
2012-07-01
Full Text Available this relationship vary by the area used for signal integration?). Results have significant implications in terms of a cost-benefit analysis: The use of a discrete return instead of a waveform system leads to a reduction in cost, data volume, signal complexity...
National Research Council Canada - National Science Library
Bogdan Gheorghe Munteanu
2013-01-01
Using the stochastic approximations, in this paper it was studiedthe convergence in distribution of the fractional parts of the sum of random variables to the truncated exponential distribution with parameter lambda...
Random Access Performance of Distributed Sensors Attacked by Unknown Jammers.
Jeong, Dae-Kyo; Wui, Jung-Hwa; Kim, Dongwoo
2017-11-18
In this paper, we model and investigate the random access (RA) performance of sensor nodes (SN) in a wireless sensor network (WSN). In the WSN, a central head sensor (HS) collects the information from distributed SNs, and jammers disturb the information transmission primarily by generating interference. In this paper, two jamming attacks are considered: power and code jamming. Power jammers (if they are friendly jammers) generate noises and, as a result, degrade the quality of the signal from SNs. Power jamming is equally harmful to all the SNs that are accessing HS and simply induces denial of service (DoS) without any need to hack HS or SNs. On the other hand, code jammers mimic legitimate SNs by sending fake signals and thus need to know certain system parameters that are used by the legitimate SNs. As a result of code jamming, HS falsely allocates radio resources to SNs. The code jamming hence increases the failure probability in sending the information messages, as well as misleads the usage of radio resources. In this paper, we present the probabilities of successful preamble transmission with power ramping according to the jammer types and provide the resulting throughput and delay of information transmission by SNs, respectively. The effect of two jamming attacks on the RA performances is compared with numerical investigation. The results show that, compared to RA without jammers, power and code jamming degrade the throughput by up to 30.3% and 40.5%, respectively, while the delay performance by up to 40.1% and 65.6%, respectively.
Random Access Performance of Distributed Sensors Attacked by Unknown Jammers
Directory of Open Access Journals (Sweden)
Dae-Kyo Jeong
2017-11-01
Full Text Available In this paper, we model and investigate the random access (RA performance of sensor nodes (SN in a wireless sensor network (WSN. In the WSN, a central head sensor (HS collects the information from distributed SNs, and jammers disturb the information transmission primarily by generating interference. In this paper, two jamming attacks are considered: power and code jamming. Power jammers (if they are friendly jammers generate noises and, as a result, degrade the quality of the signal from SNs. Power jamming is equally harmful to all the SNs that are accessing HS and simply induces denial of service (DoS without any need to hack HS or SNs. On the other hand, code jammers mimic legitimate SNs by sending fake signals and thus need to know certain system parameters that are used by the legitimate SNs. As a result of code jamming, HS falsely allocates radio resources to SNs. The code jamming hence increases the failure probability in sending the information messages, as well as misleads the usage of radio resources. In this paper, we present the probabilities of successful preamble transmission with power ramping according to the jammer types and provide the resulting throughput and delay of information transmission by SNs, respectively. The effect of two jamming attacks on the RA performances is compared with numerical investigation. The results show that, compared to RA without jammers, power and code jamming degrade the throughput by up to 30.3% and 40.5%, respectively, while the delay performance by up to 40.1% and 65.6%, respectively.
Energy Technology Data Exchange (ETDEWEB)
Granger, S.; Perotin, L. [Electricite de France (EDF), 78 - Chatou (France)
1997-12-31
Maintaining the PWR components under reliable operating conditions requires a complex design to prevent various damaging processes, including fatigue and wear problems due to flow-induced vibration. In many practical situations, it is difficult, if not impossible, to perform direct measurements or calculations of the external forces acting on vibrating structures. Instead, vibrational responses can often be conveniently measured. This paper presents an inverse method for estimating a distributed random excitation from the measurement of the structural response at a number of discrete points. This paper is devoted to the presentation of the theoretical development. The force identification method is based on a modal model for the structure and a spatial orthonormal decomposition of the excitation field. The estimation of the Fourier coefficients of this orthonormal expansion is presented. As this problem turns out to be ill-posed, a regularization process is introduced. The minimization problem associated to this process is then formulated and its solutions is developed. (author) 17 refs.
Gorski, K. M.; Hivon, Eric; Banday, A. J.; Wandelt, Benjamin D.; Hansen, Frode K.; Reinecke, Mstvos; Bartelmann, Matthia
2005-01-01
HEALPix the Hierarchical Equal Area isoLatitude Pixelization is a versatile structure for the pixelization of data on the sphere. An associated library of computational algorithms and visualization software supports fast scientific applications executable directly on discretized spherical maps generated from very large volumes of astronomical data. Originally developed to address the data processing and analysis needs of the present generation of cosmic microwave background experiments (e.g., BOOMERANG, WMAP), HEALPix can be expanded to meet many of the profound challenges that will arise in confrontation with the observational output of future missions and experiments, including, e.g., Planck, Herschel, SAFIR, and the Beyond Einstein inflation probe. In this paper we consider the requirements and implementation constraints on a framework that simultaneously enables an efficient discretization with associated hierarchical indexation and fast analysis/synthesis of functions defined on the sphere. We demonstrate how these are explicitly satisfied by HEALPix.
Directory of Open Access Journals (Sweden)
Bogdan Gheorghe Munteanu
2013-01-01
Full Text Available Using the stochastic approximations, in this paper it was studiedthe convergence in distribution of the fractional parts of the sum of random variables to the truncated exponential distribution with parameter lambda. This fact is feasible by means of the Fourier-Stieltjes sequence (FSS of the random variable.
Algorithm for generation pseudo-random series with arbitrarily assigned distribution law
Directory of Open Access Journals (Sweden)
В.С. Єременко
2005-04-01
Full Text Available Method for generation pseudo-random series with arbitrarily assigned distribution law has been proposed. The praxis of using proposed method for generation pseudo-random series with anti-modal and approximate to Gaussian distribution law has been investigated.
Larwin, Karen H.; Larwin, David A.
2011-01-01
Bootstrapping methods and random distribution methods are increasingly recommended as better approaches for teaching students about statistical inference in introductory-level statistics courses. The authors examined the effect of teaching undergraduate business statistics students using random distribution and bootstrapping simulations. It is the…
DEFF Research Database (Denmark)
Busch, Peter Andre; Zinner Henriksen, Helle
2018-01-01
discretion is suggested to reduce this footprint by influencing or replacing their discretionary practices using ICT. What is less researched is whether digital discretion can cause changes in public policy outcomes, and under what conditions such changes can occur. Using the concept of public service values......This study reviews 44 peer-reviewed articles on digital discretion published in the period from 1998 to January 2017. Street-level bureaucrats have traditionally had a wide ability to exercise discretion stirring debate since they can add their personal footprint on public policies. Digital......, we suggest that digital discretion can strengthen ethical and democratic values but weaken professional and relational values. Furthermore, we conclude that contextual factors such as considerations made by policy makers on the macro-level and the degree of professionalization of street...
Distribution of local density of states in superstatistical random matrix theory
Energy Technology Data Exchange (ETDEWEB)
Abul-Magd, A.Y. [Department of Mathematics, Faculty of Science, Zagazig University, Zagazig (Egypt)]. E-mail: a_y_abul_magd@hotmail.com
2007-07-02
We expose an interesting connection between the distribution of local spectral density of states arising in the theory of disordered systems and the notion of superstatistics introduced by Beck and Cohen and recently incorporated in random matrix theory. The latter represents the matrix-element joint probability density function as an average of the corresponding quantity in the standard random-matrix theory over a distribution of level densities. We show that this distribution is in reasonable agreement with the numerical calculation for a disordered wire, which suggests to use the results of theory of disordered conductors in estimating the parameter distribution of the superstatistical random-matrix ensemble.
Directory of Open Access Journals (Sweden)
V. Fallahi
2013-06-01
Full Text Available In this paper, the interaction between an oscillating dipole moment and a Silver nanoparticle has been studied. Our calculations are based on Mie scattering theory and discrete dipole approximation(DDA method.At first, the resonance frequency due to excitingthe localized surface plasmons has been obtained using Mie scattering theory and then by exciting a dipole moment in theclose proximity of the nanoparticle, the induced charge distribution on the nanoparticle surface has been calculated. In our calculations, we have exploited the experimental data obtained by Johnson and Christy for dielectric function.
Brémaud, Pierre
2017-01-01
The emphasis in this book is placed on general models (Markov chains, random fields, random graphs), universal methods (the probabilistic method, the coupling method, the Stein-Chen method, martingale methods, the method of types) and versatile tools (Chernoff's bound, Hoeffding's inequality, Holley's inequality) whose domain of application extends far beyond the present text. Although the examples treated in the book relate to the possible applications, in the communication and computing sciences, in operations research and in physics, this book is in the first instance concerned with theory. The level of the book is that of a beginning graduate course. It is self-contained, the prerequisites consisting merely of basic calculus (series) and basic linear algebra (matrices). The reader is not assumed to be trained in probability since the first chapters give in considerable detail the background necessary to understand the rest of the book. .
Limit distributions for queues and random rooted trees
Directory of Open Access Journals (Sweden)
Lajos Takács
1993-01-01
Full Text Available In this paper several limit theorems are proved for the fluctuations of the queue size during the initial busy period of a queuing process with one server. These theorems are used to find the solutions of various problems connected with the heights and widths of random rooted trees.
Stimulated luminescence emission from localized recombination in randomly distributed defects
DEFF Research Database (Denmark)
Jain, Mayank; Guralnik, Benny; Andersen, Martin Thalbitzer
2012-01-01
results in a highly asymmetric TL peak; this peak can be understood to derive from a continuum of several first-order TL peaks. Our model also shows an extended power law behaviour for OSL (or prompt luminescence), which is expected from localized recombination mechanisms in materials with random...
DEFF Research Database (Denmark)
Sørensen, John Aasted
2010-01-01
The introduction of the mathematics needed for analysis, design and verification of discrete systems, including applications within programming languages for computer systems. Course sessions and project work. Semester: Autumn 2010 Ectent: 5 ects Class size: 15......The introduction of the mathematics needed for analysis, design and verification of discrete systems, including applications within programming languages for computer systems. Course sessions and project work. Semester: Autumn 2010 Ectent: 5 ects Class size: 15...
DEFF Research Database (Denmark)
Sørensen, John Aasted
2010-01-01
The introduction of the mathematics needed for analysis, design and verification of discrete systems, including applications within programming languages for computer systems. Course sessions and project work. Semester: Spring 2010 Ectent: 5 ects Class size: 18......The introduction of the mathematics needed for analysis, design and verification of discrete systems, including applications within programming languages for computer systems. Course sessions and project work. Semester: Spring 2010 Ectent: 5 ects Class size: 18...
Akkoç, Betül; Arslan, Ahmet; Kök, Hatice
2017-05-01
One of the first stages in the identification of an individual is gender determination. Through gender determination, the search spectrum can be reduced. In disasters such as accidents or fires, which can render identification somewhat difficult, durable teeth are an important source for identification. This study proposes a smart system that can automatically determine gender using 3D digital maxillary tooth plaster models. The study group was composed of 40 Turkish individuals (20 female, 20 male) between the ages of 21 and 24. Using the iterative closest point (ICP) algorithm, tooth models were aligned, and after the segmentation process, models were transformed into depth images. The local discrete cosine transform (DCT) was used in the process of feature extraction, and the random forest (RF) algorithm was used for the process of classification. Classification was performed using 30 different seeds for random generator values and 10-fold cross-validation. A value of 85.166% was obtained for average classification accuracy (CA) and a value of 91.75% for the area under the ROC curve (AUC). A multi-disciplinary study is performed here that includes computer sciences, medicine and dentistry. A smart system is proposed for the determination of gender from 3D digital models of maxillary tooth plaster models. This study has the capacity to extend the field of gender determination from teeth. Copyright © 2017 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Gian Paolo Beretta
2008-08-01
Full Text Available A rate equation for a discrete probability distribution is discussed as a route to describe smooth relaxation towards the maximum entropy distribution compatible at all times with one or more linear constraints. The resulting dynamics follows the path of steepest entropy ascent compatible with the constraints. The rate equation is consistent with the Onsager theorem of reciprocity and the fluctuation-dissipation theorem. The mathematical formalism was originally developed to obtain a quantum theoretical unification of mechanics and thermodinamics. It is presented here in a general, non-quantal formulation as a part of an effort to develop tools for the phenomenological treatment of non-equilibrium problems with applications in engineering, biology, sociology, and economics. The rate equation is also extended to include the case of assigned time-dependences of the constraints and the entropy, such as for modeling non-equilibrium energy and entropy exchanges.
Electrospun dye-doped fiber networks: lasing emission from randomly distributed cavities
DEFF Research Database (Denmark)
Krammer, Sarah; Vannahme, Christoph; Smith, Cameron
2015-01-01
Dye-doped polymer fiber networks fabricated with electrospinning exhibit comb-like laser emission. We identify randomly distributed ring resonators being responsible for lasing emission by making use of spatially resolved spectroscopy. Numerical simulations confirm this result quantitatively....
Sparse Maximum-Entropy Random Graphs with a Given Power-Law Degree Distribution
van der Hoorn, Pim; Lippner, Gabor; Krioukov, Dmitri
2017-10-01
Even though power-law or close-to-power-law degree distributions are ubiquitously observed in a great variety of large real networks, the mathematically satisfactory treatment of random power-law graphs satisfying basic statistical requirements of realism is still lacking. These requirements are: sparsity, exchangeability, projectivity, and unbiasedness. The last requirement states that entropy of the graph ensemble must be maximized under the degree distribution constraints. Here we prove that the hypersoft configuration model, belonging to the class of random graphs with latent hyperparameters, also known as inhomogeneous random graphs or W-random graphs, is an ensemble of random power-law graphs that are sparse, unbiased, and either exchangeable or projective. The proof of their unbiasedness relies on generalized graphons, and on mapping the problem of maximization of the normalized Gibbs entropy of a random graph ensemble, to the graphon entropy maximization problem, showing that the two entropies converge to each other in the large-graph limit.
Computer simulation of random variables and vectors with arbitrary probability distribution laws
Bogdan, V. M.
1981-01-01
Assume that there is given an arbitrary n-dimensional probability distribution F. A recursive construction is found for a sequence of functions x sub 1 = f sub 1 (U sub 1, ..., U sub n), ..., x sub n = f sub n (U sub 1, ..., U sub n) such that if U sub 1, ..., U sub n are independent random variables having uniform distribution over the open interval (0,1), then the joint distribution of the variables x sub 1, ..., x sub n coincides with the distribution F. Since uniform independent random variables can be well simulated by means of a computer, this result allows one to simulate arbitrary n-random variables if their joint probability distribution is known.
Directory of Open Access Journals (Sweden)
Augusto Hernández Vidal
2011-12-01
Full Text Available In order to strengthen the concept of municipal autonomy, this essay proposes an extensive interpretation of administrative discretion. Discretion is the exercise of free judgment given by law to authorities for performing official acts. This legislative technique seems to be suitable whenever the legislative is intended to legislate over the essential core of municipal autonomy. This way, an eventual abuse of that autonomy could be avoided, for the disproportional restriction of the local faculty to oversee the local issues. This alternative is presented as a tool to provide with dynamism the performing of administrative activities as well, aiming to assimilate public administration new practices.
Caltagirone, Jean-Paul
2014-01-01
This book presents the fundamental principles of mechanics to re-establish the equations of Discrete Mechanics. It introduces physics and thermodynamics associated to the physical modeling. The development and the complementarity of sciences lead to review today the old concepts that were the basis for the development of continuum mechanics. The differential geometry is used to review the conservation laws of mechanics. For instance, this formalism requires a different location of vector and scalar quantities in space. The equations of Discrete Mechanics form a system of equations where the H
Eisinga, R.N.; Grotenhuis, H.F. te; Pelzer, B.J.
2013-01-01
We discuss saddlepoint approximations to the distribution of the sum of independent non-identically distributed binomial random variables. We examine the accuracy of the saddlepoint methods for a sum of 10 binomials with different sets of parameter values. The numerical results indicate that the
Theoretical solutions for degree distribution of decreasing random birth-and-death networks
Long, Yin; Zhang, Xiao-Jun; Wang, Kui
2017-05-01
In this paper, theoretical solutions for degree distribution of decreasing random birth-and-death networks (0 probability generating function approach are employed. Then, based on the form of Poisson summation, we further confirm the tail characteristic of degree distribution is Poisson tail. Finally, simulations are carried out to verify these results by comparing the theoretical solutions with computer simulations.
Rahmawan D. Arry; Aufa H. Bhagas; Qalbi A. Fairuz; Nur K. Satrio; Brahmantyo Bagas
2017-01-01
FMCG is considered as one of the industry with the highest competition in the world. To win this industry, customer satisfaction becomes the main thing. In this paper, authors will simulate a system of distribution of goods from PT X TBK which has 3 categories, namely M1 (biscuit), M2 (powder) and M3 (liquid). The distribution system has a problem on time delivery of goods which have a wide variety of obstacles, mainly on routing. There are 8 trucks with different routes and different utiliza...
Exact Distributions of Finite Random Matrices and Their Applications to Spectrum Sensing.
Zhang, Wensheng; Wang, Cheng-Xiang; Tao, Xiaofeng; Patcharamaneepakorn, Piya
2016-07-29
The exact and simple distributions of finite random matrix theory (FRMT) are critically important for cognitive radio networks (CRNs). In this paper, we unify some existing distributions of the FRMT with the proposed coefficient matrices (vectors) and represent the distributions with the coefficient-based formulations. A coefficient reuse mechanism is studied, i.e., the same coefficient matrices (vectors) can be exploited to formulate different distributions. For instance, the same coefficient matrices can be used by the largest eigenvalue (LE) and the scaled largest eigenvalue (SLE); the same coefficient vectors can be used by the smallest eigenvalue (SE) and the Demmel condition number (DCN). A new and simple cumulative distribution function (CDF) of the DCN is also deduced. In particular, the dimension boundary between the infinite random matrix theory (IRMT) and the FRMT is initially defined. The dimension boundary provides a theoretical way to divide random matrices into infinite random matrices and finite random matrices. The FRMT-based spectrum sensing (SS) schemes are studied for CRNs. The SLE-based scheme can be considered as an asymptotically-optimal SS scheme when the dimension K is larger than two. Moreover, the standard condition number (SCN)-based scheme achieves the same sensing performance as the SLE-based scheme for dual covariance matrix K = 2 . The simulation results verify that the coefficient-based distributions can fit the empirical results very well, and the FRMT-based schemes outperform the IRMT-based schemes and the conventional SS schemes.
Cohen, Denis; Schwarz, Massimiliano
2017-04-01
Shallow landslides are hillslope processes that play a key role in shaping landscapes in forested catchments. Shallow landslides are, in some regions, the dominant regulating mechanisms by which soil is delivered from the hillslopes to steep channels and fluvial systems. Several studies have highlighted the importance of roots to better understand mechanisms of root reinforcement and their contributions to the stabilization of hillslopes. In this context, the spatio-temporal distribution of root reinforcement has a major repercussion on the dynamic of sediment transport at the catchment scale and on the availability of productive soils. Here we present a new model for shallow slope stability calculations, SOSlope, that specifically considers the effects of root reinforcement on shallow landslide initiation. The model is a strain-step discrete element model that reproduces the self-organized redistribution of forces on a slope during rainfall-triggered shallow landslides. Tree roots govern tensile and compressive force redistribution and determine the stability of the slope, the timing, location, and dimension of the failure mass. We use SOSlope to quantify the role of protection forest in several localities in the European Alps, making use of detailed field measurements of root densities and root-size distribution, and root tensile and compressive strength for three species common in the Alps (spruce, fir, and beech) to compute landslide distributions and frequency during landslide-triggering rainfall events. We show the mechanisms by which tree roots impart reinforcement to slopes and offer protection against shallow landslides.
High-power random distributed feedback fiber laser: From science to application
Energy Technology Data Exchange (ETDEWEB)
Du, Xueyuan [College of Optoelectronic Science and Engineering, National University of Defense Technology, Changsha 410073 (China); Naval Academy of Armament, Beijing 100161 (China); Zhang, Hanwei; Xiao, Hu; Ma, Pengfei; Wang, Xiaolin; Zhou, Pu; Liu, Zejin [College of Optoelectronic Science and Engineering, National University of Defense Technology, Changsha 410073 (China)
2016-10-15
A fiber laser based on random distributed feedback has attracted increasing attention in recent years, as it has become an important photonic device and has found wide applications in fiber communications or sensing. In this article, recent advances in high-power random distributed feedback fiber laser are reviewed, including the theoretical analyses, experimental approaches, discussion on the practical applications and outlook. It is found that a random distributed feedback fiber laser can not only act as an information photonics device, but also has the feasibility for high-efficiency/high-power generation, which makes it competitive with conventional high-power laser sources. In addition, high-power random distributed feedback fiber laser has been successfully applied for midinfrared lasing, frequency doubling to the visible and high-quality imaging. It is believed that the high-power random distributed feedback fiber laser could become a promising light source with simple and economic configurations. (copyright 2016 by WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Zheng, Shimin; Rao, Uma; Bartolucci, Alfred A.; Singh, Karan P.
2011-01-01
Bartolucci et al.(2003) extended the distribution assumption from the normal (Lyles et al., 2000) to the elliptical contoured distribution (ECD) for random regression models used in analysis of longitudinal data accounting for both undetectable values and informative drop-outs. In this paper, the random regression models are constructed on the multivariate skew ECD. A real data set is used to illustrate that the skew ECDs can fit some unimodal continuous data better than the Gaussian distributions or more general continuous symmetric distributions when the symmetric distribution assumption is violated. Also, a simulation study is done for illustrating the model fitness from a variety of skew ECDs. The software we used is SAS/STAT, V. 9.13. PMID:21637734
Common-cavity ytterbium/Raman random distributed feedback fiber laser
Wu, Han; Wang, Zinan; He, Qiheng; Sun, Wei; Rao, Yunjiang
2017-06-01
In this letter, a common-cavity random distributed feedback fiber laser which can generate both 1064 nm ytterbium-doped random lasing and 1115 nm ytterbium-Raman random lasing is proposed and experimentally demonstrated for the first time. The common cavity is based on the combination of the double-cladding ytterbium-doped fiber and the standard single mode fiber (SMF); a 1064 nm high-reflectivity fiber Bragg grating and the fiber flat-end are connected to the signal port of the pump combiner as the point reflectors. The generated 1064 nm random lasing can serve as the Raman pump in the SMF, thus 1115 nm random lasing could be stimulated with the hybrid ytterbium-Raman gain. The feedback for 1115 nm random lasing is the combination of flat-end fiber and random Rayleigh feedback. By controlling the value of flat-end fiber’s reflectivity to 0.002, stable 1.91 W of 1064 nm ytterbium-doped random lasing and 3.72 W of 1115 nm ytterbium-Raman random lasing are generated successively. This work could provide a simple and cost-effective way to generate high-power random lasing.
DEFF Research Database (Denmark)
Mikosch, Thomas Valentin; Moser, Martin
2013-01-01
We investigate the maximum increment of a random walk with heavy-tailed jump size distribution. Here heavy-tailedness is understood as regular variation of the finite-dimensional distributions. The jump sizes constitute a strictly stationary sequence. Using a continuous mapping argument acting...... on the point processes of the normalized jump sizes, we prove that the maximum increment of the random walk converges in distribution to a Fréchet distributed random variable....
Directory of Open Access Journals (Sweden)
Rigot Thibaud
2012-11-01
Full Text Available Abstract Background Culicoides imicola KIEFFER, 1913 (Diptera: Ceratopogonidae is the principal vector of Bluetongue disease in the Mediterranean basin, Africa and Asia. Previous studies have identified a range of eco-climatic variables associated with the distribution of C. imicola, and these relationships have been used to predict the large-scale distribution of the vector. However, these studies are not temporally-explicit and can not be used to predict the seasonality in C. imicola abundances. Between 2001 and 2006, longitudinal entomological surveillance was carried out throughout Italy, and provided a comprehensive spatio-temporal dataset of C. imicola catches in Onderstepoort-type black-light traps, in particular in Sardinia where the species is considered endemic. Methods We built a dynamic model that allows describing the effect of eco-climatic indicators on the monthly abundances of C. imicola in Sardinia. Model precision and accuracy were evaluated according to the influence of process and observation errors. Results A first-order autoregressive cofactor, a digital elevation model and MODIS Land Surface Temperature (LST/or temperatures acquired from weather stations explained ~77% of the variability encountered in the samplings carried out in 9 sites during 6 years. Incorporating Normalized Difference Vegetation Index (NDVI or rainfall did not increase the model's predictive capacity. On average, dynamics simulations showed good accuracy (predicted vs. observed r corr = 0.9. Although the model did not always reproduce the absolute levels of monthly abundances peaks, it succeeded in reproducing the seasonality in population level and allowed identifying the periods of low abundances and with no apparent activity. On that basis, we mapped C. imicola monthly distribution over the entire Sardinian region. Conclusions This study demonstrated prospects for modelling data arising from Culicoides longitudinal entomological surveillance
Risk Assessment of Distribution Network Based on Random set Theory and Sensitivity Analysis
Zhang, Sh; Bai, C. X.; Liang, J.; Jiao, L.; Hou, Z.; Liu, B. Zh
2017-05-01
Considering the complexity and uncertainty of operating information in distribution network, this paper introduces the use of random set for risk assessment. The proposed method is based on the operating conditions defined in the random set framework to obtain the upper and lower cumulative probability functions of risk indices. Moreover, the sensitivity of risk indices can effectually reflect information about system reliability and operating conditions, and by use of these information the bottlenecks that suppress system reliability can be found. The analysis about a typical radial distribution network shows that the proposed method is reasonable and effective.
Parker, R Gary
1988-01-01
This book treats the fundamental issues and algorithmic strategies emerging as the core of the discipline of discrete optimization in a comprehensive and rigorous fashion. Following an introductory chapter on computational complexity, the basic algorithmic results for the two major models of polynomial algorithms are introduced--models using matroids and linear programming. Further chapters treat the major non-polynomial algorithms: branch-and-bound and cutting planes. The text concludes with a chapter on heuristic algorithms.Several appendixes are included which review the fundamental ideas o
Distribution of Schmidt-like eigenvalues for Gaussian ensembles of the random matrix theory
Pato, Mauricio P.; Oshanin, Gleb
2013-03-01
We study the probability distribution function P(β)n(w) of the Schmidt-like random variable w = x21/(∑j = 1nx2j/n), where xj, (j = 1, 2, …, n), are unordered eigenvalues of a given n × n β-Gaussian random matrix, β being the Dyson symmetry index. This variable, by definition, can be considered as a measure of how any individual (randomly chosen) eigenvalue deviates from the arithmetic mean value of all eigenvalues of a given random matrix, and its distribution is calculated with respect to the ensemble of such β-Gaussian random matrices. We show that in the asymptotic limit n → ∞ and for arbitrary β the distribution P(β)n(w) converges to the Marčenko-Pastur form, i.e. is defined as P_{n}^{( \\beta )}(w) \\sim \\sqrt{(4 - w)/w} for w ∈ [0, 4] and equals zero outside of the support, despite the fact that formally w is defined on the interval [0, n]. Furthermore, for Gaussian unitary ensembles (β = 2) we present exact explicit expressions for P(β = 2)n(w) which are valid for arbitrary n and analyse their behaviour.
Directory of Open Access Journals (Sweden)
Abdou Amza
2014-09-01
Full Text Available Antibiotic use on animals demonstrates improved growth regardless of whether or not there is clinical evidence of infectious disease. Antibiotics used for trachoma control may play an unintended benefit of improving child growth.In this sub-study of a larger randomized controlled trial, we assess anthropometry of pre-school children in a community-randomized trial of mass oral azithromycin distributions for trachoma in Niger. We measured height, weight, and mid-upper arm circumference (MUAC in 12 communities randomized to receive annual mass azithromycin treatment of everyone versus 12 communities randomized to receive biannual mass azithromycin treatments for children, 3 years after the initial mass treatment. We collected measurements in 1,034 children aged 6-60 months of age.We found no difference in the prevalence of wasting among children in the 12 annually treated communities that received three mass azithromycin distributions compared to the 12 biannually treated communities that received six mass azithromycin distributions (odds ratio = 0.88, 95% confidence interval = 0.53 to 1.49.We were unable to demonstrate a statistically significant difference in stunting, underweight, and low MUAC of pre-school children in communities randomized to annual mass azithromycin treatment or biannual mass azithromycin treatment. The role of antibiotics on child growth and nutrition remains unclear, but larger studies and longitudinal trials may help determine any association.
N-point free energy distribution function in one dimensional random directed polymers
Directory of Open Access Journals (Sweden)
V. Dotsenko
2014-09-01
Full Text Available Explicit expression for the N-point free energy distribution function in one dimensional directed polymers in a random potential is derived in terms of the Bethe ansatz replica technique. The obtained result is equivalent to the one derived earlier by Prolhac and Spohn [J. Stat. Mech., 2011, P03020].
Particle-size distribution and void fraction of geometric random packings
Brouwers, Jos
2006-01-01
This paper addresses the geometric random packing and void fraction of polydisperse particles. It is demonstrated that the bimodal packing can be transformed into a continuous particle-size distribution of the power law type. It follows that a maximum packing fraction of particles is obtained when
Reinforcing Sampling Distributions through a Randomization-Based Activity for Introducing ANOVA
Taylor, Laura; Doehler, Kirsten
2015-01-01
This paper examines the use of a randomization-based activity to introduce the ANOVA F-test to students. The two main goals of this activity are to successfully teach students to comprehend ANOVA F-tests and to increase student comprehension of sampling distributions. Four sections of students in an advanced introductory statistics course…
Is extrapair mating random? On the probability distribution of extrapair young in avian broods
Brommer, Jon E.; Korsten, Peter; Bouwman, Karen A.; Berg, Mathew L.; Komdeur, Jan
2007-01-01
A dichotomy in female extrapair copulation (EPC) behavior, with some females seeking EPC and others not, is inferred if the observed distribution of extrapair young (EPY) over broods differs from a random process on the level of individual offspring (binomial, hypergeometrical, or Poisson). A review
Limiting distribution for the maximal standardized increment of a random walk
Kabluchko, Zakhar; Wang, Yizao
2012-01-01
Let $X_1,X_2,...$ be independent identically distributed random variables with $\\mathbb E X_k=0$, $\\mathrm{Var} X_k=1$. Suppose that $\\varphi(t):=\\log \\mathbb E e^{t X_k}-\\sigma_0$ and some $\\sigma_0>0$. Let $S_k=X_1+...+X_k$ and $S_0=0$. We are interested in the limiting distribution of the multiscale scan statistic $$ M_n=\\max_{0\\leq i 0$. We argue that our results cover most interesting distributions with light tails.
Thermodynamic method for generating random stress distributions on an earthquake fault
Barall, Michael; Harris, Ruth A.
2012-01-01
This report presents a new method for generating random stress distributions on an earthquake fault, suitable for use as initial conditions in a dynamic rupture simulation. The method employs concepts from thermodynamics and statistical mechanics. A pattern of fault slip is considered to be analogous to a micro-state of a thermodynamic system. The energy of the micro-state is taken to be the elastic energy stored in the surrounding medium. Then, the Boltzmann distribution gives the probability of a given pattern of fault slip and stress. We show how to decompose the system into independent degrees of freedom, which makes it computationally feasible to select a random state. However, due to the equipartition theorem, straightforward application of the Boltzmann distribution leads to a divergence which predicts infinite stress. To avoid equipartition, we show that the finite strength of the fault acts to restrict the possible states of the system. By analyzing a set of earthquake scaling relations, we derive a new formula for the expected power spectral density of the stress distribution, which allows us to construct a computer algorithm free of infinities. We then present a new technique for controlling the extent of the rupture by generating a random stress distribution thousands of times larger than the fault surface, and selecting a portion which, by chance, has a positive stress perturbation of the desired size. Finally, we present a new two-stage nucleation method that combines a small zone of forced rupture with a larger zone of reduced fracture energy.
Firth, Jean M
1992-01-01
The analysis of signals and systems using transform methods is a very important aspect of the examination of processes and problems in an increasingly wide range of applications. Whereas the initial impetus in the development of methods appropriate for handling discrete sets of data occurred mainly in an electrical engineering context (for example in the design of digital filters), the same techniques are in use in such disciplines as cardiology, optics, speech analysis and management, as well as in other branches of science and engineering. This text is aimed at a readership whose mathematical background includes some acquaintance with complex numbers, linear differen tial equations, matrix algebra, and series. Specifically, a familiarity with Fourier series (in trigonometric and exponential forms) is assumed, and an exposure to the concept of a continuous integral transform is desirable. Such a background can be expected, for example, on completion of the first year of a science or engineering degree cour...
Generating log-normally distributed random numbers by using the Ziggurat algorithm
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Choi, Jong Soo [KINS, Daejeon (Korea, Republic of)
2016-05-15
Uncertainty analyses are usually based on the Monte Carlo method. Using an efficient random number generator(RNG) is a key element in success of Monte Carlo simulations. Log-normal distributed variates are very typical in NPP PSAs. This paper proposes an approach to generate log normally distributed variates based on the Ziggurat algorithm and evaluates the efficiency of the proposed Ziggurat RNG. The proposed RNG can be helpful to improve the uncertainty analysis of NPP PSAs. This paper focuses on evaluating the efficiency of the Ziggurat algorithm from a NPP PSA point of view. From this study, we can draw the following conclusions. - The Ziggurat algorithm is one of perfect random number generators to product normal distributed variates. - The Ziggurat algorithm is computationally much faster than the most commonly used method, Marsaglia polar method.
Localization of Discrete Time Quantum Walks on the Glued Trees
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Yusuke Ide
2014-03-01
Full Text Available In this paper, we consider the time averaged distribution of discrete time quantum walks on the glued trees. In order to analyze the walks on the glued trees, we consider a reduction to the walks on path graphs. Using a spectral analysis of the Jacobi matrices defined by the corresponding random walks on the path graphs, we have a spectral decomposition of the time evolution operator of the quantum walks. We find significant contributions of the eigenvalues, ±1, of the Jacobi matrices to the time averaged limit distribution of the quantum walks. As a consequence, we obtain the lower bounds of the time averaged distribution.
Theory of amplitude quantization of random signals
Knyshev, I. P.
2008-01-01
Conditions of ideal amplitude quantization of random signal with exact restoration of two-dimension probability density distribution function are defined. Interrelation of time discretization interval and amplitude quantization is shown. As an example transformation of normal random process is considered.
Online distribution channel increases article usage on Mendeley: a randomized controlled trial.
Kudlow, Paul; Cockerill, Matthew; Toccalino, Danielle; Dziadyk, Devin Bissky; Rutledge, Alan; Shachak, Aviv; McIntyre, Roger S; Ravindran, Arun; Eysenbach, Gunther
2017-01-01
Prior research shows that article reader counts (i.e. saves) on the online reference manager, Mendeley, correlate to future citations. There are currently no evidenced-based distribution strategies that have been shown to increase article saves on Mendeley. We conducted a 4-week randomized controlled trial to examine how promotion of article links in a novel online cross-publisher distribution channel (TrendMD) affect article saves on Mendeley. Four hundred articles published in the Journal of Medical Internet Research were randomized to either the TrendMD arm (n = 200) or the control arm (n = 200) of the study. Our primary outcome compares the 4-week mean Mendeley saves of articles randomized to TrendMD versus control. Articles randomized to TrendMD showed a 77% increase in article saves on Mendeley relative to control. The difference in mean Mendeley saves for TrendMD articles versus control was 2.7, 95% CI (2.63, 2.77), and statistically significant (p distribution channel (TrendMD) enhances article saves on Mendeley. While replication and further study are needed, these data suggest that cross-publisher article recommendations via TrendMD may enhance citations of scholarly articles.
A Permutation-Randomization Approach to Test the Spatial Distribution of Plant Diseases.
Lione, G; Gonthier, P
2016-01-01
The analysis of the spatial distribution of plant diseases requires the availability of trustworthy geostatistical methods. The mean distance tests (MDT) are here proposed as a series of permutation and randomization tests to assess the spatial distribution of plant diseases when the variable of phytopathological interest is categorical. A user-friendly software to perform the tests is provided. Estimates of power and type I error, obtained with Monte Carlo simulations, showed the reliability of the MDT (power > 0.80; type I error pathogens causing root rot on conifers was successfully performed by verifying the consistency between the MDT responses and previously published data. An application of the MDT was carried out to analyze the relation between the plantation density and the distribution of the infection of Gnomoniopsis castanea, an emerging fungal pathogen causing nut rot on sweet chestnut. Trees carrying nuts infected by the pathogen were randomly distributed in areas with different plantation densities, suggesting that the distribution of G. castanea was not related to the plantation density. The MDT could be used to analyze the spatial distribution of plant diseases both in agricultural and natural ecosystems.
Dynamical Localization for Discrete Anderson Dirac Operators
Prado, Roberto A.; de Oliveira, César R.; Carvalho, Silas L.
2017-04-01
We establish dynamical localization for random Dirac operators on the d-dimensional lattice, with d\\in { 1, 2, 3} , in the three usual regimes: large disorder, band edge and 1D. These operators are discrete versions of the continuous Dirac operators and consist in the sum of a discrete free Dirac operator with a random potential. The potential is a diagonal matrix formed by different scalar potentials, which are sequences of independent and identically distributed random variables according to an absolutely continuous probability measure with bounded density and of compact support. We prove the exponential decay of fractional moments of the Green function for such models in each of the above regimes, i.e., (j) throughout the spectrum at larger disorder, (jj) for energies near the band edges at arbitrary disorder and (jjj) in dimension one, for all energies in the spectrum and arbitrary disorder. Dynamical localization in theses regimes follows from the fractional moments method. The result in the one-dimensional regime contrast with one that was previously obtained for 1D Dirac model with Bernoulli potential.
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Wenzhi Wang
2016-07-01
Full Text Available Modeling the random fiber distribution of a fiber-reinforced composite is of great importance for studying the progressive failure behavior of the material on the micro scale. In this paper, we develop a new algorithm for generating random representative volume elements (RVEs with statistical equivalent fiber distribution against the actual material microstructure. The realistic statistical data is utilized as inputs of the new method, which is archived through implementation of the probability equations. Extensive statistical analysis is conducted to examine the capability of the proposed method and to compare it with existing methods. It is found that the proposed method presents a good match with experimental results in all aspects including the nearest neighbor distance, nearest neighbor orientation, Ripley’s K function, and the radial distribution function. Finite element analysis is presented to predict the effective elastic properties of a carbon/epoxy composite, to validate the generated random representative volume elements, and to provide insights of the effect of fiber distribution on the elastic properties. The present algorithm is shown to be highly accurate and can be used to generate statistically equivalent RVEs for not only fiber-reinforced composites but also other materials such as foam materials and particle-reinforced composites.
Coull, B A; Agresti, A
2000-03-01
The multivariate binomial logit-normal distribution is a mixture distribution for which, (i) conditional on a set of success probabilities and sample size indices, a vector of counts is independent binomial variates, and (ii) the vector of logits of the parameters has a multivariate normal distribution. We use this distribution to model multivariate binomial-type responses using a vector of random effects. The vector of logits of parameters has a mean that is a linear function of explanatory variables and has an unspecified or partly specified covariance matrix. The model generalizes and provides greater flexibility than the univariate model that uses a normal random effect to account for positive correlations in clustered data. The multivariate model is useful when different elements of the response vector refer to different characteristics, each of which may naturally have its own random effect. It is also useful for repeated binary measurement of a single response when there is a nonexchangeable association structure, such as one often expects with longitudinal data or when negative association exists for at least one pair of responses. We apply the model to an influenza study with repeated responses in which some pairs are negatively associated and to a developmental toxicity study with continuation-ratio logits applied to an ordinal response with clustered observations.
Broadband supercontinuum light source seeded by random distributed feedback fiber laser
Ma, R.; Rao, Y. J.; Zhang, W. L.; Wu, H.; Zeng, X.
2017-04-01
A novel broadband light source based on supercontinuum (SC) generation seeded by random distributed feedback fiber laser (RFL) is proposed and demonstrated for the first time. A half-opened fiber cavity formed by FBG and TrueWave fiber is used to generate random lasing and SC simultaneously. Experimental results indicate that RFL can be used as an effective pump for generation of SC. SC with 20-dB bandwidth of >250 nm was obtained. Such a broadband SC light source seeded by RFL may pave a way to generate high power broadband RFLs for use in optical sensing and measurement.
On the Marginal Distribution of the Diagonal Blocks in a Blocked Wishart Random Matrix
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Kjetil B. Halvorsen
2016-01-01
Full Text Available Let A be a (m1+m2×(m1+m2 blocked Wishart random matrix with diagonal blocks of orders m1×m1 and m2×m2. The goal of the paper is to find the exact marginal distribution of the two diagonal blocks of A. We find an expression for this marginal density involving the matrix-variate generalized hypergeometric function. We became interested in this problem because of an application in spatial interpolation of random fields of positive definite matrices, where this result will be used for parameter estimation, using composite likelihood methods.
Resonant Scattering of Acoustic Phonons by Randomly Distributed Two-Level Systems
Kayanuma, Yosuke; Yamada, Hiroshi; Tanaka, Satoshi
1985-07-01
A Green function formalism is developed for the resonant scattering of acoustic phonons by randomly distributed two-level systems. The randomness is treated by the coherent potential approximation. The theory reproduces the Jacobsen-Stevens dispersion law in the dense limit of the concentration of the two-level system and the results obtained so far by the average t-matrix approximation in the dilute limit. The gradual change of the character of the resonantly scattered phonons as the concentration is varied is investigated through the calculation of various quantities such as the phonon density of states, the neutron scattering cross sections and the sound velocity.
Wuensche, Andrew
DDLab is interactive graphics software for creating, visualizing, and analyzing many aspects of Cellular Automata, Random Boolean Networks, and Discrete Dynamical Networks in general and studying their behavior, both from the time-series perspective — space-time patterns, and from the state-space perspective — attractor basins. DDLab is relevant to research, applications, and education in the fields of complexity, self-organization, emergent phenomena, chaos, collision-based computing, neural networks, content addressable memory, genetic regulatory networks, dynamical encryption, generative art and music, and the study of the abstract mathematical/physical/dynamical phenomena in their own right.
Li, Xin; Ma, Jing; Yu, Siyuan; Tan, Liying; Shen, Tao
2013-02-01
Channel capacity is widely investigated for free space optical links to approach high-speed data-rate communication. Instead of traditional equiprobable binary symbol input distribution, an optimum input distribution is proposed with respect to channel capacity by maximizing mutual information for intersatellite optical communications in the presence of random pointing jitter. It is shown that the optimum input distribution varies with the variance of pointing jitter σ and laser beam divergence angle w0 and the normalized intensity threshold IT. For traditional normalized intensity threshold IT=0.5, the optimum input distribution ranges from about p(x=0)=0.52 for weak pointing jitter to about p(x=0)=0.24 for strong pointing jitter given the same laser beam divergence angle. The results obtained in this paper will be useful for intersatellite optical communication system design.
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Dejan Jaksic
2017-01-01
Full Text Available Mathematical modelling of the behavior of the radio propagation at mmWave bands is crucial to the development of transmission and reception algorithms of new 5G systems. In this study we will model 5G propagation in nondeterministic line-of-sight (LOS conditions, when the random nature of LOS component ratio will be observed as Inverse Gamma (IG distributed process. Closed-form expressions will be presented for the probability density function (PDF and cumulative distribution function (CDF of such random process. Further, closed-form expressions will be provided for important performance measures such as level crossing rate (LCR and average fade duration (AFD. Capitalizing on proposed expressions, LCR and AFD will be discussed in the function of transmission parameters.
Crossing probability for directed polymers in random media. II. Exact tail of the distribution.
De Luca, Andrea; Le Doussal, Pierre
2016-03-01
We study the probability p ≡ p(η)(t) that two directed polymers in a given random potential η and with fixed and nearby endpoints do not cross until time t. This probability is itself a random variable (over samples η), which, as we show, acquires a very broad probability distribution at large time. In particular, the moments of p are found to be dominated by atypical samples where p is of order unity. Building on a formula established by us in a previous work using nested Bethe ansatz and Macdonald process methods, we obtain analytically the leading large time behavior of all moments p(m) ≃ γ(m)/t. From this, we extract the exact tail ∼ρ(p)/t of the probability distribution of the noncrossing probability at large time. The exact formula is compared to numerical simulations, with excellent agreement.
A trophallaxis inspired model for distributed transport between randomly interacting agents
Gräwer, Johannes; Mazza, Marco G; Katifori, Eleni
2016-01-01
A trophallaxis inspired model for distributed transport between randomly interacting agents Trophallaxis, the regurgitation and mouth to mouth transfer of liquid food between members of eusocial insect societies, is an important process that allows the fast and efficient dissemination of food in the colony. Trophallactic systems are typically treated as a network of agent interactions. This approach, though valuable, does not easily lend itself to analytic predictions. In this work we consider a simple trophallactic system of randomly interacting agents with finite carrying capacity, and calculate analytically and via a series of simulations the global food intake rate for the whole colony as well as observables describing how uniformly the food is distributed within the nest. Our work serves as a stepping stone to describing the collective properties of more complex trophallactic systems, such as those including division of labor between foragers and workers.
Shear elastic modulus of magnetic gels with random distribution of magnetizable particles
Iskakova, L. Yu; Zubarev, A. Yu
2017-04-01
Magnetic gels present new type of composite materials with rich set of uniquie physical properties, which find active applications in many industrial and bio-medical technologies. We present results of mathematically strict theoretical study of elastic modulus of these systems with randomly distributed magnetizable particles in an elastic medium. The results show that an external magnetic field can pronouncedly increase the shear modulus of these composites.
Dimension Reduction and Discretization in Stochastic Problems by Regression Method
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager
1996-01-01
The chapter mainly deals with dimension reduction and field discretizations based directly on the concept of linear regression. Several examples of interesting applications in stochastic mechanics are also given.Keywords: Random fields discretization, Linear regression, Stochastic interpolation...
Directory of Open Access Journals (Sweden)
Raquel Caballero-Águila
2015-01-01
Full Text Available The distributed fusion state estimation problem is addressed for sensor network systems with random state transition matrix and random measurement matrices, which provide a unified framework to consider some network-induced random phenomena. The process noise and all the sensor measurement noises are assumed to be one-step autocorrelated and different sensor noises are one-step cross-correlated; also, the process noise and each sensor measurement noise are two-step cross-correlated. These correlation assumptions cover many practical situations, where the classical independence hypothesis is not realistic. Using an innovation methodology, local least-squares linear filtering estimators are recursively obtained at each sensor. The distributed fusion method is then used to form the optimal matrix-weighted sum of these local filters according to the mean squared error criterion. A numerical simulation example shows the accuracy of the proposed distributed fusion filtering algorithm and illustrates some of the network-induced stochastic uncertainties that can be dealt with in the current system model, such as sensor gain degradation, missing measurements, and multiplicative noise.
Zhao, Youxuan; Li, Feilong; Cao, Peng; Liu, Yaolu; Zhang, Jianyu; Fu, Shaoyun; Zhang, Jun; Hu, Ning
2017-08-01
Since the identification of micro-cracks in engineering materials is very valuable in understanding the initial and slight changes in mechanical properties of materials under complex working environments, numerical simulations on the propagation of the low frequency S 0 Lamb wave in thin plates with randomly distributed micro-cracks were performed to study the behavior of nonlinear Lamb waves. The results showed that while the influence of the randomly distributed micro-cracks on the phase velocity of the low frequency S 0 fundamental waves could be neglected, significant ultrasonic nonlinear effects caused by the randomly distributed micro-cracks was discovered, which mainly presented as a second harmonic generation. By using a Monte Carlo simulation method, we found that the acoustic nonlinear parameter increased linearly with the micro-crack density and the size of micro-crack zone, and it was also related to the excitation frequency and friction coefficient of the micro-crack surfaces. In addition, it was found that the nonlinear effect of waves reflected by the micro-cracks was more noticeable than that of the transmitted waves. This study theoretically reveals that the low frequency S 0 mode of Lamb waves can be used as the fundamental waves to quantitatively identify micro-cracks in thin plates. Copyright © 2017 Elsevier B.V. All rights reserved.
Pagonis, Vasilis; Kulp, Christopher; Chaney, Charity-Grace; Tachiya, M
2017-09-13
During the past 10 years, quantum tunneling has been established as one of the dominant mechanisms for recombination in random distributions of electrons and positive ions, and in many dosimetric materials. Specifically quantum tunneling has been shown to be closely associated with two important effects in luminescence materials, namely long term afterglow luminescence and anomalous fading. Two of the common assumptions of quantum tunneling models based on random distributions of electrons and positive ions are: (a) An electron tunnels from a donor to the nearest acceptor, and (b) the concentration of electrons is much lower than that of positive ions at all times during the tunneling process. This paper presents theoretical studies for arbitrary relative concentrations of electrons and positive ions in the solid. Two new differential equations are derived which describe the loss of charge in the solid by tunneling, and they are solved analytically. The analytical solution compares well with the results of Monte Carlo simulations carried out in a random distribution of electrons and positive ions. Possible experimental implications of the model are discussed for tunneling phenomena in long term afterglow signals, and also for anomalous fading studies in feldspars and apatite samples.
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Moore, Stephen R. [Environmental Toxicology Graduate Program, Department of Cell Biology and Neuroscience, University of California, Riverside, CA (United States); Radiation and Genome Stability Unit, Medical Research Council, Harwell, Oxfordshire (United Kingdom); Papworth, David [Radiation and Genome Stability Unit, Medical Research Council, Harwell, Oxfordshire (United Kingdom); Grosovsky, Andrew J. [Environmental Toxicology Graduate Program, Department of Cell Biology and Neuroscience, University of California, Riverside, CA (United States)]. E-mail: Grosovsky@ucr.edu
2006-08-30
Genomic instability is observed in tumors and in a large fraction of the progeny surviving irradiation. One of the best-characterized phenotypic manifestations of genomic instability is delayed chromosome aberrations. Our working hypothesis for the current study was that if genomic instability is in part attributable to cis mechanisms, we should observe a non-random distribution of chromosomes or sites involved in instability-associated rearrangements, regardless of radiation quality, dose, or trans factor expression. We report here the karyotypic examination of 296 instability-associated chromosomal rearrangement breaksites (IACRB) from 118 unstable TK6 human B lymphoblast, and isogenic derivative, clones. When we tested whether IACRB were distributed across the chromosomes based on target size, a significant non-random distribution was evident (p < 0.00001), and three IACRB hotspots (chromosomes 11, 12, and 22) and one IACRB coldspot (chromosome 2) were identified. Statistical analysis at the chromosomal band-level identified four IACRB hotspots accounting for 20% of all instability-associated breaks, two of which account for over 14% of all IACRB. Further, analysis of independent clones provided evidence within 14 individual clones of IACRB clustering at the chromosomal band level, suggesting a predisposition for further breaks after an initial break at some chromosomal bands. All of these events, independently, or when taken together, were highly unlikely to have occurred by chance (p < 0.000001). These IACRB band-level cluster hotspots were observed independent of radiation quality, dose, or cellular p53 status. The non-random distribution of instability-associated chromosomal rearrangements described here significantly differs from the distribution that was observed in a first-division post-irradiation metaphase analysis (p = 0.0004). Taken together, these results suggest that genomic instability may be in part driven by chromosomal cis mechanisms.
Takahashi, T.; Obana, K.; Yamamoto, Y.; Nakanishi, A.; Kodaira, S.; Kaneda, Y.
2011-12-01
In the Nankai trough, there are three seismogenic zones of megathrust earthquakes (Tokai, Tonankai and Nankai earthquakes). Lithospheric structures in and around these seismogenic zones are important for the studies on mutual interactions and synchronization of their fault ruptures. Recent studies on seismic wave scattering at high frequencies (>1Hz) make it possible to estimate 3D distributions of random inhomogeneities (or scattering coefficient) in the lithosphere, and clarified that random inhomogeneity is one of the important medium properties related to microseismicity and damaged structure near the fault zone [Asano & Hasegawa, 2004; Takahashi et al. 2009]. This study estimates the spatial distribution of the power spectral density function (PSDF) of random inhomogeneities the western part of Nankai subduction zone, and examines the relations with crustal velocity structure and seismic activity. Seismic waveform data used in this study are those recorded at seismic stations of Hi-net & F-net operated by NIED, and 160 ocean bottom seismographs (OBSs) deployed at Hyuga-nada region from Dec. 2008 to Jan. 2009. This OBS observation was conducted by JAMSTEC as a part of "Research concerning Interaction Between the Tokai, Tonankai and Nankai Earthquakes" funded by Ministry of Education, Culture, Sports, Science and Technology, Japan. Spatial distribution of random inhomogeneities is estimated by the inversion analysis of the peak delay time of small earthquakes [Takahashi et al. 2009], where the peak delay time is defined as the time lag from the S-wave onset to its maximal amplitude arrival. We assumed the von Karman type functional form for the PSDF. Peak delay times are measured from root mean squared envelopes at 4-8Hz, 8-16Hz and 16-32Hz. Inversion result can be summarized as follows. Random inhomogeneities beneath the Quaternary volcanoes are characterized by strong inhomogeneities at small spatial scale (~ a few hundreds meter) and weak spectral gradient
On adaptive refinements in discrete probabilistic fracture models
Directory of Open Access Journals (Sweden)
J. Eliáš
2017-01-01
Full Text Available The possibility to adaptively change discretization density is a well acknowledged and used feature of many continuum models. It is employed to save computational time and increase solution accuracy. Recently, adaptivity has been introduced also for discrete particle models. This contribution applies adaptive technique in probabilistic discrete modelling where material properties are varying in space according to a random field. The random field discretization is adaptively refined hand in hand with the model geometry.
Exact analysis of discrete data
Hirji, Karim F
2005-01-01
Researchers in fields ranging from biology and medicine to the social sciences, law, and economics regularly encounter variables that are discrete or categorical in nature. While there is no dearth of books on the analysis and interpretation of such data, these generally focus on large sample methods. When sample sizes are not large or the data are otherwise sparse, exact methods--methods not based on asymptotic theory--are more accurate and therefore preferable.This book introduces the statistical theory, analysis methods, and computation techniques for exact analysis of discrete data. After reviewing the relevant discrete distributions, the author develops the exact methods from the ground up in a conceptually integrated manner. The topics covered range from univariate discrete data analysis, a single and several 2 x 2 tables, a single and several 2 x K tables, incidence density and inverse sampling designs, unmatched and matched case -control studies, paired binary and trinomial response models, and Markov...
A Hardware Efficient Random Number Generator for Nonuniform Distributions with Arbitrary Precision
Directory of Open Access Journals (Sweden)
Christian de Schryver
2012-01-01
number generators is a very active research field. However, most state-of-the-art architectures are either tailored to specific distributions or use up a lot of hardware resources. At ReConFig 2010, we have presented a new design that saves up to 48% of area compared to state-of-the-art inversion-based implementation, usable for arbitrary distributions and precision. In this paper, we introduce a more flexible version together with a refined segmentation scheme that allows to further reduce the approximation error significantly. We provide a free software tool allowing users to implement their own distributions easily, and we have tested our random number generator thoroughly by statistic analysis and two application tests.
Vincent, Jean-Louis; Privalle, Christopher T; Singer, Mervyn; Lorente, José A; Boehm, Erwin; Meier-Hellmann, Andreas; Darius, Harald; Ferrer, Ricard; Sirvent, Josep-Maria; Marx, Gernot; DeAngelo, Joseph
2015-01-01
To compare the effectiveness and safety of the hemoglobin-based nitric oxide scavenger, pyridoxalated hemoglobin polyoxyethylene, against placebo in patients with vasopressor-dependent distributive shock. Multicenter, randomized, placebo-controlled, open-label study. Sixty-one participating ICUs in six European countries (Austria, Belgium, Germany, the Netherlands, Spain, and United Kingdom). All patients admitted with distributive shock, defined as the presence of at least two systemic inflammatory response syndrome criteria, persisting norepinephrine dependence and evidence of organ dysfunction/hypoperfusion despite adequate fluid resuscitation. Patients were randomized to receive 0.25 mL/kg/hr pyridoxalated hemoglobin polyoxyethylene (20 mg Hb/kg/hr) or an equal volume of placebo, infused for up to 150 hours, in addition to conventional vasopressor therapy. The study was stopped after interim analysis showed higher mortality in the pyridoxalated hemoglobin polyoxyethylene group and an increased prevalence of adverse events. At this time, 377 patients had been randomized to pyridoxalated hemoglobin polyoxyethylene (n = 183) or placebo (n = 194). Age, gender, type of patient (medical/surgical), and Acute Physiology and Chronic Health Evaluation II scores were similar between groups. Twenty-eight-day mortality rate was 44.3% in the pyridoxalated hemoglobin polyoxyethylene group versus 37.6% in the placebo group (OR, 1.29; 95% CI, 0.85-1.95; p = 0.227). In patients with higher organ dysfunction scores (Sepsis-related Organ Failure Assessment > 13), mortality rates were significantly higher in the pyridoxalated hemoglobin polyoxyethylene group when compared with those in placebo-treated patients (60.9% vs 39.2%; p = 0.014). Survivors who received pyridoxalated hemoglobin polyoxyethylene had a longer vasopressor-free time (21.3 vs 19.7 d; p = 0.035). In this randomized, controlled phase III trial in patients with vasopressor-dependent distributive shock
Intelligent discrete particle swarm optimization for multiprocessor task scheduling problem
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S Sarathambekai
2017-03-01
Full Text Available Discrete particle swarm optimization is one of the most recently developed population-based meta-heuristic optimization algorithm in swarm intelligence that can be used in any discrete optimization problems. This article presents a discrete particle swarm optimization algorithm to efficiently schedule the tasks in the heterogeneous multiprocessor systems. All the optimization algorithms share a common algorithmic step, namely population initialization. It plays a significant role because it can affect the convergence speed and also the quality of the final solution. The random initialization is the most commonly used method in majority of the evolutionary algorithms to generate solutions in the initial population. The initial good quality solutions can facilitate the algorithm to locate the optimal solution or else it may prevent the algorithm from finding the optimal solution. Intelligence should be incorporated to generate the initial population in order to avoid the premature convergence. This article presents a discrete particle swarm optimization algorithm, which incorporates opposition-based technique to generate initial population and greedy algorithm to balance the load of the processors. Make span, flow time, and reliability cost are three different measures used to evaluate the efficiency of the proposed discrete particle swarm optimization algorithm for scheduling independent tasks in distributed systems. Computational simulations are done based on a set of benchmark instances to assess the performance of the proposed algorithm.
Discrete Curvatures and Discrete Minimal Surfaces
Sun, Xiang
2012-06-01
This thesis presents an overview of some approaches to compute Gaussian and mean curvature on discrete surfaces and discusses discrete minimal surfaces. The variety of applications of differential geometry in visualization and shape design leads to great interest in studying discrete surfaces. With the rich smooth surface theory in hand, one would hope that this elegant theory can still be applied to the discrete counter part. Such a generalization, however, is not always successful. While discrete surfaces have the advantage of being finite dimensional, thus easier to treat, their geometric properties such as curvatures are not well defined in the classical sense. Furthermore, the powerful calculus tool can hardly be applied. The methods in this thesis, including angular defect formula, cotangent formula, parallel meshes, relative geometry etc. are approaches based on offset meshes or generalized offset meshes. As an important application, we discuss discrete minimal surfaces and discrete Koenigs meshes.
ERROR DISTRIBUTION EVALUATION OF THE THIRD VANISHING POINT BASED ON RANDOM STATISTICAL SIMULATION
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C. Li
2012-07-01
Full Text Available POS, integrated by GPS / INS (Inertial Navigation Systems, has allowed rapid and accurate determination of position and attitude of remote sensing equipment for MMS (Mobile Mapping Systems. However, not only does INS have system error, but also it is very expensive. Therefore, in this paper error distributions of vanishing points are studied and tested in order to substitute INS for MMS in some special land-based scene, such as ground façade where usually only two vanishing points can be detected. Thus, the traditional calibration approach based on three orthogonal vanishing points is being challenged. In this article, firstly, the line clusters, which parallel to each others in object space and correspond to the vanishing points, are detected based on RANSAC (Random Sample Consensus and parallelism geometric constraint. Secondly, condition adjustment with parameters is utilized to estimate nonlinear error equations of two vanishing points (VX, VY. How to set initial weights for the adjustment solution of single image vanishing points is presented. Solving vanishing points and estimating their error distributions base on iteration method with variable weights, co-factor matrix and error ellipse theory. Thirdly, under the condition of known error ellipses of two vanishing points (VX, VY and on the basis of the triangle geometric relationship of three vanishing points, the error distribution of the third vanishing point (VZ is calculated and evaluated by random statistical simulation with ignoring camera distortion. Moreover, Monte Carlo methods utilized for random statistical estimation are presented. Finally, experimental results of vanishing points coordinate and their error distributions are shown and analyzed.
Complementarity between entanglement-assisted and quantum distributed random access code
Hameedi, Alley; Saha, Debashis; Mironowicz, Piotr; Pawłowski, Marcin; Bourennane, Mohamed
2017-05-01
Collaborative communication tasks such as random access codes (RACs) employing quantum resources have manifested great potential in enhancing information processing capabilities beyond the classical limitations. The two quantum variants of RACs, namely, quantum random access code (QRAC) and the entanglement-assisted random access code (EARAC), have demonstrated equal prowess for a number of tasks. However, there do exist specific cases where one outperforms the other. In this article, we study a family of 3 →1 distributed RACs [J. Bowles, N. Brunner, and M. Pawłowski, Phys. Rev. A 92, 022351 (2015), 10.1103/PhysRevA.92.022351] and present its general construction of both the QRAC and the EARAC. We demonstrate that, depending on the function of inputs that is sought, if QRAC achieves the maximal success probability then EARAC fails to do so and vice versa. Moreover, a tripartite Bell-type inequality associated with the EARAC variants reveals the genuine multipartite nonlocality exhibited by our protocol. We conclude with an experimental realization of the 3 →1 distributed QRAC that achieves higher success probabilities than the maximum possible with EARACs for a number of tasks.
Takahashi, T.; Obana, K.; Yamamoto, Y.; Nakanishi, A.; Kaiho, Y.; Kodaira, S.; Kaneda, Y.
2012-12-01
The Nankai trough in southwestern Japan is a convergent margin where the Philippine sea plate is subducted beneath the Eurasian plate. There are major faults segments of huge earthquakes that are called Tokai, Tonankai and Nankai earthquakes. According to the earthquake occurrence history over the past hundreds years, we must expect various rupture patters such as simultaneous or nearly continuous ruptures of plural fault segments. Japan Agency for Marine-Earth Science and Technology (JAMSTEC) conducted seismic surveys at Nankai trough in order to clarify mutual relations between seismic structures and fault segments, as a part of "Research concerning Interaction Between the Tokai, Tonankai and Nankai Earthquakes" funded by Ministry of Education, Culture, Sports, Science and Technology, Japan. This study evaluated the spatial distribution of random velocity inhomogeneities from Hyuga-nada to Kii-channel by using velocity seismograms of small and moderate sized earthquakes. Random velocity inhomogeneities are estimated by the peak delay time analysis of S-wave envelopes (e.g., Takahashi et al. 2009). Peak delay time is defined as the time lag from the S-wave onset to its maximal amplitude arrival. This quantity mainly reflects the accumulated multiple forward scattering effect due to random inhomogeneities, and is quite insensitive to the inelastic attenuation. Peak delay times are measured from the rms envelopes of horizontal components at 4-8Hz, 8-16Hz and 16-32Hz. This study used the velocity seismograms that are recorded by 495 ocean bottom seismographs and 378 onshore seismic stations. Onshore stations are composed of the F-net and Hi-net stations that are maintained by National Research Institute for Earth Science and Disaster Prevention (NIED) of Japan. It is assumed that the random inhomogeneities are represented by the von Karman type PSDF. Preliminary result of inversion analysis shows that spectral gradient of PSDF (i.e., scale dependence of
Nagilla, Rakesh; Nord, Melanie; McAtee, Jeff J; Jolivette, Larry J
2011-09-01
The purpose of this investigation was to compare selected pharmacokinetic (PK) parameters obtained by cassette and discrete dosing of compounds in rats. The concordance of PK properties obtained by the two dosing strategies was evaluated for 116 compounds representing various therapeutic programs and diverse chemical structures. The correspondence between cassette- and discrete-dosing-derived PK properties was examined semiquantitatively and qualitatively. For semiquantitative comparison, compounds with cassette-to-discrete PK parameter ratios between 0.5 and 2 (inclusive) were considered to be in agreement. For qualitative comparison, compounds were divided into three categories (low, moderate, and high) based on the value of the PK parameter; compounds that fell into the same category following cassette and discrete dosing were considered to be in agreement. Of the 116 compounds evaluated, 89%, 91%, 80%, and 91% of the compounds were semiquantitatively equivalent for the intravenous PK parameters of clearance (CL), volume of distribution (Vdss), terminal elimination plasma half-life (HL), and mean residence time (MRT), respectively, whereas 79%, 80%, 79%, and 72% were qualitatively similar for CL, Vdss, MRT, and terminal elimination plasma HL, respectively. Following oral administration, bioavailability concordance was 72% when assessed qualitatively and 78% when determined semiquantitatively. Results from these analyses indicate that a cassette dosing strategy is a viable approach to screen compounds for PK properties within a drug discovery setting. Copyright © 2011 Wiley-Liss, Inc.
Reflection principles for biased random walks and application to escape time distributions
Khantha, M.; Balakrishnan, V.
1985-12-01
We present a reflection principle for an arbitrary biased continuous time random walk (comprising both Markovian and non-Markovian processes) in the presence of a reflecting barrier on semi-infinite and finite chains. For biased walks in the presence of a reflecting barrier this principle (which cannot be derived from combinatorics) is completely different from its familiar form in the presence of an absorbing barrier. The result enables us to obtain closed-form solutions for the Laplace transform of the conditional probability for biased walks on finite chains for all three combinations of absorbing and reflecting barriers at the two ends. An important application of these solutions is the calculation of various first-passage-time and escape-time distributions. We obtain exact results for the characteristic functions of various kinds of escape time distributions for biased random walks on finite chains. For processes governed by a long-tailed event-time distribution we show that the mean time of escape from bounded regions diverges even in the presence of a bias—suggesting, in a sense, the absence of true long-range diffusion in such "frozen" processes.
Pure random search for ambient sensor distribution optimisation in a smart home environment.
Poland, Michael P; Nugent, Chris D; Wang, Hui; Chen, Liming
2011-01-01
Smart homes are living spaces facilitated with technology to allow individuals to remain in their own homes for longer, rather than be institutionalised. Sensors are the fundamental physical layer with any smart home, as the data they generate is used to inform decision support systems, facilitating appropriate actuator actions. Positioning of sensors is therefore a fundamental characteristic of a smart home. Contemporary smart home sensor distribution is aligned to either a) a total coverage approach; b) a human assessment approach. These methods for sensor arrangement are not data driven strategies, are unempirical and frequently irrational. This Study hypothesised that sensor deployment directed by an optimisation method that utilises inhabitants' spatial frequency data as the search space, would produce more optimal sensor distributions vs. the current method of sensor deployment by engineers. Seven human engineers were tasked to create sensor distributions based on perceived utility for 9 deployment scenarios. A Pure Random Search (PRS) algorithm was then tasked to create matched sensor distributions. The PRS method produced superior distributions in 98.4% of test cases (n=64) against human engineer instructed deployments when the engineers had no access to the spatial frequency data, and in 92.0% of test cases (n=64) when engineers had full access to these data. These results thus confirmed the hypothesis.
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Jayaweera SudharmanK
2010-01-01
Full Text Available Performance gain achieved by adding mobile nodes to a stationary sensor network for target detection depends on factors such as the number of mobile nodes deployed, mobility patterns, speed and energy constraints of mobile nodes, and the nature of the target locations (deterministic or random. In this paper, we address the problem of distributed detection of a randomly located target by a hybrid sensor network. Specifically, we develop two decision-fusion architectures for detection where in the first one, impact of node mobility is taken into account for decisions updating at the fusion center, while in the second model the impact of node mobility is taken at the node level decision updating. The cost of deploying mobile nodes is analyzed in terms of the minimum fraction of mobile nodes required to achieve the desired performance level within a desired delay constraint. Moreover, we consider managing node mobility under given constraints.
Hacking on decoy-state quantum key distribution system with partial phase randomization
Sun, Shi-Hai; Jiang, Mu-Sheng; Ma, Xiang-Chun; Li, Chun-Yan; Liang, Lin-Mei
2014-04-01
Quantum key distribution (QKD) provides means for unconditional secure key transmission between two distant parties. However, in practical implementations, it suffers from quantum hacking due to device imperfections. Here we propose a hybrid measurement attack, with only linear optics, homodyne detection, and single photon detection, to the widely used vacuum + weak decoy state QKD system when the phase of source is partially randomized. Our analysis shows that, in some parameter regimes, the proposed attack would result in an entanglement breaking channel but still be able to trick the legitimate users to believe they have transmitted secure keys. That is, the eavesdropper is able to steal all the key information without discovered by the users. Thus, our proposal reveals that partial phase randomization is not sufficient to guarantee the security of phase-encoding QKD systems with weak coherent states.
Simulation of the pressure field near a jet by randomly distributed vortex rings
Fung, Y. T.; Liu, C. H.; Gunzburger, M. D.
1979-01-01
Fluctuations of the pressure field in the vicinity of a jet are simulated numerically by a flow model consisting of axially symmetric vortex rings with viscous cores submerged in a uniform stream. The time interval between the shedding of successive vortices is taken to be a random variable with a probability distribution chosen to match that from experiments. It is found that up to 5 diameters downstream of the jet exit, statistics of the computed pressure field are in good agreement with experimental results. Statistical comparisons are provided for the overall sound pressure level, the peak amplitude, and the Strouhal number based on the peak frequency of the pressure signals.
Electromagnetic wave propagation in a random distribution of C{sub 60} molecules
Energy Technology Data Exchange (ETDEWEB)
Moradi, Afshin, E-mail: a.moradi@kut.ac.ir [Department of Engineering Physics, Kermanshah University of Technology, Kermanshah, Iran and Department of Nano Sciences, Institute for Studies in Theoretical Physics and Mathematics (IPM), Tehran (Iran, Islamic Republic of)
2014-10-15
Propagation of electromagnetic waves in a random distribution of C{sub 60} molecules are investigated, within the framework of the classical electrodynamics. Electronic excitations over the each C{sub 60} molecule surface are modeled by a spherical layer of electron gas represented by two interacting fluids, which takes into account the different nature of the π and σ electrons. It is found that the present medium supports four modes of electromagnetic waves, where they can be divided into two groups: one group with shorter wavelength than the light waves of the same frequency and the other with longer wavelength than the free-space radiation.
Distribution of the phenotypic effects of random homologous recombination between two virus species.
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Florence Vuillaume
2011-05-01
Full Text Available Recombination has an evident impact on virus evolution and emergence of new pathotypes, and has generated an immense literature. However, the distribution of phenotypic effects caused by genome-wide random homologous recombination has never been formally investigated. Previous data on the subject have promoted the implicit view that most viral recombinant genomes are likely to be deleterious or lethal if the nucleotide identity of parental sequences is below 90%. We decided to challenge this view by creating a bank of near-random recombinants between two viral species of the genus Begomovirus (Family Geminiviridae exhibiting 82% nucleotide identity, and by testing infectivity and in planta accumulation of recombinant clones randomly extracted from this bank. The bank was created by DNA-shuffling-a technology initially applied to the random shuffling of individual genes, and here implemented for the first time to shuffle full-length viral genomes. Together with our previously described system allowing the direct cloning of full-length infectious geminivirus genomes, it provided a unique opportunity to generate hundreds of "mosaic" virus genomes, directly testable for infectivity. A subset of 47 randomly chosen recombinants was sequenced, individually inoculated into tomato plants, and compared with the parental viruses. Surprisingly, our results showed that all recombinants were infectious and accumulated at levels comparable or intermediate to that of the parental clones. This indicates that, in our experimental system, despite the fact that the parental genomes differ by nearly 20%, lethal and/or large deleterious effects of recombination are very rare, in striking contrast to the common view that has emerged from previous studies published on other viruses.
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Junlong Zhu
2017-01-01
Full Text Available We consider a distributed constrained optimization problem over a time-varying network, where each agent only knows its own cost functions and its constraint set. However, the local constraint set may not be known in advance or consists of huge number of components in some applications. To deal with such cases, we propose a distributed stochastic subgradient algorithm over time-varying networks, where the estimate of each agent projects onto its constraint set by using random projection technique and the implement of information exchange between agents by employing asynchronous broadcast communication protocol. We show that our proposed algorithm is convergent with probability 1 by choosing suitable learning rate. For constant learning rate, we obtain an error bound, which is defined as the expected distance between the estimates of agent and the optimal solution. We also establish an asymptotic upper bound between the global objective function value at the average of the estimates and the optimal value.
Graham, John H; Robb, Daniel T; Poe, Amy R
2012-01-01
Distributed robustness is thought to influence the buffering of random phenotypic variation through the scale-free topology of gene regulatory, metabolic, and protein-protein interaction networks. If this hypothesis is true, then the phenotypic response to the perturbation of particular nodes in such a network should be proportional to the number of links those nodes make with neighboring nodes. This suggests a probability distribution approximating an inverse power-law of random phenotypic variation. Zero phenotypic variation, however, is impossible, because random molecular and cellular processes are essential to normal development. Consequently, a more realistic distribution should have a y-intercept close to zero in the lower tail, a mode greater than zero, and a long (fat) upper tail. The double Pareto-lognormal (DPLN) distribution is an ideal candidate distribution. It consists of a mixture of a lognormal body and upper and lower power-law tails. If our assumptions are true, the DPLN distribution should provide a better fit to random phenotypic variation in a large series of single-gene knockout lines than other skewed or symmetrical distributions. We fit a large published data set of single-gene knockout lines in Saccharomyces cerevisiae to seven different probability distributions: DPLN, right Pareto-lognormal (RPLN), left Pareto-lognormal (LPLN), normal, lognormal, exponential, and Pareto. The best model was judged by the Akaike Information Criterion (AIC). Phenotypic variation among gene knockouts in S. cerevisiae fits a double Pareto-lognormal (DPLN) distribution better than any of the alternative distributions, including the right Pareto-lognormal and lognormal distributions. A DPLN distribution is consistent with the hypothesis that developmental stability is mediated, in part, by distributed robustness, the resilience of gene regulatory, metabolic, and protein-protein interaction networks. Alternatively, multiplicative cell growth, and the mixing of
Supporting scalable Bayesian networks using configurable discretizer actuators
CSIR Research Space (South Africa)
Osunmakinde, I
2009-04-01
Full Text Available The authors propose a generalized model with configurable discretizer actuators as a solution to the problem of the discretization of massive numerical datasets. Their solution is based on a concurrent distribution of the actuators and uses dynamic...
On the Distribution of Indefinite Quadratic Forms in Gaussian Random Variables
Al-Naffouri, Tareq Y.
2015-10-30
© 2015 IEEE. In this work, we propose a unified approach to evaluating the CDF and PDF of indefinite quadratic forms in Gaussian random variables. Such a quantity appears in many applications in communications, signal processing, information theory, and adaptive filtering. For example, this quantity appears in the mean-square-error (MSE) analysis of the normalized least-meansquare (NLMS) adaptive algorithm, and SINR associated with each beam in beam forming applications. The trick of the proposed approach is to replace inequalities that appear in the CDF calculation with unit step functions and to use complex integral representation of the the unit step function. Complex integration allows us then to evaluate the CDF in closed form for the zero mean case and as a single dimensional integral for the non-zero mean case. Utilizing the saddle point technique allows us to closely approximate such integrals in non zero mean case. We demonstrate how our approach can be extended to other scenarios such as the joint distribution of quadratic forms and ratios of such forms, and to characterize quadratic forms in isotropic distributed random variables.We also evaluate the outage probability in multiuser beamforming using our approach to provide an application of indefinite forms in communications.
Deviations from the Gutenberg–Richter law on account of a random distribution of block sizes
Energy Technology Data Exchange (ETDEWEB)
Sibiryakov, B. P., E-mail: sibiryakovbp@ipgg.sbras.ru [Trofimuk Institute of Oil and Gas Geology and Geophysics SB RAS, Novosibirsk, 630090 (Russian Federation); Novosibirsk State University, Novosibirsk, 630090 (Russian Federation)
2015-10-27
This paper studies properties of a continuum with structure. The characteristic size of the structure governs the fact that difference relations are nonautomatically transformed into differential ones. It is impossible to consider an infinitesimal volume of a body, to which the major conservation laws could be applied, because the minimum representative volume of the body must contain at least a few elementary microstructures. The corresponding equations of motion are equations of infinite order, solutions of which include, along with usual sound waves, unusual waves with abnormally low velocities without a lower limit. It is shown that in such media weak perturbations can increase or decrease outside the limits. The number of complex roots of the corresponding dispersion equation, which can be interpreted as the number of unstable solutions, depends on the specific surface of cracks and is an almost linear dependence on a logarithmic scale, as in the seismological Gutenberg–Richter law. If the distance between one pore (crack) to another one is a random value with some distribution, we must write another dispersion equation and examine different scenarios depending on the statistical characteristics of the random distribution. In this case, there are sufficient deviations from the Gutenberg–Richter law and this theoretical result corresponds to some field and laboratory observations.
Distribution of the Height of Local Maxima of Gaussian Random Fields*
Cheng, Dan; Schwartzman, Armin
2015-01-01
Let {f(t) : t ∈ T} be a smooth Gaussian random field over a parameter space T, where T may be a subset of Euclidean space or, more generally, a Riemannian manifold. We provide a general formula for the distribution of the height of a local maximum P{f(t0)>u∣t0 is a local maximum of f(t)} when f is non-stationary. Moreover, we establish asymptotic approximations for the overshoot distribution of a local maximum P{f(t0)>u+v∣t0 is a local maximum of f(t) and f(t0) > v} as v → ∞. Assuming further that f is isotropic, we apply techniques from random matrix theory related to the Gaussian orthogonal ensemble to compute such conditional probabilities explicitly when T is Euclidean or a sphere of arbitrary dimension. Such calculations are motivated by the statistical problem of detecting peaks in the presence of smooth Gaussian noise. PMID:26478714
Mimetic discretization methods
Castillo, Jose E
2013-01-01
To help solve physical and engineering problems, mimetic or compatible algebraic discretization methods employ discrete constructs to mimic the continuous identities and theorems found in vector calculus. Mimetic Discretization Methods focuses on the recent mimetic discretization method co-developed by the first author. Based on the Castillo-Grone operators, this simple mimetic discretization method is invariably valid for spatial dimensions no greater than three. The book also presents a numerical method for obtaining corresponding discrete operators that mimic the continuum differential and
Discrete Wigner function dynamics
Energy Technology Data Exchange (ETDEWEB)
Klimov, A B; Munoz, C [Departamento de Fisica, Universidad de Guadalajara, Revolucion 1500, 44410, Guadalajara, Jalisco (Mexico)
2005-12-01
We study the evolution of the discrete Wigner function for prime and the power of prime dimensions using the discrete version of the star-product operation. Exact and semiclassical dynamics in the limit of large dimensions are considered.
Leipus, Remigijus; Philippe, Anne; Pilipauskaitė, Vytautė; Surgailis, Donatas
2015-01-01
We discuss nonparametric estimation of the distribution function $G(x)$ of the autoregressive coefficient $a \\in (-1,1)$ from a panel of $N$ random-coefficient AR(1) data, each of length $n$, by the empirical distribution function of lag 1 sample autocorrelations of individual AR(1) processes. Consistency and asymptotic normality of the empirical distribution function and a class of kernel density estimators is established under some regularity conditions on $G(x)$ as $N$ and $n$ increase to ...
Flyckt, V. M. M.; Raaymakers, B. W.; Lagendijk, J. J. W.
2006-10-01
Prediction of the temperature distribution in the eye depends on how the impact of the blood flow is taken into account. Three methods will be compared: a simplified eye anatomy that applies a single heat transfer coefficient to describe all heat transport mechanisms between the sclera and the body core, a detailed eye anatomy in which the blood flow is accounted for either by the bioheat approach, or by including the discrete vasculature in the eye and the orbit. The comparison is done both for rabbit and human anatomies, normo-thermally and when exposed to homogeneous power densities. The first simplified model predicts much higher temperatures than the latter two. It was shown that the eye is very hard to heat when taking physiological perfusion correctly into account. It was concluded that the heat transfer coefficient describing the heat transport from the sclera to the body core reported in the literature for the first simplified model is too low. The bioheat approach is appropriate for a first-order approximation of the temperature distribution in the eye when exposed to a homogeneous power density, but the discrete vasculature down to 0.2 mm in diameter needs to be taken into account when the heterogeneity of the temperature distribution at a mm scale is of interest.
A Chemical Reaction Network to Generate Random, Power-Law-Distributed Time Intervals.
Krauss, Patrick; Schulze, Holger; Metzner, Claus
2017-10-06
In Lévy walks (LWs), particles move with a fixed speed along straight line segments and turn in new directions after random time intervals that are distributed according to a power law. Such LWs are thought to be an advantageous foraging and search strategy for organisms. While complex nervous systems are certainly capable of producing such behavior, it is not clear at present how single-cell organisms can generate the long-term correlated control signals required for a LW. Here, we construct a biochemical reaction system that generates long-time correlated concentration fluctuations of a signaling substance, with a tunable fractional exponent of the autocorrelation function. The network is based on well-known modules, and its basic function is highly robust with respect to the parameter settings.
Discovery of Non-random Spatial Distribution of Impacts in the Stardust Cometary Collector
Energy Technology Data Exchange (ETDEWEB)
Westphal, A J; Bastien, R K; Borg, J; Bridges, J; Brownlee, D E; Burchell, M J; Cheng, A F; Clark, B C; Djouadi, Z; Floss, C; Franchi, I; Gainsforth, Z; Graham, G; Green, S F; Heck, P R; Horanyi, M; Hoppe, P; Horz, F P; Huth, J; Kearsley, A; Leroux, H; Marhas, K; Nakamura-Messenger, K; Sandford, S A; See, T H; Stadermann, F J; Teslich, N E; Tsitrin, S; Warren, J L; Wozniakiewicz, P J; Zolensky, M E
2007-04-06
We report the discovery that impacts in the Stardust cometary collector are not distributed randomly in the collecting media, but appear to be clustered on scales smaller than {approx} 10 cm. We also report the discovery of at least two populations of oblique tracks. We evaluated several hypotheses that could explain the observations. No hypothesis was consistent with all the observations, but the preponderance of evidence points toward at least one impact on the central Whipple shield of the spacecraft as the origin of both clustering and low-angle oblique tracks. High-angle oblique tracks unambiguously originate from a non-cometary impact on the spacecraft bus just forward of the collector.
Discrete port Hamiltonian systems
Talasila, V.; Clemente-Gallardo, J.; Clemente Gallardo, J.J.; van der Schaft, Arjan; Horacek, P; Simandl, M; Zitek, P
2005-01-01
Either from a control theoretic viewpoint or from an analysis viewpoint it is necessary to convert smooth systems to discrete systems, which can then be implemented on computers for numerical simulations. Discrete models can be obtained either by discretizing a smooth model, or by directly modeling
Szmyt, Wojciech; Guerra, Carlos; Utke, Ivo
2017-01-01
In this work we modelled the diffusive transport of a dilute gas along arrays of randomly distributed, vertically aligned nanocylinders (nanotubes or nanowires) as opposed to gas diffusion in long pores, which is described by the well-known Knudsen theory. Analytical expressions for (i) the gas diffusion coefficient inside such arrays, (ii) the time between collisions of molecules with the nanocylinder walls (mean time of flight), (iii) the surface impingement rate, and (iv) the Knudsen number of such a system were rigidly derived based on a random-walk model of a molecule that undergoes memoryless, diffusive reflections from nanocylinder walls assuming the molecular regime of gas transport. It can be specifically shown that the gas diffusion coefficient inside such arrays is inversely proportional to the areal density of cylinders and their mean diameter. An example calculation of a diffusion coefficient is delivered for a system of titanium isopropoxide molecules diffusing between vertically aligned carbon nanotubes. Our findings are important for the correct modelling and optimisation of gas-based deposition techniques, such as atomic layer deposition or chemical vapour deposition, frequently used for surface functionalisation of high-aspect-ratio nanocylinder arrays in solar cells and energy storage applications. Furthermore, gas sensing devices with high-aspect-ratio nanocylinder arrays and the growth of vertically aligned carbon nanotubes need the fundamental understanding and precise modelling of gas transport to optimise such processes.
Ledford, Christy J W; Womack, Jasmyne J; Rider, Heather A; Seehusen, Angela B; Conner, Stephen J; Lauters, Rebecca A; Hodge, Joshua A
2017-09-01
As pregnant mothers increasingly engage in shared decision making regarding prenatal decisions, such as induction of labor, the patient's level of activation may influence pregnancy outcomes. One potential tool to increase patient activation in the clinical setting is mobile applications. However, research is limited in comparing mobile apps with other modalities of patient education and engagement tools. This study was designed to test the effectiveness of a mobile app as a replacement for a spiral notebook guide as a patient education and engagement tool in the prenatal clinical setting. This randomized controlled trial was conducted in the Women's Health Clinic and Family Health Clinic of three hospitals. Repeated-measures analysis of covariance was used to test intervention effects in the study sample of 205 patients. Mothers used a mobile app interface to more frequently record information about their pregnancy; however, across time, mothers using a mobile app reported a significant decrease in patient activation. The unexpected negative effects in the group of patients randomized to the mobile app prompt these authors to recommend that health systems pause before distributing their own version of mobile apps that may decrease patient activation. Mobile apps can be inherently empowering and engaging, but how a system encourages their use may ultimately determine their adoption and success.
Internal wave generation by tidal flow over periodically and randomly distributed seamounts
Zhang, Likun; Buijsman, Maarten C.; Comino, Eva; Swinney, Harry L.
2017-06-01
We examine numerically the conversion of barotropic tidal energy into internal waves by flow over an isolated seamount and over systems of periodically and randomly distributed 1100 m tall seamounts with Gaussian profiles. The simulations use the Massachusetts Institute of Technology general circulation model (MITgcm) to calculate for an infinitely deep ocean the dependence of the energy conversion on seamount slope, seamount separation, tidal direction, and the size and aspect ratio of the simulation domain. For neighboring seamounts with a slope greater than the internal wave beam slope, wave interference reduces the conversion relative to that calculated for an isolated seamount, and relative to that predicted by linear theory for a seamount of slope less than the beam slope. The conversion by an individual seamount in a system of random seamounts separated by an average distance of 18 km is found to be suppressed by 16% relative to the conversion by an isolated seamount. This study provides insight into tidal conversion by ocean seamounts modeled as Gaussian mountains with slopes both smaller and larger than the beam slope. We conclude that the total energy conversion by all seamounts (peak height ≥1000 m) and knolls (peak height 500-1000 m), taking into account interference affects, is of the order of 1% of the total barotropic to baroclinic energy conversion in the oceans, which is about twice as large as previous estimates.
Directory of Open Access Journals (Sweden)
Wojciech Szmyt
2017-01-01
Full Text Available In this work we modelled the diffusive transport of a dilute gas along arrays of randomly distributed, vertically aligned nanocylinders (nanotubes or nanowires as opposed to gas diffusion in long pores, which is described by the well-known Knudsen theory. Analytical expressions for (i the gas diffusion coefficient inside such arrays, (ii the time between collisions of molecules with the nanocylinder walls (mean time of flight, (iii the surface impingement rate, and (iv the Knudsen number of such a system were rigidly derived based on a random-walk model of a molecule that undergoes memoryless, diffusive reflections from nanocylinder walls assuming the molecular regime of gas transport. It can be specifically shown that the gas diffusion coefficient inside such arrays is inversely proportional to the areal density of cylinders and their mean diameter. An example calculation of a diffusion coefficient is delivered for a system of titanium isopropoxide molecules diffusing between vertically aligned carbon nanotubes. Our findings are important for the correct modelling and optimisation of gas-based deposition techniques, such as atomic layer deposition or chemical vapour deposition, frequently used for surface functionalisation of high-aspect-ratio nanocylinder arrays in solar cells and energy storage applications. Furthermore, gas sensing devices with high-aspect-ratio nanocylinder arrays and the growth of vertically aligned carbon nanotubes need the fundamental understanding and precise modelling of gas transport to optimise such processes.
Numerical simulation of fibrous biomaterials with randomly distributed fiber network structure.
Jin, Tao; Stanciulescu, Ilinca
2016-08-01
This paper presents a computational framework to simulate the mechanical behavior of fibrous biomaterials with randomly distributed fiber networks. A random walk algorithm is implemented to generate the synthetic fiber network in 2D used in simulations. The embedded fiber approach is then adopted to model the fibers as embedded truss elements in the ground matrix, which is essentially equivalent to the affine fiber kinematics. The fiber-matrix interaction is partially considered in the sense that the two material components deform together, but no relative movement is considered. A variational approach is carried out to derive the element residual and stiffness matrices for finite element method (FEM), in which material and geometric nonlinearities are both included. Using a data structure proposed to record the network geometric information, the fiber network is directly incorporated into the FEM simulation without significantly increasing the computational cost. A mesh sensitivity analysis is conducted to show the influence of mesh size on various simulation results. The proposed method can be easily combined with Monte Carlo (MC) simulations to include the influence of the stochastic nature of the network and capture the material behavior in an average sense. The computational framework proposed in this work goes midway between homogenizing the fiber network into the surrounding matrix and accounting for the fully coupled fiber-matrix interaction at the segment length scale, and can be used to study the connection between the microscopic structure and the macro-mechanical behavior of fibrous biomaterials with a reasonable computational cost.
Directory of Open Access Journals (Sweden)
P. Friederichs
2008-10-01
Full Text Available Probability distributions of multivariate random variables are generally more complex compared to their univariate counterparts which is due to a possible nonlinear dependence between the random variables. One approach to this problem is the use of copulas, which have become popular over recent years, especially in fields like econometrics, finance, risk management, or insurance. Since this newly emerging field includes various practices, a controversial discussion, and vast field of literature, it is difficult to get an overview. The aim of this paper is therefore to provide an brief overview of copulas for application in meteorology and climate research. We examine the advantages and disadvantages compared to alternative approaches like e.g. mixture models, summarize the current problem of goodness-of-fit (GOF tests for copulas, and discuss the connection with multivariate extremes. An application to station data shows the simplicity and the capabilities as well as the limitations of this approach. Observations of daily precipitation and temperature are fitted to a bivariate model and demonstrate, that copulas are valuable complement to the commonly used methods.
Heinemann, Colleen
Research in material science is increasingly reliant on image-based data from experiments, demanding construction of new analysis tools that help scientists discover information from digital images. Because there is such a wide variety of materials and image modalities, detecting different compounds from imaged materials continues to be a challenging task. A vast collection of algorithms for filtering, image segmentation, and texture description have facilitated and improved accuracy for sample measurements (see Chapter 1 Introduction and Literature Review). Despite this, the community still lacks scalable, general purpose, easily configurable image analysis frameworks that allow pattern detection on different imaging modalities across multiple scales. The need for such a framework was the motivation behind the development of a distributed-memory parallel Markov Random Field based framework. Markov Random Field (MRF) algorithms provide the ability to explore contextual information about a given dataset. Given the complexity of such algorithms, however, they are limited by performance when running serial. Thus, running in some sort of parallel fashion is necessary. The effects are twofold. Not only does running the MRF algorithm in parallel provide the ability to run current datasets faster and more efficiently, it also provides the ability for datasets to continue to grow in size and still be able to be run with such frameworks. The variation of the Markov Random Field algorithm utilized in this study first oversegments the given input image and constructs a graph model based on photometric and geometric distances. Next, the resulting graph model is refactored specifically into the MRF model to target image segmentation. Finally, a distributed approach is used for the optimization process to obtain the best labeling for the graph, which is essentially the goal of using a MRF algorithm. Given the concept of using a distributed memory parallel framework, specifically
Integer valued autoregressive processes with generalized discrete Mittag-Leffler marginals
Kanichukattu K. Jose; K. D. Mariyamma
2013-01-01
In this paper we consider a generalization of discrete Mittag-Leffler distributions. We introduce and study the properties of a new distribution called geometric generalized discrete Mittag-Leffler distribution. Autoregressive processes with geometric generalized discrete Mittag-Leffler distributions are developed and studied. The distributions are further extended to develop a more general class of geometric generalized discrete semi-Mittag-Leffler distributions. The processes are extended t...
Energy Technology Data Exchange (ETDEWEB)
Kitis, George [Nuclear Physics Laboratory, Aristotle University of Thessaloniki, 54124 Thessaloniki (Greece); Pagonis, Vasilis, E-mail: vpagonis@mcdaniel.edu [Physics Department, McDaniel College, Westminster, MD 21157 (United States)
2014-09-15
Localized electronic recombination processes in donor–acceptor pairs of luminescent materials have been recently modeled using a new kinetic model based on tunneling. Within this model, recombination is assumed to take place via the excited state of the donor, and nearest-neighbor recombinations take place within a random distribution of centers. An approximate semi-analytical version of the model has been shown to simulate successfully thermally and optically stimulated luminescence (TL and OSL), linearly modulated OSL (LM-OSL) and isothermal TL processes. This paper presents a detailed analysis of the geometrical properties of the TL glow curves obtained within three different published versions of the model. The dependence of the shape of the TL glow curves on the kinetic parameters of the model is examined by allowing simultaneous random variations of the parameters, within wide ranges of physically reasonable values covering several orders of magnitude. It is found that the TL glow curves can be characterized according to their shape factors μ{sub g}, as commonly done in TL theory of delocalized transitions. The values of the shape factor are found to depend rather weakly on the activation energy E and the frequency factor s, but they have a strong dependence on the parameter ρ′ which characterizes the concentration of acceptors in the model. It is also shown by simulation that both the variable heating rate and initial rise methods are applicable in this type of model and can yield the correct value of the activation energy E. However, the initial rise method of analysis for the semianalytical version of the model fails to yield the correct E value, since it underestimates the low temperature part of the TL glow curves. Two analytical expressions are given for the TL intensity, which can be used on an empirical basis for computerized glow curve deconvolution analysis (CGCD). - Highlights: • Detailed study of TL glow curves in a tunneling model for
DEFF Research Database (Denmark)
Yura, Harold; Hanson, Steen Grüner
2012-01-01
Methods for simulation of two-dimensional signals with arbitrary power spectral densities and signal amplitude probability density functions are disclosed. The method relies on initially transforming a white noise sample set of random Gaussian distributed numbers into a corresponding set with the......Methods for simulation of two-dimensional signals with arbitrary power spectral densities and signal amplitude probability density functions are disclosed. 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 most cases the method provides satisfactory results and can thus be considered an engineering approach. Several illustrative...
Zhang, Yin; Liang, Lanju; Yang, Jing; Feng, Yijun; Zhu, Bo; Zhao, Junming; Jiang, Tian; Jin, Biaobing; Liu, Weiwei
2016-05-26
Suppressing specular electromagnetic wave reflection or backward radar cross section is important and of broad interests in practical electromagnetic engineering. Here, we present a scheme to achieve broadband backward scattering reduction through diffuse terahertz wave reflection by a flexible metasurface. The diffuse scattering of terahertz wave is caused by the randomized reflection phase distribution on the metasurface, which consists of meta-particles of differently sized metallic patches arranged on top of a grounded polyimide substrate simply through a certain computer generated pseudorandom sequence. Both numerical simulations and experimental results demonstrate the ultralow specular reflection over a broad frequency band and wide angle of incidence due to the re-distribution of the incident energy into various directions. The diffuse scattering property is also polarization insensitive and can be well preserved when the flexible metasurface is conformably wrapped on a curved reflective object. The proposed design opens up a new route for specular reflection suppression, and may be applicable in stealth and other technology in the terahertz spectrum.
Trophallaxis-inspired model for distributed transport between randomly interacting agents
Gräwer, Johannes; Ronellenfitsch, Henrik; Mazza, Marco G.; Katifori, Eleni
2017-08-01
Trophallaxis, the regurgitation and mouth to mouth transfer of liquid food between members of eusocial insect societies, is an important process that allows the fast and efficient dissemination of food in the colony. Trophallactic systems are typically treated as a network of agent interactions. This approach, though valuable, does not easily lend itself to analytic predictions. In this work we consider a simple trophallactic system of randomly interacting agents with finite carrying capacity, and calculate analytically and via a series of simulations the global food intake rate for the whole colony as well as observables describing how uniformly the food is distributed within the nest. Our model and predictions provide a useful benchmark to assess to what level the observed food uptake rates and efficiency in food distribution is due to stochastic effects or specific trophallactic strategies by the ant colony. Our work also serves as a stepping stone to describing the collective properties of more complex trophallactic systems, such as those including division of labor between foragers and workers.
DEFF Research Database (Denmark)
Workman, Christopher; Krogh, Anders Stærmose
1999-01-01
This work investigates whether mRNA has a lower estimated folding free energy than random sequences. The free energy estimates are calculated by the mfold program for prediction of RNA secondary structures. For a set of 46 mRNAs it is shown that the predicted free energy is not significantly...... different from random sequences with the same dinucleotide distribution. For random sequences with the same mononucleotide distribution it has previously been shown that the native mRNA sequences have a lower predicted free energy, which indicates a more stable structure than random sequences. However......, dinucleotide content is important when assessing the significance of predicted free energy as the physical stability of RNA secondary structure is known to depend on dinucleotide base stacking energies. Even known RNA secondary structures, like tRNAs, can be shown to have predicted free energies...
Drake, Marvin D.; Bas, Christophe F.; Gervais, David; Renda, Priscilla F.; Townsend, Daniel; Rushanan, Joseph J.; Francoeur, Joe; Donnangelo, Nick; Stenner, Michael D.
2013-05-01
We describe an experimental laboratory system that generates and distributes random binary sequence bit streams between two optical terminals (labeled Alice and Bob). The random binary sequence is generated through probing the optical channel of a turbulent atmosphere between the two terminals with coincident laser beams. The two laser beams experience differential phase delays while propagating through the atmospheric optical channel. The differential phase delays are detected and sampled at each terminal to yield raw random bit streams. The random bit streams are processed to remove bit errors and, through privacy amplification, to yield a bit stream known only to Alice and Bob. The same chaotic physical mechanism that provides randomness also provides confidentiality. The laboratory system yielded secret key bit rates of a few bits/second. For external optical channels over longer channel lengths with atmospheric turbulence levels, secret bit rates of 10 s of bits/second are predicted.
Siri, Benoît; Berry, Hugues; Cessac, Bruno; Delord, Bruno; Quoy, Mathias
2008-12-01
We present a mathematical analysis of the effects of Hebbian learning in random recurrent neural networks, with a generic Hebbian learning rule, including passive forgetting and different timescales, for neuronal activity and learning dynamics. Previous numerical work has reported that Hebbian learning drives the system from chaos to a steady state through a sequence of bifurcations. Here, we interpret these results mathematically and show that these effects, involving a complex coupling between neuronal dynamics and synaptic graph structure, can be analyzed using Jacobian matrices, which introduce both a structural and a dynamical point of view on neural network evolution. Furthermore, we show that sensitivity to a learned pattern is maximal when the largest Lyapunov exponent is close to 0. We discuss how neural networks may take advantage of this regime of high functional interest.
Objective Bayesian meta-analysis for sparse discrete data.
Moreno, E; Vázquez-Polo, F J; Negrín, M A
2014-09-20
This paper presents a Bayesian model for meta-analysis of sparse discrete binomial data, which are out of the scope of the usual hierarchical normal random-effect models. Treatment effectiveness data are often of this type. The crucial linking distribution between the effectiveness conditional on the healthcare center and the unconditional effectiveness is constructed from specific bivariate classes of distributions with given marginals. This assures coherency between the marginal and conditional prior distributions utilized in the analysis. Further, we impose a bivariate class of priors that is able to accommodate a wide range of heterogeneity degrees between the multicenter clinical trials involved. Applications to real multicenter data are given and compared with previous meta-analysis. Copyright © 2014 John Wiley & Sons, Ltd.
Random walk with nonuniform angular distribution biased by an external periodic pulse
Acharyya, Aranyak
2016-11-01
We studied the motion of a random walker in two dimensions with nonuniform angular distribution biased by an external periodic pulse. Here, we analytically calculated the mean square displacement (end-to-end distance of a walk after n time steps), without bias and with bias. We determined the average x-component of the final displacement of the walker. Interestingly, we noted that for a particular periodicity of the bias, this average x-component of the final displacement becomes approximately zero. The average y-component of the final displacement is found to be zero for any perodicity of the bias, and its reason can be attributed to the nature of the probability density function of the angle (subtended by the displacement vector with the x-axis). These analytical results are also supported by computer simulations. The present study may be thought of as a model for arresting the bacterial motion (along a preferred direction) by an external periodic bias. This article will be useful for undergraduate students of physics, statistics and biology as an example of an interdisciplinary approach to understand a way to control bacterial motion.
McPhee, James; Videla, Yohann
2014-05-01
The 5000-km2 upper Maipo River Basin, in central Chile's Andes, has an adequate streamgage network but almost no meteorological or snow accumulation data. Therefore, hydrologic model parameterization is strongly subject to model errors stemming from input and model-state uncertainty. In this research, we apply the Cold Regions Hydrologic Model (CRHM) to the basin, force it with reanalysis data downscaled to an appropriate resolution, and inform a parsimonious basin discretization, based on the hydrologic response unit concept, with distributed data on snowpack properties obtained through snow surveys for two seasons. With minimal calibration the model is able to reproduce the seasonal accumulation and melt cycle as recorded in the one snow pillow available for the basin, and although a bias in maximum accumulation persists, snowpack persistence in time is appropriately simulated based on snow water equivalent and snow covered area observations. Blowing snow events were simulated by the model whenever daily wind speed surpassed 8 m/s, although the use of daily instead of hourly data to force the model suggests that this phenomenon could be underestimated. We investigate the representation of snow redistribution by the model, and compare it with small-scale observations of wintertime snow accumulation on glaciers, in a first step towards characterizing ice distribution within a HRU spatial discretization. Although built at a different spatial scale, we present a comparison of simulated results with distributed snow depth data obtained within a 40 km2 sub-basin of the main Maipo watershed in two snow surveys carried out at the end of winter seasons 2011 and 2012, and compare basin-wide SWE estimates with a regression tree extrapolation of the observed data.
Nezhadhaghighi, Mohsen Ghasemi
2017-08-01
Here, we present results of numerical simulations and the scaling characteristics of one-dimensional random fluctuations with heavy-tailed probability distribution functions. Assuming that the distribution function of the random fluctuations obeys Lévy statistics with a power-law scaling exponent, we investigate the fractional diffusion equation in the presence of μ -stable Lévy noise. We study the scaling properties of the global width and two-point correlation functions and then compare the analytical and numerical results for the growth exponent β and the roughness exponent α . We also investigate the fractional Fokker-Planck equation for heavy-tailed random fluctuations. We show that the fractional diffusion processes in the presence of μ -stable Lévy noise display special scaling properties in the probability distribution function (PDF). Finally, we numerically study the scaling properties of the heavy-tailed random fluctuations by using the diffusion entropy analysis. This method is based on the evaluation of the Shannon entropy of the PDF generated by the random fluctuations, rather than on the measurement of the global width of the process. We apply the diffusion entropy analysis to extract the growth exponent β and to confirm the validity of our numerical analysis.
Bhattacharyya, Pratip; Chakrabarti, Bikas K.
2008-01-01
We study different ways of determining the mean distance (r[subscript n]) between a reference point and its nth neighbour among random points distributed with uniform density in a D-dimensional Euclidean space. First, we present a heuristic method; though this method provides only a crude mathematical result, it shows a simple way of estimating…
The distribution of first hitting times of random walks on directed Erdős-Rényi networks
Tishby, Ido; Biham, Ofer; Katzav, Eytan
2017-04-01
We present analytical results for the distribution of first hitting times of random walkers (RWs) on directed Erdős-Rényi (ER) networks. Starting from a random initial node, a random walker hops randomly along directed edges between adjacent nodes in the network. The path terminates either by the retracing scenario, when the walker enters a node which it has already visited before, or by the trapping scenario, when it becomes trapped in a dead-end node from which it cannot exit. The path length, namely the number of steps, d, pursued by the random walker from the initial node up to its termination, is called the first hitting time. Using recursion equations, we obtain analytical results for the tail distribution of first hitting times, P≤ft(d>\\ell \\right) . The results are found to be in excellent agreement with numerical simulations. It turns out that the distribution P≤ft(d>\\ell \\right) can be expressed as a product of an exponential distribution and a Rayleigh distribution. We obtain expressions for the mean, median and standard deviation of this distribution in terms of the network size and its mean degree. We also calculate the distribution of last hitting times, namely the path lengths of self-avoiding walks on directed ER networks, which do not retrace their paths. The last hitting times are found to be much longer than the first hitting times. The results are compared to those obtained for undirected ER networks. It is found that the first hitting times of RWs in a directed ER network are much longer than in the corresponding undirected network. This is due to the fact that RWs on directed networks do not exhibit the backtracking scenario, which is a dominant termination mechanism of RWs on undirected networks. It is shown that our approach also applies to a broader class of networks, referred to as semi-ER networks, in which the distribution of in-degrees is Poisson, while the out-degrees may follow any desired distribution with the same mean as
Directory of Open Access Journals (Sweden)
Jun Xie
2017-07-01
Full Text Available The economic dispatch problem of a virtual power plant (VPP is becoming non-convex for distributed generators’ characteristics of valve-point loading effects, prohibited operating zones, and multiple fuel options. In this paper, the economic dispatch model of VPP is established and then solved by a distributed randomized gradient-free algorithm. To deal with the non-smooth objective function, its Gauss approximation is used to construct distributed randomized gradient-free oracles in optimization iterations. A projection operator is also introduced to solve the discontinuous variable space problem. An example simulation is implemented on a modified IEEE-34 bus test system, and the results demonstrate the effectiveness and applicability of the proposed algorithm.
A new discrete filled function algorithm for discrete global optimization
Yongjian, Yang; Yumei, Liang
2007-05-01
A definition of the discrete filled function is given in this paper. Based on the definition, a discrete filled function is proposed. Theoretical properties of the proposed discrete filled function are investigated, and an algorithm for discrete global optimization is developed from the new discrete filled function. The implementation of the algorithms on several test problems is reported with satisfactory numerical results.
Discrete Mathematics Re "Tooled."
Grassl, Richard M.; Mingus, Tabitha T. Y.
1999-01-01
Indicates the importance of teaching discrete mathematics. Describes how the use of technology can enhance the teaching and learning of discrete mathematics. Explorations using Excel, Derive, and the TI-92 proved how preservice and inservice teachers experienced a new dimension in problem solving and discovery. (ASK)
Linearity stabilizes discrete breathers
Indian Academy of Sciences (India)
2015-11-27
Nov 27, 2015 ... Here we study the dynamics of highly localized excitations, or discrete breathers, which are known to be initiated by the quasistatic stretching of bonds between adjacent particles. We show via dynamical simulations that acoustic waves introduced by the harmonic term stabilize the discrete breather by ...
DEFF Research Database (Denmark)
Jeong, Cheol-Ho
2009-01-01
discrepancies between the measured value and the theoretical random incidence absorption coefficient. Therefore the angular distribution of the incident acoustic energy onto an absorber sample should be taken into account. The angular distribution of the incident energy density was simulated using the beam...... tracing method for various room shapes and source positions. The averaged angular distribution is found to be similar to a Gaussian distribution. As a result, an angle-weighted absorption coefficient was proposed by considering the angular energy distribution to improve the agreement between...... the theoretical absorption coefficient and the reverberation room measurement. The angle-weighted absorption coefficient, together with the size correction, agrees satisfactorily with the measured absorption data by the reverberation chamber method. At high frequencies and for large samples, the averaged...
Okuyama, Yoshifumi
2014-01-01
Discrete Control Systems establishes a basis for the analysis and design of discretized/quantized control systemsfor continuous physical systems. Beginning with the necessary mathematical foundations and system-model descriptions, the text moves on to derive a robust stability condition. To keep a practical perspective on the uncertain physical systems considered, most of the methods treated are carried out in the frequency domain. As part of the design procedure, modified Nyquist–Hall and Nichols diagrams are presented and discretized proportional–integral–derivative control schemes are reconsidered. Schemes for model-reference feedback and discrete-type observers are proposed. Although single-loop feedback systems form the core of the text, some consideration is given to multiple loops and nonlinearities. The robust control performance and stability of interval systems (with multiple uncertainties) are outlined. Finally, the monograph describes the relationship between feedback-control and discrete ev...
Maximum-entropy probability distributions under Lp-norm constraints
Dolinar, S.
1991-01-01
Continuous probability density functions and discrete probability mass functions are tabulated which maximize the differential entropy or absolute entropy, respectively, among all probability distributions with a given L sub p norm (i.e., a given pth absolute moment when p is a finite integer) and unconstrained or constrained value set. Expressions for the maximum entropy are evaluated as functions of the L sub p norm. The most interesting results are obtained and plotted for unconstrained (real valued) continuous random variables and for integer valued discrete random variables. The maximum entropy expressions are obtained in closed form for unconstrained continuous random variables, and in this case there is a simple straight line relationship between the maximum differential entropy and the logarithm of the L sub p norm. Corresponding expressions for arbitrary discrete and constrained continuous random variables are given parametrically; closed form expressions are available only for special cases. However, simpler alternative bounds on the maximum entropy of integer valued discrete random variables are obtained by applying the differential entropy results to continuous random variables which approximate the integer valued random variables in a natural manner. All the results are presented in an integrated framework that includes continuous and discrete random variables, constraints on the permissible value set, and all possible values of p. Understanding such as this is useful in evaluating the performance of data compression schemes.
Directory of Open Access Journals (Sweden)
Wanxing Sheng
2016-05-01
Full Text Available In this paper, a reactive power optimization method based on historical data is investigated to solve the dynamic reactive power optimization problem in distribution network. In order to reflect the variation of loads, network loads are represented in a form of random matrix. Load similarity (LS is defined to measure the degree of similarity between the loads in different days and the calculation method of the load similarity of load random matrix (LRM is presented. By calculating the load similarity between the forecasting random matrix and the random matrix of historical load, the historical reactive power optimization dispatching scheme that most matches the forecasting load can be found for reactive power control usage. The differences of daily load curves between working days and weekends in different seasons are considered in the proposed method. The proposed method is tested on a standard 14 nodes distribution network with three different types of load. The computational result demonstrates that the proposed method for reactive power optimization is fast, feasible and effective in distribution network.
Tomita, Toshihiro; Miyaji, Kousuke
2016-04-01
The dependence of random telegraph noise (RTN) amplitude distribution on the number of traps and trap depth position is investigated using three-dimensional Monte Carlo device simulation including random dopant fluctuation (RDF) in a 30 nm NAND multi level flash memory. The ΔV th tail distribution becomes broad at fixed double traps, indicating that the number of traps greatly affects the worst RTN characteristics. It is also found that for both fixed single and fixed double traps, the ΔV th distribution in the lowest cell threshold voltage (V th) state shows the broadest distribution among all cell V th states. This is because the drain current flows at the channel surface in the lowest cell V th state, while at a high cell V th, it flows at the deeper position owing to the fringing coupling between the control gate (CG) and the channel. In this work, the ΔV th distribution with the number of traps following the Poisson distribution is also considered to cope with the variations in trap number. As a result, it is found that the number of traps is an important factor for understanding RTN characteristics. In addition, considering trap position in the tunnel oxide thickness direction is also an important factor.
Zheng, Yang; Zhou, Jianzhong; Xu, Yanhe; Zhang, Yuncheng; Qian, Zhongdong
2017-05-01
This paper proposes a distributed model predictive control based load frequency control (MPC-LFC) scheme to improve control performances in the frequency regulation of power system. In order to reduce the computational burden in the rolling optimization with a sufficiently large prediction horizon, the orthonormal Laguerre functions are utilized to approximate the predicted control trajectory. The closed-loop stability of the proposed MPC scheme is achieved by adding a terminal equality constraint to the online quadratic optimization and taking the cost function as the Lyapunov function. Furthermore, the treatments of some typical constraints in load frequency control have been studied based on the specific Laguerre-based formulations. Simulations have been conducted in two different interconnected power systems to validate the effectiveness of the proposed distributed MPC-LFC as well as its superiority over the comparative methods. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Finite Discrete Gabor Analysis
DEFF Research Database (Denmark)
Søndergaard, Peter Lempel
2007-01-01
frequency bands at certain times. Gabor theory can be formulated for both functions on the real line and for discrete signals of finite length. The two theories are largely the same because many aspects come from the same underlying theory of locally compact Abelian groups. The two types of Gabor systems...... on the real line to be well approximated by finite and discrete Gabor frames. This method of approximation is especially attractive because efficient numerical methods exists for doing computations with finite, discrete Gabor systems. This thesis presents new algorithms for the efficient computation of finite...
Ma, L. X.; Tan, J. Y.; Zhao, J. M.; Wang, F. Q.; Wang, C. A.
2017-01-01
The radiative transfer equation (RTE) has been widely used to deal with multiple scattering of light by sparsely and randomly distributed discrete particles. However, for densely packed particles, the RTE becomes questionable due to strong dependent scattering effects. This paper examines the accuracy of RTE by comparing with the exact electromagnetic theory. For an imaginary spherical volume filled with randomly distributed, densely packed spheres, the RTE is solved by the Monte Carlo method combined with the Percus-Yevick hard model to consider the dependent scattering effect, while the electromagnetic calculation is based on the multi-sphere superposition T-matrix method. The Mueller matrix elements of the system with different size parameters and volume fractions of spheres are obtained using both methods. The results verify that the RTE fails to deal with the systems with a high-volume fraction due to the dependent scattering effects. Apart from the effects of forward interference scattering and coherent backscattering, the Percus-Yevick hard sphere model shows good accuracy in accounting for the far-field interference effects for medium or smaller size parameters (up to 6.964 in this study). For densely packed discrete spheres with large size parameters (equals 13.928 in this study), the improvement of dependent scattering correction tends to deteriorate. The observations indicate that caution must be taken when using RTE in dealing with the radiative transfer in dense discrete random media even though the dependent scattering correction is applied.
Pearls of Discrete Mathematics
Erickson, Martin
2009-01-01
Presents methods for solving counting problems and other types of problems that involve discrete structures. This work illustrates the relationship of these structures to algebra, geometry, number theory and combinatorics. It addresses topics such as information and game theories
Goodrich, Christopher
2015-01-01
This text provides the first comprehensive treatment of the discrete fractional calculus. Experienced researchers will find the text useful as a reference for discrete fractional calculus and topics of current interest. Students who are interested in learning about discrete fractional calculus will find this text to provide a useful starting point. Several exercises are offered at the end of each chapter and select answers have been provided at the end of the book. The presentation of the content is designed to give ample flexibility for potential use in a myriad of courses and for independent study. The novel approach taken by the authors includes a simultaneous treatment of the fractional- and integer-order difference calculus (on a variety of time scales, including both the usual forward and backwards difference operators). The reader will acquire a solid foundation in the classical topics of the discrete calculus while being introduced to exciting recent developments, bringing them to the frontiers of the...
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 18; Issue 1. Discrete Event Simulation. Matthew Jacob ... Keywords. Simulation; modelling; computer programming. Author Affiliations. Matthew Jacob1. Department of Computer Science and Automation, Indian Institute of Science, Bangalore 560 012.
Discrete computational structures
Korfhage, Robert R
1974-01-01
Discrete Computational Structures describes discrete mathematical concepts that are important to computing, covering necessary mathematical fundamentals, computer representation of sets, graph theory, storage minimization, and bandwidth. The book also explains conceptual framework (Gorn trees, searching, subroutines) and directed graphs (flowcharts, critical paths, information network). The text discusses algebra particularly as it applies to concentrates on semigroups, groups, lattices, propositional calculus, including a new tabular method of Boolean function minimization. The text emphasize
Chang, Do Il; Pelouch, Wayne; Patki, Pallavi; McLaughlin, John
2011-12-12
Unrepeatered transmission of 8 x 120 Gb/s over 444.2 km (76.6 dB) and multi-rate transmission of 8 x 120 Gb/s and 9 x 10.7 Gb/s over a 75.4 dB span have been demonstrated with off-line digital processing for the coherent 120 Gb/s channels. Transmission of 2 x 120 Gb/s with 7 x 12.5 Gb/s over 78 dB is also demonstrated with a real-time ASIC processor. All transmission results have been achieved using standard effective-area pure-silica-core fiber using forward and backward distributed Raman amplification and remotely-pumped erbium fiber. ASIC real-time processed results match well with off-line processing. © 2011 Optical Society of America
Hildebrandt, Thomas; Pick, Denis; Einax, Jürgen W
2012-02-01
The pollution of soil and environment as a result of human activity is a major problem. Nowadays, the determination of local contaminations is of interest for environmental remediation. These hotspots can have various toxic effects on plants, animals, humans, and the whole ecological system. However, economical and juridical consequences are also possible, e.g., high costs for remediation measures. In this study three sampling strategies (simple random sampling, stratified sampling, and systematic sampling) were applied on randomly distributed hotspot contaminations to prove their efficiency in term of finding hotspots. The results were used for the validation of a computerized simulation. This application can simulate the contamination on a field, the sampling pattern, and a virtual sampling. A constant hit rate showed that none of the sampling patterns could reach better results than others. Furthermore, the uncertainty associated with the results is described by confidence intervals. It is to be considered that the uncertainty during sampling is enormous and will decrease slightly, even the number of samples applied was increased to an unreasonable amount. It is hardly possible to identify the exact number of randomly distributed hotspot contaminations by statistical sampling. But a range of possible results could be calculated. Depending on various parameters such as shape and size of the area, number of hotspots, and sample quantity, optimal sampling strategies could be derived. Furthermore, an estimation of bias arising from sampling methodology is possible. The developed computerized simulation is an innovative tool for optimizing sampling strategies in terrestrial compartments for hotspot distributions.
Chen, Ying-ping; Chen, Chao-Hong
2010-01-01
An adaptive discretization method, called split-on-demand (SoD), enables estimation of distribution algorithms (EDAs) for discrete variables to solve continuous optimization problems. SoD randomly splits a continuous interval if the number of search points within the interval exceeds a threshold, which is decreased at every iteration. After the split operation, the nonempty intervals are assigned integer codes, and the search points are discretized accordingly. As an example of using SoD with EDAs, the integration of SoD and the extended compact genetic algorithm (ECGA) is presented and numerically examined. In this integration, we adopt a local search mechanism as an optional component of our back end optimization engine. As a result, the proposed framework can be considered as a memetic algorithm, and SoD can potentially be applied to other memetic algorithms. The numerical experiments consist of two parts: (1) a set of benchmark functions on which ECGA with SoD and ECGA with two well-known discretization methods: the fixed-height histogram (FHH) and the fixed-width histogram (FWH) are compared; (2) a real-world application, the economic dispatch problem, on which ECGA with SoD is compared to other methods. The experimental results indicate that SoD is a better discretization method to work with ECGA. Moreover, ECGA with SoD works quite well on the economic dispatch problem and delivers solutions better than the best known results obtained by other methods in existence.
Zhang, Chao; Lin, Hong-bo; Li, Yue; Yang, Bao-jun
2013-09-01
Time-Frequency Peak Filtering (TFPF) is an effective method to eliminate pervasive random noise when seismic signals are analyzed. In conventional TFPF, the pseudo Wigner-Ville distribution (PWVD) is used for estimating instantaneous frequency (IF), but is sensitive to noise interferences that mask the borderline between signal and noise and detract the energy concentration on the IF curve. This leads to the deviation of the peaks of the pseudo Wigner-Ville distribution from the instantaneous frequency, which is the cause of undesirable lateral oscillations as well as of amplitude attenuation of the highly varying seismic signal, and ultimately of the biased seismic signal. With the purpose to overcome greatly these drawbacks and increase the signal-to-noise ratio, we propose in this paper a TFPF refinement that is based upon the joint time-frequency distribution (JTFD). The joint time-frequency distribution is obtained by the combination of the PWVD and smooth PWVD (SPWVD). First we use SPWVD to generate a broad time-frequency area of the signal. Then this area is filtered with a step function to remove some divergent time-frequency points. Finally, the joint time-frequency distribution JTFD is obtained from PWVD weighted by this filtered distribution. The objective pursued with all these operations is to reduce the effects of the interferences and enhance the energy concentration around the IF of the signal in the time-frequency domain. Experiments with synthetic and real seismic data demonstrate that TFPF based on the joint time-frequency distribution can effectively suppress strong random noise and preserve events of interest.
Distribution of level spacing ratios using one-plus two-body random ...
Indian Academy of Sciences (India)
2015-02-03
Feb 3, 2015 ... Probability distribution (()) of the level spacing ratios has been introduced recently and is used to investigate many-body localization as well as to quantify the distance from integrability on finite size lattices. In this paper, we study the distribution of the ratio of consecutive level spacings using one-body ...
The Effect of Distributed Practice in Undergraduate Statistics Homework Sets: A Randomized Trial
Crissinger, Bryan R.
2015-01-01
Most homework sets in statistics courses are constructed so that students concentrate or "mass" their practice on a certain topic in one problem set. Distributed practice homework sets include review problems in each set so that practice on a topic is distributed across problem sets. There is a body of research that points to the…
On the Distribution of Norm of Vector Projection and Rejection of Two Complex Normal Random Vectors
Directory of Open Access Journals (Sweden)
Mehdi Maleki
2015-01-01
Full Text Available Vector projection and vector rejection are highly common and useful operations in mathematics, information theory, and signal processing. In this paper, we find the distribution of the norm of projection and rejection vectors when the original vectors are standard complex normally distributed.
Spectral shaping of a randomized PWM DC-DC converter using maximum entropy probability distributions
CSIR Research Space (South Africa)
Dove, Albert
2017-01-01
Full Text Available stream_source_info Dove_2018.pdf.txt stream_content_type text/plain stream_size 26566 Content-Encoding UTF-8 stream_name Dove_2018.pdf.txt Content-Type text/plain; charset=UTF-8 SPECTRAL SHAPING OF A RANDOMIZED PWM DC... behind spectral shaping is to select a randomization technique with its associated PDF to analytically obtain a specified spectral profile [21]. The benefits of this idea comes in being able to achieve some level of controllability on the spectral content...
Cooper, M A
2000-01-01
We present various approximations for the angular distribution of particles emerging from an optically thick, purely isotropically scattering region into a vacuum. Our motivation is to use such a distribution for the Fleck-Canfield random walk method [1] for implicit Monte Carlo (IMC) [2] radiation transport problems. We demonstrate that the cosine distribution recommended in the original random walk paper [1] is a poor approximation to the angular distribution predicted by transport theory. Then we examine other approximations that more closely match the transport angular distribution.
DEFF Research Database (Denmark)
Visser, Andre
1997-01-01
Random walk simulation has the potential to be an extremely powerful tool in the investigation of turbulence in environmental processes. However, care must be taken in applying such simulations to the motion of particles in turbulent marine systems where turbulent diffusivity is commonly spatiall...
Directory of Open Access Journals (Sweden)
Maximiano Pinheiro
2012-01-01
Full Text Available Marginal probability density and cumulative distribution functions are presented for multidimensional variables defined by nonsingular affine transformations of vectors of independent two-piece normal variables, the most important subclass of Ferreira and Steel's general multivariate skewed distributions. The marginal functions are obtained by first expressing the joint density as a mixture of Arellano-Valle and Azzalini's unified skew-normal densities and then using the property of closure under marginalization of the latter class.
Maximiano Pinheiro
2012-01-01
Marginal probability density and cumulative distribution functions are presented for multidimensional variables defined by nonsingular affine transformations of vectors of independent two-piece normal variables, the most important subclass of Ferreira and Steel's general multivariate skewed distributions. The marginal functions are obtained by first expressing the joint density as a mixture of Arellano-Valle and Azzalini's unified skew-normal densities and then using the property of closure u...
Are anesthesia start and end times randomly distributed? The influence of electronic records.
Deal, Litisha G; Nyland, Michael E; Gravenstein, Nikolaus; Tighe, Patrick
2014-06-01
To perform a frequency analysis of start minute digits (SMD) and end minute digits (EMD) taken from the electronic, computer-assisted, and manual anesthesia billing-record systems. Retrospective cross-sectional review. University medical center. This cross-sectional review was conducted on billing records from a single healthcare institution over a 15-month period. A total of 30,738 cases were analyzed. For each record, the start time and end time were recorded. Distributions of SMD and EMD were tested against the null hypothesis of a frequency distribution equivalently spread between zero and nine. SMD and EMD aggregate distributions each differed from equivalency (P record, no differences were found between the recorded and expected equivalent distribution patterns for electronic anesthesia records for start minute (P records maintained nonequivalent distribution patterns for SMD and EMD (P record system, with automated time capture of events verified by the user, produces a more unified distribution of billing times than do more traditional methods of entering billing times. Copyright © 2014 Elsevier Inc. All rights reserved.
Directory of Open Access Journals (Sweden)
Prateek Sharma
2015-04-01
Full Text Available Abstract Simulation can be regarded as the emulation of the behavior of a real-world system over an interval of time. The process of simulation relies upon the generation of the history of a system and then analyzing that history to predict the outcome and improve the working of real systems. Simulations can be of various kinds but the topic of interest here is one of the most important kind of simulation which is Discrete-Event Simulation which models the system as a discrete sequence of events in time. So this paper aims at introducing about Discrete-Event Simulation and analyzing how it is beneficial to the real world systems.
Discrete systems and integrability
Hietarinta, J; Nijhoff, F W
2016-01-01
This first introductory text to discrete integrable systems introduces key notions of integrability from the vantage point of discrete systems, also making connections with the continuous theory where relevant. While treating the material at an elementary level, the book also highlights many recent developments. Topics include: Darboux and Bäcklund transformations; difference equations and special functions; multidimensional consistency of integrable lattice equations; associated linear problems (Lax pairs); connections with Padé approximants and convergence algorithms; singularities and geometry; Hirota's bilinear formalism for lattices; intriguing properties of discrete Painlevé equations; and the novel theory of Lagrangian multiforms. The book builds the material in an organic way, emphasizing interconnections between the various approaches, while the exposition is mostly done through explicit computations on key examples. Written by respected experts in the field, the numerous exercises and the thoroug...
Discrete choice models with multiplicative error terms
DEFF Research Database (Denmark)
Fosgerau, Mogens; Bierlaire, Michel
2009-01-01
The conditional indirect utility of many random utility maximization (RUM) discrete choice models is specified as a sum of an index V depending on observables and an independent random term ε. In general, the universe of RUM consistent models is much larger, even fixing some specification of V due...... differences. We develop some properties of this type of model and show that in several cases the change from an additive to a multiplicative formulation, maintaining a specification of V, may lead to a large improvement in fit, sometimes larger than that gained from introducing random coefficients in V....
DISCRETE MATHEMATICS/NUMBER THEORY
Mrs. Manju Devi*
2017-01-01
Discrete mathematics is the study of mathematical structures that are fundamentally discrete rather than continuous. In contrast to real numbers that have the property of varying "smoothly", the objects studied in discrete mathematics such as integers, graphs, and statements do not vary smoothly in this way, but have distinct, separated values. Discrete mathematics therefore excludes topics in "continuous mathematics" such as calculus and analysis. Discrete objects can often be enumerated by ...
Naine, Tarun Bharath; Gundawar, Manoj Kumar
2017-09-01
We demonstrate a very powerful correlation between the discrete probability of distances of neighboring cells and thermal wave propagation rate, for a system of cells spread on a one-dimensional chain. A gamma distribution is employed to model the distances of neighboring cells. In the absence of an analytical solution and the differences in ignition times of adjacent reaction cells following non-Markovian statistics, invariably the solution for thermal wave propagation rate for a one-dimensional system with randomly distributed cells is obtained by numerical simulations. However, such simulations which are based on Monte-Carlo methods require several iterations of calculations for different realizations of distribution of adjacent cells. For several one-dimensional systems, differing in the value of shaping parameter of the gamma distribution, we show that the average reaction front propagation rates obtained by a discrete probability between two limits, shows excellent agreement with those obtained numerically. With the upper limit at 1.3, the lower limit depends on the non-dimensional ignition temperature. Additionally, this approach also facilitates the prediction of burning limits of heterogeneous thermal mixtures. The proposed method completely eliminates the need for laborious, time intensive numerical calculations where the thermal wave propagation rates can now be calculated based only on macroscopic entity of discrete probability.
Introductory discrete mathematics
Balakrishnan, V K
2010-01-01
This concise text offers an introduction to discrete mathematics for undergraduate students in computer science and mathematics. Mathematics educators consider it vital that their students be exposed to a course in discrete methods that introduces them to combinatorial mathematics and to algebraic and logical structures focusing on the interplay between computer science and mathematics. The present volume emphasizes combinatorics, graph theory with applications to some stand network optimization problems, and algorithms to solve these problems.Chapters 0-3 cover fundamental operations involv
Bouleau, Nicolas; Chorro, Christophe
2017-08-01
In this paper we consider some elementary and fair zero-sum games of chance in order to study the impact of random effects on the wealth distribution of N interacting players. Even if an exhaustive analytical study of such games between many players may be tricky, numerical experiments highlight interesting asymptotic properties. In particular, we emphasize that randomness plays a key role in concentrating wealth in the extreme, in the hands of a single player. From a mathematical perspective, we interestingly adopt some diffusion limits for small and high-frequency transactions which are otherwise extensively used in population genetics. Finally, the impact of small tax rates on the preceding dynamics is discussed for several regulation mechanisms. We show that taxation of income is not sufficient to overcome this extreme concentration process in contrast to the uniform taxation of capital which stabilizes the economy and prevents agents from being ruined.
Chang, Alfred T. C.; Chiu, Long S.; Wilheit, Thomas T.
1993-01-01
Global averages and random errors associated with the monthly oceanic rain rates derived from the Special Sensor Microwave/Imager (SSM/I) data using the technique developed by Wilheit et al. (1991) are computed. Accounting for the beam-filling bias, a global annual average rain rate of 1.26 m is computed. The error estimation scheme is based on the existence of independent (morning and afternoon) estimates of the monthly mean. Calculations show overall random errors of about 50-60 percent for each 5 deg x 5 deg box. The results are insensitive to different sampling strategy (odd and even days of the month). Comparison of the SSM/I estimates with raingage data collected at the Pacific atoll stations showed a low bias of about 8 percent, a correlation of 0.7, and an rms difference of 55 percent.
Discrete Pathophysiology is Uncommon in Patients with Nonspecific Arm Pain.
Kortlever, Joost T P; Janssen, Stein J; Molleman, Jeroen; Hageman, Michiel G J S; Ring, David
2016-06-01
Nonspecific symptoms are common in all areas of medicine. Patients and caregivers can be frustrated when an illness cannot be reduced to a discrete pathophysiological process that corresponds with the symptoms. We therefore asked the following questions: 1) Which demographic factors and psychological comorbidities are associated with change from an initial diagnosis of nonspecific arm pain to eventual identification of discrete pathophysiology that corresponds with symptoms? 2) What is the percentage of patients eventually diagnosed with discrete pathophysiology, what are those pathologies, and do they account for the symptoms? We evaluated 634 patients with an isolated diagnosis of nonspecific upper extremity pain to see if discrete pathophysiology was diagnosed on subsequent visits to the same hand surgeon, a different hand surgeon, or any physician within our health system for the same pain. There were too few patients with discrete pathophysiology at follow-up to address the primary study question. Definite discrete pathophysiology that corresponded with the symptoms was identified in subsequent evaluations by the index surgeon in one patient (0.16% of all patients) and cured with surgery (nodular fasciitis). Subsequent doctors identified possible discrete pathophysiology in one patient and speculative pathophysiology in four patients and the index surgeon identified possible discrete pathophysiology in four patients, but the five discrete diagnoses accounted for only a fraction of the symptoms. Nonspecific diagnoses are not harmful. Prospective randomized research is merited to determine if nonspecific, descriptive diagnoses are better for patients than specific diagnoses that imply pathophysiology in the absence of discrete verifiable pathophysiology.
Alternative to dead reckoning for model state quantisation when migrating to a quantised discrete
CSIR Research Space (South Africa)
Duvenhage, A
2008-06-01
Full Text Available Some progress has recently been made on migrating an existing distributed parallel discrete time simulator to a quantised discrete event architecture. The migration is done to increase the scale of the real-time simulations supported...
Directory of Open Access Journals (Sweden)
Singh Jagdev
2014-07-01
Full Text Available In this paper, we obtain the distribution of mixed sum of two independent random variables with different probability density functions. One with probability density function defined in finite range and the other with probability density function defined in infinite range and associated with product of Srivastava's polynomials and H-function. We use the Laplace transform and its inverse to obtain our main result. The result obtained here is quite general in nature and is capable of yielding a large number of corresponding new and known results merely by specializing the parameters involved therein. To illustrate, some special cases of our main result are also given.
Energy Technology Data Exchange (ETDEWEB)
Stenta, Herman Roberto; Riccardi, Gerardo A; Basile, Pedro A [Universidad Nacional de Rosario (Mexico)
2008-07-15
Distributed hydrological models are suitable for the determination of time and space variability of hydrological responses within a given watershed. In a watershed, the model can be implemented with different levels of space resolution, mainly as a function of data availability, objectives of the numerical study, and requirements of the system to be modeled. In this paper, the effects on landscape representation due to different cell sizes are analyzed and scaling of parameters in a lower spatial resolution level is proposed in order to obtain similarity in hydrological responses between different degrees of discretization. The comparison was made in terms of maximum discharge, maximum flow velocity, and maximum water depth by simulating a number of observed and hypothetical hydrological events. The concept of total equilibrium state of the watershed was used. Under these circumstances, the roughness coefficients associated to overland and stream flow and the storage function of each discretization element were adjusted separately for the lower spatial resolution level. The results show that the similarity in hydrological responses, in terms of maximum water depth, obtained by adjusting the storage function of the cells, is better than that corresponding to the adjustment of roughness coefficients. [Spanish] Los modelos matematicos de parametros distribuidos resultan particularmente apropiados para determinar la variabilidad espacial y temporal de las respuestas hidrologicas dentro de un determinado sistema hidrico. En una cuenca es posible realizar la constitucion de un modelo con diferentes niveles de detalle en funcion principalmente de la disponibilidad de informacion de entrada necesaria, de los objetivos de estudio y de los requerimientos de modelado del sistema. En el presente trabajo se analizan los efectos producidos en la representacion del relieve debido a los diferentes tamanos de celda en que se ha discretizado una cuenca de llanura y se propone el
Log-concave Probability Distributions: Theory and Statistical Testing
DEFF Research Database (Denmark)
An, Mark Yuing
1996-01-01
This paper studies the broad class of log-concave probability distributions that arise in economics of uncertainty and information. For univariate, continuous, and log-concave random variables we prove useful properties without imposing the differentiability of density functions. Discrete...
Sharp, Karen Tobey
This paper cites information received from a number of sources, e.g., mathematics teachers in two-year colleges, publishers, and convention speakers, about the nature of discrete mathematics and about what topics a course in this subject should contain. Note is taken of the book edited by Ralston and Young which discusses the future of college…
Indian Academy of Sciences (India)
systems, robots, space applications, farming, biotech- nology and even medicine. The disciplines of continuous-time and discrete-time sig- nals and systems have become increasingly entwined. Without any doubt, it is advantageous to process conti- nuous-time signals by sampling them. The computer control system for a ...
Difference Discrete Variational Principles
Baleanu, Dumitru; Jarad, Fahd
2006-05-01
The paper provides the discrete Lagrangian and Hamiltonian formulations of mechanical systems for both non-singular and singular cases. The Lagrangians with linear velocities and with higher velocities are investigated and the corresponding difference Euler-Lagrange equations and Hamiltonians are found.
Discretization of continuous frame
Indian Academy of Sciences (India)
which is a positive, self-adjoint, invertible operator on H with A · IdH ≤ SWω ≤ B · IdH. 2. Main result. For establishing a relationship between discrete and continuous frame of subspaces, we generalize the concept of continuous frame and resolution of identity to arbitrary Hilbert space H. For this purpose, we introduce the ...
Directory of Open Access Journals (Sweden)
Boštjan Kerbler
2006-01-01
Full Text Available The paper systematically describes special regression methods – discrete choice models – known as probability models. The meaning of models and their methodological characteristics are described, as well as different types of models, especially binary-choice models and censored regression models. We considered three most commonly used approaches to estimating such models – logit, probit and tobit model.
de Wild Propitius, M.; Bais, F.A.; Semenoff, G.; Vinet, L.
1999-01-01
In these lectures, we present a self-contained treatment of planar gauge theories broken down to some finite residual gauge group $H$ via the Higgs mechanism. The main focus is on the discrete $H$ gauge theory describing the long distance physics of such a model. The spectrum features global $H$
Modeling the magnitude and distribution of sediment-bound pollutants in estuaries is often limited by incomplete knowledge of the site and inadequate sample density. To address these modeling limitations, a decision-support tool framework was conceived that predicts sediment cont...
Zygadło, Ryszard
2008-02-01
It is shown analytically that the flashing annihilation term of a Verhulst kinetic leads to the power-law distribution in the stationary state. For the frequency of switching slower than twice the free growth rate this provides the quasideterministic source of a Lévy noise at the macroscopic level.
Exit times for a class of random walks: exact distribution results
DEFF Research Database (Denmark)
Jacobsen, Martin
2011-01-01
the exit possible has a Laplace transform which is a rational function. The expected exit time is also determined and the paper concludes with exact distribution results concerning exits from bounded intervals. The proofs use simple martingale techniques together with some classical expansions...
A study into the distribution of gunshot residue particles in the random population.
Lucas, Nick; Brown, Hayley; Cook, Michael; Redman, Kahlee; Condon, Tanith; Wrobel, Harald; Kirkbride, K Paul; Kobus, Hilton
2016-05-01
When considering the impact and value of gunshot residues (GSR) as forensic trace evidence, the likelihood of a suspect producing a positive GSR analysis result without having direct exposure to a firearm is a major consideration. Therefore, the random prevalence of GSR and 'GSR-like' residues in the wider population is a highly pertinent question when considering the probative value of such evidence. The random prevalence of GSR in two Australian jurisdictions - Victoria and South Australia - was assessed through the collection and analysis of GSR samples obtained from randomly selected members of the public. Volunteers were asked to declare any firearms use, hobbies or potential firearms exposure before allowing their hands to be sampled using aluminium GSR sample stubs coated in adhesive tape. A total of 289 samples, 120 from Victoria and 169 from South Australia were collected and analysed using scanning electron microscopy coupled with energy dispersive X-ray microanalysis (SEM-EDS). Across all samples, three 'characteristic' three-component Pb/Ba/Sb particles were detected from a single subject in South Australia, corresponding to an overall prevalence of 0.3%. Two-component 'consistent' particles were more prevalent, with Pb/Sb particles being the most frequently occurring, in 8% of samples, and in South Australia only. A number of samples, approximately 7%, showed populations of single element particles of Pb, Ba and Sb, which has the potential to generate a false positive for GSR if using a bulk analysis technique such as NAA or AAS. The prevalence of GSR or 'GSR like' particles in this study matches closely with similar surveys conducted in other jurisdictions. Such surveys are a useful foundation for the creation of a probabilistic method for the assessment of GSR evidence. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Phase transitions of Ising mixed spin 1 and 3/2 with random crystal field distribution
Sabri, S.; EL Falaki, M.; EL Yadari, M.; Benyoussef, A.; EL Kenz, A.
2016-10-01
The thermal and magnetic properties of the mixed spin-1 and spin-3/2 in the presence of the random crystal field are studied within the mean field approach based on the Bogoliubov inequality for the Gibbs free energy. The model exhibits first, second order transitions, a tricritical point, triple point and an isolated critical end point. It is found that the system displays simple and double compensation temperatures, five topologies of the phase diagrams. A re-entrant phenomenon is also discussed and the thermal dependences of total magnetization according to extended Neel classification have been also given.
Encounter distribution of two random walkers on a finite one-dimensional interval
Energy Technology Data Exchange (ETDEWEB)
Tejedor, Vincent; Schad, Michaela; Metzler, Ralf [Physics Department, Technical University of Munich, James Franck Strasse, 85747 Garching (Germany); Benichou, Olivier; Voituriez, Raphael, E-mail: metz@ph.tum.de [Laboratoire de Physique Theorique de la Matiere Condensee (UMR 7600), Universite Pierre et Marie Curie, 4 Place Jussieu, 75255 Paris Cedex (France)
2011-09-30
We analyse the first-passage properties of two random walkers confined to a finite one-dimensional domain. For the case of absorbing boundaries at the endpoints of the interval, we derive the probability that the two particles meet before either one of them becomes absorbed at one of the boundaries. For the case of reflecting boundaries, we obtain the mean first encounter time of the two particles. Our approach leads to closed-form expressions that are more easily tractable than a previously derived solution in terms of the Weierstrass' elliptic function. (paper)
On the Two-Moment Approximation of the Discrete-Time GI/G/1 Queue with a Single Vacation
Directory of Open Access Journals (Sweden)
Doo Ho Lee
2016-01-01
Full Text Available We consider a discrete-time GI/G/1 queue in which the server takes exactly one vacation each time the system becomes empty. The interarrival times of arriving customers, the service times, and the vacation times are all generic discrete random variables. Under our study, we derive an exact transform-free expression for the stationary system size distribution through the modified supplementary variable technique. Utilizing obtained results, we introduce a simple two-moment approximation for the system size distribution. From this, approximations for the mean system size along with the system size distribution could be obtained. Finally, some numerical examples are given to validate the proposed approximation method.
Discrete dispersion models and their Tweedie asymptotics
DEFF Research Database (Denmark)
Jørgensen, Bent; Kokonendji, Célestin C.
2016-01-01
in this approach, whereas several overdispersed discrete distributions, such as the Neyman Type A, Pólya-Aeppli, negative binomial and Poisson-inverse Gaussian, turn out to be Poisson-Tweedie factorial dispersion models with power dispersion functions, analogous to ordinary Tweedie exponential dispersion models......-Tweedie asymptotic framework where Poisson-Tweedie models appear as dilation limits. This unifies many discrete convergence results and leads to Poisson and Hermite convergence results, similar to the law of large numbers and the central limit theorem, respectively. The dilation operator also leads to a duality...
The remarkable discreteness of being
Indian Academy of Sciences (India)
... and death) is random and these events change the number of individuals of the species by single units. These facts can have surprising, counterintuitive consequences. I review here three examples where these facts play, or could play, important roles: the spatial distribution of species, the structuring of biodiversity and ...
DEFF Research Database (Denmark)
Fitzek, Frank H. P.; Toth, Tamas; Szabados, Aron
2014-01-01
Distributed storage is usually considered within a cloud provider to ensure availability and reliability of the data. However, the user is still directly dependent on the quality of a single system. It is also entrusting the service provider with large amounts of private data, which may be accessed...... by a successful attack to that cloud system or even be inspected by government agencies in some countries. This paper advocates a general framework for network coding enabled distributed storage over multiple commercial cloud solutions, such as, Dropbox, Box, Skydrive, and Google Drive, as a way to address...... these reliability and privacy issues. By means of theoretical analysis and real– life implementations, we show not only that our framework constitutes a viable solution to increase the reliability of stored data and to ensure data privacy, but it also provides a way to reduce the storage costs and to increase...
King, Douglas M; Jacobson, Sheldon H
2017-12-01
Recent mass killings, such as those in Newtown, Connecticut, and Aurora, Colorado, have brought new attention to mass killings in the United States. This article examines 323 mass killings taking place between January 1, 2006, and October 4, 2016, to assess how they are distributed over time. In particular, we find that they appear to be uniformly distributed over time, which suggests that their rate has remained stable over the past decade. Moreover, analysis of subsets of these mass killings sharing a common trait (e.g., family killings, public killings) suggests that they exhibit a memoryless property, suggesting that mass killing events within each category are random in the sense that the occurrence of a mass killing event does not signal whether another mass killing event is imminent. However, the same memoryless property is not found when combining all mass killings into a single analysis, consistent with earlier research that found evidence of a contagion effect among mass killing events. Because of the temporal randomness of public mass killings and the wide geographic area over which they can occur, these results imply that these events may be best addressed by systemic infrastructure-based interventions that deter such events, incorporate resiliency into the response system, or impede such events until law enforcement can respond when they do occur.
Fast and Accurate Learning When Making Discrete Numerical Estimates.
Directory of Open Access Journals (Sweden)
Adam N Sanborn
2016-04-01
Full Text Available Many everyday estimation tasks have an inherently discrete nature, whether the task is counting objects (e.g., a number of paint buckets or estimating discretized continuous variables (e.g., the number of paint buckets needed to paint a room. While Bayesian inference is often used for modeling estimates made along continuous scales, discrete numerical estimates have not received as much attention, despite their common everyday occurrence. Using two tasks, a numerosity task and an area estimation task, we invoke Bayesian decision theory to characterize how people learn discrete numerical distributions and make numerical estimates. Across three experiments with novel stimulus distributions we found that participants fell between two common decision functions for converting their uncertain representation into a response: drawing a sample from their posterior distribution and taking the maximum of their posterior distribution. While this was consistent with the decision function found in previous work using continuous estimation tasks, surprisingly the prior distributions learned by participants in our experiments were much more adaptive: When making continuous estimates, participants have required thousands of trials to learn bimodal priors, but in our tasks participants learned discrete bimodal and even discrete quadrimodal priors within a few hundred trials. This makes discrete numerical estimation tasks good testbeds for investigating how people learn and make estimates.
Salinelli, Ernesto
2014-01-01
This book provides an introduction to the analysis of discrete dynamical systems. The content is presented by an unitary approach that blends the perspective of mathematical modeling together with the ones of several discipline as Mathematical Analysis, Linear Algebra, Numerical Analysis, Systems Theory and Probability. After a preliminary discussion of several models, the main tools for the study of linear and non-linear scalar dynamical systems are presented, paying particular attention to the stability analysis. Linear difference equations are studied in detail and an elementary introduction of Z and Discrete Fourier Transform is presented. A whole chapter is devoted to the study of bifurcations and chaotic dynamics. One-step vector-valued dynamical systems are the subject of three chapters, where the reader can find the applications to positive systems, Markov chains, networks and search engines. The book is addressed mainly to students in Mathematics, Engineering, Physics, Chemistry, Biology and Economic...
2002-01-01
Discrete geometry investigates combinatorial properties of configurations of geometric objects. To a working mathematician or computer scientist, it offers sophisticated results and techniques of great diversity and it is a foundation for fields such as computational geometry or combinatorial optimization. This book is primarily a textbook introduction to various areas of discrete geometry. In each area, it explains several key results and methods, in an accessible and concrete manner. It also contains more advanced material in separate sections and thus it can serve as a collection of surveys in several narrower subfields. The main topics include: basics on convex sets, convex polytopes, and hyperplane arrangements; combinatorial complexity of geometric configurations; intersection patterns and transversals of convex sets; geometric Ramsey-type results; polyhedral combinatorics and high-dimensional convexity; and lastly, embeddings of finite metric spaces into normed spaces. Jiri Matousek is Professor of Com...
Discrete mathematics with applications
Koshy, Thomas
2003-01-01
This approachable text studies discrete objects and the relationsips that bind them. It helps students understand and apply the power of discrete math to digital computer systems and other modern applications. It provides excellent preparation for courses in linear algebra, number theory, and modern/abstract algebra and for computer science courses in data structures, algorithms, programming languages, compilers, databases, and computation.* Covers all recommended topics in a self-contained, comprehensive, and understandable format for students and new professionals * Emphasizes problem-solving techniques, pattern recognition, conjecturing, induction, applications of varying nature, proof techniques, algorithm development and correctness, and numeric computations* Weaves numerous applications into the text* Helps students learn by doing with a wealth of examples and exercises: - 560 examples worked out in detail - More than 3,700 exercises - More than 150 computer assignments - More than 600 writing projects*...
Time Discretization Techniques
Gottlieb, S.
2016-10-12
The time discretization of hyperbolic partial differential equations is typically the evolution of a system of ordinary differential equations obtained by spatial discretization of the original problem. Methods for this time evolution include multistep, multistage, or multiderivative methods, as well as a combination of these approaches. The time step constraint is mainly a result of the absolute stability requirement, as well as additional conditions that mimic physical properties of the solution, such as positivity or total variation stability. These conditions may be required for stability when the solution develops shocks or sharp gradients. This chapter contains a review of some of the methods historically used for the evolution of hyperbolic PDEs, as well as cutting edge methods that are now commonly used.
Indian Academy of Sciences (India)
net immigrants entering the country in year k. We leave it to the reader to model the vacillating mathe- matician problem [3] as a discrete-time system. General Forms of Difference Equations. An nth order difference equation may be written, typically, either as y(k + n) + an-l y(k + n - 1) + + aO y(k) = bm u(k + m) + bm-l u(k + m ...
Czech Academy of Sciences Publication Activity Database
Mesiar, Radko; Li, J.; Pap, E.
2013-01-01
Roč. 54, č. 3 (2013), s. 357-364 ISSN 0888-613X R&D Projects: GA ČR GAP402/11/0378 Institutional support: RVO:67985556 Keywords : concave integral * pseudo-addition * pseudo- multiplication Subject RIV: BA - General Mathematics Impact factor: 1.977, year: 2013 http://library.utia.cas.cz/separaty/2013/E/mesiar-discrete pseudo-integrals. pdf
A paradigm for discrete physics
Energy Technology Data Exchange (ETDEWEB)
Noyes, H.P.; McGoveran, D.; Etter, T.; Manthey, M.J.; Gefwert, C.
1987-01-01
An example is outlined for constructing a discrete physics using as a starting point the insight from quantum physics that events are discrete, indivisible and non-local. Initial postulates are finiteness, discreteness, finite computability, absolute nonuniqueness (i.e., homogeneity in the absence of specific cause) and additivity.
Discrete port-Hamiltonian systems
Talasila, V.; Clemente-Gallardo, J.; Schaft, A.J. van der
2006-01-01
Either from a control theoretic viewpoint or from an analysis viewpoint it is necessary to convert smooth systems to discrete systems, which can then be implemented on computers for numerical simulations. Discrete models can be obtained either by discretizing a smooth model, or by directly modeling
Hamiltonian Mechanics on Discrete Manifolds
Talasila, V.; Clemente Gallardo, J.; Schaft, A.J. van der
2004-01-01
The mathematical/geometric structure of discrete models of systems, whether these models are obtained after discretization of a smooth system or as a direct result of modeling at the discrete level, have not been studied much. Mostly one is concerned regarding the nature of the solutions, but not
Hamiltonian mechanics on discrete manifolds
Talasila, V.; Clemente-Gallardo, J.; Clemente Gallardo, J.J.; van der Schaft, Arjan
2004-01-01
The mathematical/geometric structure of discrete models of systems, whether these models are obtained after discretization of a smooth system or as a direct result of modeling at the discrete level, have not been studied much. Mostly one is concerned regarding the nature of the solutions, but not
Percolation and lasing in real 3D crystals with inhomogeneous distributed random pores
Energy Technology Data Exchange (ETDEWEB)
Burlak, Gennadiy, E-mail: gburlak@uaem.mx; Calderón-Segura, Yessica
2014-11-15
We systematically study the percolation phase transition in real 3D crystals where not only the state of pores but also their radius r and displacement s are random valued numbers. The mean values R=〈r〉 and S=〈s〉 emerge as additional spatial scales in such an extended network. This leads to variations of the threshold (critical) percolation probability p{sub C} and the percolation order parameter P that become to be the intricate functions of R and S. Our numerical simulations have shown that in such extended system the incipient spanning cluster can arise even for situations where for simple periodical system the percolation does not exist. We analyzed the validity of the nearest neighbor's approximation and found that such approximation is not valid for materials with large dispersivity of pores. The lasing of nanoemitters incorporated in such percolating spanning cluster is studied too. This effect can open interesting perspectives in modern nano- and micro-information technologies.
Exact distributions of cover times for N independent random walkers in one dimension
Majumdar, Satya N.; Sabhapandit, Sanjib; Schehr, Grégory
2016-12-01
We study the probability density function (PDF) of the cover time tc of a finite interval of size L by N independent one-dimensional Brownian motions, each with diffusion constant D . The cover time tc is the minimum time needed such that each point of the entire interval is visited by at least one of the N walkers. We derive exact results for the full PDF of tc for arbitrary N ≥1 for both reflecting and periodic boundary conditions. The PDFs depend explicitly on N and on the boundary conditions. In the limit of large N , we show that tc approaches its average value of ≈L2/(16 D lnN ) with fluctuations vanishing as 1 /(lnN) 2 . We also compute the centered and scaled limiting distributions for large N for both boundary conditions and show that they are given by nontrivial N independent scaling functions.
Guo, Zhenyuan; Yang, Shaofu; Wang, Jun
2016-12-01
This paper presents theoretical results on global exponential synchronization of multiple memristive neural networks in the presence of external noise by means of two types of distributed pinning control. The multiple memristive neural networks are coupled in a general structure via a nonlinear function, which consists of a linear diffusive term and a discontinuous sign term. A pinning impulsive control law is introduced in the coupled system to synchronize all neural networks. Sufficient conditions are derived for ascertaining global exponential synchronization in mean square. In addition, a pinning adaptive control law is developed to achieve global exponential synchronization in mean square. Both pinning control laws utilize only partial state information received from the neighborhood of the controlled neural network. Simulation results are presented to substantiate the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Hiroshi Miki
2012-02-01
Full Text Available Discrete spectral transformations of skew orthogonal polynomials are presented. From these spectral transformations, it is shown that the corresponding discrete integrable systems are derived both in 1+1 dimension and in 2+1 dimension. Especially in the (2+1-dimensional case, the corresponding system can be extended to 2×2 matrix form. The factorization theorem of the Christoffel kernel for skew orthogonal polynomials in random matrix theory is presented as a by-product of these transformations.
Kinasewitz, Gary T; Privalle, Christopher T; Imm, Amy; Steingrub, Jay S; Malcynski, John T; Balk, Robert A; DeAngelo, Joseph
2008-07-01
To assess the safety and efficacy of the hemoglobin-based nitric oxide scavenger, pyridoxalated hemoglobin polyoxyethylene (PHP), in patients with distributive shock. Phase II multicenter, randomized (1:1), placebo-controlled study. Fifteen intensive care units in North America. Sixty-two patients with distributive shock, > or = 2 systemic inflammatory response syndrome criteria, and persistent catecholamine dependence despite adequate fluid resuscitation (pulmonary capillary wedge pressure > or = 12). Patients were randomized to PHP at 0.25 mL/kg/hr (20 mg/kg/hr), or an equal volume of placebo, infused for up to 100 hrs, in addition to conventional vasopressor therapy. Because treatment could not be blinded, vasopressors and ventilatory support were weaned by protocol. Sixty-two patients were randomized to PHP (n = 33) or placebo (n = 29). Age, sex, etiology of shock (sepsis in 94%), and Acute Physiology and Chronic Health Evaluation II scores (33.1 +/- 8.3 vs. 30 +/- 7) were similar in PHP and placebo patients, respectively. Baseline plasma nitrite and nitrate levels were markedly elevated in both groups. PHP infusion increased systemic blood pressure within minutes. Overall 28-day mortality was similar (58% PHP vs. 59% placebo), but PHP survivors were weaned off vasopressors faster (13.7 +/- 8.2 vs. 26.3 +/- 21.4 hrs; p = .07) and spent less time on mechanical ventilation (10.4 +/- 10.2 vs. 17.4 +/- 9.9 days; p = .21). The risk ratio (PHP/placebo) for mortality was .79 (95% confidence interval, .39-1.59) when adjusted for age, sex, Acute Physiology and Chronic Health Evaluation II score, and etiology of sepsis. No excess medical interventions were noted with PHP use. PHP survivors left the intensive care unit earlier (13.6 +/- 8.6 vs. 17.9 +/- 8.2 days; p = .21) and more were discharged by day 28 (57.1 vs. 41.7%). PHP is a hemodynamically active nitric oxide scavenger. The role of PHP in distributive shock remains to be determined.
Randomized Soil Survey of the Distribution of Burkholderia pseudomallei in Rice Fields in Laos ▿ †
Rattanavong, Sayaphet; Wuthiekanun, Vanaporn; Langla, Sayan; Amornchai, Premjit; Sirisouk, Joy; Phetsouvanh, Rattanaphone; Moore, Catrin E.; Peacock, Sharon J.; Buisson, Yves; Newton, Paul N.
2011-01-01
Melioidosis is a major cause of morbidity and mortality in Southeast Asia, where the causative organism (Burkholderia pseudomallei) is present in the soil. In the Lao People's Democratic Republic (Laos), B. pseudomallei is a significant cause of sepsis around the capital, Vientiane, and has been isolated in soil near the city, adjacent to the Mekong River. We explored whether B. pseudomallei occurs in Lao soil distant from the Mekong River, drawing three axes across northwest, northeast, and southern Laos to create nine sampling areas in six provinces. Within each sampling area, a random rice field site containing a grid of 100 sampling points each 5 m apart was selected. Soil was obtained from a depth of 30 cm and cultured for B. pseudomallei. Four of nine sites (44%) were positive for B. pseudomallei, including all three sites in Saravane Province, southern Laos. The highest isolation frequency was in east Saravane, where 94% of soil samples were B. pseudomallei positive with a geometric mean concentration of 464 CFU/g soil (95% confidence interval, 372 to 579 CFU/g soil; range, 25 to 10,850 CFU/g soil). At one site in northwest Laos (Luangnamtha), only one sample (1%) was positive for B. pseudomallei, at a concentration of 80 CFU/g soil. Therefore, B. pseudomallei occurs in Lao soils beyond the immediate vicinity of the Mekong River, alerting physicians to the likelihood of melioidosis in these areas. Further studies are needed to investigate potential climatic, soil, and biological determinants of this heterogeneity. PMID:21075883
Monotonicity, thinning and discrete versions of the Entropy Power Inequality
Johnson, Oliver
2009-01-01
We consider the entropy of sums of independent discrete random variables, in analogy with Shannon's Entropy Power Inequality, where equality holds for normals. In our case, infinite divisibility suggests that equality should hold for Poisson variables. We show that some natural analogues of the Entropy Power Inequality do not in fact hold, but propose an alternative formulation which does always hold. The key to many proofs of Shannon's Entropy Power Inequality is the behaviour of entropy on scaling of continuous random variables. We believe that R\\'{e}nyi's operation of thinning discrete random variables plays a similar role to scaling, and give a sharp bound on how the entropy of ultra log-concave random variables behaves on thinning. In the spirit of the monotonicity results established by Artstein, Ball, Barthe and Naor, we prove a stronger version of concavity of entropy, which implies a strengthened form of our discrete Entropy Power Inequality.
Carpena, Pedro; Bernaola-Galván, Pedro A; Carretero-Campos, Concepción; Coronado, Ana V
2016-11-01
Symbolic sequences have been extensively investigated in the past few years within the framework of statistical physics. Paradigmatic examples of such sequences are written texts, and deoxyribonucleic acid (DNA) and protein sequences. In these examples, the spatial distribution of a given symbol (a word, a DNA motif, an amino acid) is a key property usually related to the symbol importance in the sequence: The more uneven and far from random the symbol distribution, the higher the relevance of the symbol to the sequence. Thus, many techniques of analysis measure in some way the deviation of the symbol spatial distribution with respect to the random expectation. The problem is then to know the spatial distribution corresponding to randomness, which is typically considered to be either the geometric or the exponential distribution. However, these distributions are only valid for very large symbolic sequences and for many occurrences of the analyzed symbol. Here, we obtain analytically the exact, randomly expected spatial distribution valid for any sequence length and any symbol frequency, and we study its main properties. The knowledge of the distribution allows us to define a measure able to properly quantify the deviation from randomness of the symbol distribution, especially for short sequences and low symbol frequency. We apply the measure to the problem of keyword detection in written texts and to study amino acid clustering in protein sequences. In texts, we show how the results improve with respect to previous methods when short texts are analyzed. In proteins, which are typically short, we show how the measure quantifies unambiguously the amino acid clustering and characterize its spatial distribution.
Directory of Open Access Journals (Sweden)
Yueyang Li
2014-01-01
Full Text Available This paper investigates the H∞ fixed-lag fault estimator design for linear discrete time-varying (LDTV systems with intermittent measurements, which is described by a Bernoulli distributed random variable. Through constructing a novel partially equivalent dynamic system, the fault estimator design is converted into a deterministic quadratic minimization problem. By applying the innovation reorganization technique and the projection formula in Krein space, a necessary and sufficient condition is obtained for the existence of the estimator. The parameter matrices of the estimator are derived by recursively solving two standard Riccati equations. An illustrative example is provided to show the effectiveness and applicability of the proposed algorithm.
Non-random distribution of individual genetic diversity along an environmental gradient.
Porlier, Mélody; Bélisle, Marc; Garant, Dany
2009-06-12
Improving our knowledge of the links between ecology and evolution is especially critical in the actual context of global rapid environmental changes. A critical step in that direction is to quantify how variation in ecological factors linked to habitat modifications might shape observed levels of genetic variability in wild populations. Still, little is known on the factors affecting levels and distribution of genetic diversity at the individual level, despite its vital underlying role in evolutionary processes. In this study, we assessed the effects of habitat quality on population structure and individual genetic diversity of tree swallows (Tachycineta bicolor) breeding along a gradient of agricultural intensification in southern Québec, Canada. Using a landscape genetics approach, we found that individual genetic diversity was greater in poorer quality habitats. This counter-intuitive result was partly explained by the settlement patterns of tree swallows across the landscape. Individuals of higher genetic diversity arrived earlier on their breeding grounds and settled in the first available habitats, which correspond to intensive cultures. Our results highlight the importance of investigating the effects of environmental variability on individual genetic diversity, and of integrating information on landscape structure when conducting such studies.
Directory of Open Access Journals (Sweden)
Marcus A Bachhuber
Full Text Available Barriers to public support for naloxone distribution include lack of knowledge, concerns about potential unintended consequences, and lack of sympathy for people at risk of overdose.A randomized survey experiment was conducted with a nationally-representative web-based survey research panel (GfK KnowledgePanel. Participants were randomly assigned to read different messages alone or in combination: 1 factual information about naloxone; 2 pre-emptive refutation of potential concerns about naloxone distribution; and 3 a sympathetic narrative about a mother whose daughter died of an opioid overdose. Participants were then asked if they support or oppose policies related to naloxone distribution. For each policy item, logistic regression models were used to test the effect of each message exposure compared with the no-exposure control group.The final sample consisted of 1,598 participants (completion rate: 72.6%. Factual information and the sympathetic narrative alone each led to higher support for training first responders to use naloxone, providing naloxone to friends and family members of people using opioids, and passing laws to protect people who administer naloxone. Participants receiving the combination of the sympathetic narrative and factual information, compared to factual information alone, were more likely to support all policies: providing naloxone to friends and family members (OR: 2.0 [95% CI: 1.4 to 2.9], training first responders to use naloxone (OR: 2.0 [95% CI: 1.2 to 3.4], passing laws to protect people if they administer naloxone (OR: 1.5 [95% CI: 1.04 to 2.2], and passing laws to protect people if they call for medical help for an overdose (OR: 1.7 [95% CI: 1.2 to 2.5].All messages increased public support, but combining factual information and the sympathetic narrative was most effective. Public support for naloxone distribution can be improved through education and sympathetic portrayals of the population who stands to benefit
Bertemes-Filho, P.; Felipe, A.
2013-04-01
When a Howland source is designed, the components are chosen so that the designed source has the desired characteristics. However, the operational amplifier limitations and resistor tolerances causes undesired behaviours. This work proposes to take in account the influence of the random distribution of the commercial resistors in the Howland circuit over the frequency range of 10 Hz to 10 MHz. The probability density function due to small changes over the resistors was calculated by using an analytical model. Results show that both output current and impedance are very sensitive to the resistor tolerances. It is shown that the output impedance is very dependent on the open-loop gain of the Opamp rather than the resistor tolerances, especially at higher frequencies. This might improve the implementations of real current source used in electrical bioimpedance.
Marey, Isabelle; Ben Yaou, Rabah; Deburgrave, Nathalie; Vasson, Aurélie; Nectoux, Juliette; Leturcq, France; Eymard, Bruno; Laforet, Pascal; Behin, Anthony; Stojkovic, Tanya; Mayer, Michèle; Tiffreau, Vincent; Desguerre, Isabelle; Boyer, François Constant; Nadaj-Pakleza, Aleksandra; Ferrer, Xavier; Wahbi, Karim; Becane, Henri-Marc; Claustres, Mireille; Chelly, Jamel; Cossee, Mireille
2016-05-27
Dystrophinopathies are mostly caused by copy number variations, especially deletions, in the dystrophin gene (DMD). Despite the large size of the gene, deletions do not occur randomly but mainly in two hot spots, the main one involving exons 45 to 55. The underlying mechanisms are complex and implicate two main mechanisms: Non-homologous end joining (NHEJ) and micro-homology mediated replication-dependent recombination (MMRDR). Our goals were to assess the distribution of intronic breakpoints (BPs) in the genomic sequence of the main hot spot of deletions within DMD gene and to search for specific sequences at or near to BPs that might promote BP occurrence or be associated with DNA break repair. Using comparative genomic hybridization microarray, 57 deletions within the intron 44 to 55 region were mapped. Moreover, 21 junction fragments were sequenced to search for specific sequences. Non-randomly distributed BPs were found in introns 44, 47, 48, 49 and 53 and 50% of BPs clustered within genomic regions of less than 700bp. Repeated elements (REs), known to promote gene rearrangement via several mechanisms, were present in the vicinity of 90% of clustered BPs and less frequently (72%) close to scattered BPs, illustrating the important role of such elements in the occurrence of DMD deletions. Palindromic and TTTAAA sequences, which also promote DNA instability, were identified at fragment junctions in 20% and 5% of cases, respectively. Micro-homologies (76%) and insertions or deletions of small sequences were frequently found at BP junctions. Our results illustrate, in a large series of patients, the important role of RE and other genomic features in DNA breaks, and the involvement of different mechanisms in DMD gene deletions: Mainly replication error repair mechanisms, but also NHEJ and potentially aberrant firing of replication origins. A combination of these mechanisms may also be possible.
More about discrete gauge anomalies
Ibáñez, L E
1993-01-01
I discuss and extend several results concerning the cancellation of discrete gauge anomalies. I show how heavy fermions do not decouple in the presence of discrete gauge anomalies. As a consequence, in general, cancellation of discrete gauge anomalies cannot be described merely in terms of low energy operators involving only the light fermions. I also discuss cancellation of discrete gauge anomalies through a discrete version of the Green-Schwarz (GS) mechanism as well as the possibility of discrete gauge R-symmetries and their anomalies. Finally, some phenomenological applications are discussed. This includes symmetries guaranteeing absence of FCNC in two-Higgs models and generalized matter parities stabilizing the proton in the supersymmetric standard model. In the presence of a discrete GS mechanism or/and gauge R-symmetries, new possibilities for anomaly free such symmetries are found.
Brauer, Fred; Feng, Zhilan; Castillo-Chavez, Carlos
2010-01-01
The mathematical theory of single outbreak epidemic models really began with the work of Kermack and Mackendrick about decades ago. This gave a simple answer to the long-standing question of why epidemics woould appear suddenly and then disappear just as suddenly without having infected an entire population. Therefore it seemed natural to expect that theoreticians would immediately proceed to expand this mathematical framework both because the need to handle recurrent single infectious disease outbreaks has always been a priority for public health officials and because theoreticians often try to push the limits of exiting theories. However, the expansion of the theory via the inclusion of refined epidemiological classifications or through the incorporation of categories that are essential for the evaluation of intervention strategies, in the context of ongoing epidemic outbreaks, did not materialize. It was the global threat posed by SARS in that caused theoreticians to expand the Kermack-McKendrick single-outbreak framework. Most recently, efforts to connect theoretical work to data have exploded as attempts to deal with the threat of emergent and re-emergent diseases including the most recent H1N1 influenza pandemic, have marched to the forefront of our global priorities. Since data are collected and/or reported over discrete units of time, developing single outbreak models that fit collected data naturally is relevant. In this note, we introduce a discrete-epidemic framework and highlight, through our analyses, the similarities between single-outbreak comparable classical continuous-time epidemic models and the discrete-time models introduced in this note. The emphasis is on comparisons driven by expressions for the final epidemic size.
Cortical Neural Computation by Discrete Results Hypothesis.
Castejon, Carlos; Nuñez, Angel
2016-01-01
One of the most challenging problems we face in neuroscience is to understand how the cortex performs computations. There is increasing evidence that the power of the cortical processing is produced by populations of neurons forming dynamic neuronal ensembles. Theoretical proposals and multineuronal experimental studies have revealed that ensembles of neurons can form emergent functional units. However, how these ensembles are implicated in cortical computations is still a mystery. Although cell ensembles have been associated with brain rhythms, the functional interaction remains largely unclear. It is still unknown how spatially distributed neuronal activity can be temporally integrated to contribute to cortical computations. A theoretical explanation integrating spatial and temporal aspects of cortical processing is still lacking. In this Hypothesis and Theory article, we propose a new functional theoretical framework to explain the computational roles of these ensembles in cortical processing. We suggest that complex neural computations underlying cortical processing could be temporally discrete and that sensory information would need to be quantized to be computed by the cerebral cortex. Accordingly, we propose that cortical processing is produced by the computation of discrete spatio-temporal functional units that we have called "Discrete Results" (Discrete Results Hypothesis). This hypothesis represents a novel functional mechanism by which information processing is computed in the cortex. Furthermore, we propose that precise dynamic sequences of "Discrete Results" is the mechanism used by the cortex to extract, code, memorize and transmit neural information. The novel "Discrete Results" concept has the ability to match the spatial and temporal aspects of cortical processing. We discuss the possible neural underpinnings of these functional computational units and describe the empirical evidence supporting our hypothesis. We propose that fast-spiking (FS
Discrete shaped strain sensors for intelligent structures
Andersson, Mark S.; Crawley, Edward F.
Design of discrete, highly distributed sensor systems for intelligent structures has been studied. Data obtained indicate that discrete strain-averaging sensors satisfy the functional requirements for distributed sensing of intelligent structures. Bartlett and Gauss-Hanning sensors, in particular, provide good wavenumber characteristics while meeting the functional requirements. They are characterized by good rolloff rates and positive Fourier transforms for all wavenumbers. For the numerical integration schemes, Simpson's rule is considered to be very simple to implement and consistently provides accurate results for five sensors or more. It is shown that a sensor system that satisfies the functional requirements can be applied to a structure that supports mode shapes with purely sinusoidal curvature.
Discrete Exterior Calculus Discretization of Incompressible Navier-Stokes Equations
Mohamed, Mamdouh S.
2017-05-23
A conservative discretization of incompressible Navier-Stokes equations over surface simplicial meshes is developed using discrete exterior calculus (DEC). Numerical experiments for flows over surfaces reveal a second order accuracy for the developed scheme when using structured-triangular meshes, and first order accuracy otherwise. The mimetic character of many of the DEC operators provides exact conservation of both mass and vorticity, in addition to superior kinetic energy conservation. The employment of barycentric Hodge star allows the discretization to admit arbitrary simplicial meshes. The discretization scheme is presented along with various numerical test cases demonstrating its main characteristics.
Poisson hierarchy of discrete strings
Energy Technology Data Exchange (ETDEWEB)
Ioannidou, Theodora, E-mail: ti3@auth.gr [Faculty of Civil Engineering, School of Engineering, Aristotle University of Thessaloniki, 54249, Thessaloniki (Greece); Niemi, Antti J., E-mail: Antti.Niemi@physics.uu.se [Department of Physics and Astronomy, Uppsala University, P.O. Box 803, S-75108, Uppsala (Sweden); Laboratoire de Mathematiques et Physique Theorique CNRS UMR 6083, Fédération Denis Poisson, Université de Tours, Parc de Grandmont, F37200, Tours (France); Department of Physics, Beijing Institute of Technology, Haidian District, Beijing 100081 (China)
2016-01-28
The Poisson geometry of a discrete string in three dimensional Euclidean space is investigated. For this the Frenet frames are converted into a spinorial representation, the discrete spinor Frenet equation is interpreted in terms of a transfer matrix formalism, and Poisson brackets are introduced in terms of the spinor components. The construction is then generalised, in a self-similar manner, into an infinite hierarchy of Poisson algebras. As an example, the classical Virasoro (Witt) algebra that determines reparametrisation diffeomorphism along a continuous string, is identified as a particular sub-algebra, in the hierarchy of the discrete string Poisson algebra. - Highlights: • Witt (classical Virasoro) algebra is derived in the case of discrete string. • Infinite dimensional hierarchy of Poisson bracket algebras is constructed for discrete strings. • Spinor representation of discrete Frenet equations is developed.
Advances in discrete differential geometry
2016-01-01
This is one of the first books on a newly emerging field of discrete differential geometry and an excellent way to access this exciting area. It surveys the fascinating connections between discrete models in differential geometry and complex analysis, integrable systems and applications in computer graphics. The authors take a closer look at discrete models in differential geometry and dynamical systems. Their curves are polygonal, surfaces are made from triangles and quadrilaterals, and time is discrete. Nevertheless, the difference between the corresponding smooth curves, surfaces and classical dynamical systems with continuous time can hardly be seen. This is the paradigm of structure-preserving discretizations. Current advances in this field are stimulated to a large extent by its relevance for computer graphics and mathematical physics. This book is written by specialists working together on a common research project. It is about differential geometry and dynamical systems, smooth and discrete theories, ...
Xiaoxi Jin; Xueyuan Du; Xiong Wang; Pu Zhou; Hanwei Zhang; Xiaolin Wang; Zejin Liu
2016-01-01
We demonstrated a high-power ultralong-wavelength Tm-doped silica fiber laser operating at 2153?nm with the output power exceeding 18?W and the slope efficiency of 25.5%. A random distributed feedback fiber laser with the center wavelength of 1173?nm was employed as pump source of Tm-doped fiber laser for the first time. No amplified spontaneous emissions or parasitic oscillations were observed when the maximum output power reached, which indicates that employing 1173?nm random distributed fe...
Directory of Open Access Journals (Sweden)
Regad Leslie
2010-01-01
Full Text Available Abstract Background In bioinformatics it is common to search for a pattern of interest in a potentially large set of rather short sequences (upstream gene regions, proteins, exons, etc.. Although many methodological approaches allow practitioners to compute the distribution of a pattern count in a random sequence generated by a Markov source, no specific developments have taken into account the counting of occurrences in a set of independent sequences. We aim to address this problem by deriving efficient approaches and algorithms to perform these computations both for low and high complexity patterns in the framework of homogeneous or heterogeneous Markov models. Results The latest advances in the field allowed us to use a technique of optimal Markov chain embedding based on deterministic finite automata to introduce three innovative algorithms. Algorithm 1 is the only one able to deal with heterogeneous models. It also permits to avoid any product of convolution of the pattern distribution in individual sequences. When working with homogeneous models, Algorithm 2 yields a dramatic reduction in the complexity by taking advantage of previous computations to obtain moment generating functions efficiently. In the particular case of low or moderate complexity patterns, Algorithm 3 exploits power computation and binary decomposition to further reduce the time complexity to a logarithmic scale. All these algorithms and their relative interest in comparison with existing ones were then tested and discussed on a toy-example and three biological data sets: structural patterns in protein loop structures, PROSITE signatures in a bacterial proteome, and transcription factors in upstream gene regions. On these data sets, we also compared our exact approaches to the tempting approximation that consists in concatenating the sequences in the data set into a single sequence. Conclusions Our algorithms prove to be effective and able to handle real data sets with
2010-01-01
Background In bioinformatics it is common to search for a pattern of interest in a potentially large set of rather short sequences (upstream gene regions, proteins, exons, etc.). Although many methodological approaches allow practitioners to compute the distribution of a pattern count in a random sequence generated by a Markov source, no specific developments have taken into account the counting of occurrences in a set of independent sequences. We aim to address this problem by deriving efficient approaches and algorithms to perform these computations both for low and high complexity patterns in the framework of homogeneous or heterogeneous Markov models. Results The latest advances in the field allowed us to use a technique of optimal Markov chain embedding based on deterministic finite automata to introduce three innovative algorithms. Algorithm 1 is the only one able to deal with heterogeneous models. It also permits to avoid any product of convolution of the pattern distribution in individual sequences. When working with homogeneous models, Algorithm 2 yields a dramatic reduction in the complexity by taking advantage of previous computations to obtain moment generating functions efficiently. In the particular case of low or moderate complexity patterns, Algorithm 3 exploits power computation and binary decomposition to further reduce the time complexity to a logarithmic scale. All these algorithms and their relative interest in comparison with existing ones were then tested and discussed on a toy-example and three biological data sets: structural patterns in protein loop structures, PROSITE signatures in a bacterial proteome, and transcription factors in upstream gene regions. On these data sets, we also compared our exact approaches to the tempting approximation that consists in concatenating the sequences in the data set into a single sequence. Conclusions Our algorithms prove to be effective and able to handle real data sets with multiple sequences, as well
McKenzie, Alan
2016-01-01
The Many Worlds Interpretation (MWI) famously avoids the issue of wave function collapse. Different MWI trees representing the same quantum events can have different topologies, depending upon the observer. However, they are all isomorphic to the group of block universes containing all of the outcomes of all of the events, and so, in that sense, the group of block universes is a more fundamental representation. Different branches of the MWI tree, representing different universes in MWI, ultimately share the same quantum state in a common ancestor branch. This branching topology is incompatible with that of the Minkowski block universe; the resolution is to replace the branches with discrete, parallel block universes, each of which extends from the trunk to the outermost twigs. The number of universes in a branch is proportional to its thickness which, in turn, depends upon the absolute square of the probability amplitude for the state in that branch. Every quantum event may be represented by a kernel of unive...
Energy Technology Data Exchange (ETDEWEB)
Noyes, H.P. (Stanford Linear Accelerator Center, Menlo Park, CA (USA)); Starson, S. (STARSON Corp. (USA))
1991-03-01
Discrete physics, because it replaces time evolution generated by the energy operator with a global bit-string generator (program universe) and replaces fields'' with the relativistic Wheeler-Feynman action at a distance,'' allows the consistent formulation of the concept of signed gravitational charge for massive particles. The resulting prediction made by this version of the theory is that free anti-particles near the surface of the earth will fall'' up with the same acceleration that the corresponding particles fall down. So far as we can see, no current experimental information is in conflict with this prediction of our theory. The experiment crusis will be one of the anti-proton or anti-hydrogen experiments at CERN. Our prediction should be much easier to test than the small effects which those experiments are currently designed to detect or bound. 23 refs.
Immigration and Prosecutorial Discretion.
Apollonio, Dorie; Lochner, Todd; Heddens, Myriah
Immigration has become an increasingly salient national issue in the US, and the Department of Justice recently increased federal efforts to prosecute immigration offenses. This shift, however, relies on the cooperation of US attorneys and their assistants. Traditionally federal prosecutors have enjoyed enormous discretion and have been responsive to local concerns. To consider how the centralized goal of immigration enforcement may have influenced federal prosecutors in regional offices, we review their prosecution of immigration offenses in California using over a decade's worth of data. Our findings suggest that although centralizing forces influence immigration prosecutions, individual US attorneys' offices retain distinct characteristics. Local factors influence federal prosecutors' behavior in different ways depending on the office. Contrary to expectations, unemployment rates did not affect prosecutors' willingness to pursue immigration offenses, nor did local popular opinion about illegal immigration.
Principles of discrete time mechanics
Jaroszkiewicz, George
2014-01-01
Could time be discrete on some unimaginably small scale? Exploring the idea in depth, this unique introduction to discrete time mechanics systematically builds the theory up from scratch, beginning with the historical, physical and mathematical background to the chronon hypothesis. Covering classical and quantum discrete time mechanics, this book presents all the tools needed to formulate and develop applications of discrete time mechanics in a number of areas, including spreadsheet mechanics, classical and quantum register mechanics, and classical and quantum mechanics and field theories. A consistent emphasis on contextuality and the observer-system relationship is maintained throughout.
Scaling solutions for connectivity and conductivity of continuous random networks.
Galindo-Torres, S A; Molebatsi, T; Kong, X-Z; Scheuermann, A; Bringemeier, D; Li, L
2015-10-01
Connectivity and conductivity of two-dimensional fracture networks (FNs), as an important type of continuous random networks, are examined systematically through Monte Carlo simulations under a variety of conditions, including different power law distributions of the fracture lengths and domain sizes. The simulation results are analyzed using analogies of the percolation theory for discrete random networks. With a characteristic length scale and conductivity scale introduced, we show that the connectivity and conductivity of FNs can be well described by universal scaling solutions. These solutions shed light on previous observations of scale-dependent FN behavior and provide a powerful method for quantifying effective bulk properties of continuous random networks.
Computing compound distributions faster
Iseger, P.; Smith, M.A.J.; Dekker, Rommert
1997-01-01
textabstractThe use of Panjer's algorithm has meanwhile become a widespread standard technique for actuaries (Kuon et al., 1955). Panjer's recursion formula is used for the evaluation of compound distributions and can be applied to life and general insurance problems. The discrete version of Panjer's recursion formula is often applied to continuous distributions by discretizing the
Directory of Open Access Journals (Sweden)
Fermín Segovia
2017-10-01
Full Text Available 18F-DMFP-PET is an emerging neuroimaging modality used to diagnose Parkinson's disease (PD that allows us to examine postsynaptic dopamine D2/3 receptors. Like other neuroimaging modalities used for PD diagnosis, most of the total intensity of 18F-DMFP-PET images is concentrated in the striatum. However, other regions can also be useful for diagnostic purposes. An appropriate delimitation of the regions of interest contained in 18F-DMFP-PET data is crucial to improve the automatic diagnosis of PD. In this manuscript we propose a novel methodology to preprocess 18F-DMFP-PET data that improves the accuracy of computer aided diagnosis systems for PD. First, the data were segmented using an algorithm based on Hidden Markov Random Field. As a result, each neuroimage was divided into 4 maps according to the intensity and the neighborhood of the voxels. The maps were then individually normalized so that the shape of their histograms could be modeled by a Gaussian distribution with equal parameters for all the neuroimages. This approach was evaluated using a dataset with neuroimaging data from 87 parkinsonian patients. After these preprocessing steps, a Support Vector Machine classifier was used to separate idiopathic and non-idiopathic PD. Data preprocessed by the proposed method provided higher accuracy results than the ones preprocessed with previous approaches.
Probability distribution of the time-averaged mean-square displacement of a Gaussian process.
Grebenkov, Denis S
2011-09-01
We study the probability distribution of the time-averaged mean-square displacement of a discrete Gaussian process. An empirical approximation for the probability density is suggested and numerically validated for fractional Brownian motion. The optimality of quadratic forms for inferring dynamical and microrheological quantities from individual random trajectories is discussed, with emphasis on a reliable interpretation of single-particle tracking experiments.
Inferring gene networks from discrete expression data
Zhang, L.
2013-07-18
The modeling of gene networks from transcriptional expression data is an important tool in biomedical research to reveal signaling pathways and to identify treatment targets. Current gene network modeling is primarily based on the use of Gaussian graphical models applied to continuous data, which give a closedformmarginal likelihood. In this paper,we extend network modeling to discrete data, specifically data from serial analysis of gene expression, and RNA-sequencing experiments, both of which generate counts of mRNAtranscripts in cell samples.We propose a generalized linear model to fit the discrete gene expression data and assume that the log ratios of the mean expression levels follow a Gaussian distribution.We restrict the gene network structures to decomposable graphs and derive the graphs by selecting the covariance matrix of the Gaussian distribution with the hyper-inverse Wishart priors. Furthermore, we incorporate prior network models based on gene ontology information, which avails existing biological information on the genes of interest. We conduct simulation studies to examine the performance of our discrete graphical model and apply the method to two real datasets for gene network inference. © The Author 2013. Published by Oxford University Press. All rights reserved.
Geometric Structure-Preserving Discretization Schemes for Nonlinear Elasticity
2015-08-13
AFRL-AFOSR-VA-TR-2015-0232 Geometric Structure-Preserving Discretization Schemes for Nonlinear Elasticity Arash Yavari GEORGIA TECH RESEARCH...01-06-2012 to 31-05-2015 4. TITLE AND SUBTITLE Geometric Structure-Preserving Discretization Schemes for Nonlinear Elasticity 5a. CONTRACT...STATEMENT A DISTRIBUTION UNLIMITED: PB Public Release 13. SUPPLEMENTARY NOTES 14. ABSTRACT We introduced a smooth complex for nonlinear elasticity
White, S H
1994-04-01
This paper continues an examination of the hypothesis that modern proteins evolved from random heteropeptide sequences. In support of the hypothesis, White and Jacobs (1993, J Mol Evol 36:79-95) have shown that any sequence chosen randomly from a large collection of nonhomologous proteins has a 90% or better chance of having a lengthwise distribution of amino acids that is indistinguishable from the random expectation regardless of amino acid type. The goal of the present study was to investigate the possibility that the random-origin hypothesis could explain the lengths of modern protein sequences without invoking specific mechanisms such as gene duplication or exon splicing. The sets of sequences examined were taken from the 1989 PIR database and consisted of 1,792 "super-family" proteins selected to have little sequence identity, 623 E. coli sequences, and 398 human sequences. The length distributions of the proteins could be described with high significance by either of two closely related probability density functions: The gamma distribution with parameter 2 or the distribution for the sum of two exponential random independent variables. A simple theory for the distributions was developed which assumes that (1) protoprotein sequences had exponentially distributed random independent lengths, (2) the length dependence of protein stability determined which of these protoproteins could fold into compact primitive proteins and thereby attain the potential for biochemical activity, (3) the useful protein sequences were preserved by the primitive genome, and (4) the resulting distribution of sequence lengths is reflected by modern proteins. The theory successfully predicts the two observed distributions which can be distinguished by the functional form of the dependence of protein stability on length. The theory leads to three interesting conclusions. First, it predicts that a tetra-nucleotide was the signal for primitive translation termination. This prediction is
Discrete Mathematics and Its Applications
Oxley, Alan
2010-01-01
The article gives ideas that lecturers of undergraduate Discrete Mathematics courses can use in order to make the subject more interesting for students and encourage them to undertake further studies in the subject. It is possible to teach Discrete Mathematics with little or no reference to computing. However, students are more likely to be…
Discrete Mathematics and Curriculum Reform.
Kenney, Margaret J.
1996-01-01
Defines discrete mathematics as the mathematics necessary to effect reasoned decision making in finite situations and explains how its use supports the current view of mathematics education. Discrete mathematics can be used by curriculum developers to improve the curriculum for students of all ages and abilities. (SLD)
Multiscale expansions in discrete world
Indian Academy of Sciences (India)
... multiscale expansions discretely. The power of this manageable method is confirmed by applying it to two selected nonlinear Schrödinger evolution equations. This approach can also be applied to other nonlinear discrete evolution equations. All the computations have been made with Maple computer packet program.
Multiscale expansions in discrete world
Indian Academy of Sciences (India)
and third-order nonlinear Schrödinger equations, KdV equation is derived in §3 and 4, respectively. Finally, some conclusions are ... type to KdV-type equations in discrete world. For a given discrete nonlinear ..... Filiz Tascan and Mehmet Naci Özer. [2] M Toda, Theory of nonlinear lattices (Springer-Verlag, New York, 1981).
Boezen, H M; Schouten, J. P.; Postma, D S; Rijcken, B
1994-01-01
Peak expiratory flow (PEF) variability can be considered as an index of bronchial lability. Population studies on PEF variability are few. The purpose of the current paper is to describe the distribution of PEF variability in a random population sample of adults with a wide age range (20-70 yrs),
Wik, L.; Olsen, J.A.; Persse, D.; Sterz, F.; Lozano Jr, M.; Brouwer, M.A.; Westfall, M.; Souders, C.M.; Malzer, R.; Grunsven, P.M. van; Travis, D.T.; Whitehead, A.; Herken, U.R.; Lerner, E.B.
2014-01-01
OBJECTIVE: To compare integrated automated load distributing band CPR (iA-CPR) with high-quality manual CPR (M-CPR) to determine equivalence, superiority, or inferiority in survival to hospital discharge. METHODS: Between March 5, 2009 and January 11, 2011 a randomized, unblinded, controlled group
Elizabeth A. Freeman; Gretchen G. Moisen; Tracy S. Frescino
2012-01-01
Random Forests is frequently used to model species distributions over large geographic areas. Complications arise when data used to train the models have been collected in stratified designs that involve different sampling intensity per stratum. The modeling process is further complicated if some of the target species are relatively rare on the landscape leading to an...
Energy Technology Data Exchange (ETDEWEB)
Munoz Montplet, C.; Jurado Bruggeman, D.
2010-07-01
Geometrical random uncertainty in radiotherapy is usually characterized by a unique value in each group of patients. We propose a novel approach based on a statistically accurate characterization of the uncertainty distribution, thus reducing the risk of obtaining potentially unsafe results in CT V-Pt margins or in the selection of correction protocols.
Sawilowsky, Shlomo
1985-01-01
The Random Normal Scores Test (RNST) has been suggested as a powerful alternative to the use of the parametric analysis of variance (ANOVA) test when the underlying population is non-normally distributed. The major support for this suggestion rests on asymptotic theory. An empirical analysis of the RNST performed under the F and Chi-square…
Modern approaches to discrete curvature
Romon, Pascal
2017-01-01
This book provides a valuable glimpse into discrete curvature, a rich new field of research which blends discrete mathematics, differential geometry, probability and computer graphics. It includes a vast collection of ideas and tools which will offer something new to all interested readers. Discrete geometry has arisen as much as a theoretical development as in response to unforeseen challenges coming from applications. Discrete and continuous geometries have turned out to be intimately connected. Discrete curvature is the key concept connecting them through many bridges in numerous fields: metric spaces, Riemannian and Euclidean geometries, geometric measure theory, topology, partial differential equations, calculus of variations, gradient flows, asymptotic analysis, probability, harmonic analysis, graph theory, etc. In spite of its crucial importance both in theoretical mathematics and in applications, up to now, almost no books have provided a coherent outlook on this emerging field.
Generating Realistic Labelled, Weighted Random Graphs
Davis, Michael Charles; Liu, Weiru; Miller, Paul; Hunter, Ruth; Kee, Frank
2015-01-01
Generative algorithms for random graphs have yielded insights into the structure and evolution of real-world networks. Most networks exhibit a well-known set of properties, such as heavy-tailed degree distributions, clustering and community formation. Usually, random graph models consider only structural information, but many real-world networks also have labelled vertices and weighted edges. In this paper, we present a generative model for random graphs with discrete vertex labels and numeric edge weights. The weights are represented as a set of Beta Mixture Models (BMMs) with an arbitrary number of mixtures, which are learned from real-world networks. We propose a Bayesian Variational Inference (VI) approach, which yields an accurate estimation while keeping computation times tractable. We compare our approach to state-of-the-art random labelled graph generators and an earlier approach based on Gaussian Mixture Models (GMMs). Our results allow us to draw conclusions about the contribution of vertex labels a...
Accessibility and delay in random temporal networks
Tajbakhsh, Shahriar Etemadi; Coon, Justin P.; Simmons, David E.
2017-09-01
In a wide range of complex networks, the links between the nodes are temporal and may sporadically appear and disappear. This temporality is fundamental to analyzing the formation of paths within such networks. Moreover, the presence of the links between the nodes is a random process induced by nature in many real-world networks. In this paper, we study random temporal networks at a microscopic level and formulate the probability of accessibility from a node i to a node j after a certain number of discrete time units T . While solving the original problem is computationally intractable, we provide an upper and two lower bounds on this probability for a very general case with arbitrary time-varying probabilities of the links' existence. Moreover, for a special case where the links have identical probabilities across the network at each time slot, we obtain the exact probability of accessibility between any two nodes. Finally, we discuss scenarios where the information regarding the presence and absence of links is initially available in the form of time duration (of presence or absence intervals) continuous probability distributions rather than discrete probabilities over time slots. We provide a method for transforming such distributions to discrete probabilities, which enables us to apply the given bounds in this paper to a broader range of problem settings.
Álvarez-Pérez, Jacqueline; Sánchez-Villegas, Almudena; Díaz-Benítez, Elena María; Ruano-Rodríguez, Cristina; Corella, Dolores; Martínez-González, Míguel Ángel; Estruch, Ramón; Salas-Salvadó, Jordi; Serra-Majem, Lluís
2016-08-01
To assess the influence of a Mediterranean dietary pattern (MeDiet) on anthropometric and body composition parameters in one of the centers of the PREDIMED randomized dietary trial. 351 Canarian free-living subjects aged 55 to 80 years, with type 2 diabetes or ≥3 cardiovascular risk factors. Participants were randomly assigned to one of 3 different dietary interventions: MeDiet + extra-virgin olive oil (EVOO), MeDiet + nuts (walnuts, almonds, and hazelnuts), or a control low-fat diet. Total energy intake was ad libitum. Measures included changes in anthropometric measures (weight, body mass index [BMI] and waist circumference [WC]), body fat distribution, energy, and nutrient intake after 1 year. Body composition (percentage of total body fat [%TBF], total fat mass [TFM], free fat mass [FFM], percentage of truncal fat [%TrF], truncal fat mass [TrFM]) and total body water (TBW) were estimated by octapolar electrical impedance analysis. Paired t tests were conducted to assess within-group changes. Analyses of variance (ANOVAs) were used to assess the effect of the dietary intervention on the percentage change in anthropometric variables, body composition, and dietary intake profile. All pairwise comparisons that were statistically significant in ANOVA were subsequently adjusted using the Benjamini-Hochberg test, which penalizes for multiple comparisons. After 1 year of intervention, significant within-group reductions in all anthropometric variables were observed for the MeDiet + EVOO and the control group. The MeDiet + nuts group exhibited a significant reduction in WC and TBW. The control group showed a significant increase in %TBF and a reduction in TBW. The control group showed a significant increase in the percentage of total body fat and a reduction in TBW. However, we did not find any between-group significant difference in anthropometric or body composition changes. Mediterranean diets enriched with EVOO or specific mixed nuts (walnuts, almonds, hazelnuts
A Local-Realistic Model of Quantum Mechanics Based on a Discrete Spacetime
Sciarretta, Antonio
2018-01-01
This paper presents a realistic, stochastic, and local model that reproduces nonrelativistic quantum mechanics (QM) results without using its mathematical formulation. The proposed model only uses integer-valued quantities and operations on probabilities, in particular assuming a discrete spacetime under the form of a Euclidean lattice. Individual (spinless) particle trajectories are described as random walks. Transition probabilities are simple functions of a few quantities that are either randomly associated to the particles during their preparation, or stored in the lattice nodes they visit during the walk. QM predictions are retrieved as probability distributions of similarly-prepared ensembles of particles. The scenarios considered to assess the model comprise of free particle, constant external force, harmonic oscillator, particle in a box, the Delta potential, particle on a ring, particle on a sphere and include quantization of energy levels and angular momentum, as well as momentum entanglement.
Discrete dynamics versus analytic dynamics
DEFF Research Database (Denmark)
Toxværd, Søren
2014-01-01
For discrete classical Molecular dynamics obtained by the “Verlet” algorithm (VA) with the time increment h there exists a shadow Hamiltonian H˜ with energy E˜(h) , for which the discrete particle positions lie on the analytic trajectories for H˜ . Here, we proof that there, independent of such a......For discrete classical Molecular dynamics obtained by the “Verlet” algorithm (VA) with the time increment h there exists a shadow Hamiltonian H˜ with energy E˜(h) , for which the discrete particle positions lie on the analytic trajectories for H˜ . Here, we proof that there, independent...... of such an analytic analogy, exists an exact hidden energy invariance E * for VA dynamics. The fact that the discrete VA dynamics has the same invariances as Newtonian dynamics raises the question, which of the formulations that are correct, or alternatively, the most appropriate formulation of classical dynamics....... In this context the relation between the discrete VA dynamics and the (general) discrete dynamics investigated by Lee [Phys. Lett. B122, 217 (1983)] is presented and discussed....
de Bock, Martin; Derraik, José G B; Brennan, Christine M; Biggs, Janene B; Smith, Greg C; Cameron-Smith, David; Wall, Clare R; Cutfield, Wayne S
2012-01-01
We aimed to assess the effects of psyllium supplementation on insulin sensitivity and other parameters of the metabolic syndrome in an at risk adolescent population. This study encompassed a participant-blinded, randomized, placebo-controlled, crossover trial. Subjects were 47 healthy adolescent males aged 15-16 years, recruited from secondary schools in lower socio-economic areas with high rates of obesity. Participants received 6 g/day of psyllium or placebo for 6 weeks, with a two-week washout before crossing over. Fasting lipid profiles, ambulatory blood pressure, auxological data, body composition, activity levels, and three-day food records were collected at baseline and after each 6-week intervention. Insulin sensitivity was measured by the Matsuda method using glucose and insulin values from an oral glucose tolerance test. 45 subjects completed the study, and compliance was very high: 87% of participants took >80% of prescribed capsules. At baseline, 44% of subjects were overweight or obese. 28% had decreased insulin sensitivity, but none had impaired glucose tolerance. Fibre supplementation led to a 4% reduction in android fat to gynoid fat ratio (p = 0.019), as well as a 0.12 mmol/l (6%) reduction in LDL cholesterol (p = 0.042). No associated adverse events were recorded. Dietary supplementation with 6 g/day of psyllium over 6 weeks improves fat distribution and lipid profile (parameters of the metabolic syndrome) in an at risk population of adolescent males. Australian New Zealand Clinical Trials Registry ACTRN12609000888268.
Directory of Open Access Journals (Sweden)
Martin de Bock
Full Text Available AIMS: We aimed to assess the effects of psyllium supplementation on insulin sensitivity and other parameters of the metabolic syndrome in an at risk adolescent population. METHODS: This study encompassed a participant-blinded, randomized, placebo-controlled, crossover trial. Subjects were 47 healthy adolescent males aged 15-16 years, recruited from secondary schools in lower socio-economic areas with high rates of obesity. Participants received 6 g/day of psyllium or placebo for 6 weeks, with a two-week washout before crossing over. Fasting lipid profiles, ambulatory blood pressure, auxological data, body composition, activity levels, and three-day food records were collected at baseline and after each 6-week intervention. Insulin sensitivity was measured by the Matsuda method using glucose and insulin values from an oral glucose tolerance test. RESULTS: 45 subjects completed the study, and compliance was very high: 87% of participants took >80% of prescribed capsules. At baseline, 44% of subjects were overweight or obese. 28% had decreased insulin sensitivity, but none had impaired glucose tolerance. Fibre supplementation led to a 4% reduction in android fat to gynoid fat ratio (p = 0.019, as well as a 0.12 mmol/l (6% reduction in LDL cholesterol (p = 0.042. No associated adverse events were recorded. CONCLUSIONS: Dietary supplementation with 6 g/day of psyllium over 6 weeks improves fat distribution and lipid profile (parameters of the metabolic syndrome in an at risk population of adolescent males. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12609000888268.
Directory of Open Access Journals (Sweden)
Jinyu Ren
2015-01-01
Full Text Available Purpose: The purpose of this paper is to set up the coordinating mechanism for a decentralized distribution system consisting of a manufacturer and multiple independent retailers by means of contracts. It is in the two-stage supply chain system that all retailers sell an identical product made by the manufacturer and determine their order quantities which directly affect the expected profit of the supply chain with random demand. Design/methodology/approach: First comparison of the optimal order quantities in the centralized and decentralized system shows that the supply chain needs coordination. Then the coordination model is given based on buyback cost and compensation benefit. Finally the coordination mechanism is set up in which the manufacturer as the leader uses a buyback policy to incentive these retailers and the retailers pay profit returns to compensate the manufacturer. Findings: The results of a numerical example show that the perfect supply chain coordination and the flexible allocation of the profit can be achieved in the multi-retailer supply chain by the buyback and compensation contracts. Research limitations: The results based on assumptions might not completely hold in practice and the paper only focuses on studying a single product in two-stage supply chain. Practical implications: The coordination mechanism is applicable to a realistic supply chain under a private information setting and the research results is the foundation of further developing the coordination mechanism for a realistic multi-stage supply chain system with more products. Originality/value: This paper focused on studying the coordination mechanism for a decentralized multi-retailer supply chain by the joint application of the buyback and compensation contracts. Furthermore the perfect supply chain coordination and the flexible allocation of the profit are achieved.
The origin of discrete particles
Bastin, T
2009-01-01
This book is a unique summary of the results of a long research project undertaken by the authors on discreteness in modern physics. In contrast with the usual expectation that discreteness is the result of mathematical tools for insertion into a continuous theory, this more basic treatment builds up the world from the discrimination of discrete entities. This gives an algebraic structure in which certain fixed numbers arise. As such, one agrees with the measured value of the fine-structure constant to one part in 10,000,000 (10 7 ). Sample Chapter(s). Foreword (56 KB). Chapter 1: Introduction
Discrete symmetries from hidden sectors
Energy Technology Data Exchange (ETDEWEB)
Anastasopoulos, Pascal [Institut für Theoretische Physik, Technische Universität Wien,A-1040 Vienna (Austria); Richter, Robert [II. Institut für Theoretische Physik, Hamburg University,Hamburg (Germany); Schellekens, A.N. [NIKHEF,Science Park 105, 1098 XG Amsterdam (Netherlands); IMAPP, Radboud Universiteit Nijmegen,Nijmegen (Netherlands); Instituto de Física Fundamental, CSIC,Madrid (Spain)
2015-06-29
We study the presence of abelian discrete symmetries in globally consistent orientifold compactifications based on rational conformal field theory. We extend previous work http://dx.doi.org/10.1016/j.nuclphysb.2012.08.008 by allowing the discrete symmetries to be a linear combination of U(1) gauge factors of the visible as well as the hidden sector. This more general ansatz significantly increases the probability of finding a discrete symmetry in the low energy effective action. Applied to globally consistent MSSM-like Gepner constructions we find multiple models that allow for matter parity or Baryon triality.
Pratte, Michael S; Park, Young Eun; Rademaker, Rosanne L; Tong, Frank
2017-01-01
If we view a visual scene that contains many objects, then momentarily close our eyes, some details persist while others seem to fade. Discrete models of visual working memory (VWM) assume that only a few items can be actively maintained in memory, beyond which pure guessing will emerge. Alternatively, continuous resource models assume that all items in a visual scene can be stored with some precision. Distinguishing between these competing models is challenging, however, as resource models that allow for stochastically variable precision (across items and trials) can produce error distributions that resemble random guessing behavior. Here, we evaluated the hypothesis that a major source of variability in VWM performance arises from systematic variation in precision across the stimuli themselves; such stimulus-specific variability can be incorporated into both discrete-capacity and variable-precision resource models. Participants viewed multiple oriented gratings, and then reported the orientation of a cued grating from memory. When modeling the overall distribution of VWM errors, we found that the variable-precision resource model outperformed the discrete model. However, VWM errors revealed a pronounced "oblique effect," with larger errors for oblique than cardinal orientations. After this source of variability was incorporated into both models, we found that the discrete model provided a better account of VWM errors. Our results demonstrate that variable precision across the stimulus space can lead to an unwarranted advantage for resource models that assume stochastically variable precision. When these deterministic sources are adequately modeled, human working memory performance reveals evidence of a discrete capacity limit. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Discrete-time queues with general service times and general server interruptions
Fiems, Dieter; Steyaert, Bart; Bruneel, Herwig
2001-02-01
In this contribution, we investigate a discrete-time single- server queue subjected to server interruptions. Server interruptions are modeled as an on/off process with geometrically distributed on-periods and generally distributed off-periods. As message lengths can exceed one time-slot, different operation modes are considered depending on whether service of an interrupted message continues, partially restarts or completely restarts after an interruption. For all alternatives, we establish expressions for the steady-state probability generating functions of the buffer contents at message departure time and at random slot boundaries. From these results, closed- form expressions for various performance measures, such as mean and variance of the buffer occupancy, can be established. As an application, we show that this model is able to assess performance of low-priority traffic in a two- priority HOL scheduling discipline. We then illustrate our approach with some numerical examples.
Batch arrival discrete time queue with gated vacation system ...
African Journals Online (AJOL)
A class of single server vacation queues, which have batch arrivals and single server, is considered in discrete time. Here the server goes on vacation of random length as soon as the system becomes empty. On return from vacation, if he finds any customers waiting in the queue, the server starts serving the customers one ...
Ko, Heasin; Choi, Byung-Seok; Choe, Joong-Seon; Kim, Kap-Joong; Kim, Jong-Hoi; Youn, Chun Ju
2017-08-21
Most polarization-based BB84 quantum key distribution (QKD) systems utilize multiple lasers to generate one of four polarization quantum states randomly. However, random bit generation with multiple lasers can potentially open critical side channels that significantly endangers the security of QKD systems. In this paper, we show unnoticed side channels of temporal disparity and intensity fluctuation, which possibly exist in the operation of multiple semiconductor laser diodes. Experimental results show that the side channels can enormously degrade security performance of QKD systems. An important system issue for the improvement of quantum bit error rate (QBER) related with laser driving condition is further addressed with experimental results.
New formulation of the discrete element method
Rojek, Jerzy; Zubelewicz, Aleksander; Madan, Nikhil; Nosewicz, Szymon
2018-01-01
A new original formulation of the discrete element method based on the soft contact approach is presented in this work. The standard DEM has heen enhanced by the introduction of the additional (global) deformation mode caused by the stresses in the particles induced by the contact forces. Uniform stresses and strains are assumed for each particle. The stresses are calculated from the contact forces. The strains are obtained using an inverse constitutive relationship. The strains allow us to obtain deformed particle shapes. The deformed shapes (ellipses) are taken into account in contact detection and evaluation of the contact forces. A simple example of a uniaxial compression of a rectangular specimen, discreti.zed with equal sized particles is simulated to verify the DDEM algorithm. The numerical example shows that a particle deformation changes the particle interaction and the distribution of forces in the discrete element assembly. A quantitative study of micro-macro elastic properties proves the enhanced capabilities of the DDEM as compared to standard DEM.
Exact discretization by Fourier transforms
Tarasov, Vasily E.
2016-08-01
A discretization of differential and integral operators of integer and non-integer orders is suggested. New type of differences, which are represented by infinite series, is proposed. A characteristic feature of the suggested differences is an implementation of the same algebraic properties that have the operator of differentiation (property of algebraic correspondence). Therefore the suggested differences are considered as an exact discretization of derivatives. These differences have a property of universality, which means that these operators do not depend on the form of differential equations and the parameters of these equations. The suggested differences operators allows us to have difference equations whose solutions are equal to the solutions of corresponding differential equations. The exact discretization of the derivatives of integer orders is given by the suggested differences of the same integer orders. Similarly, the exact discretization of the Riesz derivatives and integrals of integer and non-integer order is given by the proposed fractional differences of the same order.
Discrete geodesics and cellular automata
Arrighi, Pablo
2015-01-01
This paper proposes a dynamical notion of discrete geodesics, understood as straightest trajectories in discretized curved spacetime. The notion is generic, as it is formulated in terms of a general deviation function, but readily specializes to metric spaces such as discretized pseudo-riemannian manifolds. It is effective: an algorithm for computing these geodesics naturally follows, which allows numerical validation---as shown by computing the perihelion shift of a Mercury-like planet. It is consistent, in the continuum limit, with the standard notion of timelike geodesics in a pseudo-riemannian manifold. Whether the algorithm fits within the framework of cellular automata is discussed at length. KEYWORDS: Discrete connection, parallel transport, general relativity, Regge calculus.
Discrete Input Signaling for MISO Visible Light Communication Channels
Arfaoui, Mohamed Amine
2017-05-12
In this paper, we study the achievable secrecy rate of visible light communication (VLC) links for discrete input distributions. We consider single user single eavesdropper multiple-input single-output (MISO) links. In addition, both beamforming and robust beamforming are considered. In the former case, the location of the eavesdropper is assumed to be known, whereas in the latter case, the location of the eavesdropper is unknown. We compare the obtained results with those achieved by some continuous distributions including the truncated generalized normal (TGN) distribution and the uniform distribution. We numerically show that the secrecy rate achieved by the discrete input distribution with a finite support is significantly improved as compared to those achieved by the TGN and the uniform distributions.
Discrete-to-continuous transition in quantum phase estimation
Rządkowski, Wojciech; Demkowicz-Dobrzański, Rafał
2017-09-01
We analyze the problem of quantum phase estimation in which the set of allowed phases forms a discrete N -element subset of the whole [0 ,2 π ] interval, φn=2 π n /N , n =0 ,⋯,N -1 , and study the discrete-to-continuous transition N →∞ for various cost functions as well as the mutual information. We also analyze the relation between the problems of phase discrimination and estimation by considering a step cost function of a given width σ around the true estimated value. We show that in general a direct application of the theory of covariant measurements for a discrete subgroup of the U(1 ) group leads to suboptimal strategies due to an implicit requirement of estimating only the phases that appear in the prior distribution. We develop the theory of subcovariant measurements to remedy this situation and demonstrate truly optimal estimation strategies when performing a transition from discrete to continuous phase estimation.
Random functions and turbulence
Panchev, S
1971-01-01
International Series of Monographs in Natural Philosophy, Volume 32: Random Functions and Turbulence focuses on the use of random functions as mathematical methods. The manuscript first offers information on the elements of the theory of random functions. Topics include determination of statistical moments by characteristic functions; functional transformations of random variables; multidimensional random variables with spherical symmetry; and random variables and distribution functions. The book then discusses random processes and random fields, including stationarity and ergodicity of random
Discrete solitons in coupled active lasing cavities
Prilepsky, Jaroslaw E; Johansson, Magnus; Derevyanko, Stanislav A
2012-01-01
We examine the existence and stability of discrete spatial solitons in coupled nonlinear lasing cavities (waveguide resonators), addressing the case of active media, where the gain exceeds damping in the linear limit. A zoo of stable localized structures is found and classified: these are bright and grey cavity solitons with different symmetry. It is shown that several new types of solitons with a nontrivial intensity distribution pattern can emerge in the coupled cavities due to the stability of a periodic extended state. The latter can be stable even when a bistability of homogenous states is absent.
Alfa, Attahiru S
2016-01-01
This book introduces the theoretical fundamentals for modeling queues in discrete-time, and the basic procedures for developing queuing models in discrete-time. There is a focus on applications in modern telecommunication systems. It presents how most queueing models in discrete-time can be set up as discrete-time Markov chains. Techniques such as matrix-analytic methods (MAM) that can used to analyze the resulting Markov chains are included. This book covers single node systems, tandem system and queueing networks. It shows how queues with time-varying parameters can be analyzed, and illustrates numerical issues associated with computations for the discrete-time queueing systems. Optimal control of queues is also covered. Applied Discrete-Time Queues targets researchers, advanced-level students and analysts in the field of telecommunication networks. It is suitable as a reference book and can also be used as a secondary text book in computer engineering and computer science. Examples and exercises are includ...
Analysis of stochastic effects in Kaldor-type business cycle discrete model
Bashkirtseva, Irina; Ryashko, Lev; Sysolyatina, Anna
2016-07-01
We study nonlinear stochastic phenomena in the discrete Kaldor model of business cycles. A numerical parametric analysis of stochastically forced attractors (equilibria, closed invariant curves, discrete cycles) of this model is performed using the stochastic sensitivity functions technique. A spatial arrangement of random states in stochastic attractors is modeled by confidence domains. The phenomenon of noise-induced transitions ;chaos-order; is discussed.
DEFF Research Database (Denmark)
Kjærgaard, Magnus; Poulsen, Flemming Martin
2011-01-01
. The contributions from the neighboring residues are typically removed by using neighbor correction factors determined based on each residue's effect on glycine chemical shifts. Due to its unusual conformational freedom, glycine may be particularly unrepresentative for the remaining residue types. In this study, we......Random coil chemical shifts are necessary for secondary chemical shift analysis, which is the main NMR method for identification of secondary structure in proteins. One of the largest challenges in the determination of random coil chemical shifts is accounting for the effect of neighboring residues...... use random coil peptides containing glutamine instead of glycine to determine the random coil chemical shifts and the neighbor correction factors. The resulting correction factors correlate to changes in the populations of the major wells in the Ramachandran plot, which demonstrates that changes...
Discrete Curvature Theories and Applications
Sun, Xiang
2016-08-25
Discrete Di erential Geometry (DDG) concerns discrete counterparts of notions and methods in di erential geometry. This thesis deals with a core subject in DDG, discrete curvature theories on various types of polyhedral surfaces that are practically important for free-form architecture, sunlight-redirecting shading systems, and face recognition. Modeled as polyhedral surfaces, the shapes of free-form structures may have to satisfy di erent geometric or physical constraints. We study a combination of geometry and physics { the discrete surfaces that can stand on their own, as well as having proper shapes for the manufacture. These proper shapes, known as circular and conical meshes, are closely related to discrete principal curvatures. We study curvature theories that make such surfaces possible. Shading systems of freeform building skins are new types of energy-saving structures that can re-direct the sunlight. From these systems, discrete line congruences across polyhedral surfaces can be abstracted. We develop a new curvature theory for polyhedral surfaces equipped with normal congruences { a particular type of congruences de ned by linear interpolation of vertex normals. The main results are a discussion of various de nitions of normality, a detailed study of the geometry of such congruences, and a concept of curvatures and shape operators associated with the faces of a triangle mesh. These curvatures are compatible with both normal congruences and the Steiner formula. In addition to architecture, we consider the role of discrete curvatures in face recognition. We use geometric measure theory to introduce the notion of asymptotic cones associated with a singular subspace of a Riemannian manifold, which is an extension of the classical notion of asymptotic directions. We get a simple expression of these cones for polyhedral surfaces, as well as convergence and approximation theorems. We use the asymptotic cones as facial descriptors and demonstrate the
Directory of Open Access Journals (Sweden)
Vicente D. Estruch
2017-08-01
Full Text Available The concept of random variable is a mathematical construct that presents some theoretical complexity. However, learning this concept can be facilitated if it is presented as the end of a sequential process of modeling of a real event. More specifically, to learn the concept of discrete random variable, the Monte Carlo simulation can provide an extremely useful tool because in the process of modeling / simulation one can approach the theoretical concept of random variable, while the random variable is observed \\in action". This paper presents a Research and Study Course (RSC based on series of activities related to random variables such as training and introduction of simulation elements, then the construction of the model is presented, which is the substantial part of the activity, generating a random variable and its probability function. Starting from a simple situation related to reproduction and survival of the litter of a rodent, with random components, step by step, the model that represents the real raised situation is built obtaining an \\original" random variable. In the intermediate stages of the construction of the model have a fundamental role the uniform discrete and binomial distributions. The trajectory of these stages allows reinforcing the concept of random variable while exploring the possibilities offered by Monte Carlo methods to simulate real cases and the simplicity of implementing these methods by means of the Matlab© programming language.
Discrete Model for Concrete Fracture: Numerical Study of Dynamic Response
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Květoň Josef
2016-12-01
Full Text Available The contribution presents simulations on concrete specimens. The discrete meso-scale particle model with random geometry based on Voronoi tessellation is used. The model was enhanced with dynamic solver based on implicit Newmark method. Model is tested on cantilever beam loaded by a force at the free end to verify the ability of the model to simulate the dynamic behavior of a simple linear elastic material. Results computed with different time discretization and model settings are compared. The behavior of the model in nonlinear regime is investigated on concrete specimens loaded at different displacement rates. The constitutive law used within this contribution is insensitive to strain rate.
Foundations of the probabilistic mechanics of discrete media
Axelrad, D R
1984-01-01
This latest volume in the Foundations & Philosophy of Science & Technology series provides an account of probabilistic functional analysis and shows its applicability in the formulation of the behaviour of discrete media with the inclusion of microstructural effects. Although quantum mechanics have long been recognized as a stochastic theory, the introduction of probabilistic concepts and principles to classical mechanics has in general not been attempted. In this study the author takes the view that the significant field quantities of a discrete medium are random variables or functions of s
Analysis of Discrete Mittag - Leffler Functions
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N. Shobanadevi
2015-03-01
Full Text Available Discrete Mittag - Leffler functions play a major role in the development of the theory of discrete fractional calculus. In the present article, we analyze qualitative properties of discrete Mittag - Leffler functions and establish sufficient conditions for convergence, oscillation and summability of the infinite series associated with discrete Mittag - Leffler functions.
Strong Decomposition of Random Variables
DEFF Research Database (Denmark)
Hoffmann-Jørgensen, Jørgen; Kagan, Abram M.; Pitt, Loren D.
2007-01-01
A random variable X is stongly decomposable if X=Y+Z where Y=Φ(X) and Z=X-Φ(X) are independent non-degenerated random variables (called the components). It is shown that at least one of the components is singular, and we derive a necessary and sufficient condition for strong decomposability...... of a discrete random variable....
Integer valued autoregressive processes with generalized discrete Mittag-Leffler marginals
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Kanichukattu K. Jose
2013-05-01
Full Text Available In this paper we consider a generalization of discrete Mittag-Leffler distributions. We introduce and study the properties of a new distribution called geometric generalized discrete Mittag-Leffler distribution. Autoregressive processes with geometric generalized discrete Mittag-Leffler distributions are developed and studied. The distributions are further extended to develop a more general class of geometric generalized discrete semi-Mittag-Leffler distributions. The processes are extended to higher orders also. An application with respect to an empirical data on customer arrivals in a bank counter is also given. Various areas of potential applications like human resource development, insect growth, epidemic modeling, industrial risk modeling, insurance and actuaries, town planning etc are also discussed.
Integrable structure in discrete shell membrane theory.
Schief, W K
2014-05-08
We present natural discrete analogues of two integrable classes of shell membranes. By construction, these discrete shell membranes are in equilibrium with respect to suitably chosen internal stresses and external forces. The integrability of the underlying equilibrium equations is proved by relating the geometry of the discrete shell membranes to discrete O surface theory. We establish connections with generalized barycentric coordinates and nine-point centres and identify a discrete version of the classical Gauss equation of surface theory.
Most, S.; Jia, N.; Bijeljic, B.; Nowak, W.
2016-12-01
Pre-asymptotic characteristics are almost ubiquitous when analyzing solute transport processes in porous media. These pre-asymptotic aspects are caused by spatial coherence in the velocity field and by its heterogeneity. For the Lagrangian perspective of particle displacements, the causes of pre-asymptotic, non-Fickian transport are skewed velocity distribution, statistical dependencies between subsequent increments of particle positions (memory) and dependence between the x, y and z-components of particle increments. Valid simulation frameworks should account for these factors. We propose a particle tracking random walk (PTRW) simulation technique that can use empirical pore-space velocity distributions as input, enforces memory between subsequent random walk steps, and considers cross dependence. Thus, it is able to simulate pre-asymptotic non-Fickian transport phenomena. Our PTRW framework contains an advection/dispersion term plus a diffusion term. The advection/dispersion term produces time-series of particle increments from the velocity CDFs. These time series are equipped with memory by enforcing that the CDF values of subsequent velocities change only slightly. The latter is achieved through a random walk on the axis of CDF values between 0 and 1. The virtual diffusion coefficient for that random walk is our only fitting parameter. Cross-dependence can be enforced by constraining the random walk to certain combinations of CDF values between the three velocity components in x, y and z. We will show that this modelling framework is capable of simulating non-Fickian transport by comparison with a pore-scale transport simulation and we analyze the approach to asymptotic behavior.
Nonlinear absorption in discrete systems
Energy Technology Data Exchange (ETDEWEB)
Spire, A; Leon, J [Physique Mathematique et Theorique, CNRS-UMR5825, Universite Montpellier 2, 34095 Montpellier (France)
2004-10-01
In the context of nonlinear scattering, a continuous wave incident onto a nonlinear discrete molecular chain of coupled oscillators can be partially absorbed as a result of a three-wave resonant interaction that couples two HF-waves of frequencies close to the edge of the Brillouin zone. Hence both nonlinearity and discreteness are necessary for generating this new absorption process which manifests itself by soliton generation in the medium. As a paradigm of this nonlinear absorption we consider here the Davydov model that describes exciton-phonon coupling in hydrogen-bonded molecular chains.
Some discrete multiple orthogonal polynomials
Arvesú, J.; Coussement, J.; Van Assche, W.
2003-01-01
27 pages, no figures.-- MSC2000 codes: 33C45, 33C10, 42C05, 41A28.-- Issue title: "Proceedings of the 6th International Symposium on Orthogonal Polynomials, Special Functions and their Applications" (OPSFA-VI, Rome, Italy, 18-22 June 2001). MR#: MR1985676 (2004g:33015) Zbl#: Zbl 1021.33006 In this paper, we extend the theory of discrete orthogonal polynomials (on a linear lattice) to polynomials satisfying orthogonality conditions with respect to r positive discrete measures. First w...
Institutionalism and Commissions Executive Discretion: an Empirical Analysis
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Fabio Franchino
1998-07-01
Full Text Available Theory: The adoption of EC secondary legislation can be analyzed from the perspective of agency theory whereby Member States and the Parliament delegate policy authority to the Commission and design ex-post control procedures (i.e. Comitology. Rational choice and sociological institutionalisms differ in their predictions on the way rules and norms affect the extent of executive discretion. Hypothesis: Three institutionalist hypotheses are tested. The rationalist one derives from a Bayesian game developed by the author. It posits that Commissions executive discretion in non amending secondary legislation is a function of: 1 formal legislative procedure, 2 information asymmetry and 3 distribution of principals preferences. A fourth variable, legislative instrument, is also included. The diluted rationalist hypothesis substitutes formal with informal procedure in one policy area. The socio-rational hypothesis adds two new variables, that is the opinions of the Parliament and the Economic and Social Committee. A final co-graduation test is conducted on whether more discretion leads to more stringent ex-post control. Methods: Given the bimodal error structure of the regression model, I have bootstrapped the regression coefficients and computed the 95% confidence intervals of the null hypothesis. Bootstrapping has also been used to test the role of the European Parliament, of opinions and the co-graduation between discretion and ex-post control. A stratified sample of non amending secondary legislation adopted from 1987 to 1993 has been drawn to test the hypotheses. Results: The diluted rationalist hypothesis is the most accurate. Information asymmetry, informal legislative procedures and legislative instruments are statistically and substantively relevant in explaining executive discretion. Distribution of preferences has weak explanatory power probably because of the lack of reliable data and appropriate measurement. The Parliament and opinions do
Choice certainty in Discrete Choice Experiments
DEFF Research Database (Denmark)
Uggeldahl, Kennet Christian; Jacobsen, Catrine; Lundhede, Thomas
2016-01-01
In this study, we conduct a Discrete Choice Experiment (DCE) using eye tracking technology to investigate if eye movements during the completion of choice sets reveal information about respondents’ choice certainty. We hypothesise that the number of times that respondents shift their visual...... attention between the alternatives in a choice set reflects their stated choice certainty. Based on one of the largest samples of eye tracking data in a DCE to date, we find evidence in favor of our hypothesis. We also link eye tracking observations to model-based choice certainty through parameterization...... of the scale function in a random parameters logit model. We find that choices characterized by more frequent gaze shifting do indeed exhibit a higher degree of error variance, however, this effects is insignificant once response time is controlled for. Overall, findings suggest that eye tracking can provide...
Solving discrete zero point problems
van der Laan, G.; Talman, A.J.J.; Yang, Z.F.
2004-01-01
In this paper an algorithm is proposed to .nd a discrete zero point of a function on the collection of integral points in the n-dimensional Euclidean space IRn.Starting with a given integral point, the algorithm generates a .nite sequence of adjacent integral simplices of varying dimension and
Path integrals as discrete sums
Bitar, Khalil; Khuri, N. N.; Ren, H. C.
1991-08-01
We present a new formulation of Feynman's path integral, based on Voronin's theorems on the universality of the Riemann zeta function. The result is a discrete sum over ``paths,'' each given by a zeta function. A new measure which leads to the correct quantum mechanics is explicitly given.
Modules over discrete valuation domains
Tuganbaev, Askar A
2008-01-01
This book provides the first systematic treatment of modules over discrete valuation domains which plays an important role in various areas of algebra, especially in commutative algebra. Many important results representing the state of the art are presented in the text which is supplemented by exercises and interesting open problems. An important contribution to commutative algebra.
Mudie, M H; Winzeler-Mercay, U; Radwan, S; Lee, L
2002-09-01
To determine (1) the most effective of three treatment approaches to retrain seated weight distribution long-term after stroke and (2) whether improvements could be generalized to weight distribution in standing. Inpatient rehabilitation unit. Forty asymmetrical acute stroke subjects were randomly allocated to one of four groups in this pilot study. Changes in weight distribution were compared between the 10 subjects of each of three treatment groups (task-specific reach, Bobath, or Balance Performance Monitor [BPM] feedback training) and a no specific treatment control group. One week of measurement only was followed by two weeks of daily training sessions with the treatment to which the subject was randomly allocated. Measurements were performed using the BPM daily before treatment sessions, two weeks after cessation of treatment and 12 weeks post study. Weight distribution was calculated in terms of mean balance (percentage of total body weight) or the mean of 300 balance points over a 30-s data run. In the short term, the Bobath approach was the most effective treatment for retraining sitting symmetry after stroke (p = 0.004). Training with the BPM and no training were also significant (p = 0.038 and p = 0.035 respectively) and task-specific reach training failed to reach significance (p = 0.26). At 12 weeks post study 83% of the BPM training group, 38% of the task-specific reach group, 29% of the Bobath group and 0% of the untrained group were found to be distributing their weight to both sides. Some generalization of symmetry training in sitting to standing was noted in the BPM training group which appeared to persist long term. Results should be treated with caution due to the small group sizes. However, these preliminary findings suggest that it might be possible to restore postural symmetry in sitting in the early stages of rehabilitation with therapy that focuses on creating an awareness of body position.
Execution of VHDL Models Using Parallel Discrete Event Simulation Algorithms
Ashenden, Peter J.; Henry Detmold; McKeen, Wayne S.
1994-01-01
In this paper, we discuss the use of parallel discrete event simulation (PDES) algorithms for execution of hardware models written in VHDL. We survey central event queue, conservative distributed and optimistic distributed PDES algorithms, and discuss aspects of the semantics of VHDL and VHDL-92 that affect the use of these algorithms in a VHDL simulator. Next, we describe an experiment performed as part of the Vsim Project at the University of Adelaide, in which a simulation kernel using the...
Osorio-Murillo, C. A.; Over, M. W.; Frystacky, H.; Ames, D. P.; Rubin, Y.
2013-12-01
A new software application called MAD# has been coupled with the HTCondor high throughput computing system to aid scientists and educators with the characterization of spatial random fields and enable understanding the spatial distribution of parameters used in hydrogeologic and related modeling. MAD# is an open source desktop software application used to characterize spatial random fields using direct and indirect information through Bayesian inverse modeling technique called the Method of Anchored Distributions (MAD). MAD relates indirect information with a target spatial random field via a forward simulation model. MAD# executes inverse process running the forward model multiple times to transfer information from indirect information to the target variable. MAD# uses two parallelization profiles according to computational resources available: one computer with multiple cores and multiple computers - multiple cores through HTCondor. HTCondor is a system that manages a cluster of desktop computers for submits serial or parallel jobs using scheduling policies, resources monitoring, job queuing mechanism. This poster will show how MAD# reduces the time execution of the characterization of random fields using these two parallel approaches in different case studies. A test of the approach was conducted using 1D problem with 400 cells to characterize saturated conductivity, residual water content, and shape parameters of the Mualem-van Genuchten model in four materials via the HYDRUS model. The number of simulations evaluated in the inversion was 10 million. Using the one computer approach (eight cores) were evaluated 100,000 simulations in 12 hours (10 million - 1200 hours approximately). In the evaluation on HTCondor, 32 desktop computers (132 cores) were used, with a processing time of 60 hours non-continuous in five days. HTCondor reduced the processing time for uncertainty characterization by a factor of 20 (1200 hours reduced to 60 hours.)
Ensemble unscented Kalman filter for state inference in continuous–discrete systems
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Bin Liu
2014-05-01
Full Text Available The authors consider non-linear state filtering problem in continuous–discrete systems, where the system dynamics is modelled by a stochastic differential equation, and noisy measurements of the system are obtained at discrete time instances. A novel particle method is proposed based on sequential importance sampling. This approach uses a bank of the continuous–discrete unscented Kalman filters (CDUKFs to obtain the importance proposal distribution, retaining the advantage of the CDUKF in continuous–discrete systems as well as the accuracy of particle filter in highly non-linear systems. Simulation results show that the algorithm outperforms some other benchmarks substantially in estimation accuracy.
Directory of Open Access Journals (Sweden)
Chunrong Mi
2017-01-01
Full Text Available Species distribution models (SDMs have become an essential tool in ecology, biogeography, evolution and, more recently, in conservation biology. How to generalize species distributions in large undersampled areas, especially with few samples, is a fundamental issue of SDMs. In order to explore this issue, we used the best available presence records for the Hooded Crane (Grus monacha, n = 33, White-naped Crane (Grus vipio, n = 40, and Black-necked Crane (Grus nigricollis, n = 75 in China as three case studies, employing four powerful and commonly used machine learning algorithms to map the breeding distributions of the three species: TreeNet (Stochastic Gradient Boosting, Boosted Regression Tree Model, Random Forest, CART (Classification and Regression Tree and Maxent (Maximum Entropy Models. In addition, we developed an ensemble forecast by averaging predicted probability of the above four models results. Commonly used model performance metrics (Area under ROC (AUC and true skill statistic (TSS were employed to evaluate model accuracy. The latest satellite tracking data and compiled literature data were used as two independent testing datasets to confront model predictions. We found Random Forest demonstrated the best performance for the most assessment method, provided a better model fit to the testing data, and achieved better species range maps for each crane species in undersampled areas. Random Forest has been generally available for more than 20 years and has been known to perform extremely well in ecological predictions. However, while increasingly on the rise, its potential is still widely underused in conservation, (spatial ecological applications and for inference. Our results show that it informs ecological and biogeographical theories as well as being suitable for conservation applications, specifically when the study area is undersampled. This method helps to save model-selection time and effort, and allows robust and rapid
Rijavec, Matija; Starcic Erjavec, Marjanca; Ambrozic Avgustin, Jerneja; Reissbrodt, Rolf; Fruth, Angelika; Krizan-Hergouth, Veronika; Zgur-Bertok, Darja
2006-08-01
One hundred and ten UTI Escherichia coli strains, from Ljubljana, Slovenia, were analyzed for antibiotic resistances, mobile DNA elements, serotype, and phylogenetic origin. A high prevalence of drug resistance and multidrug resistance was found. Twenty-six percent of the isolates harbored a class 1 integron, while a majority of the strains (56%) harbored rep sequences characteristic of F-like plasmids. int as well as rep sequences were found to be distributed in a random manner among strains of the four major phylogenetic groups indicating that all groups have a similar tendency to acquire and maintain mobile genetic elements frequently associated with resistance determinants.
Compressor Stability Enhancement Using Discrete Tip Injection
Suder, Kenneth L.; Hathaway, Michael D.; Thorp, Scott A.; Strazisar, Anthony J.; Bright, Michelle B.
2001-01-01
Mass injection upstream of the tip of a high-speed axial compressor rotor is a stability enhancement approach known to be effective in suppressing small in tip-critical rotors. This process is examined in a transonic axial compressor rotor through experiments and time-averaged Navier-Stokes CFD simulations. Measurements and simulations for discrete injection are presented for a range of injection rates and distributions of injectors around the annulus. The simulations indicate that tip injection increases stability by unloading the rotor tip and that increasing injection velocity improves the effectiveness of tip injection. For the tested rotor, experimental results demonstrate that at 70 percent speed the stalling flow coefficient can be reduced by 30 percent using an injected mass- flow equivalent to 1 percent of the annulus flow. At design speed, the stalling flow coefficient was reduced by 6 percent using an injected mass-fiow equivalent to 2 percent of the annulus flow. The experiments show that stability enhancement is related to the mass-averaged axial velocity at the tip. For a given injected mass-flow, the mass-averaged axial velocity at the tip is increased by injecting flow over discrete portions of the circumference as opposed to full-annular injection. The implications of these results on the design of recirculating casing treatments and other methods to enhance stability will be discussed.
Horstmann, Jan Tobias; Le Garrec, Thomas; Mincu, Daniel-Ciprian; Lévêque, Emmanuel
2017-11-01
Despite the efficiency and low dissipation of the stream-collide scheme of the discrete-velocity Boltzmann equation, which is nowadays implemented in many lattice Boltzmann solvers, a major drawback exists over alternative discretization schemes, i.e. finite-volume or finite-difference, that is the limitation to Cartesian uniform grids. In this paper, an algorithm is presented that combines the positive features of each scheme in a hybrid lattice Boltzmann method. In particular, the node-based streaming of the distribution functions is coupled with a second-order finite-volume discretization of the advection term of the Boltzmann equation under the Bhatnagar-Gross-Krook approximation. The algorithm is established on a multi-domain configuration, with the individual schemes being solved on separate sub-domains and connected by an overlapping interface of at least 2 grid cells. A critical parameter in the coupling is the CFL number equal to unity, which is imposed by the stream-collide algorithm. Nevertheless, a semi-implicit treatment of the collision term in the finite-volume formulation allows us to obtain a stable solution for this condition. The algorithm is validated in the scope of three different test cases on a 2D periodic mesh. It is shown that the accuracy of the combined discretization schemes agrees with the order of each separate scheme involved. The overall numerical error of the hybrid algorithm in the macroscopic quantities is contained between the error of the two individual algorithms. Finally, we demonstrate how such a coupling can be used to adapt to anisotropic flows with some gradual mesh refinement in the FV domain.
Vinkenoog, M.; van den Oever, M.C.; Uylings, H.B.M.; Wouterlood, F.G.
2005-01-01
We present a neuroanatomical tracing method in a stereological approach to study the proportional distribution of fibers of a particular projection over two chemically different populations of neurons. The fiber projection from the presubiculum to the medial division of the entorhinal cortex of the
Dry, Matthew J.; Preiss, Kym; Wagemans, Johan
2012-01-01
We investigated human performance on the Euclidean Traveling Salesperson Problem (TSP) and Euclidean Minimum Spanning Tree Problem (MST-P) in regards to a factor that has previously received little attention within the literature: the spatial distributions of TSP and MST-P stimuli. First, we describe a method for quantifying the relative degree of…
Relativity and the question of discretization in astronomy
Edelen, Dominic G B
1970-01-01
Theoretical researches in general relativity and observational data from galactic astronomy combine in this volume in contributions to one of the oldest questions of natural philosophy: Is the structure of the physical world more adequately described by a continuous or a discrete mode of representation? Since the days of the Pythagoreans, this question has surfaced from time to time in various guises in science as well as in philosophy. One of the most bitterly contested and illuminating controversies between the continuous and the discrete viewpoints is to be found in the wave versus corpuscular description of optical phenom enae. This controversy was not resolved to the satisfaction of most of its protaganists until the development of the quantum theory. However, several obscurities that still becloud the question suggest that some deeper formulation may be necessary before more satisfactory answers can be given 1. The firm establishment of the validity of quantized structure and discrete energy distribut...
A Discrete-Continuous Method of Mechanical System Modelling
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Hein Rafał
2017-04-01
Full Text Available The paper describes a discrete-continuous method of dynamic system modelling. The presented approach is hybrid in its nature, as it combines the advantages of spatial discretization methods with those of continuous system modelling methods. In the proposed method, a three-dimensional system is discretised in two directions only, with the third direction remaining continuous. The thus obtained discrete-continuous model is described by a set of coupled partial differential equations, derived using the rigid finite element method (RFEM. For this purpose, firstly the general differential equations are written. Then these equations are converted into difference equations. The derived equations, expressed in matrix form, allow to create a global matrix for the whole system. They are solved using the distributed transfer function method. The proposed approach is illustrated with the examples of a simple beam fixed at both ends and a simply supported plate.
Kokeny, Paul; Cheng, Yu-Chung N; Xie, He
2017-12-26
Modeling MRI signal behaviors in the presence of discrete magnetic particles is important, as magnetic particles appear in nanoparticle labeled cells, contrast agents, and other biological forms of iron. Currently, many models that take into account the discrete particle nature in a system have been used to predict magnitude signal decays in the form of R2* or R2' from one single voxel. Little work has been done for predicting phase signals. In addition, most calculations of phase signals rely on the assumption that a system containing discrete particles behaves as a continuous medium. In this work, numerical simulations are used to investigate MRI magnitude and phase signals from discrete particles, without diffusion effects. Factors such as particle size, number density, susceptibility, volume fraction, particle arrangements for their randomness, and field of view have been considered in simulations. The results are compared to either a ground truth model, theoretical work based on continuous mediums, or previous literature. Suitable parameters used to model particles in several voxels that lead to acceptable magnetic field distributions around particle surfaces and accurate MR signals are identified. The phase values as a function of echo time from a central voxel filled by particles can be significantly different from those of a continuous cubic medium. However, a completely random distribution of particles can lead to an R2' value which agrees with the prediction from the static dephasing theory. A sphere with a radius of at least 4 grid points used in simulations is found to be acceptable to generate MR signals equivalent from a larger sphere. Increasing number of particles with a fixed volume fraction in simulations reduces the resulting variance in the phase behavior, and converges to almost the same phase value for different particle numbers at each echo time. The variance of phase values is also reduced when increasing the number of particles in a fixed
Sui, Liansheng; Duan, Kuaikuai; Liang, Junli
2015-05-01
A new discrete fractional transform defined by the fractional order, periodicity and vector parameters is presented, which is named as the discrete multiple-parameter fractional angular transform. Based on this transform and two-coupled logistic map, a double-image encryption scheme is proposed. First, an enlarged image is obtained by connecting two plaintext images sequentially and scrambled by using a chaotic permutation process, in which the sequences of chaotic pairs generated by using the two-coupled logistic map. Then, the scrambled enlarged image is decomposed into two new components. Second, a chaotic random phase mask is generated based on the logistic map, with which one of two components is converted to the modulation phase mask. Another component is encoded into an interim matrix with the help of the modulation phase mask. Finally, the two-dimensional discrete multiple-parameter fractional angular transform is performed on the interim matrix to obtain the ciphertext with stationary white noise distribution. The proposed encryption scheme has an obvious advantage that no phase keys are used in the encryption and decryption process, which is convenient to key management. Moreover, the security of the cryptosystem can be enhanced by using extra parameters such as initial values of chaos functions, fractional orders and vector parameters of transform. Simulation results and security analysis verify the feasibility and effectiveness of the proposed scheme.
Nedorezov, Lev V; Löhr, Bernhard L; Sadykova, Dinara L
2008-10-07
The applicability of discrete mathematical models for the description of diamondback moth (DBM) (Plutella xylostella L.) population dynamics was investigated. The parameter values for several well-known discrete time models (Skellam, Moran-Ricker, Hassell, Maynard Smith-Slatkin, and discrete logistic models) were estimated for an experimental time series from a highland cabbage-growing area in eastern Kenya. For all sets of parameters, boundaries of confidence domains were determined. Maximum calculated birth rates varied between 1.086 and 1.359 when empirical values were used for parameter estimation. After fitting of the models to the empirical trajectory, all birth rate values resulted considerably higher (1.742-3.526). The carrying capacity was determined between 13.0 and 39.9DBM/plant, after fitting of the models these values declined to 6.48-9.3, all values well within the range encountered empirically. The application of the Durbin-Watson criteria for comparison of theoretical and experimental population trajectories produced negative correlations with all models. A test of residual value groupings for randomness showed that their distribution is non-stochastic. In consequence, we conclude that DBM dynamics cannot be explained as a result of intra-population self-regulative mechanisms only (=by any of the models tested) and that more comprehensive models are required for the explanation of DBM population dynamics.
Dynamic regimes of random fuzzy logic networks
Energy Technology Data Exchange (ETDEWEB)
Wittmann, Dominik M; Theis, Fabian J, E-mail: dominik.wittmann@helmholtz-muenchen.de [Computational Modeling in Biology, Institute for Bioinformatics and Systems Biology, Helmholtz Zentrum Muenchen-German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764 Munich-Neuherberg (Germany); Centre for Mathematical Sciences, Technische Universitaet Muenchen, Boltzmannstrasse 3, 85748 Garching (Germany)
2011-01-15
Random multistate networks, generalizations of the Boolean Kauffman networks, are generic models for complex systems of interacting agents. Depending on their mean connectivity, these networks exhibit ordered as well as chaotic behavior with a critical boundary separating both regimes. Typically, the nodes of these networks are assigned single discrete states. Here, we describe nodes by fuzzy numbers, i.e. vectors of degree-of-membership (DOM) functions specifying the degree to which the nodes are in each of their discrete states. This allows our models to deal with imprecision and uncertainties. Compatible update rules are constructed by expressing the update rules of the multistate network in terms of Boolean operators and generalizing them to fuzzy logic (FL) operators. The standard choice for these generalizations is the Goedel FL, where AND and OR are replaced by the minimum and maximum of two DOMs, respectively. In mean-field approximations we are able to analytically describe the percolation and asymptotic distribution of DOMs in random Goedel FL networks. This allows us to characterize the different dynamic regimes of random multistate networks in terms of FL. In a low-dimensional example, we provide explicit computations and validate our mean-field results by showing that they agree well with network simulations.
Dark energy from discrete spacetime.
Trout, Aaron D
2013-01-01
Dark energy accounts for most of the matter-energy content of our universe, yet current theories of its origin rely on radical physical assumptions such as the holographic principle or controversial anthropic arguments. We give a better motivated explanation for dark energy, claiming that it arises from a small negative scalar-curvature present even in empty spacetime. The vacuum has this curvature because spacetime is fundamentally discrete and there are more ways for a discrete geometry to have negative curvature than positive. We explicitly compute this effect using a variant of the well known dynamical-triangulations (DT) model for quantum gravity. Our model predicts a time-varying non-zero cosmological constant with a current value, [Formula: see text] in natural units, in agreement with observation. This calculation is made possible by a novel characterization of the possible DT action values combined with numerical evidence concerning their degeneracies.
Applied geometry and discrete mathematics
Sturm; Gritzmann, Peter; Sturmfels, Bernd
1991-01-01
This volume, published jointly with the Association for Computing Machinery, comprises a collection of research articles celebrating the occasion of Victor Klee's sixty-fifth birthday in September 1990. During his long career, Klee has made contributions to a wide variety of areas, such as discrete and computational geometry, convexity, combinatorics, graph theory, functional analysis, mathematical programming and optimization, and theoretical computer science. In addition, Klee made important contributions to mathematics education, mathematical methods in economics and the decision sciences, applications of discrete mathematics in the biological and social sciences, and the transfer of knowledge from applied mathematics to industry. In honor of Klee's achievements, this volume presents more than forty papers on topics related to Klee's research. While the majority of the papers are research articles, a number of survey articles are also included. Mirroring the breadth of Klee's mathematical contributions, th...
Discrete mathematics using a computer
Hall, Cordelia
2000-01-01
Several areas of mathematics find application throughout computer science, and all students of computer science need a practical working understanding of them. These core subjects are centred on logic, sets, recursion, induction, relations and functions. The material is often called discrete mathematics, to distinguish it from the traditional topics of continuous mathematics such as integration and differential equations. The central theme of this book is the connection between computing and discrete mathematics. This connection is useful in both directions: • Mathematics is used in many branches of computer science, in applica tions including program specification, datastructures,design and analysis of algorithms, database systems, hardware design, reasoning about the correctness of implementations, and much more; • Computers can help to make the mathematics easier to learn and use, by making mathematical terms executable, making abstract concepts more concrete, and through the use of software tools su...
Discrete symmetries in the MSSM
Energy Technology Data Exchange (ETDEWEB)
Schieren, Roland
2010-12-02
The use of discrete symmetries, especially abelian ones, in physics beyond the standard model of particle physics is discussed. A method is developed how a general, abelian, discrete symmetry can be obtained via spontaneous symmetry breaking. In addition, anomalies are treated in the path integral approach with special attention to anomaly cancellation via the Green-Schwarz mechanism. All this is applied to the minimal supersymmetric standard model. A unique Z{sup R}{sub 4} symmetry is discovered which solves the {mu}-problem as well as problems with proton decay and allows to embed the standard model gauge group into a simple group, i.e. the Z{sup R}{sub 4} is compatible with grand unification. Also the flavor problem in the context of minimal flavor violation is addressed. Finally, a string theory model is presented which exhibits the mentioned Z{sup R}{sub 4} symmetry and other desirable features. (orig.)
Dark energy from discrete spacetime.
Directory of Open Access Journals (Sweden)
Aaron D Trout
Full Text Available Dark energy accounts for most of the matter-energy content of our universe, yet current theories of its origin rely on radical physical assumptions such as the holographic principle or controversial anthropic arguments. We give a better motivated explanation for dark energy, claiming that it arises from a small negative scalar-curvature present even in empty spacetime. The vacuum has this curvature because spacetime is fundamentally discrete and there are more ways for a discrete geometry to have negative curvature than positive. We explicitly compute this effect using a variant of the well known dynamical-triangulations (DT model for quantum gravity. Our model predicts a time-varying non-zero cosmological constant with a current value, [Formula: see text] in natural units, in agreement with observation. This calculation is made possible by a novel characterization of the possible DT action values combined with numerical evidence concerning their degeneracies.
Aggregation patterns from nonlocal interactions: Discrete stochastic and continuum modeling
Hackett-Jones, Emily J.
2012-04-17
Conservation equations governed by a nonlocal interaction potential generate aggregates from an initial uniform distribution of particles. We address the evolution and formation of these aggregating steady states when the interaction potential has both attractive and repulsive singularities. Currently, no existence theory for such potentials is available. We develop and compare two complementary solution methods, a continuous pseudoinverse method and a discrete stochastic lattice approach, and formally show a connection between the two. Interesting aggregation patterns involving multiple peaks for a simple doubly singular attractive-repulsive potential are determined. For a swarming Morse potential, characteristic slow-fast dynamics in the scaled inverse energy is observed in the evolution to steady state in both the continuous and discrete approaches. The discrete approach is found to be remarkably robust to modifications in movement rules, related to the potential function. The comparable evolution dynamics and steady states of the discrete model with the continuum model suggest that the discrete stochastic approach is a promising way of probing aggregation patterns arising from two- and three-dimensional nonlocal interaction conservation equations. © 2012 American Physical Society.
Observability of discretized partial differential equations
Cohn, Stephen E.; Dee, Dick P.
1988-01-01
It is shown that complete observability of the discrete model used to assimilate data from a linear partial differential equation (PDE) system is necessary and sufficient for asymptotic stability of the data assimilation process. The observability theory for discrete systems is reviewed and applied to obtain simple observability tests for discretized constant-coefficient PDEs. Examples are used to show how numerical dispersion can result in discrete dynamics with multiple eigenvalues, thereby detracting from observability.
Discrete element modelling of pebble packing in pebble bed reactors
Energy Technology Data Exchange (ETDEWEB)
Suikkanen, Heikki, E-mail: heikki.suikkanen@lut.fi; Ritvanen, Jouni, E-mail: jouni.ritvanen@lut.fi; Jalali, Payman, E-mail: payman.jalali@lut.fi; Kyrki-Rajamäki, Riitta, E-mail: riitta.kyrki-rajamaki@lut.fi
2014-07-01
Highlights: • A discrete element method code is developed for pebble bed reactor analyses. • Methods are established to extract packing information at various spatial scales. • Packing simulations inside annular core geometry are done varying input parameters. • The restitution coefficient has the strongest effect on the resulting packing density. • Detailed analyses reveal local densification especially near the walls. - Abstract: It is important to understand the packing characteristics and behaviour of the randomly packed pebble bed to further analyse the reactor physical and thermal-hydraulic behaviour and to design a safe and economically feasible pebble bed reactor. The objective of this work was to establish methods to model and analyse the pebble packing in detail to provide useful tools and data for further analyses. Discrete element method (DEM) is a well acknowledged method for analysing granular materials, such as the fuel pebbles in a pebble bed reactor. In this work, a DEM computer code was written specifically for pebble bed analyses. Analysis methods were established to extract data at various spatial scales from the pebble beds resulting from the DEM simulations. A comparison with available experimental data was performed to validate the DEM implementation. To test the code implementation in full-scale reactor calculations, DEM packing simulations were done in annular geometry with 450,000 pebbles. Effects of the initial packing configuration, friction and restitution coefficients and pebble size distribution to the resulting pebble bed were investigated. The packing simulations revealed that from the investigated parameters the restitution coefficient had the largest effect on the resulting average packing density while other parameters had smaller effects. Detailed local packing density analysis of pebble beds with different average densities revealed local variations especially strong in the regions near the walls. The implemented DEM
Seçgin, Abdullah; Saide Sarıgül, A.
2009-03-01
This study introduces a novel scheme for the discrete high-frequency forced vibration analysis based on discrete singular convolution (DSC) and mode superposition (MS) approaches. The accuracy of the DSC-MS is validated for thin beams and plates by comparing with available analytical solutions. The performance of the DSC-MS is evaluated by predicting spatial distribution and discrete frequency spectra of the vibration response of thin plates with two different boundary conditions. The frequency spectra of the time-harmonic excitation forces are in the form of ideal and band-limited white noise so that the natural modes in the frequency band are provoked. The solution exposes high-frequency response behaviour definitely. Therefore, it is hoped with this paper to contribute the studies on the treatment of uncertainties in the high-frequency design applications.
Pischedda, Alison; Friberg, Urban; Stewart, Andrew D; Miller, Paige M; Rice, William R
2015-10-01
The effective population size (N(e)) is a fundamental parameter in population genetics that influences the rate of loss of genetic diversity. Sexual selection has the potential to reduce N(e) by causing the sex-specific distributions of individuals that successfully reproduce to diverge. To empirically estimate the effect of sexual selection on N(e), we obtained fitness distributions for males and females from an outbred, laboratory-adapted population of Drosophila melanogaster. We observed strong sexual selection in this population (the variance in male reproductive success was ∼14 times higher than that for females), but found that sexual selection had only a modest effect on N(e), which was 75% of the census size. This occurs because the substantial random offspring mortality in this population diminishes the effects of sexual selection on N(e), a result that necessarily applies to other high fecundity species. The inclusion of this random offspring mortality creates a scaling effect that reduces the variance/mean ratios for male and female reproductive success and causes them to converge. Our results demonstrate that measuring reproductive success without considering offspring mortality can underestimate Ne and overestimate the genetic consequences of sexual selection. Similarly, comparing genetic diversity among different genomic components may fail to detect strong sexual selection. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.
Jin, Xiaoxi; Du, Xueyuan; Wang, Xiong; Zhou, Pu; Zhang, Hanwei; Wang, Xiaolin; Liu, Zejin
2016-07-15
We demonstrated a high-power ultralong-wavelength Tm-doped silica fiber laser operating at 2153 nm with the output power exceeding 18 W and the slope efficiency of 25.5%. A random distributed feedback fiber laser with the center wavelength of 1173 nm was employed as pump source of Tm-doped fiber laser for the first time. No amplified spontaneous emissions or parasitic oscillations were observed when the maximum output power reached, which indicates that employing 1173 nm random distributed feedback fiber laser as pump laser is a feasible and promising scheme to achieve high-power emission of long-wavelength Tm-doped fiber laser. The output power of this Tm-doped fiber laser could be further improved by optimizing the length of active fiber, reflectivity of FBGs, increasing optical efficiency of pump laser and using better temperature management. We also compared the operation of 2153 nm Tm-doped fiber lasers pumped with 793 nm laser diodes, and the maximum output powers were limited to ~2 W by strong amplified spontaneous emission and parasitic oscillation in the range of 1900-2000 nm.
Energy Technology Data Exchange (ETDEWEB)
Dotsenko, Viktor S [Landau Institute for Theoretical Physics, Russian Academy of Sciences, Moscow (Russian Federation)
2011-03-31
In the last two decades, it has been established that a single universal probability distribution function, known as the Tracy-Widom (TW) distribution, in many cases provides a macroscopic-level description of the statistical properties of microscopically different systems, including both purely mathematical ones, such as increasing subsequences in random permutations, and quite physical ones, such as directed polymers in random media or polynuclear crystal growth. In the first part of this review, we use a number of models to examine this phenomenon at a simple qualitative level and then consider the exact solution for one-dimensional directed polymers in a random environment, showing that free energy fluctuations in such a system are described by the universal TW distribution. The second part provides detailed appendix material containing the necessary mathematical background for the first part. (reviews of topical problems)
Cuspidal discrete series for projective hyperbolic spaces
DEFF Research Database (Denmark)
Andersen, Nils Byrial; Flensted-Jensen, Mogens
2013-01-01
Abstract. We have in [1] proposed a definition of cusp forms on semisimple symmetric spaces G/H, involving the notion of a Radon transform and a related Abel transform. For the real non-Riemannian hyperbolic spaces, we showed that there exists an infinite number of cuspidal discrete series......, and at most finitely many non-cuspidal discrete series, including in particular the spherical discrete series. For the projective spaces, the spherical discrete series are the only non-cuspidal discrete series. Below, we extend these results to the other hyperbolic spaces, and we also study the question...
Feikin, Daniel R.; Bigogo, Godfrey; Audi, Allan; Pals, Sherri L.; Aol, George; Mbakaya, Charles; Williamson, John; Breiman, Robert F.; Larson, Charles P.
2014-01-01
Background Zinc treatment shortens diarrhea episodes and can prevent future episodes. In rural Africa, most children with diarrhea are not brought to health facilities. In a village-randomized trial in rural Kenya, we assessed if zinc treatment might have a community-level preventive effect on diarrhea incidence if available at home versus only at health facilities. Methods We randomized 16 Kenyan villages (1,903 eligible children) to receive a 10-day course of zinc and two oral rehydration solution (ORS) sachets every two months at home and 17 villages (2,241 eligible children) to receive ORS at home, but zinc at the health–facility only. Children’s caretakers were educated in zinc/ORS use by village workers, both unblinded to intervention arm. We evaluated whether incidence of diarrhea and acute lower respiratory illness (ALRI) reported at biweekly home visits and presenting to clinic were lower in zinc villages, using poisson regression adjusting for baseline disease rates, distance to clinic, and children’s age. Results There were no differences between village groups in diarrhea incidence either reported at the home or presenting to clinic. In zinc villages (1,440 children analyzed), 61.2% of diarrheal episodes were treated with zinc, compared to 5.4% in comparison villages (1,584 children analyzed, p<0.0001). There were no differences in ORS use between zinc (59.6%) and comparison villages (58.8%). Among children with fever or cough without diarrhea, zinc use was low (<0.5%). There was a lower incidence of reported ALRI in zinc villages (adjusted RR 0.68, 95% CI 0.46–0.99), but not presenting at clinic. Conclusions In this study, home zinc use to treat diarrhea did not decrease disease rates in the community. However, with proper training, availability of zinc at home could lead to more episodes of pediatric diarrhea being treated with zinc in parts of rural Africa where healthcare utilization is low. Trial Registration ClinicalTrials.gov NCT00530829
Directory of Open Access Journals (Sweden)
Daniel R Feikin
Full Text Available BACKGROUND: Zinc treatment shortens diarrhea episodes and can prevent future episodes. In rural Africa, most children with diarrhea are not brought to health facilities. In a village-randomized trial in rural Kenya, we assessed if zinc treatment might have a community-level preventive effect on diarrhea incidence if available at home versus only at health facilities. METHODS: We randomized 16 Kenyan villages (1,903 eligible children to receive a 10-day course of zinc and two oral rehydration solution (ORS sachets every two months at home and 17 villages (2,241 eligible children to receive ORS at home, but zinc at the health-facility only. Children's caretakers were educated in zinc/ORS use by village workers, both unblinded to intervention arm. We evaluated whether incidence of diarrhea and acute lower respiratory illness (ALRI reported at biweekly home visits and presenting to clinic were lower in zinc villages, using poisson regression adjusting for baseline disease rates, distance to clinic, and children's age. RESULTS: There were no differences between village groups in diarrhea incidence either reported at the home or presenting to clinic. In zinc villages (1,440 children analyzed, 61.2% of diarrheal episodes were treated with zinc, compared to 5.4% in comparison villages (1,584 children analyzed, p<0.0001. There were no differences in ORS use between zinc (59.6% and comparison villages (58.8%. Among children with fever or cough without diarrhea, zinc use was low (<0.5%. There was a lower incidence of reported ALRI in zinc villages (adjusted RR 0.68, 95% CI 0.46-0.99, but not presenting at clinic. CONCLUSIONS: In this study, home zinc use to treat diarrhea did not decrease disease rates in the community. However, with proper training, availability of zinc at home could lead to more episodes of pediatric diarrhea being treated with zinc in parts of rural Africa where healthcare utilization is low. TRIAL REGISTRATION: ClinicalTrials.gov NCT
Students' Misconceptions about Random Variables
Kachapova, Farida; Kachapov, Ilias
2012-01-01
This article describes some misconceptions about random variables and related counter-examples, and makes suggestions about teaching initial topics on random variables in general form instead of doing it separately for discrete and continuous cases. The focus is on post-calculus probability courses. (Contains 2 figures.)
Videla Giering, Y. A., III; McPhee, J. P.
2015-12-01
Snow hydrology in mountain environments plays an important role in the availability of hydrological resources in warm climate areas and height effects, since the magnitude of snowpack, its spatial and temporal distribution is very important to determine the availability of water in the snowmelt season and take forward different productive activities This investigation models and assess the main phenomena hydrological cycle of snow using the software Cold Region Hydrological Model (Pomeroy et al., 2007). The software is a physically based model developed by the centre for hydrology, University of Saskatchewan. The aim of this model is to have a better understanding of hydrological processes involved in cold environments, which are particular in the sense that a host of specific phenomena such as snow and ice accumulation, transport and melt, infiltration through frozen soils, and the like, control the hydrograph timing) The analysis involved the development of a hydrologic model for the Upper Maipo River Basin, with elevations between 800 and 6500 meters above sea level and 5000-km^2 watershed in the Andes of Central Chile which supplies water resources to the capital city of Santiago (7 million inhabitants), to a thriving agricultural region, as well as to hydropower and large mining activities. The paper concludes that there is a differential distribution of snow cover in the study area, determined mainly by steep terrain geomorphology. These factors have been considered in the parameterization of the model, showing considerable variation in storage time, redistributions by blowing snow, melting intervals, infiltration rates and drainage basin. The fictional scenarios modeled demonstrate noticeable changes in the hydrograph, showing the fragile climate and hydrological condition of this basin of Central Chile.
On the Fractional Poisson Process and the Discretized Stable Subordinator
Directory of Open Access Journals (Sweden)
Rudolf Gorenflo
2015-08-01
Full Text Available We consider the renewal counting number process N = N(t as a forward march over the non-negative integers with independent identically distributed waiting times. We embed the values of the counting numbers N in a “pseudo-spatial” non-negative half-line x ≥ 0 and observe that for physical time likewise we have t ≥ 0. Thus we apply the Laplace transform with respect to both variables x and t. Applying then a modification of the Montroll-Weiss-Cox formalism of continuous time random walk we obtain the essential characteristics of a renewal process in the transform domain and, if we are lucky, also in the physical domain. The process t = t(N of accumulation of waiting times is inverse to the counting number process, in honour of the Danish mathematician and telecommunication engineer A.K. Erlang we call it the Erlang process. It yields the probability of exactly n renewal events in the interval (0; t]. We apply our Laplace-Laplace formalism to the fractional Poisson process whose waiting times are of Mittag-Leffler type and to a renewal process whose waiting times are of Wright type. The process of Mittag-Leffler type includes as a limiting case the classical Poisson process, the process of Wright type represents the discretized stable subordinator and a re-scaled version of it was used in our method of parametric subordination of time-space fractional diffusion processes. Properly rescaling the counting number process N(t and the Erlang process t(N yields as diffusion limits the inverse stable and the stable subordinator, respectively.
Domain Discretization and Circle Packings
DEFF Research Database (Denmark)
Dias, Kealey
, and the edges are geodesic segments (Euclidean, hyperbolic, or spherical) connecting centers of circles that are tangent to each other. Three circles that are mutually tangent form a face of the triangulation. Since circle packing is closely related to triangulation, circle packing methods can be applied...... to domain discretization problems such as triangulation and unstructured mesh generation techniques. We wish to ask ourselves the question: given a cloud of points in the plane (we restrict ourselves to planar domains), is it possible to construct a circle packing preserving the positions of the vertices...
Discrete geometric structures for architecture
Pottmann, Helmut
2010-06-13
The emergence of freeform structures in contemporary architecture raises numerous challenging research problems, most of which are related to the actual fabrication and are a rich source of research topics in geometry and geometric computing. The talk will provide an overview of recent progress in this field, with a particular focus on discrete geometric structures. Most of these result from practical requirements on segmenting a freeform shape into planar panels and on the physical realization of supporting beams and nodes. A study of quadrilateral meshes with planar faces reveals beautiful relations to discrete differential geometry. In particular, we discuss meshes which discretize the network of principal curvature lines. Conical meshes are among these meshes; they possess conical offset meshes at a constant face/face distance, which in turn leads to a supporting beam layout with so-called torsion free nodes. This work can be generalized to a variety of multilayer structures and laid the ground for an adapted curvature theory for these meshes. There are also efforts on segmenting surfaces into planar hexagonal panels. Though these are less constrained than planar quadrilateral panels, this problem is still waiting for an elegant solution. Inspired by freeform designs in architecture which involve circles and spheres, we present a new kind of triangle mesh whose faces\\' in-circles form a packing, i.e., the in-circles of two triangles with a common edge have the same contact point on that edge. These "circle packing (CP) meshes" exhibit an aesthetic balance of shape and size of their faces. They are closely tied to sphere packings on surfaces and to various remarkable structures and patterns which are of interest in art, architecture, and design. CP meshes constitute a new link between architectural freeform design and computational conformal geometry. Recently, certain timber structures motivated us to study discrete patterns of geodesics on surfaces. This
Radiative transfer on discrete spaces
Preisendorfer, Rudolph W; Stark, M; Ulam, S
1965-01-01
Pure and Applied Mathematics, Volume 74: Radiative Transfer on Discrete Spaces presents the geometrical structure of natural light fields. This book describes in detail with mathematical precision the radiometric interactions of light-scattering media in terms of a few well established principles.Organized into four parts encompassing 15 chapters, this volume begins with an overview of the derivations of the practical formulas and the arrangement of formulas leading to numerical solution procedures of radiative transfer problems in plane-parallel media. This text then constructs radiative tran
Li, Jin; Tran, Maggie; Siwabessy, Justy
2016-01-01
Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia’s marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70). We developed optimal predictive models to predict seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), knowledge informed AVI (KIAVI), Boruta and regularized RF (RRF) were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness of four classes can be predicted with a high degree of accuracy; 3) the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5) FS methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to ‘small p and large n’ problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and
Directory of Open Access Journals (Sweden)
Jin Li
Full Text Available Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia's marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70. We developed optimal predictive models to predict seabed hardness using random forest (RF based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS methods that are variable importance (VI, averaged variable importance (AVI, knowledge informed AVI (KIAVI, Boruta and regularized RF (RRF were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1 hard90 and hard70 are effective seabed hardness classification schemes; 2 seabed hardness of four classes can be predicted with a high degree of accuracy; 3 the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4 the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5 FS methods select the most accurate predictive model(s instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6 RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to 'small p and large n' problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and
On statistical indistinguishability of complete and incomplete discrete time market models
Nikolai Dokuchaev
2015-01-01
We investigate the possibility of statistical evaluation of the market completeness for discrete time stock market models. It is known that the market completeness is not a robust property: small random deviations of the coefficients convert a complete market model into a incomplete one. The paper shows that market incompleteness is also non-robust. We show that, for any incomplete market from a wide class of discrete time models, there exists a complete market model with arbitrarily close st...
Moreau, Jacqueline F; Buchanich, Jeanine M; Geskin, Jacob Z; Akilov, Oleg E; Geskin, Larisa J
2014-07-15
Environmental hazards may play a role in the etiology of cutaneous T-cell lymphoma (CTCL). Some studies have found an increased incidence of CTCL among workers in chemical science, transportation, and manufacturing industries, but other studies have not. This discrepancy may be attributable to population migration, complicating accurate assessment of lifetime exposures. The Pittsburgh population has very low migration rates and most CTCL patients seen at the University of Pittsburgh Medical Center (UPMC) Cutaneous Lymphoma Center are life-long local residents. The Greater Pittsburgh Area used to be an industrial hub. There are residential communities positioned within close proximity to inactive industrial sites that continue to contain pollutants. To determine whether CTCL patients' residences cluster within specific Pittsburgh regions, in particular, those with high levels of environmental pollutants. Our study included patients diagnosed with CTCL at the UPMC Cutaneous Lymphoma Center between 2000 and 2012. We mapped the longitudinal and latitudinal coordinates of patients' residences at diagnosis, superfund sites, toxic release inventory sites, particular matter levels, and dermatologists' offices using ArcMap 10.1. We then performed a SaTScan analysis using zip codes to assess for geographic clustering of patients' residences in the Pittsburgh metropolitan statistical area. We assessed for a correlation between case distribution and both environmental hazards sites and dermatologist density in the area. We identified 274 patients with CTCL in the Greater Pittsburgh area. We identified a statistically significant geographic cluster (pPittsburgh and the site of the region's only CTCL clinic. We observed no relationship between the locations of superfund sites, toxic release inventory sites, or particular matter levels and CTCL case distribution. Our findings do not support an association between exposure to environmental toxins and CTCL. CTCL cases clustered in
Multiple Scattering of Waves in Discrete Random Media.
1987-12-31
chiral inclusions themselves made up of microminiature helices suspended in some other, or the same, host medium. As a wave traverses such a composite...compuietvedrs functio fo fequ omoen forb ledt[ proiaearemn]ih.h esre auso Fe~ artcls dsprse i aPVCmarix Te delcti agn r e art [2]fo the dicpoite propties
OCT Amplitude and Speckle Statistics of Discrete Random Media
Almasian, Mitra; van Leeuwen, Ton G.; Faber, Dirk J.
2017-01-01
Speckle, amplitude fluctuations in optical coherence tomography (OCT) images, contains information on sub-resolution structural properties of the imaged sample. Speckle statistics could therefore be utilized in the characterization of biological tissues. However, a rigorous theoretical framework
Imaging Through Random Discrete-Scatterer Dispersive Media
2015-08-27
positive-frequency autocorrelation function also known as the point-spread function (PSF): χF (t− 2 r0/c) = ∫ ∞ −∞ ds F ′A(s)F ∗(s− t) = ∫ ∞ −∞ ds FA(s− 2r0...important tool in characterizing waveforms is the time-frequency autocorrelation function or the ambiguity function (AF) [12], [13], [7]. Following the...carrier wavelength λ0 = 0.633µm (the red-light HeNe laser ). Then the carrier frequency and its spread are ν0 = ω0 2π ≈ 474 THz = 4.74 · 1014 Hz , ∆ νD
Garboś, Sławomir; Święcicka, Dorota
2015-11-01
The random daytime (RDT) sampling method was used for the first time in the assessment of average weekly exposure to uranium through drinking water in a large water supply zone. Data set of uranium concentrations determined in 106 RDT samples collected in three runs from the water supply zone in Wroclaw (Poland), cannot be simply described by normal or log-normal distributions. Therefore, a numerical method designed for the detection and calculation of bimodal distribution was applied. The extracted two distributions containing data from the summer season of 2011 and the winter season of 2012 (nI=72) and from the summer season of 2013 (nII=34) allowed to estimate means of U concentrations in drinking water: 0.947 μg/L and 1.23 μg/L, respectively. As the removal efficiency of uranium during applied treatment process is negligible, the effect of increase in uranium concentration can be explained by higher U concentration in the surface-infiltration water used for the production of drinking water. During the summer season of 2013, heavy rains were observed in Lower Silesia region, causing floods over the territory of the entire region. Fluctuations in uranium concentrations in surface-infiltration water can be attributed to releases of uranium from specific sources - migration from phosphate fertilizers and leaching from mineral deposits. Thus, exposure to uranium through drinking water may increase during extreme rainfall events. The average chronic weekly intakes of uranium through drinking water, estimated on the basis of central values of the extracted normal distributions, accounted for 3.2% and 4.1% of tolerable weekly intake. Copyright © 2015 Elsevier Ltd. All rights reserved.
Grabsch, Aurélien; Texier, Christophe
2016-11-01
An invariant ensemble of N × N random matrices can be characterised by a joint distribution for eigenvalues P({λ }1,\\cdots ,{λ }N). The distribution of linear statistics, i.e. of quantities of the form L=(1/N){\\sum }if({λ }i) where f(x) is a given function, appears in many physical problems. In the N\\to ∞ limit, L scales as L˜ {N}η , where the scaling exponent η depends on the ensemble and the function f(x). Its distribution can be written in the form {P}N(s={N}-η L)≃ {A}N,β (s)\\exp \\{-(β {N}2/2){{Φ }}(s)\\}, where β \\in \\{1,2,4\\} is the Dyson index. The Coulomb gas technique naturally provides the large deviation function {{Φ }}(s), which can be efficiently obtained thanks to a ‘thermodynamic identity’ introduced earlier. We conjecture the pre-exponential function {A}N,β (s). We check our conjecture on several well controlled cases within the Laguerre and the Jacobi ensembles. Then we apply our main result to a situation where the large deviation function has no minimum (and L has infinite moments): this arises in the statistical analysis of the Wigner time delay for semi-infinite multichannel disordered wires (Laguerre ensemble). The statistical analysis of the Wigner time delay then crucially depends on the pre-exponential function {A}N,β (s), which ensures the decay of the distribution for large argument.
A non-linear discrete transform for pattern recognition of discrete chaotic systems
Karanikas, C
2003-01-01
It is shown, by an invertible non-linear discrete transform that any finite sequence or any collection of strings of any length can be presented as a random walk on trees. These transforms create the mathematical background for coding any information, for exploring its local variability and diversity. With the underlying computational algorithms, with several examples and applications we propose that these transforms can be used for pattern recognition of immune type. In other words we propose a mathematical platform for detecting self and non-self strings of any alphabet, based on a negative selection algorithms, for scouting data's periodicity and self-similarity and for measuring the diversity of chaotic strings with fractal dimension methods. In particular we estimate successfully the entropy and the ratio of chaotic data with self similarity. Moreover we give some applications of a non-linear denoising filter.
Distributed Convergence to Nash Equilibria in Two-Network Zero-Sum Games
2013-02-17
convergence of discrete-time subgradient dy- namics to a saddle point. Continuous-time best-response dynamics for zero-sum games converges to the set of...convexity-concavity assumptions, continuous-time subgradient flow dynam- ics converges to a saddle point (Arrow et al., 1951, 1958). Asymptotic convergence...and M. Johansson. A random- ized incremental subgradient method for distributed optimization in networked systems. SIAM Journal on Control and
On the putative essential discreteness of q-generalized entropies
Plastino, A.; Rocca, M. C.
2017-12-01
It has been argued in Abe (2010), entitled Essential discreteness in generalized thermostatistics with non-logarithmic entropy, that ;continuous Hamiltonian systems with long-range interactions and the so-called q-Gaussian momentum distributions are seen to be outside the scope of non-extensive statistical mechanics;. The arguments are clever and appealing. We show here that, however, some mathematical subtleties render them unconvincing.
Multifractal analysis of time series generated by discrete Ito equations
Telesca, Luciano; Czechowski, Zbigniew; Lovallo, Michele
2015-06-01
In this study, we show that discrete Ito equations with short-tail Gaussian marginal distribution function generate multifractal time series. The multifractality is due to the nonlinear correlations, which are hidden in Markov processes and are generated by the interrelation between the drift and the multiplicative stochastic forces in the Ito equation. A link between the range of the generalized Hurst exponents and the mean of the squares of all averaged net forces is suggested.
A note on identification in discrete choice models with partial observability
DEFF Research Database (Denmark)
Fosgerau, Mogens; Ranjan, Abhishek
2017-01-01
This note establishes a new identification result for additive random utility discrete choice models. A decision-maker associates a random utility Uj+ mj to each alternative in a finite set j∈ {1 , … , J} , where U= {U1, … , UJ} is unobserved by the researcher and random with an unknown joint dis...... for applications where choices are observed aggregated into groups while prices and attributes vary at the level of individual alternatives....
Problem of uniqueness in the renewal process generated by the uniform distribution
Directory of Open Access Journals (Sweden)
D. Ugrin-parac
1992-01-01
Full Text Available The renewal process generated by the uniform distribution, when interpreted as a transformation of the uniform distribution into a discrete distribution, gives rise to the question of uniqueness of the inverse image. The paper deals with a particular problem from the described domain, that arose in the construction of a complex stochastic test intended to evaluate pseudo-random number generators. The connection of the treated problem with the question of a unique integral representation of Gamma-function is also mentioned.
Quantum evolution by discrete measurements
Energy Technology Data Exchange (ETDEWEB)
Roa, L [Center for Quantum Optics and Quantum Information, Departamento de Fisica, Universidad de Concepcion, Casilla 160-C, Concepcion (Chile); Guevara, M L Ladron de [Departamento de Fisica, Universidad Catolica del Norte, Casilla 1280, Antofagasta (Chile); Delgado, A [Center for Quantum Optics and Quantum Information, Departamento de Fisica, Universidad de Concepcion, Casilla 160-C, Concepcion (Chile); Olivares-RenterIa, G [Center for Quantum Optics and Quantum Information, Departamento de Fisica, Universidad de Concepcion, Casilla 160-C, Concepcion (Chile); Klimov, A B [Departamento de Fisica, Universidad de Guadalajara, Revolucion 1500, 44420 Guadalajara, Jalisco (Mexico)
2007-10-15
In this article we review two ways of driving a quantum system to a known pure state via a sequence discrete of von Neumann measurements. The first of them assumes that the initial state of the system is unknown, and the evolution is attained only with the help of two non-commuting observables. For this method, the overall success probability is maximized when the eigentstates of the involved observables constitute mutually unbiased bases. The second method assumes the initial state is known and it uses N observables which are consecutively measured to make the state of the system approach the target state. The probability of success of this procedure converges to 1 as the number of observables increases.
Discrete calculus methods for counting
Mariconda, Carlo
2016-01-01
This book provides an introduction to combinatorics, finite calculus, formal series, recurrences, and approximations of sums. Readers will find not only coverage of the basic elements of the subjects but also deep insights into a range of less common topics rarely considered within a single book, such as counting with occupancy constraints, a clear distinction between algebraic and analytical properties of formal power series, an introduction to discrete dynamical systems with a thorough description of Sarkovskii’s theorem, symbolic calculus, and a complete description of the Euler-Maclaurin formulas and their applications. Although several books touch on one or more of these aspects, precious few cover all of them. The authors, both pure mathematicians, have attempted to develop methods that will allow the student to formulate a given problem in a precise mathematical framework. The aim is to equip readers with a sound strategy for classifying and solving problems by pursuing a mathematically rigorous yet ...
Discrete modelling of drapery systems
Thoeni, Klaus; Giacomini, Anna
2016-04-01
Drapery systems are an efficient and cost-effective measure in preventing and controlling rockfall hazards on rock slopes. The simplest form consists of a row of ground anchors along the top of the slope connected to a horizontal support cable from which a wire mesh is suspended down the face of the slope. Such systems are generally referred to as simple or unsecured draperies (Badger and Duffy 2012). Variations such as secured draperies, where a pattern of ground anchors is incorporated within the field of the mesh, and hybrid systems, where the upper part of an unsecured drapery is elevated to intercept rockfalls originating upslope of the installation, are becoming more and more popular. This work presents a discrete element framework for simulation of unsecured drapery systems and its variations. The numerical model is based on the classical discrete element method (DEM) and implemented into the open-source framework YADE (Šmilauer et al., 2010). The model takes all relevant interactions between block, drapery and slope into account (Thoeni et al., 2014) and was calibrated and validated based on full-scale experiments (Giacomini et al., 2012).The block is modelled as a rigid clump made of spherical particles which allows any shape to be approximated. The drapery is represented by a set of spherical particle with remote interactions. The behaviour of the remote interactions is governed by the constitutive behaviour of the wire and generally corresponds to a piecewise linear stress-strain relation (Thoeni et al., 2013). The same concept is used to model wire ropes. The rock slope is represented by rigid triangular elements where material properties (e.g., normal coefficient of restitution, friction angle) are assigned to each triangle. The capabilities of the developed model to simulate drapery systems and estimate the residual hazard involved with such systems is shown. References Badger, T.C., Duffy, J.D. (2012) Drapery systems. In: Turner, A.K., Schuster R
Modeling discrete competitive facility location
Karakitsiou, Athanasia
2015-01-01
This book presents an up-to-date review of modeling and optimization approaches for location problems along with a new bi-level programming methodology which captures the effect of competition of both producers and customers on facility location decisions. While many optimization approaches simplify location problems by assuming decision making in isolation, this monograph focuses on models which take into account the competitive environment in which such decisions are made. New insights in modeling, algorithmic and theoretical possibilities are opened by this approach and new applications are possible. Competition on equal term plus competition between market leader and followers are considered in this study, consequently bi-level optimization methodology is emphasized and further developed. This book provides insights regarding modeling complexity and algorithmic approaches to discrete competitive location problems. In traditional location modeling, assignment of customer demands to supply sources are made ...
A Discrete Modeling Approach for Buck Converter
Zhaoxia, Leng; Qingfeng, Liu; Jinkun, Sun; Huamin, Wang
In this paper, a discrete modeling approach for Buck converters based on continuous condition mode (CCM) and discontinuous condition mode (DCM) was presented. The unified coefficient matrixes of discrete model were described by building a mathematical function and the calculation methods of the parameters in coefficient matrixes were given. The working states of Buck converter on various work conditions were described adopting one discrete equation. The validity of the proposed modeling approach was proved by contrasting the output of discrete model with the operation result of Buck converter system in Simulink.
DEFF Research Database (Denmark)
Batley, Richard; Ibáñez Rivas, Juan Nicolás
2013-01-01
The apparatus of the Random Utility Model (RUM) first emerged in the early 1960s, with Marschak (1960) and Block and Marschak (1960) translating models originally developed for discriminant analysis in psychophysics (Thurstone, 1927) to the alternative domain of discrete choice analysis in econom......The apparatus of the Random Utility Model (RUM) first emerged in the early 1960s, with Marschak (1960) and Block and Marschak (1960) translating models originally developed for discriminant analysis in psychophysics (Thurstone, 1927) to the alternative domain of discrete choice analysis...
Statistical distributions applications and parameter estimates
Thomopoulos, Nick T
2017-01-01
This book gives a description of the group of statistical distributions that have ample application to studies in statistics and probability. Understanding statistical distributions is fundamental for researchers in almost all disciplines. The informed researcher will select the statistical distribution that best fits the data in the study at hand. Some of the distributions are well known to the general researcher and are in use in a wide variety of ways. Other useful distributions are less understood and are not in common use. The book describes when and how to apply each of the distributions in research studies, with a goal to identify the distribution that best applies to the study. The distributions are for continuous, discrete, and bivariate random variables. In most studies, the parameter values are not known a priori, and sample data is needed to estimate parameter values. In other scenarios, no sample data is available, and the researcher seeks some insight that allows the estimate of ...
Energy Technology Data Exchange (ETDEWEB)
Conte, Viviane Cristhyne Bini; Arruda, Lucia Valeria Ramos de; Yamamoto, Lia [Universidade Tecnologica Federal do Parana (UTFPR), Curitiba, PR (Brazil)
2008-07-01
Planning and scheduling of the pipeline network operations aim the most efficient use of the resources resulting in a better performance of the network. A petroleum distribution pipeline network is composed by refineries, sources and/or storage parks, connected by a set of pipelines, which operate the transportation of petroleum and derivatives among adjacent areas. In real scenes, this problem is considered a combinatorial problem, which has difficult solution, which makes necessary methodologies of the resolution that present low computational time. This work aims to get solutions that attempt the demands and minimize the number of batch fragmentations on the sent operations of products for the pipelines in a simplified model of a real network, through by application of the local search metaheuristic GRASP. GRASP does not depend of solutions of previous iterations and works in a random way so it allows the search for the solution in an ampler and diversified search space. GRASP utilization does not demand complex calculation, even the construction stage that requires more computational effort, which provides relative rapidity in the attainment of good solutions. GRASP application on the scheduling of the operations of this network presented feasible solutions in a low computational time. (author)
Pilot-Wave Quantum Theory in Discrete Space and Time and the Principle of Least Action
Gluza, Janusz; Kosek, Jerzy
2016-11-01
The idea of obtaining a pilot-wave quantum theory on a lattice with discrete time is presented. The motion of quantum particles is described by a |Ψ |^2-distributed Markov chain. Stochastic matrices of the process are found by the discrete version of the least-action principle. Probability currents are the consequence of Hamilton's principle and the stochasticity of the Markov process is minimized. As an example, stochastic motion of single particles in a double-slit experiment is examined.
Hallin, M.; Piegorsch, W.; El Shaarawi, A.
2012-01-01
The random variable X taking values 0,1,2,…,x,… with probabilities pλ(x) = e−λλx/x!, where λ∈R0+ is called a Poisson variable, and its distribution a Poisson distribution, with parameter λ. The Poisson distribution with parameter λ can be obtained as the limit, as n → ∞ and p → 0 in such a way that
Cuspidal discrete series for semisimple symmetric spaces
DEFF Research Database (Denmark)
Andersen, Nils Byrial; Flensted-Jensen, Mogens; Schlichtkrull, Henrik
2012-01-01
We propose a notion of cusp forms on semisimple symmetric spaces. We then study the real hyperbolic spaces in detail, and show that there exists both cuspidal and non-cuspidal discrete series. In particular, we show that all the spherical discrete series are non-cuspidal. (C) 2012 Elsevier Inc. All...
Geometry and Hamiltonian mechanics on discrete spaces
Talasila, V.; Clemente-Gallardo, J.; Schaft, A.J. van der
2004-01-01
Numerical simulation is often crucial for analysing the behaviour of many complex systems which do not admit analytic solutions. To this end, one either converts a ‘smooth’ model into a discrete (in space and time) model, or models systems directly at a discrete level. The goal of this paper is to
Geometry and Hamiltonian mechanics on discrete spaces
Talasila, V.; Clemente Gallardo, J.J.; Clemente-Gallardo, J.; van der Schaft, Arjan
2004-01-01
Numerical simulation is often crucial for analysing the behaviour of many complex systems which do not admit analytic solutions. To this end, one either converts a 'smooth' model into a discrete (in space and time) model, or models systems directly at a discrete level. The goal of this paper is to
Quantum dynamical entropies in discrete classical chaos
Energy Technology Data Exchange (ETDEWEB)
Benatti, Fabio [Dipartimento di Fisica Teorica, Universita di Trieste, Strada Costiera 11, 34014 Trieste (Italy); Cappellini, Valerio [Dipartimento di Fisica Teorica, Universita di Trieste, Strada Costiera 11, 34014 Trieste (Italy); Zertuche, Federico [Instituto de Matematicas, UNAM, Unidad Cuernavaca, AP 273-3, Admon. 3, 62251 Cuernavaca, Morelos (Mexico)
2004-01-09
We discuss certain analogies between quantization and discretization of classical systems on manifolds. In particular, we will apply the quantum dynamical entropy of Alicki and Fannes to numerically study the footprints of chaos in discretized versions of hyperbolic maps on the torus.