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
-linear springs. The initial packing of the particles is generated by the ballistic deposition method. Salient micromechanical features of closed die and isostatic powder compaction are elucidated for both frictionless and sticking contacts. It is found that substantial rearrangement of frictionless particles......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...
Inevitable randomness in discrete mathematics
Beck, Jozsef
2009-01-01
Mathematics has been called the science of order. The subject is remarkably good for generalizing specific cases to create abstract theories. However, mathematics has little to say when faced with highly complex systems, where disorder reigns. This disorder can be found in pure mathematical arenas, such as the distribution of primes, the 3n+1 conjecture, and class field theory. The purpose of this book is to provide examples--and rigorous proofs--of the complexity law: (1) discrete systems are either simple or they exhibit advanced pseudorandomness; (2) a priori probabilities often exist even when there is no intrinsic symmetry. Part of the difficulty in achieving this purpose is in trying to clarify these vague statements. The examples turn out to be fascinating instances of deep or mysterious results in number theory and combinatorics. This book considers randomness and complexity. The traditional approach to complexity--computational complexity theory--is to study very general complexity classes, such as P...
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.
Degree distribution in discrete case
International Nuclear Information System (INIS)
Wang, Li-Na; Chen, Bin; Yan, Zai-Zai
2011-01-01
Vertex degree of many network models and real-life networks is limited to non-negative integer. By means of measure and integral, the relation of the degree distribution and the cumulative degree distribution in discrete case is analyzed. The degree distribution, obtained by the differential of its cumulative, is only suitable for continuous case or discrete case with constant degree change. When degree change is not a constant but proportional to degree itself, power-law degree distribution and its cumulative have the same exponent and the mean value is finite for power-law exponent greater than 1. -- Highlights: → Degree change is the crux for using the cumulative degree distribution method. → It suits for discrete case with constant degree change. → If degree change is proportional to degree, power-law degree distribution and its cumulative have the same exponent. → In addition, the mean value is finite for power-law exponent greater than 1.
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...
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 Riccati equation solutions: Distributed algorithms
Directory of Open Access Journals (Sweden)
D. G. Lainiotis
1996-01-01
Full Text Available In this paper new distributed algorithms for the solution of the discrete Riccati equation are introduced. The algorithms are used to provide robust and computational efficient solutions to the discrete Riccati equation. The proposed distributed algorithms are theoretically interesting and computationally attractive.
International Nuclear Information System (INIS)
Mishchenko, Michael I.; Dlugach, Janna M.; Yurkin, Maxim A.; Bi, Lei; Cairns, Brian; Liu, Li; Panetta, R. Lee; Travis, Larry D.; Yang, Ping; Zakharova, Nadezhda T.
2016-01-01
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
Mishchenko, Michael I.; Dlugach, Janna M.; Yurkin, Maxim A.; Bi, Lei; Cairns, Brian; Liu, Li; Panetta, R. Lee; Travis, Larry D.; Yang, Ping; Zakharova, Nadezhda T.
2018-01-01
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
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
Mishchenko, Michael I.; Dlugach, Janna M.; Yurkin, Maxim A.; Bi, Lei; Cairns, Brian; Liu, Li; Panetta, R. Lee; Travis, Larry D.; Yang, Ping; Zakharova, Nadezhda T.
2016-01-01
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 of
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)
Discrete scale-free distributions and associated limit theorems
International Nuclear Information System (INIS)
Hopcraft, K I; Jakeman, E; Matthews, J O
2004-01-01
Consideration is given to the convergence properties of sums of identical, independently distributed random variables drawn from a class of discrete distributions with power-law tails, which are relevant to scale-free networks. Different limiting distributions, and rates of convergence to these limits, are identified and depend on the index of the tail. For indices ≥2, the topology evolves to a random Poisson network, but the rate of convergence can be extraordinarily slow and unlikely to be yet evident for the current size of the WWW for example. It is shown that treating discrete scale-free behaviour with continuum or mean-field approximations can lead to incorrect results. (letter to the editor)
A note on inconsistent families of discrete multivariate distributions
Ghosh, Sugata; Dutta, Subhajit; Genton, Marc G.
2017-01-01
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.
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.
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
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
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....
Migliorati, Giovanni; Nobile, Fabio; Tempone, Raul
2015-01-01
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
Discrete Event Simulation of Distributed Team Communication
2012-03-22
performs, and auditory information that is provided through multiple audio devices with speech response. This paper extends previous discrete event workload...2008, pg. 1) notes that “Architecture modeling furnishes abstrac- tions for use in managing complexities, allowing engineers to visualise the proposed
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...... accommodate a variety of dependence relationships between two attributes. The special case of second-degree discrete distribution independence is equivalent to the utility independence condition. We focus on third-degree discrete distribution independence that leads to a decomposition formula that contains...
Applying Multivariate Discrete Distributions to Genetically Informative Count Data.
Kirkpatrick, Robert M; Neale, Michael C
2016-03-01
We present a novel method of conducting biometric analysis of twin data when the phenotypes are integer-valued counts, which often show an L-shaped distribution. Monte Carlo simulation is used to compare five likelihood-based approaches to modeling: our multivariate discrete method, when its distributional assumptions are correct, when they are incorrect, and three other methods in common use. With data simulated from a skewed discrete distribution, recovery of twin correlations and proportions of additive genetic and common environment variance was generally poor for the Normal, Lognormal and Ordinal models, but good for the two discrete models. Sex-separate applications to substance-use data from twins in the Minnesota Twin Family Study showed superior performance of two discrete models. The new methods are implemented using R and OpenMx and are freely available.
About SIC POVMs and discrete Wigner distributions
International Nuclear Information System (INIS)
Colin, Samuel; Corbett, John; Durt, Thomas; Gross, David
2005-01-01
A set of d 2 vectors in a Hilbert space of dimension d is called equiangular if each pair of vectors encloses the same angle. The projection operators onto these vectors define a POVM which is distinguished by its high degree of symmetry. Measures of this kind are called symmetric informationally complete, or SIC POVMs for short, and could be applied for quantum state tomography. Despite its simple geometrical description, the problem of constructing SIC POVMs or even proving their existence seems to be very hard. It is our purpose to introduce two applications of discrete Wigner functions to the analysis of the problem at hand. First, we will present a method for identifying symmetries of SIC POVMs under Clifford operations. This constitutes an alternative approach to a structure described before by Zauner and Appleby. Further, a simple and geometrically motivated construction for an SIC POVM in dimensions two and three is given (which, unfortunately, allows no generalization). Even though no new structures are found, we hope that the re-formulation of the problem may prove useful for future inquiries
Nobile, Fabio
2015-01-01
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
Continuous-time quantum random walks require discrete space
International Nuclear Information System (INIS)
Manouchehri, K; Wang, J B
2007-01-01
Quantum random walks are shown to have non-intuitive dynamics which makes them an attractive area of study for devising quantum algorithms for long-standing open problems as well as those arising in the field of quantum computing. In the case of continuous-time quantum random walks, such peculiar dynamics can arise from simple evolution operators closely resembling the quantum free-wave propagator. We investigate the divergence of quantum walk dynamics from the free-wave evolution and show that, in order for continuous-time quantum walks to display their characteristic propagation, the state space must be discrete. This behavior rules out many continuous quantum systems as possible candidates for implementing continuous-time quantum random walks
Continuous-time quantum random walks require discrete space
Manouchehri, K.; Wang, J. B.
2007-11-01
Quantum random walks are shown to have non-intuitive dynamics which makes them an attractive area of study for devising quantum algorithms for long-standing open problems as well as those arising in the field of quantum computing. In the case of continuous-time quantum random walks, such peculiar dynamics can arise from simple evolution operators closely resembling the quantum free-wave propagator. We investigate the divergence of quantum walk dynamics from the free-wave evolution and show that, in order for continuous-time quantum walks to display their characteristic propagation, the state space must be discrete. This behavior rules out many continuous quantum systems as possible candidates for implementing continuous-time quantum random walks.
Distribution for fermionic discrete lattice gas within the canonical ensemble
International Nuclear Information System (INIS)
Kutner, R.; Barszczak, T.
1991-01-01
The distinct deviations from the Fermi-Dirac statistics ascertained recently at low temperatures for a one-dimensional, spinless fermionic discrete lattice gas with conserved number of noninteracting particles hopping on the nondegenerated, well-separated single-particle energy levels are studied in numerical and theoretical terms. The generalized distribution is derived in the form n(h) = {Y h exp[(var-epsilon h -μ)β]+1} -1 valid even in the thermodynamic limit, when the discreteness of the energy levels is kept. This distribution demonstrates good agreement with the data obtained numerically both by the canonical partition-function technique and by Monte Carlo simulation
Random distributed feedback fibre lasers
Energy Technology Data Exchange (ETDEWEB)
Turitsyn, Sergei K., E-mail: s.k.turitsyn@aston.ac.uk [Aston Institute of Photonic Technologies, Aston University, Birmingham B4 7ET (United Kingdom); Novosibirsk State University, 2 Pirogova str., 630090, Novosibirsk (Russian Federation); Babin, Sergey A. [Novosibirsk State University, 2 Pirogova str., 630090, Novosibirsk (Russian Federation); Institute of Automation and Electrometry SB RAS, 1 Ac. Koptug. ave., 630090, Novosibirsk (Russian Federation); Churkin, Dmitry V. [Aston Institute of Photonic Technologies, Aston University, Birmingham B4 7ET (United Kingdom); Novosibirsk State University, 2 Pirogova str., 630090, Novosibirsk (Russian Federation); Institute of Automation and Electrometry SB RAS, 1 Ac. Koptug. ave., 630090, Novosibirsk (Russian Federation); Vatnik, Ilya D.; Nikulin, Maxim [Institute of Automation and Electrometry SB RAS, 1 Ac. Koptug. ave., 630090, Novosibirsk (Russian Federation); Podivilov, Evgenii V. [Novosibirsk State University, 2 Pirogova str., 630090, Novosibirsk (Russian Federation); Institute of Automation and Electrometry SB RAS, 1 Ac. Koptug. ave., 630090, Novosibirsk (Russian Federation)
2014-09-10
The concept of random lasers exploiting multiple scattering of photons in an amplifying disordered medium in order to generate coherent light without a traditional laser resonator has attracted a great deal of attention in recent years. This research area lies at the interface of the fundamental theory of disordered systems and laser science. The idea was originally proposed in the context of astrophysics in the 1960s by V.S. Letokhov, who studied scattering with “negative absorption” of the interstellar molecular clouds. Research on random lasers has since developed into a mature experimental and theoretical field. A simple design of such lasers would be promising for potential applications. However, in traditional random lasers the properties of the output radiation are typically characterized by complex features in the spatial, spectral and time domains, making them less attractive than standard laser systems in terms of practical applications. Recently, an interesting and novel type of one-dimensional random laser that operates in a conventional telecommunication fibre without any pre-designed resonator mirrors–random distributed feedback fibre laser–was demonstrated. The positive feedback required for laser generation in random fibre lasers is provided by the Rayleigh scattering from the inhomogeneities of the refractive index that are naturally present in silica glass. In the proposed laser concept, the randomly backscattered light is amplified through the Raman effect, providing distributed gain over distances up to 100 km. Although an effective reflection due to the Rayleigh scattering is extremely small (∼0.1%), the lasing threshold may be exceeded when a sufficiently large distributed Raman gain is provided. Such a random distributed feedback fibre laser has a number of interesting and attractive features. The fibre waveguide geometry provides transverse confinement, and effectively one-dimensional random distributed feedback leads to the
Random distributed feedback fibre lasers
International Nuclear Information System (INIS)
Turitsyn, Sergei K.; Babin, Sergey A.; Churkin, Dmitry V.; Vatnik, Ilya D.; Nikulin, Maxim; Podivilov, Evgenii V.
2014-01-01
The concept of random lasers exploiting multiple scattering of photons in an amplifying disordered medium in order to generate coherent light without a traditional laser resonator has attracted a great deal of attention in recent years. This research area lies at the interface of the fundamental theory of disordered systems and laser science. The idea was originally proposed in the context of astrophysics in the 1960s by V.S. Letokhov, who studied scattering with “negative absorption” of the interstellar molecular clouds. Research on random lasers has since developed into a mature experimental and theoretical field. A simple design of such lasers would be promising for potential applications. However, in traditional random lasers the properties of the output radiation are typically characterized by complex features in the spatial, spectral and time domains, making them less attractive than standard laser systems in terms of practical applications. Recently, an interesting and novel type of one-dimensional random laser that operates in a conventional telecommunication fibre without any pre-designed resonator mirrors–random distributed feedback fibre laser–was demonstrated. The positive feedback required for laser generation in random fibre lasers is provided by the Rayleigh scattering from the inhomogeneities of the refractive index that are naturally present in silica glass. In the proposed laser concept, the randomly backscattered light is amplified through the Raman effect, providing distributed gain over distances up to 100 km. Although an effective reflection due to the Rayleigh scattering is extremely small (∼0.1%), the lasing threshold may be exceeded when a sufficiently large distributed Raman gain is provided. Such a random distributed feedback fibre laser has a number of interesting and attractive features. The fibre waveguide geometry provides transverse confinement, and effectively one-dimensional random distributed feedback leads to the
Correlation effects in a discrete quantum random walk
International Nuclear Information System (INIS)
Stang, J B; Rezakhani, A T; Sanders, B C
2009-01-01
We introduce memory-dependent discrete-time quantum random walk models by adding uncorrelated memory terms and also by modifying the Hamiltonian of the walker to include couplings with memory-keeping agents. We next study numerically the correlation effects in these models. We also propose a correlation exponent as a relevant and promising tool for investigation of correlation or memory (hence non-Markovian) effects. Our analysis can easily be applied to more realistic models in which different regimes may emerge because of competition between different underlying physical mechanisms
Energy Technology Data Exchange (ETDEWEB)
Matthews, J O; Hopcraft, K I; Jakeman, E [Applied Mathematics Division, School of Mathematical Sciences, University of Nottingham, Nottingham, NG7 2RD (United Kingdom)
2003-11-21
Some properties of classical population processes that comprise births, deaths and multiple immigrations are investigated. The rates at which the immigrants arrive can be tailored to produce a population whose steady state fluctuations are described by a pre-selected distribution. Attention is focused on the class of distributions with a discrete stable law, which have power-law tails and whose moments and autocorrelation function do not exist. The separate problem of monitoring and characterizing the fluctuations is studied, analysing the statistics of individuals that leave the population. The fluctuations in the size of the population are transferred to the times between emigrants that form an intermittent time series of events. The emigrants are counted with a detector of finite dynamic range and response time. This is modelled through clipping the time series or saturating it at an arbitrary but finite level, whereupon its moments and correlation properties become finite. Distributions for the time to the first counted event and for the time between events exhibit power-law regimes that are characteristic of the fluctuations in population size. The processes provide analytical models with which properties of complex discrete random phenomena can be explored, and in addition provide generic means by which random time series encompassing a wide range of intermittent and other discrete random behaviour may be generated.
International Nuclear Information System (INIS)
Matthews, J O; Hopcraft, K I; Jakeman, E
2003-01-01
Some properties of classical population processes that comprise births, deaths and multiple immigrations are investigated. The rates at which the immigrants arrive can be tailored to produce a population whose steady state fluctuations are described by a pre-selected distribution. Attention is focused on the class of distributions with a discrete stable law, which have power-law tails and whose moments and autocorrelation function do not exist. The separate problem of monitoring and characterizing the fluctuations is studied, analysing the statistics of individuals that leave the population. The fluctuations in the size of the population are transferred to the times between emigrants that form an intermittent time series of events. The emigrants are counted with a detector of finite dynamic range and response time. This is modelled through clipping the time series or saturating it at an arbitrary but finite level, whereupon its moments and correlation properties become finite. Distributions for the time to the first counted event and for the time between events exhibit power-law regimes that are characteristic of the fluctuations in population size. The processes provide analytical models with which properties of complex discrete random phenomena can be explored, and in addition provide generic means by which random time series encompassing a wide range of intermittent and other discrete random behaviour may be generated
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.
Seslija, Marko; van der Schaft, Arjan; Scherpen, Jacquelien M.A.
This paper addresses the issue of structure-preserving discretization of open distributed-parameter systems with Hamiltonian dynamics. Employing the formalism of discrete exterior calculus, we introduce a simplicial Dirac structure as a discrete analogue of the Stokes-Dirac structure and demonstrate
Seslija, Marko; Scherpen, Jacquelien M.A.; van der Schaft, Arjan
2011-01-01
This paper addresses the issue of structure-preserving discretization of open distributed-parameter systems with Hamiltonian dynamics. Employing the formalism of discrete exterior calculus, we introduce simplicial Dirac structures as discrete analogues of the Stokes-Dirac structure and demonstrate
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...... means of random parameters. In this paper, we propose a practical test, based on seminonparametric techniques. The test is analyzed both on synthetic and real data, and is shown to be simple and powerful. (c) 2007 Elsevier Ltd. All rights reserved....
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...... distributions. Both approaches allow the researcher to increase the number of parameters as desired. The paper provides a range of evidence on the ability of the various approaches to recover various distributions from data. The two advanced approaches are comparable in terms of the likelihoods achieved...
Discrete random walk models for space-time fractional diffusion
International Nuclear Information System (INIS)
Gorenflo, Rudolf; Mainardi, Francesco; Moretti, Daniele; Pagnini, Gianni; Paradisi, Paolo
2002-01-01
A physical-mathematical approach to anomalous diffusion may be based on generalized diffusion equations (containing derivatives of fractional order in space or/and time) and related random walk models. By space-time fractional diffusion equation we mean an evolution equation obtained from the standard linear diffusion equation by replacing the second-order space derivative with a Riesz-Feller derivative of order α is part of (0,2] and skewness θ (moduleθ≤{α,2-α}), and the first-order time derivative with a Caputo derivative of order β is part of (0,1]. Such evolution equation implies for the flux a fractional Fick's law which accounts for spatial and temporal non-locality. The fundamental solution (for the Cauchy problem) of the fractional diffusion equation can be interpreted as a probability density evolving in time of a peculiar self-similar stochastic process that we view as a generalized diffusion process. By adopting appropriate finite-difference schemes of solution, we generate models of random walk discrete in space and time suitable for simulating random variables whose spatial probability density evolves in time according to this fractional diffusion equation
Discrete method for design of flow distribution in manifolds
International Nuclear Information System (INIS)
Wang, Junye; Wang, Hualin
2015-01-01
Flow in manifold systems is encountered in designs of various industrial processes, such as fuel cells, microreactors, microchannels, plate heat exchanger, and radial flow reactors. The uniformity of flow distribution in manifold is a key indicator for performance of the process equipment. In this paper, a discrete method for a U-type arrangement was developed to evaluate the uniformity of the flow distribution and the pressure drop and then was used for direct comparisons between the U-type and the Z-type. The uniformity of the U-type is generally better than that of the Z-type in most of cases for small ζ and large M. The U-type and the Z-type approach each other as ζ increases or M decreases. However, the Z-type is more sensitive to structures than the U-type and approaches uniform flow distribution faster than the U-type as M decreases or ζ increases. This provides a simple yet powerful tool for the designers to evaluate and select a flow arrangement and offers practical measures for industrial applications. - Highlights: • Discrete methodology of flow field designs in manifolds with U-type arrangements. • Quantitative comparison between U-type and Z-type arrangements. • Discrete solution of flow distribution with varying flow coefficients. • Practical measures and guideline to design of manifold systems.
Discrete Wavelet Transform for Fault Locations in Underground Distribution System
Apisit, C.; Ngaopitakkul, A.
2010-10-01
In this paper, a technique for detecting faults in underground distribution system is presented. Discrete Wavelet Transform (DWT) based on traveling wave is employed in order to detect the high frequency components and to identify fault locations in the underground distribution system. The first peak time obtained from the faulty bus is employed for calculating the distance of fault from sending end. The validity of the proposed technique is tested with various fault inception angles, fault locations and faulty phases. The result is found that the proposed technique provides satisfactory result and will be very useful in the development of power systems protection scheme.
Distributed mean curvature on a discrete manifold for Regge calculus
International Nuclear Information System (INIS)
Conboye, Rory; Miller, Warner A; Ray, Shannon
2015-01-01
The integrated mean curvature of a simplicial manifold is well understood in both Regge Calculus and Discrete Differential Geometry. However, a well motivated pointwise definition of curvature requires a careful choice of the volume over which to uniformly distribute the local integrated curvature. We show that hybrid cells formed using both the simplicial lattice and its circumcentric dual emerge as a remarkably natural structure for the distribution of this local integrated curvature. These hybrid cells form a complete tessellation of the simplicial manifold, contain a geometric orthonormal basis, and are also shown to give a pointwise mean curvature with a natural interpretation as the fractional rate of change of the normal vector. (paper)
Distributed mean curvature on a discrete manifold for Regge calculus
Conboye, Rory; Miller, Warner A.; Ray, Shannon
2015-09-01
The integrated mean curvature of a simplicial manifold is well understood in both Regge Calculus and Discrete Differential Geometry. However, a well motivated pointwise definition of curvature requires a careful choice of the volume over which to uniformly distribute the local integrated curvature. We show that hybrid cells formed using both the simplicial lattice and its circumcentric dual emerge as a remarkably natural structure for the distribution of this local integrated curvature. These hybrid cells form a complete tessellation of the simplicial manifold, contain a geometric orthonormal basis, and are also shown to give a pointwise mean curvature with a natural interpretation as the fractional rate of change of the normal vector.
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.
A Bernstein-Von Mises Theorem for discrete probability distributions
Boucheron, S.; Gassiat, E.
2008-01-01
We investigate the asymptotic normality of the posterior distribution in the discrete setting, when model dimension increases with sample size. We consider a probability mass function θ0 on ℕ∖{0} and a sequence of truncation levels (kn)n satisfying kn3≤ninf i≤knθ0(i). Let θ̂ denote the maximum likelihood estimate of (θ0(i))i≤kn and let Δn(θ0) denote the kn-dimensional vector which i-th coordinate is defined by $\\sqrt{n}(\\hat{\\theta}_{n}(i)-\\theta_{0}(i))$ for 1≤i≤kn. We check that under mild ...
Random graph states, maximal flow and Fuss-Catalan distributions
International Nuclear Information System (INIS)
Collins, BenoIt; Nechita, Ion; Zyczkowski, Karol
2010-01-01
For any graph consisting of k vertices and m edges we construct an ensemble of random pure quantum states which describe a system composed of 2m subsystems. Each edge of the graph represents a bipartite, maximally entangled state. Each vertex represents a random unitary matrix generated according to the Haar measure, which describes the coupling between subsystems. Dividing all subsystems into two parts, one may study entanglement with respect to this partition. A general technique to derive an expression for the average entanglement entropy of random pure states associated with a given graph is presented. Our technique relies on Weingarten calculus and flow problems. We analyze the statistical properties of spectra of such random density matrices and show for which cases they are described by the free Poissonian (Marchenko-Pastur) distribution. We derive a discrete family of generalized, Fuss-Catalan distributions and explicitly construct graphs which lead to ensembles of random states characterized by these novel distributions of eigenvalues.
Multiobjective Two-Stage Stochastic Programming Problems with Interval Discrete Random Variables
Directory of Open Access Journals (Sweden)
S. K. Barik
2012-01-01
Full Text Available Most of the real-life decision-making problems have more than one conflicting and incommensurable objective functions. In this paper, we present a multiobjective two-stage stochastic linear programming problem considering some parameters of the linear constraints as interval type discrete random variables with known probability distribution. Randomness of the discrete intervals are considered for the model parameters. Further, the concepts of best optimum and worst optimum solution are analyzed in two-stage stochastic programming. To solve the stated problem, first we remove the randomness of the problem and formulate an equivalent deterministic linear programming model with multiobjective interval coefficients. Then the deterministic multiobjective model is solved using weighting method, where we apply the solution procedure of interval linear programming technique. We obtain the upper and lower bound of the objective function as the best and the worst value, respectively. It highlights the possible risk involved in the decision-making tool. A numerical example is presented to demonstrate the proposed solution procedure.
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.
Calculation of large Reynolds number two-dimensional flow using discrete vortices with random walk
International Nuclear Information System (INIS)
Milinazzo, F.; Saffman, P.G.
1977-01-01
The numerical calculation of two-dimensional rotational flow at large Reynolds number is considered. The method of replacing a continuous distribution of vorticity by a finite number, N, of discrete vortices is examined, where the vortices move under their mutually induced velocities plus a random component to simulate effects of viscosity. The accuracy of the method is studied by comparison with the exact solution for the decay of a circular vortex. It is found, and analytical arguments are produced in support, that the quantitative error is significant unless N is large compared with a characteristic Reynolds number. The mutually induced velocities are calculated by both direct summation and by the ''cloud in cell'' technique. The latter method is found to produce comparable error and to be much faster
Electrical Conductivity Distributions in Discrete Fluid-Filled Fractures
James, S. C.; Ahmmed, B.; Knox, H. A.; Johnson, T.; Dunbar, J. A.
2017-12-01
It is commonly asserted that hydraulic fracturing enhances permeability by generating new fractures in the reservoir. Furthermore, it is assumed that in the fractured system predominant flow occurs in these newly formed and pre-existing fractures. Among the phenomenology that remains enigmatic are fluid distributions inside fractures. Therefore, determining fluid distribution and their associated temporal and spatial evolution in fractures is critical for safe and efficient hydraulic fracturing. Previous studies have used both forward modeling and inversion of electrical data to show that a geologic system consisting of fluid filled fractures has a conductivity distribution, where fractures act as electrically conductive bodies when the fluids are more conductive than the host material. We will use electrical inversion for estimating electrical conductivity distribution within multiple fractures from synthetic and measured data. Specifically, we will use data and well geometries from an experiment performed at Blue Canyon Dome in Socorro, NM, which was used as a study site for subsurface technology, engineering, and research (SubTER) funded by DOE. This project used a central borehole for energetically stimulating the system and four monitoring boreholes, emplaced in the cardinal directions. The electrical data taken during this project used 16 temporary electrodes deployed in the stimulation borehole and 64 permanent electrodes in the monitoring wells (16 each). We present results derived using E4D from scenarios with two discrete fractures, thereby discovering the electric potential response of both spatially and temporarily variant fluid distribution and the resolution of fluid and fracture boundaries. These two fractures have dimensions of 3m × 0.01m × 7m and are separated by 1m. These results can be used to develop stimulation and flow tests at the meso-scale that will be important for model validation. Sandia National Laboratories is a multi
Discrete sensors distribution for accurate plantar pressure analyses.
Claverie, Laetitia; Ille, Anne; Moretto, Pierre
2016-12-01
The aim of this study was to determine the distribution of discrete sensors under the footprint for accurate plantar pressure analyses. For this purpose, two different sensor layouts have been tested and compared, to determine which was the most accurate to monitor plantar pressure with wireless devices in research and/or clinical practice. Ten healthy volunteers participated in the study (age range: 23-58 years). The barycenter of pressures (BoP) determined from the plantar pressure system (W-inshoe®) was compared to the center of pressures (CoP) determined from a force platform (AMTI) in the medial-lateral (ML) and anterior-posterior (AP) directions. Then, the vertical ground reaction force (vGRF) obtained from both W-inshoe® and force platform was compared for both layouts for each subject. The BoP and vGRF determined from the plantar pressure system data showed good correlation (SCC) with those determined from the force platform data, notably for the second sensor organization (ML SCC= 0.95; AP SCC=0.99; vGRF SCC=0.91). The study demonstrates that an adjusted placement of removable sensors is key to accurate plantar pressure analyses. These results are promising for a plantar pressure recording outside clinical or laboratory settings, for long time monitoring, real time feedback or for whatever activity requiring a low-cost system. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Kang, Li; Tang, Sanyi
2016-01-01
Highlights: • The discrete single species and multiple species models with random perturbation are proposed. • The complex dynamics and interesting bifurcation behavior have been investigated. • The reverse effects of random perturbation on discrete systems have been discussed and revealed. • The main results can be applied for pest control and resources management. - Abstract: The natural species are likely to present several interesting and complex phenomena under random perturbations, which have been confirmed by simple mathematical models. The important questions are: how the random perturbations influence the dynamics of the discrete population models with multiple steady states or multiple species interactions? and is there any different effects for single species and multiple species models with random perturbation? To address those interesting questions, we have proposed the discrete single species model with two stable equilibria and the host-parasitoid model with Holling type functional response functions to address how the random perturbation affects the dynamics. The main results indicate that the random perturbation does not change the number of blurred orbits of the single species model with two stable steady states compared with results for the classical Ricker model with same random perturbation, but it can strength the stability. However, extensive numerical investigations depict that the random perturbation does not influence the complexities of the host-parasitoid models compared with the results for the models without perturbation, while it does increase the period of periodic orbits doubly. All those confirm that the random perturbation has a reverse effect on the dynamics of the discrete single and multiple population models, which could be applied in reality including pest control and resources management.
Directory of Open Access Journals (Sweden)
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.
Directory of Open Access Journals (Sweden)
Kristian Hovde Liland
2016-01-01
Full Text Available When a series of Bernoulli trials occur within a fixed time frame or limited space, it is often interesting to assess if the successful outcomes have occurred completely at random, or if they tend to group together. One example, in genetics, is detecting grouping of genes within a genome. Approximations of the distribution of successes are possible, but they become inaccurate for small sample sizes. In this article, we describe the exact distribution of time between random, non-overlapping successes in discrete time of fixed length. A complete description of the probability mass function, the cumulative distribution function, mean, variance and recurrence relation is included. We propose an associated test for the over-representation of short distances and illustrate the methodology through relevant examples. The theory is implemented in an R package including probability mass, cumulative distribution, quantile function, random number generator, simulation functions, and functions for testing.
Gong, Lihua; Deng, Chengzhi; Pan, Shumin; Zhou, Nanrun
2018-07-01
Based on hyper-chaotic system and discrete fractional random transform, an image compression-encryption algorithm is designed. The original image is first transformed into a spectrum by the discrete cosine transform and the resulting spectrum is compressed according to the method of spectrum cutting. The random matrix of the discrete fractional random transform is controlled by a chaotic sequence originated from the high dimensional hyper-chaotic system. Then the compressed spectrum is encrypted by the discrete fractional random transform. The order of DFrRT and the parameters of the hyper-chaotic system are the main keys of this image compression and encryption algorithm. The proposed algorithm can compress and encrypt image signal, especially can encrypt multiple images once. To achieve the compression of multiple images, the images are transformed into spectra by the discrete cosine transform, and then the spectra are incised and spliced into a composite spectrum by Zigzag scanning. Simulation results demonstrate that the proposed image compression and encryption algorithm is of high security and good compression performance.
On the Distribution of Random Geometric Graphs
DEFF Research Database (Denmark)
Badiu, Mihai Alin; Coon, Justin P.
2018-01-01
as a measure of the graph’s topological uncertainty (or information content). Moreover, the distribution is also relevant for determining average network performance or designing protocols. However, a major impediment in deducing the graph distribution is that it requires the joint probability distribution......Random geometric graphs (RGGs) are commonly used to model networked systems that depend on the underlying spatial embedding. We concern ourselves with the probability distribution of an RGG, which is crucial for studying its random topology, properties (e.g., connectedness), or Shannon entropy...... of the n(n − 1)/2 distances between n nodes randomly distributed in a bounded domain. As no such result exists in the literature, we make progress by obtaining the joint distribution of the distances between three nodes confined in a disk in R 2. This enables the calculation of the probability distribution...
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
Certain theories of multiple scattering in random media of discrete scatterers
International Nuclear Information System (INIS)
Olsen, R.L.; Kharadly, M.M.Z.; Corr, D.G.
1976-01-01
New information is presented on the accuracy of the heuristic approximations in two important theories of multiple scattering in random media of discrete scatterers: Twersky's ''free-space'' and ''two-space scatterer'' formalisms. Two complementary approaches, based primarily on a one-dimensional model and the one-dimensional forms of the theories, are used. For scatterer distributions of low average density, the ''heuristic'' asymptotic forms for the coherent field and the incoherent intensity are compared with asymptotic forms derived from a systematic analysis of the multiple scattering processes. For distributions of higher density, both in the average number of scatterers per wavelength and in the degree of packing of finite-size scatterers, the analysis is carried out ''experimentally'' by means of a Monte Carlo computer simulation. Approximate series expressions based on the systematic approach are numerically evaluated along with the heuristic expressions. The comparison (for both forward- and back-scattered field moments) is made for the worst-case conditions of strong multiple scattering for which the theories have not previously been evaluated. Several significant conclusions are drawn which have certain practical implications: in application of the theories to describe some of the scattering phenomena which occur in the troposphere, and in the further evaluation of the theories using experiments on physical models
Directory of Open Access Journals (Sweden)
Yang Yang
2013-01-01
Full Text Available We investigate the tailed asymptotic behavior of the randomly weighted sums with increments with convolution-equivalent distributions. Our obtained result can be directly applied to a discrete-time insurance risk model with insurance and financial risks and derive the asymptotics for the finite-time probability of the above risk model.
Control of discrete-event systems with modular or distributed structure
Czech Academy of Sciences Publication Activity Database
Komenda, Jan; van Schuppen, J. H.
2007-01-01
Roč. 388, č. 3 (2007), s. 199-226 ISSN 0304-3975 R&D Projects: GA AV ČR(CZ) KJB100190609 Institutional research plan: CEZ:AV0Z10190503 Keywords : supervisory control * modular discrete-event system * distributed discrete-event system Subject RIV: BA - General Mathematics Impact factor: 0.735, year: 2007
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...
The discrete additive Weibull distribution: A bathtub-shaped hazard for discontinuous failure data
International Nuclear Information System (INIS)
Bebbington, Mark; Lai, Chin-Diew; Wellington, Morgan; Zitikis, Ričardas
2012-01-01
Although failure data are usually treated as being continuous, they may have been collected in a discrete manner, or in fact be discrete in nature. Reliability models with bathtub-shaped hazard rate are fundamental to the concepts of burn-in and maintenance, but how well do they incorporate discrete data? We explore discrete versions of the additive Weibull distribution, which has the twin virtues of mathematical tractability and the ability to produce bathtub-shaped hazard rate functions. We derive conditions on the parameters for the hazard rate function to be increasing, decreasing, or bathtub shaped. While discrete versions may have the same shaped hazard rate for the same parameter values, we find that when fitted to data the fitted hazard rate shapes can vary between versions. Our results are illustrated using several real-life data sets, and the implications of using continuous models for discrete data discussed.
Migliorati, G.; Nobile, F.; von Schwerin, E.; Tempone, Raul
2013-01-01
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
Lin, Chao; Shen, Xueju; Li, Zengyan
2013-07-01
The key space of phase encryption algorithm using discrete random phase mask is investigated by numerical simulation in this paper. Random phase mask with finite and discrete phase levels is considered as the core component in most practical optical encryption architectures. The key space analysis is based on the design criteria of discrete random phase mask. The role of random amplitude mask and random phase mask in optical encryption system is identified from the perspective of confusion and diffusion. The properties of discrete random phase mask in a practical double random phase encoding scheme working in both amplitude encoding (AE) and phase encoding (PE) modes are comparably analyzed. The key space of random phase encryption algorithm is evaluated considering both the encryption quality and the brute-force attack resistibility. A method for enlarging the key space of phase encryption algorithm is also proposed to enhance the security of optical phase encryption techniques.
Li, Zejing
2012-01-01
This dissertation is mainly devoted to the research of two problems - the continuous-time portfolio optimization in different Wishart models and the effects of discrete rebalancing on portfolio wealth distribution and optimal portfolio strategy.
Global exponential stability of mixed discrete and distributively delayed cellular neural network
International Nuclear Information System (INIS)
Yao Hong-Xing; Zhou Jia-Yan
2011-01-01
This paper concernes analysis for the global exponential stability of a class of recurrent neural networks with mixed discrete and distributed delays. It first proves the existence and uniqueness of the balance point, then by employing the Lyapunov—Krasovskii functional and Young inequality, it gives the sufficient condition of global exponential stability of cellular neural network with mixed discrete and distributed delays, in addition, the example is provided to illustrate the applicability of the result. (general)
Gaussian quadrature and lattice discretization of the Fermi-Dirac distribution for graphene
Oettinger, D.; Mendoza, M.; Herrmann, H. J.
2013-01-01
We construct a lattice kinetic scheme to study electronic flow in graphene. For this purpose, we first derive a basis of orthogonal polynomials, using as weight function the ultrarelativistic Fermi-Dirac distribution at rest. Later, we use these polynomials to expand the respective distribution in a moving frame, for both cases, undoped and doped graphene. In order to discretize the Boltzmann equation and make feasible the numerical implementation, we reduce the number of discrete points in m...
Calibration of Discrete Random Walk (DRW) Model via G.I Taylor's Dispersion Theory
Javaherchi, Teymour; Aliseda, Alberto
2012-11-01
Prediction of particle dispersion in turbulent flows is still an important challenge with many applications to environmental, as well as industrial, fluid mechanics. Several models of dispersion have been developed to predict particle trajectories and their relative velocities, in combination with a RANS-based simulation of the background flow. The interaction of the particles with the velocity fluctuations at different turbulent scales represents a significant difficulty in generalizing the models to the wide range of flows where they are used. We focus our attention on the Discrete Random Walk (DRW) model applied to flow in a channel, particularly to the selection of eddies lifetimes as realizations of a Poisson distribution with a mean value proportional to κ / ɛ . We present a general method to determine the constant of this proportionality by matching the DRW model dispersion predictions for fluid element and particle dispersion to G.I Taylor's classical dispersion theory. This model parameter is critical to the magnitude of predicted dispersion. A case study of its influence on sedimentation of suspended particles in a tidal channel with an array of Marine Hydrokinetic (MHK) turbines highlights the dependency of results on this time scale parameter. Support from US DOE through the Northwest National Marine Renewable Energy Center, a UW-OSU partnership.
International Nuclear Information System (INIS)
Akıncı, Ümit
2012-01-01
The effect of the random magnetic field distribution on the phase diagrams and ground state magnetizations of the Ising nanowire has been investigated with effective field theory with correlations. Gaussian distribution has been chosen as a random magnetic field distribution. The variation of the phase diagrams with that distribution parameters has been obtained and some interesting results have been found such as disappearance of the reentrant behavior and first order transitions which appear in the case of discrete distributions. Also for single and double Gaussian distributions, ground state magnetizations for different distribution parameters have been determined which can be regarded as separate partially ordered phases of the system. - Highlights: ► We give the phase diagrams of the Ising nanowire under the continuous randomly distributed magnetic field. ► Ground state magnetization values obtained. ► Different partially ordered phases observed.
Modelling a reliability system governed by discrete phase-type distributions
International Nuclear Information System (INIS)
Ruiz-Castro, Juan Eloy; Perez-Ocon, Rafael; Fernandez-Villodre, Gemma
2008-01-01
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
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.
Stinchcombe, Adam R; Peskin, Charles S; Tranchina, Daniel
2012-06-01
We present a generalization of a population density approach for modeling and analysis of stochastic gene expression. In the model, the gene of interest fluctuates stochastically between an inactive state, in which transcription cannot occur, and an active state, in which discrete transcription events occur; and the individual mRNA molecules are degraded stochastically in an independent manner. This sort of model in simplest form with exponential dwell times has been used to explain experimental estimates of the discrete distribution of random mRNA copy number. In our generalization, the random dwell times in the inactive and active states, T_{0} and T_{1}, respectively, are independent random variables drawn from any specified distributions. Consequently, the probability per unit time of switching out of a state depends on the time since entering that state. Our method exploits a connection between the fully discrete random process and a related continuous process. We present numerical methods for computing steady-state mRNA distributions and an analytical derivation of the mRNA autocovariance function. We find that empirical estimates of the steady-state mRNA probability mass function from Monte Carlo simulations of laboratory data do not allow one to distinguish between underlying models with exponential and nonexponential dwell times in some relevant parameter regimes. However, in these parameter regimes and where the autocovariance function has negative lobes, the autocovariance function disambiguates the two types of models. Our results strongly suggest that temporal data beyond the autocovariance function is required in general to characterize gene switching.
Stable Graphical Model Estimation with Random Forests for Discrete, Continuous, and Mixed Variables
Fellinghauer, Bernd; Bühlmann, Peter; Ryffel, Martin; von Rhein, Michael; Reinhardt, Jan D.
2011-01-01
A conditional independence graph is a concise representation of pairwise conditional independence among many variables. Graphical Random Forests (GRaFo) are a novel method for estimating pairwise conditional independence relationships among mixed-type, i.e. continuous and discrete, variables. The number of edges is a tuning parameter in any graphical model estimator and there is no obvious number that constitutes a good choice. Stability Selection helps choosing this parameter with respect to...
Distributed Submodular Minimization And Motion Coordination Over Discrete State Space
Jaleel, Hassan; Shamma, Jeff S.
2017-01-01
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 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.
Implementing electric vehicles in urban distribution: A discrete event simulation
Lebeau, Philippe; Macharis, Cathy; Mierlo, Joeri Van; Maes, Guillaume
2013-01-01
Urban freight transport becomes increasingly important with the development of cities. However, it generates also inefficiencies on social, economic and environmental aspects. A possible solution is the use of urban distribution centres in order to rationalise the deliveries and to operate the last miles with clean vehicles. Electric vehicles are gaining attention lately but some barriers remain. Since costs barriers were already investigated, the paper aimed at evaluating the difference of p...
International Nuclear Information System (INIS)
Zhu Xunlin; Wang Youyi
2009-01-01
This Letter studies the exponential stability for a class of neural networks (NNs) with both discrete and distributed time-varying delays. Under weaker assumptions on the activation functions, by defining a more general type of Lyapunov functionals and developing a new convex combination technique, new less conservative and less complex stability criteria are established to guarantee the global exponential stability of the discussed NNs. The obtained conditions are dependent on both discrete and distributed delays, are expressed in terms of linear matrix inequalities (LMIs), and contain fewer decision variables. Numerical examples are given to illustrate the effectiveness and the less conservatism of the proposed conditions.
Parallel discrete ordinates algorithms on distributed and common memory systems
International Nuclear Information System (INIS)
Wienke, B.R.; Hiromoto, R.E.; Brickner, R.G.
1987-01-01
The S/sub n/ algorithm employs iterative techniques in solving the linear Boltzmann equation. These methods, both ordered and chaotic, were compared on both the Denelcor HEP and the Intel hypercube. Strategies are linked to the organization and accessibility of memory (common memory versus distributed memory architectures), with common concern for acquisition of global information. Apart from this, the inherent parallelism of the algorithm maps directly onto the two architectures. Results comparing execution times, speedup, and efficiency are based on a representative 16-group (full upscatter and downscatter) sample problem. Calculations were performed on both the Los Alamos National Laboratory (LANL) Denelcor HEP and the LANL Intel hypercube. The Denelcor HEP is a 64-bit multi-instruction, multidate MIMD machine consisting of up to 16 process execution modules (PEMs), each capable of executing 64 processes concurrently. Each PEM can cooperate on a job, or run several unrelated jobs, and share a common global memory through a crossbar switch. The Intel hypercube, on the other hand, is a distributed memory system composed of 128 processing elements, each with its own local memory. Processing elements are connected in a nearest-neighbor hypercube configuration and sharing of data among processors requires execution of explicit message-passing constructs
Traffic flow model at fixed control signals with discrete service time distribution
Directory of Open Access Journals (Sweden)
Lucky I. Igbinosun
2016-04-01
Full Text Available Most of the models of road traffic flow at fixed-cycle controlled intersection assume stationary distributions and provide steady state results. The assumption that a constant number of vehicles can leave the system during the green phase is unrealistic in real life situations. A discrete time queuing model was developed to describe the operation of traffic flow at a road intersection with fixed-cycle signalized control and to account for the randomness in the number of vehicles that can leave the system. The results show the expected queue size in the system when the traffic is light and for a busy period, respectively. For the light period, when the traffic intensity is less than one, it takes a shorter green cycle time for vehicles to clear up than during high traffic intensity (the road junction is saturated. Increasing the number of cars that can leave the junction at the turn of the green phase reduces the number of cycle times before the queue is cleared.
A random sampling procedure for anisotropic distributions
International Nuclear Information System (INIS)
Nagrajan, P.S.; Sethulakshmi, P.; Raghavendran, C.P.; Bhatia, D.P.
1975-01-01
A procedure is described for sampling the scattering angle of neutrons as per specified angular distribution data. The cosine of the scattering angle is written as a double Legendre expansion in the incident neutron energy and a random number. The coefficients of the expansion are given for C, N, O, Si, Ca, Fe and Pb and these elements are of interest in dosimetry and shielding. (author)
Gaussian quadrature and lattice discretization of the Fermi-Dirac distribution for graphene.
Oettinger, D; Mendoza, M; Herrmann, H J
2013-07-01
We construct a lattice kinetic scheme to study electronic flow in graphene. For this purpose, we first derive a basis of orthogonal polynomials, using as the weight function the ultrarelativistic Fermi-Dirac distribution at rest. Later, we use these polynomials to expand the respective distribution in a moving frame, for both cases, undoped and doped graphene. In order to discretize the Boltzmann equation and make feasible the numerical implementation, we reduce the number of discrete points in momentum space to 18 by applying a Gaussian quadrature, finding that the family of representative wave (2+1)-vectors, which satisfies the quadrature, reconstructs a honeycomb lattice. The procedure and discrete model are validated by solving the Riemann problem, finding excellent agreement with other numerical models. In addition, we have extended the Riemann problem to the case of different dopings, finding that by increasing the chemical potential the electronic fluid behaves as if it increases its effective viscosity.
Directory of Open Access Journals (Sweden)
F. Serinaldi
2010-12-01
Full Text Available Discrete multiplicative random cascade (MRC models were extensively studied and applied to disaggregate rainfall data, thanks to their formal simplicity and the small number of involved parameters. Focusing on temporal disaggregation, the rationale of these models is based on multiplying the value assumed by a physical attribute (e.g., rainfall intensity at a given time scale L, by a suitable number b of random weights, to obtain b attribute values corresponding to statistically plausible observations at a smaller L/b time resolution. In the original formulation of the MRC models, the random weights were assumed to be independent and identically distributed. However, for several studies this hypothesis did not appear to be realistic for the observed rainfall series as the distribution of the weights was shown to depend on the space-time scale and rainfall intensity. Since these findings contrast with the scale invariance assumption behind the MRC models and impact on the applicability of these models, it is worth studying their nature. This study explores the possible presence of dependence of the parameters of two discrete MRC models on rainfall intensity and time scale, by analyzing point rainfall series with 5-min time resolution. Taking into account a discrete microcanonical (MC model based on beta distribution and a discrete canonical beta-logstable (BLS, the analysis points out that the relations between the parameters and rainfall intensity across the time scales are detectable and can be modeled by a set of simple functions accounting for the parameter-rainfall intensity relationship, and another set describing the link between the parameters and the time scale. Therefore, MC and BLS models were modified to explicitly account for these relationships and compared with the continuous in scale universal multifractal (CUM model, which is used as a physically based benchmark model. Monte Carlo simulations point out
International Nuclear Information System (INIS)
Li Hongjie; Yue Dong
2010-01-01
The paper investigates the synchronization stability problem for a class of complex dynamical networks with Markovian jumping parameters and mixed time delays. The complex networks consist of m modes and the networks switch from one mode to another according to a Markovian chain with known transition probability. The mixed time delays are composed of discrete and distributed delays, the discrete time delay is assumed to be random and its probability distribution is known a priori. In terms of the probability distribution of the delays, the new type of system model with probability-distribution-dependent parameter matrices is proposed. Based on the stochastic analysis techniques and the properties of the Kronecker product, delay-dependent synchronization stability criteria in the mean square are derived in the form of linear matrix inequalities which can be readily solved by using the LMI toolbox in MATLAB, the solvability of derived conditions depends on not only the size of the delay, but also the probability of the delay-taking values in some intervals. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the proposed method.
International Nuclear Information System (INIS)
D'Oliveira, A.B.; Amorim, E.S. do; Galvao, O.B.
1981-03-01
Double differential cross sections for thermal neutrons, based on incoherent approximation, using continum distribution as discrete frequency set are theoretically estimated, regarding two models previously done. The FASTT computer program is used in order to obtain a numerical estimation. (L.C.) [pt
Verkruysse, W.; Lucassen, G. W.; de Boer, J. F.; Smithies, D. J.; Nelson, J. S.; van Gemert, M. J.
1997-01-01
Laser treatment of port wine stains has often been modelled assuming that blood is distributed homogeneously over the dermal volume, instead of enclosed within discrete vessels. The purpose of this paper is to analyse the consequences of this assumption. Due to strong light absorption by blood,
International Nuclear Information System (INIS)
Žukovič, Milan; Hristopulos, Dionissios T
2009-01-01
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 N c -state Potts model, each point is assigned to one of N c 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
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
Evaluation of angular distributions and production cross-sections for discrete gamma lines in iron
International Nuclear Information System (INIS)
Savin, M.V.; Livke, A.V.; Zvenigorodskij, A.G.
2001-01-01
The experimental data were compiled and the angular distributions and production cross-sections for the E γ = 846.8, 1238.3 and 1810.8 keV discrete gamma-lines evaluated. The Legendre polynomial coefficients describing the angular distributions in the energy range up to E n = 14.0 MeV and cross-section values in the E n = 0.85-19.0 MeV range were evaluated. (author)
Lower limits for distribution tails of randomly stopped sums
Denisov, D.E.; Korshunov, D.A.; Foss, S.G.
2008-01-01
We study lower limits for the ratio $\\overline{F^{*\\tau}}(x)/\\,\\overline F(x)$ of tail distributions, where $F^{*\\tau}$ is a distribution of a sum of a random size $\\tau$ of independent identically distributed random variables having a common distribution $F$, and a random variable $\\tau$ does not
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.
Nonlinear Estimation of Discrete-Time Signals Under Random Observation Delay
International Nuclear Information System (INIS)
Caballero-Aguila, R.; Jimenez-Lopez, J. D.; Hermoso-Carazo, A.; Linares-Perez, J.; Nakamori, S.
2008-01-01
This paper presents an approximation to the nonlinear least-squares estimation problem of discrete-time stochastic signals using nonlinear observations with additive white noise which can be randomly delayed by one sampling time. The observation delay is modelled by a sequence of independent Bernoulli random variables whose values, zero or one, indicate that the real observation arrives on time or it is delayed and, hence, the available measurement to estimate the signal is not up-to-date. Assuming that the state-space model generating the signal is unknown and only the covariance functions of the processes involved in the observation equation are ready for use, a filtering algorithm based on linear approximations of the real observations is proposed.
International Nuclear Information System (INIS)
Banu, L Jarina; Balasubramaniam, P
2015-01-01
This paper investigates the problem of non-fragile observer design for a class of discrete-time genetic regulatory networks (DGRNs) with time-varying delays and randomly occurring uncertainties. A non-fragile observer is designed, for estimating the true concentration of mRNAs and proteins from available measurement outputs. One important feature of the results obtained that are reported here is that the parameter uncertainties are assumed to be random and their probabilities of occurrence are known a priori. On the basis of the Lyapunov–Krasovskii functional approach and using a convex combination technique, a delay-dependent estimation criterion is established for DGRNs in terms of linear matrix inequalities (LMIs) that can be efficiently solved using any available LMI solver. Finally numerical examples are provided to substantiate the theoretical results. (paper)
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.
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.
Analysis of Discrete L2 Projection on Polynomial Spaces with Random Evaluations
Migliorati, Giovanni; Nobile, Fabio; von Schwerin, Erik; Tempone, Raul
2014-01-01
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.
Supervisor Localization: A Top-Down Approach to Distributed Control of Discrete-Event Systems
International Nuclear Information System (INIS)
Cai, K.; Wonham, W. M.
2009-01-01
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.
International Nuclear Information System (INIS)
Humbert, Ph.
2005-01-01
In this paper we consider the probability distribution of neutrons in a multiplying assembly. The problem is studied using a space independent one group neutron point reactor model without delayed neutrons. We recall the generating function methodology and analytical results obtained by G.I. Bell when the c 2 approximation is used and we present numerical solutions in the general case, without this approximation. The neutron source induced distribution is calculated using the single initial neutron distribution which satisfies a master (Kolmogorov backward) equation. This equation is solved using the generating function method. The generating function satisfies a differential equation and the probability distribution is derived by inversion of the generating function. Numerical results are obtained using the same methodology where the generating function is the Fourier transform of the probability distribution. Discrete Fourier transforms are used to calculate the discrete time dependent distributions and continuous Fourier transforms are used to calculate the asymptotic continuous probability distributions. Numerical applications are presented to illustrate the method. (author)
International Nuclear Information System (INIS)
Park, Ju H.
2007-01-01
This paper considers the robust stability analysis of cellular neural networks with discrete and distributed delays. Based on the Lyapunov stability theory and linear matrix inequality (LMI) technique, a novel stability criterion guaranteeing the global robust convergence of the equilibrium point is derived. The criterion can be solved easily by various convex optimization algorithms. An example is given to illustrate the usefulness of our results
On minimum divergence adaptation of discrete bivariate distributions to given marginals
Czech Academy of Sciences Publication Activity Database
Vajda, Igor; van der Meulen, E. C.
2005-01-01
Roč. 51, č. 1 (2005), s. 313-320 ISSN 0018-9448 R&D Projects: GA ČR GA201/02/1391; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : approximation of contingency tables * bivariate discrete distributions * minimization of divergences Subject RIV: BD - Theory of Information Impact factor: 2.183, year: 2005
On global stability criterion for neural networks with discrete and distributed delays
International Nuclear Information System (INIS)
Park, Ju H.
2006-01-01
Based on the Lyapunov functional stability analysis for differential equations and the linear matrix inequality (LMI) optimization approach, a new delay-dependent criterion for neural networks with discrete and distributed delays is derived to guarantee global asymptotic stability. The criterion is expressed in terms of LMIs, which can be solved easily by various convex optimization algorithms. Some numerical examples are given to show the effectiveness of proposed method
Ippolito, L. J., Jr.
1977-01-01
The multiple scattering effects on wave propagation through a volume of discrete scatterers were investigated. The mean field and intensity for a distribution of scatterers was developed using a discrete random media formulation, and second order series expansions for the mean field and total intensity derived for one-dimensional and three-dimensional configurations. The volume distribution results were shown to proceed directly from the one-dimensional results. The multiple scattering intensity expansion was compared to the classical single scattering intensity and the classical result was found to represent only the first three terms in the total intensity expansion. The Foldy approximation to the mean field was applied to develop the coherent intensity, and was found to exactly represent all coherent terms of the total intensity.
Random vs. Combinatorial Methods for Discrete Event Simulation of a Grid Computer Network
Kuhn, D. Richard; Kacker, Raghu; Lei, Yu
2010-01-01
This study compared random and t-way combinatorial inputs of a network simulator, to determine if these two approaches produce significantly different deadlock detection for varying network configurations. Modeling deadlock detection is important for analyzing configuration changes that could inadvertently degrade network operations, or to determine modifications that could be made by attackers to deliberately induce deadlock. Discrete event simulation of a network may be conducted using random generation, of inputs. In this study, we compare random with combinatorial generation of inputs. Combinatorial (or t-way) testing requires every combination of any t parameter values to be covered by at least one test. Combinatorial methods can be highly effective because empirical data suggest that nearly all failures involve the interaction of a small number of parameters (1 to 6). Thus, for example, if all deadlocks involve at most 5-way interactions between n parameters, then exhaustive testing of all n-way interactions adds no additional information that would not be obtained by testing all 5-way interactions. While the maximum degree of interaction between parameters involved in the deadlocks clearly cannot be known in advance, covering all t-way interactions may be more efficient than using random generation of inputs. In this study we tested this hypothesis for t = 2, 3, and 4 for deadlock detection in a network simulation. Achieving the same degree of coverage provided by 4-way tests would have required approximately 3.2 times as many random tests; thus combinatorial methods were more efficient for detecting deadlocks involving a higher degree of interactions. The paper reviews explanations for these results and implications for modeling and simulation.
Fast state estimation subject to random data loss in discrete-time nonlinear stochastic systems
Mahdi Alavi, S. M.; Saif, Mehrdad
2013-12-01
This paper focuses on the design of the standard observer in discrete-time nonlinear stochastic systems subject to random data loss. By the assumption that the system response is incrementally bounded, two sufficient conditions are subsequently derived that guarantee exponential mean-square stability and fast convergence of the estimation error for the problem at hand. An efficient algorithm is also presented to obtain the observer gain. Finally, the proposed methodology is employed for monitoring the Continuous Stirred Tank Reactor (CSTR) via a wireless communication network. The effectiveness of the designed observer is extensively assessed by using an experimental tested-bed that has been fabricated for performance evaluation of the over wireless-network estimation techniques under realistic radio channel conditions.
Directory of Open Access Journals (Sweden)
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.
Non-uniform approximations for sums of discrete m-dependent random variables
Vellaisamy, P.; Cekanavicius, V.
2013-01-01
Non-uniform estimates are obtained for Poisson, compound Poisson, translated Poisson, negative binomial and binomial approximations to sums of of m-dependent integer-valued random variables. Estimates for Wasserstein metric also follow easily from our results. The results are then exemplified by the approximation of Poisson binomial distribution, 2-runs and $m$-dependent $(k_1,k_2)$-events.
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.
Directory of Open Access Journals (Sweden)
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.
International Nuclear Information System (INIS)
Doebrich, Marcus; Markstaller, Klaus; Karmrodt, Jens; Kauczor, Hans-Ulrich; Eberle, Balthasar; Weiler, Norbert; Thelen, Manfred; Schreiber, Wolfgang G
2005-01-01
In this study, an algorithm was developed to measure the distribution of pulmonary time constants (TCs) from dynamic computed tomography (CT) data sets during a sudden airway pressure step up. Simulations with synthetic data were performed to test the methodology as well as the influence of experimental noise. Furthermore the algorithm was applied to in vivo data. In five pigs sudden changes in airway pressure were imposed during dynamic CT acquisition in healthy lungs and in a saline lavage ARDS model. The fractional gas content in the imaged slice (FGC) was calculated by density measurements for each CT image. Temporal variations of the FGC were analysed assuming a model with a continuous distribution of exponentially decaying time constants. The simulations proved the feasibility of the method. The influence of experimental noise could be well evaluated. Analysis of the in vivo data showed that in healthy lungs ventilation processes can be more likely characterized by discrete TCs whereas in ARDS lungs continuous distributions of TCs are observed. The temporal behaviour of lung inflation and deflation can be characterized objectively using the described new methodology. This study indicates that continuous distributions of TCs reflect lung ventilation mechanics more accurately compared to discrete TCs
Egan, Raphael; Gibou, Frédéric
2017-10-01
We present a discretization method for the multidimensional Dirac distribution. We show its applicability in the context of integration problems, and for discretizing Dirac-distributed source terms in Poisson equations with constant or variable diffusion coefficients. The discretization is cell-based and can thus be applied in a straightforward fashion to Quadtree/Octree grids. The method produces second-order accurate results for integration. Superlinear convergence is observed when it is used to model Dirac-distributed source terms in Poisson equations: the observed order of convergence is 2 or slightly smaller. The method is consistent with the discretization of Dirac delta distribution for codimension one surfaces presented in [1,2]. We present Quadtree/Octree construction procedures to preserve convergence and present various numerical examples, including multi-scale problems that are intractable with uniform grids.
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...
Robust DEA under discrete uncertain data: a case study of Iranian electricity distribution companies
Hafezalkotob, Ashkan; Haji-Sami, Elham; Omrani, Hashem
2015-06-01
Crisp input and output data are fundamentally indispensable in traditional data envelopment analysis (DEA). However, the real-world problems often deal with imprecise or ambiguous data. In this paper, we propose a novel robust data envelopment model (RDEA) to investigate the efficiencies of decision-making units (DMU) when there are discrete uncertain input and output data. The method is based upon the discrete robust optimization approaches proposed by Mulvey et al. (1995) that utilizes probable scenarios to capture the effect of ambiguous data in the case study. Our primary concern in this research is evaluating electricity distribution companies under uncertainty about input/output data. To illustrate the ability of proposed model, a numerical example of 38 Iranian electricity distribution companies is investigated. There are a large amount ambiguous data about these companies. Some electricity distribution companies may not report clear and real statistics to the government. Thus, it is needed to utilize a prominent approach to deal with this uncertainty. The results reveal that the RDEA model is suitable and reliable for target setting based on decision makers (DM's) preferences when there are uncertain input/output data.
International Nuclear Information System (INIS)
Schmidt, Jürgen M.
2012-01-01
Two commonly employed angular-mobility models for describing amino-acid side-chain χ 1 torsion conformation, the staggered-rotamer jump and the normal probability density, are discussed and performance differences in applications to scalar-coupling data interpretation highlighted. Both models differ in their distinct statistical concepts, representing discrete and continuous angle distributions, respectively. Circular statistics, introduced for describing torsion-angle distributions by using a universal circular order parameter central to all models, suggest another distribution of the continuous class, here referred to as the elliptic model. Characteristic of the elliptic model is that order parameter and circular variance form complementary moduli. Transformations between the parameter sets that describe the probability density functions underlying the different models are provided. Numerical aspects of parameter optimization are considered. The issues are typified by using a set of χ 1 related 3 J coupling constants available for FK506-binding protein. The discrete staggered-rotamer model is found generally to produce lower order parameters, implying elevated rotatory variability in the amino-acid side chains, whereas continuous models tend to give higher order parameters that suggest comparatively less variation in angle conformations. The differences perceived regarding angular mobility are attributed to conceptually different features inherent to the models.
Cai, Hong; Long, Christopher M; DeRose, Christopher T; Boynton, Nicholas; Urayama, Junji; Camacho, Ryan; Pomerene, Andrew; Starbuck, Andrew L; Trotter, Douglas C; Davids, Paul S; Lentine, Anthony L
2017-05-29
We demonstrate a silicon photonic transceiver circuit for high-speed discrete variable quantum key distribution that employs a common structure for transmit and receive functions. The device is intended for use in polarization-based quantum cryptographic protocols, such as BB84. Our characterization indicates that the circuit can generate the four BB84 states (TE/TM/45°/135° linear polarizations) with >30 dB polarization extinction ratios and gigabit per second modulation speed, and is capable of decoding any polarization bases differing by 90° with high extinction ratios.
Chen, Guiling; Li, Dingshi; Shi, Lin; van Gaans, Onno; Verduyn Lunel, Sjoerd
2018-03-01
We present new conditions for asymptotic stability and exponential stability of a class of stochastic recurrent neural networks with discrete and distributed time varying delays. Our approach is based on the method using fixed point theory, which do not resort to any Liapunov function or Liapunov functional. Our results neither require the boundedness, monotonicity and differentiability of the activation functions nor differentiability of the time varying delays. In particular, a class of neural networks without stochastic perturbations is also considered. Examples are given to illustrate our main results.
Czech Academy of Sciences Publication Activity Database
Papež, Jan; Liesen, J.; Strakoš, Z.
2014-01-01
Roč. 449, 15 May (2014), s. 89-114 ISSN 0024-3795 R&D Projects: GA AV ČR IAA100300802; GA ČR GA201/09/0917 Grant - others:GA MŠk(CZ) LL1202; GA UK(CZ) 695612 Institutional support: RVO:67985807 Keywords : numerical solution of partial differential equations * finite element method * adaptivity * a posteriori error analysis * discretization error * algebra ic error * spatial distribution of the error Subject RIV: BA - General Mathematics Impact factor: 0.939, year: 2014
A New Distribution-Random Limit Normal Distribution
Gong, Xiaolin; Yang, Shuzhen
2013-01-01
This paper introduces a new distribution to improve tail risk modeling. Based on the classical normal distribution, we define a new distribution by a series of heat equations. Then, we use market data to verify our model.
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 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.
The randomly renewed general item and the randomly inspected item with exponential life distribution
International Nuclear Information System (INIS)
Schneeweiss, W.G.
1979-01-01
For a randomly renewed item the probability distributions of the time to failure and of the duration of down time and the expectations of these random variables are determined. Moreover, it is shown that the same theory applies to randomly checked items with exponential probability distribution of life such as electronic items. The case of periodic renewals is treated as an example. (orig.) [de
International Nuclear Information System (INIS)
Ahlstrom, S.W.; Foote, H.P.; Arnett, R.C.; Cole, C.R.; Serne, R.J.
1977-05-01
The Multicomponent Mass Transfer (MMT) Model is a generic computer code, currently in its third generation, that was developed to predict the movement of radiocontaminants in the saturated and unsaturated sediments of the Hanford Site. This model was designed to use the water movement patterns produced by the unsaturated and saturated flow models coupled with dispersion and soil-waste reaction submodels to predict contaminant transport. This report documents the theorical foundation and the numerical solution procedure of the current (third) generation of the MMT Model. The present model simulates mass transport processes using an analog referred to as the Discrete-Parcel-Random-Walk (DPRW) algorithm. The basic concepts of this solution technique are described and the advantages and disadvantages of the DPRW scheme are discussed in relation to more conventional numerical techniques such as the finite-difference and finite-element methods. Verification of the numerical algorithm is demonstrated by comparing model results with known closed-form solutions. A brief error and sensitivity analysis of the algorithm with respect to numerical parameters is also presented. A simulation of the tritium plume beneath the Hanford Site is included to illustrate the use of the model in a typical application. 32 figs
Ostashev, Vladimir E; Wilson, D Keith; Muhlestein, Michael B; Attenborough, Keith
2018-02-01
Although sound propagation in a forest is important in several applications, there are currently no rigorous yet computationally tractable prediction methods. Due to the complexity of sound scattering in a forest, it is natural to formulate the problem stochastically. In this paper, it is demonstrated that the equations for the statistical moments of the sound field propagating in a forest have the same form as those for sound propagation in a turbulent atmosphere if the scattering properties of the two media are expressed in terms of the differential scattering and total cross sections. Using the existing theories for sound propagation in a turbulent atmosphere, this analogy enables the derivation of several results for predicting forest acoustics. In particular, the second-moment parabolic equation is formulated for the spatial correlation function of the sound field propagating above an impedance ground in a forest with micrometeorology. Effective numerical techniques for solving this equation have been developed in atmospheric acoustics. In another example, formulas are obtained that describe the effect of a forest on the interference between the direct and ground-reflected waves. The formulated correspondence between wave propagation in discrete and continuous random media can also be used in other fields of physics.
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.
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.
Thomas, D.L.; Johnson, D.; Griffith, B.
2006-01-01
Modeling the probability of use of land units characterized by discrete and continuous measures, we present a Bayesian random-effects model to assess resource selection. This model provides simultaneous estimation of both individual- and population-level selection. Deviance information criterion (DIC), a Bayesian alternative to AIC that is sample-size specific, is used for model selection. Aerial radiolocation data from 76 adult female caribou (Rangifer tarandus) and calf pairs during 1 year on an Arctic coastal plain calving ground were used to illustrate models and assess population-level selection of landscape attributes, as well as individual heterogeneity of selection. Landscape attributes included elevation, NDVI (a measure of forage greenness), and land cover-type classification. Results from the first of a 2-stage model-selection procedure indicated that there is substantial heterogeneity among cow-calf pairs with respect to selection of the landscape attributes. In the second stage, selection of models with heterogeneity included indicated that at the population-level, NDVI and land cover class were significant attributes for selection of different landscapes by pairs on the calving ground. Population-level selection coefficients indicate that the pairs generally select landscapes with higher levels of NDVI, but the relationship is quadratic. The highest rate of selection occurs at values of NDVI less than the maximum observed. Results for land cover-class selections coefficients indicate that wet sedge, moist sedge, herbaceous tussock tundra, and shrub tussock tundra are selected at approximately the same rate, while alpine and sparsely vegetated landscapes are selected at a lower rate. Furthermore, the variability in selection by individual caribou for moist sedge and sparsely vegetated landscapes is large relative to the variability in selection of other land cover types. The example analysis illustrates that, while sometimes computationally intense, a
On a random area variable arising in discrete-time queues and compact directed percolation
International Nuclear Information System (INIS)
Kearney, Michael J
2004-01-01
A well-known discrete-time, single-server queueing system with mean arrival rate λ and mean departure rate μ 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(-Dx 1/2 ) for all ρ ≠ 1, where ρ ≡ λ/μ, and expressions for C and D are given. For the critical case ρ = 1 we show that Pr(A > x) ∼ C'x -1/3 , with C' also given. A simple mapping, used in the derivation, establishes a connection with compact directed percolation on a square lattice. As a corollary, therefore, we are also able to specify the large-area asymptotic behaviour of this model at all points in the phase diagram. This extends previous scaling results, which are only valid close to the percolation threshold
Study on the security of discrete-variable quantum key distribution over non-Markovian channels
International Nuclear Information System (INIS)
Huang Peng; Zhu Jun; He Guangqiang; Zeng Guihua
2012-01-01
The dynamic of the secret key rate of the discrete-variable quantum key distribution (QKD) protocol over the non-Markovian quantum channel is investigated. In particular, we calculate the secret key rate for the six-state protocol over non-Markovian depolarizing channels with coloured noise and Markovian depolarizing channels with Gaussian white noise, respectively. We find that the secure secret key rate for the non-Markovian depolarizing channel will be larger than the Markovian one under the same conditions even when their upper bounds of tolerable quantum bit error rate are equal. This indicates that this coloured noise in the non-Markovian depolarizing channel can enhance the security of communication. Moreover, we show that the secret key rate fluctuates near the secure point when the coupling strength of the system with the environment is high. The results demonstrate that the non-Markovian effects of the transmission channel can have a positive impact on the security of discrete-variable QKD. (paper)
Buchmann, J.; Cabarcas, D.; Göpfert, F.; Hülsing, A.T.; Weiden, P.; Lange, T.; Lauter, K.; Lisonek, P.
2014-01-01
Several lattice-based cryptosystems require to sample from a discrete Gaussian distribution over the integers. Existing methods to sample from such a distribution either need large amounts of memory or they are very slow. In this paper we explore a different method that allows for a flexible
A methodology for more efficient tail area sampling with discrete probability distribution
International Nuclear Information System (INIS)
Park, Sang Ryeol; Lee, Byung Ho; Kim, Tae Woon
1988-01-01
Monte Carlo Method is commonly used to observe the overall distribution and to determine the lower or upper bound value in statistical approach when direct analytical calculation is unavailable. However, this method would not be efficient if the tail area of a distribution is concerned. A new method entitled 'Two Step Tail Area Sampling' is developed, which uses the assumption of discrete probability distribution and samples only the tail area without distorting the overall distribution. This method uses two step sampling procedure. First, sampling at points separated by large intervals is done and second, sampling at points separated by small intervals is done with some check points determined at first step sampling. Comparison with Monte Carlo Method shows that the results obtained from the new method converge to analytic value faster than Monte Carlo Method if the numbers of calculation of both methods are the same. This new method is applied to DNBR (Departure from Nucleate Boiling Ratio) prediction problem in design of the pressurized light water nuclear reactor
Discrete- and finite-bandwidth-frequency distributions in nonlinear stability applications
Kuehl, Joseph J.
2017-02-01
A new "wave packet" formulation of the parabolized stability equations method is presented. This method accounts for the influence of finite-bandwidth-frequency distributions on nonlinear stability calculations. The methodology is motivated by convolution integrals and is found to appropriately represent nonlinear energy transfer between primary modes and harmonics, in particular nonlinear feedback, via a "nonlinear coupling coefficient." It is found that traditional discrete mode formulations overestimate nonlinear feedback by approximately 70%. This results in smaller maximum disturbance amplitudes than those observed experimentally. The new formulation corrects this overestimation, accounts for the generation of side lobes responsible for spectral broadening, and results in disturbance representation more consistent with the experiment than traditional formulations. A Mach 6 flared-cone example is presented.
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.
LQR-Based Optimal Distributed Cooperative Design for Linear Discrete-Time Multiagent Systems.
Zhang, Huaguang; Feng, Tao; Liang, Hongjing; Luo, Yanhong
2017-03-01
In this paper, a novel linear quadratic regulator (LQR)-based optimal distributed cooperative design method is developed for synchronization control of general linear discrete-time multiagent systems on a fixed, directed graph. Sufficient conditions are derived for synchronization, which restrict the graph eigenvalues into a bounded circular region in the complex plane. The synchronizing speed issue is also considered, and it turns out that the synchronizing region reduces as the synchronizing speed becomes faster. To obtain more desirable synchronizing capacity, the weighting matrices are selected by sufficiently utilizing the guaranteed gain margin of the optimal regulators. Based on the developed LQR-based cooperative design framework, an approximate dynamic programming technique is successfully introduced to overcome the (partially or completely) model-free cooperative design for linear multiagent systems. Finally, two numerical examples are given to illustrate the effectiveness of the proposed design methods.
Global robust stability of neural networks with multiple discrete delays and distributed delays
International Nuclear Information System (INIS)
Gao Ming; Cui Baotong
2009-01-01
The problem of global robust stability is investigated for a class of uncertain neural networks with both multiple discrete time-varying delays and distributed time-varying delays. The uncertainties are assumed to be of norm-bounded form and the activation functions are supposed to be bounded and globally Lipschitz continuous. Based on the Lyapunov stability theory and linear matrix inequality technique, some robust stability conditions guaranteeing the global robust convergence of the equilibrium point are derived. The proposed LMI-based criteria are computationally efficient as they can be easily checked by using recently developed algorithms in solving LMIs. Two examples are given to show the effectiveness of the proposed results.
Distribution functions for fluids in random media
International Nuclear Information System (INIS)
Madden, W.G.; Glandt, E.D.
1988-01-01
A random medium is considered, composed of identifiable interactive sites or obstacles equilibrated at a high temperature and then quenched rapidly to form a rigid structure, statistically homogeneous on all but molecular length scales. The equilibrium statistical mechanics of a fluid contained inside this quenched medium is discussed. Various particle-particle and particle-obstacle correlation functions, which differ form the corresponding functions for a fully equilibrated binary mixture, are defined through an averaging process over the static ensemble of obstacle configurations and applications of topological reduction techniques. The Ornstein-Zernike equations also differ from their equilibrium counterparts
Eigenvalue distribution of large random matrices
Pastur, Leonid
2011-01-01
Random matrix theory is a wide and growing field with a variety of concepts, results, and techniques and a vast range of applications in mathematics and the related sciences. The book, written by well-known experts, offers beginners a fairly balanced collection of basic facts and methods (Part 1 on classical ensembles) and presents experts with an exposition of recent advances in the subject (Parts 2 and 3 on invariant ensembles and ensembles with independent entries). The text includes many of the authors' results and methods on several main aspects of the theory, thus allowing them to present a unique and personal perspective on the subject and to cover many topics using a unified approach essentially based on the Stieltjes transform and orthogonal polynomials. The exposition is supplemented by numerous comments, remarks, and problems. This results in a book that presents a detailed and self-contained treatment of the basic random matrix ensembles and asymptotic regimes. This book will be an important refer...
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.
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.
Distributed authentication for randomly compromised networks
International Nuclear Information System (INIS)
Beals, Travis R; Hynes, Kevin P; Sanders, Barry C
2009-01-01
We introduce a simple, practical approach with probabilistic information-theoretic security to solve one of quantum key distribution's major security weaknesses: the requirement of an authenticated classical channel to prevent man-in-the-middle attacks. Our scheme employs classical secret sharing and partially trusted intermediaries to provide arbitrarily high confidence in the security of the protocol. Although certain failures elude detection, we discuss preemptive strategies to reduce the probability of failure to an arbitrarily small level: the probability of such failures is exponentially suppressed with increases in connectivity (i.e. connections per node).
Bekkouche, Toufik; Bouguezel, Saad
2018-03-01
We propose a real-to-real image encryption method. It is a double random amplitude encryption method based on the parametric discrete Fourier transform coupled with chaotic maps to perform the scrambling. The main idea behind this method is the introduction of a complex-to-real conversion by exploiting the inherent symmetry property of the transform in the case of real-valued sequences. This conversion allows the encrypted image to be real-valued instead of being a complex-valued image as in all existing double random phase encryption methods. The advantage is to store or transmit only one image instead of two images (real and imaginary parts). Computer simulation results and comparisons with the existing double random amplitude encryption methods are provided for peak signal-to-noise ratio, correlation coefficient, histogram analysis, and key sensitivity.
Random distribution of nucleoli in metabolic cells
Energy Technology Data Exchange (ETDEWEB)
Beckman, R.J.; Waterman, M.S.
1977-01-01
Hasofer (1974) has studied a probabilistic model for the fusion of nucleoli in metabolic cells. The nucleoli are uniformly distributed at points in the nucleus, assumed to be a sphere. The nucleoli grow from a point to a maximum size during interphase, and fusion is said to occur if the nucleoli touch. For this model, Hasofer calculated the probability of fusion and found it much smaller than experimental data would indicate. Experimental data of this type is taken by use of a microscope where a two-dimensional view or projection of the three-dimensional cell is obtained. Hasofer implicitly assumes that actual fusion can be distinguished from the case where the two nucleoli do not touch but their two-dimensional projections overlap. It is assumed, in this letter, that these two cases cannot be distinguished. The probability obtained by Beckman and Waterman is larger than Hasofer's and a much better fit to the experimental data is obtained. Even if true fusion can be unfailingly distinguished from overlap of the two-dimensional projections, it is hoped that these calculations will allow someone to propose the correct (non-uniform) model. It is concluded, for the assumptions used, that there is not sufficient evidence to reject the hypothesis of uniform distribution of the nucleoli.
CSIR Research Space (South Africa)
Van Aardt, JAN
2012-07-01
Full Text Available The goals of the study were to (i) determine if there is a direct relationship between waveform LiDAR intensity-by-height and discrete return frequency-by-height (do the distributions match?) and (ii) assess the impact of scale (does...
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.
Fully-distributed randomized cooperation in wireless sensor networks
Bader, Ahmed; Abed-Meraim, Karim; Alouini, Mohamed-Slim
2015-01-01
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.
Global stability of stochastic high-order neural networks with discrete and distributed delays
International Nuclear Information System (INIS)
Wang Zidong; Fang Jianan; Liu Xiaohui
2008-01-01
High-order neural networks can be considered as an expansion of Hopfield neural networks, and have stronger approximation property, faster convergence rate, greater storage capacity, and higher fault tolerance than lower-order neural networks. In this paper, the global asymptotic stability analysis problem is considered for a class of stochastic high-order neural networks with discrete and distributed time-delays. Based on an Lyapunov-Krasovskii functional and the stochastic stability analysis theory, several sufficient conditions are derived, which guarantee the global asymptotic convergence of the equilibrium point in the mean square. It is shown that the stochastic high-order delayed neural networks under consideration are globally asymptotically stable in the mean square if two linear matrix inequalities (LMIs) are feasible, where the feasibility of LMIs can be readily checked by the Matlab LMI toolbox. It is also shown that the main results in this paper cover some recently published works. A numerical example is given to demonstrate the usefulness of the proposed global stability criteria
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.
Polyakov, Pavel D; Duval, Jérôme F L
2014-02-07
We report a comprehensive theory to evaluate the kinetics of complex formation between metal ions and charged spherical nanoparticles. The latter consist of an ion-impermeable core surrounded by a soft shell layer characterized by a discrete axisymmetric 2D distribution of charged sites that bind metal ions. The theory explicitly integrates the conductive diffusion of metal ions from bulk solution toward the respective locations of the reactive sites within the particle shell volume. The kinetic constant k for outer-sphere nanoparticle-metal association is obtained from the sum of the contributions stemming from all reactive sites, each evaluated from the corresponding incoming flux of metal ions derived from steady-state Poisson-Nernst-Planck equations. Illustrations are provided to capture the basic intertwined impacts of particle size, overall particle charge, spatial heterogeneity in site distribution, type of particle (hard, core-shell or porous) and concentration of the background electrolyte on k. As a limit, k converges with predictions from previously reported analytical expressions derived for porous particles with low and high charge density, cases that correspond to coulombic and mean-field (smeared-out) electrostatic treatments, respectively. The conditions underlying the applicability of these latter approaches are rigorously identified in terms of (i) the extent of overlap between electric double layers around charged neighbouring sites, and (ii) the magnitude of the intraparticulate metal concentration gradient. For the first time, the proposed theory integrates the differentiated impact of the local potential around the charged binding sites amidst the overall particle field, together with that of the so-far discarded intraparticulate flux of metal ions.
Energy Technology Data Exchange (ETDEWEB)
Vanderbei, Robert J., E-mail: rvdb@princeton.edu [Princeton University, Department of Operations Research and Financial Engineering (United States); P Latin-Small-Letter-Dotless-I nar, Mustafa C., E-mail: mustafap@bilkent.edu.tr [Bilkent University, Department of Industrial Engineering (Turkey); Bozkaya, Efe B. [Sabanc Latin-Small-Letter-Dotless-I University, Faculty of Administrative Sciences (Turkey)
2013-02-15
An American option (or, warrant) is the right, but not the obligation, to purchase or sell an underlying equity at any time up to a predetermined expiration date for a predetermined amount. A perpetual American option differs from a plain American option in that it does not expire. In this study, we solve the optimal stopping problem of a perpetual American option (both call and put) in discrete time using linear programming duality. Under the assumption that the underlying stock price follows a discrete time and discrete state Markov process, namely a geometric random walk, we formulate the pricing problem as an infinite dimensional linear programming (LP) problem using the excessive-majorant property of the value function. This formulation allows us to solve complementary slackness conditions in closed-form, revealing an optimal stopping strategy which highlights the set of stock-prices where the option should be exercised. The analysis for the call option reveals that such a critical value exists only in some cases, depending on a combination of state-transition probabilities and the economic discount factor (i.e., the prevailing interest rate) whereas it ceases to be an issue for the put.
International Nuclear Information System (INIS)
Vanderbei, Robert J.; Pınar, Mustafa Ç.; Bozkaya, Efe B.
2013-01-01
An American option (or, warrant) is the right, but not the obligation, to purchase or sell an underlying equity at any time up to a predetermined expiration date for a predetermined amount. A perpetual American option differs from a plain American option in that it does not expire. In this study, we solve the optimal stopping problem of a perpetual American option (both call and put) in discrete time using linear programming duality. Under the assumption that the underlying stock price follows a discrete time and discrete state Markov process, namely a geometric random walk, we formulate the pricing problem as an infinite dimensional linear programming (LP) problem using the excessive-majorant property of the value function. This formulation allows us to solve complementary slackness conditions in closed-form, revealing an optimal stopping strategy which highlights the set of stock-prices where the option should be exercised. The analysis for the call option reveals that such a critical value exists only in some cases, depending on a combination of state-transition probabilities and the economic discount factor (i.e., the prevailing interest rate) whereas it ceases to be an issue for the put.
Influence of random setup error on dose distribution
International Nuclear Information System (INIS)
Zhai Zhenyu
2008-01-01
Objective: To investigate the influence of random setup error on dose distribution in radiotherapy and determine the margin from ITV to PTV. Methods: A random sample approach was used to simulate the fields position in target coordinate system. Cumulative effect of random setup error was the sum of dose distributions of all individual treatment fractions. Study of 100 cumulative effects might get shift sizes of 90% dose point position. Margins from ITV to PTV caused by random setup error were chosen by 95% probability. Spearman's correlation was used to analyze the influence of each factor. Results: The average shift sizes of 90% dose point position was 0.62, 1.84, 3.13, 4.78, 6.34 and 8.03 mm if random setup error was 1,2,3,4,5 and 6 mm,respectively. Univariate analysis showed the size of margin was associated only by the size of random setup error. Conclusions: Margin of ITV to PTV is 1.2 times random setup error for head-and-neck cancer and 1.5 times for thoracic and abdominal cancer. Field size, energy and target depth, unlike random setup error, have no relation with the size of the margin. (authors)
Randomness determines practical security of BB84 quantum key distribution
Li, Hong-Wei; Yin, Zhen-Qiang; Wang, Shuang; Qian, Yong-Jun; Chen, Wei; Guo, Guang-Can; Han, Zheng-Fu
2015-11-01
Unconditional security of the BB84 quantum key distribution protocol has been proved by exploiting the fundamental laws of quantum mechanics, but the practical quantum key distribution system maybe hacked by considering the imperfect state preparation and measurement respectively. Until now, different attacking schemes have been proposed by utilizing imperfect devices, but the general security analysis model against all of the practical attacking schemes has not been proposed. Here, we demonstrate that the general practical attacking schemes can be divided into the Trojan horse attack, strong randomness attack and weak randomness attack respectively. We prove security of BB84 protocol under randomness attacking models, and these results can be applied to guarantee the security of the practical quantum key distribution system.
Maximum Likelihood and Bayes Estimation in Randomly Censored Geometric Distribution
Directory of Open Access Journals (Sweden)
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.
The relationship between randomness and power-law distributed move lengths in random walk algorithms
Sakiyama, Tomoko; Gunji, Yukio-Pegio
2014-05-01
Recently, we proposed a new random walk algorithm, termed the REV algorithm, in which the agent alters the directional rule that governs it using the most recent four random numbers. Here, we examined how a non-bounded number, i.e., "randomness" regarding move direction, was important for optimal searching and power-law distributed step lengths in rule change. We proposed two algorithms: the REV and REV-bounded algorithms. In the REV algorithm, one of the four random numbers used to change the rule is non-bounded. In contrast, all four random numbers in the REV-bounded algorithm are bounded. We showed that the REV algorithm exhibited more consistent power-law distributed step lengths and flexible searching behavior.
Limit distributions of random walks on stochastic matrices
Indian Academy of Sciences (India)
condition that μm(P) > 0 for some positive integer m (as opposed to just 1, instead of m, considered in [1]), where μm is the ...... Limit distributions of random walks. 611. PROPOSITION 3.2. Let f be as introduced before Proposition 3.1. The probability distribution λ is the image of π by the map b ↦→ f (b). In other words, λ = ∑.
Directory of Open Access Journals (Sweden)
J. Dehotin
2008-05-01
Full Text Available Distributed hydrological models are valuable tools to derive distributed estimation of water balance components or to study the impact of land-use or climate change on water resources and water quality. In these models, the choice of an appropriate spatial discretization is a crucial issue. It is obviously linked to the available data, their spatial resolution and the dominant hydrological processes. For a given catchment and a given data set, the "optimal" spatial discretization should be adapted to the modelling objectives, as the latter determine the dominant hydrological processes considered in the modelling. For small catchments, landscape heterogeneity can be represented explicitly, whereas for large catchments such fine representation is not feasible and simplification is needed. The question is thus: is it possible to design a flexible methodology to represent landscape heterogeneity efficiently, according to the problem to be solved? This methodology should allow a controlled and objective trade-off between available data, the scale of the dominant water cycle components and the modelling objectives.
In this paper, we propose a general methodology for such catchment discretization. It is based on the use of nested discretizations. The first level of discretization is composed of the sub-catchments, organised by the river network topology. The sub-catchment variability can be described using a second level of discretizations, which is called hydro-landscape units. This level of discretization is only performed if it is consistent with the modelling objectives, the active hydrological processes and data availability. The hydro-landscapes take into account different geophysical factors such as topography, land-use, pedology, but also suitable hydrological discontinuities such as ditches, hedges, dams, etc. For numerical reasons these hydro-landscapes can be further subdivided into smaller elements that will constitute the
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.
Directory of Open Access Journals (Sweden)
Huaiqin Wu
2012-01-01
Full Text Available By combing the theories of the switched systems and the interval neural networks, the mathematics model of the switched interval neural networks with discrete and distributed time-varying delays of neural type is presented. A set of the interval parameter uncertainty neural networks with discrete and distributed time-varying delays of neural type are used as the individual subsystem, and an arbitrary switching rule is assumed to coordinate the switching between these networks. By applying the augmented Lyapunov-Krasovskii functional approach and linear matrix inequality (LMI techniques, a delay-dependent criterion is achieved to ensure to such switched interval neural networks to be globally asymptotically robustly stable in terms of LMIs. The unknown gain matrix is determined by solving this delay-dependent LMIs. Finally, an illustrative example is given to demonstrate the validity of the theoretical results.
Free energy distribution function of a random Ising ferromagnet
International Nuclear Information System (INIS)
Dotsenko, Victor; Klumov, Boris
2012-01-01
We study the free energy distribution function of a weakly disordered Ising ferromagnet in terms of the D-dimensional random temperature Ginzburg–Landau Hamiltonian. It is shown that besides the usual Gaussian 'body' this distribution function exhibits non-Gaussian tails both in the paramagnetic and in the ferromagnetic phases. Explicit asymptotic expressions for these tails are derived. It is demonstrated that the tails are strongly asymmetric: the left tail (for large negative values of the free energy) is much slower than the right one (for large positive values of the free energy). It is argued that at the critical point the free energy of the random Ising ferromagnet in dimensions D < 4 is described by a non-trivial universal distribution function which is non-self-averaging
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.
A discrete spherical X-ray transform of orientation distribution functions using bounding cubes
DEFF Research Database (Denmark)
Kazantsev, Ivan G; Schmidt, Søren; Poulsen, Henning Friis
2009-01-01
We investigate a cubed sphere parametrization of orientation space with the aim of constructing a discrete voxelized version of the spherical x-ray transform. For tracing the propagation of a unit great circle through the partition subsets, the frustums of the cubed sphere, a fast procedure...
Quasi-stationary distributions for reducible absorbing Markov chains in discrete time
van Doorn, Erik A.; Pollett, P.K.
2009-01-01
We consider discrete-time Markov chains with one coffin state and a finite set $S$ of transient states, and are interested in the limiting behaviour of such a chain as time $n \\to \\infty,$ conditional on survival up to $n$. It is known that, when $S$ is irreducible, the limiting conditional
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.
International Nuclear Information System (INIS)
Lee, T.D.
1985-01-01
This paper reviews the role of time throughout all phases of mechanics: classical mechanics, non-relativistic quantum mechanics, and relativistic quantum theory. As an example of the relativistic quantum field theory, the case of a massless scalar field interacting with an arbitrary external current is discussed. The comparison between the new discrete theory and the usual continuum formalism is presented. An example is given of a two-dimensional random lattice and its duel. The author notes that there is no evidence that the discrete mechanics is more appropriate than the usual continuum mechanics
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.
Gravitational lensing by eigenvalue distributions of random matrix models
Martínez Alonso, Luis; Medina, Elena
2018-05-01
We propose to use eigenvalue densities of unitary random matrix ensembles as mass distributions in gravitational lensing. The corresponding lens equations reduce to algebraic equations in the complex plane which can be treated analytically. We prove that these models can be applied to describe lensing by systems of edge-on galaxies. We illustrate our analysis with the Gaussian and the quartic unitary matrix ensembles.
Iterative algorithm of discrete Fourier transform for processing randomly sampled NMR data sets
International Nuclear Information System (INIS)
Stanek, Jan; Kozminski, Wiktor
2010-01-01
Spectra obtained by application of multidimensional Fourier Transformation (MFT) to sparsely sampled nD NMR signals are usually corrupted due to missing data. In the present paper this phenomenon is investigated on simulations and experiments. An effective iterative algorithm for artifact suppression for sparse on-grid NMR data sets is discussed in detail. It includes automated peak recognition based on statistical methods. The results enable one to study NMR spectra of high dynamic range of peak intensities preserving benefits of random sampling, namely the superior resolution in indirectly measured dimensions. Experimental examples include 3D 15 N- and 13 C-edited NOESY-HSQC spectra of human ubiquitin.
Random generation of RNA secondary structures according to native distributions
Directory of Open Access Journals (Sweden)
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
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.
International Nuclear Information System (INIS)
Ali, M. Syed
2014-01-01
In this paper, the global asymptotic stability problem of Markovian jumping stochastic Cohen—Grossberg neural networks with discrete and distributed time-varying delays (MJSCGNNs) is considered. A novel LMI-based stability criterion is obtained by constructing a new Lyapunov functional to guarantee the asymptotic stability of MJSCGNNs. Our results can be easily verified and they are also less restrictive than previously known criteria and can be applied to Cohen—Grossberg neural networks, recurrent neural networks, and cellular neural networks. Finally, the proposed stability conditions are demonstrated with numerical examples
International Nuclear Information System (INIS)
Chen, J.-D.
2007-01-01
In this paper, the robust control problem of output dynamic observer-based control for a class of uncertain neutral systems with discrete and distributed time delays is considered. Linear matrix inequality (LMI) optimization approach is used to design the new output dynamic observer-based controls. Three classes of observer-based controls are proposed and the maximal perturbed bound is given. Based on the results of this paper, the constraint of matrix equality is not necessary for designing the observer-based controls. Finally, a numerical example is given to illustrate the usefulness of the proposed method
Exarchakis, Georgios; Lücke, Jörg
2017-11-01
Sparse coding algorithms with continuous latent variables have been the subject of a large number of studies. However, discrete latent spaces for sparse coding have been largely ignored. In this work, we study sparse coding with latents described by discrete instead of continuous prior distributions. We consider the general case in which the latents (while being sparse) can take on any value of a finite set of possible values and in which we learn the prior probability of any value from data. This approach can be applied to any data generated by discrete causes, and it can be applied as an approximation of continuous causes. As the prior probabilities are learned, the approach then allows for estimating the prior shape without assuming specific functional forms. To efficiently train the parameters of our probabilistic generative model, we apply a truncated expectation-maximization approach (expectation truncation) that we modify to work with a general discrete prior. We evaluate the performance of the algorithm by applying it to a variety of tasks: (1) we use artificial data to verify that the algorithm can recover the generating parameters from a random initialization, (2) use image patches of natural images and discuss the role of the prior for the extraction of image components, (3) use extracellular recordings of neurons to present a novel method of analysis for spiking neurons that includes an intuitive discretization strategy, and (4) apply the algorithm on the task of encoding audio waveforms of human speech. The diverse set of numerical experiments presented in this letter suggests that discrete sparse coding algorithms can scale efficiently to work with realistic data sets and provide novel statistical quantities to describe the structure of the data.
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.
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.
Hessian eigenvalue distribution in a random Gaussian landscape
Yamada, Masaki; Vilenkin, Alexander
2018-03-01
The energy landscape of multiverse cosmology is often modeled by a multi-dimensional random Gaussian potential. The physical predictions of such models crucially depend on the eigenvalue distribution of the Hessian matrix at potential minima. In particular, the stability of vacua and the dynamics of slow-roll inflation are sensitive to the magnitude of the smallest eigenvalues. The Hessian eigenvalue distribution has been studied earlier, using the saddle point approximation, in the leading order of 1/ N expansion, where N is the dimensionality of the landscape. This approximation, however, is insufficient for the small eigenvalue end of the spectrum, where sub-leading terms play a significant role. We extend the saddle point method to account for the sub-leading contributions. We also develop a new approach, where the eigenvalue distribution is found as an equilibrium distribution at the endpoint of a stochastic process (Dyson Brownian motion). The results of the two approaches are consistent in cases where both methods are applicable. We discuss the implications of our results for vacuum stability and slow-roll inflation in the landscape.
Three dimensional multi perspective imaging with randomly distributed sensors
International Nuclear Information System (INIS)
DaneshPanah, Mehdi; Javidi, Bahrain
2008-01-01
In this paper, we review a three dimensional (3D) passive imaging system that exploits the visual information captured from the scene from multiple perspectives to reconstruct the scene voxel by voxel in 3D space. The primary contribution of this work is to provide a computational reconstruction scheme based on randomly distributed sensor locations in space. In virtually all of multi perspective techniques (e.g. integral imaging, synthetic aperture integral imaging, etc), there is an implicit assumption that the sensors lie on a simple, regular pickup grid. Here, we relax this assumption and suggest a computational reconstruction framework that unifies the available methods as its special cases. The importance of this work is that it enables three dimensional imaging technology to be implemented in a multitude of novel application domains such as 3D aerial imaging, collaborative imaging, long range 3D imaging and etc, where sustaining a regular pickup grid is not possible and/or the parallax requirements call for a irregular or sparse synthetic aperture mode. Although the sensors can be distributed in any random arrangement, we assume that the pickup position is measured at the time of capture of each elemental image. We demonstrate the feasibility of the methods proposed here by experimental results.
Global and local consistencies in distributed fault diagnosis for discrete-event systems
Su, R.; Wonham, W.M.
2005-01-01
In this paper, we present a unified framework for distributed diagnosis. We first introduce the concepts of global and local consistency in terms of supremal global and local supports, then present two distributed diagnosis problems based on them. After that, we provide algorithms to achieve
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, Pimpact 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.
Yu, Han; Douglas, Craig C.
2014-01-01
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.
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.
2014-09-18
researcher discovered issues that affected the research. The most important of 19 these was the lack of advanced math functions in the DEVS- JAVA ...to install a comparative JAVA -language scientific library. This issue was reported to RTSync, but there was no fix to this issue during the research...and tracking systems necessary to deal with high relative angular motion. random motion of the platforms. and atmospheric turbulence that would be
Fitting and Analyzing Randomly Censored Geometric Extreme Exponential Distribution
Directory of Open Access Journals (Sweden)
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.
Smooth conditional distribution function and quantiles under random censorship.
Leconte, Eve; Poiraud-Casanova, Sandrine; Thomas-Agnan, Christine
2002-09-01
We consider a nonparametric random design regression model in which the response variable is possibly right censored. The aim of this paper is to estimate the conditional distribution function and the conditional alpha-quantile of the response variable. We restrict attention to the case where the response variable as well as the explanatory variable are unidimensional and continuous. We propose and discuss two classes of estimators which are smooth with respect to the response variable as well as to the covariate. Some simulations demonstrate that the new methods have better mean square error performances than the generalized Kaplan-Meier estimator introduced by Beran (1981) and considered in the literature by Dabrowska (1989, 1992) and Gonzalez-Manteiga and Cadarso-Suarez (1994).
International Nuclear Information System (INIS)
Shah, S.A.; Shah, W.; Shaikh, F.K.
2012-01-01
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 hypo geometrically 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. (author)
International Nuclear Information System (INIS)
Konopka, Ladislav; Kosek, Juraj
2015-01-01
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. (paper)
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
Models for randomly distributed nanoscopic domains on spherical vesicles
Anghel, Vinicius N. P.; Bolmatov, Dima; Katsaras, John
2018-06-01
The existence of lipid domains in the plasma membrane of biological systems has proven controversial, primarily due to their nanoscopic size—a length scale difficult to interrogate with most commonly used experimental techniques. Scattering techniques have recently proven capable of studying nanoscopic lipid domains populating spherical vesicles. However, the development of analytical methods able of predicting and analyzing domain pair correlations from such experiments has not kept pace. Here, we developed models for the random distribution of monodisperse, circular nanoscopic domains averaged on the surface of a spherical vesicle. Specifically, the models take into account (i) intradomain correlations corresponding to form factors and interdomain correlations corresponding to pair distribution functions, and (ii) the analytical computation of interdomain correlations for cases of two and three domains on a spherical vesicle. In the case of more than three domains, these correlations are treated either by Monte Carlo simulations or by spherical analogs of the Ornstein-Zernike and Percus-Yevick (PY) equations. Importantly, the spherical analog of the PY equation works best in the case of nanoscopic size domains, a length scale that is mostly inaccessible by experimental approaches such as, for example, fluorescent techniques and optical microscopies. The analytical form factors and structure factors of nanoscopic domains populating a spherical vesicle provide a new and important framework for the quantitative analysis of experimental data from commonly studied phase-separated vesicles used in a wide range of biophysical studies.
Neutron distribution modeling based on integro-probabilistic approach of discrete ordinates method
International Nuclear Information System (INIS)
Khromov, V.V.; Kryuchkov, E.F.; Tikhomirov, G.V.
1992-01-01
In this paper is described the universal nodal method for the neutron distribution calculation in reactor and shielding problems, based on using of influence functions and factors of local-integrated volume and surface neutron sources in phase subregions. This method permits to avoid the limited capabilities of collision-probability method concerning with the detailed calculation of angular neutron flux dependence, scattering anisotropy and empty channels. The proposed method may be considered as modification of S n - method with advantage of ray-effects elimination. There are presented the description of method theory and algorithm following by the examples of method applications for calculation of neutron distribution in three-dimensional model of fusion reactor blanket and in highly heterogeneous reactor with empty channel
Aichinger, Ida; Larcher, Gerhard; Kersevan, Roberto
2017-01-01
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-induc...
International Nuclear Information System (INIS)
Scherpelz, R.I.; MacLellan, J.A.
1987-09-01
The Pacific Northwest Laboratory (PNL) is sending a torso phantom with radioactive material uniformly distributed in the lungs to in vivo bioassay laboratories for analysis. Although the radionuclides ultimately chosen for the studies had relatively long half-lives, future accreditation testing will require repeated tests with short half-life test nuclides. Computer modeling was used to simulate the major components of the phantom. Radiation transport calculations were then performed using the computer models to calculate dose rates either 15 cm from the chest or at its surface. For 144 Ce and 60 Co, three configurations were used for the lung comparison tests. Calculations show that, for most detector positions, a single plug containing 40 K located in the back of the heart provides a good approximation to a uniform distribution of 40 K. The approximation would lead, however, to a positive bias for the detector reading if the detector were located at the chest surface near the center. Loading the 40 K in a uniform layer inside the chest wall is not a good approximation of the uniform distribution in the lungs, because most of the radionuclides would be situated close to the detector location and the only shielding would be the thickness of the chest wall. The calculated dose rates for 60 Co and 144 Ce were similar at all calculated reference points. 3 refs., 5 figs., 10 tabs
Zero-inflated Conway-Maxwell Poisson Distribution to Analyze Discrete Data.
Sim, Shin Zhu; Gupta, Ramesh C; Ong, Seng Huat
2018-01-09
In this paper, we study the zero-inflated Conway-Maxwell Poisson (ZICMP) distribution and develop a regression model. Score and likelihood ratio tests are also implemented for testing the inflation/deflation parameter. Simulation studies are carried out to examine the performance of these tests. A data example is presented to illustrate the concepts. In this example, the proposed model is compared to the well-known zero-inflated Poisson (ZIP) and the zero- inflated generalized Poisson (ZIGP) regression models. It is shown that the fit by ZICMP is comparable or better than these models.
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.
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...
Asymptotic distribution of products of sums of independent random ...
Indian Academy of Sciences (India)
integrable random variables (r.v.) are asymptotically log-normal. This fact ... the product of the partial sums of i.i.d. positive random variables as follows. .... Now define ..... by Henan Province Foundation and Frontier Technology Research Plan.
Krishnasamy, M.; Qian, Feng; Zuo, Lei; Lenka, T. R.
2018-03-01
The charge cancellation due to the change of strain along single continuous piezoelectric layer can remarkably affect the performance of a cantilever based harvester. In this paper, analytical models using distributed parameters are developed with some extent of averting the charge cancellation in cantilever piezoelectric transducer where the piezoelectric layers are segmented at strain nodes of concerned vibration mode. The electrode of piezoelectric segments are parallelly connected with a single external resistive load in the 1st model (Model 1). While each bimorph piezoelectric layers are connected in parallel to a resistor to form an independent circuit in the 2nd model (Model 2). The analytical expressions of the closed-form electromechanical coupling responses in frequency domain under harmonic base excitation are derived based on the Euler-Bernoulli beam assumption for both models. The developed analytical models are validated by COMSOL and experimental results. The results demonstrate that the energy harvesting performance of the developed segmented piezoelectric layer models is better than the traditional model of continuous piezoelectric layer.
International Nuclear Information System (INIS)
Kantorovich, L.N.; Fogel, G.M.; Gotlib, V.I.
1990-01-01
Thermoluminescence kinetics is discussed within the framework of a band model containing an arbitrary number of types of recombination and trapping centres at an arbitrary correlation of all centre parameters. It is shown that the initial system of kinetic equations is reduced to an equivalent system consisting of two integro-differential equations which permit one to perform an accurate generalisation, in the case of a continuous centre distribution, to their parameters for the description of irradiation and thermoluminescence, taking into account charge carrier redistribution to both types of centre. In addition, if only one electron (hole) channel is taken into account, only one integro-differential equation is obtained. On the basis of this equation a precise algebraic equation is obtained for calculation of the area of an arbitrary part of the thermoluminescence curve (TLC), consisting of one or several peaks, which slightly overlap with other peaks. It is shown that at doses which are less than the saturation dose, when the centres are not completely filled by the charge carriers, the dose dependences of such a part of the TLC may have a non-linear character at a simultaneous linear dependence of the area of the whole TLC. At doses which are greater than the saturation dose, the dose dependences of the area of the whole TLC, as well as of its separate parts, undergo breaks at the saturation doses. (author)
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
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...
International Nuclear Information System (INIS)
Mejlikhov, E.Z.; Farzetdinova, R.M.
1997-01-01
Critical current of inhomogeneous intergranular Josephson transition is calculated in the assumption concerning superconductivity suppression by local strains of boundary dislocations with random distribution
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.
International Nuclear Information System (INIS)
Balasubramaniam, P.; Lakshmanan, S.; Manivannan, A.
2012-01-01
Highlights: ► Robust stability analysis for Markovian jumping interval neural networks is considered. ► Both linear fractional and interval uncertainties are considered. ► A new LKF is constructed with triple integral terms. ► MATLAB LMI control toolbox is used to validate theoretical results. ► Numerical examples are given to illustrate the effectiveness of the proposed method. - Abstract: This paper investigates robust stability analysis for Markovian jumping interval neural networks with discrete and distributed time-varying delays. The parameter uncertainties are assumed to be bounded in given compact sets. The delay is assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. Based on the new Lyapunov–Krasovskii functional (LKF), some inequality techniques and stochastic stability theory, new delay-dependent stability criteria have been obtained in terms of linear matrix inequalities (LMIs). Finally, two numerical examples are given to illustrate the less conservative and effectiveness of our theoretical results.
Heston, Steven L.; Nandi, Saikat
1999-01-01
This paper develops a discrete-time two-factor model of interest rates with analytical solutions for bonds and many interest rate derivatives when the volatility of the short rate follows a GARCH process that can be correlated with the level of the short rate itself. Besides bond and bond futures, the model yields analytical solutions for prices of European options on discount bonds (and futures) as well as other interest rate derivatives such as caps, floors, average rate options, yield curv...
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…
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.
International Nuclear Information System (INIS)
Granger, S.; Perotin, L.
1997-01-01
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)
A simple consensus algorithm for distributed averaging in random ...
Indian Academy of Sciences (India)
Random geographical networks are realistic models for wireless sensor ... work are cheap, unreliable, with limited computational power and limited .... signal xj from node j, j does not need to transmit its degree to i in order to let i compute.
On lower limits and equivalences for distribution tails of randomly stopped sums
Denisov, D.E.; Foss, S.G.; Korshunov, D.A.
2008-01-01
For a distribution F*t of a random sum St=¿1+¿+¿t of i.i.d. random variables with a common distribution F on the half-line [0, 8), we study the limits of the ratios of tails as x¿8 (here, t is a counting random variable which does not depend on {¿n}n=1). We also consider applications of the results
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.
Distributed Detection with Collisions in a Random, Single-Hop Wireless Sensor Network
2013-05-26
public release; distribution is unlimited. Distributed detection with collisions in a random, single-hop wireless sensor network The views, opinions...1274 2 ABSTRACT Distributed detection with collisions in a random, single-hop wireless sensor network Report Title We consider the problem of... WIRELESS SENSOR NETWORK Gene T. Whipps?† Emre Ertin† Randolph L. Moses† ?U.S. Army Research Laboratory, Adelphi, MD 20783 †The Ohio State University
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...
Zero Distribution of System with Unknown Random Variables Case Study: Avoiding Collision Path
Directory of Open Access Journals (Sweden)
Parman Setyamartana
2014-07-01
Full Text Available This paper presents the stochastic analysis of finding the feasible trajectories of robotics arm motion at obstacle surrounding. Unknown variables are coefficients of polynomials joint angle so that the collision-free motion is achieved. ãk is matrix consisting of these unknown feasible polynomial coefficients. The pattern of feasible polynomial in the obstacle environment shows as random. This paper proposes to model the pattern of this randomness values using random polynomial with unknown variables as coefficients. The behavior of the system will be obtained from zero distribution as the characteristic of such random polynomial. Results show that the pattern of random polynomial of avoiding collision can be constructed from zero distribution. Zero distribution is like building block of the system with obstacles as uncertainty factor. By scale factor k, which has range, the random coefficient pattern can be predicted.
Jia, Zhongxiao; Yang, Yanfei
2018-05-01
In this paper, we propose new randomization based algorithms for large scale linear discrete ill-posed problems with general-form regularization: subject to , where L is a regularization matrix. Our algorithms are inspired by the modified truncated singular value decomposition (MTSVD) method, which suits only for small to medium scale problems, and randomized SVD (RSVD) algorithms that generate good low rank approximations to A. We use rank-k truncated randomized SVD (TRSVD) approximations to A by truncating the rank- RSVD approximations to A, where q is an oversampling parameter. The resulting algorithms are called modified TRSVD (MTRSVD) methods. At every step, we use the LSQR algorithm to solve the resulting inner least squares problem, which is proved to become better conditioned as k increases so that LSQR converges faster. We present sharp bounds for the approximation accuracy of the RSVDs and TRSVDs for severely, moderately and mildly ill-posed problems, and substantially improve a known basic bound for TRSVD approximations. We prove how to choose the stopping tolerance for LSQR in order to guarantee that the computed and exact best regularized solutions have the same accuracy. Numerical experiments illustrate that the best regularized solutions by MTRSVD are as accurate as the ones by the truncated generalized singular value decomposition (TGSVD) algorithm, and at least as accurate as those by some existing truncated randomized generalized singular value decomposition (TRGSVD) algorithms. This work was supported in part by the National Science Foundation of China (Nos. 11771249 and 11371219).
A method for generating skewed random numbers using two overlapping uniform distributions
International Nuclear Information System (INIS)
Ermak, D.L.; Nasstrom, J.S.
1995-02-01
The objective of this work was to implement and evaluate a method for generating skewed random numbers using a combination of uniform random numbers. The method provides a simple and accurate way of generating skewed random numbers from the specified first three moments without an a priori specification of the probability density function. We describe the procedure for generating skewed random numbers from unifon-n random numbers, and show that it accurately produces random numbers with the desired first three moments over a range of skewness values. We also show that in the limit of zero skewness, the distribution of random numbers is an accurate approximation to the Gaussian probability density function. Future work win use this method to provide skewed random numbers for a Langevin equation model for diffusion in skewed turbulence
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...
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....
Fermi-dirac and random carrier distributions in quantum dot lasers
Hutchings, M.; O'Driscoll, Ian; Smowton, P. M.; Blood, P.
2014-01-01
Using experimental gain and emission measurements as functions of temperature, a method is described to characterise the carrier distribution of radiative states in a quantum dot (QD) laser structure in terms of a temperature. This method is independent of the form of the inhomogeneous dot distribution. A thermal distribution at the lattice temperature is found between 200 and 300K. Below 200K the characteristic temperature exceeds the lattice temperature and the distribution becomes random b...
Rossi, R.; Hendrix, E.M.T.
2014-01-01
We discuss the problem of computing optimal linearisation parameters for the first order loss function of a family of arbitrarily distributed random variable. We demonstrate that, in contrast to the problem in which parameters must be determined for the loss function of a single random variable,
ESEARCH OF THE LAW OF DISTRIBUTION OF THE RANDOM VARIABLE OF THE COMPRESSION
Directory of Open Access Journals (Sweden)
I. Sarayeva
2011-01-01
Full Text Available At research of diagnosing the process of modern automobile engines by means of methods of mathematical statistics the experimental data of the random variable of compression are analysed and it is proved that the random variable of compression has the form of the normal law of distribution.
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. .
On the generation of log-Levy distributions and extreme randomness
International Nuclear Information System (INIS)
Eliazar, Iddo; Klafter, Joseph
2011-01-01
The log-normal distribution is prevalent across the sciences, as it emerges from the combination of multiplicative processes and the central limit theorem (CLT). The CLT, beyond yielding the normal distribution, also yields the class of Levy distributions. The log-Levy distributions are the Levy counterparts of the log-normal distribution, they appear in the context of ultraslow diffusion processes, and they are categorized by Mandelbrot as belonging to the class of extreme randomness. In this paper, we present a natural stochastic growth model from which both the log-normal distribution and the log-Levy distributions emerge universally-the former in the case of deterministic underlying setting, and the latter in the case of stochastic underlying setting. In particular, we establish a stochastic growth model which universally generates Mandelbrot's extreme randomness. (paper)
Synchronization Techniques in Parallel Discrete Event Simulation
Lindén, Jonatan
2018-01-01
Discrete event simulation is an important tool for evaluating system models in many fields of science and engineering. To improve the performance of large-scale discrete event simulations, several techniques to parallelize discrete event simulation have been developed. In parallel discrete event simulation, the work of a single discrete event simulation is distributed over multiple processing elements. A key challenge in parallel discrete event simulation is to ensure that causally dependent ...
International Nuclear Information System (INIS)
Vlad, Valentin I.; Ionescu-Pallas, Nicholas
2000-10-01
The Planck radiation spectrum of ideal cubic and spherical cavities, in the region of small adiabatic invariance, γ = TV 1/3 , is shown to be discrete and strongly dependent on the cavity geometry and temperature. This behavior is the consequence of the random distribution of the state weights in the cubic cavity and of the random overlapping of the successive multiplet components, for the spherical cavity. The total energy (obtained by summing up the exact contributions of the eigenvalues and their weights, for low values of the adiabatic invariance) does not obey any longer Stefan-Boltzmann law. The new law includes a corrective factor depending on γ and imposes a faster decrease of the total energy to zero, for γ → 0. We have defined the double quantized regime both for cubic and spherical cavities by the superior and inferior limits put on the principal quantum numbers or the adiabatic invariance. The total energy of the double quantized cavities shows large differences from the classical calculations over unexpected large intervals, which are measurable and put in evidence important macroscopic quantum effects. (author)
Correlated random sampling for multivariate normal and log-normal distributions
International Nuclear Information System (INIS)
Žerovnik, Gašper; Trkov, Andrej; Kodeli, Ivan A.
2012-01-01
A method for correlated random sampling is presented. Representative samples for multivariate normal or log-normal distribution can be produced. Furthermore, any combination of normally and log-normally distributed correlated variables may be sampled to any requested accuracy. Possible applications of the method include sampling of resonance parameters which are used for reactor calculations.
An efficient method of randomly sampling the coherent angular scatter distribution
International Nuclear Information System (INIS)
Williamson, J.F.; Morin, R.L.
1983-01-01
Monte Carlo simulations of photon transport phenomena require random selection of an interaction process at each collision site along the photon track. Possible choices are usually limited to photoelectric absorption and incoherent scatter as approximated by the Klein-Nishina distribution. A technique is described for sampling the coherent angular scatter distribution, for the benefit of workers in medical physics. (U.K.)
Statistical distributions of optimal global alignment scores of random protein sequences
Directory of Open Access Journals (Sweden)
Tang Jiaowei
2005-10-01
Full Text Available Abstract Background The inference of homology from statistically significant sequence similarity is a central issue in sequence alignments. So far the statistical distribution function underlying the optimal global alignments has not been completely determined. Results In this study, random and real but unrelated sequences prepared in six different ways were selected as reference datasets to obtain their respective statistical distributions of global alignment scores. All alignments were carried out with the Needleman-Wunsch algorithm and optimal scores were fitted to the Gumbel, normal and gamma distributions respectively. The three-parameter gamma distribution performs the best as the theoretical distribution function of global alignment scores, as it agrees perfectly well with the distribution of alignment scores. The normal distribution also agrees well with the score distribution frequencies when the shape parameter of the gamma distribution is sufficiently large, for this is the scenario when the normal distribution can be viewed as an approximation of the gamma distribution. Conclusion We have shown that the optimal global alignment scores of random protein sequences fit the three-parameter gamma distribution function. This would be useful for the inference of homology between sequences whose relationship is unknown, through the evaluation of gamma distribution significance between sequences.
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.
Real-time definition of non-randomness in the distribution of genomic events.
Directory of Open Access Journals (Sweden)
Ulrich Abel
Full Text Available Features such as mutations or structural characteristics can be non-randomly or non-uniformly distributed within a genome. So far, computer simulations were required for statistical inferences on the distribution of sequence motifs. Here, we show that these analyses are possible using an analytical, mathematical approach. For the assessment of non-randomness, our calculations only require information including genome size, number of (sampled sequence motifs and distance parameters. We have developed computer programs evaluating our analytical formulas for the real-time determination of expected values and p-values. This approach permits a flexible cluster definition that can be applied to most effectively identify non-random or non-uniform sequence motif distribution. As an example, we show the effectivity and reliability of our mathematical approach in clinical retroviral vector integration site distribution.
Lawnik, Marcin
2018-01-01
The scope of the paper is the presentation of a new method of generating numbers from a given distribution. The method uses the inverse cumulative distribution function and a method of flattening of probabilistic distributions. On the grounds of these methods, a new construction of chaotic maps was derived, which generates values from a given distribution. The analysis of the new method was conducted on the example of a newly constructed chaotic recurrences, based on the Box-Muller transformation and the quantile function of the exponential distribution. The obtained results certify that the proposed method may be successively applicable for the construction of generators of pseudo-random numbers.
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...... 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...... to new problems. Relations and functions: Define a product set; define and apply equivalence relations; construct and apply functions. Apply these concepts to new problems. Natural numbers and induction: Define the natural numbers; apply the principle of induction to verify a selection of properties...
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...
Renault, Nisa K E; Pritchett, Sonja M; Howell, Robin E; Greer, Wenda L; Sapienza, Carmen; Ørstavik, Karen Helene; Hamilton, David C
2013-01-01
In eutherian mammals, one X-chromosome in every XX somatic cell is transcriptionally silenced through the process of X-chromosome inactivation (XCI). Females are thus functional mosaics, where some cells express genes from the paternal X, and the others from the maternal X. The relative abundance of the two cell populations (X-inactivation pattern, XIP) can have significant medical implications for some females. In mice, the ‘choice' of which X to inactivate, maternal or paternal, in each cell of the early embryo is genetically influenced. In humans, the timing of XCI choice and whether choice occurs completely randomly or under a genetic influence is debated. Here, we explore these questions by analysing the distribution of XIPs in large populations of normal females. Models were generated to predict XIP distributions resulting from completely random or genetically influenced choice. Each model describes the discrete primary distribution at the onset of XCI, and the continuous secondary distribution accounting for changes to the XIP as a result of development and ageing. Statistical methods are used to compare models with empirical data from Danish and Utah populations. A rigorous data treatment strategy maximises information content and allows for unbiased use of unphased XIP data. The Anderson–Darling goodness-of-fit statistics and likelihood ratio tests indicate that a model of genetically influenced XCI choice better fits the empirical data than models of completely random choice. PMID:23652377
Statistics for Ratios of Rayleigh, Rician, Nakagami-m, and Weibull Distributed Random Variables
Directory of Open Access Journals (Sweden)
Dragana Č. Pavlović
2013-01-01
Full Text Available The distributions of ratios of random variables are of interest in many areas of the sciences. In this brief paper, we present the joint probability density function (PDF and PDF of maximum of ratios μ1=R1/r1 and μ2=R2/r2 for the cases where R1, R2, r1, and r2 are Rayleigh, Rician, Nakagami-m, and Weibull distributed random variables. Random variables R1 and R2, as well as random variables r1 and r2, are correlated. Ascertaining on the suitability of the Weibull distribution to describe fading in both indoor and outdoor environments, special attention is dedicated to the case of Weibull random variables. For this case, analytical expressions for the joint PDF, PDF of maximum, PDF of minimum, and product moments of arbitrary number of ratios μi=Ri/ri, i=1,…,L are obtained. Random variables in numerator, Ri, as well as random variables in denominator, ri, are exponentially correlated. To the best of the authors' knowledge, analytical expressions for the PDF of minimum and product moments of {μi}i=1L are novel in the open technical literature. The proposed mathematical analysis is complemented by various numerical results. An application of presented theoretical results is illustrated with respect to performance assessment of wireless systems.
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)
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....
Fermi-dirac and random carrier distributions in quantum dot lasers
International Nuclear Information System (INIS)
Hutchings, M.; Smowton, P. M.; Blood, P.; O'Driscoll, I.
2014-01-01
Using experimental gain and emission measurements as functions of temperature, a method is described to characterise the carrier distribution of radiative states in a quantum dot (QD) laser structure in terms of a temperature. This method is independent of the form of the inhomogeneous dot distribution. A thermal distribution at the lattice temperature is found between 200 and 300 K. Below 200 K the characteristic temperature exceeds the lattice temperature and the distribution becomes random below about 60 K. This enables the temperature range for which Fermi-Dirac statistics are applicable in QD laser threshold calculations to be identified
Thompson, J. R.; Taylor, M. S.
1982-01-01
Let X be a K-dimensional random variable serving as input for a system with output Y (not necessarily of dimension k). given X, an outcome Y or a distribution of outcomes G(Y/X) may be obtained either explicitly or implicity. The situation is considered in which there is a real world data set X sub j sub = 1 (n) and a means of simulating an outcome Y. A method for empirical random number generation based on the sample of observations of the random variable X without estimating the underlying density is discussed.
An efficient algorithm for generating random number pairs drawn from a bivariate normal distribution
Campbell, C. W.
1983-01-01
An efficient algorithm for generating random number pairs from a bivariate normal distribution was developed. Any desired value of the two means, two standard deviations, and correlation coefficient can be selected. Theoretically the technique is exact and in practice its accuracy is limited only by the quality of the uniform distribution random number generator, inaccuracies in computer function evaluation, and arithmetic. A FORTRAN routine was written to check the algorithm and good accuracy was obtained. Some small errors in the correlation coefficient were observed to vary in a surprisingly regular manner. A simple model was developed which explained the qualities aspects of the errors.
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...
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...
ON THE ESTIMATION OF DISTANCE DISTRIBUTION FUNCTIONS FOR POINT PROCESSES AND RANDOM SETS
Directory of Open Access Journals (Sweden)
Dietrich Stoyan
2011-05-01
Full Text Available This paper discusses various estimators for the nearest neighbour distance distribution function D of a stationary point process and for the quadratic contact distribution function Hq of a stationary random closed set. It recommends the use of Hanisch's estimator of D, which is of Horvitz-Thompson type, and the minussampling estimator of Hq. This recommendation is based on simulations for Poisson processes and Boolean models.
Distributed Random Process for a Large-Scale Peer-to-Peer Lottery
Grumbach, Stéphane; Riemann, Robert
2017-01-01
International audience; Most online lotteries today fail to ensure the verifiability of the random process and rely on a trusted third party. This issue has received little attention since the emergence of distributed protocols like Bitcoin that demonstrated the potential of protocols with no trusted third party. We argue that the security requirements of online lotteries are similar to those of online voting, and propose a novel distributed online lottery protocol that applies techniques dev...
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.
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.
Distribution of Schmidt-like eigenvalues for Gaussian ensembles of the random matrix theory
International Nuclear Information System (INIS)
Pato, Mauricio P; Oshanin, Gleb
2013-01-01
We study the probability distribution function P (β) n (w) of the Schmidt-like random variable w = x 2 1 /(∑ j=1 n x 2 j /n), where x j , (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 (β) (w)∼√((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. (paper)
International Nuclear Information System (INIS)
Gogolak, C.V.
1986-11-01
The concentration of a contaminant measured in a particular medium might be distributed as a positive random variable when it is present, but it may not always be present. If there is a level below which the concentration cannot be distinguished from zero by the analytical apparatus, a sample from such a population will be censored on the left. The presence of both zeros and positive values in the censored portion of such samples complicates the problem of estimating the parameters of the underlying positive random variable and the probability of a zero observation. Using the method of maximum likelihood, it is shown that the solution to this estimation problem reduces largely to that of estimating the parameters of the distribution truncated at the point of censorship. The maximum likelihood estimate of the proportion of zero values follows directly. The derivation of the maximum likelihood estimates for a lognormal population with zeros is given in detail, and the asymptotic properties of the estimates are examined. The estimation method was used to fit several different distributions to a set of severely censored 85 Kr monitoring data from six locations at the Savannah River Plant chemical separations facilities
International Nuclear Information System (INIS)
Munoz Montplet, C.; Jurado Bruggeman, D.
2010-01-01
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 CTV-PTV margins or in the selection of correction protocols.
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…
Laser absorption of carbon fiber reinforced polymer with randomly distributed carbon fibers
Hu, Jun; Xu, Hebing; Li, Chao
2018-03-01
Laser processing of carbon fiber reinforced polymer (CFRP) is a non-traditional machining method which has many prospective applications. The laser absorption characteristics of CFRP are analyzed in this paper. A ray tracing model describing the interaction of the laser spot with CFRP is established. The material model contains randomly distributed carbon fibers which are generated using an improved carbon fiber placement method. It was found that CFRP has good laser absorption due to multiple reflections of the light rays in the material’s microstructure. The randomly distributed carbon fibers make the absorptivity of the light rays change randomly in the laser spot. Meanwhile, the average absorptivity fluctuation is obvious during movement of the laser. The experimental measurements agree well with the values predicted by the ray tracing model.
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.
Gatto, Riccardo
2017-12-01
This article considers the random walk over Rp, with p ≥ 2, where a given particle starts at the origin and moves stepwise with uniformly distributed step directions and step lengths following a common distribution. Step directions and step lengths are independent. The case where the number of steps of the particle is fixed and the more general case where it follows an independent continuous time inhomogeneous counting process are considered. Saddlepoint approximations to the distribution of the distance from the position of the particle to the origin are provided. Despite the p-dimensional nature of the random walk, the computations of the saddlepoint approximations are one-dimensional and thus simple. Explicit formulae are derived with dimension p = 3: for uniformly and exponentially distributed step lengths, for fixed and for Poisson distributed number of steps. In these situations, the high accuracy of the saddlepoint approximations is illustrated by numerical comparisons with Monte Carlo simulation. Contribution to the "Topical Issue: Continuous Time Random Walk Still Trendy: Fifty-year History, Current State and Outlook", edited by Ryszard Kutner and Jaume Masoliver.
Tan, Zhi-Jie; Zou, Xian-Wu; Huang, Sheng-You; Zhang, Wei; Jin, Zhun-Zhi
2002-07-01
We investigate the pattern of particle distribution and its evolution with time in multiparticle systems using the model of random walks with memory enhancement and decay. This model describes some biological intelligent walks. With decrease in the memory decay exponent α, the distribution of particles changes from a random dispersive pattern to a locally dense one, and then returns to the random one. Correspondingly, the fractal dimension Df,p characterizing the distribution of particle positions increases from a low value to a maximum and then decreases to the low one again. This is determined by the degree of overlap of regions consisting of sites with remanent information. The second moment of the density ρ(2) was introduced to investigate the inhomogeneity of the particle distribution. The dependence of ρ(2) on α is similar to that of Df,p on α. ρ(2) increases with time as a power law in the process of adjusting the particle distribution, and then ρ(2) tends to a stable equilibrium value.
Generating log-normally distributed random numbers by using the Ziggurat algorithm
International Nuclear Information System (INIS)
Choi, Jong Soo
2016-01-01
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
On Origin of Power-Law Distributions in Self-Organized Criticality from Random Walk Treatment
International Nuclear Information System (INIS)
Cao Xiaofeng; Deng Zongwei; Yang Chunbin
2008-01-01
The origin of power-law distributions in self-organized criticality is investigated by treating the variation of the number of active sites in the system as a stochastic process. An avalanche is then regarded as a first-return random walk process in a one-dimensional lattice. We assume that the variation of the number of active sites has three possibilities in each update: to increase by 1 with probability f 1 , to decrease by 1 with probability f 2 , or remain unchanged with probability 1-f 1 -f 2 . This mimics the dynamics in the system. Power-law distributions of the lifetime are found when the random walk is unbiased with equal probability to move in opposite directions. This shows that power-law distributions in self-organized criticality may be caused by the balance of competitive interactions.
Directory of Open Access Journals (Sweden)
Kaibo Shi
2014-01-01
Full Text Available This paper is concerned with the problem of delay-dependent robust stability analysis for a class of uncertain neutral type Lur’e systems with mixed time-varying delays. The system has not only time-varying uncertainties and sector-bounded nonlinearity, but also discrete and distributed delays, which has never been discussed in the previous literature. Firstly, by employing one effective mathematical technique, some less conservative delay-dependent stability results are established without employing the bounding technique and the mode transformation approach. Secondly, by constructing an appropriate new type of Lyapunov-Krasovskii functional with triple terms, improved delay-dependent stability criteria in terms of linear matrix inequalities (LMIs derived in this paper are much brief and valid. Furthermore, both nonlinearities located in finite sector and infinite one have been also fully taken into account. Finally, three numerical examples are presented to illustrate lesser conservatism and the advantage of the proposed main results.
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
Xie, Wen-Jie; Han, Rui-Qi; Jiang, Zhi-Qiang; Wei, Lijian; Zhou, Wei-Xing
2017-08-01
Complex network is not only a powerful tool for the analysis of complex system, but also a promising way to analyze time series. The algorithm of horizontal visibility graph (HVG) maps time series into graphs, whose degree distributions are numerically and analytically investigated for certain time series. We derive the degree distributions of HVGs through an iterative construction process of HVGs. The degree distributions of the HVG and the directed HVG for random series are derived to be exponential, which confirms the analytical results from other methods. We also obtained the analytical expressions of degree distributions of HVGs and in-degree and out-degree distributions of directed HVGs transformed from multifractal binomial measures, which agree excellently with numerical simulations.
Emoto, Akira; Fukuda, Takashi
2013-02-20
For Fourier transform holography, an effective random phase distribution with randomly displaced phase segments is proposed for obtaining a smooth finite optical intensity distribution in the Fourier transform plane. Since unitary phase segments are randomly distributed in-plane, the blanks give various spatial frequency components to an image, and thus smooth the spectrum. Moreover, by randomly changing the phase segment size, spike generation from the unitary phase segment size in the spectrum can be reduced significantly. As a result, a smooth spectrum including sidebands can be formed at a relatively narrow extent. The proposed phase distribution sustains the primary functions of a random phase mask for holographic-data recording and reconstruction. Therefore, this distribution is expected to find applications in high-density holographic memory systems, replacing conventional random phase mask patterns.
Probability distribution for the Gaussian curvature of the zero level surface of a random function
Hannay, J. H.
2018-04-01
A rather natural construction for a smooth random surface in space is the level surface of value zero, or ‘nodal’ surface f(x,y,z) = 0, of a (real) random function f; the interface between positive and negative regions of the function. A physically significant local attribute at a point of a curved surface is its Gaussian curvature (the product of its principal curvatures) because, when integrated over the surface it gives the Euler characteristic. Here the probability distribution for the Gaussian curvature at a random point on the nodal surface f = 0 is calculated for a statistically homogeneous (‘stationary’) and isotropic zero mean Gaussian random function f. Capitalizing on the isotropy, a ‘fixer’ device for axes supplies the probability distribution directly as a multiple integral. Its evaluation yields an explicit algebraic function with a simple average. Indeed, this average Gaussian curvature has long been known. For a non-zero level surface instead of the nodal one, the probability distribution is not fully tractable, but is supplied as an integral expression.
Hyman, J.; Aldrich, G. A.; Viswanathan, H. S.; Makedonska, N.; Karra, S.
2016-12-01
We characterize how different fracture size-transmissivity relationships influence flow and transport simulations through sparse three-dimensional discrete fracture networks. Although it is generally accepted that there is a positive correlation between a fracture's size and its transmissivity/aperture, the functional form of that relationship remains a matter of debate. Relationships that assume perfect correlation, semi-correlation, and non-correlation between the two have been proposed. To study the impact that adopting one of these relationships has on transport properties, we generate multiple sparse fracture networks composed of circular fractures whose radii follow a truncated power law distribution. The distribution of transmissivities are selected so that the mean transmissivity of the fracture networks are the same and the distributions of aperture and transmissivity in models that include a stochastic term are also the same.We observe that adopting a correlation between a fracture size and its transmissivity leads to earlier breakthrough times and higher effective permeability when compared to networks where no correlation is used. While fracture network geometry plays the principal role in determining where transport occurs within the network, the relationship between size and transmissivity controls the flow speed. These observations indicate DFN modelers should be aware that breakthrough times and effective permeabilities can be strongly influenced by such a relationship in addition to fracture and network statistics.
Distribution of sizes of erased loops for loop-erased random walks
Dhar, Deepak; Dhar, Abhishek
1997-01-01
We study the distribution of sizes of erased loops for loop-erased random walks on regular and fractal lattices. We show that for arbitrary graphs the probability $P(l)$ of generating a loop of perimeter $l$ is expressible in terms of the probability $P_{st}(l)$ of forming a loop of perimeter $l$ when a bond is added to a random spanning tree on the same graph by the simple relation $P(l)=P_{st}(l)/l$. On $d$-dimensional hypercubical lattices, $P(l)$ varies as $l^{-\\sigma}$ for large $l$, whe...
Distributed Synchronization in Networks of Agent Systems With Nonlinearities and Random Switchings.
Tang, Yang; Gao, Huijun; Zou, Wei; Kurths, Jürgen
2013-02-01
In this paper, the distributed synchronization problem of networks of agent systems with controllers and nonlinearities subject to Bernoulli switchings is investigated. Controllers and adaptive updating laws injected in each vertex of networks depend on the state information of its neighborhood. Three sets of Bernoulli stochastic variables are introduced to describe the occurrence probabilities of distributed adaptive controllers, updating laws and nonlinearities, respectively. By the Lyapunov functions method, we show that the distributed synchronization of networks composed of agent systems with multiple randomly occurring nonlinearities, multiple randomly occurring controllers, and multiple randomly occurring updating laws can be achieved in mean square under certain criteria. The conditions derived in this paper can be solved by semi-definite programming. Moreover, by mathematical analysis, we find that the coupling strength, the probabilities of the Bernoulli stochastic variables, and the form of nonlinearities have great impacts on the convergence speed and the terminal control strength. The synchronization criteria and the observed phenomena are demonstrated by several numerical simulation examples. In addition, the advantage of distributed adaptive controllers over conventional adaptive controllers is illustrated.
Directory of Open Access Journals (Sweden)
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.
Directory of Open Access Journals (Sweden)
Helmut Prodinger
2007-01-01
Full Text Available In words, generated by independent geometrically distributed random variables, we study the l th descent, which is, roughly speaking, the l th occurrence of a neighbouring pair ab with a>b. The value a is called the initial height, and b the end height. We study these two random variables (and some similar ones by combinatorial and probabilistic tools. We find in all instances a generating function Ψ(v,u, where the coefficient of v j u i refers to the j th descent (ascent, and i to the initial (end height. From this, various conclusions can be drawn, in particular expected values. In the probabilistic part, a Markov chain model is used, which allows to get explicit expressions for the heights of the second descent. In principle, one could go further, but the complexity of the results forbids it. This is extended to permutations of a large number of elements. Methods from q-analysis are used to simplify the expressions. This is the reason that we confine ourselves to the geometric distribution only. For general discrete distributions, no such tools are available.
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 < 0.01). There was a positive correlation between pageviews driven by TrendMD and article saves on Mendeley (Spearman's rho r = 0.60). This is the first randomized controlled trial to show how an online cross-publisher 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.
Directory of Open Access Journals (Sweden)
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.
The area distribution of two-dimensional random walks and non-Hermitian Hofstadter quantum mechanics
International Nuclear Information System (INIS)
Matveenko, Sergey; Ouvry, Stéphane
2014-01-01
When random walks on a square lattice are biased horizontally to move solely to the right, the probability distribution of their algebraic area can be obtained exactly (Mashkevich and Ouvry 2009 J. Stat. Phys. 137 71). We explicitly map this biased classical random system onto a non-Hermitian Hofstadter-like quantum model where a charged particle on a square lattice coupled to a perpendicular magnetic field hops only to the right. For the commensurate case, when the magnetic flux per unit cell is rational, an exact solution of the quantum model is obtained. The periodicity of the lattice allows one to relate traces of the Nth power of the Hamiltonian to probability distribution generating functions of biased walks of length N. (paper)
Effect of a data buffer on the recorded distribution of time intervals for random events
Energy Technology Data Exchange (ETDEWEB)
Barton, J C [Polytechnic of North London (UK)
1976-03-15
The use of a data buffer enables the distribution of the time intervals between events to be studied for times less than the recording system dead-time but the usual negative exponential distribution for random events has to be modified. The theory for this effect is developed for an n-stage buffer followed by an asynchronous recorder. Results are evaluated for the values of n from 1 to 5. In the language of queueing theory the system studied is of type M/D/1/n+1, i.e. with constant service time and a finite number of places.
A distribution-free newsvendor model with balking penalty and random yield
Directory of Open Access Journals (Sweden)
Chongfeng Lan
2015-05-01
Full Text Available Purpose: The purpose of this paper is to extend the analysis of the distribution-free newsvendor problem in an environment of customer balking, which occurs when customers are reluctant to buy a product if its available inventory falls below a threshold level. Design/methodology/approach: We provide a new tradeoff tool as a replacement of the traditional one to weigh the holding cost and the goodwill costs segment: in addition to the shortage penalty, we also introduce the balking penalty. Furthermore, we extend our model to the case of random yield. Findings: A model is presented for determining both an optimal order quantity and a lower bound on the profit under the worst possible distribution of the demand. We also study the effects of shortage penalty and the balking penalty on the optimal order quantity, which have been largely bypassed in the existing distribution free single period models with balking. Numerical examples are presented to illustrate the result. Originality/value: The incorporation of balking penalty and random yield represents an important improvement in inventory policy performance for distribution-free newsvendor problem when customer balking occurs and the distributional form of demand is unknown.
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.
Huber, Marcus; Pawlowski, Marcin
2013-01-01
We show that in device independent quantum key distribution protocols the privacy of randomness is of crucial importance. For sublinear test sample sizes even the slightest guessing probability by an eavesdropper will completely compromise security. We show that a combined attack exploiting test sample and measurement choices compromises the security even with a linear size test sample and otherwise device independent security considerations. We explicitly derive the sample size needed to ret...
Distributed Pseudo-Random Number Generation and Its Application to Cloud Database
Chen, Jiageng; Miyaji, Atsuko; Su, Chunhua
2014-01-01
Cloud database is now a rapidly growing trend in cloud computing market recently. It enables the clients run their computation on out-sourcing databases or access to some distributed database service on the cloud. At the same time, the security and privacy concerns is major challenge for cloud database to continue growing. To enhance the security and privacy of the cloud database technology, the pseudo-random number generation (PRNG) plays an important roles in data encryptions and privacy-pr...
Limit distribution function of inhomogeneities in regions with random boundary in the Hilbert space
International Nuclear Information System (INIS)
Rasulova, M.Yu.; Tashpulatov, S.M.
2004-10-01
The interaction of charged particle systems with a membrane consisting of nonhomogeneities which are randomly distributed by the same law in the vicinity of appropriate sites of a planax crystal lattice is studied. A system of equations for the self-consistent potential U 1 (x,ξ 0 ,..., ξ N ,...) and the density of induced charges σ(x,ξ 0 ,...,ξ N ,...) is solved on Hilbert space. (author)
International Nuclear Information System (INIS)
Ebert, M.A.; Zavgorodni, S.F.; Kendrick, L.A.; Weston, S.; Harper, C.S.
2001-01-01
Purpose: This investigation examined the effect of alignment and localization errors on dose distributions in stereotactic radiotherapy (SRT) with arced circular fields. In particular, it was desired to determine the effect of systematic and random localization errors on multi-isocenter treatments. Methods and Materials: A research version of the FastPlan system from Surgical Navigation Technologies was used to generate a series of SRT plans of varying complexity. These plans were used to examine the influence of random setup errors by recalculating dose distributions with successive setup errors convolved into the off-axis ratio data tables used in the dose calculation. The influence of systematic errors was investigated by displacing isocenters from their planned positions. Results: For single-isocenter plans, it is found that the influences of setup error are strongly dependent on the size of the target volume, with minimum doses decreasing most significantly with increasing random and systematic alignment error. For multi-isocenter plans, similar variations in target dose are encountered, with this result benefiting from the conventional method of prescribing to a lower isodose value for multi-isocenter treatments relative to single-isocenter treatments. Conclusions: It is recommended that the systematic errors associated with target localization in SRT be tracked via a thorough quality assurance program, and that random setup errors be minimized by use of a sufficiently robust relocation system. These errors should also be accounted for by incorporating corrections into the treatment planning algorithm or, alternatively, by inclusion of sufficient margins in target definition
Directory of Open Access Journals (Sweden)
Chih-Hsueh Lin
2016-04-01
Full Text Available In wireless sensor networks, sensing information must be transmitted from sensor nodes to the base station by multiple hopping. Every sensor node is a sender and a relay node that forwards the sensing information that is sent by other nodes. Under an attack, the sensing information may be intercepted, modified, interrupted, or fabricated during transmission. Accordingly, the development of mutual trust to enable a secure path to be established for forwarding information is an important issue. Random key pre-distribution has been proposed to establish mutual trust among sensor nodes. This article modifies the random key pre-distribution to a random secret pre-distribution and incorporates identity-based cryptography to establish an effective method of establishing mutual trust for a wireless sensor network. In the proposed method, base station assigns an identity and embeds n secrets into the private secret keys for every sensor node. Based on the identity and private secret keys, the mutual trust method is utilized to explore the types of trust among neighboring sensor nodes. The novel method can resist malicious attacks and satisfy the requirements of wireless sensor network, which are resistance to compromising attacks, masquerading attacks, forger attacks, replying attacks, authentication of forwarding messages, and security of sensing information.
Pang, Yu; Zhang, Kunning; Yang, Zhen; Jiang, Song; Ju, Zhenyi; Li, Yuxing; Wang, Xuefeng; Wang, Danyang; Jian, Muqiang; Zhang, Yingying; Liang, Renrong; Tian, He; Yang, Yi; Ren, Tian-Ling
2018-03-27
Recently, wearable pressure sensors have attracted tremendous attention because of their potential applications in monitoring physiological signals for human healthcare. Sensitivity and linearity are the two most essential parameters for pressure sensors. Although various designed micro/nanostructure morphologies have been introduced, the trade-off between sensitivity and linearity has not been well balanced. Human skin, which contains force receptors in a reticular layer, has a high sensitivity even for large external stimuli. Herein, inspired by the skin epidermis with high-performance force sensing, we have proposed a special surface morphology with spinosum microstructure of random distribution via the combination of an abrasive paper template and reduced graphene oxide. The sensitivity of the graphene pressure sensor with random distribution spinosum (RDS) microstructure is as high as 25.1 kPa -1 in a wide linearity range of 0-2.6 kPa. Our pressure sensor exhibits superior comprehensive properties compared with previous surface-modified pressure sensors. According to simulation and mechanism analyses, the spinosum microstructure and random distribution contribute to the high sensitivity and large linearity range, respectively. In addition, the pressure sensor shows promising potential in detecting human physiological signals, such as heartbeat, respiration, phonation, and human motions of a pushup, arm bending, and walking. The wearable pressure sensor array was further used to detect gait states of supination, neutral, and pronation. The RDS microstructure provides an alternative strategy to improve the performance of pressure sensors and extend their potential applications in monitoring human activities.
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.
International Nuclear Information System (INIS)
Moore, Stephen R.; Papworth, David; Grosovsky, Andrew J.
2006-01-01
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
Energy Technology Data Exchange (ETDEWEB)
Murata, Isao [Osaka Univ., Suita (Japan); Mori, Takamasa; Nakagawa, Masayuki; Itakura, Hirofumi
1996-03-01
The method to calculate neutronics parameters of a core composed of randomly distributed spherical fuels has been developed based on a statistical geometry model with a continuous energy Monte Carlo method. This method was implemented in a general purpose Monte Carlo code MCNP, and a new code MCNP-CFP had been developed. This paper describes the model and method how to use it and the validation results. In the Monte Carlo calculation, the location of a spherical fuel is sampled probabilistically along the particle flight path from the spatial probability distribution of spherical fuels, called nearest neighbor distribution (NND). This sampling method was validated through the following two comparisons: (1) Calculations of inventory of coated fuel particles (CFPs) in a fuel compact by both track length estimator and direct evaluation method, and (2) Criticality calculations for ordered packed geometries. This method was also confined by applying to an analysis of the critical assembly experiment at VHTRC. The method established in the present study is quite unique so as to a probabilistic model of the geometry with a great number of spherical fuels distributed randomly. Realizing the speed-up by vector or parallel computations in future, it is expected to be widely used in calculation of a nuclear reactor core, especially HTGR cores. (author).
Chandra, Vikas; Das, Tapojyoti; Gulati, Puneet; Biswas, Nidhan K; Rote, Sarang; Chatterjee, Uttara; Ghosh, Samarendra N; Deb, Sumit; Saha, Suniti K; Chowdhury, Anup K; Ghosh, Subhashish; Rudin, Charles M; Mukherjee, Ankur; Basu, Analabha; Dhara, Surajit
2015-01-01
Hedgehog (Hh) signaling pathway is a valid therapeutic target in a wide range of malignancies. We focus here on glioblastoma multiforme (GBM), a lethal malignancy of the central nervous system (CNS). By analyzing RNA-sequencing based transcriptomics data on 149 clinical cases of TCGA-GBM database we show here a strong correlation (r = 0.7) between GLI1 and PTCH1 mRNA expression--as a hallmark of the canonical Hh-pathway activity in this malignancy. GLI1 mRNA expression varied in 3 orders of magnitude among the GBM patients of the same cohort showing a single continuous distribution-unlike the discrete high/low-GLI1 mRNA expressing clusters of medulloblastoma (MB). When compared with MB as a reference, the median GLI1 mRNA expression in GBM appeared 14.8 fold lower than that of the "high-Hh" cluster of MB but 5.6 fold higher than that of the "low-Hh" cluster of MB. Next, we demonstrated statistically significant up- and down-regulation of GLI1 mRNA expressions in GBM patient-derived low-passage neurospheres in vitro by sonic hedgehog ligand-enriched conditioned media (shh-CM) and by Hh-inhibitor drug vismodegib respectively. We also showed clinically achievable dose (50 μM) of vismodegib alone to be sufficient to induce apoptosis and cell cycle arrest in these low-passage GBM neurospheres in vitro. Vismodegib showed an effect on the neurospheres, both by down-regulating GLI1 mRNA expression and by inducing apoptosis/cell cycle arrest, irrespective of their relative endogenous levels of GLI1 mRNA expression. We conclude from our study that this single continuous distribution pattern of GLI1 mRNA expression technically puts almost all GBM patients in a single group rather than discrete high- or low-clusters in terms of Hh-pathway activity. That is suggestive of therapies with Hh-pathway inhibitor drugs in this malignancy without a need for further stratification of patients on the basis of relative levels of Hh-pathway activity among them.
International Nuclear Information System (INIS)
Ni Xiaohui; Jiang Zhiqiang; Zhou Weixing
2009-01-01
The dynamics of a complex system is usually recorded in the form of time series, which can be studied through its visibility graph from a complex network perspective. We investigate the visibility graphs extracted from fractional Brownian motions and multifractal random walks, and find that the degree distributions exhibit power-law behaviors, in which the power-law exponent α is a linear function of the Hurst index H of the time series. We also find that the degree distribution of the visibility graph is mainly determined by the temporal correlation of the original time series with minor influence from the possible multifractal nature. As an example, we study the visibility graphs constructed from three Chinese stock market indexes and unveil that the degree distributions have power-law tails, where the tail exponents of the visibility graphs and the Hurst indexes of the indexes are close to the α∼H linear relationship.
Zhang, Y.; Li, F.; Zhang, S.; Hao, W.; Zhu, T.; Yuan, L.; Xiao, F.
2017-09-01
In this paper, Statistical Distribution based Conditional Random Fields (STA-CRF) algorithm is exploited for improving marginal ice-water classification. Pixel level ice concentration is presented as the comparison of methods based on CRF. Furthermore, in order to explore the effective statistical distribution model to be integrated into STA-CRF, five statistical distribution models are investigated. The STA-CRF methods are tested on 2 scenes around Prydz Bay and Adélie Depression, where contain a variety of ice types during melt season. Experimental results indicate that the proposed method can resolve sea ice edge well in Marginal Ice Zone (MIZ) and show a robust distinction of ice and water.
Mitchell, Erica L; Lee, Dae Y; Sevdalis, Nick; Partsafas, Aaron W; Landry, Gregory J; Liem, Timothy K; Moneta, Gregory L
2011-01-01
practice influences new skill acquisition. The aim of this study was to prospectively investigate the impact of practice distribution (weekly vs monthly) on complex motor skill (end-side vascular anastomosis) acquisition and 4-month retention. twenty-four surgical interns were randomly assigned to weekly training for 4 weeks or monthly training for 4 months, with equal total training times. Performance was assessed before training, immediately after training, after the completion of distributed training, and 4 months later. there was no statistical difference in surgical skill acquisition and retention between the weekly and monthly scheduled groups, as measured by procedural checklist scores, global rating scores of operative performance, final product analysis, and overall performance or assessment of operative "competence." distributed practice results in improvement and retention of a newly acquired surgical skill independent of weekly or monthly practice schedules. Flexibility in a surgical skills laboratory curriculum is possible without adversely affecting training. 2011 Elsevier Inc. All rights reserved.
Nagaev, Alexander; Zaigraev, Alexander
2005-01-01
A class of absolutely continuous distributions in Rd is considered. Each distribution belongs to the domain of normal attraction of an α-stable law. The limit law is characterized by a spectral measure which is absolutely continuous with respect to the spherical Lebesgue measure. The large-deviation problem for sums of independent and identically distributed random vectors when the underlying distribution belongs to that class is studied. At the focus of attention are the deviations in the di...
Effect of particle size distribution on permeability in the randomly packed porous media
Markicevic, Bojan
2017-11-01
An answer of how porous medium heterogeneity influences the medium permeability is still inconclusive, where both increase and decrease in the permeability value are reported. A numerical procedure is used to generate a randomly packed porous material consisting of spherical particles. Six different particle size distributions are used including mono-, bi- and three-disperse particles, as well as uniform, normal and log-normal particle size distribution with the maximum to minimum particle size ratio ranging from three to eight for different distributions. In all six cases, the average particle size is kept the same. For all media generated, the stochastic homogeneity is checked from distribution of three coordinates of particle centers, where uniform distribution of x-, y- and z- positions is found. The medium surface area remains essentially constant except for bi-modal distribution in which medium area decreases, while no changes in the porosity are observed (around 0.36). The fluid flow is solved in such domain, and after checking for the pressure axial linearity, the permeability is calculated from the Darcy law. The permeability comparison reveals that the permeability of the mono-disperse medium is smallest, and the permeability of all poly-disperse samples is less than ten percent higher. For bi-modal particles, the permeability is for a quarter higher compared to the other media which can be explained by volumetric contribution of larger particles and larger passages for fluid flow to take place.
ERROR DISTRIBUTION EVALUATION OF THE THIRD VANISHING POINT BASED ON RANDOM STATISTICAL SIMULATION
Directory of Open Access Journals (Sweden)
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.
Error Distribution Evaluation of the Third Vanishing Point Based on Random Statistical Simulation
Li, C.
2012-07-01
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.
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
International Nuclear Information System (INIS)
Zhang Yu; Wang Guangyi; Lu Xinmiao; Hu Yongcai; Xu Jiangtao
2016-01-01
The random telegraph signal noise in the pixel source follower MOSFET is the principle component of the noise in the CMOS image sensor under low light. In this paper, the physical and statistical model of the random telegraph signal noise in the pixel source follower based on the binomial distribution is set up. The number of electrons captured or released by the oxide traps in the unit time is described as the random variables which obey the binomial distribution. As a result, the output states and the corresponding probabilities of the first and the second samples of the correlated double sampling circuit are acquired. The standard deviation of the output states after the correlated double sampling circuit can be obtained accordingly. In the simulation section, one hundred thousand samples of the source follower MOSFET have been simulated, and the simulation results show that the proposed model has the similar statistical characteristics with the existing models under the effect of the channel length and the density of the oxide trap. Moreover, the noise histogram of the proposed model has been evaluated at different environmental temperatures. (paper)
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
Extended q -Gaussian and q -exponential distributions from gamma random variables
Budini, Adrián A.
2015-05-01
The family of q -Gaussian and q -exponential probability densities fit the statistical behavior of diverse complex self-similar nonequilibrium systems. These distributions, independently of the underlying dynamics, can rigorously be obtained by maximizing Tsallis "nonextensive" entropy under appropriate constraints, as well as from superstatistical models. In this paper we provide an alternative and complementary scheme for deriving these objects. We show that q -Gaussian and q -exponential random variables can always be expressed as a function of two statistically independent gamma random variables with the same scale parameter. Their shape index determines the complexity q parameter. This result also allows us to define an extended family of asymmetric q -Gaussian and modified q -exponential densities, which reduce to the standard ones when the shape parameters are the same. Furthermore, we demonstrate that a simple change of variables always allows relating any of these distributions with a beta stochastic variable. The extended distributions are applied in the statistical description of different complex dynamics such as log-return signals in financial markets and motion of point defects in a fluid flow.
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.
3D vector distribution of the electro-magnetic fields on a random gold film
Canneson, Damien; Berini, Bruno; Buil, Stéphanie; Hermier, Jean-Pierre; Quélin, Xavier
2018-05-01
The 3D vector distribution of the electro-magnetic fields at the very close vicinity of the surface of a random gold film is studied. Such films are well known for their properties of light confinement and large fluctuations of local density of optical states. Using Finite-Difference Time-Domain simulations, we show that it is possible to determine the local orientation of the electro-magnetic fields. This allows us to obtain a complete characterization of the fields. Large fluctuations of their amplitude are observed as previously shown. Here, we demonstrate large variations of their direction depending both on the position on the random gold film, and on the distance to it. Such characterization could be useful for a better understanding of applications like the coupling of point-like dipoles to such films.
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
2014-04-23
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.
ACORN—A new method for generating sequences of uniformly distributed Pseudo-random Numbers
Wikramaratna, R. S.
1989-07-01
A new family of pseudo-random number generators, the ACORN ( additive congruential random number) generators, is proposed. The resulting numbers are distributed uniformly in the interval [0, 1). The ACORN generators are defined recursively, and the ( k + 1)th order generator is easily derived from the kth order generator. Some theorems concerning the period length are presented and compared with existing results for linear congruential generators. A range of statistical tests are applied to the ACORN generators, and their performance is compared with that of the linear congruential generators and the Chebyshev generators. The tests show the ACORN generators to be statistically superior to the Chebyshev generators, while being statistically similar to the linear congruential generators. However, the ACORN generators execute faster than linear congruential generators for the same statistical faithfulness. The main advantages of the ACORN generator are speed of execution, long period length, and simplicity of coding.
Camposeo, Andrea; Del Carro, Pompilio; Persano, Luana; Cyprych, Konrad; Szukalski, Adam; Sznitko, Lech; Mysliwiec, Jaroslaw; Pisignano, Dario
2014-10-28
Room-temperature nanoimprinted, DNA-based distributed feedback (DFB) laser operation at 605 nm is reported. The laser is made of a pure DNA host matrix doped with gain dyes. At high excitation densities, the emission of the untextured dye-doped DNA films is characterized by a broad emission peak with an overall line width of 12 nm and superimposed narrow peaks, characteristic of random lasing. Moreover, direct patterning of the DNA films is demonstrated with a resolution down to 100 nm, enabling the realization of both surface-emitting and edge-emitting DFB lasers with a typical line width of <0.3 nm. The resulting emission is polarized, with a ratio between the TE- and TM-polarized intensities exceeding 30. In addition, the nanopatterned devices dissolve in water within less than 2 min. These results demonstrate the possibility of realizing various physically transient nanophotonics and laser architectures, including random lasing and nanoimprinted devices, based on natural biopolymers.
Dorin, Bryce; Parkinson, Patrick; Scully, Patricia
2018-04-01
The development of cost-effective electrical packaging for randomly distributed micro/nano-scale devices is a widely recognized challenge for fabrication technologies. Three-dimensional direct laser writing (DLW) has been proposed as a solution to this challenge, and has enabled the creation of rapid and low resistance graphitic wires within commercial polyimide substrates. In this work, we utilize the DLW technique to electrically contact three fully encapsulated and randomly positioned light-emitting diodes (LEDs) in a one-step process. The resolution of the contacts is in the order of 20 μ m, with an average circuit resistance of 29 ± 18 kΩ per LED contacted. The speed and simplicity of this technique is promising to meet the needs of future microelectronics and device packaging.
Topology determines force distributions in one-dimensional random spring networks
Heidemann, Knut M.; Sageman-Furnas, Andrew O.; Sharma, Abhinav; Rehfeldt, Florian; Schmidt, Christoph F.; Wardetzky, Max
2018-02-01
Networks of elastic fibers are ubiquitous in biological systems and often provide mechanical stability to cells and tissues. Fiber-reinforced materials are also common in technology. An important characteristic of such materials is their resistance to failure under load. Rupture occurs when fibers break under excessive force and when that failure propagates. Therefore, it is crucial to understand force distributions. Force distributions within such networks are typically highly inhomogeneous and are not well understood. Here we construct a simple one-dimensional model system with periodic boundary conditions by randomly placing linear springs on a circle. We consider ensembles of such networks that consist of N nodes and have an average degree of connectivity z but vary in topology. Using a graph-theoretical approach that accounts for the full topology of each network in the ensemble, we show that, surprisingly, the force distributions can be fully characterized in terms of the parameters (N ,z ) . Despite the universal properties of such (N ,z ) ensembles, our analysis further reveals that a classical mean-field approach fails to capture force distributions correctly. We demonstrate that network topology is a crucial determinant of force distributions in elastic spring networks.
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.
Discrete gradients in discrete classical mechanics
International Nuclear Information System (INIS)
Renna, L.
1987-01-01
A simple model of discrete classical mechanics is given where, starting from the continuous Hamilton equations, discrete equations of motion are established together with a proper discrete gradient definition. The conservation laws of the total discrete momentum, angular momentum, and energy are demonstrated
Magneto-transport properties of a random distribution of few-layer graphene patches
International Nuclear Information System (INIS)
Iacovella, Fabrice; Mitioglu, Anatolie; Pierre, Mathieu; Raquet, Bertrand; Goiran, Michel; Plochocka, Paulina; Escoffier, Walter; Trinsoutrot, Pierre; Vergnes, Hugues; Caussat, Brigitte; Conédéra, Véronique
2014-01-01
In this study, we address the electronic properties of conducting films constituted of an array of randomly distributed few layer graphene patches and investigate on their most salient galvanometric features in the moderate and extreme disordered limit. We demonstrate that, in annealed devices, the ambipolar behaviour and the onset of Landau level quantization in high magnetic field constitute robust hallmarks of few-layer graphene films. In the strong disorder limit, however, the magneto-transport properties are best described by a variable-range hopping behaviour. A large negative magneto-conductance is observed at the charge neutrality point, in consistency with localized transport regime
A heuristic for the distribution of point counts for random curves over a finite field.
Achter, Jeffrey D; Erman, Daniel; Kedlaya, Kiran S; Wood, Melanie Matchett; Zureick-Brown, David
2015-04-28
How many rational points are there on a random algebraic curve of large genus g over a given finite field Fq? We propose a heuristic for this question motivated by a (now proven) conjecture of Mumford on the cohomology of moduli spaces of curves; this heuristic suggests a Poisson distribution with mean q+1+1/(q-1). We prove a weaker version of this statement in which g and q tend to infinity, with q much larger than g. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Directory of Open Access Journals (Sweden)
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.
Krivitsky, Pavel N; Handcock, Mark S; Raftery, Adrian E; Hoff, Peter D
2009-07-01
Social network data often involve transitivity, homophily on observed attributes, clustering, and heterogeneity of actor degrees. We propose a latent cluster random effects model to represent all of these features, and we describe a Bayesian estimation method for it. The model is applicable to both binary and non-binary network data. We illustrate the model using two real datasets. We also apply it to two simulated network datasets with the same, highly skewed, degree distribution, but very different network behavior: one unstructured and the other with transitivity and clustering. Models based on degree distributions, such as scale-free, preferential attachment and power-law models, cannot distinguish between these very different situations, but our model does.
Online Distributed Learning Over Networks in RKH Spaces Using Random Fourier Features
Bouboulis, Pantelis; Chouvardas, Symeon; Theodoridis, Sergios
2018-04-01
We present a novel diffusion scheme for online kernel-based learning over networks. So far, a major drawback of any online learning algorithm, operating in a reproducing kernel Hilbert space (RKHS), is the need for updating a growing number of parameters as time iterations evolve. Besides complexity, this leads to an increased need of communication resources, in a distributed setting. In contrast, the proposed method approximates the solution as a fixed-size vector (of larger dimension than the input space) using Random Fourier Features. This paves the way to use standard linear combine-then-adapt techniques. To the best of our knowledge, this is the first time that a complete protocol for distributed online learning in RKHS is presented. Conditions for asymptotic convergence and boundness of the networkwise regret are also provided. The simulated tests illustrate the performance of the proposed scheme.
Heimann, G; Neuhaus, G
1998-03-01
In the random censorship model, the log-rank test is often used for comparing a control group with different dose groups. If the number of tumors is small, so-called exact methods are often applied for computing critical values from a permutational distribution. Two of these exact methods are discussed and shown to be incorrect. The correct permutational distribution is derived and studied with respect to its behavior under unequal censoring in the light of recent results proving that the permutational version and the unconditional version of the log-rank test are asymptotically equivalent even under unequal censoring. The log-rank test is studied by simulations of a realistic scenario from a bioassay with small numbers of tumors.
Montiel, F.; Squire, V. A.
2013-12-01
A new ocean wave/sea-ice interaction model is proposed that simulates how a directional wave spectrum evolves as it travels through a realistic marginal ice zone (MIZ), where wave/ice dynamics are entirely governed by coherent conservative wave scattering effects. Field experiments conducted by Wadhams et al. (1986) in the Greenland Sea generated important data on wave attenuation in the MIZ and, particularly, on whether the wave spectrum spreads directionally or collimates with distance from the ice edge. The data suggest that angular isotropy, arising from multiple scattering by ice floes, occurs close to the edge and thenceforth dominates wave propagation throughout the MIZ. Although several attempts have been made to replicate this finding theoretically, including by the use of numerical models, none have confronted this problem in a 3D MIZ with fully randomised floe distribution properties. We construct such a model by subdividing the discontinuous ice cover into adjacent infinite slabs of finite width parallel to the ice edge. Each slab contains an arbitrary (but finite) number of circular ice floes with randomly distributed properties. Ice floes are modeled as thin elastic plates with uniform thickness and finite draught. We consider a directional wave spectrum with harmonic time dependence incident on the MIZ from the open ocean, defined as a continuous superposition of plane waves traveling at different angles. The scattering problem within each slab is then solved using Graf's interaction theory for an arbitrary incident directional plane wave spectrum. Using an appropriate integral representation of the Hankel function of the first kind (see Cincotti et al., 1993), we map the outgoing circular wave field from each floe on the slab boundaries into a directional spectrum of plane waves, which characterizes the slab reflected and transmitted fields. Discretizing the angular spectrum, we can obtain a scattering matrix for each slab. Standard recursive
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...
Sadeh, Sadra; Rotter, Stefan
2014-01-01
Neurons in the primary visual cortex are more or less selective for the orientation of a light bar used for stimulation. A broad distribution of individual grades of orientation selectivity has in fact been reported in all species. A possible reason for emergence of broad distributions is the recurrent network within which the stimulus is being processed. Here we compute the distribution of orientation selectivity in randomly connected model networks that are equipped with different spatial patterns of connectivity. We show that, for a wide variety of connectivity patterns, a linear theory based on firing rates accurately approximates the outcome of direct numerical simulations of networks of spiking neurons. Distance dependent connectivity in networks with a more biologically realistic structure does not compromise our linear analysis, as long as the linearized dynamics, and hence the uniform asynchronous irregular activity state, remain stable. We conclude that linear mechanisms of stimulus processing are indeed responsible for the emergence of orientation selectivity and its distribution in recurrent networks with functionally heterogeneous synaptic connectivity.
Analysis and applications of a frequency selective surface via a random distribution method
International Nuclear Information System (INIS)
Xie Shao-Yi; Huang Jing-Jian; Yuan Nai-Chang; Liu Li-Guo
2014-01-01
A novel frequency selective surface (FSS) for reducing radar cross section (RCS) is proposed in this paper. This FSS is based on the random distribution method, so it can be called random surface. In this paper, the stacked patches serving as periodic elements are employed for RCS reduction. Previous work has demonstrated the efficiency by utilizing the microstrip patches, especially for the reflectarray. First, the relevant theory of the method is described. Then a sample of a three-layer variable-sized stacked patch random surface with a dimension of 260 mm×260 mm is simulated, fabricated, and measured in order to demonstrate the validity of the proposed design. For the normal incidence, the 8-dB RCS reduction can be achieved both by the simulation and the measurement in 8 GHz–13 GHz. The oblique incidence of 30° is also investigated, in which the 7-dB RCS reduction can be obtained in a frequency range of 8 GHz–14 GHz. (condensed matter: electronic structure, electrical, magnetic, and optical properties)
Distributed clone detection in static wireless sensor networks: random walk with network division.
Khan, Wazir Zada; Aalsalem, Mohammed Y; Saad, N M
2015-01-01
Wireless Sensor Networks (WSNs) are vulnerable to clone attacks or node replication attacks as they are deployed in hostile and unattended environments where they are deprived of physical protection, lacking physical tamper-resistance of sensor nodes. As a result, an adversary can easily capture and compromise sensor nodes and after replicating them, he inserts arbitrary number of clones/replicas into the network. If these clones are not efficiently detected, an adversary can be further capable to mount a wide variety of internal attacks which can emasculate the various protocols and sensor applications. Several solutions have been proposed in the literature to address the crucial problem of clone detection, which are not satisfactory as they suffer from some serious drawbacks. In this paper we propose a novel distributed solution called Random Walk with Network Division (RWND) for the detection of node replication attack in static WSNs which is based on claimer-reporter-witness framework and combines a simple random walk with network division. RWND detects clone(s) by following a claimer-reporter-witness framework and a random walk is employed within each area for the selection of witness nodes. Splitting the network into levels and areas makes clone detection more efficient and the high security of witness nodes is ensured with moderate communication and memory overheads. Our simulation results show that RWND outperforms the existing witness node based strategies with moderate communication and memory overheads.
Distributed clone detection in static wireless sensor networks: random walk with network division.
Directory of Open Access Journals (Sweden)
Wazir Zada Khan
Full Text Available Wireless Sensor Networks (WSNs are vulnerable to clone attacks or node replication attacks as they are deployed in hostile and unattended environments where they are deprived of physical protection, lacking physical tamper-resistance of sensor nodes. As a result, an adversary can easily capture and compromise sensor nodes and after replicating them, he inserts arbitrary number of clones/replicas into the network. If these clones are not efficiently detected, an adversary can be further capable to mount a wide variety of internal attacks which can emasculate the various protocols and sensor applications. Several solutions have been proposed in the literature to address the crucial problem of clone detection, which are not satisfactory as they suffer from some serious drawbacks. In this paper we propose a novel distributed solution called Random Walk with Network Division (RWND for the detection of node replication attack in static WSNs which is based on claimer-reporter-witness framework and combines a simple random walk with network division. RWND detects clone(s by following a claimer-reporter-witness framework and a random walk is employed within each area for the selection of witness nodes. Splitting the network into levels and areas makes clone detection more efficient and the high security of witness nodes is ensured with moderate communication and memory overheads. Our simulation results show that RWND outperforms the existing witness node based strategies with moderate communication and memory overheads.
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.
Czernik, Pawel
2013-10-01
The hardware random number generator based on the 74121 monostable multivibrators for applications in cryptographically secure distributed measurement and control systems with asymmetric resources was presented. This device was implemented on the basis of the physical electronic vibration generator in which the circuit is composed of two "loop" 74121 monostable multivibrators, D flip-flop and external clock signal source. The clock signal, witch control D flip-flop was generated by a computer on one of the parallel port pins. There was presented programmed the author's acquisition process of random data from the measuring system to a computer. The presented system was designed, builded and thoroughly tested in the term of cryptographic security in our laboratory, what there is the most important part of this publication. Real cryptographic security was tested based on the author's software and the software environment called RDieHarder. The obtained results was here presented and analyzed in detail with particular reference to the specificity of distributed measurement and control systems with asymmetric resources.
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.
Caballero-Águila, R.; Hermoso-Carazo, A.; Linares-Pérez, J.
2017-07-01
This paper studies the distributed fusion estimation problem from multisensor measured outputs perturbed by correlated noises and uncertainties modelled by random parameter matrices. Each sensor transmits its outputs to a local processor over a packet-erasure channel and, consequently, random losses may occur during transmission. Different white sequences of Bernoulli variables are introduced to model the transmission losses. For the estimation, each lost output is replaced by its estimator based on the information received previously, and only the covariances of the processes involved are used, without requiring the signal evolution model. First, a recursive algorithm for the local least-squares filters is derived by using an innovation approach. Then, the cross-correlation matrices between any two local filters is obtained. Finally, the distributed fusion filter weighted by matrices is obtained from the local filters by applying the least-squares criterion. The performance of the estimators and the influence of both sensor uncertainties and transmission losses on the estimation accuracy are analysed in a numerical example.
Scattering of elastic waves on fractures randomly distributed in a three-dimensional medium
Strizhkov, S. A.; Ponyatovskaya, V. I.
1985-02-01
The purpose of this work is to determine the variation in basic characteristics of the wave field formed in a jointed medium, such as the intensity of fluctuations of amplitude, correlation radius, scattering coefficient and frequency composition of waves, as functions of jointing parameters. Fractures are simulated by flat plates randomly distributed and chaotically oriented in a three-dimensional medium. Experiments were performed using an alabaster model, a rectangular block measuring 50 x 50 x 120 mm. The plates were introduced into liquid alabaster which was then agitated. Models made in this way contain randomly distributed and chaotically oriented fractures. The influence of these fractures appears as fluctuations in the wave field formed in the medium. The data obtained in experimental studies showed that the dimensions of heterogeneities determined by waves in the jointed medium and the dimensions of the fractures themselves coincide only if the distance between fractures is rather great. If the distance between fractures is less than the wavelength, the dimensions of the heterogeneities located by the wave depend on wavelength.
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
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.
Time distributions of solar energetic particle events: Are SEPEs really random?
Jiggens, P. T. A.; Gabriel, S. B.
2009-10-01
Solar energetic particle events (SEPEs) can exhibit flux increases of several orders of magnitude over background levels and have always been considered to be random in nature in statistical models with no dependence of any one event on the occurrence of previous events. We examine whether this assumption of randomness in time is correct. Engineering modeling of SEPEs is important to enable reliable and efficient design of both Earth-orbiting and interplanetary spacecraft and future manned missions to Mars and the Moon. All existing engineering models assume that the frequency of SEPEs follows a Poisson process. We present analysis of the event waiting times using alternative distributions described by Lévy and time-dependent Poisson processes and compared these with the usual Poisson distribution. The results show significant deviation from a Poisson process and indicate that the underlying physical processes might be more closely related to a Lévy-type process, suggesting that there is some inherent “memory” in the system. Inherent Poisson assumptions of stationarity and event independence are investigated, and it appears that they do not hold and can be dependent upon the event definition used. SEPEs appear to have some memory indicating that events are not completely random with activity levels varying even during solar active periods and are characterized by clusters of events. This could have significant ramifications for engineering models of the SEP environment, and it is recommended that current statistical engineering models of the SEP environment should be modified to incorporate long-term event dependency and short-term system memory.
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)
Zorareh Hadj Mohammad
Full Text Available The paper addresses the problem of the influence of randomly distributed corrosion wastage on the collapse strength and behaviour of unstiffened/stiffened steel plates in longitudinal compression. A series of elastic-plastic large deflection finite element analyses is performed on both-sides randomly corroded steel plates and stiffened plates. The effects of general corrosion are introduced into the finite element models using a novel random thickness surface model. Buckling strength, post-buckling behaviour, ultimate strength and post-ultimate behaviour of the models are investigated as results of both-sides random corrosion.
The remarkable discreteness of being
Indian Academy of Sciences (India)
Life is a discrete, stochastic phenomenon: 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, counterintuitive consequences. I review here three ...
The distribution of the number of node neighbors in random hypergraphs
International Nuclear Information System (INIS)
López, Eduardo
2013-01-01
Hypergraphs, the generalization of graphs in which edges become conglomerates of r nodes called hyperedges of rank r ⩾ 2, are excellent models to study systems with interactions that are beyond the pairwise level. For hypergraphs, the node degree ℓ (number of hyperedges connected to a node) and the number of neighbors k of a node differ from each other in contrast to the case of graphs, where counting the number of edges is equivalent to counting the number of neighbors. In this paper, I calculate the distribution of the number of node neighbors in random hypergraphs in which hyperedges of uniform rank r have a homogeneous (equal for all hyperedges) probability p to appear. This distribution is equivalent to the degree distribution of ensembles of graphs created as projections of hypergraph or bipartite network ensembles, where the projection connects any two nodes in the projected graph when they are also connected in the hypergraph or bipartite network. The calculation is non-trivial due to the possibility that neighbor nodes belong simultaneously to multiple hyperedges (node overlaps). From the exact results, the traditional asymptotic approximation to the distribution in the sparse regime (small p) where overlaps are ignored is rederived and improved; the approximation exhibits Poisson-like behavior accompanied by strong fluctuations modulated by power-law decays in the system size N with decay exponents equal to the minimum number of overlapping nodes possible for a given number of neighbors. It is shown that the dense limit cannot be explained if overlaps are ignored, and the correct asymptotic distribution is provided. The neighbor distribution requires the calculation of a new combinatorial coefficient Q r−1 (k, ℓ), which counts the number of distinct labeled hypergraphs of k nodes, ℓ hyperedges of rank r − 1, and where every node is connected to at least one hyperedge. Some identities of Q r−1 (k, ℓ) are derived and applied to the
Discrete Curvatures and Discrete Minimal Surfaces
Sun, Xiang
2012-01-01
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
International Nuclear Information System (INIS)
Olson, Gordon L.
2008-01-01
In binary stochastic media in two- and three-dimensions consisting of randomly placed impenetrable disks or spheres, the chord lengths in the background material between disks and spheres closely follow exponential distributions if the disks and spheres occupy less than 10% of the medium. This work demonstrates that for regular spatial structures of disks and spheres, the tails of the chord length distributions (CLDs) follow power laws rather than exponentials. In dilute media, when the disks and spheres are widely spaced, the slope of the power law seems to be independent of the details of the structure. When approaching a close-packed arrangement, the exact placement of the spheres can make a significant difference. When regular structures are perturbed by small random displacements, the CLDs become power laws with steeper slopes. An example CLD from a quasi-random distribution of spheres in clusters shows a modified exponential distribution
Energy Technology Data Exchange (ETDEWEB)
Olson, Gordon L. [Computer and Computational Sciences Division (CCS-2), Los Alamos National Laboratory, 5 Foxglove Circle, Madison, WI 53717 (United States)], E-mail: olson99@tds.net
2008-11-15
In binary stochastic media in two- and three-dimensions consisting of randomly placed impenetrable disks or spheres, the chord lengths in the background material between disks and spheres closely follow exponential distributions if the disks and spheres occupy less than 10% of the medium. This work demonstrates that for regular spatial structures of disks and spheres, the tails of the chord length distributions (CLDs) follow power laws rather than exponentials. In dilute media, when the disks and spheres are widely spaced, the slope of the power law seems to be independent of the details of the structure. When approaching a close-packed arrangement, the exact placement of the spheres can make a significant difference. When regular structures are perturbed by small random displacements, the CLDs become power laws with steeper slopes. An example CLD from a quasi-random distribution of spheres in clusters shows a modified exponential distribution.
Intelligent discrete particle swarm optimization for multiprocessor task scheduling problem
Directory of Open Access Journals (Sweden)
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.
Distributed feedback multimode Brillouin–Raman random fiber laser in the S-band
International Nuclear Information System (INIS)
Ahmad, H; Zulkifli, M Z; Jemangin, M H; Harun, S W
2013-01-01
A novel S-band multimode Brillouin–Raman random fiber laser based on distributed feedback of Rayleigh scattered light is demonstrated. It relies on a short length, 7.7 km long angle-cleaved dispersion compensating fiber in a mirror-less open cavity. Two 1425 nm laser diodes at a modest operating power amplify a Brillouin pump (BP) signal, which in turn generates a multi-wavelength laser output through the stimulated Brillouin scattering. Eleven Brillouin Stokes lines, spanning from 1515.15 to 1516.00 nm, were obtained at a Raman pump power of 361.66 mW. Out of these, five odd Brillouin Stokes lines were generated with a flat peak power of about 0 dBm. (letter)
DEFF Research Database (Denmark)
Fitzek, Frank; Toth, Tamas; Szabados, Áron
2014-01-01
This paper advocates the use of random linear network coding for storage in distributed clouds in order to reduce storage and traffic costs in dynamic settings, i.e. when adding and removing numerous storage devices/clouds on-the-fly and when the number of reachable clouds is limited. We introduce...... various network coding approaches that trade-off reliability, storage and traffic costs, and system complexity relying on probabilistic recoding for cloud regeneration. We compare these approaches with other approaches based on data replication and Reed-Solomon codes. A simulator has been developed...... to carry out a thorough performance evaluation of the various approaches when relying on different system settings, e.g., finite fields, and network/storage conditions, e.g., storage space used per cloud, limited network use, and limited recoding capabilities. In contrast to standard coding approaches, our...
Random Linear Network Coding is Key to Data Survival in Highly Dynamic Distributed Storage
DEFF Research Database (Denmark)
Sipos, Marton A.; Fitzek, Frank; Roetter, Daniel Enrique Lucani
2015-01-01
Distributed storage solutions have become widespread due to their ability to store large amounts of data reliably across a network of unreliable nodes, by employing repair mechanisms to prevent data loss. Conventional systems rely on static designs with a central control entity to oversee...... and control the repair process. Given the large costs for maintaining and cooling large data centers, our work proposes and studies the feasibility of a fully decentralized systems that can store data even on unreliable and, sometimes, unavailable mobile devices. This imposes new challenges on the design...... as the number of available nodes varies greatly over time and keeping track of the system's state becomes unfeasible. As a consequence, conventional erasure correction approaches are ill-suited for maintaining data integrity. In this highly dynamic context, random linear network coding (RLNC) provides...
Random distribution of background charge density for numerical simulation of discharge inception
International Nuclear Information System (INIS)
Grange, F.; Loiseau, J.F.; Spyrou, N.
1998-01-01
The models of electric streamers based on a uniform background density of electrons may appear not to be physical, as the number of electrons in the small active region located in the vicinity of the electrode tip under regular conditions can be less than one. To avoid this, the electron background is modelled by a random density distribution such that, after a certain time lag, at least one electron is present in the grid close to the point electrode. The modelling performed shows that the streamer inception is not very sensitive to the initial location of the charged particles; the ionizing front, however, may be delayed by several tens of nanoseconds, depending on the way the electron has to drift before reaching the anode. (J.U.)
Energy Technology Data Exchange (ETDEWEB)
Schubert, I; Rieger, R [Akademie der Wissenschaften der DDR, Gatersleben. Zentralinst. fuer Genetik und Kulturpflanzenforschung
1976-04-01
A reconstructed karyotype of Vicia faba, with all chromosomes individually distinguishable, was treated with X-rays, fast neutrons, (/sup 3/H) uridine (/sup 3/HU). The distribution within metaphase chromosomes of induced chromatid aberrations was non-random for all agents used. Aberration clustering, in part agent specific, occurred in chromosome segments containing heterochromatin as defined by the presence of G bands. The pattern of aberration clustering found after treatment with /sup 3/HU did not allow the recognition of chromosome regions active in transcription during treatment. Furthermore, it was impossible to obtain unambiguous indications of the presence of AT- and GC-base clusters from the patterns of /sup 3/HT- and /sup 3/HC-induced chromatid aberrations, respectively. Possible reasons underlying these observations are discussed.
Liu, Hong; Zhu, Jingping; Wang, Kai
2015-08-24
The geometrical attenuation model given by Blinn was widely used in the geometrical optics bidirectional reflectance distribution function (BRDF) models. Blinn's geometrical attenuation model based on symmetrical V-groove assumption and ray scalar theory causes obvious inaccuracies in BRDF curves and negatives the effects of polarization. Aiming at these questions, a modified polarized geometrical attenuation model based on random surface microfacet theory is presented by combining of masking and shadowing effects and polarized effect. The p-polarized, s-polarized and unpolarized geometrical attenuation functions are given in their separate expressions and are validated with experimental data of two samples. It shows that the modified polarized geometrical attenuation function reaches better physical rationality, improves the precision of BRDF model, and widens the applications for different polarization.
Improvement of Characteristics of Clayey Soil Mixed with Randomly Distributed Natural Fibers
Maity, J.; Chattopadhyay, B. C.; Mukherjee, S. P.
2017-11-01
In subgrade construction for flexible road pavement, properties of clayey soils available locally can be improved by providing randomly distributed fibers in the soil. The fibers added in subgrade constructions are expected to provide better compact interlocking system between the fiber and the soil grain, greater resistance to deformation and quicker dissipation of pore water pressure, thus helping consolidation and strengthening. Many natural fibers like jute, coir, sabai grass etc. which are economical and eco-friendly, are grown in abundance in India. If suitable they can be used as additive material in the subgrade soil to result in increase in strength and decrease in deformability. Such application will also reduce the cost of construction of roads, by providing lesser thickness of pavement layer. In this paper, the efficacy of using natural jute, coir or sabai grass fibers with locally available clayey soil has been studied. A series of Standard Proctor test, Soaked and Unsoaked California Bearing Ratio (CBR) test, and Unconfined Compressive Strength test were done on locally available clayey soil mixed with different types of natural fiber for various length and proportion to study the improvement of strength properties of fiber-soil composites placed at optimum moisture content. From the test results, it was observed that there was a substantial increase in CBR value for the clayey soil when mixed with increasing percentage of all three types of randomly distributed natural fibers up to 2% of the dry weight of soil. The CBR attains maximum value when the length for all types of fibers mixed with the clay taken in this study, attains a value of 10 mm.
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.
The sink strengths of voids and the expected swelling for both random and ordered void distributions
International Nuclear Information System (INIS)
Quigley, T.M.; Murphy, S.M.; Bullough, R.; Wood, M.H.
1981-10-01
The sink strength of a void has been obtained when the void is a member of a random or ordered distribution of voids. The former sink strength derivation has employed the embedding model and the latter the cellular model. In each case the spatially varying size-effect interaction between the intrinsic point defects and the voids has been included together with the presence of other sink types in addition to the voids. The results are compared with previously published sink strengths that have made use of an approximate representation for the size-effect interactions, and indicate the importance of using the exact form of the interaction. In particular the bias for interstitials compared with vacancies of small voids is now much reduced and contamination of the surfaces of such voids no longer appears essential to facilitate the nucleation and growth of the voids. These new sink strengths have been used, in conjunction with recently published dislocation sink strengths, to calculate the expected swelling of materials containing network dislocations and voids. Results are presented for both the random and the void lattice situations. (author)
Ledford, Christy J W; Womack, Jasmyne J; Rider, Heather A; Seehusen, Angela B; Conner, Stephen J; Lauters, Rebecca A; Hodge, Joshua A
2018-06-01
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.
Process Modeling for Energy Usage in “Smart House” System with a Help of Markov Discrete Chain
Directory of Open Access Journals (Sweden)
Victor Kravets
2016-05-01
Full Text Available Method for evaluating economic efficiency of technical systems using discrete Markov chains modelling illustrated by the system of “Smart house”, consisting, for example, of the three independently functioning elements. Dynamic model of a random power consumption process in the form of a symmetrical state graph of heterogeneous discrete Markov chain is built. The corresponding mathematical model of a random Markov process of power consumption in the “smart house” system in recurrent matrix form is being developed. Technique of statistical determination of probability of random transition elements of the system and the corresponding to the transition probability matrix of the discrete inhomogeneous Markov chain are developed. Statistically determined random transitions of system elements power consumption and the corresponding distribution laws are introduced. The matrix of transition prices, expectations for the possible states of a system price transition and, eventually, the cost of Markov process of power consumption throughout the day.
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...
Quantifying spatial distribution of snow depth errors from LiDAR using Random Forests
Tinkham, W.; Smith, A. M.; Marshall, H.; Link, T. E.; Falkowski, M. J.; Winstral, A. H.
2013-12-01
There is increasing need to characterize the distribution of snow in complex terrain using remote sensing approaches, especially in isolated mountainous regions that are often water-limited, the principal source of terrestrial freshwater, and sensitive to climatic shifts and variations. We apply intensive topographic surveys, multi-temporal LiDAR, and Random Forest modeling to quantify snow volume and characterize associated errors across seven land cover types in a semi-arid mountainous catchment at a 1 and 4 m spatial resolution. The LiDAR-based estimates of both snow-off surface topology and snow depths were validated against ground-based measurements across the catchment. Comparison of LiDAR-derived snow depths to manual snow depth surveys revealed that LiDAR based estimates were more accurate in areas of low lying vegetation such as shrubs (RMSE = 0.14 m) as compared to areas consisting of tree cover (RMSE = 0.20-0.35 m). The highest errors were found along the edge of conifer forests (RMSE = 0.35 m), however a second conifer transect outside the catchment had much lower errors (RMSE = 0.21 m). This difference is attributed to the wind exposure of the first site that led to highly variable snow depths at short spatial distances. The Random Forest modeled errors deviated from the field measured errors with a RMSE of 0.09-0.34 m across the different cover types. Results show that snow drifts, which are important for maintaining spring and summer stream flows and establishing and sustaining water-limited plant species, contained 30 × 5-6% of the snow volume while only occupying 10% of the catchment area similar to findings by prior physically-based modeling approaches. This study demonstrates the potential utility of combining multi-temporal LiDAR with Random Forest modeling to quantify the distribution of snow depth with a reasonable degree of accuracy. Future work could explore the utility of Terrestrial LiDAR Scanners to produce validation of snow-on surface
Zhao, Chao; Jiang, Jingchi; Guan, Yi; Guo, Xitong; He, Bin
2018-05-01
Electronic medical records (EMRs) contain medical knowledge that can be used for clinical decision support (CDS). Our objective is to develop a general system that can extract and represent knowledge contained in EMRs to support three CDS tasks-test recommendation, initial diagnosis, and treatment plan recommendation-given the condition of a patient. We extracted four kinds of medical entities from records and constructed an EMR-based medical knowledge network (EMKN), in which nodes are entities and edges reflect their co-occurrence in a record. Three bipartite subgraphs (bigraphs) were extracted from the EMKN, one to support each task. One part of the bigraph was the given condition (e.g., symptoms), and the other was the condition to be inferred (e.g., diseases). Each bigraph was regarded as a Markov random field (MRF) to support the inference. We proposed three graph-based energy functions and three likelihood-based energy functions. Two of these functions are based on knowledge representation learning and can provide distributed representations of medical entities. Two EMR datasets and three metrics were utilized to evaluate the performance. As a whole, the evaluation results indicate that the proposed system outperformed the baseline methods. The distributed representation of medical entities does reflect similarity relationships with respect to knowledge level. Combining EMKN and MRF is an effective approach for general medical knowledge representation and inference. Different tasks, however, require individually designed energy functions. Copyright © 2018 Elsevier B.V. All rights reserved.
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.
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.
Discrete Choice and Rational Inattention
DEFF Research Database (Denmark)
Fosgerau, Mogens; Melo, Emerson; de Palma, André
2017-01-01
This paper establishes a general equivalence between discrete choice and rational inattention models. Matejka and McKay (2015, AER) showed that when information costs are modelled using the Shannon entropy, the result- ing choice probabilities in the rational inattention model take the multinomial...... logit form. We show that when information costs are modelled using a class of generalized entropies, then the choice probabilities in any rational inattention model are observationally equivalent to some additive random utility discrete choice model and vice versa. This equivalence arises from convex...
Yura, Harold T; Hanson, Steen G
2012-04-01
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 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 examples with relevance for optics are given.
International Nuclear Information System (INIS)
Yanchev, I.
2003-01-01
A new expression for the Fourier transform of the binary correlation function of the random potential near the semiconductor-insulator interface is derived. The screening from the metal electrode in MIS-structure is taken into account introducing an effective insulator thickness. An essential advantage of this correlation function is the finite dispersion of the random potential to which it leads in distinction with the so far known correlation functions leading to a divergent dispersion. The dispersion, an important characteristic of the random potential distribution, determining the amplitude of the potential fluctuations is calculated
International Nuclear Information System (INIS)
Yanchev, I; Slavcheva, G.
1993-01-01
A new expression for the Fourier transform of the binary correlation function of the random potential near the semiconductor-insulator interface is derived. The screening from the metal electrode in MIS-structure is taken into account introducing an effective insulator thickness. An essential advantage of this correlation function is the finite dispersion of the random potential Γ 2 to which it leads in distinction with the so far known correlation functions leading to divergent dispersion. The important characteristic of the random potential distribution Γ 2 determining the amplitude of the potential fluctuations is calculated. 7 refs. (orig.)
International Nuclear Information System (INIS)
Slavcheva, G.; Yanchev, I.
1991-01-01
A new expression for the Fourier transform of the binary correlation function of the random potential near the semiconductor-insulator interface is derived. The screening due to the image charge with respect to the metal electrode in MIS-structure is taken into account, introducing an effective insulator thickness. An essential advantage of this correlation function is the finite dispersion of the random potential Γ 2 to which it leads in distinction with the so far known correlation functions leading to divergent dispersion. The important characteristic of the random potential distribution Γ 2 determining the amplitude of the potential fluctuations is calculated. (author). 7 refs, 1 fig
Yanchev, I
2003-01-01
A new expression for the Fourier transform of the binary correlation function of the random potential near the semiconductor-insulator interface is derived. The screening from the metal electrode in MIS-structure is taken into account introducing an effective insulator thickness. An essential advantage of this correlation function is the finite dispersion of the random potential to which it leads in distinction with the so far known correlation functions leading to a divergent dispersion. The dispersion, an important characteristic of the random potential distribution, determining the amplitude of the potential fluctuations is calculated.
Energy Technology Data Exchange (ETDEWEB)
Yanchev, I
2003-07-01
A new expression for the Fourier transform of the binary correlation function of the random potential near the semiconductor-insulator interface is derived. The screening from the metal electrode in MIS-structure is taken into account introducing an effective insulator thickness. An essential advantage of this correlation function is the finite dispersion of the random potential to which it leads in distinction with the so far known correlation functions leading to a divergent dispersion. The dispersion, an important characteristic of the random potential distribution, determining the amplitude of the potential fluctuations is calculated.
Effects of random pebble distribution on the multiplication factor in HTR pebble bed reactors
Energy Technology Data Exchange (ETDEWEB)
Auwerda, G.J., E-mail: g.j.auwerda@tudelft.n [Department of Physics of Nuclear Reactors at the Delft University of Technology, Mekelweg 15, Delft (Netherlands); Kloosterman, J.L.; Lathouwers, D.; Hagen, T.H.J.J. van der [Department of Physics of Nuclear Reactors at the Delft University of Technology, Mekelweg 15, Delft (Netherlands)
2010-08-15
In pebble bed reactors the pebbles have a random distribution within the core. The usual approach in modeling the bed is homogenizing the entire bed. To quantify the errors arising in such a model, this article investigates the effect on k{sub eff} of three phenomena in random pebble distributions: non-uniform packing density, neutron streaming in between the pebbles, and variations in Dancoff factor. For a 100 cm high cylinder with reflective top and bottom boundary conditions 25 pebble beds were generated. Of each bed three core models were made: a homogeneous model, a zones model including density fluctuations, and an exact model with all pebbles modeled individually. The same was done for a model of the PROTEUS facility. k{sub eff} calculations were performed with three codes: Monte Carlo, diffusion, and finite element transport. By comparing k{sub eff} of the homogenized and zones model the effect of including density fluctuations in the pebble bed was found to increase k{sub eff} by 71 pcm for the infinite cylinder and 649 pcm for PROTEUS. The large value for PROTEUS is due to the low packing fraction near the top of the pebble bed, causing a significant lower packing fraction for the bulk of the pebble bed in the homogenized model. The effect of neutron streaming was calculated by comparing the zones model with the exact model, and was found to decrease k{sub eff} by 606 pcm for the infinite cylinder, and by 1240 pcm for PROTEUS. This was compared with the effect of using a streaming correction factor on the diffusion coefficient in the zones model, which resulted in {Delta}{sub streaming} values of 340 and 1085 pcm. From this we conclude neutron streaming is an important effect in pebble bed reactors, and is not accurately described by the correction factor on the diffusion coefficient. Changing the Dancoff factor in the outer part of the pebble bed to compensate for the lower probability of neutrons to enter other fuel pebbles caused no significant changes
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...
Huang, N. E.; Tung, C.-C.
1977-01-01
The influence of the directional distribution of wave energy on the dispersion relation is calculated numerically using various directional wave spectrum models. The results indicate that the dispersion relation varies both as a function of the directional energy distribution and the direction of propagation of the wave component under consideration. Furthermore, both the mean deviation and the random scatter from the linear approximation increase as the energy spreading decreases. Limited observational data are compared with the theoretical results. The agreement is favorable.
Current-voltage characteristic of a Josephson junction with randomly distributed Abrikosov vortices
International Nuclear Information System (INIS)
Fistul, M.V.; Giuliani, G.F.
1997-01-01
We have developed a theory of the current-voltage characteristic of a Josephson junction in the presence of randomly distributed, pinned misaligned Abrikosov vortices oriented perpendicularly to the junction plane. Under these conditions the Josephson phase difference var-phi acquires an interesting stochastic dependence on the position in the plane of the junction. In this situation it is possible to define an average critical current which is determined by the spatial correlations of this function. Due to the inhomogeneity, we find that for finite voltage bias the electromagnetic waves propagating in the junction display a broad spectrum of wavelengths. This is at variance with the situation encountered in homogeneous junctions. The amplitude of these modes is found to decrease as the bias is increased. We predict that the presence of these excitations is directly related to a remarkable feature in the current-voltage characteristic. The dependence of the position and the magnitude of this feature on the vortex concentration has been determined. copyright 1997 The American Physical Society
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.
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.
Probing the random distribution of half-metallic Co2Mn1-xFexSi Heusler alloys
Wurmehl, S.; Kohlhepp, J.T.; Swagten, H.J.M.; Koopmans, B.; Wójcik, M.; Balke, B.; Blum, C.G.F.; Ksenofontov, V.; Fecher, G.H.; Felser, C.
2007-01-01
Co2Mn1-xFexSi Heusler alloys crystallize in the L21 structure. This structure type requires random distribution of Mn and Fe in case of the mixed alloys. The spin echo nuclear magnetic resonance (NMR) technique probes the direct local environments of the active atoms and is thus able to resolve next
International Nuclear Information System (INIS)
Perotin, L.; Granger, S.
1997-01-01
In order to improve the prediction of wear problems due to flow-induced vibration in PWR components, an inverse method for identifying a distributed random excitation acting on a dynamical system has been developed at EDF. This method, whose applications go far beyond the flow-induced vibration field, has been implemented into the MEIDEE software. This method is presented. (author)
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
Energy Technology Data Exchange (ETDEWEB)
Flyckt, V M M; Raaymakers, B W; Lagendijk, J J W [Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht (Netherlands)
2006-10-07
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.
International Nuclear Information System (INIS)
Flyckt, V M M; Raaymakers, B W; Lagendijk, J J W
2006-01-01
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
Gong, Yongmei; Zwinger, Thomas; Åström, Jan; Gladstone, Rupert; Schellenberger, Thomas; Altena, Bas; Moore, John
2017-04-01
The outlet glacier at Basin 3, Austfonna ice-cap entered its active surge phase in autumn 2012. We assess the evolution of the basal friction during the surge through inverse modelling of basal friction coefficients using recent velocity observation from 2012 to 2014 in a continuum ice dynamic model Elmer/ice. The obtained basal friction coefficient distributions at different time instances are further used as a boundary condition in a discrete element model (HiDEM) that is capable of computing fracturing of ice. The inverted basal friction coefficient evolution shows a gradual 'unplugging' of the stagnant frontal area and northwards and inland expansion of the fast flowing region in the southern basin. The validation between the modeled crevasses distribution and the satellite observation in August 2013 shows a good agreement in shear zones inland and at the frontal area. Crevasse distributions of the summer before and after the glacier reached its maximum velocity in January 2013 (August 2012 and August 2014, respectively) are also evaluated. Previous studies suggest the triggering and development of the surge are linked to surface melt water penetrating through ice to form an efficient basal hydrology system thereby triggering a hydro- thermodynamic feedback. This preliminary offline coupling between a continuum ice dynamic model and a discrete element model will give a hint on future model development of linking supra-glacial to sub-glacial hydrology system.
International Nuclear Information System (INIS)
Souza, Manoelito M. de
1997-01-01
We discuss the physical meaning and the geometric interpretation of implementation in classical field theories. The origin of infinities and other inconsistencies in field theories is traced to fields defined with support on the light cone; a finite and consistent field theory requires a light-cone generator as the field support. Then, we introduce a classical field theory with support on the light cone generators. It results on a description of discrete (point-like) interactions in terms of localized particle-like fields. We find the propagators of these particle-like fields and discuss their physical meaning, properties and consequences. They are conformally invariant, singularity-free, and describing a manifestly covariant (1 + 1)-dimensional dynamics in a (3 = 1) spacetime. Remarkably this conformal symmetry remains even for the propagation of a massive field in four spacetime dimensions. We apply this formalism to Classical electrodynamics and to the General Relativity Theory. The standard formalism with its distributed fields is retrieved in terms of spacetime average of the discrete field. Singularities are the by-products of the averaging process. This new formalism enlighten the meaning and the problem of field theory, and may allow a softer transition to a quantum theory. (author)
Wróbel, P.; Antosiewicz, T. J.; Stefaniuk, T.; Ciesielski, A.; Iwan, A.; Wronkowska, A. A.; Wronkowski, A.; Szoplik, T.
2015-05-01
In photovoltaic devices, metal nanoparticles embedded in a semiconductor layer allow the enhancement of solar-toelectric energy conversion efficiency due to enhanced light absorption via a prolonged optical path, enhanced electric fields near the metallic inclusions, direct injection of hot electrons, or local heating. Here we pursue the first two avenues. In the first, light scattered at an angle beyond the critical angle for reflection is coupled into the semiconductor layer and confined within such planar waveguide up to possible exciton generation. In the second, light is trapped by the excitation of localized surface plasmons on metal nanoparticles leading to enhanced near-field plasmon-exciton coupling at the peak of the plasmon resonance. We report on results of a numerical experiment on light absorption in polymer- (fullerene derivative) blends, using the 3D FDTD method, where exact optical parameters of the materials involved are taken from our recent measurements. In simulations we investigate light absorption in randomly distributed metal nanoparticles dispersed in polyazomethine-(fullerene derivative) blends, which serve as active layers in bulkheterojunction polymer solar cells. In the study Ag and Al nanoparticles of different diameters and fill factors are diffused in two air-stable aromatic polyazomethines with different chemical structures (abbreviated S9POF and S15POF) mixed with phenyl-C61-butyric acid methyl ester (PCBM) or [6,6]-phenyl-C71-butyric acid methyl ester (PC71BM). The mixtures are spin coated on a 100 nm thick Al layer deposited on a fused silica substrate. Optical constants of the active layers are taken from spectroscopic ellipsometry and reflectance measurements using a rotating analyzer type ellipsometer with auto-retarder performed in the wavelength range from 225 nm to 2200 nm. The permittivities of Ag and Al particles of diameters from 20 to 60 nm are assumed to be equal to those measured on 100 to 200 nm thick metal films.
DEFF Research Database (Denmark)
Jeong, Cheol-Ho
2009-01-01
Most acoustic measurements are based on an assumption of ideal conditions. One such ideal condition is a diffuse and reverberant field. In practice, a perfectly diffuse sound field cannot be achieved in a reverberation chamber. Uneven incident energy density under measurement conditions can cause...... 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...
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...
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.
Ponomarev, A. L.; Brenner, D.; Hlatky, L. R.; Sachs, R. K.
2000-01-01
DNA double-strand breaks (DSBs) produced by densely ionizing radiation are not located randomly in the genome: recent data indicate DSB clustering along chromosomes. Stochastic DSB clustering at large scales, from > 100 Mbp down to simulations and analytic equations. A random-walk, coarse-grained polymer model for chromatin is combined with a simple track structure model in Monte Carlo software called DNAbreak and is applied to data on alpha-particle irradiation of V-79 cells. The chromatin model neglects molecular details but systematically incorporates an increase in average spatial separation between two DNA loci as the number of base-pairs between the loci increases. Fragment-size distributions obtained using DNAbreak match data on large fragments about as well as distributions previously obtained with a less mechanistic approach. Dose-response relations, linear at small doses of high linear energy transfer (LET) radiation, are obtained. They are found to be non-linear when the dose becomes so large that there is a significant probability of overlapping or close juxtaposition, along one chromosome, for different DSB clusters from different tracks. The non-linearity is more evident for large fragments than for small. The DNAbreak results furnish an example of the RLC (randomly located clusters) analytic formalism, which generalizes the broken-stick fragment-size distribution of the random-breakage model that is often applied to low-LET data.
Time Discretization Techniques
Gottlieb, S.; Ketcheson, David I.
2016-01-01
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
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.
Energy Technology Data Exchange (ETDEWEB)
Lee, Jae Yong; Kim, Song Hyun; Shin, Chang Ho; Kim, Jong Kyung [Hanyang Univ., Seoul (Korea, Republic of)
2014-05-15
In this study, as a preliminary study to develop an implicit method having high accuracy, the distribution characteristics of spherical particles were evaluated by using explicit modeling techniques in various volume packing fractions. This study was performed to evaluate implicitly simulated distribution of randomly packed spheres in a medium. At first, an explicit modeling method to simulate random packed spheres in a hexahedron medium was proposed. The distributed characteristics of l{sub p} and r{sub p}, which are used in the particle position sampling, was estimated. It is analyzed that the use of the direct exponential distribution, which is generally used in the implicit modeling, can cause the distribution bias of the spheres. It is expected that the findings in this study can be utilized for improving the accuracy in using the implicit method. Spherical particles, which are randomly distributed in medium, are utilized for the radiation shields, fusion reactor blanket, fuels of VHTR reactors. Due to the difficulty on the simulation of the stochastic distribution, Monte Carlo (MC) method has been mainly considered as the tool for the analysis of the particle transport. For the MC modeling of the spherical particles, three methods are known; repeated structure, explicit modeling, and implicit modeling. Implicit method (called as the track length sampling method) is a modeling method that is the sampling based modeling technique of each spherical geometry (or track length of the sphere) during the MC simulation. Implicit modeling method has advantages in high computational efficiency and user convenience. However, it is noted that the implicit method has lower modeling accuracy in various finite mediums.
Directory of Open Access Journals (Sweden)
A. Stankovic
2012-12-01
Full Text Available The distributions of random variables are of interest in many areas of science. In this paper, ascertaining on the importance of multi-hop transmission in contemporary wireless communications systems operating over fading channels in the presence of cochannel interference, the probability density functions (PDFs of minimum of arbitrary number of ratios of Rayleigh, Rician, Nakagami-m, Weibull and α-µ random variables are derived. These expressions can be used to study the outage probability as an important multi-hop system performance measure. Various numerical results complement the proposed mathematical analysis.
Anastario, Michael P; Rodriguez, Hector P; Gallagher, Patricia M; Cleary, Paul D; Shaller, Dale; Rogers, William H; Bogen, Karen; Safran, Dana Gelb
2010-01-01
Objective To assess the effect of survey distribution protocol (mail versus handout) on data quality and measurement of patient care experiences. Data Sources/Study Setting Multisite randomized trial of survey distribution protocols. Analytic sample included 2,477 patients of 15 clinicians at three practice sites in New York State. Data Collection/Extraction Methods Mail and handout distribution modes were alternated weekly at each site for 6 weeks. Principal Findings Handout protocols yielded an incomplete distribution rate (74 percent) and lower overall response rates (40 percent versus 58 percent) compared with mail. Handout distribution rates decreased over time and resulted in more favorable survey scores compared with mailed surveys. There were significant mode–physician interaction effects, indicating that data cannot simply be pooled and adjusted for mode. Conclusions In-office survey distribution has the potential to bias measurement and comparison of physicians and sites on patient care experiences. Incomplete distribution rates observed in-office, together with between-office differences in distribution rates and declining rates over time suggest staff may be burdened by the process and selective in their choice of patients. Further testing with a larger physician and site sample is important to definitively establish the potential role for in-office distribution in obtaining reliable, valid assessment of patient care experiences. PMID:20579126
Müller, Christian L.; Sbalzarini, Ivo F.; van Gunsteren, Wilfred F.; Žagrović, Bojan; Hünenberger, Philippe H.
2009-06-01
The concept of high-resolution shapes (also referred to as folds or states, depending on the context) of a polymer chain plays a central role in polymer science, structural biology, bioinformatics, and biopolymer dynamics. However, although the idea of shape is intuitively very useful, there is no unambiguous mathematical definition for this concept. In the present work, the distributions of high-resolution shapes within the ideal random-walk ensembles with N =3,…,6 beads (or up to N =10 for some properties) are investigated using a systematic (grid-based) approach based on a simple working definition of shapes relying on the root-mean-square atomic positional deviation as a metric (i.e., to define the distance between pairs of structures) and a single cutoff criterion for the shape assignment. Although the random-walk ensemble appears to represent the paramount of homogeneity and randomness, this analysis reveals that the distribution of shapes within this ensemble, i.e., in the total absence of interatomic interactions characteristic of a specific polymer (beyond the generic connectivity constraint), is significantly inhomogeneous. In particular, a specific (densest) shape occurs with a local probability that is 1.28, 1.79, 2.94, and 10.05 times (N =3,…,6) higher than the corresponding average over all possible shapes (these results can tentatively be extrapolated to a factor as large as about 1028 for N =100). The qualitative results of this analysis lead to a few rather counterintuitive suggestions, namely, that, e.g., (i) a fold classification analysis applied to the random-walk ensemble would lead to the identification of random-walk "folds;" (ii) a clustering analysis applied to the random-walk ensemble would also lead to the identification random-walk "states" and associated relative free energies; and (iii) a random-walk ensemble of polymer chains could lead to well-defined diffraction patterns in hypothetical fiber or crystal diffraction experiments
Reliable gain-scheduled control of discrete-time systems and its application to CSTR model
Sakthivel, R.; Selvi, S.; Mathiyalagan, K.; Shi, Y.
2016-10-01
This paper is focused on reliable gain-scheduled controller design for a class of discrete-time systems with randomly occurring nonlinearities and actuator fault. Further, the nonlinearity in the system model is assumed to occur randomly according to a Bernoulli distribution with measurable time-varying probability in real time. The main purpose of this paper is to design a gain-scheduled controller by implementing a probability-dependent Lyapunov function and linear matrix inequality (LMI) approach such that the closed-loop discrete-time system is stochastically stable for all admissible randomly occurring nonlinearities. The existence conditions for the reliable controller is formulated in terms of LMI constraints. Finally, the proposed reliable gain-scheduled control scheme is applied on continuously stirred tank reactor model to demonstrate the effectiveness and applicability of the proposed design technique.
Sakaguchi, Hidetsugu; Kadowaki, Shuntaro
2017-07-01
We study slowly pulling block-spring models in random media. Second-order phase transitions exist in a model pulled by a constant force in the case of velocity-strengthening friction. If external forces are slowly increased, nearly critical states are self-organized. Slips of various sizes occur, and the probability distributions of slip size roughly obey power laws. The exponent is close to that in the quenched Edwards-Wilkinson model. Furthermore, the slip-size distributions are investigated in cases of Coulomb friction, velocity-weakening friction, and two-dimensional block-spring models.
Changzhi, Bian
2015-01-01
This paper addresses the multiobjective discrete network design problem under demand uncertainty. The OD travel demands are supposed to be random variables with the given probability distribution. The problem is formulated as a bilevel stochastic optimization model where the decision maker’s objective is to minimize the construction cost, the expectation, and the standard deviation of total travel time simultaneously and the user’s route choice is described using user equilibrium model on the...
International Nuclear Information System (INIS)
Rosales, J.; Perez, J.; Garcia, C.; Munnoz, A.; Lira, C. A. B. O.
2015-01-01
TRISO particles are the specific features of HTR-10 and generally HTGR reactors. Their heterogeneity and random arrangement in graphite matrix of these reactors create a significant modeling challenge. In the simulation of spherical fuel elements using MCNPX are usually created repetitive structures using uniform distribution models. The use of these repetitive structures introduces two major approaches: the non-randomness of the TRISO particles inside the pebbles and the intersection of the pebble surface with the TRISO particles. These approaches could affect significantly the multiplicative properties of the core. In order to study the influence of these approaches in the multiplicative properties was estimated the K inf value in one pebble with white boundary conditions using 4 different configurations regarding the distribution of the TRISO particles inside the pebble: uniform hexagonal model, cubic uniform model, cubic uniform without the effect of cutting and a random distribution model. It was studied the impact these models on core scale solving the problem B1, from the Benchmark Problems presented in a Coordinated Research Program of the IAEA. (Author)
A Spectral Analysis of Discrete-Time Quantum Walks Related to the Birth and Death Chains
Ho, Choon-Lin; Ide, Yusuke; Konno, Norio; Segawa, Etsuo; Takumi, Kentaro
2018-04-01
In this paper, we consider a spectral analysis of discrete time quantum walks on the path. For isospectral coin cases, we show that the time averaged distribution and stationary distributions of the quantum walks are described by the pair of eigenvalues of the coins as well as the eigenvalues and eigenvectors of the corresponding random walks which are usually referred as the birth and death chains. As an example of the results, we derive the time averaged distribution of so-called Szegedy's walk which is related to the Ehrenfest model. It is represented by Krawtchouk polynomials which is the eigenvectors of the model and includes the arcsine law.
Discrete Bose-Einstein spectra
International Nuclear Information System (INIS)
Vlad, Valentin I.; Ionescu-Pallas, Nicholas
2001-03-01
The Bose-Einstein energy spectrum of a quantum gas, confined in a rigid cubic box, is shown to become discrete and strongly dependent on the box geometry (size L), temperature, T and atomic mass number, A at , in the region of small γ=A at TV 1/3 . This behavior is the consequence of the random state degeneracy in the box. Furthermore, we demonstrate that the total energy does not obey the conventional law any longer, but a new law, which depends on γ and on the quantum gas fugacity. This energy law imposes a faster decrease to zero than it is classically expected, for γ→0. The lighter the gas atoms, the higher the temperatures or the box size, for the same effects in the discrete Bose-Einstein regime. (author)
Random distance distribution for spherical objects: general theory and applications to physics
International Nuclear Information System (INIS)
Tu Shuju; Fischbach, Ephraim
2002-01-01
A formalism is presented for analytically obtaining the probability density function, P n (s), for the random distance s between two random points in an n-dimensional spherical object of radius R. Our formalism allows P n (s) to be calculated for a spherical n-ball having an arbitrary volume density, and reproduces the well-known results for the case of uniform density. The results find applications in geometric probability, computational science, molecular biological systems, statistical physics, astrophysics, condensed matter physics, nuclear physics and elementary particle physics. As one application of these results, we propose a new statistical method derived from our formalism to study random number generators used in Monte Carlo simulations. (author)
APPROXIMATION OF PROBABILITY DISTRIBUTIONS IN QUEUEING MODELS
Directory of Open Access Journals (Sweden)
T. I. Aliev
2013-03-01
Full Text Available For probability distributions with variation coefficient, not equal to unity, mathematical dependences for approximating distributions on the basis of first two moments are derived by making use of multi exponential distributions. It is proposed to approximate distributions with coefficient of variation less than unity by using hypoexponential distribution, which makes it possible to generate random variables with coefficient of variation, taking any value in a range (0; 1, as opposed to Erlang distribution, having only discrete values of coefficient of variation.
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…
Yan, Huaicheng; Zhang, Hao; Yang, Fuwen; Zhan, Xisheng; Peng, Chen
2017-08-18
This paper is concerned with the guaranteed cost control problem for a class of Markov jump discrete-time neural networks (NNs) with event-triggered mechanism, asynchronous jumping, and fading channels. The Markov jump NNs are introduced to be close to reality, where the modes of the NNs and guaranteed cost controller are determined by two mutually independent Markov chains. The asynchronous phenomenon is considered, which increases the difficulty of designing required mode-dependent controller. The event-triggered mechanism is designed by comparing the relative measurement error with the last triggered state at the process of data transmission, which is used to eliminate dispensable transmission and reduce the networked energy consumption. In addition, the signal fading is considered for the effect of signal reflection and shadow in wireless networks, which is modeled by the novel Rice fading models. Some novel sufficient conditions are obtained to guarantee that the closed-loop system reaches a specified cost value under the designed jumping state feedback control law in terms of linear matrix inequalities. Finally, some simulation results are provided to illustrate the effectiveness of the proposed method.
Discrete dipole approximation simulation of bead enhanced diffraction grating biosensor
International Nuclear Information System (INIS)
Arif, Khalid Mahmood
2016-01-01
We present the discrete dipole approximation simulation of light scattering from bead enhanced diffraction biosensor and report the effect of bead material, number of beads forming the grating and spatial randomness on the diffraction intensities of 1st and 0th orders. The dipole models of gratings are formed by volume slicing and image processing while the spatial locations of the beads on the substrate surface are randomly computed using discrete probability distribution. The effect of beads reduction on far-field scattering of 632.8 nm incident field, from fully occupied gratings to very coarse gratings, is studied for various bead materials. Our findings give insight into many difficult or experimentally impossible aspects of this genre of biosensors and establish that bead enhanced grating may be used for rapid and precise detection of small amounts of biomolecules. The results of simulations also show excellent qualitative similarities with experimental observations. - Highlights: • DDA was used to study the relationship between the number of beads forming gratings and ratio of first and zeroth order diffraction intensities. • A very flexible modeling program was developed to design complicated objects for DDA. • Material and spatial effects of bead distribution on surfaces were studied. • It has been shown that bead enhanced grating biosensor can be useful for fast detection of small amounts of biomolecules. • Experimental results qualitatively support the simulations and thus open a way to optimize the grating biosensors.
Sums and Products of Jointly Distributed Random Variables: A Simplified Approach
Stein, Sheldon H.
2005-01-01
Three basic theorems concerning expected values and variances of sums and products of random variables play an important role in mathematical statistics and its applications in education, business, the social sciences, and the natural sciences. A solid understanding of these theorems requires that students be familiar with the proofs of these…
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.
Neigel, J E; Avise, J C
1993-12-01
In rapidly evolving molecules, such as animal mitochondrial DNA, mutations that delineate specific lineages may not be dispersed at sufficient rates to attain an equilibrium between genetic drift and gene flow. Here we predict conditions that lead to nonequilibrium geographic distributions of mtDNA lineages, test the robustness of these predictions and examine mtDNA data sets for consistency with our model. Under a simple isolation by distance model, the variance of an mtDNA lineage's geographic distribution is expected be proportional to its age. Simulation results indicated that this relationship is fairly robust. Analysis of mtDNA data from natural populations revealed three qualitative distributional patterns: (1) significant departure of lineage structure from equilibrium geographic distributions, a pattern exhibited in three rodent species with limited dispersal; (2) nonsignificant departure from equilibrium expectations, exhibited by two avian and two marine fish species with potentials for relatively long-distance dispersal; and (3) a progression from nonequilibrium distributions for younger lineages to equilibrium distributions for older lineages, a condition displayed by one surveyed avian species. These results demonstrate the advantages of considering mutation and genealogy in the interpretation of mtDNA geographic variation.
Distributed fiber sparse-wideband vibration sensing by sub-Nyquist additive random sampling
Zhang, Jingdong; Zheng, Hua; Zhu, Tao; Yin, Guolu; Liu, Min; Bai, Yongzhong; Qu, Dingrong; Qiu, Feng; Huang, Xianbing
2018-05-01
The round trip time of the light pulse limits the maximum detectable vibration frequency response range of phase-sensitive optical time domain reflectometry ({\\phi}-OTDR). Unlike the uniform laser pulse interval in conventional {\\phi}-OTDR, we randomly modulate the pulse interval, so that an equivalent sub-Nyquist additive random sampling (sNARS) is realized for every sensing point of the long interrogation fiber. For an {\\phi}-OTDR system with 10 km sensing length, the sNARS method is optimized by theoretical analysis and Monte Carlo simulation, and the experimental results verify that a wide-band spars signal can be identified and reconstructed. Such a method can broaden the vibration frequency response range of {\\phi}-OTDR, which is of great significance in sparse-wideband-frequency vibration signal detection, such as rail track monitoring and metal defect detection.
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.
Modeling biological tissue growth: discrete to continuum representations.
Hywood, Jack D; Hackett-Jones, Emily J; Landman, Kerry A
2013-09-01
There is much interest in building deterministic continuum models from discrete agent-based models governed by local stochastic rules where an agent represents a biological cell. In developmental biology, cells are able to move and undergo cell division on and within growing tissues. A growing tissue is itself made up of cells which undergo cell division, thereby providing a significant transport mechanism for other cells within it. We develop a discrete agent-based model where domain agents represent tissue cells. Each agent has the ability to undergo a proliferation event whereby an additional domain agent is incorporated into the lattice. If a probability distribution describes the waiting times between proliferation events for an individual agent, then the total length of the domain is a random variable. The average behavior of these stochastically proliferating agents defining the growing lattice is determined in terms of a Fokker-Planck equation, with an advection and diffusion term. The diffusion term differs from the one obtained Landman and Binder [J. Theor. Biol. 259, 541 (2009)] when the rate of growth of the domain is specified, but the choice of agents is random. This discrepancy is reconciled by determining a discrete-time master equation for this process and an associated asymmetric nonexclusion random walk, together with consideration of synchronous and asynchronous updating schemes. All theoretical results are confirmed with numerical simulations. This study furthers our understanding of the relationship between agent-based rules, their implementation, and their associated partial differential equations. Since tissue growth is a significant cellular transport mechanism during embryonic growth, it is important to use the correct partial differential equation description when combining with other cellular functions.
Baecklund transformations for discrete Painleve equations: Discrete PII-PV
International Nuclear Information System (INIS)
Sakka, A.; Mugan, U.
2006-01-01
Transformation properties of discrete Painleve equations are investigated by using an algorithmic method. This method yields explicit transformations which relates the solutions of discrete Painleve equations, discrete P II -P V , with different values of parameters. The particular solutions which are expressible in terms of the discrete analogue of the classical special functions of discrete Painleve equations can also be obtained from these transformations
Sharma, Ajeet K.; Ahmed, Nabeel; O'Brien, Edward P.
2018-02-01
Ribosome profiling experiments have found greater than 100-fold variation in ribosome density along mRNA transcripts, indicating that individual codon elongation rates can vary to a similar degree. This wide range of elongation times, coupled with differences in codon usage between transcripts, suggests that the average codon translation-rate per gene can vary widely. Yet, ribosome run-off experiments have found that the average codon translation rate for different groups of transcripts in mouse stem cells is constant at 5.6 AA/s. How these seemingly contradictory results can be reconciled is the focus of this study. Here, we combine knowledge of the molecular factors shown to influence translation speed with genomic information from Escherichia coli, Saccharomyces cerevisiae and Homo sapiens to simulate the synthesis of cytosolic proteins in these organisms. The model recapitulates a near constant average translation rate, which we demonstrate arises because the molecular determinants of translation speed are distributed nearly randomly amongst most of the transcripts. Consequently, codon translation rates are also randomly distributed and fast-translating segments of a transcript are likely to be offset by equally probable slow-translating segments, resulting in similar average elongation rates for most transcripts. We also show that the codon usage bias does not significantly affect the near random distribution of codon translation rates because only about 10 % of the total transcripts in an organism have high codon usage bias while the rest have little to no bias. Analysis of Ribo-Seq data and an in vivo fluorescent assay supports these conclusions.
Discrete Gabor transform and discrete Zak transform
Bastiaans, M.J.; Namazi, N.M.; Matthews, K.
1996-01-01
Gabor's expansion of a discrete-time signal into a set of shifted and modulated versions of an elementary signal or synthesis window is introduced, along with the inverse operation, i.e. the Gabor transform, which uses an analysis window that is related to the synthesis window and with the help of
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)
Multivariate Discrete First Order Stochastic Dominance
DEFF Research Database (Denmark)
Tarp, Finn; Østerdal, Lars Peter
This paper characterizes the principle of first order stochastic dominance in a multivariate discrete setting. We show that a distribution f first order stochastic dominates distribution g if and only if f can be obtained from g by iteratively shifting density from one outcome to another...
International Nuclear Information System (INIS)
Bunzl, K.
2002-01-01
In the field, the distribution coefficient, K d , for the sorption of a radionuclide by the soil cannot be expected to be constant. Even in a well defined soil horizon, K d will vary stochastically in horizontal as well as in vertical direction around a mean value. The horizontal random variability of K d produce a pronounced tailing effect in the concentration depth profile of a fallout radionuclide, much less is known on the corresponding effect of the vertical random variability. To analyze this effect theoretically, the classical convection-dispersion model in combination with the random-walk particle method was applied. The concentration depth profile of a radionuclide was calculated one year after deposition assuming constant values of the pore water velocity, the diffusion/dispersion coefficient, and the distribution coefficient (K d = 100 cm 3 x g -1 ) and exhibiting a vertical variability for K d according to a log-normal distribution with a geometric mean of 100 cm 3 x g -1 and a coefficient of variation of CV 0.53. The results show that these two concentration depth profiles are only slightly different, the location of the peak is shifted somewhat upwards, and the dispersion of the concentration depth profile is slightly larger. A substantial tailing effect of the concentration depth profile is not perceivable. Especially with respect to the location of the peak, a very good approximation of the concentration depth profile is obtained if the arithmetic mean of the K d -values (K d = 113 cm 3 x g -1 ) and a slightly increased dispersion coefficient are used in the analytical solution of the classical convection-dispersion equation with constant K d . The evaluation of the observed concentration depth profile with the analytical solution of the classical convection-dispersion equation with constant parameters will, within the usual experimental limits, hardly reveal the presence of a log-normal random distribution of K d in the vertical direction in
Directory of Open Access Journals (Sweden)
Min-Jhong Gu
2014-08-01
Full Text Available This article describes the development of a suite of programs that is capable of simulating the radiation properties of a random rough surface (RRS. The fundamental approach involves the generation, by fast Fourier transform (FFT built with rigorous finite difference time domain (FDTD, as the theoretical basis for the simulation of a bidirectional reflectance distribution function (BRDF of the RRS. The results are compared with the measurements and modeling of existing work to verify the feasibility of customized programming. It was found that the results of this study were a better match to the measurement data than those achieved in other modeling work.
International Nuclear Information System (INIS)
Chen, Binchao; Phillips, Aaron; Matis, Timothy I.
2012-01-01
The random waypoint (RWP) mobility model is frequently used in describing the movement pattern of mobile users in a mobile ad hoc network (MANET). As the asymptotic spatial distribution of nodes under a RWP model exhibits central tendency, the two-terminal reliability of the MANET is investigated as a function of the source node location. In particular, analytical expressions for one and two hop connectivities are developed as well as an efficient simulation methodology for two-terminal reliability. A study is then performed to assess the effect of nodal density and network topology on network reliability.
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.
Homogenization of discrete media
International Nuclear Information System (INIS)
Pradel, F.; Sab, K.
1998-01-01
Material such as granular media, beam assembly are easily seen as discrete media. They look like geometrical points linked together thanks to energetic expressions. Our purpose is to extend discrete kinematics to the one of an equivalent continuous material. First we explain how we build the localisation tool for periodic materials according to estimated continuum medium type (classical Cauchy, and Cosserat media). Once the bridge built between discrete and continuum media, we exhibit its application over two bidimensional beam assembly structures : the honey comb and a structural reinforced variation. The new behavior is then applied for the simple plan shear problem in a Cosserat continuum and compared with the real discrete solution. By the mean of this example, we establish the agreement of our new model with real structures. The exposed method has a longer range than mechanics and can be applied to every discrete problems like electromagnetism in which relationship between geometrical points can be summed up by an energetic function. (orig.)
International Nuclear Information System (INIS)
Aydin, Alhun; Sisman, Altug
2016-01-01
By considering the quantum-mechanically minimum allowable energy interval, we exactly count number of states (NOS) and introduce discrete density of states (DOS) concept for a particle in a box for various dimensions. Expressions for bounded and unbounded continua are analytically recovered from discrete ones. Even though substantial fluctuations prevail in discrete DOS, they're almost completely flattened out after summation or integration operation. It's seen that relative errors of analytical expressions of bounded/unbounded continua rapidly decrease for high NOS values (weak confinement or high energy conditions), while the proposed analytical expressions based on Weyl's conjecture always preserve their lower error characteristic. - Highlights: • Discrete density of states considering minimum energy difference is proposed. • Analytical DOS and NOS formulas based on Weyl conjecture are given. • Discrete DOS and NOS functions are examined for various dimensions. • Relative errors of analytical formulas are much better than the conventional ones.
Energy Technology Data Exchange (ETDEWEB)
Aydin, Alhun; Sisman, Altug, E-mail: sismanal@itu.edu.tr
2016-03-22
By considering the quantum-mechanically minimum allowable energy interval, we exactly count number of states (NOS) and introduce discrete density of states (DOS) concept for a particle in a box for various dimensions. Expressions for bounded and unbounded continua are analytically recovered from discrete ones. Even though substantial fluctuations prevail in discrete DOS, they're almost completely flattened out after summation or integration operation. It's seen that relative errors of analytical expressions of bounded/unbounded continua rapidly decrease for high NOS values (weak confinement or high energy conditions), while the proposed analytical expressions based on Weyl's conjecture always preserve their lower error characteristic. - Highlights: • Discrete density of states considering minimum energy difference is proposed. • Analytical DOS and NOS formulas based on Weyl conjecture are given. • Discrete DOS and NOS functions are examined for various dimensions. • Relative errors of analytical formulas are much better than the conventional ones.
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...
Discrete repulsive oscillator wavefunctions
International Nuclear Information System (INIS)
Munoz, Carlos A; Rueda-Paz, Juvenal; Wolf, Kurt Bernardo
2009-01-01
For the study of infinite discrete systems on phase space, the three-dimensional Lorentz algebra and group, so(2,1) and SO(2,1), provide a discrete model of the repulsive oscillator. Its eigenfunctions are found in the principal irreducible representation series, where the compact generator-that we identify with the position operator-has the infinite discrete spectrum of the integers Z, while the spectrum of energies is a double continuum. The right- and left-moving wavefunctions are given by hypergeometric functions that form a Dirac basis for l 2 (Z). Under contraction, the discrete system limits to the well-known quantum repulsive oscillator. Numerical computations of finite approximations raise further questions on the use of Dirac bases for infinite discrete systems.
Energy Technology Data Exchange (ETDEWEB)
Morris, J; Johnson, S
2007-12-03
The Distinct Element Method (also frequently referred to as the Discrete Element Method) (DEM) is a Lagrangian numerical technique where the computational domain consists of discrete solid elements which interact via compliant contacts. This can be contrasted with Finite Element Methods where the computational domain is assumed to represent a continuum (although many modern implementations of the FEM can accommodate some Distinct Element capabilities). Often the terms Discrete Element Method and Distinct Element Method are used interchangeably in the literature, although Cundall and Hart (1992) suggested that Discrete Element Methods should be a more inclusive term covering Distinct Element Methods, Displacement Discontinuity Analysis and Modal Methods. In this work, DEM specifically refers to the Distinct Element Method, where the discrete elements interact via compliant contacts, in contrast with Displacement Discontinuity Analysis where the contacts are rigid and all compliance is taken up by the adjacent intact material.
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 spatially...... are incorrect, and a simple technique that can properly simulate turbulent diffusion in the marine environment is discussed...... non-uniform. The problems associated with this nonuniformity are far from negligible and have been recognised for quite some time. However, incorrect implementations continue to appear in the Literature. In this note computer simulations are presented to illustrate how and why these implementations...
Modeling the magnitude and distribution of estuarine sediment contamination by pollutants of historic (e.g. PCB) and emerging concern (e.g., personal care products, PCP) is often limited by incomplete site knowledge and inadequate sediment contamination sampling. We tested a mode...
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...
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 maintaining constraints in a DC-DC converter is investigated. A probability distribution whose aim is to ensure maximal harmonic spreading and yet mainaint constraints is presented. The PDFs are determined from a direct application of the method of Maximum...
Bhamidi, S.; Van der Hofstad, R.; Hooghiemstra, G.
2010-01-01
We study first passage percolation (FPP) on the configuration model (CM) having power-law degrees with exponent ? ? [1, 2) and exponential edge weights. We derive the distributional limit of the minimal weight of a path between typical vertices in the network and the number of edges on the
Electroless plating apparatus for discrete microsized particles
International Nuclear Information System (INIS)
Mayer, A.
1978-01-01
Method and apparatus are disclosed for producing very uniform coatings of a desired material on discrete microsized particles by electroless techniques. Agglomeration or bridging of the particles during the deposition process is prevented by imparting a sufficiently random motion to the particles that they are not in contact with each other for a time sufficient for such to occur
Electrolytic plating apparatus for discrete microsized particles
International Nuclear Information System (INIS)
Mayer, A.
1976-01-01
Method and apparatus are disclosed for electrolytically producing very uniform coatings of a desired material on discrete microsized particles. Agglomeration or bridging of the particles during the deposition process is prevented by imparting a sufficiently random motion to the particles that they are not in contact with a powered cathode for a time sufficient for such to occur. 4 claims, 2 figures
Spherically symmetric random walks. II. Dimensionally dependent critical behavior
International Nuclear Information System (INIS)
Bender, C.M.; Boettcher, S.; Meisinger, P.N.
1996-01-01
A recently developed model of random walks on a D-dimensional hyperspherical lattice, where D is not restricted to integer values, is extended to include the possibility of creating and annihilating random walkers. Steady-state distributions of random walkers are obtained for all dimensions D approx-gt 0 by solving a discrete eigenvalue problem. These distributions exhibit dimensionally dependent critical behavior as a function of the birth rate. This remarkably simple model exhibits a second-order phase transition with a universal, nontrivial critical exponent for all dimensions D approx-gt 0. copyright 1996 The American Physical Society
International Nuclear Information System (INIS)
Tahir-Kheli, R.A.
1975-01-01
A few simple problems relating to random magnetic systems are presented. Translational symmetry, only on the macroscopic scale, is assumed for these systems. A random set of parameters, on the microscopic scale, for the various regions of these systems is also assumed. A probability distribution for randomness is obeyed. Knowledge of the form of these probability distributions, is assumed in all cases [pt
Self-organisation of random oscillators with Lévy stable distributions
Moradi, Sara; Anderson, Johan
2017-08-01
A novel possibility of self-organized behaviour of stochastically driven oscillators is presented. It is shown that synchronization by Lévy stable processes is significantly more efficient than that by oscillators with Gaussian statistics. The impact of outlier events from the tail of the distribution function was examined by artificially introducing a few additional oscillators with very strong coupling strengths and it is found that remarkably even one such rare and extreme event may govern the long term behaviour of the coupled system. In addition to the multiplicative noise component, we have investigated the impact of an external additive Lévy distributed noise component on the synchronisation properties of the oscillators.
A Predictive Analysis of the Department of Defense Distribution System Utilizing Random Forests
2016-06-01
resources capable of meeting both customer and individual resource constraints and goals while also maximizing the global benefit to the supply...and probability rules to determine the optimal red wine distribution network for an Italian-based wine producer. The decision support model for...combinations of factors that will result in delivery of the highest quality wines . The model’s first stage inputs basic logistics information to look
Zhang, Li-Zhi; Yuan, Wu-Zhi
2018-04-01
The motion of coalescence-induced condensate droplets on superhydrophobic surface (SHS) has attracted increasing attention in energy-related applications. Previous researches were focused on regularly rough surfaces. Here a new approach, a mesoscale lattice Boltzmann method (LBM), is proposed and used to model the dynamic behavior of coalescence-induced droplet jumping on SHS with randomly distributed rough structures. A Fast Fourier Transformation (FFT) method is used to generate non-Gaussian randomly distributed rough surfaces with the skewness (Sk), kurtosis (K) and root mean square (Rq) obtained from real surfaces. Three typical spreading states of coalesced droplets are observed through LBM modeling on various rough surfaces, which are found to significantly influence the jumping ability of coalesced droplet. The coalesced droplets spreading in Cassie state or in composite state will jump off the rough surfaces, while the ones spreading in Wenzel state would eventually remain on the rough surfaces. It is demonstrated that the rough surfaces with smaller Sks, larger Rqs and a K at 3.0 are beneficial to coalescence-induced droplet jumping. The new approach gives more detailed insights into the design of SHS.
A dynamic discretization method for reliability inference in Dynamic Bayesian Networks
International Nuclear Information System (INIS)
Zhu, Jiandao; Collette, Matthew
2015-01-01
The material and modeling parameters that drive structural reliability analysis for marine structures are subject to a significant uncertainty. This is especially true when time-dependent degradation mechanisms such as structural fatigue cracking are considered. Through inspection and monitoring, information such as crack location and size can be obtained to improve these parameters and the corresponding reliability estimates. Dynamic Bayesian Networks (DBNs) are a powerful and flexible tool to model dynamic system behavior and update reliability and uncertainty analysis with life cycle data for problems such as fatigue cracking. However, a central challenge in using DBNs is the need to discretize certain types of continuous random variables to perform network inference while still accurately tracking low-probability failure events. Most existing discretization methods focus on getting the overall shape of the distribution correct, with less emphasis on the tail region. Therefore, a novel scheme is presented specifically to estimate the likelihood of low-probability failure events. The scheme is an iterative algorithm which dynamically partitions the discretization intervals at each iteration. Through applications to two stochastic crack-growth example problems, the algorithm is shown to be robust and accurate. Comparisons are presented between the proposed approach and existing methods for the discretization problem. - Highlights: • A dynamic discretization method is developed for low-probability events in DBNs. • The method is compared to existing approaches on two crack growth problems. • The method is shown to improve on existing methods for low-probability events
Izadi, F A; Bagirov, G
2009-01-01
With its origins stretching back several centuries, discrete calculus is now an increasingly central methodology for many problems related to discrete systems and algorithms. The topics covered here usually arise in many branches of science and technology, especially in discrete mathematics, numerical analysis, statistics and probability theory as well as in electrical engineering, but our viewpoint here is that these topics belong to a much more general realm of mathematics; namely calculus and differential equations because of the remarkable analogy of the subject to this branch of mathemati
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.
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...... can also be related by sampling and periodization. This thesis extends on this theory by showing new results for window construction. It also provides a discussion of the problems associated to discrete Gabor bases. The sampling and periodization connection is handy because it allows 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...
Adaptive Discrete Hypergraph Matching.
Yan, Junchi; Li, Changsheng; Li, Yin; Cao, Guitao
2018-02-01
This paper addresses the problem of hypergraph matching using higher-order affinity information. We propose a solver that iteratively updates the solution in the discrete domain by linear assignment approximation. The proposed method is guaranteed to converge to a stationary discrete solution and avoids the annealing procedure and ad-hoc post binarization step that are required in several previous methods. Specifically, we start with a simple iterative discrete gradient assignment solver. This solver can be trapped in an -circle sequence under moderate conditions, where is the order of the graph matching problem. We then devise an adaptive relaxation mechanism to jump out this degenerating case and show that the resulting new path will converge to a fixed solution in the discrete domain. The proposed method is tested on both synthetic and real-world benchmarks. The experimental results corroborate the efficacy of our method.
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...
International Nuclear Information System (INIS)
Williams, Ruth M
2006-01-01
A review is given of a number of approaches to discrete quantum gravity, with a restriction to those likely to be relevant in four dimensions. This paper is dedicated to Rafael Sorkin on the occasion of his sixtieth birthday
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
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.
Discrete ellipsoidal statistical BGK model and Burnett equations
Zhang, Yu-Dong; Xu, Ai-Guo; Zhang, Guang-Cai; Chen, Zhi-Hua; Wang, Pei
2018-06-01
A new discrete Boltzmann model, the discrete ellipsoidal statistical Bhatnagar-Gross-Krook (ESBGK) model, is proposed to simulate nonequilibrium compressible flows. Compared with the original discrete BGK model, the discrete ES-BGK has a flexible Prandtl number. For the discrete ES-BGK model in the Burnett level, two kinds of discrete velocity model are introduced and the relations between nonequilibrium quantities and the viscous stress and heat flux in the Burnett level are established. The model is verified via four benchmark tests. In addition, a new idea is introduced to recover the actual distribution function through the macroscopic quantities and their space derivatives. The recovery scheme works not only for discrete Boltzmann simulation but also for hydrodynamic ones, for example, those based on the Navier-Stokes or the Burnett equations.
Mapping of uncertainty relations between continuous and discrete time.
Chiuchiù, Davide; Pigolotti, Simone
2018-03-01
Lower bounds on fluctuations of thermodynamic currents depend on the nature of time, discrete or continuous. To understand the physical reason, we compare current fluctuations in discrete-time Markov chains and continuous-time master equations. We prove that current fluctuations in the master equations are always more likely, due to random timings of transitions. This comparison leads to a mapping of the moments of a current between discrete and continuous time. We exploit this mapping to obtain uncertainty bounds. Our results reduce the quests for uncertainty bounds in discrete and continuous time to a single problem.
Discrete stochastic analogs of Erlang epidemic models.
Getz, Wayne M; Dougherty, Eric R
2018-12-01
Erlang differential equation models of epidemic processes provide more realistic disease-class transition dynamics from susceptible (S) to exposed (E) to infectious (I) and removed (R) categories than the ubiquitous SEIR model. The latter is itself is at one end of the spectrum of Erlang SE[Formula: see text]I[Formula: see text]R models with [Formula: see text] concatenated E compartments and [Formula: see text] concatenated I compartments. Discrete-time models, however, are computationally much simpler to simulate and fit to epidemic outbreak data than continuous-time differential equations, and are also much more readily extended to include demographic and other types of stochasticity. Here we formulate discrete-time deterministic analogs of the Erlang models, and their stochastic extension, based on a time-to-go distributional principle. Depending on which distributions are used (e.g. discretized Erlang, Gamma, Beta, or Uniform distributions), we demonstrate that our formulation represents both a discretization of Erlang epidemic models and generalizations thereof. We consider the challenges of fitting SE[Formula: see text]I[Formula: see text]R models and our discrete-time analog to data (the recent outbreak of Ebola in Liberia). We demonstrate that the latter performs much better than the former; although confining fits to strict SEIR formulations reduces the numerical challenges, but sacrifices best-fit likelihood scores by at least 7%.
Hopf Bifurcation Analysis for a Stochastic Discrete-Time Hyperchaotic System
Directory of Open Access Journals (Sweden)
Jie Ran
2015-01-01
Full Text Available The dynamics of a discrete-time hyperchaotic system and the amplitude control of Hopf bifurcation for a stochastic discrete-time hyperchaotic system are investigated in this paper. Numerical simulations are presented to exhibit the complex dynamical behaviors in the discrete-time hyperchaotic system. Furthermore, the stochastic discrete-time hyperchaotic system with random parameters is transformed into its equivalent deterministic system with the orthogonal polynomial theory of discrete random function. In addition, the dynamical features of the discrete-time hyperchaotic system with random disturbances are obtained through its equivalent deterministic system. By using the Hopf bifurcation conditions of the deterministic discrete-time system, the specific conditions for the existence of Hopf bifurcation in the equivalent deterministic system are derived. And the amplitude control with random intensity is discussed in detail. Finally, the feasibility of the control method is demonstrated by numerical simulations.
International Nuclear Information System (INIS)
Bhattacharyya, Pratip; Chakrabarti, Bikas K
2008-01-01
We study different ways of determining the mean distance (r 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 (r n ). Next, we describe two alternative means of deriving the exact expression of (r n ): we review the method using absolute probability and develop an alternative method using conditional probability. Finally, we obtain an approximation to (r n ) from the mean volume between the reference point and its nth neighbour and compare it with the heuristic and exact results
Phase diagrams of a spin-1/2 transverse Ising model with three-peak random field distribution
International Nuclear Information System (INIS)
Bassir, A.; Bassir, C.E.; Benyoussef, A.; Ez-Zahraouy, H.
1996-07-01
The effect of the transverse magnetic field on the phase diagrams structures of the Ising model in a random longitudinal magnetic field with a trimodal symmetric distribution is investigated within a finite cluster approximation. We find that a small magnetizations ordered phase (small ordered phase) disappears completely for a sufficiently large value of the transverse field or/and large value of the concentration of the disorder of the magnetic field. Multicritical behaviour and reentrant phenomena are discussed. The regions where the tricritical, reentrant phenomena and the small ordered phase persist are delimited as a function of the transverse field and the concentration p. Longitudinal magnetizations are also presented. (author). 33 refs, 6 figs
International Nuclear Information System (INIS)
Ruthe, Sebastian
2015-01-01
The ongoing shift towards decentralized power systems and the related rapidly growing number of decentralized energy resources (DER) like wind- and PV-units, CHP-units, storage devices and shiftable loads requires new information systems and control algorithms in order to pland and optimize the commitment of DER in line with the conventional generation system. In this context the paradigm of market based control derived from the Lagrangian relaxation of the unit commitment problem represents a promising solution approach to build highly scalable distributed systems able to perform this task within the required time limits. Market based control approaches typically achieve high quality solutions and protect the private data of the controlled units. However in case of DER with discontinuous utility functions market based control approaches suffer under the problem of ''joint commitment'', which may lead to a divergence of the iterative solution algorithm resulting in highly cost inefficient solutions. This thesis introduces a new concept of randomizing the Lagrangian multipliers to spread the individual commitment thresholds of DER thereby mitigating th negative effects of ''joint commitments''. Based on the randomized solution approach different boundaries for the solution quality regarding the overall energy production costs and the equilibrium constraints are established. Furthermore it is shown how the developed approach can be utilized to build new scalable information systems for future energy markets and their interfaces to the existing energy markets.
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.
A discrete stress-strength interference model based on universal generating function
International Nuclear Information System (INIS)
An Zongwen; Huang Hongzhong; Liu Yu
2008-01-01
Continuous stress-strength interference (SSI) model regards stress and strength as continuous random variables with known probability density function. This, to some extent, results in a limitation of its application. In this paper, stress and strength are treated as discrete random variables, and a discrete SSI model is presented by using the universal generating function (UGF) method. Finally, case studies demonstrate the validity of the discrete model in a variety of circumstances, in which stress and strength can be represented by continuous random variables, discrete random variables, or two groups of experimental data
International Nuclear Information System (INIS)
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. - Highlights: • The Muller matrix of randomly distributed, densely packed spheres are investigated. • The effects of multiple scattering and dependent scattering are analyzed. • The accuracy of radiative transfer theory for densely packed spheres is discussed. • Dependent scattering correction takes effect at medium size parameter or smaller. • Performance of dependent scattering correction
Homogenization of discrete media
Energy Technology Data Exchange (ETDEWEB)
Pradel, F.; Sab, K. [CERAM-ENPC, Marne-la-Vallee (France)
1998-11-01
Material such as granular media, beam assembly are easily seen as discrete media. They look like geometrical points linked together thanks to energetic expressions. Our purpose is to extend discrete kinematics to the one of an equivalent continuous material. First we explain how we build the localisation tool for periodic materials according to estimated continuum medium type (classical Cauchy, and Cosserat media). Once the bridge built between discrete and continuum media, we exhibit its application over two bidimensional beam assembly structures : the honey comb and a structural reinforced variation. The new behavior is then applied for the simple plan shear problem in a Cosserat continuum and compared with the real discrete solution. By the mean of this example, we establish the agreement of our new model with real structures. The exposed method has a longer range than mechanics and can be applied to every discrete problems like electromagnetism in which relationship between geometrical points can be summed up by an energetic function. (orig.) 7 refs.
Stable and efficient retrospective 4D-MRI using non-uniformly distributed quasi-random numbers
Breuer, Kathrin; Meyer, Cord B.; Breuer, Felix A.; Richter, Anne; Exner, Florian; Weng, Andreas M.; Ströhle, Serge; Polat, Bülent; Jakob, Peter M.; Sauer, Otto A.; Flentje, Michael; Weick, Stefan
2018-04-01
The purpose of this work is the development of a robust and reliable three-dimensional (3D) Cartesian imaging technique for fast and flexible retrospective 4D abdominal MRI during free breathing. To this end, a non-uniform quasi random (NU-QR) reordering of the phase encoding (k y –k z ) lines was incorporated into 3D Cartesian acquisition. The proposed sampling scheme allocates more phase encoding points near the k-space origin while reducing the sampling density in the outer part of the k-space. Respiratory self-gating in combination with SPIRiT-reconstruction is used for the reconstruction of abdominal data sets in different respiratory phases (4D-MRI). Six volunteers and three patients were examined at 1.5 T during free breathing. Additionally, data sets with conventional two-dimensional (2D) linear and 2D quasi random phase encoding order were acquired for the volunteers for comparison. A quantitative evaluation of image quality versus scan times (from 70 s to 626 s) for the given sampling schemes was obtained by calculating the normalized mutual information (NMI) for all volunteers. Motion estimation was accomplished by calculating the maximum derivative of a signal intensity profile of a transition (e.g. tumor or diaphragm). The 2D non-uniform quasi-random distribution of phase encoding lines in Cartesian 3D MRI yields more efficient undersampling patterns for parallel imaging compared to conventional uniform quasi-random and linear sampling. Median NMI values of NU-QR sampling are the highest for all scan times. Therefore, within the same scan time 4D imaging could be performed with improved image quality. The proposed method allows for the reconstruction of motion artifact reduced 4D data sets with isotropic spatial resolution of 2.1 × 2.1 × 2.1 mm3 in a short scan time, e.g. 10 respiratory phases in only 3 min. Cranio-caudal tumor displacements between 23 and 46 mm could be observed. NU-QR sampling enables for stable 4D
Zhang, Guo-Qiang; Tao, Shiqiang; Xing, Guangming; Mozes, Jeno; Zonjy, Bilal; Lhatoo, Samden D; Cui, Licong
2015-11-10
A unique study identifier serves as a key for linking research data about a study subject without revealing protected health information in the identifier. While sufficient for single-site and limited-scale studies, the use of common unique study identifiers has several drawbacks for large multicenter studies, where thousands of research participants may be recruited from multiple sites. An important property of study identifiers is error tolerance (or validatable), in that inadvertent editing mistakes during their transmission and use will most likely result in invalid study identifiers. This paper introduces a novel method called "Randomized N-gram Hashing (NHash)," for generating unique study identifiers in a distributed and validatable fashion, in multicenter research. NHash has a unique set of properties: (1) it is a pseudonym serving the purpose of linking research data about a study participant for research purposes; (2) it can be generated automatically in a completely distributed fashion with virtually no risk for identifier collision; (3) it incorporates a set of cryptographic hash functions based on N-grams, with a combination of additional encryption techniques such as a shift cipher; (d) it is validatable (error tolerant) in the sense that inadvertent edit errors will mostly result in invalid identifiers. NHash consists of 2 phases. First, an intermediate string using randomized N-gram hashing is generated. This string consists of a collection of N-gram hashes f1, f2, ..., fk. The input for each function fi has 3 components: a random number r, an integer n, and input data m. The result, fi(r, n, m), is an n-gram of m with a starting position s, which is computed as (r mod |m|), where |m| represents the length of m. The output for Step 1 is the concatenation of the sequence f1(r1, n1, m1), f2(r2, n2, m2), ..., fk(rk, nk, mk). In the second phase, the intermediate string generated in Phase 1 is encrypted using techniques such as shift cipher. The result
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.
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 ...
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.
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
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...
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...
Reproductive Health Services Discrete-Event Simulation
Lee, Sungjoo; Giles, Denise F.; Goldsman, David; Cook, Douglas A.; Mishra, Ninad; McCarthy, Brian
2006-01-01
Low resource healthcare environments are often characteristic of patient flow patterns with varying patient risks, extensive patient waiting times, uneven workload distributions, and inefficient service delivery. Models from industrial and systems engineering allow for a greater examination of processes by applying discrete-event computer simulation techniques to evaluate and optimize hospital performance.
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
Prateek Sharma
2015-01-01
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 ev...
Multiscale Path Metrics for the Analysis of Discrete Geometric Structures
2017-11-30
Report: Multiscale Path Metrics for the Analysis of Discrete Geometric Structures The views, opinions and/or findings contained in this report are those...Analysis of Discrete Geometric Structures Report Term: 0-Other Email: tomasi@cs.duke.edu Distribution Statement: 1-Approved for public release
Discrete time analysis of a repairable machine
Alfa, Attahiru Sule; Castro, I. T.
2002-01-01
We consider, in discrete time, a single machine system that operates for a period of time represented by a general distribution. This machine is subject to failures during operations and the occurrence of these failures depends on how many times the machine has previously failed. Some failures are repairable and the repair times may or may not depend on the number of times the machine was previously repaired. Repair times also have a general distribution. The operating times...
A variational synthesis nodal discrete ordinates method
International Nuclear Information System (INIS)
Favorite, J.A.; Stacey, W.M.
1999-01-01
A self-consistent nodal approximation method for computing discrete ordinates neutron flux distributions has been developed from a variational functional for neutron transport theory. The advantage of the new nodal method formulation is that it is self-consistent in its definition of the homogenized nodal parameters, the construction of the global nodal equations, and the reconstruction of the detailed flux distribution. The efficacy of the method is demonstrated by two-dimensional test problems
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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
Nuel, Gregory; Regad, Leslie; Martin, Juliette; Camproux, Anne-Claude
2010-01-26
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. 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. Our algorithms prove to be effective and able to handle real data sets with multiple sequences, as well as biological patterns of
Indian Academy of Sciences (India)
We also describe discrete-time systems in terms of difference ... A more modern alternative, especially for larger systems, is to convert ... In other words, ..... picture?) State-variable equations are also called state-space equations because the ...
Discrete Lorentzian quantum gravity
Loll, R.
2000-01-01
Just as for non-abelian gauge theories at strong coupling, discrete lattice methods are a natural tool in the study of non-perturbative quantum gravity. They have to reflect the fact that the geometric degrees of freedom are dynamical, and that therefore also the lattice theory must be formulated
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…
Energy Technology Data Exchange (ETDEWEB)
Egbe, Daniel A.M.; Adam, Getachew; Pivrikas, Almantas; Ulbricht, Christoph; Ramil, Alberto M.; Sariciftci, Niyazi Serdar [Johannes Kepler Univ., Linz (AT). Linz Inst. for Organic Solar Cells (LIOS); Hoppe, Harald [Technische Univ. Ilmenau (Germany). Inst. of Physics and Inst. of Micro- and Nanotechnologies; Rathgeber, Silke [Mainz Univ. (Germany). Inst. of Physics
2010-07-01
The random distribution of segments of linear octyloxy side chains and of branched 2-ethylhexyloxy side chains, on the backbone of anthracene containing poly(p-phenylene-ethynylene)-alt-poly(p-phenylene-vinylene) (PPE-PPV) has resulted in a side chain based statistical copolymer, denoted AnE-PVstat, showing optimized features as compared to the well defined homologues AnE-PVaa, -ab, -ba and -bb, whose constitutional units are incorporated into its backbone. WAXS studies on AnE-P's demonstrate the highest degree of order at the self-assembly state of AnE-PVstat, which is confirmed by its highly structured thin film absorption band. Electric field independent charge carrier mobility ({mu}{sub hole}) for AnE-PVstat was demonstrated by CELIV and OFET measurements, both methods resulting in similar {mu}{sub hole} values of up to 5.43 x 10{sup -4} cm{sup 2}/Vs. Upon comparison, our results show that charge carrier mobility as measured by CELIV technique is predominantly an intrachain process and less an interchain one, which is in line with past photoconductivity results from PPE-PPV based materials. The present side chain distribution favors efficient solar cell active layer phase separation. As a result, a smaller amount of PC{sub 60}BM is needed to achieve relatively high energy conversion efficiencies above 3 %. The efficiency of {eta}{sub AM1.5} {approx} 3.8 % obtained for AnE-PVstat:PC{sub 60}BM blend is presently the state-of-art value for PPV-based materials. (orig.)
Discrete Exterior Calculus Discretization of Incompressible Navier-Stokes Equations
Mohamed, Mamdouh S.; Hirani, Anil N.; Samtaney, Ravi
2017-01-01
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
Discrete mKdV and discrete sine-Gordon flows on discrete space curves
International Nuclear Information System (INIS)
Inoguchi, Jun-ichi; Kajiwara, Kenji; Matsuura, Nozomu; Ohta, Yasuhiro
2014-01-01
In this paper, we consider the discrete deformation of the discrete space curves with constant torsion described by the discrete mKdV or the discrete sine-Gordon equations, and show that it is formulated as the torsion-preserving equidistant deformation on the osculating plane which satisfies the isoperimetric condition. The curve is reconstructed from the deformation data by using the Sym–Tafel formula. The isoperimetric equidistant deformation of the space curves does not preserve the torsion in general. However, it is possible to construct the torsion-preserving deformation by tuning the deformation parameters. Further, it is also possible to make an arbitrary choice of the deformation described by the discrete mKdV equation or by the discrete sine-Gordon equation at each step. We finally show that the discrete deformation of discrete space curves yields the discrete K-surfaces. (paper)
Discrete modelling of the electrochemical performance of SOFC electrodes
International Nuclear Information System (INIS)
Schneider, L.C.R.; Martin, C.L.; Bultel, Y.; Bouvard, D.; Siebert, E.
2006-01-01
The composite anode and cathode of solid oxide fuel cells (SOFC) are modelled as sintered mixtures of electrolyte and electrocatalyst particles. A particle packing is first created numerically by the discrete element method (DEM) from a loose packing of 40 000 spherical, monosized, homogeneously mixed, and randomly positioned particles. Once the microstructure is sintered numerically, the effective electrode conductivity is determined by discretization of the particle packing into a resistance network. Each particle contact is characteristic of a bond resistance that depends on contact geometry and particle properties. The network, which typically consists of 120 000 bond resistances in total, is solved using Kirchhoff's current law. Distributions of local current densities and particle potentials are then performed. We investigate how electrode performance depends on parameters such as electrode composition, thickness, density and intrinsic material conductivities that are temperature dependent. The simulations show that the best electrode performance is obtained for compositions close to the percolation threshold of the electronic conductor. Depending on particle conductivities, the electrode performance is a function of its thickness. Additionally, DEM simulations generate useful microstructural information such as: coordination numbers, triple phase boundary length and percolation thresholds
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.
Sputtering calculations with the discrete ordinated method
International Nuclear Information System (INIS)
Hoffman, T.J.; Dodds, H.L. Jr.; Robinson, M.T.; Holmes, D.K.
1977-01-01
The purpose of this work is to investigate the applicability of the discrete ordinates (S/sub N/) method to light ion sputtering problems. In particular, the neutral particle discrete ordinates computer code, ANISN, was used to calculate sputtering yields. No modifications to this code were necessary to treat charged particle transport. However, a cross section processing code was written for the generation of multigroup cross sections; these cross sections include a modification to the total macroscopic cross section to account for electronic interactions and small-scattering-angle elastic interactions. The discrete ordinates approach enables calculation of the sputtering yield as functions of incident energy and angle and of many related quantities such as ion reflection coefficients, angular and energy distributions of sputtering particles, the behavior of beams penetrating thin foils, etc. The results of several sputtering problems as calculated with ANISN are presented
Random matrices and random difference equations
International Nuclear Information System (INIS)
Uppuluri, V.R.R.
1975-01-01
Mathematical models leading to products of random matrices and random difference equations are discussed. A one-compartment model with random behavior is introduced, and it is shown how the average concentration in the discrete time model converges to the exponential function. This is of relevance to understanding how radioactivity gets trapped in bone structure in blood--bone systems. The ideas are then generalized to two-compartment models and mammillary systems, where products of random matrices appear in a natural way. The appearance of products of random matrices in applications in demography and control theory is considered. Then random sequences motivated from the following problems are studied: constant pulsing and random decay models, random pulsing and constant decay models, and random pulsing and random decay models
Wang, Shao-Jiang; Guo, Qi; Cai, Rong-Gen
2017-12-01
We investigate the impact of different redshift distributions of random samples on the baryon acoustic oscillations (BAO) measurements of D_V(z)r_d^fid/r_d from the two-point correlation functions of galaxies in the Data Release 12 of the Baryon Oscillation Spectroscopic Survey (BOSS). Big surveys, such as BOSS, usually assign redshifts to the random samples by randomly drawing values from the measured redshift distributions of the data, which would necessarily introduce fiducial signals of fluctuations into the random samples, weakening the signals of BAO, if the cosmic variance cannot be ignored. We propose a smooth function of redshift distribution that fits the data well to populate the random galaxy samples. The resulting cosmological parameters match the input parameters of the mock catalogue very well. The significance of BAO signals has been improved by 0.33σ for a low-redshift sample and by 0.03σ for a constant-stellar-mass sample, though the absolute values do not change significantly. Given the precision of the measurements of current cosmological parameters, it would be appreciated for the future improvements on the measurements of galaxy clustering.
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.
Discrete Input Signaling for MISO Visible Light Communication Channels
Arfaoui, Mohamed Amine; Rezki, Zouheir; Ghrayeb, Ali; Alouini, Mohamed-Slim
2017-01-01
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
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.
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),
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...
John R. Jones
1985-01-01
Quaking aspen is the most widely distributed native North American tree species (Little 1971, Sargent 1890). It grows in a great diversity of regions, environments, and communities (Harshberger 1911). Only one deciduous tree species in the world, the closely related Eurasian aspen (Populus tremula), has a wider range (Weigle and Frothingham 1911)....
Yang, Yu-Guang; Xu, Peng; Yang, Rui; Zhou, Yi-Hua; Shi, Wei-Min
2016-01-01
Quantum information and quantum computation have achieved a huge success during the last years. In this paper, we investigate the capability of quantum Hash function, which can be constructed by subtly modifying quantum walks, a famous quantum computation model. It is found that quantum Hash function can act as a hash function for the privacy amplification process of quantum key distribution systems with higher security. As a byproduct, quantum Hash function can also be used for pseudo-random number generation due to its inherent chaotic dynamics. Further we discuss the application of quantum Hash function to image encryption and propose a novel image encryption algorithm. Numerical simulations and performance comparisons show that quantum Hash function is eligible for privacy amplification in quantum key distribution, pseudo-random number generation and image encryption in terms of various hash tests and randomness tests. It extends the scope of application of quantum computation and quantum information.
Yang, Yu-Guang; Xu, Peng; Yang, Rui; Zhou, Yi-Hua; Shi, Wei-Min
2016-01-01
Quantum information and quantum computation have achieved a huge success during the last years. In this paper, we investigate the capability of quantum Hash function, which can be constructed by subtly modifying quantum walks, a famous quantum computation model. It is found that quantum Hash function can act as a hash function for the privacy amplification process of quantum key distribution systems with higher security. As a byproduct, quantum Hash function can also be used for pseudo-random number generation due to its inherent chaotic dynamics. Further we discuss the application of quantum Hash function to image encryption and propose a novel image encryption algorithm. Numerical simulations and performance comparisons show that quantum Hash function is eligible for privacy amplification in quantum key distribution, pseudo-random number generation and image encryption in terms of various hash tests and randomness tests. It extends the scope of application of quantum computation and quantum information. PMID:26823196
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*...
Discrete and computational geometry
Devadoss, Satyan L
2011-01-01
Discrete geometry is a relatively new development in pure mathematics, while computational geometry is an emerging area in applications-driven computer science. Their intermingling has yielded exciting advances in recent years, yet what has been lacking until now is an undergraduate textbook that bridges the gap between the two. Discrete and Computational Geometry offers a comprehensive yet accessible introduction to this cutting-edge frontier of mathematics and computer science. This book covers traditional topics such as convex hulls, triangulations, and Voronoi diagrams, as well as more recent subjects like pseudotriangulations, curve reconstruction, and locked chains. It also touches on more advanced material, including Dehn invariants, associahedra, quasigeodesics, Morse theory, and the recent resolution of the Poincaré conjecture. Connections to real-world applications are made throughout, and algorithms are presented independently of any programming language. This richly illustrated textbook also fe...
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...
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.
Effects of Macroion Geometry and Charge Discretization in Charge Reversal
Mukherjee, Arup K.
2008-01-01
The effects of discrete macroion surface charge distribution and valences of these surface charges and counterions on charge reversal have been studied for macroions of three different geometries and compared with those of continuous surface charge distributions. The geometry of the macroion has been observed to play an important role in overcharging in these cases. The interplay of valences of discrete microions and counterions have noticeable effects on overcharging efficiency. For some val...
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
Discrete variational Hamiltonian mechanics
International Nuclear Information System (INIS)
Lall, S; West, M
2006-01-01
The main contribution of this paper is to present a canonical choice of a Hamiltonian theory corresponding to the theory of discrete Lagrangian mechanics. We make use of Lagrange duality and follow a path parallel to that used for construction of the Pontryagin principle in optimal control theory. We use duality results regarding sensitivity and separability to show the relationship between generating functions and symplectic integrators. We also discuss connections to optimal control theory and numerical algorithms
International Nuclear Information System (INIS)
Jalnapurkar, Sameer M; Leok, Melvin; Marsden, Jerrold E; West, Matthew
2006-01-01
This paper develops the theory of Abelian Routh reduction for discrete mechanical systems and applies it to the variational integration of mechanical systems with Abelian symmetry. The reduction of variational Runge-Kutta discretizations is considered, as well as the extent to which symmetry reduction and discretization commute. These reduced methods allow the direct simulation of dynamical features such as relative equilibria and relative periodic orbits that can be obscured or difficult to identify in the unreduced dynamics. The methods are demonstrated for the dynamics of an Earth orbiting satellite with a non-spherical J 2 correction, as well as the double spherical pendulum. The J 2 problem is interesting because in the unreduced picture, geometric phases inherent in the model and those due to numerical discretization can be hard to distinguish, but this issue does not appear in the reduced algorithm, where one can directly observe interesting dynamical structures in the reduced phase space (the cotangent bundle of shape space), in which the geometric phases have been removed. The main feature of the double spherical pendulum example is that it has a non-trivial magnetic term in its reduced symplectic form. Our method is still efficient as it can directly handle the essential non-canonical nature of the symplectic structure. In contrast, a traditional symplectic method for canonical systems could require repeated coordinate changes if one is evoking Darboux' theorem to transform the symplectic structure into canonical form, thereby incurring additional computational cost. Our method allows one to design reduced symplectic integrators in a natural way, despite the non-canonical nature of the symplectic structure
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
A paradigm for discrete physics
International Nuclear Information System (INIS)
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
Directory of Open Access Journals (Sweden)
Asma Shaheen
2018-03-01
Full Text Available In third world countries, industries mainly cause environmental contamination due to lack of environmental policies or oversight during their implementation. The Sheikhupura industrial zone, which includes industries such as tanneries, leather, chemical, textiles, and colour and dyes, contributes massive amounts of untreated effluents that are released directly into drains and used for the irrigation of crops and vegetables. This practice causes not only soil contamination with an excessive amount of heavy metals, but is also considered a source of toxicity in the food chain, i.e., bioaccumulation in plants and ultimately in human body organs. The objective of this research study was to assess the spatial distribution of the heavy metals chromium (Cr, cadmium (Cd, and lead (Pb, at three depths of soil using geostatistics and the selection of significant contributing variables to soil contamination using the Random Forest (RF function of the Boruta Algorithm. A total of 60 sampling locations were selected in the study area to collect soil samples (180 samples at three depths (0–15 cm, 15–30 cm, and 60–90 cm. The soil samples were analysed for their physico-chemical properties, i.e., soil saturation, electrical conductivity (EC, organic matter (OM, pH, phosphorus (P, potassium (K, and Cr, Cd, and Pb using standard laboratory procedures. The data were analysed with comprehensive statistics and geostatistical techniques. The correlation coefficient matrix between the heavy metals and the physico-chemical properties revealed that electrical conductivity (EC had a significant (p ≤ 0.05 negative correlation with Cr, Cd, and Pb. The RF function of the Boruta Algorithm employed soil depth as a classifier and ranked the significant soil contamination parameters (Cr, Cd, Pb, EC, and P in relation to depth. The mobility factor indicated the leachate percentage of heavy metals at different vertical depths of soil. The spatial distribution pattern of
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.
International Nuclear Information System (INIS)
Mazzolini, A.P.; Legge, G.J.F.
1982-01-01
A scanning proton microprobe has been used to determine the distribution of Cu and other elements in Wimmera ryegrass roots grown in solution cultures. Cu was found to be localized on or near the surface of the roots in randomly distributed discrete zones. The distribution of Cu was partially correlated with those of Fe, P and Ca and possibly indicates some form of association; co-precipitation in a precipitate of ferric phosphate or hydroxy-oxide is favoured
Two new discrete integrable systems
International Nuclear Information System (INIS)
Chen Xiao-Hong; Zhang Hong-Qing
2013-01-01
In this paper, we focus on the construction of new (1+1)-dimensional discrete integrable systems according to a subalgebra of loop algebra Ã 1 . By designing two new (1+1)-dimensional discrete spectral problems, two new discrete integrable systems are obtained, namely, a 2-field lattice hierarchy and a 3-field lattice hierarchy. When deriving the two new discrete integrable systems, we find the generalized relativistic Toda lattice hierarchy and the generalized modified Toda lattice hierarchy. Moreover, we also obtain the Hamiltonian structures of the two lattice hierarchies by means of the discrete trace identity
Asymptotic results for the semi-Markovian random walk with delay
International Nuclear Information System (INIS)
Khaniyev, T.A.; Aliyev, R.T.
2006-12-01
In this study, the semi-Markovian random walk with a discrete interference of chance (X(t) ) is considered and under some weak assumptions the ergodicity of this process is discussed. Characteristic function of the ergodic distribution of X(t) is expressed by means of the probability characteristics of the boundary functionals (N,S N ). Some exact formulas for first and second moments of ergodic distribution of the process X(t) are obtained when the random variable ζ 1 - s, which is describing a discrete interference of chance, has Gamma distribution on the interval [0, ∞) with parameter (α,λ) . Based on these results, the asymptotic expansions with three terms for the first two moments of the ergodic distribution of the process X(t) are obtained, as λ → 0. (author)
Probabilistic Power Flow Method Considering Continuous and Discrete Variables
Directory of Open Access Journals (Sweden)
Xuexia Zhang
2017-04-01
Full Text Available This paper proposes a probabilistic power flow (PPF method considering continuous and discrete variables (continuous and discrete power flow, CDPF for power systems. The proposed method—based on the cumulant method (CM and multiple deterministic power flow (MDPF calculations—can deal with continuous variables such as wind power generation (WPG and loads, and discrete variables such as fuel cell generation (FCG. In this paper, continuous variables follow a normal distribution (loads or a non-normal distribution (WPG, and discrete variables follow a binomial distribution (FCG. Through testing on IEEE 14-bus and IEEE 118-bus power systems, the proposed method (CDPF has better accuracy compared with the CM, and higher efficiency compared with the Monte Carlo simulation method (MCSM.
Stochastic space interval as a link between quantum randomness and macroscopic randomness?
Haug, Espen Gaarder; Hoff, Harald
2018-03-01
For many stochastic phenomena, we observe statistical distributions that have fat-tails and high-peaks compared to the Gaussian distribution. In this paper, we will explain how observable statistical distributions in the macroscopic world could be related to the randomness in the subatomic world. We show that fat-tailed (leptokurtic) phenomena in our everyday macroscopic world are ultimately rooted in Gaussian - or very close to Gaussian-distributed subatomic particle randomness, but they are not, in a strict sense, Gaussian distributions. By running a truly random experiment over a three and a half-year period, we observed a type of random behavior in trillions of photons. Combining our results with simple logic, we find that fat-tailed and high-peaked statistical distributions are exactly what we would expect to observe if the subatomic world is quantized and not continuously divisible. We extend our analysis to the fact that one typically observes fat-tails and high-peaks relative to the Gaussian distribution in stocks and commodity prices and many aspects of the natural world; these instances are all observable and documentable macro phenomena that strongly suggest that the ultimate building blocks of nature are discrete (e.g. they appear in quanta).
Discrete variable theory of triatomic photodissociation
International Nuclear Information System (INIS)
Heather, R.W.; Light, J.C.
1983-01-01
The coupled equations describing the photodissociation process are expressed in the discrete variable representation (DVR) in which the coupled equations are labeled by quadrature points rather than by internal basis functions. A large reduction in the dimensionality of the coupled equations can be realized since the spatially localized bound state nuclear wave function vanishes at most of the quadrature points, making only certain orientations of the fragments important in the region of strong interaction (small separation). The discrete variable theory of photodissociation is applied to the model dissociation of bent HCN in which the CN fragment is treated as a rigid rotor. The truncated DVR rotational distributions are compared with the exact close coupled rotational distributions, and excellent agreement with greatly reduced dimensionality of the equations is found
Hirsch, M; Peinado, E; Valle, J W F
2010-01-01
We propose a new motivation for the stability of dark matter (DM). We suggest that the same non-abelian discrete flavor symmetry which accounts for the observed pattern of neutrino oscillations, spontaneously breaks to a Z2 subgroup which renders DM stable. The simplest scheme leads to a scalar doublet DM potentially detectable in nuclear recoil experiments, inverse neutrino mass hierarchy, hence a neutrinoless double beta decay rate accessible to upcoming searches, while reactor angle equal to zero gives no CP violation in neutrino oscillations.
Ruin Probabilities in a Dependent Discrete-Time Risk Model With Gamma-Like Tailed Insurance Risks
Directory of Open Access Journals (Sweden)
Xing-Fang Huang
2017-03-01
Full Text Available This paper considered a dependent discrete-time risk model, in which the insurance risks are represented by a sequence of independent and identically distributed real-valued random variables with a common Gamma-like tailed distribution; the ﬁnancial risks are denoted by another sequence of independent and identically distributed positive random variables with a ﬁnite upper endpoint, but a general dependence structure exists between each pair of the insurance risks and the ﬁnancial risks. Following the works of Yang and Yuen in 2016, we derive some asymptotic relations for the ﬁnite-time and inﬁnite-time ruin probabilities. As a complement, we demonstrate our obtained result through a Crude Monte Carlo (CMC simulation with asymptotics.
Nuclear data preparation and discrete ordinates calculation
International Nuclear Information System (INIS)
Carmignani, B.
1980-01-01
These lectures deal with the use of the GAM-GATHER and GAM-THERMOS chains for the calculation of lattice cross sections and within use of the discrete ordinates one dimensional ANISN code for the calculation of criticality and flux distribution of the cell and of the whole reactor. As an example the codes are applied to the calculation of a PWR. Results of different approximations are compared. (author)
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.
DEFF Research Database (Denmark)
Yura, Harold; Hanson, Steen Grüner
2012-01-01
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...
International Nuclear Information System (INIS)
Huijbregtse, J.M.; Klaassen, F.C.; Geest, R.C.F. van der; Dam, B.; Griessen, R.
1999-01-01
Recently, the authors showed that natural linear defects are the origin of the high critical currents in laser ablated YGBa 2 Cu 3 O 7-δ films. Combining wet-chemical etching and Atomic Force Microscopy, they find that these dislocations are created by island coalescence during growth. Consequently, the defect density can be reproducibly varied by manipulating the density of growth islands, which in turn depends on the substrate temperature. Interestingly, the radial defect distribution function approaches zero at small distances, indicating short range order. Therefore, they are now able to study vortex matter in films with a tailored non-random distribution of natural strong pinning sites
An innovative discrete multilevel sampler design
International Nuclear Information System (INIS)
Marvin, B.K.; De Clercq, P.J.; Taylor, B.B.; Mauro, D.M.
1995-01-01
An innovative, small-diameter PVC discrete multilevel sampler (DMLS) was designed for the Electric Power Research Institute (EPRI) to provide low-cost, discrete groundwater samples from shallow aquifers. When combined with appropriately-sized direct push soil sampling technologies, high resolution aquifer characterization can be achieved during initial site assessment or remediation monitoring activities. The sampler is constructed from 1-inch diameter PVC well materials, containing polyethylene tubing threaded through PVC disks. Self-expanding annular and internal bentonite seals were developed which isolate discrete sampling zones. The DMLS design allows customization of sampling and isolation zone lengths to suit site-specific goals. Installation of the DMLS is achieved using a temporary, expendable-tipped casting driven by direct push methods. This technique minimizes mobilization costs, site and soil column disturbances, and allows rapid installation in areas of limited overhead clearance. Successful pilot installations of the DMLS prototype have been made at a former manufactured gas plant (MGP) site and a diesel fuel spill site. Analysis of groundwater samples from these sites, using relative compound distributions and contaminant concentration profiling, confirmed that representative discrete samples were collected. This design provides both economical and versatile groundwater monitoring during all phases of site assessment and remediation
Discrete dispersion models and their Tweedie asymptotics
DEFF Research Database (Denmark)
Jørgensen, Bent; Kokonendji, Célestin C.
2016-01-01
The paper introduce a class of two-parameter discrete dispersion models, obtained by combining convolution with a factorial tilting operation, similar to exponential dispersion models which combine convolution and exponential tilting. The equidispersed Poisson model has a special place in this ap......The paper introduce a class of two-parameter discrete dispersion models, obtained by combining convolution with a factorial tilting operation, similar to exponential dispersion models which combine convolution and exponential tilting. The equidispersed Poisson model has a special place...... 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...... with power variance functions. Using the factorial cumulant generating function as tool, we introduce a dilation operation as a discrete analogue of scaling, generalizing binomial thinning. The Poisson-Tweedie factorial dispersion models are closed under dilation, which in turn leads to a Poisson...
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, ...