Maximum a posteriori probability estimates in infinite-dimensional Bayesian inverse problems

International Nuclear Information System (INIS)

Helin, T; Burger, M

2015-01-01

A demanding challenge in Bayesian inversion is to efficiently characterize the posterior distribution. This task is problematic especially in high-dimensional non-Gaussian problems, where the structure of the posterior can be very chaotic and difficult to analyse. Current inverse problem literature often approaches the problem by considering suitable point estimators for the task. Typically the choice is made between the maximum a posteriori (MAP) or the conditional mean (CM) estimate. The benefits of either choice are not well-understood from the perspective of infinite-dimensional theory. Most importantly, there exists no general scheme regarding how to connect the topological description of a MAP estimate to a variational problem. The recent results by Dashti and others (Dashti et al 2013 Inverse Problems 29 095017) resolve this issue for nonlinear inverse problems in Gaussian framework. In this work we improve the current understanding by introducing a novel concept called the weak MAP (wMAP) estimate. We show that any MAP estimate in the sense of Dashti et al (2013 Inverse Problems 29 095017) is a wMAP estimate and, moreover, how the wMAP estimate connects to a variational formulation in general infinite-dimensional non-Gaussian problems. The variational formulation enables to study many properties of the infinite-dimensional MAP estimate that were earlier impossible to study. In a recent work by the authors (Burger and Lucka 2014 Maximum a posteriori estimates in linear inverse problems with logconcave priors are proper bayes estimators preprint) the MAP estimator was studied in the context of the Bayes cost method. Using Bregman distances, proper convex Bayes cost functions were introduced for which the MAP estimator is the Bayes estimator. Here, we generalize these results to the infinite-dimensional setting. Moreover, we discuss the implications of our results for some examples of prior models such as the Besov prior and hierarchical prior. (paper)

Greedy algorithms for high-dimensional non-symmetric linear problems***

Directory of Open Access Journals (Sweden)

Cancès E.

2013-12-01

Full Text Available In this article, we present a family of numerical approaches to solve high-dimensional linear non-symmetric problems. The principle of these methods is to approximate a function which depends on a large number of variates by a sum of tensor product functions, each term of which is iteratively computed via a greedy algorithm ? . There exists a good theoretical framework for these methods in the case of (linear and nonlinear symmetric elliptic problems. However, the convergence results are not valid any more as soon as the problems under consideration are not symmetric. We present here a review of the main algorithms proposed in the literature to circumvent this difficulty, together with some new approaches. The theoretical convergence results and the practical implementation of these algorithms are discussed. Their behaviors are illustrated through some numerical examples. Dans cet article, nous présentons une famille de méthodes numériques pour résoudre des problèmes linéaires non symétriques en grande dimension. Le principe de ces approches est de représenter une fonction dépendant d’un grand nombre de variables sous la forme d’une somme de fonctions produit tensoriel, dont chaque terme est calculé itérativement via un algorithme glouton ? . Ces méthodes possèdent de bonnes propriétés théoriques dans le cas de problèmes elliptiques symétriques (linéaires ou non linéaires, mais celles-ci ne sont plus valables dès lors que les problèmes considérés ne sont plus symétriques. Nous présentons une revue des principaux algorithmes proposés dans la littérature pour contourner cette difficulté ainsi que de nouvelles approches que nous proposons. Les résultats de convergence théoriques et la mise en oeuvre pratique de ces algorithmes sont détaillés et leur comportement est illustré au travers d’exemples numériques.

An algebraic approach to the inverse eigenvalue problem for a quantum system with a dynamical group

International Nuclear Information System (INIS)

Wang, S.J.

1993-04-01

An algebraic approach to the inverse eigenvalue problem for a quantum system with a dynamical group is formulated for the first time. One dimensional problem is treated explicitly in detail for both the finite dimensional and infinite dimensional Hilbert spaces. For the finite dimensional Hilbert space, the su(2) algebraic representation is used; while for the infinite dimensional Hilbert space, the Heisenberg-Weyl algebraic representation is employed. Fourier expansion technique is generalized to the generator space, which is suitable for analysis of irregular spectra. The polynormial operator basis is also used for complement, which is appropriate for analysis of some simple Hamiltonians. The proposed new approach is applied to solve the classical inverse Sturn-Liouville problem and to study the problems of quantum regular and irregular spectra. (orig.)

Dimensional reduction of a generalized flux problem

International Nuclear Information System (INIS)

Moroz, A.

1992-01-01

In this paper, a generalized flux problem with Abelian and non-Abelian fluxes is considered. In the Abelian case we shall show that the generalized flux problem for tight-binding models of noninteracting electrons on either 2n- or (2n + 1)-dimensional lattice can always be reduced to an n-dimensional hopping problem. A residual freedom in this reduction enables one to identify equivalence classes of hopping Hamiltonians which have the same spectrum. In the non-Abelian case, the reduction is not possible in general unless the flux tensor factorizes into an Abelian one times are element of the corresponding algebra

Renormalization group study of the one-dimensional quantum Potts model

International Nuclear Information System (INIS)

Solyom, J.; Pfeuty, P.

1981-01-01

The phase transition of the classical two-dimensional Potts model, in particular the order of the transition as the number of components q increases, is studied by constructing renormalization group transformations on the equivalent one-dimensional quatum problem. It is shown that the block transformation with two sites per cell indicates the existence of a critical qsub(c) separating the small q and large q regions with different critical behaviours. The physically accessible fixed point for q>qsub(c) is a discontinuity fixed point where the specific heat exponent α=1 and therefore the transition is of first order. (author)

Toward precise solution of one-dimensional velocity inverse problems

International Nuclear Information System (INIS)

Gray, S.; Hagin, F.

1980-01-01

A family of one-dimensional inverse problems are considered with the goal of reconstructing velocity profiles to reasonably high accuracy. The travel-time variable change is used together with an iteration scheme to produce an effective algorithm for computation. Under modest assumptions the scheme is shown to be convergent

Infinite dimensional groups and algebras in quantum physics

International Nuclear Information System (INIS)

Ottesen, J.T.

1995-01-01

This book is an introduction to the application of infite-dimensional groups and algebras in quantum physics. Especially considered are the spin representation of the infinite-dimensional orthogonal group, the metaplectic representation of the infinite-dimensional symplectic groups, and Loop and Virasoro algebras. (HSI)

The quantum-field renormalization group in the problem of a growing phase boundary

International Nuclear Information System (INIS)

Antonov, N.V.; Vasil'ev, A.N.

1995-01-01

Within the quantum-field renormalization-group approach we examine the stochastic equation discussed by S.I. Pavlik in describing a randomly growing phase boundary. We show that, in contrast to Pavlik's assertion, the model is not multiplicatively renormalizable and that its consistent renormalization-group analysis requires introducing an infinite number of counterterms and the respective coupling constants (open-quotes chargeclose quotes). An explicit calculation in the one-loop approximation shows that a two-dimensional surface of renormalization-group points exits in the infinite-dimensional charge space. If the surface contains an infrared stability region, the problem allows for scaling with the nonuniversal critical dimensionalities of the height of the phase boundary and time, δ h and δ t , which satisfy the exact relationship 2 δ h = δ t + d, where d is the dimensionality of the phase boundary. 23 refs., 1 tab

Effects of dependence in high-dimensional multiple testing problems

Directory of Open Access Journals (Sweden)

van de Wiel Mark A

2008-02-01

Full Text Available Abstract Background We consider effects of dependence among variables of high-dimensional data in multiple hypothesis testing problems, in particular the False Discovery Rate (FDR control procedures. Recent simulation studies consider only simple correlation structures among variables, which is hardly inspired by real data features. Our aim is to systematically study effects of several network features like sparsity and correlation strength by imposing dependence structures among variables using random correlation matrices. Results We study the robustness against dependence of several FDR procedures that are popular in microarray studies, such as Benjamin-Hochberg FDR, Storey's q-value, SAM and resampling based FDR procedures. False Non-discovery Rates and estimates of the number of null hypotheses are computed from those methods and compared. Our simulation study shows that methods such as SAM and the q-value do not adequately control the FDR to the level claimed under dependence conditions. On the other hand, the adaptive Benjamini-Hochberg procedure seems to be most robust while remaining conservative. Finally, the estimates of the number of true null hypotheses under various dependence conditions are variable. Conclusion We discuss a new method for efficient guided simulation of dependent data, which satisfy imposed network constraints as conditional independence structures. Our simulation set-up allows for a structural study of the effect of dependencies on multiple testing criterions and is useful for testing a potentially new method on π0 or FDR estimation in a dependency context.

A high-order integral solver for scalar problems of diffraction by screens and apertures in three-dimensional space

Energy Technology Data Exchange (ETDEWEB)

Bruno, Oscar P., E-mail: obruno@caltech.edu; Lintner, Stéphane K.

2013-11-01

We present a novel methodology for the numerical solution of problems of diffraction by infinitely thin screens in three-dimensional space. Our approach relies on new integral formulations as well as associated high-order quadrature rules. The new integral formulations involve weighted versions of the classical integral operators related to the thin-screen Dirichlet and Neumann problems as well as a generalization to the open-surface problem of the classical Calderón formulae. The high-order quadrature rules we introduce for these operators, in turn, resolve the multiple Green function and edge singularities (which occur at arbitrarily close distances from each other, and which include weakly singular as well as hypersingular kernels) and thus give rise to super-algebraically fast convergence as the discretization sizes are increased. When used in conjunction with Krylov-subspace linear algebra solvers such as GMRES, the resulting solvers produce results of high accuracy in small numbers of iterations for low and high frequencies alike. We demonstrate our methodology with a variety of numerical results for screen and aperture problems at high frequencies—including simulation of classical experiments such as the diffraction by a circular disc (featuring in particular the famous Poisson spot), evaluation of interference fringes resulting from diffraction across two nearby circular apertures, as well as solution of problems of scattering by more complex geometries consisting of multiple scatterers and cavities.

High dimensional neurocomputing growth, appraisal and applications

CERN Document Server

Tripathi, Bipin Kumar

2015-01-01

The book presents a coherent understanding of computational intelligence from the perspective of what is known as "intelligent computing" with high-dimensional parameters. It critically discusses the central issue of high-dimensional neurocomputing, such as quantitative representation of signals, extending the dimensionality of neuron, supervised and unsupervised learning and design of higher order neurons. The strong point of the book is its clarity and ability of the underlying theory to unify our understanding of high-dimensional computing where conventional methods fail. The plenty of application oriented problems are presented for evaluating, monitoring and maintaining the stability of adaptive learning machine. Author has taken care to cover the breadth and depth of the subject, both in the qualitative as well as quantitative way. The book is intended to enlighten the scientific community, ranging from advanced undergraduates to engineers, scientists and seasoned researchers in computational intelligenc...

Probabilistic numerical methods for high-dimensional stochastic control and valuation problems on electricity markets

International Nuclear Information System (INIS)

Langrene, Nicolas

2014-01-01

This thesis deals with the numerical solution of general stochastic control problems, with notable applications for electricity markets. We first propose a structural model for the price of electricity, allowing for price spikes well above the marginal fuel price under strained market conditions. This model allows to price and partially hedge electricity derivatives, using fuel forwards as hedging instruments. Then, we propose an algorithm, which combines Monte-Carlo simulations with local basis regressions, to solve general optimal switching problems. A comprehensive rate of convergence of the method is provided. Moreover, we manage to make the algorithm parsimonious in memory (and hence suitable for high dimensional problems) by generalizing to this framework a memory reduction method that avoids the storage of the sample paths. We illustrate this on the problem of investments in new power plants (our structural power price model allowing the new plants to impact the price of electricity). Finally, we study more general stochastic control problems (the control can be continuous and impact the drift and volatility of the state process), the solutions of which belong to the class of fully nonlinear Hamilton-Jacobi-Bellman equations, and can be handled via constrained Backward Stochastic Differential Equations, for which we develop a backward algorithm based on control randomization and parametric optimizations. A rate of convergence between the constraPned BSDE and its discrete version is provided, as well as an estimate of the optimal control. This algorithm is then applied to the problem of super replication of options under uncertain volatilities (and correlations). (author)

Hypergraph-based anomaly detection of high-dimensional co-occurrences.

Science.gov (United States)

Silva, Jorge; Willett, Rebecca

2009-03-01

This paper addresses the problem of detecting anomalous multivariate co-occurrences using a limited number of unlabeled training observations. A novel method based on using a hypergraph representation of the data is proposed to deal with this very high-dimensional problem. Hypergraphs constitute an important extension of graphs which allow edges to connect more than two vertices simultaneously. A variational Expectation-Maximization algorithm for detecting anomalies directly on the hypergraph domain without any feature selection or dimensionality reduction is presented. The resulting estimate can be used to calculate a measure of anomalousness based on the False Discovery Rate. The algorithm has O(np) computational complexity, where n is the number of training observations and p is the number of potential participants in each co-occurrence event. This efficiency makes the method ideally suited for very high-dimensional settings, and requires no tuning, bandwidth or regularization parameters. The proposed approach is validated on both high-dimensional synthetic data and the Enron email database, where p > 75,000, and it is shown that it can outperform other state-of-the-art methods.

Multi-dimensional Bin Packing Problems with Guillotine Constraints

DEFF Research Database (Denmark)

Amossen, Rasmus Resen; Pisinger, David

2010-01-01

The problem addressed in this paper is the decision problem of determining if a set of multi-dimensional rectangular boxes can be orthogonally packed into a rectangular bin while satisfying the requirement that the packing should be guillotine cuttable. That is, there should exist a series of face...... parallel straight cuts that can recursively cut the bin into pieces so that each piece contains a box and no box has been intersected by a cut. The unrestricted problem is known to be NP-hard. In this paper we present a generalization of a constructive algorithm for the multi-dimensional bin packing...... problem, with and without the guillotine constraint, based on constraint programming....

Moving Least Squares Method for a One-Dimensional Parabolic Inverse Problem

Directory of Open Access Journals (Sweden)

Baiyu Wang

2014-01-01

Full Text Available This paper investigates the numerical solution of a class of one-dimensional inverse parabolic problems using the moving least squares approximation; the inverse problem is the determination of an unknown source term depending on time. The collocation method is used for solving the equation; some numerical experiments are presented and discussed to illustrate the stability and high efficiency of the method.

Constrained optimization by radial basis function interpolation for high-dimensional expensive black-box problems with infeasible initial points

Science.gov (United States)

Regis, Rommel G.

2014-02-01

This article develops two new algorithms for constrained expensive black-box optimization that use radial basis function surrogates for the objective and constraint functions. These algorithms are called COBRA and Extended ConstrLMSRBF and, unlike previous surrogate-based approaches, they can be used for high-dimensional problems where all initial points are infeasible. They both follow a two-phase approach where the first phase finds a feasible point while the second phase improves this feasible point. COBRA and Extended ConstrLMSRBF are compared with alternative methods on 20 test problems and on the MOPTA08 benchmark automotive problem (D.R. Jones, Presented at MOPTA 2008), which has 124 decision variables and 68 black-box inequality constraints. The alternatives include a sequential penalty derivative-free algorithm, a direct search method with kriging surrogates, and two multistart methods. Numerical results show that COBRA algorithms are competitive with Extended ConstrLMSRBF and they generally outperform the alternatives on the MOPTA08 problem and most of the test problems.

High-Dimensional Adaptive Particle Swarm Optimization on Heterogeneous Systems

International Nuclear Information System (INIS)

Wachowiak, M P; Sarlo, B B; Foster, A E Lambe

2014-01-01

Much work has recently been reported in parallel GPU-based particle swarm optimization (PSO). Motivated by the encouraging results of these investigations, while also recognizing the limitations of GPU-based methods for big problems using a large amount of data, this paper explores the efficacy of employing other types of parallel hardware for PSO. Most commodity systems feature a variety of architectures whose high-performance capabilities can be exploited. In this paper, high-dimensional problems and those that employ a large amount of external data are explored within the context of heterogeneous systems. Large problems are decomposed into constituent components, and analyses are undertaken of which components would benefit from multi-core or GPU parallelism. The current study therefore provides another demonstration that ''supercomputing on a budget'' is possible when subtasks of large problems are run on hardware most suited to these tasks. Experimental results show that large speedups can be achieved on high dimensional, data-intensive problems. Cost functions must first be analysed for parallelization opportunities, and assigned hardware based on the particular task

Irreducible quantum group modules with finite dimensional weight spaces

DEFF Research Database (Denmark)

Pedersen, Dennis Hasselstrøm

a finitely generated U q -module which has finite dimensional weight spaces and is a sum of those. Our approach follows the procedures used by S. Fernando and O. Mathieu to solve the corresponding problem for semisimple complex Lie algebra modules. To achieve this we have to overcome a number of obstacles...... not present in the classical case. In the process we also construct twisting functors rigerously for quantum group modules, study twisted Verma modules and show that these admit a Jantzen filtration with corresponding Jantzen sum formula....

Detecting low-dimensional chaos by the “noise titration” technique: Possible problems and remedies

International Nuclear Information System (INIS)

Gao Jianbo; Hu Jing; Mao Xiang; Tung Wenwen

2012-01-01

Highlights: ► Distinguishing low-dimensional chaos from noise is an important issue. ► Noise titration technique is one of the main approaches on the issue. ► Problems of noise titration technique are systematically discussed. ► Solutions to the problems of noise titration technique are provided. - Abstract: Distinguishing low-dimensional chaos from noise is an important issue in time series analysis. Among the many methods proposed for this purpose is the noise titration technique, which quantifies the amount of noise that needs to be added to the signal to fully destroy its nonlinearity. Two groups of researchers recently have questioned the validity of the technique. In this paper, we report a broad range of situations where the noise titration technique fails, and offer solutions to fix the problems identified.

Solution of the two-dimensional spectral factorization problem

Science.gov (United States)

Lawton, W. M.

1985-01-01

An approximation theorem is proven which solves a classic problem in two-dimensional (2-D) filter theory. The theorem shows that any continuous two-dimensional spectrum can be uniformly approximated by the squared modulus of a recursively stable finite trigonometric polynomial supported on a nonsymmetric half-plane.

A numerical algorithm for optimal feedback gains in high dimensional linear quadratic regulator problems

Science.gov (United States)

Banks, H. T.; Ito, K.

1991-01-01

A hybrid method for computing the feedback gains in linear quadratic regulator problem is proposed. The method, which combines use of a Chandrasekhar type system with an iteration of the Newton-Kleinman form with variable acceleration parameter Smith schemes, is formulated to efficiently compute directly the feedback gains rather than solutions of an associated Riccati equation. The hybrid method is particularly appropriate when used with large dimensional systems such as those arising in approximating infinite-dimensional (distributed parameter) control systems (e.g., those governed by delay-differential and partial differential equations). Computational advantages of the proposed algorithm over the standard eigenvector (Potter, Laub-Schur) based techniques are discussed, and numerical evidence of the efficacy of these ideas is presented.

High-dimensional model estimation and model selection

CERN Multimedia

CERN. Geneva

2015-01-01

I will review concepts and algorithms from high-dimensional statistics for linear model estimation and model selection. I will particularly focus on the so-called p>>n setting where the number of variables p is much larger than the number of samples n. I will focus mostly on regularized statistical estimators that produce sparse models. Important examples include the LASSO and its matrix extension, the Graphical LASSO, and more recent non-convex methods such as the TREX. I will show the applicability of these estimators in a diverse range of scientific applications, such as sparse interaction graph recovery and high-dimensional classification and regression problems in genomics.

Engineering two-photon high-dimensional states through quantum interference

Science.gov (United States)

Zhang, Yingwen; Roux, Filippus S.; Konrad, Thomas; Agnew, Megan; Leach, Jonathan; Forbes, Andrew

2016-01-01

Many protocols in quantum science, for example, linear optical quantum computing, require access to large-scale entangled quantum states. Such systems can be realized through many-particle qubits, but this approach often suffers from scalability problems. An alternative strategy is to consider a lesser number of particles that exist in high-dimensional states. The spatial modes of light are one such candidate that provides access to high-dimensional quantum states, and thus they increase the storage and processing potential of quantum information systems. We demonstrate the controlled engineering of two-photon high-dimensional states entangled in their orbital angular momentum through Hong-Ou-Mandel interference. We prepare a large range of high-dimensional entangled states and implement precise quantum state filtering. We characterize the full quantum state before and after the filter, and are thus able to determine that only the antisymmetric component of the initial state remains. This work paves the way for high-dimensional processing and communication of multiphoton quantum states, for example, in teleportation beyond qubits. PMID:26933685

Relativistic bound-state problem of a one-dimensional system

International Nuclear Information System (INIS)

Sato, T.; Niwa, T.; Ohtsubo, H.; Tamura, K.

1991-01-01

A Poincare-covariant description of the two-body bound-state problem in one-dimensional space is studied by using the relativistic Schrodinger equation. We derive the many-body Hamiltonian, electromagnetic current and generators of the Poincare group in the framework of one-boson exchange. Our theory satisfies Poincare algebra within the one-boson-exchange approximation. We numerically study the relativistic effects on the bound-state wavefunction and the elastic electromagnetic form factor. The Lorentz boost of the bound-state wavefunction and the two-body exchange current are shown to play an important role in guaranteeing the Lorentz invariance of the form factor. (author)

Using High-Dimensional Image Models to Perform Highly Undetectable Steganography

Science.gov (United States)

Pevný, Tomáš; Filler, Tomáš; Bas, Patrick

This paper presents a complete methodology for designing practical and highly-undetectable stegosystems for real digital media. The main design principle is to minimize a suitably-defined distortion by means of efficient coding algorithm. The distortion is defined as a weighted difference of extended state-of-the-art feature vectors already used in steganalysis. This allows us to "preserve" the model used by steganalyst and thus be undetectable even for large payloads. This framework can be efficiently implemented even when the dimensionality of the feature set used by the embedder is larger than 107. The high dimensional model is necessary to avoid known security weaknesses. Although high-dimensional models might be problem in steganalysis, we explain, why they are acceptable in steganography. As an example, we introduce HUGO, a new embedding algorithm for spatial-domain digital images and we contrast its performance with LSB matching. On the BOWS2 image database and in contrast with LSB matching, HUGO allows the embedder to hide 7× longer message with the same level of security level.

A finite-dimensional reduction method for slightly supercritical elliptic problems

Directory of Open Access Journals (Sweden)

Riccardo Molle

2004-01-01

Full Text Available We describe a finite-dimensional reduction method to find solutions for a class of slightly supercritical elliptic problems. A suitable truncation argument allows us to work in the usual Sobolev space even in the presence of supercritical nonlinearities: we modify the supercritical term in such a way to have subcritical approximating problems; for these problems, the finite-dimensional reduction can be obtained applying the methods already developed in the subcritical case; finally, we show that, if the truncation is realized at a sufficiently large level, then the solutions of the approximating problems, given by these methods, also solve the supercritical problems when the parameter is small enough.

Matrix-type multiple reciprocity boundary element method for solving three-dimensional two-group neutron diffusion equations

International Nuclear Information System (INIS)

Itagaki, Masafumi; Sahashi, Naoki.

1997-01-01

The multiple reciprocity boundary element method has been applied to three-dimensional two-group neutron diffusion problems. A matrix-type boundary integral equation has been derived to solve the first and the second group neutron diffusion equations simultaneously. The matrix-type fundamental solutions used here satisfy the equation which has a point source term and is adjoint to the neutron diffusion equations. A multiple reciprocity method has been employed to transform the matrix-type domain integral related to the fission source into an equivalent boundary one. The higher order fundamental solutions required for this formulation are composed of a series of two types of analytic functions. The eigenvalue itself is also calculated using only boundary integrals. Three-dimensional test calculations indicate that the present method provides stable and accurate solutions for criticality problems. (author)

Dimensional analysis and group theory in astrophysics

CERN Document Server

Kurth, Rudolf

2013-01-01

Dimensional Analysis and Group Theory in Astrophysics describes how dimensional analysis, refined by mathematical regularity hypotheses, can be applied to purely qualitative physical assumptions. The book focuses on the continuous spectral of the stars and the mass-luminosity relationship. The text discusses the technique of dimensional analysis, covering both relativistic phenomena and the stellar systems. The book also explains the fundamental conclusion of dimensional analysis, wherein the unknown functions shall be given certain specified forms. The Wien and Stefan-Boltzmann Laws can be si

An inverse problem for a one-dimensional time-fractional diffusion problem

KAUST Repository

Jin, Bangti; Rundell, William

2012-01-01

We study an inverse problem of recovering a spatially varying potential term in a one-dimensional time-fractional diffusion equation from the flux measurements taken at a single fixed time corresponding to a given set of input sources. The unique

Variables separation and superintegrability of the nine-dimensional MICZ-Kepler problem

Science.gov (United States)

Phan, Ngoc-Hung; Le, Dai-Nam; Thoi, Tuan-Quoc N.; Le, Van-Hoang

2018-03-01

The nine-dimensional MICZ-Kepler problem is of recent interest. This is a system describing a charged particle moving in the Coulomb field plus the field of a SO(8) monopole in a nine-dimensional space. Interestingly, this problem is equivalent to a 16-dimensional harmonic oscillator via the Hurwitz transformation. In the present paper, we report on the multiseparability, a common property of superintegrable systems, and the superintegrability of the problem. First, we show the solvability of the Schrödinger equation of the problem by the variables separation method in different coordinates. Second, based on the SO(10) symmetry algebra of the system, we construct explicitly a set of seventeen invariant operators, which are all in the second order of the momentum components, satisfying the condition of superintegrability. The found number 17 coincides with the prediction of (2n - 1) law of maximal superintegrability order in the case n = 9. Until now, this law is accepted to apply only to scalar Hamiltonian eigenvalue equations in n-dimensional space; therefore, our results can be treated as evidence that this definition of superintegrability may also apply to some vector equations such as the Schrödinger equation for the nine-dimensional MICZ-Kepler problem.

hdm: High-dimensional metrics

OpenAIRE

Chernozhukov, Victor; Hansen, Christian; Spindler, Martin

2016-01-01

In this article the package High-dimensional Metrics (\\texttt{hdm}) is introduced. It is a collection of statistical methods for estimation and quantification of uncertainty in high-dimensional approximately sparse models. It focuses on providing confidence intervals and significance testing for (possibly many) low-dimensional subcomponents of the high-dimensional parameter vector. Efficient estimators and uniformly valid confidence intervals for regression coefficients on target variables (e...

Decay rate in a multi-dimensional fission problem

Energy Technology Data Exchange (ETDEWEB)

Brink, D M; Canto, L F

1986-06-01

The multi-dimensional diffusion approach of Zhang Jing Shang and Weidenmueller (1983 Phys. Rev. C28, 2190) is used to study a simplified model for induced fission. In this model it is shown that the coupling of the fission coordinate to the intrinsic degrees of freedom is equivalent to an extra friction and a mass correction in the corresponding one-dimensional problem.

Reducing the Complexity of Genetic Fuzzy Classifiers in Highly-Dimensional Classification Problems

Directory of Open Access Journals (Sweden)

DimitrisG. Stavrakoudis

2012-04-01

Full Text Available This paper introduces the Fast Iterative Rule-based Linguistic Classifier (FaIRLiC, a Genetic Fuzzy Rule-Based Classification System (GFRBCS which targets at reducing the structural complexity of the resulting rule base, as well as its learning algorithm's computational requirements, especially when dealing with high-dimensional feature spaces. The proposed methodology follows the principles of the iterative rule learning (IRL approach, whereby a rule extraction algorithm (REA is invoked in an iterative fashion, producing one fuzzy rule at a time. The REA is performed in two successive steps: the first one selects the relevant features of the currently extracted rule, whereas the second one decides the antecedent part of the fuzzy rule, using the previously selected subset of features. The performance of the classifier is finally optimized through a genetic tuning post-processing stage. Comparative results in a hyperspectral remote sensing classification as well as in 12 real-world classification datasets indicate the effectiveness of the proposed methodology in generating high-performing and compact fuzzy rule-based classifiers, even for very high-dimensional feature spaces.

Two-dimensional boundary-value problem for ion-ion diffusion

International Nuclear Information System (INIS)

Tuszewski, M.; Lichtenberg, A.J.

1977-01-01

Like-particle diffusion is usually negligible compared with unlike-particle diffusion because it is two orders higher in spatial derivatives. When the ratio of the ion gyroradius to the plasma transverse dimension is of the order of the fourth root of the mass ratio, previous one-dimensional analysis indicated that like-particle diffusion is significant. A two-dimensional boundary-value problem for ion-ion diffusion is investigated. Numerical solutions are found with models for which the nonlinear partial differential equation reduces to an ordinary fourth-order differential equation. These solutions indicate that the ion-ion losses are higher by a factor of six for a slab geometry, and by a factor of four for circular geometry, than estimated from dimensional analysis. The solutions are applied to a multiple mirror experiment stabilized with a quadrupole magnetic field which generates highly elliptical flux surfaces. It is found that the ion-ion losses dominate the electron-ion losses and that these classical radial losses contribute to a significant decrease of plasma lifetime, in qualitiative agreement with the experimental results

Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation

International Nuclear Information System (INIS)

Tripathy, Rohit; Bilionis, Ilias; Gonzalez, Marcial

2016-01-01

Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the

Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation

Science.gov (United States)

Tripathy, Rohit; Bilionis, Ilias; Gonzalez, Marcial

2016-09-01

Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the

Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation

Energy Technology Data Exchange (ETDEWEB)

Tripathy, Rohit, E-mail: rtripath@purdue.edu; Bilionis, Ilias, E-mail: ibilion@purdue.edu; Gonzalez, Marcial, E-mail: marcial-gonzalez@purdue.edu

2016-09-15

Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the

One-dimensional inverse problems of mathematical physics

CERN Document Server

Lavrent'ev, M M; Yakhno, V G; Schulenberger, J R

1986-01-01

This monograph deals with the inverse problems of determining a variable coefficient and right side for hyperbolic and parabolic equations on the basis of known solutions at fixed points of space for all times. The problems are one-dimensional in nature since the desired coefficient of the equation is a function of only one coordinate, while the desired right side is a function only of time. The authors use methods based on the spectral theory of ordinary differential operators of second order and also methods which make it possible to reduce the investigation of the inverse problems to the in

Approximate solutions for the two-dimensional integral transport equation. Solution of complex two-dimensional transport problems

International Nuclear Information System (INIS)

Sanchez, Richard.

1980-11-01

This work is divided into two parts: the first part deals with the solution of complex two-dimensional transport problems, the second one (note CEA-N-2166) treats the critically mixed methods of resolution. A set of approximate solutions for the isotropic two-dimensional neutron transport problem has been developed using the interface current formalism. The method has been applied to regular lattices of rectangular cells containing a fuel pin, cladding, and water, or homogenized structural material. The cells are divided into zones that are homogeneous. A zone-wise flux expansion is used to formulate a direct collision probability problem within a cell. The coupling of the cells is effected by making extra assumptions on the currents entering and leaving the interfaces. Two codes have been written: CALLIOPE uses a cylindrical cell model and one or three terms for the flux expansion, and NAUSICAA uses a two-dimensional flux representation and does a truly two-dimensional calculation inside each cell. In both codes, one or three terms can be used to make a space-independent expansion of the angular fluxes entering and leaving each side of the cell. The accuracies and computing times achieved with the different approximations are illustrated by numerical studies on two benchmark problems and by calculations performed in the APOLLO multigroup code [fr

Hybrid subgroup decomposition method for solving fine-group eigenvalue transport problems

International Nuclear Information System (INIS)

Yasseri, Saam; Rahnema, Farzad

2014-01-01

Highlights: • An acceleration technique for solving fine-group eigenvalue transport problems. • Coarse-group quasi transport theory to solve coarse-group eigenvalue transport problems. • Consistent and inconsistent formulations for coarse-group quasi transport theory. • Computational efficiency amplified by a factor of 2 using hybrid SGD for 1D BWR problem. - Abstract: In this paper, a new hybrid method for solving fine-group eigenvalue transport problems is developed. This method extends the subgroup decomposition method to efficiently couple a new coarse-group quasi transport theory with a set of fixed-source transport decomposition sweeps to obtain the fine-group transport solution. The advantages of the quasi transport theory are its high accuracy, straight-forward implementation and numerical stability. The hybrid method is analyzed for a 1D benchmark problem characteristic of boiling water reactors (BWR). It is shown that the method reproduces the fine-group transport solution with high accuracy while increasing the computational efficiency up to 12 times compared to direct fine-group transport calculations

Multigrid for high dimensional elliptic partial differential equations on non-equidistant grids

NARCIS (Netherlands)

bin Zubair, H.; Oosterlee, C.E.; Wienands, R.

2006-01-01

This work presents techniques, theory and numbers for multigrid in a general d-dimensional setting. The main focus is the multigrid convergence for high-dimensional partial differential equations (PDEs). As a model problem we have chosen the anisotropic diffusion equation, on a unit hypercube. We

Multiple Attribute Group Decision-Making Methods Based on Trapezoidal Fuzzy Two-Dimensional Linguistic Partitioned Bonferroni Mean Aggregation Operators.

Science.gov (United States)

Yin, Kedong; Yang, Benshuo; Li, Xuemei

2018-01-24

In this paper, we investigate multiple attribute group decision making (MAGDM) problems where decision makers represent their evaluation of alternatives by trapezoidal fuzzy two-dimensional uncertain linguistic variable. To begin with, we introduce the definition, properties, expectation, operational laws of trapezoidal fuzzy two-dimensional linguistic information. Then, to improve the accuracy of decision making in some case where there are a sort of interrelationship among the attributes, we analyze partition Bonferroni mean (PBM) operator in trapezoidal fuzzy two-dimensional variable environment and develop two operators: trapezoidal fuzzy two-dimensional linguistic partitioned Bonferroni mean (TF2DLPBM) aggregation operator and trapezoidal fuzzy two-dimensional linguistic weighted partitioned Bonferroni mean (TF2DLWPBM) aggregation operator. Furthermore, we develop a novel method to solve MAGDM problems based on TF2DLWPBM aggregation operator. Finally, a practical example is presented to illustrate the effectiveness of this method and analyses the impact of different parameters on the results of decision-making.

High Dimensional Classification Using Features Annealed Independence Rules.

Science.gov (United States)

Fan, Jianqing; Fan, Yingying

2008-01-01

Classification using high-dimensional features arises frequently in many contemporary statistical studies such as tumor classification using microarray or other high-throughput data. The impact of dimensionality on classifications is largely poorly understood. In a seminal paper, Bickel and Levina (2004) show that the Fisher discriminant performs poorly due to diverging spectra and they propose to use the independence rule to overcome the problem. We first demonstrate that even for the independence classification rule, classification using all the features can be as bad as the random guessing due to noise accumulation in estimating population centroids in high-dimensional feature space. In fact, we demonstrate further that almost all linear discriminants can perform as bad as the random guessing. Thus, it is paramountly important to select a subset of important features for high-dimensional classification, resulting in Features Annealed Independence Rules (FAIR). The conditions under which all the important features can be selected by the two-sample t-statistic are established. The choice of the optimal number of features, or equivalently, the threshold value of the test statistics are proposed based on an upper bound of the classification error. Simulation studies and real data analysis support our theoretical results and demonstrate convincingly the advantage of our new classification procedure.

The dimension split element-free Galerkin method for three-dimensional potential problems

Science.gov (United States)

Meng, Z. J.; Cheng, H.; Ma, L. D.; Cheng, Y. M.

2018-02-01

This paper presents the dimension split element-free Galerkin (DSEFG) method for three-dimensional potential problems, and the corresponding formulae are obtained. The main idea of the DSEFG method is that a three-dimensional potential problem can be transformed into a series of two-dimensional problems. For these two-dimensional problems, the improved moving least-squares (IMLS) approximation is applied to construct the shape function, which uses an orthogonal function system with a weight function as the basis functions. The Galerkin weak form is applied to obtain a discretized system equation, and the penalty method is employed to impose the essential boundary condition. The finite difference method is selected in the splitting direction. For the purposes of demonstration, some selected numerical examples are solved using the DSEFG method. The convergence study and error analysis of the DSEFG method are presented. The numerical examples show that the DSEFG method has greater computational precision and computational efficiency than the IEFG method.

HEXAGA-II-120, -60, -30 two-dimensional multi-group neutron diffusion programmes for a uniform triangular mesh with arbitrary group scattering

International Nuclear Information System (INIS)

Woznicki, Z.

1979-06-01

This report presents the AGA two-sweep iterative methods belonging to the family of factorization techniques in their practical application in the HEXAGA-II two-dimensional programme to obtain the numerical solution to the multi-group, time-independent, (real and/or adjoint) neutron diffusion equations for a fine uniform triangular mesh. An arbitrary group scattering model is permitted. The report written for the users provides the description of input and output. The use of HEXAGA-II is illustrated by two sample reactor problems. (orig.) [de

Complexity of hierarchically and 1-dimensional periodically specified problems

Energy Technology Data Exchange (ETDEWEB)

Marathe, M.V.; Hunt, H.B. III; Stearns, R.E.; Radhakrishnan, V.

1995-08-23

We study the complexity of various combinatorial and satisfiability problems when instances are specified using one of the following specifications: (1) the 1-dimensional finite periodic narrow specifications of Wanke and Ford et al. (2) the 1-dimensional finite periodic narrow specifications with explicit boundary conditions of Gale (3) the 2-way infinite1-dimensional narrow periodic specifications of Orlin et al. and (4) the hierarchical specifications of Lengauer et al. we obtain three general types of results. First, we prove that there is a polynomial time algorithm that given a 1-FPN- or 1-FPN(BC)specification of a graph (or a C N F formula) constructs a level-restricted L-specification of an isomorphic graph (or formula). This theorem along with the hardness results proved here provides alternative and unified proofs of many hardness results proved in the past either by Lengauer and Wagner or by Orlin. Second, we study the complexity of generalized CNF satisfiability problems of Schaefer. Assuming P {ne} PSPACE, we characterize completely the polynomial time solvability of these problems, when instances are specified as in (1), (2),(3) or (4). As applications of our first two types of results, we obtain a number of new PSPACE-hardness and polynomial time algorithms for problems specified as in (1), (2), (3) or(4). Many of our results also hold for O(log N) bandwidth bounded planar instances.

The 'thousand words' problem: Summarizing multi-dimensional data

International Nuclear Information System (INIS)

Scott, David M.

2011-01-01

Research highlights: → Sophisticated process sensors produce large multi-dimensional data sets. → Plant control systems cannot handle images or large amounts of data. → Various techniques reduce the dimensionality, extracting information from raw data. → Simple 1D and 2D methods can often be extended to 3D and 4D applications. - Abstract: An inherent difficulty in the application of multi-dimensional sensing to process monitoring and control is the extraction and interpretation of useful information. Ultimately the measured data must be collapsed into a relatively small number of values that capture the salient characteristics of the process. Although multiple dimensions are frequently necessary to isolate a particular physical attribute (such as the distribution of a particular chemical species in a reactor), plant control systems are not equipped to use such data directly. The production of a multi-dimensional data set (often displayed as an image) is not the final step of the measurement process, because information must still be extracted from the raw data. In the metaphor of one picture being equal to a thousand words, the problem becomes one of paraphrasing a lengthy description of the image with one or two well-chosen words. Various approaches to solving this problem are discussed using examples from the fields of particle characterization, image processing, and process tomography.

Asymptotics of empirical eigenstructure for high dimensional spiked covariance.

Science.gov (United States)

Wang, Weichen; Fan, Jianqing

2017-06-01

We derive the asymptotic distributions of the spiked eigenvalues and eigenvectors under a generalized and unified asymptotic regime, which takes into account the magnitude of spiked eigenvalues, sample size, and dimensionality. This regime allows high dimensionality and diverging eigenvalues and provides new insights into the roles that the leading eigenvalues, sample size, and dimensionality play in principal component analysis. Our results are a natural extension of those in Paul (2007) to a more general setting and solve the rates of convergence problems in Shen et al. (2013). They also reveal the biases of estimating leading eigenvalues and eigenvectors by using principal component analysis, and lead to a new covariance estimator for the approximate factor model, called shrinkage principal orthogonal complement thresholding (S-POET), that corrects the biases. Our results are successfully applied to outstanding problems in estimation of risks of large portfolios and false discovery proportions for dependent test statistics and are illustrated by simulation studies.

Irregular grid methods for pricing high-dimensional American options

NARCIS (Netherlands)

Berridge, S.J.

2004-01-01

This thesis proposes and studies numerical methods for pricing high-dimensional American options; important examples being basket options, Bermudan swaptions and real options. Four new methods are presented and analysed, both in terms of their application to various test problems, and in terms of

An adaptive ANOVA-based PCKF for high-dimensional nonlinear inverse modeling

Science.gov (United States)

Li, Weixuan; Lin, Guang; Zhang, Dongxiao

2014-02-01

The probabilistic collocation-based Kalman filter (PCKF) is a recently developed approach for solving inverse problems. It resembles the ensemble Kalman filter (EnKF) in every aspect-except that it represents and propagates model uncertainty by polynomial chaos expansion (PCE) instead of an ensemble of model realizations. Previous studies have shown PCKF is a more efficient alternative to EnKF for many data assimilation problems. However, the accuracy and efficiency of PCKF depends on an appropriate truncation of the PCE series. Having more polynomial chaos basis functions in the expansion helps to capture uncertainty more accurately but increases computational cost. Selection of basis functions is particularly important for high-dimensional stochastic problems because the number of polynomial chaos basis functions required to represent model uncertainty grows dramatically as the number of input parameters (random dimensions) increases. In classic PCKF algorithms, the PCE basis functions are pre-set based on users' experience. Also, for sequential data assimilation problems, the basis functions kept in PCE expression remain unchanged in different Kalman filter loops, which could limit the accuracy and computational efficiency of classic PCKF algorithms. To address this issue, we present a new algorithm that adaptively selects PCE basis functions for different problems and automatically adjusts the number of basis functions in different Kalman filter loops. The algorithm is based on adaptive functional ANOVA (analysis of variance) decomposition, which approximates a high-dimensional function with the summation of a set of low-dimensional functions. Thus, instead of expanding the original model into PCE, we implement the PCE expansion on these low-dimensional functions, which is much less costly. We also propose a new adaptive criterion for ANOVA that is more suited for solving inverse problems. The new algorithm was tested with different examples and demonstrated

High-Dimensional Metrics in R

OpenAIRE

Chernozhukov, Victor; Hansen, Chris; Spindler, Martin

2016-01-01

The package High-dimensional Metrics (\\Rpackage{hdm}) is an evolving collection of statistical methods for estimation and quantification of uncertainty in high-dimensional approximately sparse models. It focuses on providing confidence intervals and significance testing for (possibly many) low-dimensional subcomponents of the high-dimensional parameter vector. Efficient estimators and uniformly valid confidence intervals for regression coefficients on target variables (e.g., treatment or poli...

An analytical approach for a nodal scheme of two-dimensional neutron transport problems

International Nuclear Information System (INIS)

Barichello, L.B.; Cabrera, L.C.; Prolo Filho, J.F.

2011-01-01

Research highlights: → Nodal equations for a two-dimensional neutron transport problem. → Analytical Discrete Ordinates Method. → Numerical results compared with the literature. - Abstract: In this work, a solution for a two-dimensional neutron transport problem, in cartesian geometry, is proposed, on the basis of nodal schemes. In this context, one-dimensional equations are generated by an integration process of the multidimensional problem. Here, the integration is performed for the whole domain such that no iterative procedure between nodes is needed. The ADO method is used to develop analytical discrete ordinates solution for the one-dimensional integrated equations, such that final solutions are analytical in terms of the spatial variables. The ADO approach along with a level symmetric quadrature scheme, lead to a significant order reduction of the associated eigenvalues problems. Relations between the averaged fluxes and the unknown fluxes at the boundary are introduced as the usually needed, in nodal schemes, auxiliary equations. Numerical results are presented and compared with test problems.

Parallel Simulation of Three-Dimensional Free Surface Fluid Flow Problems

International Nuclear Information System (INIS)

BAER, THOMAS A.; SACKINGER, PHILIP A.; SUBIA, SAMUEL R.

1999-01-01

Simulation of viscous three-dimensional fluid flow typically involves a large number of unknowns. When free surfaces are included, the number of unknowns increases dramatically. Consequently, this class of problem is an obvious application of parallel high performance computing. We describe parallel computation of viscous, incompressible, free surface, Newtonian fluid flow problems that include dynamic contact fines. The Galerkin finite element method was used to discretize the fully-coupled governing conservation equations and a ''pseudo-solid'' mesh mapping approach was used to determine the shape of the free surface. In this approach, the finite element mesh is allowed to deform to satisfy quasi-static solid mechanics equations subject to geometric or kinematic constraints on the boundaries. As a result, nodal displacements must be included in the set of unknowns. Other issues discussed are the proper constraints appearing along the dynamic contact line in three dimensions. Issues affecting efficient parallel simulations include problem decomposition to equally distribute computational work among a SPMD computer and determination of robust, scalable preconditioners for the distributed matrix systems that must be solved. Solution continuation strategies important for serial simulations have an enhanced relevance in a parallel coquting environment due to the difficulty of solving large scale systems. Parallel computations will be demonstrated on an example taken from the coating flow industry: flow in the vicinity of a slot coater edge. This is a three dimensional free surface problem possessing a contact line that advances at the web speed in one region but transitions to static behavior in another region. As such, a significant fraction of the computational time is devoted to processing boundary data. Discussion focuses on parallel speed ups for fixed problem size, a class of problems of immediate practical importance

Symmetry analysis and exact solutions of one class of (1+3)-dimensional boundary-value problems of the Stefan type

OpenAIRE

Kovalenko, S. S.

2014-01-01

We present the group classification of one class of (1+3)-dimensional nonlinear boundary-value problems of the Stefan type that simulate the processes of melting and evaporation of metals. The results obtained are used for the construction of the exact solution of one boundary-value problem from the class under study.

Common Group Problems: A Field Study.

Science.gov (United States)

Weinberg, Sanford B.; And Others

1981-01-01

A field study of a naturally functioning group (N=125) was conducted to identify common group problems. Trained observers attended group meetings and described the problems encountered. Difficulties of cohesion, leadership, sub-group formation, and personality conflict were identified. (RC)

Detection of Subtle Context-Dependent Model Inaccuracies in High-Dimensional Robot Domains.

Science.gov (United States)

Mendoza, Juan Pablo; Simmons, Reid; Veloso, Manuela

2016-12-01

Autonomous robots often rely on models of their sensing and actions for intelligent decision making. However, when operating in unconstrained environments, the complexity of the world makes it infeasible to create models that are accurate in every situation. This article addresses the problem of using potentially large and high-dimensional sets of robot execution data to detect situations in which a robot model is inaccurate-that is, detecting context-dependent model inaccuracies in a high-dimensional context space. To find inaccuracies tractably, the robot conducts an informed search through low-dimensional projections of execution data to find parametric Regions of Inaccurate Modeling (RIMs). Empirical evidence from two robot domains shows that this approach significantly enhances the detection power of existing RIM-detection algorithms in high-dimensional spaces.

Dimensional analysis and qualitative methods in problem solving: II

International Nuclear Information System (INIS)

Pescetti, D

2009-01-01

We show that the underlying mathematical structure of dimensional analysis (DA), in the qualitative methods in problem-solving context, is the algebra of the affine spaces. In particular, we show that the qualitative problem-solving procedure based on the parallel decomposition of a problem into simple special cases yields the new original mathematical concepts of special points and special representations of affine spaces. A qualitative problem-solving algorithm piloted by the mathematics of DA is illustrated by a set of examples.

Model-based Clustering of High-Dimensional Data in Astrophysics

Science.gov (United States)

Bouveyron, C.

2016-05-01

The nature of data in Astrophysics has changed, as in other scientific fields, in the past decades due to the increase of the measurement capabilities. As a consequence, data are nowadays frequently of high dimensionality and available in mass or stream. Model-based techniques for clustering are popular tools which are renowned for their probabilistic foundations and their flexibility. However, classical model-based techniques show a disappointing behavior in high-dimensional spaces which is mainly due to their dramatical over-parametrization. The recent developments in model-based classification overcome these drawbacks and allow to efficiently classify high-dimensional data, even in the "small n / large p" situation. This work presents a comprehensive review of these recent approaches, including regularization-based techniques, parsimonious modeling, subspace classification methods and classification methods based on variable selection. The use of these model-based methods is also illustrated on real-world classification problems in Astrophysics using R packages.

Global communication schemes for the numerical solution of high-dimensional PDEs

DEFF Research Database (Denmark)

Hupp, Philipp; Heene, Mario; Jacob, Riko

2016-01-01

The numerical treatment of high-dimensional partial differential equations is among the most compute-hungry problems and in urgent need for current and future high-performance computing (HPC) systems. It is thus also facing the grand challenges of exascale computing such as the requirement...

A numerical method for two-dimensional anisotropic transport problem in cylindrical geometry

International Nuclear Information System (INIS)

Du Mingsheng; Feng Tiekai; Fu Lianxiang; Cao Changshu; Liu Yulan

1988-01-01

The authors deal with the triangular mesh-discontinuous finite element method for solving the time-dependent anisotropic neutron transport problem in two-dimensional cylindrical geometry. A prior estimate of the numerical solution is given. Stability is proved. The authors have computed a two dimensional anisotropic neutron transport problem and a Tungsten-Carbide critical assembly problem by using the numerical method. In comparision with DSN method and the experimental results obtained by others both at home and abroad, the method is satisfactory

Inverse radiative transfer problems in two-dimensional heterogeneous media

International Nuclear Information System (INIS)

Tito, Mariella Janette Berrocal

2001-01-01

The analysis of inverse problems in participating media where emission, absorption and scattering take place has several relevant applications in engineering and medicine. Some of the techniques developed for the solution of inverse problems have as a first step the solution of the direct problem. In this work the discrete ordinates method has been used for the solution of the linearized Boltzmann equation in two dimensional cartesian geometry. The Levenberg - Marquardt method has been used for the solution of the inverse problem of internal source and absorption and scattering coefficient estimation. (author)

Fast Markov chain Monte Carlo sampling for sparse Bayesian inference in high-dimensional inverse problems using L1-type priors

International Nuclear Information System (INIS)

Lucka, Felix

2012-01-01

Sparsity has become a key concept for solving of high-dimensional inverse problems using variational regularization techniques. Recently, using similar sparsity-constraints in the Bayesian framework for inverse problems by encoding them in the prior distribution has attracted attention. Important questions about the relation between regularization theory and Bayesian inference still need to be addressed when using sparsity promoting inversion. A practical obstacle for these examinations is the lack of fast posterior sampling algorithms for sparse, high-dimensional Bayesian inversion. Accessing the full range of Bayesian inference methods requires being able to draw samples from the posterior probability distribution in a fast and efficient way. This is usually done using Markov chain Monte Carlo (MCMC) sampling algorithms. In this paper, we develop and examine a new implementation of a single component Gibbs MCMC sampler for sparse priors relying on L1-norms. We demonstrate that the efficiency of our Gibbs sampler increases when the level of sparsity or the dimension of the unknowns is increased. This property is contrary to the properties of the most commonly applied Metropolis–Hastings (MH) sampling schemes. We demonstrate that the efficiency of MH schemes for L1-type priors dramatically decreases when the level of sparsity or the dimension of the unknowns is increased. Practically, Bayesian inversion for L1-type priors using MH samplers is not feasible at all. As this is commonly believed to be an intrinsic feature of MCMC sampling, the performance of our Gibbs sampler also challenges common beliefs about the applicability of sample based Bayesian inference. (paper)

Problem specific heuristics for group scheduling problems in cellular manufacturing

OpenAIRE

Neufeld, Janis Sebastian

2016-01-01

The group scheduling problem commonly arises in cellular manufacturing systems, where parts are grouped into part families. It is characterized by a sequencing task on two levels: on the one hand, a sequence of jobs within each part family has to be identified while, on the other hand, a family sequence has to be determined. In order to solve this NP-hard problem usually heuristic solution approaches are used. In this thesis different aspects of group scheduling are discussed and problem spec...

HEXAGA-III-120, -30. Three dimensional multi-group neutron diffusion programmes for a uniform triangular mesh with arbitrary group scattering

International Nuclear Information System (INIS)

Woznicki, Z.I.

1983-07-01

This report presents the HEXAGA-III-programme solving multi-group time-independent real and/or adjoint neutron diffusion equations for three-dimensional-triangular-z-geometry. The method of solution is based on the AGA two-sweep iterative method belonging to the family of factorization techniques. An arbitrary neutron scattering model is permitted. The report written for users provides the description of the programme input and output and the use of HEXAGA-III is illustrated by a sample reactor problem. (orig.) [de

Green function of a three-dimensional Wick problem

International Nuclear Information System (INIS)

Matveev, V.A.

1988-01-01

An exact solution of a three-dimensional Coulomb Wick-Cutkovsky problem has been obtained which possesses the hidden 0(4)-symmetry. Here we shell give the derivation of the corresponding Green function and consider its connection with the asymptoric behaviour of the scattering amplitude. 9 refs

Multi-dimensional Analysis for SLB Transient in ATLAS Facility as Activity of DSP (Domestic Standard Problem)

International Nuclear Information System (INIS)

Bae, B. U.; Park, Y. S.; Kim, J. R.; Kang, K. H.; Choi, K. Y.; Sung, H. J.; Hwang, M. J.; Kang, D. H.; Lim, S. G.; Jun, S. S.

2015-01-01

Participants of DSP-03 were divided in three groups and each group has focused on the specific subject related to the enhancement of the code analysis. The group A tried to investigate scaling capability of ATLAS test data by comparing to the code analysis for a prototype, and the group C studied to investigate effect of various models in the one-dimensional codes. This paper briefly summarizes the code analysis result from the group B participants in the DSP-03 of the ATLAS test facility. The code analysis by Group B focuses highly on investigating the multi-dimensional thermal hydraulic phenomena in the ATLAS facility during the SLB transient. Even though the one-dimensional system analysis code cannot simulate the whole system of the ATLAS facility with a nodalization of the CFD (Computational Fluid Dynamics) scale, a reactor pressure vessel can be considered with multi-dimensional components to reflect the thermal mixing phenomena inside a downcomer and a core. Also, the CFD could give useful information for understanding complex phenomena in specific components such as the reactor pressure vessel. From the analysis activity of Group B in ATLAS DSP-03, participants adopted a multi-dimensional approach to the code analysis for the SLB transient in the ATLAS test facility. The main purpose of the analysis was to investigate prediction capability of multi-dimensional analysis tools for the SLB experiment result. In particular, the asymmetric cooling and thermal mixing phenomena in the reactor pressure vessel could be significantly focused for modeling the multi-dimensional components

High-dimensional cluster analysis with the Masked EM Algorithm

Science.gov (United States)

Kadir, Shabnam N.; Goodman, Dan F. M.; Harris, Kenneth D.

2014-01-01

Cluster analysis faces two problems in high dimensions: first, the “curse of dimensionality” that can lead to overfitting and poor generalization performance; and second, the sheer time taken for conventional algorithms to process large amounts of high-dimensional data. We describe a solution to these problems, designed for the application of “spike sorting” for next-generation high channel-count neural probes. In this problem, only a small subset of features provide information about the cluster member-ship of any one data vector, but this informative feature subset is not the same for all data points, rendering classical feature selection ineffective. We introduce a “Masked EM” algorithm that allows accurate and time-efficient clustering of up to millions of points in thousands of dimensions. We demonstrate its applicability to synthetic data, and to real-world high-channel-count spike sorting data. PMID:25149694

Spectrally-Corrected Estimation for High-Dimensional Markowitz Mean-Variance Optimization

NARCIS (Netherlands)

Z. Bai (Zhidong); H. Li (Hua); M.J. McAleer (Michael); W.-K. Wong (Wing-Keung)

2016-01-01

textabstractThis paper considers the portfolio problem for high dimensional data when the dimension and size are both large. We analyze the traditional Markowitz mean-variance (MV) portfolio by large dimension matrix theory, and find the spectral distribution of the sample covariance is the main

Problem-Based Group Activities for Teaching Sensation and Perception

Science.gov (United States)

Kreiner, David S.

2009-01-01

This article describes 14 problem-based group activities for a sensation and perception course. The intent was to provide opportunities for students to practice applying their knowledge to real-world problems related to course content. Student ratings of how effectively the activities helped them learn were variable but relatively high. Students…

Three-dimensional problems in the theory of cracks

International Nuclear Information System (INIS)

Panasyuk, V.V.; Andrejkiv, A.E.; Stadnik, M.M.

1979-01-01

Review of the main mechanical conceptions and mathematic methods, used in solving of spatial problems of the theory of cracks is given. At that, cases of effects upon a body of force static and cyclic and geometrically variable temperature fields are considered. The main calculation models of the theory of cracks are characterized in detail. Other models, derived from these ones and used in solving the above problems are also mentioned. Analysis and synthesis of the most general mathematic methods of solving three-dimensional problems of the theory of cracks are made. Besides precise methods, approximate ones are also presented, being efficient enough in engineering practice

TWO-DIMENSIONAL APPROXIMATION OF EIGENVALUE PROBLEMS IN SHELL THEORY: FLEXURAL SHELLS

Institute of Scientific and Technical Information of China (English)

无

2000-01-01

The eigenvalue problem for a thin linearly elastic shell, of thickness 2e, clamped along its lateral surface is considered. Under the geometric assumption on the middle surface of the shell that the space of inextensional displacements is non-trivial, the authors obtain, as ε→0,the eigenvalue problem for the two-dimensional"flexural shell"model if the dimension of the space is infinite. If the space is finite dimensional, the limits of the eigenvalues could belong to the spectra of both flexural and membrane shells. The method consists of rescaling the variables and studying the problem over a fixed domain. The principal difficulty lies in obtaining suitable a priori estimates for the scaled eigenvalues.

Variational group-PCA for intrinsic dimensionality determination in fMRI data

DEFF Research Database (Denmark)

Hinrich, Jesper Løve; Nielsen, Søren Føns Vind; Madsen, Kristoffer Hougaard

2016-01-01

. Furthermore, in an fMRI-context it is not fully understood how information from multiple subjects should best be incorporated when applying dimensionality reduction. We propose a Bayesian group principal component analysis (Group-BPCA) model with an automatic relevance determination (ARD) prior to determine...... on the spatial maps are shared, leads to pruning components, but provide better generalization in two of three scenarios. We show that the right level of subject variability is highly dependent on the chosen validation scheme....

An irregular grid approach for pricing high-dimensional American options

NARCIS (Netherlands)

Berridge, S.J.; Schumacher, J.M.

2008-01-01

We propose and test a new method for pricing American options in a high-dimensional setting. The method is centered around the approximation of the associated complementarity problem on an irregular grid. We approximate the partial differential operator on this grid by appealing to the SDE

An Irregular Grid Approach for Pricing High-Dimensional American Options

NARCIS (Netherlands)

Berridge, S.J.; Schumacher, J.M.

2004-01-01

We propose and test a new method for pricing American options in a high-dimensional setting.The method is centred around the approximation of the associated complementarity problem on an irregular grid.We approximate the partial differential operator on this grid by appealing to the SDE

Reinforcement learning on slow features of high-dimensional input streams.

Directory of Open Access Journals (Sweden)

Robert Legenstein

Full Text Available Humans and animals are able to learn complex behaviors based on a massive stream of sensory information from different modalities. Early animal studies have identified learning mechanisms that are based on reward and punishment such that animals tend to avoid actions that lead to punishment whereas rewarded actions are reinforced. However, most algorithms for reward-based learning are only applicable if the dimensionality of the state-space is sufficiently small or its structure is sufficiently simple. Therefore, the question arises how the problem of learning on high-dimensional data is solved in the brain. In this article, we propose a biologically plausible generic two-stage learning system that can directly be applied to raw high-dimensional input streams. The system is composed of a hierarchical slow feature analysis (SFA network for preprocessing and a simple neural network on top that is trained based on rewards. We demonstrate by computer simulations that this generic architecture is able to learn quite demanding reinforcement learning tasks on high-dimensional visual input streams in a time that is comparable to the time needed when an explicit highly informative low-dimensional state-space representation is given instead of the high-dimensional visual input. The learning speed of the proposed architecture in a task similar to the Morris water maze task is comparable to that found in experimental studies with rats. This study thus supports the hypothesis that slowness learning is one important unsupervised learning principle utilized in the brain to form efficient state representations for behavioral learning.

Data analysis in high-dimensional sparse spaces

DEFF Research Database (Denmark)

Clemmensen, Line Katrine Harder

classification techniques for high-dimensional problems are presented: Sparse discriminant analysis, sparse mixture discriminant analysis and orthogonality constrained support vector machines. The first two introduces sparseness to the well known linear and mixture discriminant analysis and thereby provide low...... are applied to classifications of fish species, ear canal impressions used in the hearing aid industry, microbiological fungi species, and various cancerous tissues and healthy tissues. In addition, novel applications of sparse regressions (also called the elastic net) to the medical, concrete, and food...

Transport synthetic acceleration scheme for multi-dimensional neutron transport problems

Energy Technology Data Exchange (ETDEWEB)

Modak, R S; Kumar, Vinod; Menon, S V.G. [Theoretical Physics Div., Bhabha Atomic Research Centre, Mumbai (India); Gupta, Anurag [Reactor Physics Design Div., Bhabha Atomic Research Centre, Mumbai (India)

2005-09-15

The numerical solution of linear multi-energy-group neutron transport equation is required in several analyses in nuclear reactor physics and allied areas. Computer codes based on the discrete ordinates (Sn) method are commonly used for this purpose. These codes solve external source problem and K-eigenvalue problem. The overall solution technique involves solution of source problem in each energy group as intermediate procedures. Such a single-group source problem is solved by the so-called Source Iteration (SI) method. As is well-known, the SI-method converges very slowly for optically thick and highly scattering regions, leading to large CPU times. Over last three decades, many schemes have been tried to accelerate the SI; the most prominent being the Diffusion Synthetic Acceleration (DSA) scheme. The DSA scheme, however, often fails and is also rather difficult to implement. In view of this, in 1997, Ramone and others have developed a new acceleration scheme called Transport Synthetic Acceleration (TSA) which is much more robust and easy to implement. This scheme has been recently incorporated in 2-D and 3-D in-house codes at BARC. This report presents studies on the utility of TSA scheme for fairly general test problems involving many energy groups and anisotropic scattering. The scheme is found to be useful for problems in Cartesian as well as Cylindrical geometry. (author)

Transport synthetic acceleration scheme for multi-dimensional neutron transport problems

International Nuclear Information System (INIS)

Modak, R.S.; Vinod Kumar; Menon, S.V.G.; Gupta, Anurag

2005-09-01

The numerical solution of linear multi-energy-group neutron transport equation is required in several analyses in nuclear reactor physics and allied areas. Computer codes based on the discrete ordinates (Sn) method are commonly used for this purpose. These codes solve external source problem and K-eigenvalue problem. The overall solution technique involves solution of source problem in each energy group as intermediate procedures. Such a single-group source problem is solved by the so-called Source Iteration (SI) method. As is well-known, the SI-method converges very slowly for optically thick and highly scattering regions, leading to large CPU times. Over last three decades, many schemes have been tried to accelerate the SI; the most prominent being the Diffusion Synthetic Acceleration (DSA) scheme. The DSA scheme, however, often fails and is also rather difficult to implement. In view of this, in 1997, Ramone and others have developed a new acceleration scheme called Transport Synthetic Acceleration (TSA) which is much more robust and easy to implement. This scheme has been recently incorporated in 2-D and 3-D in-house codes at BARC. This report presents studies on the utility of TSA scheme for fairly general test problems involving many energy groups and anisotropic scattering. The scheme is found to be useful for problems in Cartesian as well as Cylindrical geometry. (author)

One-dimensional computational modeling on nuclear reactor problems

International Nuclear Information System (INIS)

Alves Filho, Hermes; Baptista, Josue Costa; Trindade, Luiz Fernando Santos; Heringer, Juan Diego dos Santos

2013-01-01

In this article, we present a computational modeling, which gives us a dynamic view of some applications of Nuclear Engineering, specifically in the power distribution and the effective multiplication factor (keff) calculations. We work with one-dimensional problems of deterministic neutron transport theory, with the linearized Boltzmann equation in the discrete ordinates (SN) formulation, independent of time, with isotropic scattering and then built a software (Simulator) for modeling computational problems used in a typical calculations. The program used in the implementation of the simulator was Matlab, version 7.0. (author)

Two-Dimensional Key Table-Based Group Key Distribution in Advanced Metering Infrastructure

Directory of Open Access Journals (Sweden)

Woong Go

2014-01-01

Full Text Available A smart grid provides two-way communication by using the information and communication technology. In order to establish two-way communication, the advanced metering infrastructure (AMI is used in the smart grid as the core infrastructure. This infrastructure consists of smart meters, data collection units, maintenance data management systems, and so on. However, potential security problems of the AMI increase owing to the application of the public network. This is because the transmitted information is electricity consumption data for charging. Thus, in order to establish a secure connection to transmit electricity consumption data, encryption is necessary, for which key distribution is required. Further, a group key is more efficient than a pairwise key in the hierarchical structure of the AMI. Therefore, we propose a group key distribution scheme using a two-dimensional key table through the analysis result of the sensor network group key distribution scheme. The proposed scheme has three phases: group key predistribution, selection of group key generation element, and generation of group key.

Quantum trajectories in complex space: One-dimensional stationary scattering problems

International Nuclear Information System (INIS)

Chou, C.-C.; Wyatt, Robert E.

2008-01-01

One-dimensional time-independent scattering problems are investigated in the framework of the quantum Hamilton-Jacobi formalism. The equation for the local approximate quantum trajectories near the stagnation point of the quantum momentum function is derived, and the first derivative of the quantum momentum function is related to the local structure of quantum trajectories. Exact complex quantum trajectories are determined for two examples by numerically integrating the equations of motion. For the soft potential step, some particles penetrate into the nonclassical region, and then turn back to the reflection region. For the barrier scattering problem, quantum trajectories may spiral into the attractors or from the repellers in the barrier region. Although the classical potentials extended to complex space show different pole structures for each problem, the quantum potentials present the same second-order pole structure in the reflection region. This paper not only analyzes complex quantum trajectories and the total potentials for these examples but also demonstrates general properties and similar structures of the complex quantum trajectories and the quantum potentials for one-dimensional time-independent scattering problems

Application of space-angle synthesis to two-dimensional neutral-particle transport problems of weapon physics

International Nuclear Information System (INIS)

Roberds, R.M.

1975-01-01

A space-angle synthesis (SAS) method has been developed for treating the steady-state, two-dimensional transport of neutrons and gamma rays from a point source of simulated nuclear weapon radiation in air. The method was validated by applying it to the problem of neutron transport from a point source in air over a ground interface, and then comparing the results to those obtained by DOT, a state-of-the-art, discrete-ordinates code. In the SAS method, the energy dependence of the Boltzmann transport equation was treated in the standard multigroup manner. The angular dependence was treated by expanding the flux in specially tailored trial functions and applying the method of weighted residuals which analytically integrated the transport equation over all angles. The weighted-residual approach was analogous to the conventional spherical-harmonics (P/sub N/) method with the exception that the tailored expansion allowed for more rapid convergence than a spherical-harmonics P 1 expansion and resulted in a greater degree of accuracy. The trial functions used in the expansion were odd and even combinations of selected trial solutions, the trial solutions being shaped ellipsoids which approximated the angular distribution of the neutron flux in one-dimensional space. The parameters which described the shape of the ellipsoid varied with energy group and the spatial medium, only, and were obtained from a one-dimensional discrete-ordinates calculation. Thus, approximate transport solutions were made available for all two-dimensional problems of a certain class by using tabulated parameters obtained from a single, one-dimensional calculation

Classical Lie Point Symmetry Analysis of a Steady Nonlinear One-Dimensional Fin Problem

Directory of Open Access Journals (Sweden)

R. J. Moitsheki

2012-01-01

Full Text Available We consider the one-dimensional steady fin problem with the Dirichlet boundary condition at one end and the Neumann boundary condition at the other. Both the thermal conductivity and the heat transfer coefficient are given as arbitrary functions of temperature. We perform preliminary group classification to determine forms of the arbitrary functions appearing in the considered equation for which the principal Lie algebra is extended. Some invariant solutions are constructed. The effects of thermogeometric fin parameter and the exponent on temperature are studied. Also, the fin efficiency is analyzed.

High-Dimensional Intrinsic Interpolation Using Gaussian Process Regression and Diffusion Maps

International Nuclear Information System (INIS)

Thimmisetty, Charanraj A.; Ghanem, Roger G.; White, Joshua A.; Chen, Xiao

2017-01-01

This article considers the challenging task of estimating geologic properties of interest using a suite of proxy measurements. The current work recast this task as a manifold learning problem. In this process, this article introduces a novel regression procedure for intrinsic variables constrained onto a manifold embedded in an ambient space. The procedure is meant to sharpen high-dimensional interpolation by inferring non-linear correlations from the data being interpolated. The proposed approach augments manifold learning procedures with a Gaussian process regression. It first identifies, using diffusion maps, a low-dimensional manifold embedded in an ambient high-dimensional space associated with the data. It relies on the diffusion distance associated with this construction to define a distance function with which the data model is equipped. This distance metric function is then used to compute the correlation structure of a Gaussian process that describes the statistical dependence of quantities of interest in the high-dimensional ambient space. The proposed method is applicable to arbitrarily high-dimensional data sets. Here, it is applied to subsurface characterization using a suite of well log measurements. The predictions obtained in original, principal component, and diffusion space are compared using both qualitative and quantitative metrics. Considerable improvement in the prediction of the geological structural properties is observed with the proposed method.

The scalar curvature problem on the four dimensional half sphere

CERN Document Server

Ben-Ayed, M; El-Mehdi, K

2003-01-01

In this paper, we consider the problem of prescribing the scalar curvature under minimal boundary conditions on the standard four dimensional half sphere. We provide an Euler-Hopf type criterion for a given function to be a scalar curvature for some metric conformal to the standard one. Our proof involves the study of critical points at infinity of the associated variational problem.

Recursive solutions for multi-group neutron kinetics diffusion equations in homogeneous three-dimensional rectangular domains with time dependent perturbations

Energy Technology Data Exchange (ETDEWEB)

Petersen, Claudio Z. [Universidade Federal de Pelotas, Capao do Leao (Brazil). Programa de Pos Graduacao em Modelagem Matematica; Bodmann, Bardo E.J.; Vilhena, Marco T. [Universidade Federal do Rio Grande do Sul, Porto Alegre, RS (Brazil). Programa de Pos-graduacao em Engenharia Mecanica; Barros, Ricardo C. [Universidade do Estado do Rio de Janeiro, Nova Friburgo, RJ (Brazil). Inst. Politecnico

2014-12-15

In the present work we solve in analytical representation the three dimensional neutron kinetic diffusion problem in rectangular Cartesian geometry for homogeneous and bounded domains for any number of energy groups and precursor concentrations. The solution in analytical representation is constructed using a hierarchical procedure, i.e. the original problem is reduced to a problem previously solved by the authors making use of a combination of the spectral method and a recursive decomposition approach. Time dependent absorption cross sections of the thermal energy group are considered with step, ramp and Chebyshev polynomial variations. For these three cases, we present numerical results and discuss convergence properties and compare our results to those available in the literature.

HEXAGA-II. A two-dimensional multi-group neutron diffusion programme for a uniform triangular mesh with arbitrary group scattering for the IBM/370-168 computer

International Nuclear Information System (INIS)

Woznicki, Z.

1976-05-01

This report presents the AGA two-sweep iterative methods belonging to the family of factorization techniques in their practical application in the HEXAGA-II two-dimensional programme to obtain the numerical solution to the multi-group, time-independent, (real and/or adjoint) neutron diffusion equations for a fine uniform triangular mesh. An arbitrary group scattering model is permitted. The report written for the users provides the description of input and output. The use of HEXAGA-II is illustrated by two sample reactor problems. (orig.) [de

Inhomogeneous Quantum Invariance Group of Multi-Dimensional Multi-parameter Deformed Boson Algebra

International Nuclear Information System (INIS)

Altintas Azmi Ali; Arik Metin; Arikan Ali Serdar; Dil Emre

2012-01-01

We investigate the inhomogeneous invariance quantum group of the d-dimensional d-parameter deformed boson algebra. It is found that the homogeneous part of this quantum group is given by the d-parameter deformed general linear group. We construct the R-matrix which collects all information about the non-commuting structure of the quantum group for the two-dimensional case. (general)

Multivariate sparse group lasso for the multivariate multiple linear regression with an arbitrary group structure.

Science.gov (United States)

Li, Yanming; Nan, Bin; Zhu, Ji

2015-06-01

We propose a multivariate sparse group lasso variable selection and estimation method for data with high-dimensional predictors as well as high-dimensional response variables. The method is carried out through a penalized multivariate multiple linear regression model with an arbitrary group structure for the regression coefficient matrix. It suits many biology studies well in detecting associations between multiple traits and multiple predictors, with each trait and each predictor embedded in some biological functional groups such as genes, pathways or brain regions. The method is able to effectively remove unimportant groups as well as unimportant individual coefficients within important groups, particularly for large p small n problems, and is flexible in handling various complex group structures such as overlapping or nested or multilevel hierarchical structures. The method is evaluated through extensive simulations with comparisons to the conventional lasso and group lasso methods, and is applied to an eQTL association study. © 2015, The International Biometric Society.

Pro-Lie Groups: A Survey with Open Problems

Directory of Open Access Journals (Sweden)

Karl H. Hofmann

2015-07-01

Full Text Available A topological group is called a pro-Lie group if it is isomorphic to a closed subgroup of a product of finite-dimensional real Lie groups. This class of groups is closed under the formation of arbitrary products and closed subgroups and forms a complete category. It includes each finite-dimensional Lie group, each locally-compact group that has a compact quotient group modulo its identity component and, thus, in particular, each compact and each connected locally-compact group; it also includes all locally-compact Abelian groups. This paper provides an overview of the structure theory and the Lie theory of pro-Lie groups, including results more recent than those in the authors’ reference book on pro-Lie groups. Significantly, it also includes a review of the recent insight that weakly-complete unital algebras provide a natural habitat for both pro-Lie algebras and pro-Lie groups, indeed for the exponential function that links the two. (A topological vector space is weakly complete if it is isomorphic to a power RX of an arbitrary set of copies of R. This class of real vector spaces is at the basis of the Lie theory of pro-Lie groups. The article also lists 12 open questions connected to pro-Lie groups.

Dynamics of infinite-dimensional groups the Ramsey-Dvoretzky-Milman phenomenon

CERN Document Server

Pestov, Vladimir

2006-01-01

The "infinite-dimensional groups" in the title refer to unitary groups of Hilbert spaces, the infinite symmetric group, groups of homeomorphisms of manifolds, groups of transformations of measure spaces, etc. The book presents an approach to the study of such groups based on ideas from geometric functional analysis and from exploring the interplay between dynamical properties of those groups, combinatorial Ramsey-type theorems, and the phenomenon of concentration of measure. The dynamics of infinite-dimensional groups is very much unlike that of locally compact groups. For instance, every locally compact group acts freely on a suitable compact space (Veech). By contrast, a 1983 result by Gromov and Milman states that whenever the unitary group of a separable Hilbert space continuously acts on a compact space, it has a common fixed point. In the book, this new fast-growing theory is built strictly from well-understood examples up. The book has no close counterpart and is based on recent research articles. At t...

Efficient and accurate nearest neighbor and closest pair search in high-dimensional space

KAUST Repository

Tao, Yufei

2010-07-01

Nearest Neighbor (NN) search in high-dimensional space is an important problem in many applications. From the database perspective, a good solution needs to have two properties: (i) it can be easily incorporated in a relational database, and (ii) its query cost should increase sublinearly with the dataset size, regardless of the data and query distributions. Locality-Sensitive Hashing (LSH) is a well-known methodology fulfilling both requirements, but its current implementations either incur expensive space and query cost, or abandon its theoretical guarantee on the quality of query results. Motivated by this, we improve LSH by proposing an access method called the Locality-Sensitive B-tree (LSB-tree) to enable fast, accurate, high-dimensional NN search in relational databases. The combination of several LSB-trees forms a LSB-forest that has strong quality guarantees, but improves dramatically the efficiency of the previous LSH implementation having the same guarantees. In practice, the LSB-tree itself is also an effective index which consumes linear space, supports efficient updates, and provides accurate query results. In our experiments, the LSB-tree was faster than: (i) iDistance (a famous technique for exact NN search) by two orders ofmagnitude, and (ii) MedRank (a recent approximate method with nontrivial quality guarantees) by one order of magnitude, and meanwhile returned much better results. As a second step, we extend our LSB technique to solve another classic problem, called Closest Pair (CP) search, in high-dimensional space. The long-term challenge for this problem has been to achieve subquadratic running time at very high dimensionalities, which fails most of the existing solutions. We show that, using a LSB-forest, CP search can be accomplished in (worst-case) time significantly lower than the quadratic complexity, yet still ensuring very good quality. In practice, accurate answers can be found using just two LSB-trees, thus giving a substantial

Non-intrusive low-rank separated approximation of high-dimensional stochastic models

KAUST Repository

Doostan, Alireza; Validi, AbdoulAhad; Iaccarino, Gianluca

2013-01-01

This work proposes a sampling-based (non-intrusive) approach within the context of low-. rank separated representations to tackle the issue of curse-of-dimensionality associated with the solution of models, e.g., PDEs/ODEs, with high-dimensional random inputs. Under some conditions discussed in details, the number of random realizations of the solution, required for a successful approximation, grows linearly with respect to the number of random inputs. The construction of the separated representation is achieved via a regularized alternating least-squares regression, together with an error indicator to estimate model parameters. The computational complexity of such a construction is quadratic in the number of random inputs. The performance of the method is investigated through its application to three numerical examples including two ODE problems with high-dimensional random inputs. © 2013 Elsevier B.V.

Non-intrusive low-rank separated approximation of high-dimensional stochastic models

KAUST Repository

Doostan, Alireza

2013-08-01

This work proposes a sampling-based (non-intrusive) approach within the context of low-. rank separated representations to tackle the issue of curse-of-dimensionality associated with the solution of models, e.g., PDEs/ODEs, with high-dimensional random inputs. Under some conditions discussed in details, the number of random realizations of the solution, required for a successful approximation, grows linearly with respect to the number of random inputs. The construction of the separated representation is achieved via a regularized alternating least-squares regression, together with an error indicator to estimate model parameters. The computational complexity of such a construction is quadratic in the number of random inputs. The performance of the method is investigated through its application to three numerical examples including two ODE problems with high-dimensional random inputs. © 2013 Elsevier B.V.

BASHAN: A few-group three-dimensional diffusion code with burnup and fuel management features

International Nuclear Information System (INIS)

Pearce, D.F.

1970-12-01

The diffusion equation for a two or three-dimensional, two-group or multi-group downscatter problem is solved by conventional finite difference techniques. An x-y-z geometry is assumed with an 'in-channel' mesh point representation. Options are available which allow representation of a soluble poison dispersed throughout the reactor, and also absorber rods in specified channels. The power distribution and multiplication factor k eff are calculated and a point rating map is used to advance the irradiation at each mesh point by a specified time-step so that burnup is followed. Fuel changes may be made so that radial shuffling and axial shuffling fuel management schemes can be studies. The code has been written in FORTRAN S2 for an IBM 7030 (STRETCH) computer which, with a fast store of 80,000 locations, allows problems of up to 15,000 mesh points to be dealt with. Conversion to FORTRAN IV for IBM 360 has now been completed. (author)

HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.

Science.gov (United States)

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2011-01-01

The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied.

Topology of high-dimensional manifolds

Energy Technology Data Exchange (ETDEWEB)

Farrell, F T [State University of New York, Binghamton (United States); Goettshe, L [Abdus Salam ICTP, Trieste (Italy); Lueck, W [Westfaelische Wilhelms-Universitaet Muenster, Muenster (Germany)

2002-08-15

The School on High-Dimensional Manifold Topology took place at the Abdus Salam ICTP, Trieste from 21 May 2001 to 8 June 2001. The focus of the school was on the classification of manifolds and related aspects of K-theory, geometry, and operator theory. The topics covered included: surgery theory, algebraic K- and L-theory, controlled topology, homology manifolds, exotic aspherical manifolds, homeomorphism and diffeomorphism groups, and scalar curvature. The school consisted of 2 weeks of lecture courses and one week of conference. Thwo-part lecture notes volume contains the notes of most of the lecture courses.

A comparison of two efficient nonlinear heat conduction methodologies using a two-dimensional time-dependent benchmark problem

International Nuclear Information System (INIS)

Wilson, G.L.; Rydin, R.A.; Orivuori, S.

1988-01-01

Two highly efficient nonlinear time-dependent heat conduction methodologies, the nonlinear time-dependent nodal integral technique (NTDNT) and IVOHEAT are compared using one- and two-dimensional time-dependent benchmark problems. The NTDNT is completely based on newly developed time-dependent nodal integral methods, whereas IVOHEAT is based on finite elements in space and Crank-Nicholson finite differences in time. IVOHEAT contains the geometric flexibility of the finite element approach, whereas the nodal integral method is constrained at present to Cartesian geometry. For test problems where both methods are equally applicable, the nodal integral method is approximately six times more efficient per dimension than IVOHEAT when a comparable overall accuracy is chosen. This translates to a factor of 200 for a three-dimensional problem having relatively homogeneous regions, and to a smaller advantage as the degree of heterogeneity increases

Problems associated with dimensional analysis of electroencephalogram data

Energy Technology Data Exchange (ETDEWEB)

Layne, S.; Mayer-Kress, G.; Holzfuss, J.

1985-01-01

The goal was to evaluate anesthetic depth for a series of 5 to 10 patients by dimensional analysis. It has been very difficult to obtain clean EEG records from the operating room. Noise is prominent due to electrocautery and to movement of the patient's head by operating room personnel. In addition, specialized EEG equipment must be used to reduce noise and to accommodate limited space in the room. This report discusses problems associated with dimensional analysis of the EEG. We choose one EEG record from a single patient, in order to study the method but not to draw general conclusions. For simplicity, we consider only two states: awake but quiet, and medium anesthesia. 14 refs., 8 figs., 1 tab.

Orbits of the n-dimensional Kepler-Coulomb problem and universality of the Kepler laws

International Nuclear Information System (INIS)

Oender, M; Vercin, A

2006-01-01

In the standard classical mechanics textbooks used at undergraduate and graduate levels, no attention is paid to the dimensional aspects of the Kepler-Coulomb problem. We have shown that the orbits of the n-dimensional classical Kepler-Coulomb problem are the usual conic sections in a fixed two-dimensional subspace and the Kepler laws with their well-known forms are valid independent of dimension. The basic characteristics of motion in a central force field are also established in an arbitrary dimension. The approach followed is easily accessible to late undergraduate and recent graduate students

An iterative bidirectional heuristic placement algorithm for solving the two-dimensional knapsack packing problem

Science.gov (United States)

Shiangjen, Kanokwatt; Chaijaruwanich, Jeerayut; Srisujjalertwaja, Wijak; Unachak, Prakarn; Somhom, Samerkae

2018-02-01

This article presents an efficient heuristic placement algorithm, namely, a bidirectional heuristic placement, for solving the two-dimensional rectangular knapsack packing problem. The heuristic demonstrates ways to maximize space utilization by fitting the appropriate rectangle from both sides of the wall of the current residual space layer by layer. The iterative local search along with a shift strategy is developed and applied to the heuristic to balance the exploitation and exploration tasks in the solution space without the tuning of any parameters. The experimental results on many scales of packing problems show that this approach can produce high-quality solutions for most of the benchmark datasets, especially for large-scale problems, within a reasonable duration of computational time.

Decision problems for groups and semigroups

International Nuclear Information System (INIS)

Adian, S I; Durnev, V G

2000-01-01

The paper presents a detailed survey of results concerning the main decision problems of group theory and semigroup theory, including the word problem, the isomorphism problem, recognition problems, and other algorithmic questions related to them. The well-known theorems of Markov-Post, P.S. Novikov, Adian-Rabin, Higman, Magnus, and Lyndon are given with complete proofs. As a rule, the proofs presented in this survey are substantially simpler than those given in the original papers. For the sake of completeness, we first prove the insolubility of the halting problem for Turing machines, on which the insolubility of the word problem for semigroups is based. Specific attention is also paid to the simplest examples of semigroups with insoluble word problem. We give a detailed proof of the significant result of Lyndon that, in the class of groups presented by a system of defining relations for which the maximum mutual overlapping of any two relators is strictly less than one fifth of their lengths, the word problem is soluble, while insoluble word problems can occur when non-strict inequality is allowed. A proof of the corresponding result for finitely presented semigroups is also given, when the corresponding fraction is one half

Wigner functions from the two-dimensional wavelet group.

Science.gov (United States)

Ali, S T; Krasowska, A E; Murenzi, R

2000-12-01

Following a general procedure developed previously [Ann. Henri Poincaré 1, 685 (2000)], here we construct Wigner functions on a phase space related to the similitude group in two dimensions. Since the group space in this case is topologically homeomorphic to the phase space in question, the Wigner functions so constructed may also be considered as being functions on the group space itself. Previously the similitude group was used to construct wavelets for two-dimensional image analysis; we discuss here the connection between the wavelet transform and the Wigner function.

Overcoming the sign problem in 1-dimensional QCD by new integration rules with polynomial exactness

Energy Technology Data Exchange (ETDEWEB)

Ammon, A. [IVU-Traffic Technologies AG, Berlin (Germany); Hartung, T. [King' s College London (United Kingdom). Dept. of Mathematics; Jansen, K.; Volmer, J. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Leoevey, H. [Humboldt-Universitaet, Berlin (Germany). Inst. fuer Mathematik

2016-08-15

In this paper we describe a new integration method for the groups U(N) and SU(N), for which we verified numerically that it is polynomially exact for N≤3. The method is applied to the example of 1-dimensional QCD with a chemical potential. We explore, in particular, regions of the parameter space in which the sign problem appears due the presence of the chemical potential. While Markov Chain Monte Carlo fails in this region, our new integration method still provides results for the chiral condensate on arbitrary precision, demonstrating clearly that it overcomes the sign problem. Furthermore, we demonstrate that our new method leads to orders of magnitude reduced errors also in other regions of parameter space.

Impact of high-frequency pumping on anomalous finite-size effects in three-dimensional topological insulators

Science.gov (United States)

Pervishko, Anastasiia A.; Yudin, Dmitry; Shelykh, Ivan A.

2018-02-01

Lowering of the thickness of a thin-film three-dimensional topological insulator down to a few nanometers results in the gap opening in the spectrum of topologically protected two-dimensional surface states. This phenomenon, which is referred to as the anomalous finite-size effect, originates from hybridization between the states propagating along the opposite boundaries. In this work, we consider a bismuth-based topological insulator and show how the coupling to an intense high-frequency linearly polarized pumping can further be used to manipulate the value of a gap. We address this effect within recently proposed Brillouin-Wigner perturbation theory that allows us to map a time-dependent problem into a stationary one. Our analysis reveals that both the gap and the components of the group velocity of the surface states can be tuned in a controllable fashion by adjusting the intensity of the driving field within an experimentally accessible range and demonstrate the effect of light-induced band inversion in the spectrum of the surface states for high enough values of the pump.

Canonical Groups for Quantization on the Two-Dimensional Sphere and One-Dimensional Complex Projective Space

International Nuclear Information System (INIS)

Sumadi A H A; H, Zainuddin

2014-01-01

Using Isham's group-theoretic quantization scheme, we construct the canonical groups of the systems on the two-dimensional sphere and one-dimensional complex projective space, which are homeomorphic. In the first case, we take SO(3) as the natural canonical Lie group of rotations of the two-sphere and find all the possible Hamiltonian vector fields, and followed by verifying the commutator and Poisson bracket algebra correspondences with the Lie algebra of the group. In the second case, the same technique is resumed to define the Lie group, in this case SU (2), of CP'.We show that one can simply use a coordinate transformation from S 2 to CP 1 to obtain all the Hamiltonian vector fields of CP 1 . We explicitly show that the Lie algebra structures of both canonical groups are locally homomorphic. On the other hand, globally their corresponding canonical groups are acting on different geometries, the latter of which is almost complex. Thus the canonical group for CP 1 is the double-covering group of SO(3), namely SU(2). The relevance of the proposed formalism is to understand the idea of CP 1 as a space of where the qubit lives which is known as a Bloch sphere

Variance inflation in high dimensional Support Vector Machines

DEFF Research Database (Denmark)

Abrahamsen, Trine Julie; Hansen, Lars Kai

2013-01-01

Many important machine learning models, supervised and unsupervised, are based on simple Euclidean distance or orthogonal projection in a high dimensional feature space. When estimating such models from small training sets we face the problem that the span of the training data set input vectors...... the case of Support Vector Machines (SVMS) and we propose a non-parametric scheme to restore proper generalizability. We illustrate the algorithm and its ability to restore performance on a wide range of benchmark data sets....... follow a different probability law with less variance. While the problem and basic means to reconstruct and deflate are well understood in unsupervised learning, the case of supervised learning is less well understood. We here investigate the effect of variance inflation in supervised learning including...

The two-dimensional cutting stock problem within the roller blind production process

NARCIS (Netherlands)

E.R. de Gelder; A.P.M. Wagelmans (Albert)

2007-01-01

textabstractIn this paper we consider a two-dimensional cutting stock problem encountered at a large manufacturer of window covering products. The problem occurs in the production process of made-to-measure roller blinds. We develop a solution method that takes into account the characteristics of

Efficient and accurate nearest neighbor and closest pair search in high-dimensional space

KAUST Repository

Tao, Yufei; Yi, Ke; Sheng, Cheng; Kalnis, Panos

2010-01-01

Nearest Neighbor (NN) search in high-dimensional space is an important problem in many applications. From the database perspective, a good solution needs to have two properties: (i) it can be easily incorporated in a relational database, and (ii

One-, two- and three-dimensional transport codes using multi-group double-differential form cross sections

International Nuclear Information System (INIS)

Mori, Takamasa; Nakagawa, Masayuki; Sasaki, Makoto.

1988-11-01

We have developed a group of computer codes to realize the accurate transport calculation by using the multi-group double-differential form cross section. This type of cross section can correctly take account of the energy-angle correlated reaction kinematics. Accordingly, the transport phenomena in materials with highly anisotropic scattering are accurately calculated by using this cross section. They include the following four codes or code systems: PROF-DD : a code system to generate the multi-group double-differential form cross section library by processing basic nuclear data file compiled in the ENDF / B-IV or -V format, ANISN-DD : a one-dimensional transport code based on the discrete ordinate method, DOT-DD : a two-dimensional transport code based on the discrete ordinate method, MORSE-DD : a three-dimensional transport code based on the Monte Carlo method. In addition to these codes, several auxiliary codes have been developed to process calculated results. This report describes the calculation algorithm employed in these codes and how to use them. (author)

AN EFFECTIVE MULTI-CLUSTERING ANONYMIZATION APPROACH USING DISCRETE COMPONENT TASK FOR NON-BINARY HIGH DIMENSIONAL DATA SPACES

Directory of Open Access Journals (Sweden)

L.V. Arun Shalin

2016-01-01

Full Text Available Clustering is a process of grouping elements together, designed in such a way that the elements assigned to similar data points in a cluster are more comparable to each other than the remaining data points in a cluster. During clustering certain difficulties related when dealing with high dimensional data are ubiquitous and abundant. Works concentrated using anonymization method for high dimensional data spaces failed to address the problem related to dimensionality reduction during the inclusion of non-binary databases. In this work we study methods for dimensionality reduction for non-binary database. By analyzing the behavior of dimensionality reduction for non-binary database, results in performance improvement with the help of tag based feature. An effective multi-clustering anonymization approach called Discrete Component Task Specific Multi-Clustering (DCTSM is presented for dimensionality reduction on non-binary database. To start with we present the analysis of attribute in the non-binary database and cluster projection identifies the sparseness degree of dimensions. Additionally with the quantum distribution on multi-cluster dimension, the solution for relevancy of attribute and redundancy on non-binary data spaces is provided resulting in performance improvement on the basis of tag based feature. Multi-clustering tag based feature reduction extracts individual features and are correspondingly replaced by the equivalent feature clusters (i.e. tag clusters. During training, the DCTSM approach uses multi-clusters instead of individual tag features and then during decoding individual features is replaced by corresponding multi-clusters. To measure the effectiveness of the method, experiments are conducted on existing anonymization method for high dimensional data spaces and compared with the DCTSM approach using Statlog German Credit Data Set. Improved tag feature extraction and minimum error rate compared to conventional anonymization

Class prediction for high-dimensional class-imbalanced data

Directory of Open Access Journals (Sweden)

Lusa Lara

2010-10-01

Full Text Available Abstract Background The goal of class prediction studies is to develop rules to accurately predict the class membership of new samples. The rules are derived using the values of the variables available for each subject: the main characteristic of high-dimensional data is that the number of variables greatly exceeds the number of samples. Frequently the classifiers are developed using class-imbalanced data, i.e., data sets where the number of samples in each class is not equal. Standard classification methods used on class-imbalanced data often produce classifiers that do not accurately predict the minority class; the prediction is biased towards the majority class. In this paper we investigate if the high-dimensionality poses additional challenges when dealing with class-imbalanced prediction. We evaluate the performance of six types of classifiers on class-imbalanced data, using simulated data and a publicly available data set from a breast cancer gene-expression microarray study. We also investigate the effectiveness of some strategies that are available to overcome the effect of class imbalance. Results Our results show that the evaluated classifiers are highly sensitive to class imbalance and that variable selection introduces an additional bias towards classification into the majority class. Most new samples are assigned to the majority class from the training set, unless the difference between the classes is very large. As a consequence, the class-specific predictive accuracies differ considerably. When the class imbalance is not too severe, down-sizing and asymmetric bagging embedding variable selection work well, while over-sampling does not. Variable normalization can further worsen the performance of the classifiers. Conclusions Our results show that matching the prevalence of the classes in training and test set does not guarantee good performance of classifiers and that the problems related to classification with class

Development of a coarse mesh code for the solution of two group static diffusion problems

International Nuclear Information System (INIS)

Barros, R.C. de.

1985-01-01

This new coarse mesh code designed for the solution of 2 and 3 dimensional static diffusion problems, is based on an alternating direction method which consists in the solution of one dimensional problem along each coordinate direction with leakage terms for the remaining directions estimated from previous interactions. Four versions of this code have been developed: AD21 - 2D - 1/4, AD21 - 2D - 4/4, AD21 - 3D - 1/4 and AD21 - 3D - 4/4; these versions have been designed for 2 and 3 dimensional problems with or without 1/4 symmetry. (Author) [pt

Manifold learning to interpret JET high-dimensional operational space

International Nuclear Information System (INIS)

Cannas, B; Fanni, A; Pau, A; Sias, G; Murari, A

2013-01-01

In this paper, the problem of visualization and exploration of JET high-dimensional operational space is considered. The data come from plasma discharges selected from JET campaigns from C15 (year 2005) up to C27 (year 2009). The aim is to learn the possible manifold structure embedded in the data and to create some representations of the plasma parameters on low-dimensional maps, which are understandable and which preserve the essential properties owned by the original data. A crucial issue for the design of such mappings is the quality of the dataset. This paper reports the details of the criteria used to properly select suitable signals downloaded from JET databases in order to obtain a dataset of reliable observations. Moreover, a statistical analysis is performed to recognize the presence of outliers. Finally data reduction, based on clustering methods, is performed to select a limited and representative number of samples for the operational space mapping. The high-dimensional operational space of JET is mapped using a widely used manifold learning method, the self-organizing maps. The results are compared with other data visualization methods. The obtained maps can be used to identify characteristic regions of the plasma scenario, allowing to discriminate between regions with high risk of disruption and those with low risk of disruption. (paper)

A Shell Multi-dimensional Hierarchical Cubing Approach for High-Dimensional Cube

Science.gov (United States)

Zou, Shuzhi; Zhao, Li; Hu, Kongfa

The pre-computation of data cubes is critical for improving the response time of OLAP systems and accelerating data mining tasks in large data warehouses. However, as the sizes of data warehouses grow, the time it takes to perform this pre-computation becomes a significant performance bottleneck. In a high dimensional data warehouse, it might not be practical to build all these cuboids and their indices. In this paper, we propose a shell multi-dimensional hierarchical cubing algorithm, based on an extension of the previous minimal cubing approach. This method partitions the high dimensional data cube into low multi-dimensional hierarchical cube. Experimental results show that the proposed method is significantly more efficient than other existing cubing methods.

About the problem of generating three-dimensional pseudo-random points.

Science.gov (United States)

Carpintero, D. D.

The author demonstrates that a popular pseudo-random number generator is not adequate in some circumstances to generate n-dimensional random points, n > 2. This problem is particularly noxious when direction cosines are generated. He proposes several soultions, among them a good generator that satisfies all statistical criteria.

Three-Dimensional Electromagnetic High Frequency Axisymmetric Cavity Scars.

Energy Technology Data Exchange (ETDEWEB)

Warne, Larry Kevin; Jorgenson, Roy Eberhardt

2014-10-01

This report examines the localization of high frequency electromagnetic fi elds in three-dimensional axisymmetric cavities along periodic paths between opposing sides of the cavity. The cases where these orbits lead to unstable localized modes are known as scars. This report treats both the case where the opposing sides, or mirrors, are convex, where there are no interior foci, and the case where they are concave, leading to interior foci. The scalar problem is treated fi rst but the approximations required to treat the vector fi eld components are also examined. Particular att ention is focused on the normalization through the electromagnetic energy theorem. Both projections of the fi eld along the scarred orbit as well as point statistics are examined. Statistical comparisons are m ade with a numerical calculation of the scars run with an axisymmetric simulation. This axisymmetric cas eformstheoppositeextreme(wherethetwomirror radii at each end of the ray orbit are equal) from the two -dimensional solution examined previously (where one mirror radius is vastly di ff erent from the other). The enhancement of the fi eldontheorbitaxiscanbe larger here than in the two-dimensional case. Intentionally Left Blank

Solving one-dimensional phase change problems with moving grid method and mesh free radial basis functions

International Nuclear Information System (INIS)

Vrankar, L.; Turk, G.; Runovc, F.; Kansa, E.J.

2006-01-01

Many heat-transfer problems involve a change of phase of material due to solidification or melting. Applications include: the safety studies of nuclear reactors (molten core concrete interaction), the drilling of high ice-content soil, the storage of thermal energy, etc. These problems are often called Stefan's or moving boundary value problems. Mathematically, the interface motion is expressed implicitly in an equation for the conservation of thermal energy at the interface (Stefan's conditions). This introduces a non-linear character to the system which treats each problem somewhat uniquely. The exact solution of phase change problems is limited exclusively to the cases in which e.g. the heat transfer regions are infinite or semi-infinite one dimensional-space. Therefore, solution is obtained either by approximate analytical solution or by numerical methods. Finite-difference methods and finite-element techniques have been used extensively for numerical solution of moving boundary problems. Recently, the numerical methods have focused on the idea of using a mesh-free methodology for the numerical solution of partial differential equations based on radial basis functions. In our case we will study solid-solid transformation. The numerical solutions will be compared with analytical solutions. Actually, in our work we will examine usefulness of radial basis functions (especially multiquadric-MQ) for one-dimensional Stefan's problems. The position of the moving boundary will be simulated by moving grid method. The resultant system of RBF-PDE will be solved by affine space decomposition. (author)

The ADO-nodal method for solving two-dimensional discrete ordinates transport problems

International Nuclear Information System (INIS)

Barichello, L.B.; Picoloto, C.B.; Cunha, R.D. da

2017-01-01

Highlights: • Two-dimensional discrete ordinates neutron transport. • Analytical Discrete Ordinates (ADO) nodal method. • Heterogeneous media fixed source problems. • Local solutions. - Abstract: In this work, recent results on the solution of fixed-source two-dimensional transport problems, in Cartesian geometry, are reported. Homogeneous and heterogeneous media problems are considered in order to incorporate the idea of arbitrary number of domain division into regions (nodes) when applying the ADO method, which is a method of analytical features, to those problems. The ADO-nodal formulation is developed, for each node, following previous work devoted to heterogeneous media problem. Here, however, the numerical procedure is extended to higher number of domain divisions. Such extension leads, in some cases, to the use of an iterative method for solving the general linear system which defines the arbitrary constants of the general solution. In addition to solve alternative heterogeneous media configurations than reported in previous works, the present approach allows comparisons with results provided by other metodologies generated with refined meshes. Numerical results indicate the ADO solution may achieve a prescribed accuracy using coarser meshes than other schemes.

Comment on "Calculations for the one-dimensional soft Coulomb problem and the hard Coulomb limit".

Science.gov (United States)

Carrillo-Bernal, M A; Núñez-Yépez, H N; Salas-Brito, A L; Solis, Didier A

2015-02-01

In the referred paper, the authors use a numerical method for solving ordinary differential equations and a softened Coulomb potential -1/√[x(2)+β(2)] to study the one-dimensional Coulomb problem by approaching the parameter β to zero. We note that even though their numerical findings in the soft potential scenario are correct, their conclusions do not extend to the one-dimensional Coulomb problem (β=0). Their claims regarding the possible existence of an even ground state with energy -∞ with a Dirac-δ eigenfunction and of well-defined parity eigenfunctions in the one-dimensional hydrogen atom are questioned.

High-dimensional covariance estimation with high-dimensional data

CERN Document Server

Pourahmadi, Mohsen

2013-01-01

Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance matrices as well as their applications to the rapidly developing areas lying at the intersection of statistics and mac

Covariance problem in two-dimensional quantum chromodynamics

International Nuclear Information System (INIS)

Hagen, C.R.

1979-01-01

The problem of covariance in the field theory of a two-dimensional non-Abelian gauge field is considered. Since earlier work has shown that covariance fails (in charged sectors) for the Schwinger model, particular attention is given to an evaluation of the role played by the non-Abelian nature of the fields. In contrast to all earlier attempts at this problem, it is found that the potential covariance-breaking terms are identical to those found in the Abelian theory provided that one expresses them in terms of the total (i.e., conserved) current operator. The question of covariance is thus seen to reduce in all cases to a determination as to whether there exists a conserved global charge in the theory. Since the charge operator in the Schwinger model is conserved only in neutral sectors, one is thereby led to infer a probable failure of covariance in the non-Abelian theory, but one which is identical to that found for the U(1) case

Use of endochronic plasticity for multi-dimensional small and large strain problems

International Nuclear Information System (INIS)

Hsieh, B.J.

1980-04-01

The endochronic plasticity theory was proposed in its general form by K.C. Valanis. An intrinsic time measure, which is a property of the material, is used in the theory. the explicit forms of the constitutive equation resemble closely those of the classical theory of linear viscoelasticity. Excellent agreement between the predicted and experimental results is obtained for some metallic and non-metallic materials for one dimensional cases. No reference on the use of endochronic plasticity consistent with the general theory proposed by Valanis is available in the open literature. In this report, the explicit constitutive equations are derived that are consistent with the general theory for one-dimensional (simple tension or compression), two-dimensional plane strain or stress and three-dimensional axisymmetric problems

Group theoretic derivation of angular functions for the non-relativistic A-body problem in the K-harmonics approach

International Nuclear Information System (INIS)

Alcaras, J.A.C.; Ferreira, J.L.

1975-01-01

A derivation of an angular basis for the A-body problem, suitable for the K-harmonics method, is presented. Those angular functions are obtained from homogeneous and harmonic polynomials, which are completely specified by labels associated to eigenvalues of the Casimir invariants of subgroups of the 3(A-1)-dimensional orthogonal group, among them, the total angular momentum and its z-projection [pt

Convergent-beam electron diffraction study of incommensurately modulated crystals. Pt. 2. (3 + 1)-dimensional space groups

International Nuclear Information System (INIS)

Terauchi, Masami; Takahashi, Mariko; Tanaka, Michiyoshi

1994-01-01

The convergent-beam electron diffraction (CBED) method for determining three-dimensional space groups is extended to the determination of the (3 + 1)-dimensional space groups for one-dimensional incommensurately modulated crystals. It is clarified than an approximate dynamical extinction line appears in the CBED discs of the reflections caused by an incommensurate modulation. The extinction enables the space-group determination of the (3 + 1)-dimensional crystals or the one-dimensional incommensurately modulated crystals. An example of the dynamical extinction line is shown using an incommensurately modulated crystal of Sr 2 Nb 2 O 7 . Tables of the dynamical extinction lines appearing in CBED patterns are given for all the (3 + 1)-dimensional space groups of the incommensurately modulated crystal. (orig.)

Resolvent approach for two-dimensional scattering problems. Application to the nonstationary Schroedinger problem and the KPI equation

International Nuclear Information System (INIS)

Boiti, M.; Pempinelli, F.; Pogrebkov, A.K.; Polivanov, M.C.

1993-01-01

The resolvent operator of the linear problem is determined as the full Green function continued in the complex domain in two variables. An analog of the known Hilbert identity is derived. The authors demonstrate the role of this identity in the study of two-dimensional scattering. Considering the nonstationary Schroedinger equation as an example, it is shown that all types of solutions of the linear problem, as well as spectral data known in the literature, are given as specific values of this unique function - the resolvent function. A new form of the inverse problem is formulated. 7 refs

Group Work Tests for Context-Rich Problems

Science.gov (United States)

Meyer, Chris

2016-05-01

The group work test is an assessment strategy that promotes higher-order thinking skills for solving context-rich problems. With this format, teachers are able to pose challenging, nuanced questions on a test, while providing the support weaker students need to get started and show their understanding. The test begins with a group discussion phase, when students are given a "number-free" version of the problem. This phase allows students to digest the story-like problem, explore solution ideas, and alleviate some test anxiety. After 10-15 minutes of discussion, students inform the instructor of their readiness for the individual part of the test. What follows next is a pedagogical phase change from lively group discussion to quiet individual work. The group work test is a natural continuation of the group work in our daily physics classes and helps reinforce the importance of collaboration. This method has met with success at York Mills Collegiate Institute, in Toronto, Ontario, where it has been used consistently for unit tests and the final exam of the grade 12 university preparation physics course.

Similarity-dissimilarity plot for visualization of high dimensional data in biomedical pattern classification.

Science.gov (United States)

Arif, Muhammad

2012-06-01

In pattern classification problems, feature extraction is an important step. Quality of features in discriminating different classes plays an important role in pattern classification problems. In real life, pattern classification may require high dimensional feature space and it is impossible to visualize the feature space if the dimension of feature space is greater than four. In this paper, we have proposed a Similarity-Dissimilarity plot which can project high dimensional space to a two dimensional space while retaining important characteristics required to assess the discrimination quality of the features. Similarity-dissimilarity plot can reveal information about the amount of overlap of features of different classes. Separable data points of different classes will also be visible on the plot which can be classified correctly using appropriate classifier. Hence, approximate classification accuracy can be predicted. Moreover, it is possible to know about whom class the misclassified data points will be confused by the classifier. Outlier data points can also be located on the similarity-dissimilarity plot. Various examples of synthetic data are used to highlight important characteristics of the proposed plot. Some real life examples from biomedical data are also used for the analysis. The proposed plot is independent of number of dimensions of the feature space.

Behaviors of Problem-Solving Groups

National Research Council Canada - National Science Library

Bennis, Warren G

1958-01-01

The results of two studies are contained in this report in summary form. They represent the first parts of a program of research designed to study the effects of change and history on the on the behaviors of problem-solving Groups...

3D overlapped grouping Ga for optimum 2D guillotine cutting stock problem

Directory of Open Access Journals (Sweden)

Maged R. Rostom

2014-09-01

Full Text Available The cutting stock problem (CSP is one of the significant optimization problems in operations research and has gained a lot of attention for increasing efficiency in industrial engineering, logistics and manufacturing. In this paper, new methodologies for optimally solving the cutting stock problem are presented. A modification is proposed to the existing heuristic methods with a hybrid new 3-D overlapped grouping Genetic Algorithm (GA for nesting of two-dimensional rectangular shapes. The objective is the minimization of the wastage of the sheet material which leads to maximizing material utilization and the minimization of the setup time. The model and its results are compared with real life case study from a steel workshop in a bus manufacturing factory. The effectiveness of the proposed approach is shown by comparing and shop testing of the optimized cutting schedules. The results reveal its superiority in terms of waste minimization comparing to the current cutting schedules. The whole procedure can be completed in a reasonable amount of time by the developed optimization program.

Network-based group variable selection for detecting expression quantitative trait loci (eQTL

Directory of Open Access Journals (Sweden)

Zhang Xuegong

2011-06-01

Full Text Available Abstract Background Analysis of expression quantitative trait loci (eQTL aims to identify the genetic loci associated with the expression level of genes. Penalized regression with a proper penalty is suitable for the high-dimensional biological data. Its performance should be enhanced when we incorporate biological knowledge of gene expression network and linkage disequilibrium (LD structure between loci in high-noise background. Results We propose a network-based group variable selection (NGVS method for QTL detection. Our method simultaneously maps highly correlated expression traits sharing the same biological function to marker sets formed by LD. By grouping markers, complex joint activity of multiple SNPs can be considered and the dimensionality of eQTL problem is reduced dramatically. In order to demonstrate the power and flexibility of our method, we used it to analyze two simulations and a mouse obesity and diabetes dataset. We considered the gene co-expression network, grouped markers into marker sets and treated the additive and dominant effect of each locus as a group: as a consequence, we were able to replicate results previously obtained on the mouse linkage dataset. Furthermore, we observed several possible sex-dependent loci and interactions of multiple SNPs. Conclusions The proposed NGVS method is appropriate for problems with high-dimensional data and high-noise background. On eQTL problem it outperforms the classical Lasso method, which does not consider biological knowledge. Introduction of proper gene expression and loci correlation information makes detecting causal markers more accurate. With reasonable model settings, NGVS can lead to novel biological findings.

Collisional plasma transport: two-dimensional scalar formulation of the initial boundary value problem and quasi one-dimensional models

International Nuclear Information System (INIS)

Mugge, J.W.

1979-10-01

The collisional plasma transport problem is formulated as an initial boundary value problem for general characteristic boundary conditions. Starting from the full set of hydrodynamic and electrodynamic equations an expansion in the electron-ion mass ratio together with a multiple timescale method yields simplified equations on each timescale. On timescales where many collisions have taken place for the simplified equations the initial boundary value problem is formulated. Through the introduction of potentials a two-dimensional scalar formulation in terms of quasi-linear integro-differential equations of second order for a domain consisting of plasma and vacuum sub-domains is obtained. (Auth.)

An inverse problem for a one-dimensional time-fractional diffusion problem

KAUST Repository

Jin, Bangti

2012-06-26

We study an inverse problem of recovering a spatially varying potential term in a one-dimensional time-fractional diffusion equation from the flux measurements taken at a single fixed time corresponding to a given set of input sources. The unique identifiability of the potential is shown for two cases, i.e. the flux at one end and the net flux, provided that the set of input sources forms a complete basis in L 2(0, 1). An algorithm of the quasi-Newton type is proposed for the efficient and accurate reconstruction of the coefficient from finite data, and the injectivity of the Jacobian is discussed. Numerical results for both exact and noisy data are presented. © 2012 IOP Publishing Ltd.

The development of a collapsing method for the mixed group and point cross sections and its application on multi-dimensional deep penetration calculations

International Nuclear Information System (INIS)

Bor-Jing Chang; Yen-Wan H. Liu

1992-01-01

The HYBRID, or mixed group and point, method was developed to solve the neutron transport equation deterministically using detailed treatment at cross section minima for deep penetration calculations. Its application so far is limited to one-dimensional calculations due to the enormous computing time involved in multi-dimensional calculations. In this article, a collapsing method is developed for the mixed group and point cross section sets to provide a more direct and practical way of using the HYBRID method in the multi-dimensional calculations. A testing problem is run. The method is then applied to the calculation of a deep penetration benchmark experiment. It is observed that half of the window effect is smeared in the collapsing treatment, but it still provide a better cross section set than the VITAMIN-C cross sections for the deep penetrating calculations

NESTLE: Few-group neutron diffusion equation solver utilizing the nodal expansion method for eigenvalue, adjoint, fixed-source steady-state and transient problems

International Nuclear Information System (INIS)

Turinsky, P.J.; Al-Chalabi, R.M.K.; Engrand, P.; Sarsour, H.N.; Faure, F.X.; Guo, W.

1994-06-01

NESTLE is a FORTRAN77 code that solves the few-group neutron diffusion equation utilizing the Nodal Expansion Method (NEM). NESTLE can solve the eigenvalue (criticality); eigenvalue adjoint; external fixed-source steady-state; or external fixed-source. or eigenvalue initiated transient problems. The code name NESTLE originates from the multi-problem solution capability, abbreviating Nodal Eigenvalue, Steady-state, Transient, Le core Evaluator. The eigenvalue problem allows criticality searches to be completed, and the external fixed-source steady-state problem can search to achieve a specified power level. Transient problems model delayed neutrons via precursor groups. Several core properties can be input as time dependent. Two or four energy groups can be utilized, with all energy groups being thermal groups (i.e. upscatter exits) if desired. Core geometries modelled include Cartesian and Hexagonal. Three, two and one dimensional models can be utilized with various symmetries. The non-linear iterative strategy associated with the NEM method is employed. An advantage of the non-linear iterative strategy is that NSTLE can be utilized to solve either the nodal or Finite Difference Method representation of the few-group neutron diffusion equation

Algebraic K-theory of crystallographic groups the three-dimensional splitting case

CERN Document Server

Farley, Daniel Scott

2014-01-01

The Farrell-Jones isomorphism conjecture in algebraic K-theory offers a description of the algebraic K-theory of a group using a generalized homology theory. In cases where the conjecture is known to be a theorem, it gives a powerful method for computing the lower algebraic K-theory of a group. This book contains a computation of the lower algebraic K-theory of the split three-dimensional crystallographic groups, a geometrically important class of three-dimensional crystallographic group, representing a third of the total number. The book leads the reader through all aspects of the calculation. The first chapters describe the split crystallographic groups and their classifying spaces. Later chapters assemble the techniques that are needed to apply the isomorphism theorem. The result is a useful starting point for researchers who are interested in the computational side of the Farrell-Jones isomorphism conjecture, and a contribution to the growing literature in the field.

Dimensional reduction of exceptional E6,E8 gauge groups and flavour chirality

International Nuclear Information System (INIS)

Koca, M.

1984-01-01

Ten-dimensional Yang - Mills gauge theories based on the exceptional groups E 6 and E 8 are reduced to four-dimensional flavour-chiral Yang - Mills - Higgs theories where the extra six dimensions are identified with the compact G 2 /SU(3) and SO(7)/SO(6) coset spaces. A ten-dimensional E 8 theory leads to three families of SU(5), one of which lies in the 144-dimensional representation of SO(10)

Gender-associated analysis of high-risk groups for mental health problems in law-enforcement officers

Directory of Open Access Journals (Sweden)

Vitaliy Omelyanovich

2017-11-01

Full Text Available Background. Mental disorders prevention in specific professional groups is impossible without scientifically substantiated allocation of groups with increased neuropsychiatric and psychosomatic disorders risk. This fact indicates the need to study the gender, age and professional characteristics in law enforcement workers who already have problems with psychological adaptation. Methods and materials. The study involved 1630 law enforcement officers (1,301 men and 329 women who were evaluated with the Symptom Checklist-90-R (SCL-90-R. As the statistical methods were used the partial regression calculation coefficient η2, cohort calculation risk measures, φ*-total Fischer transformation method, and single-factor dispersion Fisher's analysis. Results. According to gender characteristics, the problems with psychological adaptation in men were significantly less pronounced than in women (φ*=1.79; p=0.37. These data were confirmed by the cohort calculation and risk measures results: men – 0.261, women – 0.349 (the psychological disadaptation risk in women was 1.3 times higher than men. There weren’t any statistically significant age differences between the representatives of both gender groups with psychological adaptation disturbances and healthy ones (φ* ≤1.19; p≥0.1. Among patients who suffered from psychosomatic diseases, were men over the age of 35 (φ* ≥2.28; p≤0.0001 and women over 26 years old (φ*= 2.16; p=0.014 prevailed. There were significantly fewer people among men with psychosomatic illnesses with 4-9 years of professional working experience than in a healthy group. On the contrary, there were significantly more patients in a law enforcement workers group with 10-15 years working experience than in the healthy one (φ*>1.73; p<0.0001. Conclusion. The risk of mental health problems in female police officers is much higher than in men. Disadaptation development is not related to the age and length of working

On the equivalence of four-dimensional self-duality equations to the continual analogue of the principal chiral field problem

International Nuclear Information System (INIS)

Leznov, A.N.

1987-01-01

A connection is found between the self-dual equations of 4-dimensional space and the principal chiral field problem in n-dimensional space. It is shown that any solution of the principal chiral field equations in n-dimensional space with arbitrary 2-dimensional functions of definite linear combinations of 4 variables y, y-bar, z, z-bar as independent arguments satisfies the system of self-dual equations of 4-dimensional space. General solution of self-dual equations depending on the suitable number of functions of three independent variables coincides with the general solution of the principal chiral field problem when the dimensionality of the space tends to the infinity

Effectiveness of Self Instructional Module on Coping Strategies of Tri-Dimensional Problems of Premenopausal Women – A Community Based Study

Science.gov (United States)

Boro, Enu; Jamil, MD; Roy, Aakash

2016-01-01

Introduction Pre-menopause in women presents with diverse symptoms, encompassing the tri-dimensional spheres of physical, social and psychological domains, which requires development of appropriate coping strategies to overcome these problems. Aim To assess level of knowledge about tri-dimensional problems in pre-menopausal women and evaluate effectiveness of self instruction module on coping strategies of these problems by pre-test and post-test analysis. Materials and Methods In a cross-sectional, community based study, in pre-menopausal women aged 40-49years baseline knowledge of tridimensional problems was assessed in 300 pre-menopausal women, selected by convenient sampling after satisfying selection criteria, by a pre-formed questionnaire. This was followed by administration of a pre-tested, Self-Instructional Module (SIM). The SIM dealt with imparting knowledge about coping strategies regarding pre-menopausal problems and the participants were required to read and retain the SIM. Post-test was conducted using same questionnaire after seven days. Statistical Analysis Chi-square test/ Paired t-test was used for comparing ratios. A ‘p-value’ <0.05 was considered statistically significant. Results Baseline knowledge of tridimensional problems was adequate in 10%, moderate in 73% and inadequate in 17% women with a pre-test mean knowledge score of 8.66±2.45. The post-test mean knowledge score was higher (19.11±3.38) compared to the pre-test score. The post-test mean knowledge difference from pre-test was -10.45 with a highly significant paired t-value of -47.45 indicating that the self-instructional module was effective in increasing the knowledge score of pre- menopausal women under study. Conclusion Administration of self instructional module was shown to significantly increase the knowledge scores in all areas of pre-menopausal tri-dimensional problems. Such self-instructional module can be used as an effective educational tool in increasing the knowledge

Emergent Leadership in Children's Cooperative Problem Solving Groups

Science.gov (United States)

Sun, Jingjng; Anderson, Richard C.; Perry, Michelle; Lin, Tzu-Jung

2017-01-01

Social skills involved in leadership were examined in a problem-solving activity in which 252 Chinese 5th-graders worked in small groups on a spatial-reasoning puzzle. Results showed that students who engaged in peer-managed small-group discussions of stories prior to problem solving produced significantly better solutions and initiated…

Inverse Problem for Two-Dimensional Discrete Schr`dinger Equation

CERN Document Server

Serdyukova, S I

2000-01-01

For two-dimensional discrete Schroedinger equation the boundary-value problem in rectangle M times N with zero boundary conditions is solved. It's stated in this work, that inverse problem reduces to reconstruction of C symmetric five-diagonal matrix with given spectrum and given first k(M,N), 1<-kproblem to the end in the process of concrete calculations. Deriving and solving the huge polynomial systems had been perfor...

Group theory approach to scattering

International Nuclear Information System (INIS)

Wu, J.

1985-01-01

For certain physical systems, there exists a dynamical group which contains the operators connecting states with the same energy but belonging to potentials with different strengths. This group is called the potential group of that system. The SO(2,1) potential groups structure is introduced to describe physical systems with mixed spectra, such as Morse and Poeschl-teller potentials. The discrete spectrum describes bound states and the continuous spectrum describes bound states and the continuous spectrum describes scattering states. A solvable class of one-dimensional potentials given by Natanzon belongs to this structure with an SO(2,2) potential group. The potential group structure provides us with an algebraic procedure generating the recursion relations for the scattering matrix, which can be formulated in a purely algebraic fashion, divorced from any differential realization. This procedure, when applied to the three-dimensional scattering problem with SO(3,1) symmetry, generates the scattering matrix of the Coulomb problem. Preliminary phenomenological models for elastic scattering in a heavy-ion collision are constructed on the basis. The results obtained here can be regarded as an important extension of the group theory techniques to scattering problems similar to that developed for bound state problems

Estimates of error introduced when one-dimensional inverse heat transfer techniques are applied to multi-dimensional problems

International Nuclear Information System (INIS)

Lopez, C.; Koski, J.A.; Razani, A.

2000-01-01

A study of the errors introduced when one-dimensional inverse heat conduction techniques are applied to problems involving two-dimensional heat transfer effects was performed. The geometry used for the study was a cylinder with similar dimensions as a typical container used for the transportation of radioactive materials. The finite element analysis code MSC P/Thermal was used to generate synthetic test data that was then used as input for an inverse heat conduction code. Four different problems were considered including one with uniform flux around the outer surface of the cylinder and three with non-uniform flux applied over 360 deg C, 180 deg C, and 90 deg C sections of the outer surface of the cylinder. The Sandia One-Dimensional Direct and Inverse Thermal (SODDIT) code was used to estimate the surface heat flux of all four cases. The error analysis was performed by comparing the results from SODDIT and the heat flux calculated based on the temperature results obtained from P/Thermal. Results showed an increase in error of the surface heat flux estimates as the applied heat became more localized. For the uniform case, SODDIT provided heat flux estimates with a maximum error of 0.5% whereas for the non-uniform cases, the maximum errors were found to be about 3%, 7%, and 18% for the 360 deg C, 180 deg C, and 90 deg C cases, respectively

Two-dimensional unsteady lift problems in supersonic flight

Science.gov (United States)

Heaslet, Max A; Lomax, Harvard

1949-01-01

The variation of pressure distribution is calculated for a two-dimensional supersonic airfoil either experiencing a sudden angle-of-attack change or entering a sharp-edge gust. From these pressure distributions the indicial lift functions applicable to unsteady lift problems are determined for two cases. Results are presented which permit the determination of maximum increment in lift coefficient attained by an unrestrained airfoil during its flight through a gust. As an application of these results, the minimum altitude for safe flight through a specific gust is calculated for a particular supersonic wing of given strength and wing loading.

Statistical mechanics of complex neural systems and high dimensional data

International Nuclear Information System (INIS)

Advani, Madhu; Lahiri, Subhaneil; Ganguli, Surya

2013-01-01

Recent experimental advances in neuroscience have opened new vistas into the immense complexity of neuronal networks. This proliferation of data challenges us on two parallel fronts. First, how can we form adequate theoretical frameworks for understanding how dynamical network processes cooperate across widely disparate spatiotemporal scales to solve important computational problems? Second, how can we extract meaningful models of neuronal systems from high dimensional datasets? To aid in these challenges, we give a pedagogical review of a collection of ideas and theoretical methods arising at the intersection of statistical physics, computer science and neurobiology. We introduce the interrelated replica and cavity methods, which originated in statistical physics as powerful ways to quantitatively analyze large highly heterogeneous systems of many interacting degrees of freedom. We also introduce the closely related notion of message passing in graphical models, which originated in computer science as a distributed algorithm capable of solving large inference and optimization problems involving many coupled variables. We then show how both the statistical physics and computer science perspectives can be applied in a wide diversity of contexts to problems arising in theoretical neuroscience and data analysis. Along the way we discuss spin glasses, learning theory, illusions of structure in noise, random matrices, dimensionality reduction and compressed sensing, all within the unified formalism of the replica method. Moreover, we review recent conceptual connections between message passing in graphical models, and neural computation and learning. Overall, these ideas illustrate how statistical physics and computer science might provide a lens through which we can uncover emergent computational functions buried deep within the dynamical complexities of neuronal networks. (paper)

Using Localised Quadratic Functions on an Irregular Grid for Pricing High-Dimensional American Options

NARCIS (Netherlands)

Berridge, S.J.; Schumacher, J.M.

2004-01-01

We propose a method for pricing high-dimensional American options on an irregular grid; the method involves using quadratic functions to approximate the local effect of the Black-Scholes operator.Once such an approximation is known, one can solve the pricing problem by time stepping in an explicit

Two-dimensional multiferroics in monolayer group IV monochalcogenides

Science.gov (United States)

Wang, Hua; Qian, Xiaofeng

2017-03-01

Low-dimensional multiferroic materials hold great promises in miniaturized device applications such as nanoscale transducers, actuators, sensors, photovoltaics, and nonvolatile memories. Here, using first-principles theory we predict that two-dimensional (2D) monolayer group IV monochalcogenides including GeS, GeSe, SnS, and SnSe are a class of 2D semiconducting multiferroics with giant strongly-coupled in-plane spontaneous ferroelectric polarization and spontaneous ferroelastic lattice strain that are thermodynamically stable at room temperature and beyond, and can be effectively modulated by elastic strain engineering. Their optical absorption spectra exhibit strong in-plane anisotropy with visible-spectrum excitonic gaps and sizable exciton binding energies, rendering the unique characteristics of low-dimensional semiconductors. More importantly, the predicted low domain wall energy and small migration barrier together with the coupled multiferroic order and anisotropic electronic structures suggest their great potentials for tunable multiferroic functional devices by manipulating external electrical, mechanical, and optical field to control the internal responses, and enable the development of four device concepts including 2D ferroelectric memory, 2D ferroelastic memory, and 2D ferroelastoelectric nonvolatile photonic memory as well as 2D ferroelectric excitonic photovoltaics.

The discrete cones methods for two-dimensional neutral particle transport problems with voids

International Nuclear Information System (INIS)

Watanabe, Y.; Maynard, C.W.

1983-01-01

One of the most widely applied deterministic methods for time-independent, two-dimensional neutron transport calculations is the discrete ordinates method (DSN). The DSN solution, however, fails to be accurate in a void due to the ray effect. In order to circumvent this drawback, the authors have been developing a novel approximation: the discrete cones method (DCN), where a group of particles in a cone are simultaneously traced instead of particles in discrete directions for the DSN method. Programs, which apply to the DSN method in a non-vacuum region and the DCN method in a void, have been written for transport calculations in X-Y coordinates. The solutions for test problems demonstrate mitigation of the ray effect in voids without loosing the computational efficiency of the DSN method

Group Design Problems in Engineering Design Graphics.

Science.gov (United States)

Kelley, David

2001-01-01

Describes group design techniques used within the engineering design graphics sequence at Western Washington University. Engineering and design philosophies such as concurrent engineering place an emphasis on group collaboration for the solving of design problems. (Author/DDR)

Enhanced, targeted sampling of high-dimensional free-energy landscapes using variationally enhanced sampling, with an application to chignolin.

Science.gov (United States)

Shaffer, Patrick; Valsson, Omar; Parrinello, Michele

2016-02-02

The capabilities of molecular simulations have been greatly extended by a number of widely used enhanced sampling methods that facilitate escaping from metastable states and crossing large barriers. Despite these developments there are still many problems which remain out of reach for these methods which has led to a vigorous effort in this area. One of the most important problems that remains unsolved is sampling high-dimensional free-energy landscapes and systems that are not easily described by a small number of collective variables. In this work we demonstrate a new way to compute free-energy landscapes of high dimensionality based on the previously introduced variationally enhanced sampling, and we apply it to the miniprotein chignolin.

Enhanced, targeted sampling of high-dimensional free-energy landscapes using variationally enhanced sampling, with an application to chignolin

Science.gov (United States)

Shaffer, Patrick; Valsson, Omar; Parrinello, Michele

2016-01-01

The capabilities of molecular simulations have been greatly extended by a number of widely used enhanced sampling methods that facilitate escaping from metastable states and crossing large barriers. Despite these developments there are still many problems which remain out of reach for these methods which has led to a vigorous effort in this area. One of the most important problems that remains unsolved is sampling high-dimensional free-energy landscapes and systems that are not easily described by a small number of collective variables. In this work we demonstrate a new way to compute free-energy landscapes of high dimensionality based on the previously introduced variationally enhanced sampling, and we apply it to the miniprotein chignolin. PMID:26787868

Fast three-dimensional core optimization based on modified one-group model

Energy Technology Data Exchange (ETDEWEB)

Freire, Fernando S. [ELETROBRAS Termonuclear S.A. - ELETRONUCLEAR, Rio de Janeiro, RJ (Brazil). Dept. GCN-T], e-mail: freire@eletronuclear.gov.br; Martinez, Aquilino S.; Silva, Fernando C. da [Coordenacao dos Programas de Pos-graduacao de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Nuclear], e-mail: aquilino@con.ufrj.br, e-mail: fernando@con.ufrj.br

2009-07-01

The optimization of any nuclear reactor core is an extremely complex process that consumes a large amount of computer time. Fortunately, the nuclear designer can rely on a variety of methodologies able to approximate the analysis of each available core loading pattern. Two-dimensional codes are usually used to analyze the loading scheme. However, when particular axial effects are present in the core, two-dimensional analysis cannot produce good results and three-dimensional analysis can be required at all time. Basically, in this paper are presented the major advantages that can be found when one use the modified one-group diffusion theory coupled with a buckling correction model in optimization process. The results of the proposed model are very accurate when compared to benchmark results obtained from detailed calculations using three-dimensional nodal codes (author)

Fast three-dimensional core optimization based on modified one-group model

International Nuclear Information System (INIS)

Freire, Fernando S.; Martinez, Aquilino S.; Silva, Fernando C. da

2009-01-01

The optimization of any nuclear reactor core is an extremely complex process that consumes a large amount of computer time. Fortunately, the nuclear designer can rely on a variety of methodologies able to approximate the analysis of each available core loading pattern. Two-dimensional codes are usually used to analyze the loading scheme. However, when particular axial effects are present in the core, two-dimensional analysis cannot produce good results and three-dimensional analysis can be required at all time. Basically, in this paper are presented the major advantages that can be found when one use the modified one-group diffusion theory coupled with a buckling correction model in optimization process. The results of the proposed model are very accurate when compared to benchmark results obtained from detailed calculations using three-dimensional nodal codes (author)

Non-commutative cryptography and complexity of group-theoretic problems

CERN Document Server

Myasnikov, Alexei; Ushakov, Alexander

2011-01-01

This book is about relations between three different areas of mathematics and theoretical computer science: combinatorial group theory, cryptography, and complexity theory. It explores how non-commutative (infinite) groups, which are typically studied in combinatorial group theory, can be used in public-key cryptography. It also shows that there is remarkable feedback from cryptography to combinatorial group theory because some of the problems motivated by cryptography appear to be new to group theory, and they open many interesting research avenues within group theory. In particular, a lot of emphasis in the book is put on studying search problems, as compared to decision problems traditionally studied in combinatorial group theory. Then, complexity theory, notably generic-case complexity of algorithms, is employed for cryptanalysis of various cryptographic protocols based on infinite groups, and the ideas and machinery from the theory of generic-case complexity are used to study asymptotically dominant prop...

A parallel algorithm for solving linear equations arising from one-dimensional network problems

International Nuclear Information System (INIS)

Mesina, G.L.

1991-01-01

One-dimensional (1-D) network problems, such as those arising from 1- D fluid simulations and electrical circuitry, produce systems of sparse linear equations which are nearly tridiagonal and contain a few non-zero entries outside the tridiagonal. Most direct solution techniques for such problems either do not take advantage of the special structure of the matrix or do not fully utilize parallel computer architectures. We describe a new parallel direct linear equation solution algorithm, called TRBR, which is especially designed to take advantage of this structure on MIMD shared memory machines. The new method belongs to a family of methods which split the coefficient matrix into the sum of a tridiagonal matrix T and a matrix comprised of the remaining coefficients R. Efficient tridiagonal methods are used to algebraically simplify the linear system. A smaller auxiliary subsystem is created and solved and its solution is used to calculate the solution of the original system. The newly devised BR method solves the subsystem. The serial and parallel operation counts are given for the new method and related earlier methods. TRBR is shown to have the smallest operation count in this class of direct methods. Numerical results are given. Although the algorithm is designed for one-dimensional networks, it has been applied successfully to three-dimensional problems as well. 20 refs., 2 figs., 4 tabs

Multivariate statistics high-dimensional and large-sample approximations

CERN Document Server

Fujikoshi, Yasunori; Shimizu, Ryoichi

2010-01-01

A comprehensive examination of high-dimensional analysis of multivariate methods and their real-world applications Multivariate Statistics: High-Dimensional and Large-Sample Approximations is the first book of its kind to explore how classical multivariate methods can be revised and used in place of conventional statistical tools. Written by prominent researchers in the field, the book focuses on high-dimensional and large-scale approximations and details the many basic multivariate methods used to achieve high levels of accuracy. The authors begin with a fundamental presentation of the basic

Highly ordered three-dimensional macroporous carbon spheres for determination of heavy metal ions

International Nuclear Information System (INIS)

Zhang, Yuxiao; Zhang, Jianming; Liu, Yang; Huang, Hui; Kang, Zhenhui

2012-01-01

Highlights: ► Highly ordered three dimensional macroporous carbon spheres (MPCSs) were prepared. ► MPCS was covalently modified by cysteine (MPCS–CO–Cys). ► MPCS–CO–Cys was first time used in electrochemical detection of heavy metal ions. ► Heavy metal ions such as Pb 2+ and Cd 2+ can be simultaneously determined. -- Abstract: An effective voltammetric method for detection of trace heavy metal ions using chemically modified highly ordered three dimensional macroporous carbon spheres electrode surfaces is described. The highly ordered three dimensional macroporous carbon spheres were prepared by carbonization of glucose in silica crystal bead template, followed by removal of the template. The highly ordered three dimensional macroporous carbon spheres were covalently modified by cysteine, an amino acid with high affinities towards some heavy metals. The materials were characterized by physical adsorption of nitrogen, scanning electron microscopy, and transmission electron microscopy techniques. While the Fourier-transform infrared spectroscopy was used to characterize the functional groups on the surface of carbon spheres. High sensitivity was exhibited when this material was used in electrochemical detection (square wave anodic stripping voltammetry) of heavy metal ions due to the porous structure. And the potential application for simultaneous detection of heavy metal ions was also investigated.

STAB: A kinetic, three-dimensional, one-group digital computer program

International Nuclear Information System (INIS)

Curtis, A.R.; Tyror, J.G.; Wrigley, H.E.

1961-10-01

A computer program for solving the one-group, time dependent, three-dimensional diffusion equation together with auxiliary equations representing heat transfer, xenon production and control rod movements, is presented. The equations and the methods of solution are discussed. (author)

Poincare-Birkhoff-Witt theorems and generalized Casimir invariants for some infinite-dimensional Lie groups: II

International Nuclear Information System (INIS)

Ton-That, Tuong

2005-01-01

In a previous paper we gave a generalization of the notion of Casimir invariant differential operators for the infinite-dimensional Lie groups GL ∞ (C) (or equivalently, for its Lie algebra gj ∞ (C)). In this paper we give a generalization of the Casimir invariant differential operators for a class of infinite-dimensional Lie groups (or equivalently, for their Lie algebras) which contains the infinite-dimensional complex classical groups. These infinite-dimensional Lie groups, and their Lie algebras, are inductive limits of finite-dimensional Lie groups, and their Lie algebras, with some additional properties. These groups or their Lie algebras act via the generalized adjoint representations on projective limits of certain chains of vector spaces of universal enveloping algebras. Then the generalized Casimir operators are the invariants of the generalized adjoint representations. In order to be able to explicitly compute the Casimir operators one needs a basis for the universal enveloping algebra of a Lie algebra. The Poincare-Birkhoff-Witt (PBW) theorem gives an explicit construction of such a basis. Thus in the first part of this paper we give a generalization of the PBW theorem for inductive limits of Lie algebras. In the last part of this paper a generalization of the very important theorem in representation theory, namely the Chevalley-Racah theorem, is also discussed

Bayesian Multiresolution Variable Selection for Ultra-High Dimensional Neuroimaging Data.

Science.gov (United States)

Zhao, Yize; Kang, Jian; Long, Qi

2018-01-01

Ultra-high dimensional variable selection has become increasingly important in analysis of neuroimaging data. For example, in the Autism Brain Imaging Data Exchange (ABIDE) study, neuroscientists are interested in identifying important biomarkers for early detection of the autism spectrum disorder (ASD) using high resolution brain images that include hundreds of thousands voxels. However, most existing methods are not feasible for solving this problem due to their extensive computational costs. In this work, we propose a novel multiresolution variable selection procedure under a Bayesian probit regression framework. It recursively uses posterior samples for coarser-scale variable selection to guide the posterior inference on finer-scale variable selection, leading to very efficient Markov chain Monte Carlo (MCMC) algorithms. The proposed algorithms are computationally feasible for ultra-high dimensional data. Also, our model incorporates two levels of structural information into variable selection using Ising priors: the spatial dependence between voxels and the functional connectivity between anatomical brain regions. Applied to the resting state functional magnetic resonance imaging (R-fMRI) data in the ABIDE study, our methods identify voxel-level imaging biomarkers highly predictive of the ASD, which are biologically meaningful and interpretable. Extensive simulations also show that our methods achieve better performance in variable selection compared to existing methods.

A three-dimensional neutron transport benchmark solution

International Nuclear Information System (INIS)

Ganapol, B.D.; Kornreich, D.E.

1993-01-01

For one-group neutron transport theory in one dimension, several powerful analytical techniques have been developed to solve the neutron transport equation, including Caseology, Wiener-Hopf factorization, and Fourier and Laplace transform methods. In addition, after a Fourier transform in the transverse plane and formulation of a pseudo problem, two-dimensional (2-D) and three-dimensional (3-D) problems can be solved using the techniques specifically developed for the one-dimensional (1-D) case. Numerical evaluation of the resulting expressions requiring an inversion in the transverse plane have been successful for 2-D problems but becomes exceedingly difficult in the 3-D case. In this paper, we show that by using the symmetry along the beam direction, a 2-D problem can be transformed into a 3-D problem in an infinite medium. The numerical solution to the 3-D problem is then demonstrated. Thus, a true 3-D transport benchmark solution can be obtained from a well-established numerical solution to a 2-D problem

Classical gauge theories on the coadjoint orbits of infinite dimensional groups

International Nuclear Information System (INIS)

Grabowski, M.P.; Virginia Polytechnic Inst. and State Univ., Blacksburg; Tze Chiahsiung

1991-01-01

We reformulate several classical gauge theories on the coadjoint orbits of the semidirect product of the gauge group and the Weyl group. The construction is given for the Yang-Mills theories in arbitrary spacetime dimension d, Chern-Simons topological theory (d=3) and higher dimensional topological models of Horowitz (d≥4). (orig.)

Resolvent approach for two-dimensional scattering problems. Application to the nonstationary Schrödinger problem and the KPI equation

Science.gov (United States)

Boiti, M.; Pempinelli, F.; Pogrebkov, A. K.; Polivanov, M. C.

1992-11-01

The resolvent operator of the linear problem is determined as the full Green function continued in the complex domain in two variables. An analog of the known Hilbert identity is derived. We demonstrate the role of this identity in the study of two-dimensional scattering. Considering the nonstationary Schrödinger equation as an example, we show that all types of solutions of the linear problems, as well as spectral data known in the literature, are given as specific values of this unique function — the resolvent function. A new form of the inverse problem is formulated.

Maxwell Strata and Cut Locus in the Sub-Riemannian Problem on the Engel Group

Science.gov (United States)

Ardentov, Andrei A.; Sachkov, Yuri L.

2017-12-01

We consider the nilpotent left-invariant sub-Riemannian structure on the Engel group. This structure gives a fundamental local approximation of a generic rank 2 sub-Riemannian structure on a 4-manifold near a generic point (in particular, of the kinematic models of a car with a trailer). On the other hand, this is the simplest sub-Riemannian structure of step three. We describe the global structure of the cut locus (the set of points where geodesics lose their global optimality), the Maxwell set (the set of points that admit more than one minimizer), and the intersection of the cut locus with the caustic (the set of conjugate points along all geodesics). The group of symmetries of the cut locus is described: it is generated by a one-parameter group of dilations R+ and a discrete group of reflections Z2 × Z2 × Z2. The cut locus admits a stratification with 6 three-dimensional strata, 12 two-dimensional strata, and 2 one-dimensional strata. Three-dimensional strata of the cut locus are Maxwell strata of multiplicity 2 (for each point there are 2 minimizers). Two-dimensional strata of the cut locus consist of conjugate points. Finally, one-dimensional strata are Maxwell strata of infinite multiplicity, they consist of conjugate points as well. Projections of sub-Riemannian geodesics to the 2-dimensional plane of the distribution are Euler elasticae. For each point of the cut locus, we describe the Euler elasticae corresponding to minimizers coming to this point. Finally, we describe the structure of the optimal synthesis, i. e., the set of minimizers for each terminal point in the Engel group.

Eisenstein series for infinite-dimensional U-duality groups

Science.gov (United States)

Fleig, Philipp; Kleinschmidt, Axel

2012-06-01

We consider Eisenstein series appearing as coefficients of curvature corrections in the low-energy expansion of type II string theory four-graviton scattering amplitudes. We define these Eisenstein series over all groups in the E n series of string duality groups, and in particular for the infinite-dimensional Kac-Moody groups E 9, E 10 and E 11. We show that, remarkably, the so-called constant term of Kac-Moody-Eisenstein series contains only a finite number of terms for particular choices of a parameter appearing in the definition of the series. This resonates with the idea that the constant term of the Eisenstein series encodes perturbative string corrections in BPS-protected sectors allowing only a finite number of corrections. We underpin our findings with an extensive discussion of physical degeneration limits in D < 3 space-time dimensions.

A two-dimensional embedded-boundary method for convection problems with moving boundaries

NARCIS (Netherlands)

Y.J. Hassen (Yunus); B. Koren (Barry)

2010-01-01

htmlabstractIn this work, a two-dimensional embedded-boundary algorithm for convection problems is presented. A moving body of arbitrary boundary shape is immersed in a Cartesian finite-volume grid, which is fixed in space. The boundary surface is reconstructed in such a way that only certain fluxes

Minimax Rate-optimal Estimation of High-dimensional Covariance Matrices with Incomplete Data.

Science.gov (United States)

Cai, T Tony; Zhang, Anru

2016-09-01

Missing data occur frequently in a wide range of applications. In this paper, we consider estimation of high-dimensional covariance matrices in the presence of missing observations under a general missing completely at random model in the sense that the missingness is not dependent on the values of the data. Based on incomplete data, estimators for bandable and sparse covariance matrices are proposed and their theoretical and numerical properties are investigated. Minimax rates of convergence are established under the spectral norm loss and the proposed estimators are shown to be rate-optimal under mild regularity conditions. Simulation studies demonstrate that the estimators perform well numerically. The methods are also illustrated through an application to data from four ovarian cancer studies. The key technical tools developed in this paper are of independent interest and potentially useful for a range of related problems in high-dimensional statistical inference with missing data.

Minimax Rate-optimal Estimation of High-dimensional Covariance Matrices with Incomplete Data*

Science.gov (United States)

Cai, T. Tony; Zhang, Anru

2016-01-01

Missing data occur frequently in a wide range of applications. In this paper, we consider estimation of high-dimensional covariance matrices in the presence of missing observations under a general missing completely at random model in the sense that the missingness is not dependent on the values of the data. Based on incomplete data, estimators for bandable and sparse covariance matrices are proposed and their theoretical and numerical properties are investigated. Minimax rates of convergence are established under the spectral norm loss and the proposed estimators are shown to be rate-optimal under mild regularity conditions. Simulation studies demonstrate that the estimators perform well numerically. The methods are also illustrated through an application to data from four ovarian cancer studies. The key technical tools developed in this paper are of independent interest and potentially useful for a range of related problems in high-dimensional statistical inference with missing data. PMID:27777471

Modification of equivalent charge method for the Roben three-dimensional problem in electrostatics

International Nuclear Information System (INIS)

Barsukov, A.B.; Surenskij, A.V.

1989-01-01

The approach of the Roben problem solution for the calculation of the potential of intermediate electrode of accelerating structure with HFQ focusing is considered. The solution is constructed on the basis of variational formulation of the equivalent charge method, where electrostatic problem is reduced to equations of root-mean-square residuals on the system conductors. The technique presented permits to solve efficiently the three-dimensional problems of electrostatics for rather complicated from geometrical viewpoint systems of electrodes. Processing time is comparable with methods of integral equations. 5 refs.; 2 figs

Magnetic translation groups in an n-dimensional torus and their representations

International Nuclear Information System (INIS)

Tanimura, Shogo

2002-01-01

A charged particle in a uniform magnetic field in a two-dimensional torus has a discrete noncommutative translation symmetry instead of a continuous commutative translation symmetry. We study topology and symmetry of a particle in a magnetic field in a torus of arbitrary dimensions. The magnetic translation group (MTG) is defined as a group of translations that leave the gauge field invariant. We show that the MTG in an n-dimensional torus is isomorphic to a central extension of a cyclic group Z ν 1 x···xZ ν 2l xT m by U(1) with 2l+m=n. We construct and classify irreducible unitary representations of the MTG in a three-torus and apply the representation theory to three examples. We briefly describe a representation theory for a general n-torus. The MTG in an n-torus can be regarded as a generalization of the so-called noncommutative torus

Highly ordered three-dimensional macroporous carbon spheres for determination of heavy metal ions

Energy Technology Data Exchange (ETDEWEB)

Zhang, Yuxiao; Zhang, Jianming [Institute of Functional Nano and Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123 (China); Liu, Yang, E-mail: yangl@suda.edu.cn [Institute of Functional Nano and Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123 (China); Huang, Hui [Institute of Functional Nano and Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123 (China); Kang, Zhenhui, E-mail: zhkang@suda.edu.cn [Institute of Functional Nano and Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123 (China)

2012-04-15

Highlights: Black-Right-Pointing-Pointer Highly ordered three dimensional macroporous carbon spheres (MPCSs) were prepared. Black-Right-Pointing-Pointer MPCS was covalently modified by cysteine (MPCS-CO-Cys). Black-Right-Pointing-Pointer MPCS-CO-Cys was first time used in electrochemical detection of heavy metal ions. Black-Right-Pointing-Pointer Heavy metal ions such as Pb{sup 2+} and Cd{sup 2+} can be simultaneously determined. -- Abstract: An effective voltammetric method for detection of trace heavy metal ions using chemically modified highly ordered three dimensional macroporous carbon spheres electrode surfaces is described. The highly ordered three dimensional macroporous carbon spheres were prepared by carbonization of glucose in silica crystal bead template, followed by removal of the template. The highly ordered three dimensional macroporous carbon spheres were covalently modified by cysteine, an amino acid with high affinities towards some heavy metals. The materials were characterized by physical adsorption of nitrogen, scanning electron microscopy, and transmission electron microscopy techniques. While the Fourier-transform infrared spectroscopy was used to characterize the functional groups on the surface of carbon spheres. High sensitivity was exhibited when this material was used in electrochemical detection (square wave anodic stripping voltammetry) of heavy metal ions due to the porous structure. And the potential application for simultaneous detection of heavy metal ions was also investigated.

Use of frozen stress in extracting stress intensity factor distributions in three dimensional cracked body problems

Science.gov (United States)

Smith, C. W.

1992-01-01

The adaptation of the frozen stress photoelastic method to the determination of the distribution of stress intensity factors in three dimensional problems is briefly reviewed. The method is then applied to several engineering problems of practical significance.

Implementation of a computationally efficient least-squares algorithm for highly under-determined three-dimensional diffuse optical tomography problems.

Science.gov (United States)

Yalavarthy, Phaneendra K; Lynch, Daniel R; Pogue, Brian W; Dehghani, Hamid; Paulsen, Keith D

2008-05-01

Three-dimensional (3D) diffuse optical tomography is known to be a nonlinear, ill-posed and sometimes under-determined problem, where regularization is added to the minimization to allow convergence to a unique solution. In this work, a generalized least-squares (GLS) minimization method was implemented, which employs weight matrices for both data-model misfit and optical properties to include their variances and covariances, using a computationally efficient scheme. This allows inversion of a matrix that is of a dimension dictated by the number of measurements, instead of by the number of imaging parameters. This increases the computation speed up to four times per iteration in most of the under-determined 3D imaging problems. An analytic derivation, using the Sherman-Morrison-Woodbury identity, is shown for this efficient alternative form and it is proven to be equivalent, not only analytically, but also numerically. Equivalent alternative forms for other minimization methods, like Levenberg-Marquardt (LM) and Tikhonov, are also derived. Three-dimensional reconstruction results indicate that the poor recovery of quantitatively accurate values in 3D optical images can also be a characteristic of the reconstruction algorithm, along with the target size. Interestingly, usage of GLS reconstruction methods reduces error in the periphery of the image, as expected, and improves by 20% the ability to quantify local interior regions in terms of the recovered optical contrast, as compared to LM methods. Characterization of detector photo-multiplier tubes noise has enabled the use of the GLS method for reconstructing experimental data and showed a promise for better quantification of target in 3D optical imaging. Use of these new alternative forms becomes effective when the ratio of the number of imaging property parameters exceeds the number of measurements by a factor greater than 2.

Low-dimensional gravities as gauge theories with non-compact groups

International Nuclear Information System (INIS)

Cangeni, D.

1993-01-01

In another note presented in these Proceedings it is shown that the two main lineal gravities can be given a gauge formulation. If it is already known that one of them the Sitter model - is a dimensional reduction of a Chern-Simons model in (2+1) dimensions, it was not clear whether the other one - the extended Poincare model follows from a similar reduction. The purpose of this note is to show that this is indeed the case provide we start in 2+1 dimensions with an extension ISO(2,1) of the Poincare groups as gauge group of a Chern-Simons model. We first show that this model gives a new proposal for gravity in 2*1 dimensions, since we get classically the Einstein's equations. Performing then a dimensional reduction, we recover not only the extended Poincare model but also the de Sitter one; hence, both lineal gravities get unified in the reduced model. (Author) 6 refs

The High School Dropout Problem: Perspectives of Teachers and Principals

Science.gov (United States)

Bridgeland, John M.; Dilulio, John J., Jr.; Balfanz, Robert

2009-01-01

To better understand the views of teachers and administrators on the high school dropout problem, focus groups and nationally representative surveys were conducted of high school teachers and principals. A focus group of superintendents and school board members was also included. To help interpret the results, the authors convened a colloquium…

A solution to the collective action problem in between-group conflict with within-group inequality.

Science.gov (United States)

Gavrilets, Sergey; Fortunato, Laura

2014-03-26

Conflict with conspecifics from neighbouring groups over territory, mating opportunities and other resources is observed in many social organisms, including humans. Here we investigate the evolutionary origins of social instincts, as shaped by selection resulting from between-group conflict in the presence of a collective action problem. We focus on the effects of the differences between individuals on the evolutionary dynamics. Our theoretical models predict that high-rank individuals, who are able to usurp a disproportional share of resources in within-group interactions, will act seemingly altruistically in between-group conflict, expending more effort and often having lower reproductive success than their low-rank group-mates. Similar behaviour is expected for individuals with higher motivation, higher strengths or lower costs, or for individuals in a leadership position. Our theory also provides an evolutionary foundation for classical equity theory, and it has implications for the origin of coercive leadership and for reproductive skew theory.

Basic problems solving for two-dimensional discrete 3 × 4 order hidden markov model

International Nuclear Information System (INIS)

Wang, Guo-gang; Gan, Zong-liang; Tang, Gui-jin; Cui, Zi-guan; Zhu, Xiu-chang

2016-01-01

A novel model is proposed to overcome the shortages of the classical hypothesis of the two-dimensional discrete hidden Markov model. In the proposed model, the state transition probability depends on not only immediate horizontal and vertical states but also on immediate diagonal state, and the observation symbol probability depends on not only current state but also on immediate horizontal, vertical and diagonal states. This paper defines the structure of the model, and studies the three basic problems of the model, including probability calculation, path backtracking and parameters estimation. By exploiting the idea that the sequences of states on rows or columns of the model can be seen as states of a one-dimensional discrete 1 × 2 order hidden Markov model, several algorithms solving the three questions are theoretically derived. Simulation results further demonstrate the performance of the algorithms. Compared with the two-dimensional discrete hidden Markov model, there are more statistical characteristics in the structure of the proposed model, therefore the proposed model theoretically can more accurately describe some practical problems.

Many-body problems in high temperature superconductivity

International Nuclear Information System (INIS)

Yu Lu.

1991-10-01

In this brief review the basic experimental facts about high T c superconductors are outlined. The superconducting properties of these superconductors are not very different from those of the ordinary superconductors. However, their normal state properties cannot be described by the standard Fermi liquid (FL) theory. Our current understanding of the strongly correlated models is summarized. In one dimension these systems behave like a ''Luttinger liquid'', very much distinct from the FL. In spite of the enormous efforts made in two-dimensional studies, the question of FL vs non-FL behaviour is still open. The numerical results as well as various approximation schemes are discussed. Both the single hole problem in a quantum antiferromagnet and finite doping regime are considered. (author). 104 refs, 9 figs

Renormalization-group study of the four-body problem

International Nuclear Information System (INIS)

Schmidt, Richard; Moroz, Sergej

2010-01-01

We perform a renormalization-group analysis of the nonrelativistic four-boson problem by means of a simple model with pointlike three- and four-body interactions. We investigate in particular the region where the scattering length is infinite and all energies are close to the atom threshold. We find that the four-body problem behaves truly universally, independent of any four-body parameter. Our findings confirm the recent conjectures of others that the four-body problem is universal, now also from a renormalization-group perspective. We calculate the corresponding relations between the four- and three-body bound states, as well as the full bound-state spectrum and comment on the influence of effective range corrections.

Harnessing high-dimensional hyperentanglement through a biphoton frequency comb

Science.gov (United States)

Xie, Zhenda; Zhong, Tian; Shrestha, Sajan; Xu, Xinan; Liang, Junlin; Gong, Yan-Xiao; Bienfang, Joshua C.; Restelli, Alessandro; Shapiro, Jeffrey H.; Wong, Franco N. C.; Wei Wong, Chee

2015-08-01

Quantum entanglement is a fundamental resource for secure information processing and communications, and hyperentanglement or high-dimensional entanglement has been separately proposed for its high data capacity and error resilience. The continuous-variable nature of the energy-time entanglement makes it an ideal candidate for efficient high-dimensional coding with minimal limitations. Here, we demonstrate the first simultaneous high-dimensional hyperentanglement using a biphoton frequency comb to harness the full potential in both the energy and time domain. Long-postulated Hong-Ou-Mandel quantum revival is exhibited, with up to 19 time-bins and 96.5% visibilities. We further witness the high-dimensional energy-time entanglement through Franson revivals, observed periodically at integer time-bins, with 97.8% visibility. This qudit state is observed to simultaneously violate the generalized Bell inequality by up to 10.95 standard deviations while observing recurrent Clauser-Horne-Shimony-Holt S-parameters up to 2.76. Our biphoton frequency comb provides a platform for photon-efficient quantum communications towards the ultimate channel capacity through energy-time-polarization high-dimensional encoding.

Three-dimensional CT imaging of soft-tissue anatomy

International Nuclear Information System (INIS)

Fishman, E.K.; Ney, D.R.; Magid, D.; Kuhlman, J.E.

1988-01-01

Three-dimensional display of computed tomographic data has been limited to skeletal structures. This was in part related to the reconstruction algorithm used, which relied on a binary classification scheme. A new algorithm, volumetric rendering with percentage classification, provides the ability to display three-dimensional images of muscle and soft tissue. A review was conducted of images in 35 cases in which muscle and/or soft tissue were part of the clinical problem. In all cases, individual muscle groups could be clearly identified and discriminated. Branching vessels in the range of 2.3 mm could be identified. Similarly, lymph nodes could be clearly defined. High-resolution three-dimensional images were found to be useful both in providing an increased understanding of complex muscle and soft tissue anatomy and in surgical planning

Variational Homotopy Perturbation Method for Solving Higher Dimensional Initial Boundary Value Problems

Directory of Open Access Journals (Sweden)

Muhammad Aslam Noor

2008-01-01

Full Text Available We suggest and analyze a technique by combining the variational iteration method and the homotopy perturbation method. This method is called the variational homotopy perturbation method (VHPM. We use this method for solving higher dimensional initial boundary value problems with variable coefficients. The developed algorithm is quite efficient and is practically well suited for use in these problems. The proposed scheme finds the solution without any discritization, transformation, or restrictive assumptions and avoids the round-off errors. Several examples are given to check the reliability and efficiency of the proposed technique.

NATO Advanced Study Institute on Low-dimensional Cooperative Phenomena : the Possibility of High-Temperature Superconductivity

CERN Document Server

1975-01-01

Theoretical and experimental work on solids with low-dimensional cooperative phenomena has been rather explosively expanded in the last few years, and it seems to be quite fashionable to con­ tribute to this field, especially to the problem of one-dimensional metals. On the whole, one could divide the huge amount of recent investigations into two parts although there is much overlap bet­ ween these regimes, namely investigations on magnetic exchange interactions constrained to mainly one or two dimensions and, secondly, work done on Id metallic solids or linear chain compounds with Id delocalized electrons. There is, of course, overlap from one extreme case to the other with these solids and in some rare cases both phenomena are studied on one and the same crystal. In fact, however, most of the scientific groups in this area could be associated roughly with one of these categories and,in addition, a separation between theoreticians and experimentalists in each of these groups leads to a further splitting of...

Three-dimensional printing in pharmaceutics: promises and problems.

Science.gov (United States)

Yu, Deng Guang; Zhu, Li-Min; Branford-White, Christopher J; Yang, Xiang Liang

2008-09-01

Three-dimensional printing (3DP) is a rapid prototyping (RP) technology. Prototyping involves constructing specific layers that uses powder processing and liquid binding materials. Reports in the literature have highlighted the many advantages of the 3DP system over other processes in enhancing pharmaceutical applications, these include new methods in design, development, manufacture, and commercialization of various types of solid dosage forms. For example, 3DP technology is flexible in that it can be used in applications linked to linear drug delivery systems (DDS), colon-targeted DDS, oral fast disintegrating DDS, floating DDS, time controlled, and pulse release DDS as well as dosage form with multiphase release properties and implantable DDS. In addition 3DP can also provide solutions for resolving difficulties relating to the delivery of poorly water-soluble drugs, peptides and proteins, preparation of DDS for high toxic and potent drugs and controlled-release of multidrugs in a single dosage forms. Due to its flexible and highly reproducible manufacturing process, 3DP has some advantages over conventional compressing and other RP technologies in fabricating solid DDS. This enables 3DP to be further developed for use in pharmaceutics applications. However, there are some problems that limit the further applications of the system, such as the selections of suitable excipients and the pharmacotechnical properties of 3DP products. Further developments are therefore needed to overcome these issues where 3DP systems can be successfully combined with conventional pharmaceutics. Here we present an overview and the potential 3DP in the development of new drug delivery systems.

Numerical solution to a multi-dimensional linear inverse heat conduction problem by a splitting-based conjugate gradient method

International Nuclear Information System (INIS)

Dinh Nho Hao; Nguyen Trung Thanh; Sahli, Hichem

2008-01-01

In this paper we consider a multi-dimensional inverse heat conduction problem with time-dependent coefficients in a box, which is well-known to be severely ill-posed, by a variational method. The gradient of the functional to be minimized is obtained by aids of an adjoint problem and the conjugate gradient method with a stopping rule is then applied to this ill-posed optimization problem. To enhance the stability and the accuracy of the numerical solution to the problem we apply this scheme to the discretized inverse problem rather than to the continuous one. The difficulties with large dimensions of discretized problems are overcome by a splitting method which only requires the solution of easy-to-solve one-dimensional problems. The numerical results provided by our method are very good and the techniques seem to be very promising.

One- and two-dimensional sublattices as preconditions for high-Tc superconductivity

International Nuclear Information System (INIS)

Krueger, E.

1989-01-01

In an earlier paper it was proposed describing superconductivity in the framework of a nonadiabatic Heisenberg model in order to interprete the outstanding symmetry proper ties of the (spin-dependent) Wannier functions in the conduction bands of superconductors. This new group-theoretical model suggests that Cooper pair formation can only be mediated by boson excitations carrying crystal-spin-angular momentum. While in the three-dimensionally isotropic lattices of the standard superconductors phonons are able to transport crystal-spin-angular momentum, this is not true for phonons propagating through the one- or two-dimensional Cu-O sublattices of the high-T c compounds. Therefore, if such an anisotropic material is superconducting, it is necessarily higher-energetic excitations (of well-defined symmetry) which mediate pair formation. This fact is proposed being responsible for the high transition temperatures of these compounds. (author)

High-definition resolution three-dimensional imaging systems in laparoscopic radical prostatectomy: randomized comparative study with high-definition resolution two-dimensional systems.

Science.gov (United States)

Kinoshita, Hidefumi; Nakagawa, Ken; Usui, Yukio; Iwamura, Masatsugu; Ito, Akihiro; Miyajima, Akira; Hoshi, Akio; Arai, Yoichi; Baba, Shiro; Matsuda, Tadashi

2015-08-01

Three-dimensional (3D) imaging systems have been introduced worldwide for surgical instrumentation. A difficulty of laparoscopic surgery involves converting two-dimensional (2D) images into 3D images and depth perception rearrangement. 3D imaging may remove the need for depth perception rearrangement and therefore have clinical benefits. We conducted a multicenter, open-label, randomized trial to compare the surgical outcome of 3D-high-definition (HD) resolution and 2D-HD imaging in laparoscopic radical prostatectomy (LRP), in order to determine whether an LRP under HD resolution 3D imaging is superior to that under HD resolution 2D imaging in perioperative outcome, feasibility, and fatigue. One-hundred twenty-two patients were randomly assigned to a 2D or 3D group. The primary outcome was time to perform vesicourethral anastomosis (VUA), which is technically demanding and may include a number of technical difficulties considered in laparoscopic surgeries. VUA time was not significantly shorter in the 3D group (26.7 min, mean) compared with the 2D group (30.1 min, mean) (p = 0.11, Student's t test). However, experienced surgeons and 3D-HD imaging were independent predictors for shorter VUA times (p = 0.000, p = 0.014, multivariate logistic regression analysis). Total pneumoperitoneum time was not different. No conversion case from 3D to 2D or LRP to open RP was observed. Fatigue was evaluated by a simulation sickness questionnaire and critical flicker frequency. Results were not different between the two groups. Subjective feasibility and satisfaction scores were significantly higher in the 3D group. Using a 3D imaging system in LRP may have only limited advantages in decreasing operation times over 2D imaging systems. However, the 3D system increased surgical feasibility and decreased surgeons' effort levels without inducing significant fatigue.

Backtrack Programming: A Computer-Based Approach to Group Problem Solving.

Science.gov (United States)

Scott, Michael D.; Bodaken, Edward M.

Backtrack problem-solving appears to be a viable alternative to current problem-solving methodologies. It appears to have considerable heuristic potential as a conceptual and operational framework for small group communication research, as well as functional utility for the student group in the small group class or the management team in the…

Cooperative simulation of lithography and topography for three-dimensional high-aspect-ratio etching

Science.gov (United States)

Ichikawa, Takashi; Yagisawa, Takashi; Furukawa, Shinichi; Taguchi, Takafumi; Nojima, Shigeki; Murakami, Sadatoshi; Tamaoki, Naoki

2018-06-01

A topography simulation of high-aspect-ratio etching considering transports of ions and neutrals is performed, and the mechanism of reactive ion etching (RIE) residues in three-dimensional corner patterns is revealed. Limited ion flux and CF2 diffusion from the wide space of the corner is found to have an effect on the RIE residues. Cooperative simulation of lithography and topography is used to solve the RIE residue problem.

Scalable Nearest Neighbor Algorithms for High Dimensional Data.

Science.gov (United States)

Muja, Marius; Lowe, David G

2014-11-01

For many computer vision and machine learning problems, large training sets are key for good performance. However, the most computationally expensive part of many computer vision and machine learning algorithms consists of finding nearest neighbor matches to high dimensional vectors that represent the training data. We propose new algorithms for approximate nearest neighbor matching and evaluate and compare them with previous algorithms. For matching high dimensional features, we find two algorithms to be the most efficient: the randomized k-d forest and a new algorithm proposed in this paper, the priority search k-means tree. We also propose a new algorithm for matching binary features by searching multiple hierarchical clustering trees and show it outperforms methods typically used in the literature. We show that the optimal nearest neighbor algorithm and its parameters depend on the data set characteristics and describe an automated configuration procedure for finding the best algorithm to search a particular data set. In order to scale to very large data sets that would otherwise not fit in the memory of a single machine, we propose a distributed nearest neighbor matching framework that can be used with any of the algorithms described in the paper. All this research has been released as an open source library called fast library for approximate nearest neighbors (FLANN), which has been incorporated into OpenCV and is now one of the most popular libraries for nearest neighbor matching.

Progress in high-dimensional percolation and random graphs

CERN Document Server

Heydenreich, Markus

2017-01-01

This text presents an engaging exposition of the active field of high-dimensional percolation that will likely provide an impetus for future work. With over 90 exercises designed to enhance the reader’s understanding of the material, as well as many open problems, the book is aimed at graduate students and researchers who wish to enter the world of this rich topic.  The text may also be useful in advanced courses and seminars, as well as for reference and individual study. Part I, consisting of 3 chapters, presents a general introduction to percolation, stating the main results, defining the central objects, and proving its main properties. No prior knowledge of percolation is assumed. Part II, consisting of Chapters 4–9, discusses mean-field critical behavior by describing the two main techniques used, namely, differential inequalities and the lace expansion. In Parts I and II, all results are proved, making this the first self-contained text discussing high-dimensiona l percolation.  Part III, consist...

A study of the one dimensional total generalised variation regularisation problem

KAUST Repository

Papafitsoros, Konstantinos

2015-03-01

© 2015 American Institute of Mathematical Sciences. In this paper we study the one dimensional second order total generalised variation regularisation (TGV) problem with L2 data fitting term. We examine the properties of this model and we calculate exact solutions using simple piecewise affine functions as data terms. We investigate how these solutions behave with respect to the TGV parameters and we verify our results using numerical experiments.

A study of the one dimensional total generalised variation regularisation problem

KAUST Repository

Papafitsoros, Konstantinos; Bredies, Kristian

2015-01-01

© 2015 American Institute of Mathematical Sciences. In this paper we study the one dimensional second order total generalised variation regularisation (TGV) problem with L2 data fitting term. We examine the properties of this model and we calculate exact solutions using simple piecewise affine functions as data terms. We investigate how these solutions behave with respect to the TGV parameters and we verify our results using numerical experiments.

Supporting Dynamic Quantization for High-Dimensional Data Analytics.

Science.gov (United States)

Guzun, Gheorghi; Canahuate, Guadalupe

2017-05-01

Similarity searches are at the heart of exploratory data analysis tasks. Distance metrics are typically used to characterize the similarity between data objects represented as feature vectors. However, when the dimensionality of the data increases and the number of features is large, traditional distance metrics fail to distinguish between the closest and furthest data points. Localized distance functions have been proposed as an alternative to traditional distance metrics. These functions only consider dimensions close to query to compute the distance/similarity. Furthermore, in order to enable interactive explorations of high-dimensional data, indexing support for ad-hoc queries is needed. In this work we set up to investigate whether bit-sliced indices can be used for exploratory analytics such as similarity searches and data clustering for high-dimensional big-data. We also propose a novel dynamic quantization called Query dependent Equi-Depth (QED) quantization and show its effectiveness on characterizing high-dimensional similarity. When applying QED we observe improvements in kNN classification accuracy over traditional distance functions. Gheorghi Guzun and Guadalupe Canahuate. 2017. Supporting Dynamic Quantization for High-Dimensional Data Analytics. In Proceedings of Ex-ploreDB'17, Chicago, IL, USA, May 14-19, 2017, 6 pages. https://doi.org/http://dx.doi.org/10.1145/3077331.3077336.

Clothing Problems of Upper Middle Socio-Economic Group ...

African Journals Online (AJOL)

This paper focuses on the clothing problems of affluent female consumers in the upper middle socioeconomic group, who have money to spend, as well as some access to retail fashion. Their clothing problems were discussed in relation to fashion leadership, fashion involvement, brand typologies, maintaining an interest in ...

High dimensional entanglement

CSIR Research Space (South Africa)

Mc

2012-07-01

Full Text Available stream_source_info McLaren_2012.pdf.txt stream_content_type text/plain stream_size 2190 Content-Encoding ISO-8859-1 stream_name McLaren_2012.pdf.txt Content-Type text/plain; charset=ISO-8859-1 High dimensional... entanglement M. McLAREN1,2, F.S. ROUX1 & A. FORBES1,2,3 1. CSIR National Laser Centre, PO Box 395, Pretoria 0001 2. School of Physics, University of the Stellenbosch, Private Bag X1, 7602, Matieland 3. School of Physics, University of Kwazulu...

Classical r-matrices and Poisson bracket structures on infinite-dimensional groups

International Nuclear Information System (INIS)

Aratyn, H.; Nissimov, E.; Pacheva, S.

1992-01-01

Starting with a canonical symplectic structure defined on the contangent bundle T * G we derive, via Dirac hamiltonian reduction, Poisson brackets (PBs) on an arbitrary infinite-dimensional group G (admitting central extension). The PB structures are given in terms of an r-operator kernel related to the two-cocycle of the underlying Lie algebra and satisfying a differential classical Yang-Baxter equation. The explicit expressions of the PBs among the group variables for the (N, 0) for N=0, 1, ..., 4 (super-) Virasoro groups and the group of area-preserving diffeomorphisms on the torus are presented. (orig.)

Characterization of differentially expressed genes using high-dimensional co-expression networks

DEFF Research Database (Denmark)

Coelho Goncalves de Abreu, Gabriel; Labouriau, Rodrigo S.

2010-01-01

We present a technique to characterize differentially expressed genes in terms of their position in a high-dimensional co-expression network. The set-up of Gaussian graphical models is used to construct representations of the co-expression network in such a way that redundancy and the propagation...... that allow to make effective inference in problems with high degree of complexity (e.g. several thousands of genes) and small number of observations (e.g. 10-100) as typically occurs in high throughput gene expression studies. Taking advantage of the internal structure of decomposable graphical models, we...... construct a compact representation of the co-expression network that allows to identify the regions with high concentration of differentially expressed genes. It is argued that differentially expressed genes located in highly interconnected regions of the co-expression network are less informative than...

Three-dimensional multiple reciprocity boundary element method for one-group neutron diffusion eigenvalue computations

International Nuclear Information System (INIS)

Itagaki, Masafumi; Sahashi, Naoki.

1996-01-01

The multiple reciprocity method (MRM) in conjunction with the boundary element method has been employed to solve one-group eigenvalue problems described by the three-dimensional (3-D) neutron diffusion equation. The domain integral related to the fission source is transformed into a series of boundary-only integrals, with the aid of the higher order fundamental solutions based on the spherical and the modified spherical Bessel functions. Since each degree of the higher order fundamental solutions in the 3-D cases has a singularity of order (1/r), the above series of boundary integrals requires additional terms which do not appear in the 2-D MRM formulation. The critical eigenvalue itself can be also described using only boundary integrals. Test calculations show that Wielandt's spectral shift technique guarantees rapid and stable convergence of 3-D MRM computations. (author)

Conflict Management in "Ad Hoc" Problem-Solving Groups: A Preliminary Investigation.

Science.gov (United States)

Wallace, Les; Baxter, Leslie

Full study of small group communication must include consideration of task and socio-emotional dimensions, especially in relation to group problem solving. Thirty small groups were tested for their reactions in various "ad hoc" conflict resolution situations. Instructions to the groups were (1) no problem-solving instructions (control),…

Three dimensional modeling of laterally loaded pile groups resting in sand

Directory of Open Access Journals (Sweden)

Amr Farouk Elhakim

2016-04-01

Full Text Available Many structures often carry lateral loads due to earth pressure, wind, earthquakes, wave action and ship impact. The accurate predictions of the load–displacement response of the pile group as well as the straining actions are needed for a safe and economic design. Most research focused on the behavior of laterally loaded single piles though piles are most frequently used in groups. Soil is modeled as an elastic-perfectly plastic model using the Mohr–Coulomb constitutive model. The three-dimensional Plaxis model is validated using load–displacement results from centrifuge tests of laterally loaded piles embedded in sand. This study utilizes three dimensional finite element modeling to better understand the main parameters that affect the response of laterally loaded pile groups (2 × 2 and 3 × 3 pile configurations including sand relative density, pile spacing (s = 2.5 D, 5 D and 8 D and pile location within the group. The fixity of the pile head affects its load–displacement under lateral loading. Typically, the pile head may be unrestrained (free head as the pile head is allowed to rotate, or restrained (fixed head condition where no pile head rotation is permitted. The analyses were performed for both free and fixed head conditions.

Localization of the solution of a one-dimensional one-phase Stefan problem

OpenAIRE

Cortazar, C.; Elgueta, M.; Primicerio, M.

1996-01-01

Studiamo la localizzazione, l'insieme dei punti di blow up ed alcuni aspetti della velocità di propagazione della frontiera libera di soluzioni di un problema di Stefan unidimensionale ad una fase. We study localization, the set of blow up points and some aspects of the speed of the free boundary of solutions of a one-dimensional, one-phase Stefan problem.

Group Problem Solving as a Zone of Proximal Development activity

Science.gov (United States)

Brewe, Eric

2006-12-01

Vygotsky described learning as a process, intertwined with development, which is strongly influenced by social interactions with others that are at differing developmental stages.i These interactions create a Zone of Proximal Development for each member of the interaction. Vygotsky’s notion of social constructivism is not only a theory of learning, but also of development. While teaching introductory physics in an interactive format, I have found manifestations of Vygotsky’s theory in my classroom. The source of evidence is a paired problem solution. A standard mechanics problem was solved by students in two classes as a homework assignment. Students handed in the homework and then solved the same problem in small groups. The solutions to both the group and individual problem were assessed by multiple reviewers. In many cases the group score was the same as the highest individual score in the group, but in some cases, the group score was higher than any individual score. For this poster, I will analyze the individual and group scores and focus on three groups solutions and video that provide evidence of learning through membership in a Zone of Proximal Development. Endnotes i L. Vygotsky -Mind and society: The development of higher mental processes. Cambridge, MA: Harvard University Press. (1978).

Boundary element methods applied to two-dimensional neutron diffusion problems

International Nuclear Information System (INIS)

Itagaki, Masafumi

1985-01-01

The Boundary element method (BEM) has been applied to two-dimensional neutron diffusion problems. The boundary integral equation and its discretized form have been derived. Some numerical techniques have been developed, which can be applied to critical and fixed-source problems including multi-region ones. Two types of test programs have been developed according to whether the 'zero-determinant search' or the 'source iteration' technique is adopted for criticality search. Both programs require only the fluxes and currents on boundaries as the unknown variables. The former allows a reduction in computing time and memory in comparison with the finite element method (FEM). The latter is not always efficient in terms of computing time due to the domain integral related to the inhomogeneous source term; however, this domain integral can be replaced by the equivalent boundary integral for a region with a non-multiplying medium or with a uniform source, resulting in a significant reduction in computing time. The BEM, as well as the FEM, is well suited for solving irregular geometrical problems for which the finite difference method (FDM) is unsuited. The BEM also solves problems with infinite domains, which cannot be solved by the ordinary FEM and FDM. Some simple test calculations are made to compare the BEM with the FEM and FDM, and discussions are made concerning the relative merits of the BEM and problems requiring future solution. (author)

A Mindfulness-Based Cognitive Psychoeducational Group Manual for Problem Gambling

Science.gov (United States)

Cormier, Abigail; McBride, Dawn Lorraine

2012-01-01

This project provides a comprehensive overview of the research literature on problem gambling in adults and includes a detailed mindfulness-based psychoeducational group manual for problem gambling, complete with an extensive group counselling consent form, assessment and screening protocols, 10 user-friendly lesson plans, templates for a…

Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data.

Science.gov (United States)

Dazard, Jean-Eudes; Rao, J Sunil

2012-07-01

The paper addresses a common problem in the analysis of high-dimensional high-throughput "omics" data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel "similarity statistic"-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called 'MVR' ('Mean-Variance Regularization'), downloadable from the CRAN website.

Continuity of the direct and inverse problems in one-dimensional scattering theory and numerical solution of the inverse problem

International Nuclear Information System (INIS)

Moura, C.A. de.

1976-09-01

We propose an algorithm for computing the potential V(x) associated to the one-dimensional Schroedinger operator E identical to - d 2 /dx 2 + V(x) -infinite < x< infinite from knowledge of the S.matrix, more exactly, of one of the reelection coefficients. The convergence of the algorithm is guaranteed by the stability results obtained for both the direct and inverse problems

Clustering high dimensional data using RIA

Energy Technology Data Exchange (ETDEWEB)

Aziz, Nazrina [School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah (Malaysia)

2015-05-15

Clustering may simply represent a convenient method for organizing a large data set so that it can easily be understood and information can efficiently be retrieved. However, identifying cluster in high dimensionality data sets is a difficult task because of the curse of dimensionality. Another challenge in clustering is some traditional functions cannot capture the pattern dissimilarity among objects. In this article, we used an alternative dissimilarity measurement called Robust Influence Angle (RIA) in the partitioning method. RIA is developed using eigenstructure of the covariance matrix and robust principal component score. We notice that, it can obtain cluster easily and hence avoid the curse of dimensionality. It is also manage to cluster large data sets with mixed numeric and categorical value.

An Improved Ensemble Learning Method for Classifying High-Dimensional and Imbalanced Biomedicine Data.

Science.gov (United States)

Yu, Hualong; Ni, Jun

2014-01-01

Training classifiers on skewed data can be technically challenging tasks, especially if the data is high-dimensional simultaneously, the tasks can become more difficult. In biomedicine field, skewed data type often appears. In this study, we try to deal with this problem by combining asymmetric bagging ensemble classifier (asBagging) that has been presented in previous work and an improved random subspace (RS) generation strategy that is called feature subspace (FSS). Specifically, FSS is a novel method to promote the balance level between accuracy and diversity of base classifiers in asBagging. In view of the strong generalization capability of support vector machine (SVM), we adopt it to be base classifier. Extensive experiments on four benchmark biomedicine data sets indicate that the proposed ensemble learning method outperforms many baseline approaches in terms of Accuracy, F-measure, G-mean and AUC evaluation criterions, thus it can be regarded as an effective and efficient tool to deal with high-dimensional and imbalanced biomedical data.

The nodal discrete-ordinate transport calculation of anisotropy scattering problem in three-dimensional cartesian geometry

International Nuclear Information System (INIS)

Wu Hongchun; Xie Zhongsheng; Zhu Xuehua

1994-01-01

The nodal discrete-ordinate transport calculating model of anisotropy scattering problem in three-dimensional cartesian geometry is given. The computing code NOTRAN/3D has been encoded and the satisfied conclusion is gained

Asymptotically Honest Confidence Regions for High Dimensional

DEFF Research Database (Denmark)

Caner, Mehmet; Kock, Anders Bredahl

While variable selection and oracle inequalities for the estimation and prediction error have received considerable attention in the literature on high-dimensional models, very little work has been done in the area of testing and construction of confidence bands in high-dimensional models. However...... develop an oracle inequality for the conservative Lasso only assuming the existence of a certain number of moments. This is done by means of the Marcinkiewicz-Zygmund inequality which in our context provides sharper bounds than Nemirovski's inequality. As opposed to van de Geer et al. (2014) we allow...

Continuous Energy, Multi-Dimensional Transport Calculations for Problem Dependent Resonance Self-Shielding

International Nuclear Information System (INIS)

Downar, T.

2009-01-01

The overall objective of the work here has been to eliminate the approximations used in current resonance treatments by developing continuous energy multi-dimensional transport calculations for problem dependent self-shielding calculations. The work here builds on the existing resonance treatment capabilities in the ORNL SCALE code system. The overall objective of the work here has been to eliminate the approximations used in current resonance treatments by developing continuous energy multidimensional transport calculations for problem dependent self-shielding calculations. The work here builds on the existing resonance treatment capabilities in the ORNL SCALE code system. Specifically, the methods here utilize the existing continuous energy SCALE5 module, CENTRM, and the multi-dimensional discrete ordinates solver, NEWT to develop a new code, CENTRM( ) NEWT. The work here addresses specific theoretical limitations in existing CENTRM resonance treatment, as well as investigates advanced numerical and parallel computing algorithms for CENTRM and NEWT in order to reduce the computational burden. The result of the work here will be a new computer code capable of performing problem dependent self-shielding analysis for both existing and proposed GENIV fuel designs. The objective of the work was to have an immediate impact on the safety analysis of existing reactors through improvements in the calculation of fuel temperature effects, as well as on the analysis of more sophisticated GENIV/NGNP systems through improvements in the depletion/transmutation of actinides for Advanced Fuel Cycle Initiatives.

Group invariance in engineering boundary value problems

CERN Document Server

Seshadri, R

1985-01-01

REFEREN CES . 156 9 Transforma.tion of a Boundary Value Problem to an Initial Value Problem . 157 9.0 Introduction . 157 9.1 Blasius Equation in Boundary Layer Flow . 157 9.2 Longitudinal Impact of Nonlinear Viscoplastic Rods . 163 9.3 Summary . 168 REFERENCES . . . . . . . . . . . . . . . . . . 168 . 10 From Nonlinear to Linear Differential Equa.tions Using Transformation Groups. . . . . . . . . . . . . . 169 . 10.1 From Nonlinear to Linear Differential Equations . 170 10.2 Application to Ordinary Differential Equations -Bernoulli's Equation . . . . . . . . . . . 173 10.3 Application to Partial Differential Equations -A Nonlinear Chemical Exchange Process . 178 10.4 Limitations of the Inspectional Group Method . 187 10.5 Summary . 188 REFERENCES . . . . 188 11 Miscellaneous Topics . 190 11.1 Reduction of Differential Equations to Algebraic Equations 190 11.2 Reduction of Order of an Ordinary Differential Equation . 191 11.3 Transformat.ion From Ordinary to Partial Differential Equations-Search for First Inte...

HDclassif : An R Package for Model-Based Clustering and Discriminant Analysis of High-Dimensional Data

Directory of Open Access Journals (Sweden)

Laurent Berge

2012-01-01

Full Text Available This paper presents the R package HDclassif which is devoted to the clustering and the discriminant analysis of high-dimensional data. The classification methods proposed in the package result from a new parametrization of the Gaussian mixture model which combines the idea of dimension reduction and model constraints on the covariance matrices. The supervised classification method using this parametrization is called high dimensional discriminant analysis (HDDA. In a similar manner, the associated clustering method iscalled high dimensional data clustering (HDDC and uses the expectation-maximization algorithm for inference. In order to correctly t the data, both methods estimate the specific subspace and the intrinsic dimension of the groups. Due to the constraints on the covariance matrices, the number of parameters to estimate is significantly lower than other model-based methods and this allows the methods to be stable and efficient in high dimensions. Two introductory examples illustrated with R codes allow the user to discover the hdda and hddc functions. Experiments on simulated and real datasets also compare HDDC and HDDA with existing classification methods on high-dimensional datasets. HDclassif is a free software and distributed under the general public license, as part of the R software project.

Multi-group transport methods for high-resolution neutron activation analysis

International Nuclear Information System (INIS)

Burns, K. A.; Smith, L. E.; Gesh, C. J.; Shaver, M. W.

2009-01-01

The accurate and efficient simulation of coupled neutron-photon problems is necessary for several important radiation detection applications. Examples include the detection of nuclear threats concealed in cargo containers and prompt gamma neutron activation analysis for nondestructive determination of elemental composition of unknown samples. In these applications, high-resolution gamma-ray spectrometers are used to preserve as much information as possible about the emitted photon flux, which consists of both continuum and characteristic gamma rays with discrete energies. Monte Carlo transport is the most commonly used modeling tool for this type of problem, but computational times for many problems can be prohibitive. This work explores the use of multi-group deterministic methods for the simulation of neutron activation problems. Central to this work is the development of a method for generating multi-group neutron-photon cross-sections in a way that separates the discrete and continuum photon emissions so that the key signatures in neutron activation analysis (i.e., the characteristic line energies) are preserved. The mechanics of the cross-section preparation method are described and contrasted with standard neutron-gamma cross-section sets. These custom cross-sections are then applied to several benchmark problems. Multi-group results for neutron and photon flux are compared to MCNP results. Finally, calculated responses of high-resolution spectrometers are compared. Preliminary findings show promising results when compared to MCNP. A detailed discussion of the potential benefits and shortcomings of the multi-group-based approach, in terms of accuracy, and computational efficiency, is provided. (authors)

Assessing the Internal Dynamics of Mathematical Problem Solving in Small Groups.

Science.gov (United States)

Artzt, Alice F.; Armour-Thomas, Eleanor

The purpose of this exploratory study was to examine the problem-solving behaviors and perceptions of (n=27) seventh-grade students as they worked on solving a mathematical problem within a small-group setting. An assessment system was developed that allowed for this analysis. To assess problem-solving behaviors within a small group a Group…

Riemann surfaces, Clifford algebras and infinite dimensional groups

International Nuclear Information System (INIS)

Carey, A.L.; Eastwood, M.G.; Hannabuss, K.C.

1990-01-01

We introduce of class of Riemann surfaces which possess a fixed point free involution and line bundles over these surfaces with which we can associate an infinite dimensional Clifford algebra. Acting by automorphisms of this algebra is a 'gauge' group of meromorphic functions on the Riemann surface. There is a natural Fock representation of the Clifford algebra and an associated projective representation of this group of meromorphic functions in close analogy with the construction of the basic representation of Kac-Moody algebras via a Fock representation of the Fermion algebra. In the genus one case we find a form of vertex operator construction which allows us to prove a version of the Boson-Fermion correspondence. These results are motivated by the analysis of soliton solutions of the Landau-Lifshitz equation and are rather distinct from recent developments in quantum field theory on Riemann surfaces. (orig.)

16-dimensional smooth projective planes with large collineation groups

OpenAIRE

Bödi, Richard

1998-01-01

Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch) Smooth projective planes are projective planes defined on smooth manifolds (i.e. the set of points and the set of lines are smooth manifolds) such that the geometric operations of join and intersection are smooth. A systematic study of such planes and of their collineation groups can be found in previous works of the author. We prove in this paper that a 16-dimensional smooth projective plane which admits a ...

Modulated Structures of Homologous Compounds In MO 3(ZnO) m( M=In, Ga; m=Integer) Described by Four-Dimensional Superspace Group

Science.gov (United States)

Li, Chunfei; Bando, Yoshio; Nakamura, Masaki; Onoda, Mitsuko; Kimizuka, Noboru

1998-09-01

The modulated structures appearing in the homologous compounds InMO3(ZnO)m(M=In, Ga;m=integer) were observed by using a high-resoultion transmission electron microscope and are described based on a four-dimensional superspace group. The electron diffraction patterns for compounds withmlarger than 6 reveal extra spots, indicating the formation of a modulated structure. The subcell structures form=odd and even numbers are assigned to be either monoclinic or orthorhombic, respectively. On the other hand, extra spots can be indexed by one-dimensional modulated structure. The possible space groups for the subcell structure areCm,C2, andC2/mform=odd numbers, while those form=even numbers areCcm21andCcmm, respectively. Then, corresponding possible superspace groups are assigned to bePC2s,PCmoverline1, andPC2/msoverline1for oddmnumbers andPCcm211overline1overline1andPCcmm1overline11for evenmnumbers. Based on the superspace group determination, a structure model for a one-dimensional modulated structure is proposed.

Uniqueness in some higher order elliptic boundary value problems in n dimensional domains

Directory of Open Access Journals (Sweden)

C.-P. Danet

2011-07-01

Full Text Available We develop maximum principles for several P functions which are defined on solutions to equations of fourth and sixth order (including a equation which arises in plate theory and bending of cylindrical shells. As a consequence, we obtain uniqueness results for fourth and sixth order boundary value problems in arbitrary n dimensional domains.

Explicit formulation of a nodal transport method for discrete ordinates calculations in two-dimensional fixed-source problems

Energy Technology Data Exchange (ETDEWEB)

Tres, Anderson [Universidade Federal do Rio Grande do Sul, Porto Alegre, RS (Brazil). Programa de Pos-Graduacao em Matematica Aplicada; Becker Picoloto, Camila [Universidade Federal do Rio Grande do Sul, Porto Alegre, RS (Brazil). Programa de Pos-Graduacao em Engenharia Mecanica; Prolo Filho, Joao Francisco [Universidade Federal do Rio Grande do Sul, Porto Alegre, RS (Brazil). Inst de Matematica, Estatistica e Fisica; Dias da Cunha, Rudnei; Basso Barichello, Liliane [Universidade Federal do Rio Grande do Sul, Porto Alegre, RS (Brazil). Inst de Matematica

2014-04-15

In this work a study of two-dimensional fixed-source neutron transport problems, in Cartesian geometry, is reported. The approach reduces the complexity of the multidimensional problem using a combination of nodal schemes and the Analytical Discrete Ordinates Method (ADO). The unknown leakage terms on the boundaries that appear from the use of the derivation of the nodal scheme are incorporated to the problem source term, such as to couple the one-dimensional integrated solutions, made explicit in terms of the x and y spatial variables. The formulation leads to a considerable reduction of the order of the associated eigenvalue problems when combined with the usual symmetric quadratures, thereby providing solutions that have a higher degree of computational efficiency. Reflective-type boundary conditions are introduced to represent the domain on a simpler form than that previously considered in connection with the ADO method. Numerical results obtained with the technique are provided and compared to those present in the literature. (orig.)

Modeling High-Dimensional Multichannel Brain Signals

KAUST Repository

Hu, Lechuan; Fortin, Norbert J.; Ombao, Hernando

2017-01-01

aspects: first, there are major statistical and computational challenges for modeling and analyzing high-dimensional multichannel brain signals; second, there is no set of universally agreed measures for characterizing connectivity. To model multichannel

Energy Efficient MAC Scheme for Wireless Sensor Networks with High-Dimensional Data Aggregate

Directory of Open Access Journals (Sweden)

Seokhoon Kim

2015-01-01

Full Text Available This paper presents a novel and sustainable medium access control (MAC scheme for wireless sensor network (WSN systems that process high-dimensional aggregated data. Based on a preamble signal and buffer threshold analysis, it maximizes the energy efficiency of the wireless sensor devices which have limited energy resources. The proposed group management MAC (GM-MAC approach not only sets the buffer threshold value of a sensor device to be reciprocal to the preamble signal but also sets a transmittable group value to each sensor device by using the preamble signal of the sink node. The primary difference between the previous and the proposed approach is that existing state-of-the-art schemes use duty cycle and sleep mode to save energy consumption of individual sensor devices, whereas the proposed scheme employs the group management MAC scheme for sensor devices to maximize the overall energy efficiency of the whole WSN systems by minimizing the energy consumption of sensor devices located near the sink node. Performance evaluations show that the proposed scheme outperforms the previous schemes in terms of active time of sensor devices, transmission delay, control overhead, and energy consumption. Therefore, the proposed scheme is suitable for sensor devices in a variety of wireless sensor networking environments with high-dimensional data aggregate.

Electrons, pseudoparticles, and quasiparticles in the one-dimensional many-electron problem

International Nuclear Information System (INIS)

Carmelo, J.M.; Castro Neto, A.H.

1996-01-01

We generalize the concept of quasiparticle for one-dimensional (1D) interacting electronic systems. The ↑ and ↓ quasiparticles recombine the pseudoparticle colors c and s (charge and spin at zero-magnetic field) and are constituted by one many-pseudoparticle topological-momentum shift and one or two pseudoparticles. These excitations cannot be separated. We consider the case of the Hubbard chain. We show that the low-energy electron-quasiparticle transformation has a singular character which justifies the perturbative and nonperturbative nature of the quantum problem in the pseudoparticle and electronic basis, respectively. This follows from the absence of zero-energy electron-quasiparticle overlap in 1D. The existence of Fermi-surface quasiparticles both in 1D and three dimensional (3D) many-electron systems suggests their existence in quantum liquids in dimensions 1 1 or whether it becomes finite as soon as we leave 1D remains an unsolved question. copyright 1996 The American Physical Society

A sparse grid based method for generative dimensionality reduction of high-dimensional data

Science.gov (United States)

Bohn, Bastian; Garcke, Jochen; Griebel, Michael

2016-03-01

Generative dimensionality reduction methods play an important role in machine learning applications because they construct an explicit mapping from a low-dimensional space to the high-dimensional data space. We discuss a general framework to describe generative dimensionality reduction methods, where the main focus lies on a regularized principal manifold learning variant. Since most generative dimensionality reduction algorithms exploit the representer theorem for reproducing kernel Hilbert spaces, their computational costs grow at least quadratically in the number n of data. Instead, we introduce a grid-based discretization approach which automatically scales just linearly in n. To circumvent the curse of dimensionality of full tensor product grids, we use the concept of sparse grids. Furthermore, in real-world applications, some embedding directions are usually more important than others and it is reasonable to refine the underlying discretization space only in these directions. To this end, we employ a dimension-adaptive algorithm which is based on the ANOVA (analysis of variance) decomposition of a function. In particular, the reconstruction error is used to measure the quality of an embedding. As an application, the study of large simulation data from an engineering application in the automotive industry (car crash simulation) is performed.

Pattern-set generation algorithm for the one-dimensional multiple stock sizes cutting stock problem

Science.gov (United States)

Cui, Yaodong; Cui, Yi-Ping; Zhao, Zhigang

2015-09-01

A pattern-set generation algorithm (PSG) for the one-dimensional multiple stock sizes cutting stock problem (1DMSSCSP) is presented. The solution process contains two stages. In the first stage, the PSG solves the residual problems repeatedly to generate the patterns in the pattern set, where each residual problem is solved by the column-generation approach, and each pattern is generated by solving a single large object placement problem. In the second stage, the integer linear programming model of the 1DMSSCSP is solved using a commercial solver, where only the patterns in the pattern set are considered. The computational results of benchmark instances indicate that the PSG outperforms existing heuristic algorithms and rivals the exact algorithm in solution quality.

Solution of the two-dimensional space-time reactor kinetics equation by a locally one-dimensional method

International Nuclear Information System (INIS)

Chen, G.S.; Christenson, J.M.

1985-01-01

In this paper, the authors present some initial results from an investigation of the application of a locally one-dimensional (LOD) finite difference method to the solution of the two-dimensional, two-group reactor kinetics equations. Although the LOD method is relatively well known, it apparently has not been previously applied to the space-time kinetics equations. In this investigation, the LOD results were benchmarked against similar computational results (using the same computing environment, the same programming structure, and the same sample problems) obtained by the TWIGL program. For all of the problems considered, the LOD method provided accurate results in one-half to one-eight of the time required by the TWIGL program

Approximation of High-Dimensional Rank One Tensors

KAUST Repository

Bachmayr, Markus

2013-11-12

Many real world problems are high-dimensional in that their solution is a function which depends on many variables or parameters. This presents a computational challenge since traditional numerical techniques are built on model classes for functions based solely on smoothness. It is known that the approximation of smoothness classes of functions suffers from the so-called \\'curse of dimensionality\\'. Avoiding this curse requires new model classes for real world functions that match applications. This has led to the introduction of notions such as sparsity, variable reduction, and reduced modeling. One theme that is particularly common is to assume a tensor structure for the target function. This paper investigates how well a rank one function f(x 1,...,x d)=f 1(x 1)⋯f d(x d), defined on Ω=[0,1]d can be captured through point queries. It is shown that such a rank one function with component functions f j in W∞ r([0,1]) can be captured (in L ∞) to accuracy O(C(d,r)N -r) from N well-chosen point evaluations. The constant C(d,r) scales like d dr. The queries in our algorithms have two ingredients, a set of points built on the results from discrepancy theory and a second adaptive set of queries dependent on the information drawn from the first set. Under the assumption that a point z∈Ω with nonvanishing f(z) is known, the accuracy improves to O(dN -r). © 2013 Springer Science+Business Media New York.

Approximation of High-Dimensional Rank One Tensors

KAUST Repository

Bachmayr, Markus; Dahmen, Wolfgang; DeVore, Ronald; Grasedyck, Lars

2013-01-01

Many real world problems are high-dimensional in that their solution is a function which depends on many variables or parameters. This presents a computational challenge since traditional numerical techniques are built on model classes for functions based solely on smoothness. It is known that the approximation of smoothness classes of functions suffers from the so-called 'curse of dimensionality'. Avoiding this curse requires new model classes for real world functions that match applications. This has led to the introduction of notions such as sparsity, variable reduction, and reduced modeling. One theme that is particularly common is to assume a tensor structure for the target function. This paper investigates how well a rank one function f(x 1,...,x d)=f 1(x 1)⋯f d(x d), defined on Ω=[0,1]d can be captured through point queries. It is shown that such a rank one function with component functions f j in W∞ r([0,1]) can be captured (in L ∞) to accuracy O(C(d,r)N -r) from N well-chosen point evaluations. The constant C(d,r) scales like d dr. The queries in our algorithms have two ingredients, a set of points built on the results from discrepancy theory and a second adaptive set of queries dependent on the information drawn from the first set. Under the assumption that a point z∈Ω with nonvanishing f(z) is known, the accuracy improves to O(dN -r). © 2013 Springer Science+Business Media New York.

On mixed derivatives type high dimensional multi-term fractional partial differential equations approximate solutions

Science.gov (United States)

Talib, Imran; Belgacem, Fethi Bin Muhammad; Asif, Naseer Ahmad; Khalil, Hammad

2017-01-01

In this research article, we derive and analyze an efficient spectral method based on the operational matrices of three dimensional orthogonal Jacobi polynomials to solve numerically the mixed partial derivatives type multi-terms high dimensions generalized class of fractional order partial differential equations. We transform the considered fractional order problem to an easily solvable algebraic equations with the aid of the operational matrices. Being easily solvable, the associated algebraic system leads to finding the solution of the problem. Some test problems are considered to confirm the accuracy and validity of the proposed numerical method. The convergence of the method is ensured by comparing our Matlab software simulations based obtained results with the exact solutions in the literature, yielding negligible errors. Moreover, comparative results discussed in the literature are extended and improved in this study.

One-dimensional central-force problem, including radiation reaction

International Nuclear Information System (INIS)

Kasher, J.C.

1976-01-01

Two equal masses of equal charge magnitude (either attractive or repulsive) are held a certain distance apart for their entire past history. AT t = 0 one of them is either started from rest or given an initial velocity toward or away from the other charge. When the Dirac radiation-reaction force is included in the force equation, our Taylor-series numerical calculations lead to two types of nonphysical results for both the attractive and repulsive cases. In the attractive case, the moving charge either stops and moves back out to infinity, or violates energy conservation as it nears collision with the fixed charge. For the repulsive charges, the moving particle either eventually approaches and collides with the fixed one, or violates energy conservation as it goes out to infinity. These results lead us to conclude that the Lorentz-Dirac equation is not valid for the one-dimensional central-force problem

The Group Evacuation Behavior Based on Fire Effect in the Complicated Three-Dimensional Space

Directory of Open Access Journals (Sweden)

Jun Hu

2014-01-01

Full Text Available In order to effectively depict the group evacuation behavior in the complicated three-dimensional space, a novel pedestrian flow model is proposed with three-dimensional cellular automata. In this model the calculation methods of floor field and fire gain are elaborated at first, and the transition gain of target position at the next moment is defined. Then, in consideration of pedestrian intimacy and velocity change, the group evacuation strategy and evolution rules are given. Finally, the experiments were conducted with the simulation platform to study the relationships of evacuation time, pedestrian density, average system velocity, and smoke spreading velocity. The results had shown that large-scale group evacuation should be avoided, and in case of large pedestrian density, the shortest route of evacuation strategy would extend system evacuation time.

Kleinian groups and uniformization in examples and problems

CERN Document Server

Krushkal′, S L

1986-01-01

Aimed at researchers, graduate students and undergraduates alike, this book presents a unified exposition of all the main areas and methods of the theory of Kleinian groups and the theory of uniformization of manifolds. The past 20 years have seen a rejuvenation of the field, due to the development of powerful new methods in topology, the theory of functions of several complex variables, and the theory of quasiconformal mappings. Thus this new book should provide a valuable resource, listing the basic facts regarding Kleinian groups and serving as a general guide to the primary literature, particularly the Russian literature in the field. In addition, the book includes a large number of examples, problems, and unsolved problems, many of them presented for the first time.

Two-Dimensional High Definition Versus Three-Dimensional Endoscopy in Endonasal Skull Base Surgery: A Comparative Preclinical Study.

Science.gov (United States)

Rampinelli, Vittorio; Doglietto, Francesco; Mattavelli, Davide; Qiu, Jimmy; Raffetti, Elena; Schreiber, Alberto; Villaret, Andrea Bolzoni; Kucharczyk, Walter; Donato, Francesco; Fontanella, Marco Maria; Nicolai, Piero

2017-09-01

Three-dimensional (3D) endoscopy has been recently introduced in endonasal skull base surgery. Only a relatively limited number of studies have compared it to 2-dimensional, high definition technology. The objective was to compare, in a preclinical setting for endonasal endoscopic surgery, the surgical maneuverability of 2-dimensional, high definition and 3D endoscopy. A group of 68 volunteers, novice and experienced surgeons, were asked to perform 2 tasks, namely simulating grasping and dissection surgical maneuvers, in a model of the nasal cavities. Time to complete the tasks was recorded. A questionnaire to investigate subjective feelings during tasks was filled by each participant. In 25 subjects, the surgeons' movements were continuously tracked by a magnetic-based neuronavigator coupled with dedicated software (ApproachViewer, part of GTx-UHN) and the recorded trajectories were analyzed by comparing jitter, sum of square differences, and funnel index. Total execution time was significantly lower with 3D technology (P < 0.05) in beginners and experts. Questionnaires showed that beginners preferred 3D endoscopy more frequently than experts. A minority (14%) of beginners experienced discomfort with 3D endoscopy. Analysis of jitter showed a trend toward increased effectiveness of surgical maneuvers with 3D endoscopy. Sum of square differences and funnel index analyses documented better values with 3D endoscopy in experts. In a preclinical setting for endonasal skull base surgery, 3D technology appears to confer an advantage in terms of time of execution and precision of surgical maneuvers. Copyright © 2017 Elsevier Inc. All rights reserved.

Selecting Optimal Feature Set in High-Dimensional Data by Swarm Search

Directory of Open Access Journals (Sweden)

Simon Fong

2013-01-01

Full Text Available Selecting the right set of features from data of high dimensionality for inducing an accurate classification model is a tough computational challenge. It is almost a NP-hard problem as the combinations of features escalate exponentially as the number of features increases. Unfortunately in data mining, as well as other engineering applications and bioinformatics, some data are described by a long array of features. Many feature subset selection algorithms have been proposed in the past, but not all of them are effective. Since it takes seemingly forever to use brute force in exhaustively trying every possible combination of features, stochastic optimization may be a solution. In this paper, we propose a new feature selection scheme called Swarm Search to find an optimal feature set by using metaheuristics. The advantage of Swarm Search is its flexibility in integrating any classifier into its fitness function and plugging in any metaheuristic algorithm to facilitate heuristic search. Simulation experiments are carried out by testing the Swarm Search over some high-dimensional datasets, with different classification algorithms and various metaheuristic algorithms. The comparative experiment results show that Swarm Search is able to attain relatively low error rates in classification without shrinking the size of the feature subset to its minimum.

Inference for High-dimensional Differential Correlation Matrices.

Science.gov (United States)

Cai, T Tony; Zhang, Anru

2016-01-01

Motivated by differential co-expression analysis in genomics, we consider in this paper estimation and testing of high-dimensional differential correlation matrices. An adaptive thresholding procedure is introduced and theoretical guarantees are given. Minimax rate of convergence is established and the proposed estimator is shown to be adaptively rate-optimal over collections of paired correlation matrices with approximately sparse differences. Simulation results show that the procedure significantly outperforms two other natural methods that are based on separate estimation of the individual correlation matrices. The procedure is also illustrated through an analysis of a breast cancer dataset, which provides evidence at the gene co-expression level that several genes, of which a subset has been previously verified, are associated with the breast cancer. Hypothesis testing on the differential correlation matrices is also considered. A test, which is particularly well suited for testing against sparse alternatives, is introduced. In addition, other related problems, including estimation of a single sparse correlation matrix, estimation of the differential covariance matrices, and estimation of the differential cross-correlation matrices, are also discussed.

Three-dimensional Modeling of Type Ia Supernova Explosions

Science.gov (United States)

Khokhlov, Alexei

2001-06-01

A deflagration explosion of a Type Ia Supernova (SNIa) is studied using three-dimensional, high-resolution, adaptive mesh refinement fluid dynamic calculations. Deflagration speed in an exploding Chandrasekhar-mass carbon-oxygen white dwarf (WD) grows exponentially, reaches approximately 30the speed of sound, and then declines due to a WD expansion. Outermost layers of the WD remain unburned. The explosion energy is comparable to that of a Type Ia supernova. The freezing of turbulent motions by expansion appears to be a crucial physical mechanism regulating the strength of a supernova explosion. In contrast to one-dimensional models, three-dimensional calculations predict the formation of Si-group elements and pockets of unburned CO in the middle and in central regions of a supernova ejecta. This, and the presence of unburned outer layer of carbon-oxygen may pose problems for SNIa spectra. Explosion sensitivity to initial conditions and its relation to a diversity of SNIa is discussed.

Invert 1.0: A program for solving the nonlinear inverse heat conduction problem for one-dimensional solids

International Nuclear Information System (INIS)

Snider, D.M.

1981-02-01

INVERT 1.0 is a digital computer program written in FORTRAN IV which calculates the surface heat flux of a one-dimensional solid using an interior-measured temperature and a physical description of the solid. By using two interior-measured temperatures, INVERT 1.0 can provide a solution for the heat flux at two surfaces, the heat flux at a boundary and the time dependent power, or the heat flux at a boundary and the time varying thermal conductivity of a material composing the solid. The analytical solution to inversion problem is described for the one-dimensional cylinder, sphere, or rectangular slab. The program structure, input instructions, and sample problems demonstrating the accuracy of the solution technique are included

Matrix correlations for high-dimensional data: The modified RV-coefficient

NARCIS (Netherlands)

Smilde, A.K.; Kiers, H.A.L.; Bijlsma, S.; Rubingh, C.M.; Erk, M.J. van

2009-01-01

Motivation: Modern functional genomics generates high-dimensional datasets. It is often convenient to have a single simple number characterizing the relationship between pairs of such high-dimensional datasets in a comprehensive way. Matrix correlations are such numbers and are appealing since they

Explorations on High Dimensional Landscapes: Spin Glasses and Deep Learning

Science.gov (United States)

Sagun, Levent

This thesis deals with understanding the structure of high-dimensional and non-convex energy landscapes. In particular, its focus is on the optimization of two classes of functions: homogeneous polynomials and loss functions that arise in machine learning. In the first part, the notion of complexity of a smooth, real-valued function is studied through its critical points. Existing theoretical results predict that certain random functions that are defined on high dimensional domains have a narrow band of values whose pre-image contains the bulk of its critical points. This section provides empirical evidence for convergence of gradient descent to local minima whose energies are near the predicted threshold justifying the existing asymptotic theory. Moreover, it is empirically shown that a similar phenomenon may hold for deep learning loss functions. Furthermore, there is a comparative analysis of gradient descent and its stochastic version showing that in high dimensional regimes the latter is a mere speedup. The next study focuses on the halting time of an algorithm at a given stopping condition. Given an algorithm, the normalized fluctuations of the halting time follow a distribution that remains unchanged even when the input data is sampled from a new distribution. Two qualitative classes are observed: a Gumbel-like distribution that appears in Google searches, human decision times, and spin glasses and a Gaussian-like distribution that appears in conjugate gradient method, deep learning with MNIST and random input data. Following the universality phenomenon, the Hessian of the loss functions of deep learning is studied. The spectrum is seen to be composed of two parts, the bulk which is concentrated around zero, and the edges which are scattered away from zero. Empirical evidence is presented for the bulk indicating how over-parametrized the system is, and for the edges that depend on the input data. Furthermore, an algorithm is proposed such that it would

Approximating high-dimensional dynamics by barycentric coordinates with linear programming

Energy Technology Data Exchange (ETDEWEB)

Hirata, Yoshito, E-mail: yoshito@sat.t.u-tokyo.ac.jp; Aihara, Kazuyuki; Suzuki, Hideyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); CREST, JST, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012 (Japan); Shiro, Masanori [Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); Mathematical Neuroinformatics Group, Advanced Industrial Science and Technology, Tsukuba, Ibaraki 305-8568 (Japan); Takahashi, Nozomu; Mas, Paloma [Center for Research in Agricultural Genomics (CRAG), Consorci CSIC-IRTA-UAB-UB, Barcelona 08193 (Spain)

2015-01-15

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.

Approximating high-dimensional dynamics by barycentric coordinates with linear programming.

Science.gov (United States)

Hirata, Yoshito; Shiro, Masanori; Takahashi, Nozomu; Aihara, Kazuyuki; Suzuki, Hideyuki; Mas, Paloma

2015-01-01

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.

Approximating high-dimensional dynamics by barycentric coordinates with linear programming

International Nuclear Information System (INIS)

Hirata, Yoshito; Aihara, Kazuyuki; Suzuki, Hideyuki; Shiro, Masanori; Takahashi, Nozomu; Mas, Paloma

2015-01-01

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data

Restoration of dimensional reduction in the random-field Ising model at five dimensions

Science.gov (United States)

Fytas, Nikolaos G.; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas

2017-04-01

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D -2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D =5 . We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3 ≤D equality at all studied dimensions.

Sub-cell balanced nodal expansion methods using S4 eigenfunctions for multi-group SN transport problems in slab geometry

International Nuclear Information System (INIS)

Hong, Ser Gi; Lee, Deokjung

2015-01-01

A highly accurate S 4 eigenfunction-based nodal method has been developed to solve multi-group discrete ordinate neutral particle transport problems with a linearly anisotropic scattering in slab geometry. The new method solves the even-parity form of discrete ordinates transport equation with an arbitrary S N order angular quadrature using two sub-cell balance equations and the S 4 eigenfunctions of within-group transport equation. The four eigenfunctions from S 4 approximation have been chosen as basis functions for the spatial expansion of the angular flux in each mesh. The constant and cubic polynomial approximations are adopted for the scattering source terms from other energy groups and fission source. A nodal method using the conventional polynomial expansion and the sub-cell balances was also developed to be used for demonstrating the high accuracy of the new methods. Using the new methods, a multi-group eigenvalue problem has been solved as well as fixed source problems. The numerical test results of one-group problem show that the new method has third-order accuracy as mesh size is finely refined and it has much higher accuracies for large meshes than the diamond differencing method and the nodal method using sub-cell balances and polynomial expansion of angular flux. For multi-group problems including eigenvalue problem, it was demonstrated that the new method using the cubic polynomial approximation of the sources could produce very accurate solutions even with large mesh sizes. (author)

Verification of a three-dimensional neutronics model based on multi-point kinetics equations for transient problems

Energy Technology Data Exchange (ETDEWEB)

Park, Kyung Seok; Kim, Hyun Dae; Yeom, Choong Sub [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

1995-07-01

A computer code for solving the three-dimensional reactor neutronic transient problems utilizing multi-point reactor kinetics equations recently developed has been developed. For evaluating its applicability, the code has been tested with typical 3-D LWR and CANDU reactor transient problems. The performance of the method and code has been compared with the results by fine and coarse meshes computer codes employing the direct methods.

A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data

Directory of Open Access Journals (Sweden)

Hongchao Song

2017-01-01

Full Text Available Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observation and suffer from the curse of dimensionality in high-dimensional space; for example, the distances between any pair of samples are similar and each sample may perform like an outlier. In this paper, we propose a hybrid semi-supervised anomaly detection model for high-dimensional data that consists of two parts: a deep autoencoder (DAE and an ensemble k-nearest neighbor graphs- (K-NNG- based anomaly detector. Benefiting from the ability of nonlinear mapping, the DAE is first trained to learn the intrinsic features of a high-dimensional dataset to represent the high-dimensional data in a more compact subspace. Several nonparametric KNN-based anomaly detectors are then built from different subsets that are randomly sampled from the whole dataset. The final prediction is made by all the anomaly detectors. The performance of the proposed method is evaluated on several real-life datasets, and the results confirm that the proposed hybrid model improves the detection accuracy and reduces the computational complexity.

High-dimensional quantum cloning and applications to quantum hacking.

Science.gov (United States)

Bouchard, Frédéric; Fickler, Robert; Boyd, Robert W; Karimi, Ebrahim

2017-02-01

Attempts at cloning a quantum system result in the introduction of imperfections in the state of the copies. This is a consequence of the no-cloning theorem, which is a fundamental law of quantum physics and the backbone of security for quantum communications. Although perfect copies are prohibited, a quantum state may be copied with maximal accuracy via various optimal cloning schemes. Optimal quantum cloning, which lies at the border of the physical limit imposed by the no-signaling theorem and the Heisenberg uncertainty principle, has been experimentally realized for low-dimensional photonic states. However, an increase in the dimensionality of quantum systems is greatly beneficial to quantum computation and communication protocols. Nonetheless, no experimental demonstration of optimal cloning machines has hitherto been shown for high-dimensional quantum systems. We perform optimal cloning of high-dimensional photonic states by means of the symmetrization method. We show the universality of our technique by conducting cloning of numerous arbitrary input states and fully characterize our cloning machine by performing quantum state tomography on cloned photons. In addition, a cloning attack on a Bennett and Brassard (BB84) quantum key distribution protocol is experimentally demonstrated to reveal the robustness of high-dimensional states in quantum cryptography.

Analytical Modeling of Transient Process In Terms of One-Dimensional Problem of Dynamics With Kinematic Action

Directory of Open Access Journals (Sweden)

Kravets Victor V.

2016-05-01

Full Text Available One-dimensional dynamic design of a component characterized by inertia coefficient, elastic coefficient, and coefficient of energy dispersion. The component is affected by external action in the form of time-independent initial kinematic disturbances and varying ones. Mathematical model of component dynamics as well as a new form of analytical representation of transient in terms of one-dimensional problem of kinematic effect is provided. Dynamic design of a component is being carried out according to a theory of modal control.

Central subspace dimensionality reduction using covariance operators.

Science.gov (United States)

Kim, Minyoung; Pavlovic, Vladimir

2011-04-01

We consider the task of dimensionality reduction informed by real-valued multivariate labels. The problem is often treated as Dimensionality Reduction for Regression (DRR), whose goal is to find a low-dimensional representation, the central subspace, of the input data that preserves the statistical correlation with the targets. A class of DRR methods exploits the notion of inverse regression (IR) to discover central subspaces. Whereas most existing IR techniques rely on explicit output space slicing, we propose a novel method called the Covariance Operator Inverse Regression (COIR) that generalizes IR to nonlinear input/output spaces without explicit target slicing. COIR's unique properties make DRR applicable to problem domains with high-dimensional output data corrupted by potentially significant amounts of noise. Unlike recent kernel dimensionality reduction methods that employ iterative nonconvex optimization, COIR yields a closed-form solution. We also establish the link between COIR, other DRR techniques, and popular supervised dimensionality reduction methods, including canonical correlation analysis and linear discriminant analysis. We then extend COIR to semi-supervised settings where many of the input points lack their labels. We demonstrate the benefits of COIR on several important regression problems in both fully supervised and semi-supervised settings.

On spectral distribution of high dimensional covariation matrices

DEFF Research Database (Denmark)

Heinrich, Claudio; Podolskij, Mark

In this paper we present the asymptotic theory for spectral distributions of high dimensional covariation matrices of Brownian diffusions. More specifically, we consider N-dimensional Itô integrals with time varying matrix-valued integrands. We observe n equidistant high frequency data points...... of the underlying Brownian diffusion and we assume that N/n -> c in (0,oo). We show that under a certain mixed spectral moment condition the spectral distribution of the empirical covariation matrix converges in distribution almost surely. Our proof relies on method of moments and applications of graph theory....

HSM: Heterogeneous Subspace Mining in High Dimensional Data

DEFF Research Database (Denmark)

Müller, Emmanuel; Assent, Ira; Seidl, Thomas

2009-01-01

Heterogeneous data, i.e. data with both categorical and continuous values, is common in many databases. However, most data mining algorithms assume either continuous or categorical attributes, but not both. In high dimensional data, phenomena due to the "curse of dimensionality" pose additional...... challenges. Usually, due to locally varying relevance of attributes, patterns do not show across the full set of attributes. In this paper we propose HSM, which defines a new pattern model for heterogeneous high dimensional data. It allows data mining in arbitrary subsets of the attributes that are relevant...... for the respective patterns. Based on this model we propose an efficient algorithm, which is aware of the heterogeneity of the attributes. We extend an indexing structure for continuous attributes such that HSM indexing adapts to different attribute types. In our experiments we show that HSM efficiently mines...

A Simple Proof of the Theorem Concerning Optimality in a One-Dimensional Ergodic Control Problem

International Nuclear Information System (INIS)

Fujita, Y.

2000-01-01

We give a simple proof of the theorem concerning optimality in a one-dimensional ergodic control problem. We characterize the optimal control in the class of all Markov controls. Our proof is probabilistic and does not need to solve the corresponding Bellman equation. This simplifies the proof

Group problem-solving skills training for self-harm: randomised controlled trial

OpenAIRE

McAuliffe, Carmel; McLeavey, Breda C.; Fitzgerald, Anthony P.; Corcoran, Paul; Carroll, Bernie; Ryan, Louise; Fitzgerald, Eva; O'Regan, Mary; Mulqueen, Jillian; Arensman, Ella

2014-01-01

Background: Rates of self-harm are high and have recently increased. This trend and the repetitive nature of self-harm pose a significant challenge to mental health services. Aims: To determine the efficacy of a structured group problem-solving skills training (PST) programme as an intervention approach for self-harm in addition to treatment as usual (TAU) as offered by mental health services. Method: A total of 433 participants (aged 18-64 years) were randomly assigned to TAU plus PST or TAU...

Kernel based methods for accelerated failure time model with ultra-high dimensional data

Directory of Open Access Journals (Sweden)

Jiang Feng

2010-12-01

Full Text Available Abstract Background Most genomic data have ultra-high dimensions with more than 10,000 genes (probes. Regularization methods with L1 and Lp penalty have been extensively studied in survival analysis with high-dimensional genomic data. However, when the sample size n ≪ m (the number of genes, directly identifying a small subset of genes from ultra-high (m > 10, 000 dimensional data is time-consuming and not computationally efficient. In current microarray analysis, what people really do is select a couple of thousands (or hundreds of genes using univariate analysis or statistical tests, and then apply the LASSO-type penalty to further reduce the number of disease associated genes. This two-step procedure may introduce bias and inaccuracy and lead us to miss biologically important genes. Results The accelerated failure time (AFT model is a linear regression model and a useful alternative to the Cox model for survival analysis. In this paper, we propose a nonlinear kernel based AFT model and an efficient variable selection method with adaptive kernel ridge regression. Our proposed variable selection method is based on the kernel matrix and dual problem with a much smaller n × n matrix. It is very efficient when the number of unknown variables (genes is much larger than the number of samples. Moreover, the primal variables are explicitly updated and the sparsity in the solution is exploited. Conclusions Our proposed methods can simultaneously identify survival associated prognostic factors and predict survival outcomes with ultra-high dimensional genomic data. We have demonstrated the performance of our methods with both simulation and real data. The proposed method performs superbly with limited computational studies.

High-dimensional statistical inference: From vector to matrix

Science.gov (United States)

Zhang, Anru

Statistical inference for sparse signals or low-rank matrices in high-dimensional settings is of significant interest in a range of contemporary applications. It has attracted significant recent attention in many fields including statistics, applied mathematics and electrical engineering. In this thesis, we consider several problems in including sparse signal recovery (compressed sensing under restricted isometry) and low-rank matrix recovery (matrix recovery via rank-one projections and structured matrix completion). The first part of the thesis discusses compressed sensing and affine rank minimization in both noiseless and noisy cases and establishes sharp restricted isometry conditions for sparse signal and low-rank matrix recovery. The analysis relies on a key technical tool which represents points in a polytope by convex combinations of sparse vectors. The technique is elementary while leads to sharp results. It is shown that, in compressed sensing, delta kA 0, delta kA < 1/3 + epsilon, deltak A + thetak,kA < 1 + epsilon, or deltatkA< √(t - 1) / t + epsilon are not sufficient to guarantee the exact recovery of all k-sparse signals for large k. Similar result also holds for matrix recovery. In addition, the conditions delta kA<1/3, deltak A+ thetak,kA<1, delta tkA < √(t - 1)/t and deltarM<1/3, delta rM+ thetar,rM<1, delta trM< √(t - 1)/ t are also shown to be sufficient respectively for stable recovery of approximately sparse signals and low-rank matrices in the noisy case. For the second part of the thesis, we introduce a rank-one projection model for low-rank matrix recovery and propose a constrained nuclear norm minimization method for stable recovery of low-rank matrices in the noisy case. The procedure is adaptive to the rank and robust against small perturbations. Both upper and lower bounds for the estimation accuracy under the Frobenius norm loss are obtained. The proposed estimator is shown to be rate-optimal under certain conditions. The

Group relationships in early and late sessions and improvement in interpersonal problems.

Science.gov (United States)

Lo Coco, Gianluca; Gullo, Salvatore; Di Fratello, Carla; Giordano, Cecilia; Kivlighan, Dennis M

2016-07-01

Groups are more effective when positive bonds are established and interpersonal conflicts resolved in early sessions and work is accomplished in later sessions. Previous research has provided mixed support for this group development model. We performed a test of this theoretical perspective using group members' (actors) and aggregated group members' (partners) perceptions of positive bonding, positive working, and negative group relationships measured early and late in interpersonal growth groups. Participants were 325 Italian graduate students randomly (within semester) assigned to 1 of 16 interpersonal growth groups. Groups met for 9 weeks with experienced psychologists using Yalom and Leszcz's (2005) interpersonal process model. Outcome was assessed pre- and posttreatment using the Inventory of Interpersonal Problems, and group relationships were measured at Sessions 3 and 6 using the Group Questionnaire. As hypothesized, early measures of positive bonding and late measures of positive working, for both actors and partners, were positively related to improved interpersonal problems. Also as hypothesized, late measures of positive bonding and early measures of positive working, for both actors and partners, were negatively related to improved interpersonal problems. We also found that early actor and partner positive bonding and negative relationships interacted to predict changes in interpersonal problems. The findings are consistent with group development theory and suggest that group therapists focus on group-as-a-whole positive bonding relationships in early group sessions and on group-as-a-whole positive working relationships in later group sessions. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Basic problems and solution methods for two-dimensional continuous 3 × 3 order hidden Markov model

International Nuclear Information System (INIS)

Wang, Guo-gang; Tang, Gui-jin; Gan, Zong-liang; Cui, Zi-guan; Zhu, Xiu-chang

2016-01-01

A novel model referred to as two-dimensional continuous 3 × 3 order hidden Markov model is put forward to avoid the disadvantages of the classical hypothesis of two-dimensional continuous hidden Markov model. This paper presents three equivalent definitions of the model, in which the state transition probability relies on not only immediate horizontal and vertical states but also immediate diagonal state, and in which the probability density of the observation relies on not only current state but also immediate horizontal and vertical states. The paper focuses on the three basic problems of the model, namely probability density calculation, parameters estimation and path backtracking. Some algorithms solving the questions are theoretically derived, by exploiting the idea that the sequences of states on rows or columns of the model can be viewed as states of a one-dimensional continuous 1 × 2 order hidden Markov model. Simulation results further demonstrate the performance of the algorithms. Because there are more statistical characteristics in the structure of the proposed new model, it can more accurately describe some practical problems, as compared to two-dimensional continuous hidden Markov model.

Analysing spatially extended high-dimensional dynamics by recurrence plots

Energy Technology Data Exchange (ETDEWEB)

Marwan, Norbert, E-mail: marwan@pik-potsdam.de [Potsdam Institute for Climate Impact Research, 14412 Potsdam (Germany); Kurths, Jürgen [Potsdam Institute for Climate Impact Research, 14412 Potsdam (Germany); Humboldt Universität zu Berlin, Institut für Physik (Germany); Nizhny Novgorod State University, Department of Control Theory, Nizhny Novgorod (Russian Federation); Foerster, Saskia [GFZ German Research Centre for Geosciences, Section 1.4 Remote Sensing, Telegrafenberg, 14473 Potsdam (Germany)

2015-05-08

Recurrence plot based measures of complexity are capable tools for characterizing complex dynamics. In this letter we show the potential of selected recurrence plot measures for the investigation of even high-dimensional dynamics. We apply this method on spatially extended chaos, such as derived from the Lorenz96 model and show that the recurrence plot based measures can qualitatively characterize typical dynamical properties such as chaotic or periodic dynamics. Moreover, we demonstrate its power by analysing satellite image time series of vegetation cover with contrasting dynamics as a spatially extended and potentially high-dimensional example from the real world. - Highlights: • We use recurrence plots for analysing partially extended dynamics. • We investigate the high-dimensional chaos of the Lorenz96 model. • The approach distinguishes different spatio-temporal dynamics. • We use the method for studying vegetation cover time series.

Exploring creativity and critical thinking in traditional and innovative problem-based learning groups.

Science.gov (United States)

Chan, Zenobia C Y

2013-08-01

To explore students' attitude towards problem-based learning, creativity and critical thinking, and the relevance to nursing education and clinical practice. Critical thinking and creativity are crucial in nursing education. The teaching approach of problem-based learning can help to reduce the difficulties of nurturing problem-solving skills. However, there is little in the literature on how to improve the effectiveness of a problem-based learning lesson by designing appropriate and innovative activities such as composing songs, writing poems and using role plays. Exploratory qualitative study. A sample of 100 students participated in seven semi-structured focus groups, of which two were innovative groups and five were standard groups, adopting three activities in problem-based learning, namely composing songs, writing poems and performing role plays. The data were analysed using thematic analysis. There are three themes extracted from the conversations: 'students' perceptions of problem-based learning', 'students' perceptions of creative thinking' and 'students' perceptions of critical thinking'. Participants generally agreed that critical thinking is more important than creativity in problem-based learning and clinical practice. Participants in the innovative groups perceived a significantly closer relationship between critical thinking and nursing care, and between creativity and nursing care than the standard groups. Both standard and innovative groups agreed that problem-based learning could significantly increase their critical thinking and problem-solving skills. Further, by composing songs, writing poems and using role plays, the innovative groups had significantly increased their awareness of the relationship among critical thinking, creativity and nursing care. Nursing educators should include more types of creative activities than it often does in conventional problem-based learning classes. The results could help nurse educators design an appropriate

Generalized coherent states for the Coulomb problem in one dimension

International Nuclear Information System (INIS)

Nouri, S.

2002-01-01

A set of generalized coherent states for the one-dimensional Coulomb problem in coordinate representation is constructed. At first, we obtain a mapping for proper transformation of the one-dimensional Coulomb problem into a nonrotating four-dimensional isotropic harmonic oscillator in the hyperspherical space, and the generalized coherent states for the one-dimensional Coulomb problem is then obtained in exact closed form. This exactly soluble model can provide an adequate means for a quantum coherency description of the Coulomb problem in one dimension, sample for coherent aspects of the exciton model in one-dimension example in high-temperature superconductivity, semiconductors, and polymers. Also, it can be useful for investigating the coherent scattering of the Coulomb particles in one dimension

Social problem-solving in high-functioning schizophrenia: specific deficits in sending skills.

Science.gov (United States)

Vaskinn, Anja; Sundet, Kjetil; Hultman, Christina M; Friis, Svein; Andreassen, Ole A

2009-02-28

This study examined social problem-solving performance in high-functioning schizophrenia (n=26) and its relation to neurocognition. Ten healthy controls were used as a comparison group. Social problem-solving was assessed with the Assessment of Interpersonal Problem Solving Skills (AIPSS) method. The schizophrenia group was outperformed by healthy controls on all AIPSS measures, reaching statistical significance for sending skills. Exploration of the internal relationship between different aspects of social problem-solving showed that identification of an interpersonal problem (a receiving skill) was not correlated with formulating solutions to the problem (processing skills) or successfully role-playing solutions (interpersonal sending skills). Non-verbal performance in the role-play (an interpersonal sending skill) was not significantly correlated with identification of an interpersonal problem or the generation of solutions. This suggests a dissociation of social problem-solving processes. Social problem-solving was significantly associated with psychomotor speed, verbal learning, semantic fluency and cognitive flexibility. Clinical implications are that remediation of social problem-solving skills should focus on role-playing (nonverbal) interpersonal behaviors, rather than on verbally analyzing an interpersonal problem and clarifying alternative solutions.

Comparison of three-dimensional ocean general circulation models on a benchmark problem

International Nuclear Information System (INIS)

Chartier, M.

1990-12-01

A french and an american Ocean General Circulation Models for deep-sea disposal of radioactive wastes are compared on a benchmark test problem. Both models are three-dimensional. They solve the hydrostatic primitive equations of the ocean with two different finite difference techniques. Results show that the dynamics simulated by both models are consistent. Several methods for the running of a model from a known state are tested in the French model: the diagnostic method, the prognostic method, the acceleration of convergence and the robust-diagnostic method

Computing group cardinality constraint solutions for logistic regression problems.

Science.gov (United States)

Zhang, Yong; Kwon, Dongjin; Pohl, Kilian M

2017-01-01

We derive an algorithm to directly solve logistic regression based on cardinality constraint, group sparsity and use it to classify intra-subject MRI sequences (e.g. cine MRIs) of healthy from diseased subjects. Group cardinality constraint models are often applied to medical images in order to avoid overfitting of the classifier to the training data. Solutions within these models are generally determined by relaxing the cardinality constraint to a weighted feature selection scheme. However, these solutions relate to the original sparse problem only under specific assumptions, which generally do not hold for medical image applications. In addition, inferring clinical meaning from features weighted by a classifier is an ongoing topic of discussion. Avoiding weighing features, we propose to directly solve the group cardinality constraint logistic regression problem by generalizing the Penalty Decomposition method. To do so, we assume that an intra-subject series of images represents repeated samples of the same disease patterns. We model this assumption by combining series of measurements created by a feature across time into a single group. Our algorithm then derives a solution within that model by decoupling the minimization of the logistic regression function from enforcing the group sparsity constraint. The minimum to the smooth and convex logistic regression problem is determined via gradient descent while we derive a closed form solution for finding a sparse approximation of that minimum. We apply our method to cine MRI of 38 healthy controls and 44 adult patients that received reconstructive surgery of Tetralogy of Fallot (TOF) during infancy. Our method correctly identifies regions impacted by TOF and generally obtains statistically significant higher classification accuracy than alternative solutions to this model, i.e., ones relaxing group cardinality constraints. Copyright © 2016 Elsevier B.V. All rights reserved.

A Cure for Variance Inflation in High Dimensional Kernel Principal Component Analysis

DEFF Research Database (Denmark)

Abrahamsen, Trine Julie; Hansen, Lars Kai

2011-01-01

Small sample high-dimensional principal component analysis (PCA) suffers from variance inflation and lack of generalizability. It has earlier been pointed out that a simple leave-one-out variance renormalization scheme can cure the problem. In this paper we generalize the cure in two directions......: First, we propose a computationally less intensive approximate leave-one-out estimator, secondly, we show that variance inflation is also present in kernel principal component analysis (kPCA) and we provide a non-parametric renormalization scheme which can quite efficiently restore generalizability in kPCA....... As for PCA our analysis also suggests a simplified approximate expression. © 2011 Trine J. Abrahamsen and Lars K. Hansen....

Hydraulic performance numerical simulation of high specific speed mixed-flow pump based on quasi three-dimensional hydraulic design method

International Nuclear Information System (INIS)

Zhang, Y X; Su, M; Hou, H C; Song, P F

2013-01-01

This research adopts the quasi three-dimensional hydraulic design method for the impeller of high specific speed mixed-flow pump to achieve the purpose of verifying the hydraulic design method and improving hydraulic performance. Based on the two families of stream surface theory, the direct problem is completed when the meridional flow field of impeller is obtained by employing iterative calculation to settle the continuity and momentum equation of fluid. The inverse problem is completed by using the meridional flow field calculated in the direct problem. After several iterations of the direct and inverse problem, the shape of impeller and flow field information can be obtained finally when the result of iteration satisfies the convergent criteria. Subsequently the internal flow field of the designed pump are simulated by using RANS equations with RNG k-ε two-equation turbulence model. The static pressure and streamline distributions at the symmetrical cross-section, the vector velocity distribution around blades and the reflux phenomenon are analyzed. The numerical results show that the quasi three-dimensional hydraulic design method for high specific speed mixed-flow pump improves the hydraulic performance and reveal main characteristics of the internal flow of mixed-flow pump as well as provide basis for judging the rationality of the hydraulic design, improvement and optimization of hydraulic model

The relationship between interpersonal problems, therapeutic alliance, and outcomes following group and individual cognitive behaviour therapy.

Science.gov (United States)

McEvoy, Peter M; Burgess, Melissa M; Nathan, Paula

2014-03-01

Cognitive behavioural therapy (CBT) is efficacious, but there remains individual variability in outcomes. Patient's interpersonal problems may affect treatment outcomes, either directly or through a relationship mediated by helping alliance. Interpersonal problems may affect alliance and outcomes differentially in individual and group (CBGT) treatments. The main aim of this study was to investigate the relationship between interpersonal problems, alliance, dropout and outcomes for a clinical sample receiving either individual or group CBT for anxiety or depression in a community clinic. Patients receiving individual CBT (N=84) or CBGT (N=115) completed measures of interpersonal problems, alliance, and disorder specific symptoms at the commencement and completion of CBT. In CBGT higher pre-treatment interpersonal problems were associated with increased risk of dropout and poorer outcomes. This relationship was not mediated by alliance. In individual CBT those who reported higher alliance were more likely to complete treatment, although alliance was not associated with symptom change, and interpersonal problems were not related to attrition or outcome. Allocation to group and individual therapy was non-random, so selection bias may have influenced these results. Some analyses were only powered to detect large effects. Helping alliance ratings were high, so range restriction may have obscured the relationship between helping alliance, attrition and outcomes. Pre-treatment interpersonal problems increase risk of dropout and predict poorer outcomes in CBGT, but not in individual CBT, and this relationship is not mediated by helping alliance. Stronger alliance is associated with treatment completion in individual, but not group CBT. Copyright © 2014 Elsevier B.V. All rights reserved.

TESTING HIGH-DIMENSIONAL COVARIANCE MATRICES, WITH APPLICATION TO DETECTING SCHIZOPHRENIA RISK GENES.

Science.gov (United States)

Zhu, Lingxue; Lei, Jing; Devlin, Bernie; Roeder, Kathryn

2017-09-01

Scientists routinely compare gene expression levels in cases versus controls in part to determine genes associated with a disease. Similarly, detecting case-control differences in co-expression among genes can be critical to understanding complex human diseases; however statistical methods have been limited by the high dimensional nature of this problem. In this paper, we construct a sparse-Leading-Eigenvalue-Driven (sLED) test for comparing two high-dimensional covariance matrices. By focusing on the spectrum of the differential matrix, sLED provides a novel perspective that accommodates what we assume to be common, namely sparse and weak signals in gene expression data, and it is closely related with Sparse Principal Component Analysis. We prove that sLED achieves full power asymptotically under mild assumptions, and simulation studies verify that it outperforms other existing procedures under many biologically plausible scenarios. Applying sLED to the largest gene-expression dataset obtained from post-mortem brain tissue from Schizophrenia patients and controls, we provide a novel list of genes implicated in Schizophrenia and reveal intriguing patterns in gene co-expression change for Schizophrenia subjects. We also illustrate that sLED can be generalized to compare other gene-gene "relationship" matrices that are of practical interest, such as the weighted adjacency matrices.

Time-stepping approach for solving upper-bound problems: Application to two-dimensional Rayleigh-Bénard convection

Science.gov (United States)

Wen, Baole; Chini, Gregory P.; Kerswell, Rich R.; Doering, Charles R.

2015-10-01

An alternative computational procedure for numerically solving a class of variational problems arising from rigorous upper-bound analysis of forced-dissipative infinite-dimensional nonlinear dynamical systems, including the Navier-Stokes and Oberbeck-Boussinesq equations, is analyzed and applied to Rayleigh-Bénard convection. A proof that the only steady state to which this numerical algorithm can converge is the required global optimal of the relevant variational problem is given for three canonical flow configurations. In contrast with most other numerical schemes for computing the optimal bounds on transported quantities (e.g., heat or momentum) within the "background field" variational framework, which employ variants of Newton's method and hence require very accurate initial iterates, the new computational method is easy to implement and, crucially, does not require numerical continuation. The algorithm is used to determine the optimal background-method bound on the heat transport enhancement factor, i.e., the Nusselt number (Nu), as a function of the Rayleigh number (Ra), Prandtl number (Pr), and domain aspect ratio L in two-dimensional Rayleigh-Bénard convection between stress-free isothermal boundaries (Rayleigh's original 1916 model of convection). The result of the computation is significant because analyses, laboratory experiments, and numerical simulations have suggested a range of exponents α and β in the presumed Nu˜PrαRaβ scaling relation. The computations clearly show that for Ra≤1010 at fixed L =2 √{2 },Nu≤0.106 Pr0Ra5/12 , which indicates that molecular transport cannot generally be neglected in the "ultimate" high-Ra regime.

Shielding benchmark problems, (2)

International Nuclear Information System (INIS)

Tanaka, Shun-ichi; Sasamoto, Nobuo; Oka, Yoshiaki; Shin, Kazuo; Tada, Keiko.

1980-02-01

Shielding benchmark problems prepared by Working Group of Assessment of Shielding Experiments in the Research Committee on Shielding Design in the Atomic Energy Society of Japan were compiled by Shielding Laboratory in Japan Atomic Energy Research Institute. Fourteen shielding benchmark problems are presented newly in addition to twenty-one problems proposed already, for evaluating the calculational algorithm and accuracy of computer codes based on discrete ordinates method and Monte Carlo method and for evaluating the nuclear data used in codes. The present benchmark problems are principally for investigating the backscattering and the streaming of neutrons and gamma rays in two- and three-dimensional configurations. (author)

hree-Dimensional Finite Element Simulation of the Buried Pipe Problem in Geogrid Reinforced Soil

Directory of Open Access Journals (Sweden)

Mohammed Yousif Fattah

2016-05-01

Full Text Available Buried pipeline systems are commonly used to transport water, sewage, natural oil/gas and other materials. The beneficial of using geogrid reinforcement is to increase the bearing capacity of the soil and decrease the load transfer to the underground structures. This paper deals with simulation of the buried pipe problem numerically by finite elements method using the newest version of PLAXIS-3D software. Rajkumar and Ilamaruthi's study, 2008 has been selected to be reanalyzed as 3D problem because it is containing all the properties needed by the program such as the modulus of elasticity, Poisson's ratio, angle of internal friction. It was found that the results of vertical crown deflection for the model without geogrid obtained from PLAXIS-3D are higher than those obtained by two-dimensional plane strain by about 21.4% while this percent becomes 12.1 for the model with geogrid, but in general, both have the same trend. The two dimensional finite elements analysis predictions of pipe-soil system behavior indicate an almost linear displacement of pipe deflection with applied pressure while 3-D analysis exhibited non-linear behavior especially at higher loads.

Two numerical methods for the solution of two-dimensional eddy current problems

International Nuclear Information System (INIS)

Biddlecombe, C.S.

1978-07-01

A general method for the solution of eddy current problems in two dimensions - one component of current density and two of magnetic field, is reported. After examining analytical methods two numerical methods are presented. Both solve the two dimensional, low frequency limit of Maxwell's equations for transient eddy currents in conducting material, which may be permeable, in the presence of other non-conducting permeable material. Both solutions are expressed in terms of the magnetic vector potential. The first is an integral equation method, using zero order elements in the discretisation of the unknown source regions. The other is a differential equation method, using a first order finite element mesh, and the Galerkin weighted residual procedure. The resulting equations are solved as initial-value problems. Results from programs based on each method are presented showing the power and limitations of the methods and the range of problems solvable. The methods are compared and recommendations are made for choosing between them. Suggestions are made for improving both methods, involving boundary integral techniques. (author)

HAMMER, 1-D Multigroup Neutron Transport Infinite System Cell Calculation for Few-Group Diffusion Calculation

International Nuclear Information System (INIS)

Honeck, H.C.

1984-01-01

1 - Description of problem or function: HAMMER performs infinite lattice, one-dimensional cell multigroup calculations, followed (optionally) by one-dimensional, few-group, multi-region reactor calculations with neutron balance edits. 2 - Method of solution: Infinite lattice parameters are calculated by means of multigroup transport theory, composite reactor parameters by few-group diffusion theory. 3 - Restrictions on the complexity of the problem: - Cell calculations - maxima of: 30 thermal groups; 54 epithermal groups; 20 space points; 20 regions; 18 isotopes; 10 mixtures; 3 thermal up-scattering mixtures; 200 resonances per group; no overlap or interference; single level only. - Reactor calculations - maxima of : 40 regions; 40 mixtures; 250 space points; 4 groups

Three-body problem in d-dimensional space: Ground state, (quasi)-exact-solvability

Science.gov (United States)

Turbiner, Alexander V.; Miller, Willard; Escobar-Ruiz, M. A.

2018-02-01

As a straightforward generalization and extension of our previous paper [A. V. Turbiner et al., "Three-body problem in 3D space: Ground state, (quasi)-exact-solvability," J. Phys. A: Math. Theor. 50, 215201 (2017)], we study the aspects of the quantum and classical dynamics of a 3-body system with equal masses, each body with d degrees of freedom, with interaction depending only on mutual (relative) distances. The study is restricted to solutions in the space of relative motion which are functions of mutual (relative) distances only. It is shown that the ground state (and some other states) in the quantum case and the planar trajectories (which are in the interaction plane) in the classical case are of this type. The quantum (and classical) Hamiltonian for which these states are eigenfunctions is derived. It corresponds to a three-dimensional quantum particle moving in a curved space with special d-dimension-independent metric in a certain d-dependent singular potential, while at d = 1, it elegantly degenerates to a two-dimensional particle moving in flat space. It admits a description in terms of pure geometrical characteristics of the interaction triangle which is defined by the three relative distances. The kinetic energy of the system is d-independent; it has a hidden sl(4, R) Lie (Poisson) algebra structure, alternatively, the hidden algebra h(3) typical for the H3 Calogero model as in the d = 3 case. We find an exactly solvable three-body S3-permutationally invariant, generalized harmonic oscillator-type potential as well as a quasi-exactly solvable three-body sextic polynomial type potential with singular terms. For both models, an extra first order integral exists. For d = 1, the whole family of 3-body (two-dimensional) Calogero-Moser-Sutherland systems as well as the Tremblay-Turbiner-Winternitz model is reproduced. It is shown that a straightforward generalization of the 3-body (rational) Calogero model to d > 1 leads to two primitive quasi

Parallelization characteristics of a three-dimensional whole-core code DeCART

International Nuclear Information System (INIS)

Cho, J. Y.; Joo, H.K.; Kim, H. Y.; Lee, J. C.; Jang, M. H.

2003-01-01

Neutron transport calculation for three-dimensional amount of computing time but also huge memory. Therefore, whole-core codes such as DeCART need both also parallel computation and distributed memory capabilities. This paper is to implement such parallel capabilities based on MPI grouping and memory distribution on the DeCART code, and then to evaluate the performance by solving the C5G7 three-dimensional benchmark and a simplified three-dimensional SMART core problem. In C5G7 problem with 24 CPUs, a speedup of maximum 22 is obtained on IBM regatta machine and 21 on a LINUX cluster for the MOC kernel, which indicates good parallel performance of the DeCART code. The simplified SMART problem which need about 11 GBytes memory with one processors requires about 940 MBytes, which means that the DeCART code can now solve large core problems on affordable LINUX clusters

Sufficient condition for existence of solutions for higher-order resonance boundary value problem with one-dimensional p-Laplacian

Directory of Open Access Journals (Sweden)

Liu Yang

2007-10-01

Full Text Available By using coincidence degree theory of Mawhin, existence results for some higher order resonance multipoint boundary value problems with one dimensional p-Laplacian operator are obtained.

LABAN-PEL: a two-dimensional, multigroup diffusion, high-order response matrix code

International Nuclear Information System (INIS)

Mueller, E.Z.

1991-06-01

The capabilities of LABAN-PEL is described. LABAN-PEL is a modified version of the two-dimensional, high-order response matrix code, LABAN, written by Lindahl. The new version extends the capabilities of the original code with regard to the treatment of neutron migration by including an option to utilize full group-to-group diffusion coefficient matrices. In addition, the code has been converted from single to double precision and the necessary routines added to activate its multigroup capability. The coding has also been converted to standard FORTRAN-77 to enhance the portability of the code. Details regarding the input data requirements and calculational options of LABAN-PEL are provided. 13 refs

Sequence-specific high mobility group box factors recognize 10-12-base pair minor groove motifs

DEFF Research Database (Denmark)

van Beest, M; Dooijes, D; van De Wetering, M

2000-01-01

Sequence-specific high mobility group (HMG) box factors bind and bend DNA via interactions in the minor groove. Three-dimensional NMR analyses have provided the structural basis for this interaction. The cognate HMG domain DNA motif is generally believed to span 6-8 bases. However, alignment...

Use of the Fox derivatives in the solution of the word problem for groups

International Nuclear Information System (INIS)

Majumdar, S.

1988-09-01

Applying Fox's free partial derivative, the word problem of a finitely presented group has been reduced to the problem of finding an algorithm for determining the existence of a root of a system of linear equations over the integral group ring. The solubility of the word problem for torsion-free one-relator groups and torsion-free polycyclic-by-finite groups has been deduced. (author). 10 refs

Highly indefinite multigrid for eigenvalue problems

Energy Technology Data Exchange (ETDEWEB)

Borges, L.; Oliveira, S.

1996-12-31

Eigenvalue problems are extremely important in understanding dynamic processes such as vibrations and control systems. Large scale eigenvalue problems can be very difficult to solve, especially if a large number of eigenvalues and the corresponding eigenvectors need to be computed. For solving this problem a multigrid preconditioned algorithm is presented in {open_quotes}The Davidson Algorithm, preconditioning and misconvergence{close_quotes}. Another approach for solving eigenvalue problems is by developing efficient solutions for highly indefinite problems. In this paper we concentrate on the use of new highly indefinite multigrid algorithms for the eigenvalue problem.

An Unbiased Distance-based Outlier Detection Approach for High-dimensional Data

DEFF Research Database (Denmark)

Nguyen, Hoang Vu; Gopalkrishnan, Vivekanand; Assent, Ira

2011-01-01

than a global property. Different from existing approaches, it is not grid-based and dimensionality unbiased. Thus, its performance is impervious to grid resolution as well as the curse of dimensionality. In addition, our approach ranks the outliers, allowing users to select the number of desired...... outliers, thus mitigating the issue of high false alarm rate. Extensive empirical studies on real datasets show that our approach efficiently and effectively detects outliers, even in high-dimensional spaces....

Collective Action Problem in Heterogeneous Groups with Punishment and Foresight

Science.gov (United States)

Perry, Logan; Shrestha, Mahendra Duwal; Vose, Michael D.; Gavrilets, Sergey

2018-03-01

The collective action problem can easily undermine cooperation in groups. Recent work has shown that within-group heterogeneity can under some conditions promote voluntary provisioning of collective goods. Here we generalize this work for the case when individuals can not only contribute to the production of collective goods, but also punish free-riders. To do this, we extend the standard theory by allowing individuals to have limited foresight so they can anticipate actions of their group-mates. For humans, this is a realistic assumption because we possess a "theory of mind". We use agent-based simulations to study collective actions that aim to overcome challenges from nature or win competition with neighboring groups. We contrast the dynamics of collective action in egalitarian and hierarchical groups. We show that foresight allows groups to overcome both the first- and second-order free-rider problems. While foresight increases cooperation, it does not necessarily result in higher payoffs. We show that while between-group conflicts promotes within-group cooperation, the effects of cultural group selection on cooperation are relatively small. Our models predict the emergence of a division of labor in which more powerful individuals specialize in punishment while less powerful individuals mostly contribute to the production of collective goods.

A non-Abelian SO(8) monopole as generalization of Dirac-Yang monopoles for a 9-dimensional space

International Nuclear Information System (INIS)

Le, Van-Hoang; Nguyen, Thanh-Son

2011-01-01

We establish an explicit form of a non-Abelian SO(8) monopole in a 9-dimensional space and show that it is indeed a direct generalization of Dirac and Yang monopoles. Using the generalized Hurwitz transformation, we have found a connection between a 16-dimensional harmonic oscillator and a 9-dimensional hydrogenlike atom in the field of the SO(8) monopole (MICZ-Kepler problem). Using the built connection the group of dynamical symmetry of the 9-dimensional MICZ-Kepler problem is found as SO(10, 2).

Analysis of chaos in high-dimensional wind power system.

Science.gov (United States)

Wang, Cong; Zhang, Hongli; Fan, Wenhui; Ma, Ping

2018-01-01

A comprehensive analysis on the chaos of a high-dimensional wind power system is performed in this study. A high-dimensional wind power system is more complex than most power systems. An 11-dimensional wind power system proposed by Huang, which has not been analyzed in previous studies, is investigated. When the systems are affected by external disturbances including single parameter and periodic disturbance, or its parameters changed, chaotic dynamics of the wind power system is analyzed and chaotic parameters ranges are obtained. Chaos existence is confirmed by calculation and analysis of all state variables' Lyapunov exponents and the state variable sequence diagram. Theoretical analysis and numerical simulations show that the wind power system chaos will occur when parameter variations and external disturbances change to a certain degree.

Application of the group-theoretical method to physical problems

OpenAIRE

Abd-el-malek, Mina B.

1998-01-01

The concept of the theory of continuous groups of transformations has attracted the attention of applied mathematicians and engineers to solve many physical problems in the engineering sciences. Three applications are presented in this paper. The first one is the problem of time-dependent vertical temperature distribution in a stagnant lake. Two cases have been considered for the forms of the water parameters, namely water density and thermal conductivity. The second application is the unstea...

Inverse radiative transfer problems in two-dimensional heterogeneous media; Problemas inversos em transferencia radiativa em meios heterogeneos bidimensionais

Energy Technology Data Exchange (ETDEWEB)

Tito, Mariella Janette Berrocal

2001-01-01

The analysis of inverse problems in participating media where emission, absorption and scattering take place has several relevant applications in engineering and medicine. Some of the techniques developed for the solution of inverse problems have as a first step the solution of the direct problem. In this work the discrete ordinates method has been used for the solution of the linearized Boltzmann equation in two dimensional cartesian geometry. The Levenberg - Marquardt method has been used for the solution of the inverse problem of internal source and absorption and scattering coefficient estimation. (author)

Three-dimensional dynamic rupture simulation with a high-order discontinuous Galerkin method on unstructured tetrahedral meshes

KAUST Repository

Pelties, Christian

2012-02-18

Accurate and efficient numerical methods to simulate dynamic earthquake rupture and wave propagation in complex media and complex fault geometries are needed to address fundamental questions in earthquake dynamics, to integrate seismic and geodetic data into emerging approaches for dynamic source inversion, and to generate realistic physics-based earthquake scenarios for hazard assessment. Modeling of spontaneous earthquake rupture and seismic wave propagation by a high-order discontinuous Galerkin (DG) method combined with an arbitrarily high-order derivatives (ADER) time integration method was introduced in two dimensions by de la Puente et al. (2009). The ADER-DG method enables high accuracy in space and time and discretization by unstructured meshes. Here we extend this method to three-dimensional dynamic rupture problems. The high geometrical flexibility provided by the usage of tetrahedral elements and the lack of spurious mesh reflections in the ADER-DG method allows the refinement of the mesh close to the fault to model the rupture dynamics adequately while concentrating computational resources only where needed. Moreover, ADER-DG does not generate spurious high-frequency perturbations on the fault and hence does not require artificial Kelvin-Voigt damping. We verify our three-dimensional implementation by comparing results of the SCEC TPV3 test problem with two well-established numerical methods, finite differences, and spectral boundary integral. Furthermore, a convergence study is presented to demonstrate the systematic consistency of the method. To illustrate the capabilities of the high-order accurate ADER-DG scheme on unstructured meshes, we simulate an earthquake scenario, inspired by the 1992 Landers earthquake, that includes curved faults, fault branches, and surface topography. Copyright 2012 by the American Geophysical Union.

The effect of training and breed group on problem-solving behaviours in dogs.

Science.gov (United States)

Marshall-Pescini, Sarah; Frazzi, Chiara; Valsecchi, Paola

2016-05-01

Dogs have become the focus of cognitive studies looking at both their physical and social problem-solving abilities (Bensky et al. in Adv Stud Behav, 45:209-387, 2013), but very little is known about the environmental and inherited factors that may affect these abilities. In the current study, we presented a manipulation task (a puzzle box) and a spatial task (the detour) to 128 dogs belonging to four different breed groups: Herding, Mastiff-like, Working and Retrievers (von Holdt et al. in Nature 464:898-902, 2010). Within each group, we tested highly trained and non-trained dogs. Results showed that trained dogs were faster at obtaining the reward in the detour task. In the manipulation task, trained dogs approached the apparatus sooner in the first familiarization trial, but no effect of breed emerged on this variable. Furthermore, regardless of breed, dogs in the trained group spent proportionally more time interacting with the apparatus and were more likely to succeed in the test trial than dogs in the non-trained group, whereas regardless of training, dogs in the working breed group were more likely to succeed than dogs in the retriever and herding breed groups (but not the mastiff-like group). Finally, trained dogs were less likely to look at a person than non-trained dogs during testing, but dogs in the herding group more likely to do so than dogs in the retriever and working but not the mastiff-like breed groups. Overall, results reveal a strong influence of training experience but less consistent differences between breed groups on different components thought to affect problem solving.

Uniqueness theorems for variational problems by the method of transformation groups

CERN Document Server

Reichel, Wolfgang

2004-01-01

A classical problem in the calculus of variations is the investigation of critical points of functionals {\\cal L} on normed spaces V. The present work addresses the question: Under what conditions on the functional {\\cal L} and the underlying space V does {\\cal L} have at most one critical point? A sufficient condition for uniqueness is given: the presence of a "variational sub-symmetry", i.e., a one-parameter group G of transformations of V, which strictly reduces the values of {\\cal L}. The "method of transformation groups" is applied to second-order elliptic boundary value problems on Riemannian manifolds. Further applications include problems of geometric analysis and elasticity.

Exploiting Group Symmetry in Semidefinite Programming Relaxations of the Quadratic Assignment Problem

NARCIS (Netherlands)

de Klerk, E.; Sotirov, R.

2007-01-01

We consider semidefinite programming relaxations of the quadratic assignment problem, and show how to exploit group symmetry in the problem data. Thus we are able to compute the best known lower bounds for several instances of quadratic assignment problems from the problem library: [R.E. Burkard,

High-dimensional data in economics and their (robust) analysis

Czech Academy of Sciences Publication Activity Database

Kalina, Jan

2017-01-01

Roč. 12, č. 1 (2017), s. 171-183 ISSN 1452-4864 R&D Projects: GA ČR GA17-07384S Institutional support: RVO:67985556 Keywords : econometrics * high-dimensional data * dimensionality reduction * linear regression * classification analysis * robustness Subject RIV: BA - General Mathematics OBOR OECD: Business and management http://library.utia.cas.cz/separaty/2017/SI/kalina-0474076.pdf

Explicit and implicit positive alcohol expectancies in problem and non-problem drinkers: differences across age groups from young adolescence to adulthood

Directory of Open Access Journals (Sweden)

Aurélie eVilenne

2015-11-01

Full Text Available Aims: Recent studies with animal models showed that the stimulant and sedative effects of alcohol change during the adolescent period. In humans, the stimulant effects of ethanol are most often indirectly recorded through the measurement of explicit and implicit alcohol effect expectancies. However, it is unknown how such implicit and explicit expectancies evolve with age in humans during adolescence.Methods: Adolescent (13-16 year old, young adult (17-18 year old and adult (35-55 year old participants were recruited. On the basis of their score on the Alcohol Use Disorder Identification Test (AUDIT, they were classified as non-problem (AUDIT ≤ 7 or problem (AUDIT ≥ 11 drinkers. The participants completed the Alcohol Expectancy Questionnaire (AEQ and performed two unipolar Implicit Association Test (IAT to assess implicit associations between alcohol and the concepts of stimulation and sedation.Results: Problem drinkers from the three age groups reported significantly higher positive alcohol expectancies than non-problem drinkers on all AEQ subscales. Positive alcohol explicit expectancies also gradually decreased with age, with adolescent problem drinkers reporting especially high positive expectancies. This effect was statistically significant for all positive expectancies, with the exception of relaxation expectancies that were only close to statistical significance. In contrast, stimulation and sedation alcohol implicit associations were not significantly different between problem and non-problem drinkers and did not change with age.Conclusions: These results indicate that explicit positive alcohol effect expectancies predict current alcohol consumption levels, especially in adolescents. Positive alcohol expectancies also gradually decrease with age in the three cross-sectional groups of adolescents, young adults and adults. This effect might be related to changes in the physiological response to alcohol.

Gauging the gaps in student problem-solving skills: assessment of individual and group use of problem-solving strategies using online discussions.

Science.gov (United States)

Anderson, William L; Mitchell, Steven M; Osgood, Marcy P

2008-01-01

For the past 3 yr, faculty at the University of New Mexico, Department of Biochemistry and Molecular Biology have been using interactive online Problem-Based Learning (PBL) case discussions in our large-enrollment classes. We have developed an illustrative tracking method to monitor student use of problem-solving strategies to provide targeted help to groups and to individual students. This method of assessing performance has a high interrater reliability, and senior students, with training, can serve as reliable graders. We have been able to measure improvements in many students' problem-solving strategies, but, not unexpectedly, there is a population of students who consistently apply the same failing strategy when there is no faculty intervention. This new methodology provides an effective tool to direct faculty to constructively intercede in this area of student development.

Developing cross entropy genetic algorithm for solving Two-Dimensional Loading Heterogeneous Fleet Vehicle Routing Problem (2L-HFVRP)

Science.gov (United States)

Paramestha, D. L.; Santosa, B.

2018-04-01

Two-dimensional Loading Heterogeneous Fleet Vehicle Routing Problem (2L-HFVRP) is a combination of Heterogeneous Fleet VRP and a packing problem well-known as Two-Dimensional Bin Packing Problem (BPP). 2L-HFVRP is a Heterogeneous Fleet VRP in which these costumer demands are formed by a set of two-dimensional rectangular weighted item. These demands must be served by a heterogeneous fleet of vehicles with a fix and variable cost from the depot. The objective function 2L-HFVRP is to minimize the total transportation cost. All formed routes must be consistent with the capacity and loading process of the vehicle. Sequential and unrestricted scenarios are considered in this paper. We propose a metaheuristic which is a combination of the Genetic Algorithm (GA) and the Cross Entropy (CE) named Cross Entropy Genetic Algorithm (CEGA) to solve the 2L-HFVRP. The mutation concept on GA is used to speed up the algorithm CE to find the optimal solution. The mutation mechanism was based on local improvement (2-opt, 1-1 Exchange, and 1-0 Exchange). The probability transition matrix mechanism on CE is used to avoid getting stuck in the local optimum. The effectiveness of CEGA was tested on benchmark instance based 2L-HFVRP. The result of experiments shows a competitive result compared with the other algorithm.

Multisymplectic Structure-Preserving in Simple Finite Element Method in High Dimensional Case

Institute of Scientific and Technical Information of China (English)

BAI Yong-Qiang; LIU Zhen; PEI Ming; ZHENG Zhu-Jun

2003-01-01

In this paper, we study a finite element scheme of some semi-linear elliptic boundary value problems inhigh-dimensional space. With uniform mesh, we find that, the numerical scheme derived from finite element method cankeep a preserved multisymplectic structure.

Renormalization group equation for interacting Thirring fields in dimensional regularization scheme

International Nuclear Information System (INIS)

Chowdhury, A.R.; Roy, T.; Kar, S.

1976-01-01

The dynamics of two interacting Thirring fields has been investigated within the dimensional regularization framework. The coupling constants are renormalized in the same way as observed in the non-perturbative approach of Ansel'm et al (Sov. Phys. - JETP 36: 608 (1959)). Functionsβsub(i)(g 1 , g 2 , g 3 ) and γsub(i)(g 1 , g 2 , g 3 ), pertaining to the stability and anomalous behaviour of the problem, are computed up to a third order in the coupling parameters. With the help of these, subsidiary non-linear differential equations of the renormalization group are studied in 2-epsilon dimension. The results show up some peculiar features of the theory: a zero of βsub(i)(g 1 , g 2 , g 3 ) corresponding to g 2 approximately α√epsilon, a characteristic of phi theory. The scale invariant limit is reached when g 2 → 0 (i.e. the two Thirring fields are decoupled) and also when g 1 = xg 2 = g 3 , where x is a root of 2x 3 + 2x 2 - 1 = 0. The branch-point zero makes the transition to the epsilon tends to 0 limit non-unique. The anomalous dimensions are obtained and seen to match that of the Dashen-Frishman model (Phys. Lett.; 46B 439 (1973)). The existence of a non-trivial scale invariant limit distinguishes the model from many simple field theories. (author)

Utility Function for modeling Group Multicriteria Decision Making problems as games

OpenAIRE

Alexandre Bevilacqua Leoneti

2016-01-01

To assist in the decision making process, several multicriteria methods have been proposed. However, the existing methods assume a single decision-maker and do not consider decision under risk, which is better addressed by Game Theory. Hence, the aim of this research is to propose a Utility Function that makes it possible to model Group Multicriteria Decision Making problems as games. The advantage of using Game Theory for solving Group Multicriteria Decision Making problems is to evaluate th...

Analytic Approximations to the Free Boundary and Multi-dimensional Problems in Financial Derivatives Pricing

Science.gov (United States)

Lau, Chun Sing

This thesis studies two types of problems in financial derivatives pricing. The first type is the free boundary problem, which can be formulated as a partial differential equation (PDE) subject to a set of free boundary condition. Although the functional form of the free boundary condition is given explicitly, the location of the free boundary is unknown and can only be determined implicitly by imposing continuity conditions on the solution. Two specific problems are studied in details, namely the valuation of fixed-rate mortgages and CEV American options. The second type is the multi-dimensional problem, which involves multiple correlated stochastic variables and their governing PDE. One typical problem we focus on is the valuation of basket-spread options, whose underlying asset prices are driven by correlated geometric Brownian motions (GBMs). Analytic approximate solutions are derived for each of these three problems. For each of the two free boundary problems, we propose a parametric moving boundary to approximate the unknown free boundary, so that the original problem transforms into a moving boundary problem which can be solved analytically. The governing parameter of the moving boundary is determined by imposing the first derivative continuity condition on the solution. The analytic form of the solution allows the price and the hedging parameters to be computed very efficiently. When compared against the benchmark finite-difference method, the computational time is significantly reduced without compromising the accuracy. The multi-stage scheme further allows the approximate results to systematically converge to the benchmark results as one recasts the moving boundary into a piecewise smooth continuous function. For the multi-dimensional problem, we generalize the Kirk (1995) approximate two-asset spread option formula to the case of multi-asset basket-spread option. Since the final formula is in closed form, all the hedging parameters can also be derived in

Application of the finite element method to neutronics problems with inhomogeneous boundray conditions

International Nuclear Information System (INIS)

Yoo, K.J.

1982-01-01

The albedo boundary conditions are incorporated into the finite element method using bicubic Hermite element functions in order to reduce the computer memory and computation time in two-group diffusion calculations by excluding the reflector regions in computation space. The basis functions at the core-reflector interfaces are newly established to satisfy the albedo boundary conditions, and then the ''weak'' form of two-group diffusion equations is discretized using the principle of the weighted residual method in combination with the Galerkin approximation. The discretized two-group diffusion equation is then solved by the Gaussian elimination method with the scaled column pivoting algorithm in one-dimensional problem and Gauss-Seidel method in two-dimensional problem. Prior to the application of the method to two-group diffusion problems, the same method is applied to the one-speed neutron transport equation in a bare slab reactor with the vacuum boundary condition to confirm its usefulness in the diffusion calculations. To investigate the applicability of our diffusion method, several numerical calculations are performed: two-dimensional IAEA benchmark problem and two-dimensional ZION problem. The results are compared with the available results from the conventional finite difference and other finite element methods. If the albedo values are appropriately adjusted, our results of the two-dimensional IAEA benchmark problem are agreed within 0.002% of ksub(eff) with the fine mesh PDQ results. Comparing with CITATION results, one-eighth of core memory and one-fifteenth of computing time are required to obtain the same accuracy even though no acceleration technique is used in the present case. Also, it is found that the results are comparable with the other finite element results. However, no significant saving is obtained in computation time comparing with the other finite element results, where the reflector regions are explicity included. This mainly comes from

Use of exact albedo conditions in numerical methods for one-dimensional one-speed discrete ordinates eigenvalue problems

International Nuclear Information System (INIS)

Abreu, M.P. de

1994-01-01

The use of exact albedo boundary conditions in numerical methods applied to one-dimensional one-speed discrete ordinates (S n ) eigenvalue problems for nuclear reactor global calculations is described. An albedo operator that treats the reflector region around a nuclear reactor core implicitly is described and exactly was derived. To illustrate the method's efficiency and accuracy, it was used conventional linear diamond method with the albedo option to solve typical model problems. (author)

Preparation of wholemount mouse intestine for high-resolution three-dimensional imaging using two-photon microscopy.

Science.gov (United States)

Appleton, P L; Quyn, A J; Swift, S; Näthke, I

2009-05-01

Visualizing overall tissue architecture in three dimensions is fundamental for validating and integrating biochemical, cell biological and visual data from less complex systems such as cultured cells. Here, we describe a method to generate high-resolution three-dimensional image data of intact mouse gut tissue. Regions of highest interest lie between 50 and 200 mum within this tissue. The quality and usefulness of three-dimensional image data of tissue with such depth is limited owing to problems associated with scattered light, photobleaching and spherical aberration. Furthermore, the highest-quality oil-immersion lenses are designed to work at a maximum distance of image at high-resolution deep within tissue. We show that manipulating the refractive index of the mounting media and decreasing sample opacity greatly improves image quality such that the limiting factor for a standard, inverted multi-photon microscope is determined by the working distance of the objective as opposed to detectable fluorescence. This method negates the need for mechanical sectioning of tissue and enables the routine generation of high-quality, quantitative image data that can significantly advance our understanding of tissue architecture and physiology.

Three-Dimensional Triplet Tracking for LHC and Future High Rate Experiments

CERN Document Server

Schöning, Andre

2014-10-20

The hit combinatorial problem is a main challenge for track reconstruction and triggering at high rate experiments. At hadron colliders the dominant fraction of hits is due to low momentum tracks for which multiple scattering (MS) effects dominate the hit resolution. MS is also the dominating source for hit confusion and track uncertainties in low energy precision experiments. In all such environments, where MS dominates, track reconstruction and fitting can be largely simplified by using three-dimensional (3D) hit-triplets as provided by pixel detectors. This simplification is possible since track uncertainties are solely determined by MS if high precision spatial information is provided. Fitting of hit-triplets is especially simple for tracking detectors in solenoidal magnetic fields. The over-constrained 3D-triplet method provides a complete set of track parameters and is robust against fake hit combinations. The triplet method is ideally suited for pixel detectors where hits can be treated as 3D-space poi...

High-dimensional Data in Economics and their (Robust) Analysis

Czech Academy of Sciences Publication Activity Database

Kalina, Jan

2017-01-01

Roč. 12, č. 1 (2017), s. 171-183 ISSN 1452-4864 R&D Projects: GA ČR GA17-07384S Grant - others:GA ČR(CZ) GA13-01930S Institutional support: RVO:67985807 Keywords : econometrics * high-dimensional data * dimensionality reduction * linear regression * classification analysis * robustness Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability

Testing problem-solving capacities: differences between individual testing and social group setting.

Science.gov (United States)

Krasheninnikova, Anastasia; Schneider, Jutta M

2014-09-01

Testing animals individually in problem-solving tasks limits distractions of the subjects during the test, so that they can fully concentrate on the problem. However, such individual performance may not indicate the problem-solving capacity that is commonly employed in the wild when individuals are faced with a novel problem in their social groups, where the presence of a conspecific influences an individual's behaviour. To assess the validity of data gathered from parrots when tested individually, we compared the performance on patterned-string tasks among parrots tested singly and parrots tested in social context. We tested two captive groups of orange-winged amazons (Amazona amazonica) with several patterned-string tasks. Despite the differences in the testing environment (singly vs. social context), parrots from both groups performed similarly. However, we found that the willingness to participate in the tasks was significantly higher for the individuals tested in social context. The study provides further evidence for the crucial influence of social context on individual's response to a challenging situation such as a problem-solving test.

Few-Group Transport Analysis of the Core-Reflector Problem in Fast Reactor Cores via Equivalent Group Condensation and Local/Global Iteration

International Nuclear Information System (INIS)

Won, Jong Hyuck; Cho, Nam Zin

2011-01-01

In deterministic neutron transport methods, a process called fine-group to few-group condensation is used to reduce the computational burden. However, recent results on the core-reflector problem in fast reactor cores show that use of a small number of energy groups has limitation to describe neutron flux around core reflector interface. Therefore, researches are still ongoing to overcome this limitation. Recently, the authors proposed I) direct application of equivalently condensed angle-dependent total cross section to discrete ordinates method to overcome the limitation of conventional multi-group approximations, and II) local/global iteration framework in which fine-group discrete ordinates calculation is used in local problems while few-group transport calculation is used in the global problem iteratively. In this paper, an analysis of the core-reflector problem is performed in few-group structure using equivalent angle-dependent total cross section with local/global iteration. Numerical results are obtained under S 12 discrete ordinates-like transport method with scattering cross section up to P1 Legendre expansion

Perfect 3-dimensional lattice actions for 4-dimensional quantum field theories at finite temperature

International Nuclear Information System (INIS)

Kerres, U.; Mack, G.; Palma, G.

1994-12-01

We propose a two-step procedure to study the order of phase transitions at finite temperature in electroweak theory and in simplified models thereof. In a first step a coarse grained free energy is computed by perturbative methods. It is obtained in the form of a 3-dimensional perfect lattice action by a block spin transformation. It has finite temperature dependent coefficients. In this way the UV-problem and the infrared problem is separated in a clean way. In the second step the effective 3-dimensional lattice theory is treated in a nonperturbative way, either by the Feynman-Bololiubov method (solution of a gap equation), by real space renormalization group methods, or by computer simulations. In this paper we outline the principles for φ 4 -theory and scalar electrodynamics. The Balaban-Jaffe block spin transformation for the gauge field is used. It is known how to extend this transformation to the nonabelian case, but this will not be discussed here. (orig.)

One-dimensional singular problems involving the p-Laplacian and nonlinearities indefinite in sign

OpenAIRE

Kaufmann, Uriel; Medri, Iván

2015-01-01

Let $\\Omega$ be a bounded open interval, let $p>1$ and $\\gamma>0$, and let $m:\\Omega\\rightarrow\\mathbb{R}$ be a function that may change sign in $\\Omega $. In this article we study the existence and nonexistence of positive solutions for one-dimensional singular problems of the form $-(\\left\\vert u^{\\prime}\\right\\vert ^{p-2}u^{\\prime})^{\\prime}=m\\left( x\\right) u^{-\\gamma}$ in $\\Omega$, $u=0$ on $\\partial\\Omega$. As a consequence we also derive existence results for other related nonlinearities.

Surveying Turkish high school and university students’ attitudes and approaches to physics problem solving

Directory of Open Access Journals (Sweden)

Nuri Balta

2016-04-01

Full Text Available Students’ attitudes and approaches to physics problem solving can impact how well they learn physics and how successful they are in solving physics problems. Prior research in the U.S. using a validated Attitude and Approaches to Problem Solving (AAPS survey suggests that there are major differences between students in introductory physics and astronomy courses and physics experts in terms of their attitudes and approaches to physics problem solving. Here we discuss the validation, administration, and analysis of data for the Turkish version of the AAPS survey for high school and university students in Turkey. After the validation and administration of the Turkish version of the survey, the analysis of the data was conducted by grouping the data by grade level, school type, and gender. While there are no statistically significant differences between the averages of various groups on the survey, overall, the university students in Turkey were more expertlike than vocational high school students. On an item by item basis, there are statistically differences between the averages of the groups on many items. For example, on average, the university students demonstrated less expertlike attitudes about the role of equations and formulas in problem solving, in solving difficult problems, and in knowing when the solution is not correct, whereas they displayed more expertlike attitudes and approaches on items related to metacognition in physics problem solving. A principal component analysis on the data yields item clusters into which the student responses on various survey items can be grouped. A comparison of the responses of the Turkish and American university students enrolled in algebra-based introductory physics courses shows that on more than half of the items, the responses of these two groups were statistically significantly different, with the U.S. students on average responding to the items in a more expertlike manner.

High-Dimensional Function Approximation With Neural Networks for Large Volumes of Data.

Science.gov (United States)

Andras, Peter

2018-02-01

Approximation of high-dimensional functions is a challenge for neural networks due to the curse of dimensionality. Often the data for which the approximated function is defined resides on a low-dimensional manifold and in principle the approximation of the function over this manifold should improve the approximation performance. It has been show that projecting the data manifold into a lower dimensional space, followed by the neural network approximation of the function over this space, provides a more precise approximation of the function than the approximation of the function with neural networks in the original data space. However, if the data volume is very large, the projection into the low-dimensional space has to be based on a limited sample of the data. Here, we investigate the nature of the approximation error of neural networks trained over the projection space. We show that such neural networks should have better approximation performance than neural networks trained on high-dimensional data even if the projection is based on a relatively sparse sample of the data manifold. We also find that it is preferable to use a uniformly distributed sparse sample of the data for the purpose of the generation of the low-dimensional projection. We illustrate these results considering the practical neural network approximation of a set of functions defined on high-dimensional data including real world data as well.

Surface harmonics method for two-dimensional time-dependent neutron transport problems of square-lattice nuclear reactors

Energy Technology Data Exchange (ETDEWEB)

Boyarinov, V. F.; Kondrushin, A. E.; Fomichenko, P. A. [National Research Centre Kurchatov Institute, Kurchatov Sq. 1, Moscow (Russian Federation)

2013-07-01

Time-dependent equations of the Surface Harmonics Method (SHM) have been derived from the time-dependent neutron transport equation with explicit representation of delayed neutrons for solving the two-dimensional time-dependent problems. These equations have been realized in the SUHAM-TD code. The TWIGL benchmark problem has been used for verification of the SUHAM-TD code. The results of the study showed that computational costs required to achieve necessary accuracy of the solution can be an order of magnitude less than with the use of the conventional finite difference method (FDM). (authors)

A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix

KAUST Repository

Hu, Zongliang; Dong, Kai; Dai, Wenlin; Tong, Tiejun

2017-01-01

The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.

A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix

KAUST Repository

Hu, Zongliang

2017-09-27

The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.

A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix.

Science.gov (United States)

Hu, Zongliang; Dong, Kai; Dai, Wenlin; Tong, Tiejun

2017-09-21

The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.

Heuristic geometric ''eigenvalue universality'' in a one-dimensional neutron transport problem with anisotropic scattering

International Nuclear Information System (INIS)

Goncalves, G.A.; Vilhena, M.T. de; Bodmann, B.E.J.

2010-01-01

In the present work we propose a heuristic construction of a transport equation for neutrons with anisotropic scattering considering only the radial cylinder dimension. The eigenvalues of the solutions of the equation correspond to the positive values for the one dimensional case. The central idea of the procedure is the application of the S N method for the discretisation of the angular variable followed by the application of the zero order Hankel transformation. The basis the construction of the scattering terms in form of an integro-differential equation for stationary transport resides in the hypothesis that the eigenvalues that compose the elementary solutions are independent of geometry for a homogeneous medium. We compare the solutions for the cartesian one dimensional problem for an infinite cylinder with azimuthal symmetry and linear anisotropic scattering for two cases. (orig.)

Renormalization group aspects of 3-dimensional Pure U(1) lattice gauge theory

International Nuclear Information System (INIS)

Gopfert, M.; Mack, G.

1983-01-01

A few surprises in a recent study of the 3-dimensional pure U(1) lattice gauge theory model, from the point of view of the renormalization group theory, are discussed. Since the gauge group U(1) of this model is abelian, the model is subject to KramersWannier duality transformation. One obtains a ferromagnet with a global symmetry group Z. The duality transformation shows that the surface tension alpha of the model equals the strong tension of the U(1) gauge model. A theorem to represent the true asymptotic behaviour of alpha is derived. A second theorem considers the correlation functions. Discrepiancies between the theorems result in a solution that ''is regarded as a catastrophe'' in renormalization group theory. A lesson is drawn: To choose a good block spin in a renormalization group procedure, know what the low lying excitations of the theory are, to avoid integrating some of them by mischief

A comprehensive analysis of earthquake damage patterns using high dimensional model representation feature selection

Science.gov (United States)

Taşkin Kaya, Gülşen

2013-10-01

-output relationships in high-dimensional systems for many problems in science and engineering. The HDMR method is developed to improve the efficiency of the deducing high dimensional behaviors. The method is formed by a particular organization of low dimensional component functions, in which each function is the contribution of one or more input variables to the output variables.

Some problems of dynamical systems on three dimensional manifolds

International Nuclear Information System (INIS)

Dong Zhenxie.

1985-08-01

It is important to study the dynamical systems on 3-dimensional manifolds, its importance is showing up in its close relation with our life. Because of the complication of topological structure of Dynamical systems on 3-dimensional manifolds, generally speaking, the search for 3-dynamical systems is not easier than 2-dynamical systems. This paper is a summary of the partial result of dynamical systems on 3-dimensional manifolds. (author)

Efficient evaluation of influence coefficients in three-dimensional extended boundary-node method for potential problems

International Nuclear Information System (INIS)

Itoh, Taku; Saitoh, Ayumu; Kamitani, Atsushi; Nakamura, Hiroaki

2011-01-01

For the purpose of speed-up of the three-dimensional eXtended Boundary-Node Method (X-BNM), an efficient algorithm for evaluating influence coefficients has been developed. The algorithm can be easily implemented into the X-BNM without using any integration cells. By applying the resulting X-BNM to the Laplace problem, the performance of the algorithm is numerically investigated. The numerical experiments show that, by using the algorithm, computational costs for evaluating influence coefficients in the X-BNM are reduced considerably. Especially for a large-sized problem, the algorithm is efficiently performed, and the computational costs of the X-BNM are close to those of the Boundary-Element Method (BEM). In addition, for the problem, the X-BNM shows almost the same accuracy as that of the BEM. (author)

Relativized problems with abelian phase group in topological dynamics.

Science.gov (United States)

McMahon, D

1976-04-01

Let (X, T) be the equicontinuous minimal transformation group with X = pi(infinity)Z(2), the Cantor group, and S = [unk](infinity)Z(2) endowed with the discrete topology acting on X by right multiplication. For any countable group T we construct a function F:X x S --> T such that if (Y, T) is a minimal transformation group, then (X x Y, S) is a minimal transformation group with the action defined by (x, y)s = [xs, yF(x, s)]. If (W, T) is a minimal transformation group and varphi:(Y, T) --> (W, T) is a homomorphism, then identity x varphi:(X x Y, S) --> (X x W, S) is a homomorphism and has many of the same properties that varphi has. For this reason, one may assume that the phase group is abelian (or S) without loss of generality for many relativized problems in topological dynamics.

Introduction to high-dimensional statistics

CERN Document Server

Giraud, Christophe

2015-01-01

Ever-greater computing technologies have given rise to an exponentially growing volume of data. Today massive data sets (with potentially thousands of variables) play an important role in almost every branch of modern human activity, including networks, finance, and genetics. However, analyzing such data has presented a challenge for statisticians and data analysts and has required the development of new statistical methods capable of separating the signal from the noise.Introduction to High-Dimensional Statistics is a concise guide to state-of-the-art models, techniques, and approaches for ha

High-Dimensional Single-Photon Quantum Gates: Concepts and Experiments.

Science.gov (United States)

Babazadeh, Amin; Erhard, Manuel; Wang, Feiran; Malik, Mehul; Nouroozi, Rahman; Krenn, Mario; Zeilinger, Anton

2017-11-03

Transformations on quantum states form a basic building block of every quantum information system. From photonic polarization to two-level atoms, complete sets of quantum gates for a variety of qubit systems are well known. For multilevel quantum systems beyond qubits, the situation is more challenging. The orbital angular momentum modes of photons comprise one such high-dimensional system for which generation and measurement techniques are well studied. However, arbitrary transformations for such quantum states are not known. Here we experimentally demonstrate a four-dimensional generalization of the Pauli X gate and all of its integer powers on single photons carrying orbital angular momentum. Together with the well-known Z gate, this forms the first complete set of high-dimensional quantum gates implemented experimentally. The concept of the X gate is based on independent access to quantum states with different parities and can thus be generalized to other photonic degrees of freedom and potentially also to other quantum systems.

On Riemann boundary value problems for null solutions of the two dimensional Helmholtz equation

Science.gov (United States)

Bory Reyes, Juan; Abreu Blaya, Ricardo; Rodríguez Dagnino, Ramón Martin; Kats, Boris Aleksandrovich

2018-01-01

The Riemann boundary value problem (RBVP to shorten notation) in the complex plane, for different classes of functions and curves, is still widely used in mathematical physics and engineering. For instance, in elasticity theory, hydro and aerodynamics, shell theory, quantum mechanics, theory of orthogonal polynomials, and so on. In this paper, we present an appropriate hyperholomorphic approach to the RBVP associated to the two dimensional Helmholtz equation in R^2 . Our analysis is based on a suitable operator calculus.

Solution of the one-dimensional time-dependent discrete ordinates problem in a slab by the spectral and LTSN methods

International Nuclear Information System (INIS)

Oliveira, J.V.P. de; Cardona, A.V.; Vilhena, M.T.M.B. de

2002-01-01

In this work, we present a new approach to solve the one-dimensional time-dependent discrete ordinates problem (S N problem) in a slab. The main idea is based upon the application of the spectral method to the set of S N time-dependent differential equations and solution of the resulting coupling equations by the LTS N method. We report numerical simulations

On the solution of the inverse scattering problem for the quadratic bundle of the one-dimensional Schroedinger operators of the whole axis

International Nuclear Information System (INIS)

Maksudov, F.G.; Gusejnov, G.Sh.

1986-01-01

Inverse scattering problem for the quadratic bundle of the Schroedinger one-dimensional operators in the whole axis is solved. The problem solution is given on the assumption of the discrete spectrum absence. In the discrete spectrum presence the inverse scattering problem solution is known for the Shroedinger differential equation considered

Parallelization of a three-dimensional whole core transport code DeCART

Energy Technology Data Exchange (ETDEWEB)

Jin Young, Cho; Han Gyu, Joo; Ha Yong, Kim; Moon-Hee, Chang [Korea Atomic Energy Research Institute, Yuseong-gu, Daejon (Korea, Republic of)

2003-07-01

Parallelization of the DeCART (deterministic core analysis based on ray tracing) code is presented that reduces the computational burden of the tremendous computing time and memory required in three-dimensional whole core transport calculations. The parallelization employs the concept of MPI grouping and the MPI/OpenMP mixed scheme as well. Since most of the computing time and memory are used in MOC (method of characteristics) and the multi-group CMFD (coarse mesh finite difference) calculation in DeCART, variables and subroutines related to these two modules are the primary targets for parallelization. Specifically, the ray tracing module was parallelized using a planar domain decomposition scheme and an angular domain decomposition scheme. The parallel performance of the DeCART code is evaluated by solving a rodded variation of the C5G7MOX three dimensional benchmark problem and a simplified three-dimensional SMART PWR core problem. In C5G7MOX problem with 24 CPUs, a speedup of maximum 21 is obtained on an IBM Regatta machine and 22 on a LINUX Cluster in the MOC kernel, which indicates good parallel performance of the DeCART code. In the simplified SMART problem, the memory requirement of about 11 GBytes in the single processor cases reduces to 940 Mbytes with 24 processors, which means that the DeCART code can now solve large core problems with affordable LINUX clusters. (authors)

Problems of high energy physics

International Nuclear Information System (INIS)

Kadyshevskij, V.G.

1989-01-01

Some problems of high energy physics are discussed. The main attention is paid to describibg the standard model. The model comprises quantum chromodynamics and electroweak interaction theory. The problem of CP breaking is considered as well. 8 refs.; 1 tab

Spectral dimensionality of random superconducting networks

International Nuclear Information System (INIS)

Day, A.R.; Xia, W.; Thorpe, M.F.

1988-01-01

We compute the spectral dimensionality d of random superconducting-normal networks by directly examining the low-frequency density of states at the percolation threshold. We find that d = 4.1 +- 0.2 and 5.8 +- 0.3 in two and three dimensions, respectively, which confirms the scaling relation d = 2d/(2-s/ν), where s is the superconducting exponent and ν the correlation-length exponent for percolation. We also consider the one-dimensional problem where scaling arguments predict, and our numerical simulations confirm, that d = 0. A simple argument provides an expression for the density of states of the localized high-frequency modes in this special case. We comment on the connection between our calculations and the ''termite'' problem of a random walker on a random superconducting-normal network and point out difficulties in inferring d from simulations of the termite problem

Differences in problems of motivation in different special groups

NARCIS (Netherlands)

Kunnen, E.S.; Steenbeek, H.W.

1999-01-01

In general, children with a range of special needs have below-average motivation and perceived control. We have investigated whether differences exist between the types of problem in different special groups. Theory distinguishes between two types: low motivation and perceived control can be based

Differences in problems of motivation in different special groups

NARCIS (Netherlands)

Kunnen, E.S.; Steenbeek, H.W.

In general, children with a range of special needs have below-average motivation and perceived control. We have investigated whether differences exist between the types of problem in different special groups. Theory distinguishes between two types: low motivation and perceived control can be based

Evaluating Clustering in Subspace Projections of High Dimensional Data

DEFF Research Database (Denmark)

Müller, Emmanuel; Günnemann, Stephan; Assent, Ira

2009-01-01

Clustering high dimensional data is an emerging research field. Subspace clustering or projected clustering group similar objects in subspaces, i.e. projections, of the full space. In the past decade, several clustering paradigms have been developed in parallel, without thorough evaluation...... and comparison between these paradigms on a common basis. Conclusive evaluation and comparison is challenged by three major issues. First, there is no ground truth that describes the "true" clusters in real world data. Second, a large variety of evaluation measures have been used that reflect different aspects...... of the clustering result. Finally, in typical publications authors have limited their analysis to their favored paradigm only, while paying other paradigms little or no attention. In this paper, we take a systematic approach to evaluate the major paradigms in a common framework. We study representative clustering...

Distribution of high-dimensional entanglement via an intra-city free-space link.

Science.gov (United States)

Steinlechner, Fabian; Ecker, Sebastian; Fink, Matthias; Liu, Bo; Bavaresco, Jessica; Huber, Marcus; Scheidl, Thomas; Ursin, Rupert

2017-07-24

Quantum entanglement is a fundamental resource in quantum information processing and its distribution between distant parties is a key challenge in quantum communications. Increasing the dimensionality of entanglement has been shown to improve robustness and channel capacities in secure quantum communications. Here we report on the distribution of genuine high-dimensional entanglement via a 1.2-km-long free-space link across Vienna. We exploit hyperentanglement, that is, simultaneous entanglement in polarization and energy-time bases, to encode quantum information, and observe high-visibility interference for successive correlation measurements in each degree of freedom. These visibilities impose lower bounds on entanglement in each subspace individually and certify four-dimensional entanglement for the hyperentangled system. The high-fidelity transmission of high-dimensional entanglement under real-world atmospheric link conditions represents an important step towards long-distance quantum communications with more complex quantum systems and the implementation of advanced quantum experiments with satellite links.

High performance computing of density matrix renormalization group method for 2-dimensional model. Parallelization strategy toward peta computing

International Nuclear Information System (INIS)

Yamada, Susumu; Igarashi, Ryo; Machida, Masahiko; Imamura, Toshiyuki; Okumura, Masahiko; Onishi, Hiroaki

2010-01-01

We parallelize the density matrix renormalization group (DMRG) method, which is a ground-state solver for one-dimensional quantum lattice systems. The parallelization allows us to extend the applicable range of the DMRG to n-leg ladders i.e., quasi two-dimension cases. Such an extension is regarded to bring about several breakthroughs in e.g., quantum-physics, chemistry, and nano-engineering. However, the straightforward parallelization requires all-to-all communications between all processes which are unsuitable for multi-core systems, which is a mainstream of current parallel computers. Therefore, we optimize the all-to-all communications by the following two steps. The first one is the elimination of the communications between all processes by only rearranging data distribution with the communication data amount kept. The second one is the avoidance of the communication conflict by rescheduling the calculation and the communication. We evaluate the performance of the DMRG method on multi-core supercomputers and confirm that our two-steps tuning is quite effective. (author)

Statistical Analysis for High-Dimensional Data : The Abel Symposium 2014

CERN Document Server

Bühlmann, Peter; Glad, Ingrid; Langaas, Mette; Richardson, Sylvia; Vannucci, Marina

2016-01-01

This book features research contributions from The Abel Symposium on Statistical Analysis for High Dimensional Data, held in Nyvågar, Lofoten, Norway, in May 2014. The focus of the symposium was on statistical and machine learning methodologies specifically developed for inference in “big data” situations, with particular reference to genomic applications. The contributors, who are among the most prominent researchers on the theory of statistics for high dimensional inference, present new theories and methods, as well as challenging applications and computational solutions. Specific themes include, among others, variable selection and screening, penalised regression, sparsity, thresholding, low dimensional structures, computational challenges, non-convex situations, learning graphical models, sparse covariance and precision matrices, semi- and non-parametric formulations, multiple testing, classification, factor models, clustering, and preselection. Highlighting cutting-edge research and casting light on...

A phase change processor method for solving a one-dimensional phase change problem with convection boundary

Energy Technology Data Exchange (ETDEWEB)

Halawa, E.; Saman, W.; Bruno, F. [Institute for Sustainable Systems and Technologies, School of Advanced Manufacturing and Mechanical Engineering, University of South Australia, Mawson Lakes SA 5095 (Australia)

2010-08-15

A simple yet accurate iterative method for solving a one-dimensional phase change problem with convection boundary is described. The one-dimensional model takes into account the variation in the wall temperature along the direction of the flow as well as the sensible heat during preheating/pre-cooling of the phase change material (PCM). The mathematical derivation of convective boundary conditions has been integrated into a phase change processor (PCP) algorithm that solves the liquid fraction and temperature of the nodes. The algorithm is based on the heat balance at each node as it undergoes heating or cooling which inevitably involves phase change. The paper presents the model and its experimental validation. (author)

Gauge fields in nonlinear group realizations involving two-dimensional space-time symmetry

International Nuclear Information System (INIS)

Machacek, M.E.; McCliment, E.R.

1975-01-01

It is shown that gauge fields may be consistently introduced into a model Lagrangian previously considered by the authors. The model is suggested by the spontaneous breaking of a Lorentz-type group into a quasiphysical two-dimensional space-time and one internal degree of freedom, loosely associated with charge. The introduction of zero-mass gauge fields makes possible the absorption via the Higgs mechanism of the Goldstone fields that appear in the model despite the fact that the Goldstone fields do not transform as scalars. Specifically, gauge invariance of the Yang-Mills type requires the introduction of two sets of massless gauge fields. The transformation properties in two-dimensional space-time suggest that one set is analogous to a charge doublet that behaves like a second-rank tensor in real four-dimensional space time. The other set suggests a spin-one-like charge triplet. Via the Higgs mechanism, the first set absorbs the Goldstone fields and acquires mass. The second set remains massless. If massive gauge fields are introduced, the associated currents are not conserved and the Higgs mechanism is no longer fully operative. The Goldstone fields are not eliminated, but coupling between the Goldstone fields and the gauge fields does shift the mass of the antisymmetric second-rank-tensor gauge field components

A comparison of high-order polynomial and wave-based methods for Helmholtz problems

Science.gov (United States)

Lieu, Alice; Gabard, Gwénaël; Bériot, Hadrien

2016-09-01

The application of computational modelling to wave propagation problems is hindered by the dispersion error introduced by the discretisation. Two common strategies to address this issue are to use high-order polynomial shape functions (e.g. hp-FEM), or to use physics-based, or Trefftz, methods where the shape functions are local solutions of the problem (typically plane waves). Both strategies have been actively developed over the past decades and both have demonstrated their benefits compared to conventional finite-element methods, but they have yet to be compared. In this paper a high-order polynomial method (p-FEM with Lobatto polynomials) and the wave-based discontinuous Galerkin method are compared for two-dimensional Helmholtz problems. A number of different benchmark problems are used to perform a detailed and systematic assessment of the relative merits of these two methods in terms of interpolation properties, performance and conditioning. It is generally assumed that a wave-based method naturally provides better accuracy compared to polynomial methods since the plane waves or Bessel functions used in these methods are exact solutions of the Helmholtz equation. Results indicate that this expectation does not necessarily translate into a clear benefit, and that the differences in performance, accuracy and conditioning are more nuanced than generally assumed. The high-order polynomial method can in fact deliver comparable, and in some cases superior, performance compared to the wave-based DGM. In addition to benchmarking the intrinsic computational performance of these methods, a number of practical issues associated with realistic applications are also discussed.

Modeling high dimensional multichannel brain signals

KAUST Repository

Hu, Lechuan

2017-03-27

In this paper, our goal is to model functional and effective (directional) connectivity in network of multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The primary challenges here are twofold: first, there are major statistical and computational difficulties for modeling and analyzing high dimensional multichannel brain signals; second, there is no set of universally-agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with sufficiently high order so that complex lead-lag temporal dynamics between the channels can be accurately characterized. However, such a model contains a large number of parameters. Thus, we will estimate the high dimensional VAR parameter space by our proposed hybrid LASSLE method (LASSO+LSE) which is imposes regularization on the first step (to control for sparsity) and constrained least squares estimation on the second step (to improve bias and mean-squared error of the estimator). Then to characterize connectivity between channels in a brain network, we will use various measures but put an emphasis on partial directed coherence (PDC) in order to capture directional connectivity between channels. PDC is a directed frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative all possible receivers in the network. Using the proposed modeling approach, we have achieved some insights on learning in a rat engaged in a non-spatial memory task.

Modeling high dimensional multichannel brain signals

KAUST Repository

Hu, Lechuan; Fortin, Norbert; Ombao, Hernando

2017-01-01

In this paper, our goal is to model functional and effective (directional) connectivity in network of multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The primary challenges here are twofold: first, there are major statistical and computational difficulties for modeling and analyzing high dimensional multichannel brain signals; second, there is no set of universally-agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with sufficiently high order so that complex lead-lag temporal dynamics between the channels can be accurately characterized. However, such a model contains a large number of parameters. Thus, we will estimate the high dimensional VAR parameter space by our proposed hybrid LASSLE method (LASSO+LSE) which is imposes regularization on the first step (to control for sparsity) and constrained least squares estimation on the second step (to improve bias and mean-squared error of the estimator). Then to characterize connectivity between channels in a brain network, we will use various measures but put an emphasis on partial directed coherence (PDC) in order to capture directional connectivity between channels. PDC is a directed frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative all possible receivers in the network. Using the proposed modeling approach, we have achieved some insights on learning in a rat engaged in a non-spatial memory task.

Genuinely high-dimensional nonlocality optimized by complementary measurements

International Nuclear Information System (INIS)

Lim, James; Ryu, Junghee; Yoo, Seokwon; Lee, Changhyoup; Bang, Jeongho; Lee, Jinhyoung

2010-01-01

Qubits exhibit extreme nonlocality when their state is maximally entangled and this is observed by mutually unbiased local measurements. This criterion does not hold for the Bell inequalities of high-dimensional systems (qudits), recently proposed by Collins-Gisin-Linden-Massar-Popescu and Son-Lee-Kim. Taking an alternative approach, called the quantum-to-classical approach, we derive a series of Bell inequalities for qudits that satisfy the criterion as for the qubits. In the derivation each d-dimensional subsystem is assumed to be measured by one of d possible measurements with d being a prime integer. By applying to two qubits (d=2), we find that a derived inequality is reduced to the Clauser-Horne-Shimony-Holt inequality when the degree of nonlocality is optimized over all the possible states and local observables. Further applying to two and three qutrits (d=3), we find Bell inequalities that are violated for the three-dimensionally entangled states but are not violated by any two-dimensionally entangled states. In other words, the inequalities discriminate three-dimensional (3D) entanglement from two-dimensional (2D) entanglement and in this sense they are genuinely 3D. In addition, for the two qutrits we give a quantitative description of the relations among the three degrees of complementarity, entanglement and nonlocality. It is shown that the degree of complementarity jumps abruptly to very close to its maximum as nonlocality starts appearing. These characteristics imply that complementarity plays a more significant role in the present inequality compared with the previously proposed inequality.

Three-dimensional printing and pediatric liver disease.

Science.gov (United States)

Alkhouri, Naim; Zein, Nizar N

2016-10-01

Enthusiastic physicians and medical researchers are investigating the role of three-dimensional printing in medicine. The purpose of the current review is to provide a concise summary of the role of three-dimensional printing technology as it relates to the field of pediatric hepatology and liver transplantation. Our group and others have recently demonstrated the feasibility of printing three-dimensional livers with identical anatomical and geometrical landmarks to the native liver to facilitate presurgical planning of complex liver surgeries. Medical educators are exploring the use of three-dimensional printed organs in anatomy classes and surgical residencies. Moreover, mini-livers are being developed by regenerative medicine scientist as a way to test new drugs and, eventually, whole livers will be grown in the laboratory to replace organs with end-stage disease solving the organ shortage problem. From presurgical planning to medical education to ultimately the bioprinting of whole organs for transplantation, three-dimensional printing will change medicine as we know in the next few years.

Does Anxiety Modify the Risk for, or Severity of, Conduct Problems Among Children With Co-Occurring ADHD: Categorical and Dimensional and Analyses.

Science.gov (United States)

Danforth, Jeffrey S; Doerfler, Leonard A; Connor, Daniel F

2017-08-01

The goal was to examine whether anxiety modifies the risk for, or severity of, conduct problems in children with ADHD. Assessment included both categorical and dimensional measures of ADHD, anxiety, and conduct problems. Analyses compared conduct problems between children with ADHD features alone versus children with co-occurring ADHD and anxiety features. When assessed by dimensional rating scales, results showed that compared with children with ADHD alone, those children with ADHD co-occurring with anxiety are at risk for more intense conduct problems. When assessment included a Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV) diagnosis via the Schedule for Affective Disorders and Schizophrenia for School Age Children-Epidemiologic Version (K-SADS), results showed that compared with children with ADHD alone, those children with ADHD co-occurring with anxiety neither had more intense conduct problems nor were they more likely to be diagnosed with oppositional defiant disorder or conduct disorder. Different methodological measures of ADHD, anxiety, and conduct problem features influenced the outcome of the analyses.

Specifications for a two-dimensional multi-group scattering code: ALCI

International Nuclear Information System (INIS)

Bayard, J.P.; Guillou, A.; Lago, B.; Bureau du Colombier, M.J.; Guillou, G.; Vasseur, Ch.

1965-02-01

This report describes the specifications of the ALCI programme. This programme resolves the system of difference equations similar to the homogeneous problem of multigroup neutron scattering, with two dimensions in space, in the three geometries XY, RZ, RΘ. It is possible with this method to calculate geometric and composition criticalities and also to calculate the accessory problem on demand. The maximum number of points dealt with is 6000. The maximum permissible number of groups is 12. The internal iterations are treated by the method of alternating directions. The external iterations are accelerated using the extrapolation method due to Tchebychev. (authors) [fr

The Figured Worlds of High School Science Teachers: Uncovering Three-Dimensional Assessment Decisions

Science.gov (United States)

Ewald, Megan

As a result of recent mandates of the Next Generation Science Standards, assessments are a "system of meaning" amidst a paradigm shift toward three-dimensional assessments. This study is motivated by two research questions: 1) how do high school science teachers describe their processes of decision-making in the development and use of three-dimensional assessments and 2) how do high school science teachers negotiate their identities as assessors in designing three-dimensional assessments. An important factor in teachers' assessment decision making is how they identify themselves as assessors. Therefore, this study investigated the teachers' roles as assessors through the Sociocultural Identity Theory. The most important contribution from this study is the emergent teacher assessment sub-identities: the modifier-recycler , the feeler-finder, and the creator. Using a qualitative phenomenological research design, focus groups, three-series interviews, think-alouds, and document analysis were utilized in this study. These qualitative methods were chosen to elicit rich conversations among teachers, make meaning of the teachers' experiences through in-depth interviews, amplify the thought processes of individual teachers while making assessment decisions, and analyze assessment documents in relation to teachers' perspectives. The findings from this study suggest that--of the 19 participants--only two teachers could consistently be identified as creators and aligned their assessment practices with NGSS. However, assessment sub-identities are not static and teachers may negotiate their identities from one moment to the next within socially constructed realms of interpretation known as figured worlds. Because teachers are positioned in less powerful figured worlds within the dominant discourse of standardization, this study raises awareness as to how the external pressures from more powerful figured worlds socially construct teachers' identities as assessors. For teachers

Highly Scalable Trip Grouping for Large Scale Collective Transportation Systems

DEFF Research Database (Denmark)

Gidofalvi, Gyozo; Pedersen, Torben Bach; Risch, Tore

2008-01-01

Transportation-related problems, like road congestion, parking, and pollution, are increasing in most cities. In order to reduce traffic, recent work has proposed methods for vehicle sharing, for example for sharing cabs by grouping "closeby" cab requests and thus minimizing transportation cost...... and utilizing cab space. However, the methods published so far do not scale to large data volumes, which is necessary to facilitate large-scale collective transportation systems, e.g., ride-sharing systems for large cities. This paper presents highly scalable trip grouping algorithms, which generalize previous...

Two-dimensional lift-up problem for a rigid porous bed

Energy Technology Data Exchange (ETDEWEB)

Chang, Y.; Huang, L. H.; Yang, F. P. Y. [Department of Civil Engineering, National Taiwan University, Taipei, Taiwan (China)

2015-05-15

The present study analytically reinvestigates the two-dimensional lift-up problem for a rigid porous bed that was studied by Mei, Yeung, and Liu [“Lifting of a large object from a porous seabed,” J. Fluid Mech. 152, 203 (1985)]. Mei, Yeung, and Liu proposed a model that treats the bed as a rigid porous medium and performed relevant experiments. In their model, they assumed the gap flow comes from the periphery of the gap, and there is a shear layer in the porous medium; the flow in the gap is described by adhesion approximation [D. J. Acheson, Elementary Fluid Dynamics (Clarendon, Oxford, 1990), pp. 243-245.] and the pore flow by Darcy’s law, and the slip-flow condition proposed by Beavers and Joseph [“Boundary conditions at a naturally permeable wall,” J. Fluid Mech. 30, 197 (1967)] is applied to the bed interface. In this problem, however, the gap flow initially mainly comes from the porous bed, and the shear layer may not exist. Although later the shear effect becomes important, the empirical slip-flow condition might not physically respond to the shear effect, and the existence of the vertical velocity affects the situation so greatly that the slip-flow condition might not be appropriate. In contrast, the present study proposes a more general model for the problem, applying Stokes flow to the gap, the Brinkman equation to the porous medium, and Song and Huang’s [“Laminar poroelastic media flow,” J. Eng. Mech. 126, 358 (2000)] complete interfacial conditions to the bed interface. The exact solution to the problem is found and fits Mei’s experiments well. The breakout phenomenon is examined for different soil beds, mechanics that cannot be illustrated by Mei’s model are revealed, and the theoretical breakout times obtained using Mei’s model and our model are compared. The results show that the proposed model is more compatible with physics and provides results that are more precise.

Resonating-group method for nuclear many-body problems

International Nuclear Information System (INIS)

Tang, Y.C.; LeMere, M.; Thompson, D.R.

1977-01-01

The resonating-group method is a microscopic method which uses fully antisymmetric wave functions, treats correctly the motion of the total center of mass, and takes cluster correlation into consideration. In this review, the formulation of this method is discussed for various nuclear many-body problems, and a complex-generator-coordinate technique which has been employed to evaluate matrix elements required in resonating-group calculations is described. Several illustrative examples of bound-state, scattering, and reaction calculations, which serve to demonstrate the usefulness of this method, are presented. Finally, by utilization of the results of these calculations, the role played by the Pauli principle in nuclear scattering and reaction processes is discussed. 21 figures, 2 tables, 185 references

Three-dimensional formulation of the relativistic two-body problem in terms of rapidities

International Nuclear Information System (INIS)

Amirkhanov, I.V.; Grusha, G.V.; Mir-Kasimov, R.M.

1976-01-01

The scheme, based on the three-dimensional relativistic equation of the quasi-potential type is developed. As a basic variable rapidity, canonically conjugated to the relativistic relative distance is adopted. The free Green function has a simple pole in the complex rapidity plane, ensuring the fulfillment of the elastic unitarity for real potentials. In the local potential case the corresponding partial wave equation in configurational r-representation is a differential second-order equation. The problem of boundary conditions, which is a non-trivial one in the relativistic r-space, is studied. The exact solutions of the equation in simple cases have been found

Two-dimensional impurity transport calculations for a high recycling divertor

International Nuclear Information System (INIS)

Brooks, J.N.

1986-04-01

Two dimensional analysis of impurity transport in a high recycling divertor shows asymmetric particle fluxes to the divertor plate, low helium pumping efficiency, and high scrapeoff zone shielding for sputtered impurities

Outcomes of specific interpersonal problems for binge eating disorder: comparing group psychodynamic interpersonal psychotherapy and group cognitive behavioral therapy.

Science.gov (United States)

Tasca, Giorgio A; Balfour, Louise; Presniak, Michelle D; Bissada, Hany

2012-04-01

We assessed whether an attachment-based treatment, Group Psychodynamic Interpersonal Psychotherapy (GPIP) had a greater impact compared to Group Cognitive Behavioral Therapy (GCBT) on Cold/Distant and Intrusive/Needy interpersonal problems. Ninety-five individuals with Binge Eating Disorder (BED) were randomized to GPIP or GCBT and assessed at pre-, post-, and six months post-treatment. Both therapies resulted in a significant decrease in all eight interpersonal problem subscales except the Nonassertive subscale. GPIP resulted in a greater reduction in the Cold/Distant subscale compared to GCBT, but no differences were found for changes in the Intrusive/Needy subscale. GPIP may be most relevant for those with BED who have Cold/Distant interpersonal problems and attachment avoidance.

The finite element solution of two-dimensional transverse magnetic scattering problems on the connection machine

International Nuclear Information System (INIS)

Hutchinson, S.; Costillo, S.; Dalton, K.; Hensel, E.

1990-01-01

A study is conducted of the finite element solution of the partial differential equations governing two-dimensional electromagnetic field scattering problems on a SIMD computer. A nodal assembly technique is introduced which maps a single node to a single processor. The physical domain is first discretized in parallel to yield the node locations of an O-grid mesh. Next, the system of equations is assembled and then solved in parallel using a conjugate gradient algorithm for complex-valued, non-symmetric, non-positive definite systems. Using this technique and Thinking Machines Corporation's Connection Machine-2 (CM-2), problems with more than 250k nodes are solved. Results of electromagnetic scattering, governed by the 2-d scalar Hemoholtz wave equations are presented in this paper. Solutions are demonstrated for a wide range of objects. A summary of performance data is given for the set of test problems

On the Zeeman Effect in highly excited atoms: 2. Three-dimensional case

International Nuclear Information System (INIS)

Baseia, B.; Medeiros e Silva Filho, J.

1984-01-01

A previous result, found in two-dimensional hydrogen-atoms, is extended to the three-dimensional case. A mapping of a four-dimensional space R 4 onto R 3 , that establishes an equivalence between Coulomb and harmonic potentials, is used to show that the exact solution of the Zeeman effect in highly excited atoms, cannot be reached. (Author) [pt

Larger groups of passerines are more efficient problem solvers in the wild

Science.gov (United States)

Morand-Ferron, Julie; Quinn, John L.

2011-01-01

Group living commonly helps organisms face challenging environmental conditions. Although a known phenomenon in humans, recent findings suggest that a benefit of group living in animals generally might be increased innovative problem-solving efficiency. This benefit has never been demonstrated in a natural context, however, and the mechanisms underlying improved efficiency are largely unknown. We examined the problem-solving performance of great and blue tits at automated devices and found that efficiency increased with flock size. This relationship held when restricting the analysis to naive individuals, demonstrating that larger groups increased innovation efficiency. In addition to this effect of naive flock size, the presence of at least one experienced bird increased the frequency of solving, and larger flocks were more likely to contain experienced birds. These findings provide empirical evidence for the “pool of competence” hypothesis in nonhuman animals. The probability of success also differed consistently between individuals, a necessary condition for the pool of competence hypothesis. Solvers had a higher probability of success when foraging with a larger number of companions and when using devices located near rather than further from protective tree cover, suggesting a role for reduced predation risk on problem-solving efficiency. In contrast to traditional group living theory, individuals joining larger flocks benefited from a higher seed intake, suggesting that group living facilitated exploitation of a novel food source through improved problem-solving efficiency. Together our results suggest that both ecological and social factors, through reduced predation risk and increased pool of competence, mediate innovation in natural populations. PMID:21930936

Multi-dimensional analysis of high resolution γ-ray data

International Nuclear Information System (INIS)

Flibotte, S.; Huttmeier, U.J.; France, G. de; Haas, B.; Romain, P.; Theisen, Ch.; Vivien, J.P.; Zen, J.; Bednarczyk, P.

1992-01-01

High resolution γ-ray multi-detectors capable of measuring high-fold coincidences with a large efficiency are presently under construction (EUROGAM, GASP, GAMMASPHERE). The future experimental progress in our understanding of nuclear structure at high spin critically depends on our ability to analyze the data in a multi-dimensional space and to resolve small photopeaks of interest from the generally large background. Development of programs to process such high-fold events is still in its infancy and only the 3-fold case has been treated so far. As a contribution to the software development associated with the EUROGAM spectrometer, we have written and tested the performances of computer codes designed to select multi-dimensional gates from 3-, 4- and 5-fold coincidence databases. The tests were performed on events generated with a Monte Carlo simulation and also on experimental data (triples) recorded with the 8π spectrometer and with a preliminary version of the EUROGAM array. (author). 7 refs., 3 tabs., 1 fig

Multi-dimensional analysis of high resolution {gamma}-ray data

Energy Technology Data Exchange (ETDEWEB)

Flibotte, S; Huttmeier, U J; France, G de; Haas, B; Romain, P; Theisen, Ch; Vivien, J P; Zen, J [Centre National de la Recherche Scientifique (CNRS), 67 - Strasbourg (France); Bednarczyk, P [Institute of Nuclear Physics, Cracow (Poland)

1992-08-01

High resolution {gamma}-ray multi-detectors capable of measuring high-fold coincidences with a large efficiency are presently under construction (EUROGAM, GASP, GAMMASPHERE). The future experimental progress in our understanding of nuclear structure at high spin critically depends on our ability to analyze the data in a multi-dimensional space and to resolve small photopeaks of interest from the generally large background. Development of programs to process such high-fold events is still in its infancy and only the 3-fold case has been treated so far. As a contribution to the software development associated with the EUROGAM spectrometer, we have written and tested the performances of computer codes designed to select multi-dimensional gates from 3-, 4- and 5-fold coincidence databases. The tests were performed on events generated with a Monte Carlo simulation and also on experimental data (triples) recorded with the 8{pi} spectrometer and with a preliminary version of the EUROGAM array. (author). 7 refs., 3 tabs., 1 fig.

On Robust Information Extraction from High-Dimensional Data

Czech Academy of Sciences Publication Activity Database

Kalina, Jan

2014-01-01

Roč. 9, č. 1 (2014), s. 131-144 ISSN 1452-4864 Grant - others:GA ČR(CZ) GA13-01930S Institutional support: RVO:67985807 Keywords : data mining * high-dimensional data * robust econometrics * outliers * machine learning Subject RIV: IN - Informatics, Computer Science

Exact Solution of the Two-Dimensional Problem on an Impact Ideal-Liquid Jet

Science.gov (United States)

Belik, V. D.

2018-05-01

The two-dimensional problem on the collision of a potential ideal-liquid jet, outflowing from a reservoir through a nozzle, with an infinite plane obstacle was considered for the case where the distance between the nozzle exit section and the obstacle is finite. An exact solution of this problem has been found using methods of the complex-variable function theory. Simple analytical expressions for the complex velocity of the liquid, its flow rate, and the force of action of the jet on the obstacle have been obtained. The velocity distributions of the liquid at the nozzle exit section, in the region of spreading of the jet, and at the obstacle have been constructed for different distances between the nozzle exit section and the obstacle. Analytical expressions for the thickness of the boundary layer and the Nusselt number at the point of stagnation of the jet have been obtained. A number of distributions of the local friction coefficient and the Nusselt number of the indicated jet are presented.

An analytical discrete ordinates solution for a nodal model of a two-dimensional neutron transport problem

International Nuclear Information System (INIS)

Filho, J. F. P.; Barichello, L. B.

2013-01-01

In this work, an analytical discrete ordinates method is used to solve a nodal formulation of a neutron transport problem in x, y-geometry. The proposed approach leads to an important reduction in the order of the associated eigenvalue systems, when combined with the classical level symmetric quadrature scheme. Auxiliary equations are proposed, as usually required for nodal methods, to express the unknown fluxes at the boundary introduced as additional unknowns in the integrated equations. Numerical results, for the problem defined by a two-dimensional region with a spatially constant and isotropically emitting source, are presented and compared with those available in the literature. (authors)

Monolayer group-III monochalcogenides by oxygen functionalization: a promising class of two-dimensional topological insulators

Science.gov (United States)

Zhou, Si; Liu, Cheng-Cheng; Zhao, Jijun; Yao, Yugui

2018-03-01

Monolayer group-III monochalcogenides (MX, M = Ga, In; X = S, Se, Te), an emerging category of two-dimensional (2D) semiconductors, hold great promise for electronics, optoelectronics and catalysts. By first-principles calculations, we show that the phonon dispersion and Raman spectra, as well as the electronic and topological properties of monolayer MX can be tuned by oxygen functionalization. Chemisorption of oxygen atoms on one side or both sides of the MX sheet narrows or even closes the band gap, enlarges work function, and significantly reduces the carrier effective mass. More excitingly, InS, InSe, and InTe monolayers with double-side oxygen functionalization are 2D topological insulators with sizeable bulk gap up to 0.21 eV. Their low-energy bands near the Fermi level are dominated by the px and py orbitals of atoms, allowing band engineering via in-plane strains. Our studies provide viable strategy for realizing quantum spin Hall effect in monolayer group-III monochalcogenides at room temperature, and utilizing these novel 2D materials for high-speed and dissipationless transport devices.

High-resolution coherent three-dimensional spectroscopy of Br2.

Science.gov (United States)

Chen, Peter C; Wells, Thresa A; Strangfeld, Benjamin R

2013-07-25

In the past, high-resolution spectroscopy has been limited to small, simple molecules that yield relatively uncongested spectra. Larger and more complex molecules have a higher density of peaks and are susceptible to complications (e.g., effects from conical intersections) that can obscure the patterns needed to resolve and assign peaks. Recently, high-resolution coherent two-dimensional (2D) spectroscopy has been used to resolve and sort peaks into easily identifiable patterns for molecules where pattern-recognition has been difficult. For very highly congested spectra, however, the ability to resolve peaks using coherent 2D spectroscopy is limited by the bandwidth of instrumentation. In this article, we introduce and investigate high-resolution coherent three-dimensional spectroscopy (HRC3D) as a method for dealing with heavily congested systems. The resulting patterns are unlike those in high-resolution coherent 2D spectra. Analysis of HRC3D spectra could provide a means for exploring the spectroscopy of large and complex molecules that have previously been considered too difficult to study.

Three-dimensional triplet tracking for LHC and future high rate experiments

International Nuclear Information System (INIS)

Schöning, A

2014-01-01

The hit combinatorial problem is a main challenge for track reconstruction and triggering at high rate experiments. At hadron colliders the dominant fraction of hits is due to low momentum tracks for which multiple scattering (MS) effects dominate the hit resolution. MS is also the dominating source for hit confusion and track uncertainties in low energy precision experiments. In all such environments, where MS dominates, track reconstruction and fitting can be largely simplified by using three-dimensional (3D) hit-triplets as provided by pixel detectors. This simplification is possible since track uncertainties are solely determined by MS if high precision spatial information is provided. Fitting of hit-triplets is especially simple for tracking detectors in solenoidal magnetic fields. The over-constrained 3D-triplet method provides a complete set of track parameters and is robust against fake hit combinations. Full tracks can be reconstructed step-wise by connecting hit triplet combinations from different layers, thus heavily reducing the combinatorial problem and accelerating track linking. The triplet method is ideally suited for pixel detectors where hits can be treated as 3D-space points. With the advent of relatively cheap and industrially available CMOS-sensors the construction of highly granular full scale pixel tracking detectors seems to be possible also for experiments at LHC or future high energy (hadron) colliders. In this paper tracking performance studies for full-scale pixel detectors, including their optimisation for 3D-triplet tracking, are presented. The results obtained for different types of tracker geometries and different reconstruction methods are compared. The potential of reducing the number of tracking layers and - along with that - the material budget using this new tracking concept is discussed. The possibility of using 3D-triplet tracking for triggering and fast online reconstruction is highlighted

Convergence rates and finite-dimensional approximations for nonlinear ill-posed problems involving monotone operators in Banach spaces

International Nuclear Information System (INIS)

Nguyen Buong.

1992-11-01

The purpose of this paper is to investigate convergence rates for an operator version of Tikhonov regularization constructed by dual mapping for nonlinear ill-posed problems involving monotone operators in real reflective Banach spaces. The obtained results are considered in combination with finite-dimensional approximations for the space. An example is considered for illustration. (author). 15 refs

An approximate solution of the two-group critical problem for reflected slabs

International Nuclear Information System (INIS)

Ishiguro, Y.; Garcia, R.D.M.

1977-01-01

A new approximation is developed to solve two group slab problems involving two media where one of the media is infinite. The method consists in combining the P sub(L) approximation with invariance principles. Several numerical results are reported for the critical slab problem [pt

An Inverse Source Problem for a One-dimensional Wave Equation: An Observer-Based Approach

KAUST Repository

Asiri, Sharefa M.

2013-05-25

Observers are well known in the theory of dynamical systems. They are used to estimate the states of a system from some measurements. However, recently observers have also been developed to estimate some unknowns for systems governed by Partial differential equations. Our aim is to design an observer to solve inverse source problem for a one dimensional wave equation. Firstly, the problem is discretized in both space and time and then an adaptive observer based on partial field measurements (i.e measurements taken form the solution of the wave equation) is applied to estimate both the states and the source. We see the effectiveness of this observer in both noise-free and noisy cases. In each case, numerical simulations are provided to illustrate the effectiveness of this approach. Finally, we compare the performance of the observer approach with Tikhonov regularization approach.

Three dimensional analysis of laterally loaded piles

International Nuclear Information System (INIS)

Yilmaz, C.

1987-01-01

In this study static analysis of laterally loaded pile is studied by the three models. The first model is the beam on discrete elastic springs. This model is analyzed using a flexibility method. The second model is the beam on a two-parameter elastic foundation. This model is analyzed using the linear finite element method. The third model is the finite element model, using the three-dimensional iso-parametric parabolic brick element. Three-dimensional pile group analysis is also performed using elastic constants of single pile obtained by any one of the above analyses. The main objective is to develop computer programs for each model related to single piles and to group analysis. Then, the deflections, rotations, moments, shears, stresses and strains of the single pile are obtained at any arbitrary point. Comparison is made between each model and with other studies such as Poulos 1971, Desai and Appel 1976. In addition, to provide a benchmark of three-dimensional finite element analysis, the Boussinesq problem is analyzed. (orig.)

Do High School Students in India Gamble? A Study of Problem Gambling and Its Correlates.

Science.gov (United States)

Jaisoorya, T S; Beena, K V; Beena, M; Ellangovan, K; Thennarassu, K; Bowden-Jones, Henrietta; Benegal, Vivek; George, Sanju

2017-06-01

Studies from the West suggest that significant numbers of high school students gamble, despite it being illegal in this age group. To date, there have been no studies on the prevalence of gambling among senior high school and higher secondary school students in India. This study reports point prevalence of gambling and its psychosocial correlates among high school students in the State of Kerala, India. 5043 high school students in the age group 15-19 years, from 73 schools, were selected by cluster random sampling from the district of Ernakulam, Kerala, South India. They completed questionnaires that assessed gambling, substance use, psychological distress, suicidality, and symptoms of Attention Deficit Hyperactivity Disorder (ADHD). Of a total of 4989 completed questionnaires, 1400 (27.9 %) high school students reported to have ever gambled and 353 (7.1 %) were problem gamblers. Of those who had ever gambled, 25.2 % were problem gamblers. Sports betting (betting on cricket and football) was the most popular form of gambling followed by the lottery. Problem gamblers when compared with non-problem gamblers and non-gamblers were significantly more likely to be male, have academic failures, have higher rates of lifetime alcohol and tobacco use, psychological distress, suicidality, history of sexual abuse and higher ADHD symptom scores. Gambling among adolescents in India deserves greater attention, as one in four students who ever gambled was a problem gambler and because of its association with a range of psychosocial variables.

Shilajit: A panacea for high-altitude problems.

Science.gov (United States)

Meena, Harsahay; Pandey, H K; Arya, M C; Ahmed, Zakwan

2010-01-01

High altitude problems like hypoxia, acute mountain sickness, high altitude cerebral edema, pulmonary edema, insomnia, tiredness, lethargy, lack of appetite, body pain, dementia, and depression may occur when a person or a soldier residing in a lower altitude ascends to high-altitude areas. These problems arise due to low atmospheric pressure, severe cold, high intensity of solar radiation, high wind velocity, and very high fluctuation of day and night temperatures in these regions. These problems may escalate rapidly and may sometimes become life-threatening. Shilajit is a herbomineral drug which is pale-brown to blackish-brown, is composed of a gummy exudate that oozes from the rocks of the Himalayas in the summer months. It contains humus, organic plant materials, and fulvic acid as the main carrier molecules. It actively takes part in the transportation of nutrients into deep tissues and helps to overcome tiredness, lethargy, and chronic fatigue. Shilajit improves the ability to handle high altitudinal stresses and stimulates the immune system. Thus, Shilajit can be given as a supplement to people ascending to high-altitude areas so that it can act as a "health rejuvenator" and help to overcome high-altitude related problems.

High-intensity ionization approximations: test of convergence in a one-dimensional model

International Nuclear Information System (INIS)

Antunes Neto, H.S.; Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro); Davidovich, L.; Marchesin, D.

1983-06-01

By solving numerically a one-dimensional model, the range of validity of some non-perturbative treatments proposed for the problem of atomic ionization by strong laser fields is examined. Some scalling properties of the ionization probability are stablished and a new approximation, which converges to the exact results in the limit of very strong fields is proposed. (Author) [pt

Inference in High-dimensional Dynamic Panel Data Models

DEFF Research Database (Denmark)

Kock, Anders Bredahl; Tang, Haihan

We establish oracle inequalities for a version of the Lasso in high-dimensional fixed effects dynamic panel data models. The inequalities are valid for the coefficients of the dynamic and exogenous regressors. Separate oracle inequalities are derived for the fixed effects. Next, we show how one can...

Group problem-solving skills training for self-harm: randomised controlled trial.

Science.gov (United States)

McAuliffe, Carmel; McLeavey, Breda C; Fitzgerald, Tony; Corcoran, Paul; Carroll, Bernie; Ryan, Louise; O'Keeffe, Brian; Fitzgerald, Eva; Hickey, Portia; O'Regan, Mary; Mulqueen, Jillian; Arensman, Ella

2014-01-01

Rates of self-harm are high and have recently increased. This trend and the repetitive nature of self-harm pose a significant challenge to mental health services. To determine the efficacy of a structured group problem-solving skills training (PST) programme as an intervention approach for self-harm in addition to treatment as usual (TAU) as offered by mental health services. A total of 433 participants (aged 18-64 years) were randomly assigned to TAU plus PST or TAU alone. Assessments were carried out at baseline and at 6-week and 6-month follow-up and repeated hospital-treated self-harm was ascertained at 12-month follow-up. The treatment groups did not differ in rates of repeated self-harm at 6-week, 6-month and 12-month follow-up. Both treatment groups showed significant improvements in psychological and social functioning at follow-up. Only one measure (needing and receiving practical help from those closest to them) showed a positive treatment effect at 6-week (P = 0.004) and 6-month (P = 0.01) follow-up. Repetition was not associated with waiting time in the PST group. This brief intervention for self-harm is no more effective than treatment as usual. Further work is required to establish whether a modified, more intensive programme delivered sooner after the index episode would be effective.

(Weakly) three-dimensional caseology

International Nuclear Information System (INIS)

Pomraning, G.C.

1996-01-01

The singular eigenfunction technique of Case for solving one-dimensional planar symmetry linear transport problems is extended to a restricted class of three-dimensional problems. This class involves planar geometry, but with forcing terms (either boundary conditions or internal sources) which are weakly dependent upon the transverse spatial variables. Our analysis involves a singular perturbation about the classic planar analysis, and leads to the usual Case discrete and continuum modes, but modulated by weakly dependent three-dimensional spatial functions. These functions satisfy parabolic differential equations, with a different diffusion coefficient for each mode. Representative one-speed time-independent transport problems are solved in terms of these generalised Case eigenfunctions. Our treatment is very heuristic, but may provide an impetus for more rigorous analysis. (author)

Procedures for two-dimensional electrophoresis of proteins

Energy Technology Data Exchange (ETDEWEB)

Tollaksen, S.L.; Giometti, C.S.

1996-10-01

High-resolution two-dimensional gel electrophoresis (2DE) of proteins, using isoelectric focusing in the first dimension and sodium dodecyl sulfate/polyacrylamide gel electrophoresis (SDS-PAGE) in the second, was first described in 1975. In the 20 years since those publications, numerous modifications of the original method have evolved. The ISO-DALT system of 2DE is a high-throughput approach that has stood the test of time. The problem of casting many isoelectric focusing gels and SDS-PAGE slab gels (up to 20) in a reproducible manner has been solved by the use of the techniques and equipment described in this manual. The ISO-DALT system of two-dimensional gel electrophoresis originated in the late 1970s and has been modified many times to improve its high-resolution, high-throughput capabilities. This report provides the detailed procedures used with the current ISO-DALT system to prepare, run, stain, and photograph two-dimensional gels for protein analysis.

[Application Progress of Three-dimensional Laser Scanning Technology in Medical Surface Mapping].

Science.gov (United States)

Zhang, Yonghong; Hou, He; Han, Yuchuan; Wang, Ning; Zhang, Ying; Zhu, Xianfeng; Wang, Mingshi

2016-04-01

The booming three-dimensional laser scanning technology can efficiently and effectively get spatial three-dimensional coordinates of the detected object surface and reconstruct the image at high speed,high precision and large capacity of information.Non-radiation,non-contact and the ability of visualization make it increasingly popular in three-dimensional surface medical mapping.This paper reviews the applications and developments of three-dimensional laser scanning technology in medical field,especially in stomatology,plastic surgery and orthopedics.Furthermore,the paper also discusses the application prospects in the future as well as the biomedical engineering problems it would encounter with.

High-dimensional orbital angular momentum entanglement concentration based on Laguerre–Gaussian mode selection

International Nuclear Information System (INIS)

Zhang, Wuhong; Su, Ming; Wu, Ziwen; Lu, Meng; Huang, Bingwei; Chen, Lixiang

2013-01-01

Twisted photons enable the definition of a Hilbert space beyond two dimensions by orbital angular momentum (OAM) eigenstates. Here we propose a feasible entanglement concentration experiment, to enhance the quality of high-dimensional entanglement shared by twisted photon pairs. Our approach is started from the full characterization of entangled spiral bandwidth, and is then based on the careful selection of the Laguerre–Gaussian (LG) modes with specific radial and azimuthal indices p and ℓ. In particular, we demonstrate the possibility of high-dimensional entanglement concentration residing in the OAM subspace of up to 21 dimensions. By means of LabVIEW simulations with spatial light modulators, we show that the Shannon dimensionality could be employed to quantify the quality of the present concentration. Our scheme holds promise in quantum information applications defined in high-dimensional Hilbert space. (letter)

Intertwined Hamiltonians in two-dimensional curved spaces

International Nuclear Information System (INIS)

Aghababaei Samani, Keivan; Zarei, Mina

2005-01-01

The problem of intertwined Hamiltonians in two-dimensional curved spaces is investigated. Explicit results are obtained for Euclidean plane, Minkowski plane, Poincare half plane (AdS 2 ), de Sitter plane (dS 2 ), sphere, and torus. It is shown that the intertwining operator is related to the Killing vector fields and the isometry group of corresponding space. It is shown that the intertwined potentials are closely connected to the integral curves of the Killing vector fields. Two problems are considered as applications of the formalism presented in the paper. The first one is the problem of Hamiltonians with equispaced energy levels and the second one is the problem of Hamiltonians whose spectrum is like the spectrum of a free particle

High Dimensional Modulation and MIMO Techniques for Access Networks

DEFF Research Database (Denmark)

Binti Othman, Maisara

Exploration of advanced modulation formats and multiplexing techniques for next generation optical access networks are of interest as promising solutions for delivering multiple services to end-users. This thesis addresses this from two different angles: high dimensionality carrierless...... the capacity per wavelength of the femto-cell network. Bit rate up to 1.59 Gbps with fiber-wireless transmission over 1 m air distance is demonstrated. The results presented in this thesis demonstrate the feasibility of high dimensionality CAP in increasing the number of dimensions and their potentially......) optical access network. 2 X 2 MIMO RoF employing orthogonal frequency division multiplexing (OFDM) with 5.6 GHz RoF signaling over all-vertical cavity surface emitting lasers (VCSEL) WDM passive optical networks (PONs). We have employed polarization division multiplexing (PDM) to further increase...

Method for coupling two-dimensional to three-dimensional discrete ordinates calculations

International Nuclear Information System (INIS)

Thompson, J.L.; Emmett, M.B.; Rhoades, W.A.; Dodds, H.L. Jr.

1985-01-01

A three-dimensional (3-D) discrete ordinates transport code, TORT, has been developed at the Oak Ridge National Laboratory for radiation penetration studies. It is not feasible to solve some 3-D penetration problems with TORT, such as a building located a large distance from a point source, because (a) the discretized 3-D problem is simply too big to fit on the computer or (b) the computing time (and corresponding cost) is prohibitive. Fortunately, such problems can be solved with a hybrid approach by coupling a two-dimensional (2-D) description of the point source, which is assumed to be azimuthally symmetric, to a 3-D description of the building, the region of interest. The purpose of this paper is to describe this hybrid methodology along with its implementation and evaluation in the DOTTOR (Discrete Ordinates to Three-dimensional Oak Ridge Transport) code

Evaluation of group theoretical characteristics using the symbolic manipulation language MAPLE

International Nuclear Information System (INIS)

Taneri, U.; Paldus, J.

1994-01-01

Relying on theoretical developments exploiting quasispin and the pseudo-orthogonal group in the Hubbard model of cyclic polyenes, the general expressions for generating polynomials, providing the dimensional information for relevant irreducible representations, were derived. These generating polynomials result from 1-dimensional formulas through rather tedious algebraic manipulations involving ratios of polynomials with fractional powers. It is shown that these expressions may be efficiently handled using the symbolic manipulation language MAPLE and the dimensional information for an arbitrary spin, isospin, and quasimomentum obtained. Exploitation of symbolic computation for other group theoretical problems that are relevant in quantum chemical calculations and their relationship with Guassian polynomial based combinatorial approaches is also briefly addressed and various possible applications outlined

A parameter identification problem arising from a two-dimensional airfoil section model

International Nuclear Information System (INIS)

Cerezo, G.M.

1994-01-01

The development of state space models for aeroelastic systems, including unsteady aerodynamics, is particularly important for the design of highly maneuverable aircraft. In this work we present a state space formulation for a special class of singular neutral functional differential equations (SNFDE) with initial data in C(-1, 0). This work is motivated by the two-dimensional airfoil model presented by Burns, Cliff and Herdman in. In the same authors discuss the validity of the assumptions under which the model was formulated. They pay special attention to the derivation of the evolution equation for the circulation on the airfoil. This equation was coupled to the rigid-body dynamics of the airfoil in order to obtain a complete set of functional differential equations that describes the composite system. The resulting mathematical model for the aeroelastic system has a weakly singular component. In this work we consider a finite delay approximation to the model presented in. We work with a scalar model in which we consider the weak singularity appearing in the original problem. The main goal of this work is to develop numerical techniques for the identification of the parameters appearing in the kernel of the associated scalar integral equation. Clearly this is the first step in the study of parameter identification for the original model and the corresponding validation of this model for the aeroelastic system

Minimizing waste (off-cuts using cutting stock model: The case of one dimensional cutting stock problem in wood working industry

Directory of Open Access Journals (Sweden)

Gbemileke A. Ogunranti

2016-09-01

Full Text Available Purpose: The main objective of this study is to develop a model for solving the one dimensional cutting stock problem in the wood working industry, and develop a program for its implementation. Design/methodology/approach: This study adopts the pattern oriented approach in the formulation of the cutting stock model. A pattern generation algorithm was developed and coded using Visual basic.NET language. The cutting stock model developed is a Linear Programming (LP Model constrained by numerous feasible patterns. A LP solver was integrated with the pattern generation algorithm program to develop a one - dimensional cutting stock model application named GB Cutting Stock Program. Findings and Originality/value: Applying the model to a real life optimization problem significantly reduces material waste (off-cuts and minimizes the total stock used. The result yielded about 30.7% cost savings for company-I when the total stock materials used is compared with the former cutting plan. Also, to evaluate the efficiency of the application, Case I problem was solved using two top commercial 1D-cutting stock software.  The results show that the GB program performs better when related results were compared. Research limitations/implications: This study round up the linear programming solution for the number of pattern to cut. Practical implications: From Managerial perspective, implementing optimized cutting plans increases productivity by eliminating calculating errors and drastically reducing operator mistakes. Also, financial benefits that can annually amount to millions in cost savings can be achieved through significant material waste reduction. Originality/value: This paper developed a linear programming one dimensional cutting stock model based on a pattern generation algorithm to minimize waste in the wood working industry. To implement the model, the algorithm was coded using VisualBasic.net and linear programming solver called lpsolvedll (dynamic

NUMERICAL METHOD OF MIXED FINITE VOLUME-MODIFIED UPWIND FRACTIONAL STEP DIFFERENCE FOR THREE-DIMENSIONAL SEMICONDUCTOR DEVICE TRANSIENT BEHAVIOR PROBLEMS

Institute of Scientific and Technical Information of China (English)

Yirang YUAN; Qing YANG; Changfeng LI; Tongjun SUN

2017-01-01

Transient behavior of three-dimensional semiconductor device with heat conduction is described by a coupled mathematical system of four quasi-linear partial differential equations with initial-boundary value conditions.The electric potential is defined by an elliptic equation and it appears in the following three equations via the electric field intensity.The electron concentration and the hole concentration are determined by convection-dominated diffusion equations and the temperature is interpreted by a heat conduction equation.A mixed finite volume element approximation,keeping physical conservation law,is used to get numerical values of the electric potential and the accuracy is improved one order.Two concentrations and the heat conduction are computed by a fractional step method combined with second-order upwind differences.This method can overcome numerical oscillation,dispersion and decreases computational complexity.Then a three-dimensional problem is solved by computing three successive one-dimensional problems where the method of speedup is used and the computational work is greatly shortened.An optimal second-order error estimate in L2 norm is derived by using prior estimate theory and other special techniques of partial differential equations.This type of mass-conservative parallel method is important and is most valuable in numerical analysis and application of semiconductor device.

On the Special Problems in Creating Group Cohesion Within the Prison Setting.

Science.gov (United States)

Juda, Daniel P.

1983-01-01

Describes attempts to form a communication group among male and female inmates. The failure of this effort is discussed with emphasis on the special problems and needs of groups in prisons and the lack of insight among the institution's administration and staff. (JAC)

High-dimensional single-cell cancer biology.

Science.gov (United States)

Irish, Jonathan M; Doxie, Deon B

2014-01-01

Cancer cells are distinguished from each other and from healthy cells by features that drive clonal evolution and therapy resistance. New advances in high-dimensional flow cytometry make it possible to systematically measure mechanisms of tumor initiation, progression, and therapy resistance on millions of cells from human tumors. Here we describe flow cytometry techniques that enable a "single-cell " view of cancer. High-dimensional techniques like mass cytometry enable multiplexed single-cell analysis of cell identity, clinical biomarkers, signaling network phospho-proteins, transcription factors, and functional readouts of proliferation, cell cycle status, and apoptosis. This capability pairs well with a signaling profiles approach that dissects mechanism by systematically perturbing and measuring many nodes in a signaling network. Single-cell approaches enable study of cellular heterogeneity of primary tissues and turn cell subsets into experimental controls or opportunities for new discovery. Rare populations of stem cells or therapy-resistant cancer cells can be identified and compared to other types of cells within the same sample. In the long term, these techniques will enable tracking of minimal residual disease (MRD) and disease progression. By better understanding biological systems that control development and cell-cell interactions in healthy and diseased contexts, we can learn to program cells to become therapeutic agents or target malignant signaling events to specifically kill cancer cells. Single-cell approaches that provide deep insight into cell signaling and fate decisions will be critical to optimizing the next generation of cancer treatments combining targeted approaches and immunotherapy.

An analytical approach for a nodal formulation of a two-dimensional fixed-source neutron transport problem in heterogeneous medium

Energy Technology Data Exchange (ETDEWEB)

Basso Barichello, Liliane; Dias da Cunha, Rudnei [Universidade Federal do Rio Grande do Sul, Porto Alegre, RS (Brazil). Inst. de Matematica; Becker Picoloto, Camila [Universidade Federal do Rio Grande do Sul, Porto Alegre, RS (Brazil). Programa de Pos-Graduacao em Engenharia Mecanica; Tres, Anderson [Universidade Federal do Rio Grande do Sul, Porto Alegre, RS (Brazil). Programa de Pos-Graduacao em Matematica Aplicada

2015-05-15

A nodal formulation of a fixed-source two-dimensional neutron transport problem, in Cartesian geometry, defined in a heterogeneous medium, is solved by an analytical approach. Explicit expressions, in terms of the spatial variables, are derived for averaged fluxes in each region in which the domain is subdivided. The procedure is an extension of an analytical discrete ordinates method, the ADO method, for the solution of the two-dimensional homogeneous medium case. The scheme is developed from the discrete ordinates version of the two-dimensional transport equation along with the level symmetric quadrature scheme. As usual for nodal schemes, relations between the averaged fluxes and the unknown angular fluxes at the contours are introduced as auxiliary equations. Numerical results are in agreement with results available in the literature.

Estimation of surface temperature by using inverse problem. Part 1. Steady state analyses of two-dimensional cylindrical system

International Nuclear Information System (INIS)

Takahashi, Toshio; Terada, Atsuhiko

2006-03-01

In the corrosive process environment of thermochemical hydrogen production Iodine-Sulfur process plant, there is a difficulty in the direct measurement of surface temperature of the structural materials. An inverse problem method can effectively be applied for this problem, which enables estimation of the surface temperature using the temperature data at the inside of structural materials. This paper shows analytical results of steady state temperature distributions in a two-dimensional cylindrical system cooled by impinging jet flow, and clarifies necessary order of multiple-valued function from the viewpoint of engineeringly satisfactory precision. (author)

Simulation-based hypothesis testing of high dimensional means under covariance heterogeneity.

Science.gov (United States)

Chang, Jinyuan; Zheng, Chao; Zhou, Wen-Xin; Zhou, Wen

2017-12-01

In this article, we study the problem of testing the mean vectors of high dimensional data in both one-sample and two-sample cases. The proposed testing procedures employ maximum-type statistics and the parametric bootstrap techniques to compute the critical values. Different from the existing tests that heavily rely on the structural conditions on the unknown covariance matrices, the proposed tests allow general covariance structures of the data and therefore enjoy wide scope of applicability in practice. To enhance powers of the tests against sparse alternatives, we further propose two-step procedures with a preliminary feature screening step. Theoretical properties of the proposed tests are investigated. Through extensive numerical experiments on synthetic data sets and an human acute lymphoblastic leukemia gene expression data set, we illustrate the performance of the new tests and how they may provide assistance on detecting disease-associated gene-sets. The proposed methods have been implemented in an R-package HDtest and are available on CRAN. © 2017, The International Biometric Society.

Improving Study Habits of Junior High School Students Through Self-Management versus Group Discussion

Science.gov (United States)

Harris, Mary B.; Trujillo, Amaryllis E.

1975-01-01

Both a self-management approach, teaching the principles of behavior modification and self-control (n=36), and a group-discussion technique, involving discussion of study habits and problems (n=41), led to improvements in grade point averages compared with a no-treatment control group (n=36) for low-achieving junior high school students. (Author)

Estimating High-Dimensional Time Series Models

DEFF Research Database (Denmark)

Medeiros, Marcelo C.; Mendes, Eduardo F.

We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. We assume both the number of covariates in the model and candidate variables can increase with the number of observations and the number of candidate variables is, possibly......, larger than the number of observations. We show the adaLASSO consistently chooses the relevant variables as the number of observations increases (model selection consistency), and has the oracle property, even when the errors are non-Gaussian and conditionally heteroskedastic. A simulation study shows...

High-Dimensional Quantum Information Processing with Linear Optics

Science.gov (United States)

Fitzpatrick, Casey A.

Quantum information processing (QIP) is an interdisciplinary field concerned with the development of computers and information processing systems that utilize quantum mechanical properties of nature to carry out their function. QIP systems have become vastly more practical since the turn of the century. Today, QIP applications span imaging, cryptographic security, computation, and simulation (quantum systems that mimic other quantum systems). Many important strategies improve quantum versions of classical information system hardware, such as single photon detectors and quantum repeaters. Another more abstract strategy engineers high-dimensional quantum state spaces, so that each successful event carries more information than traditional two-level systems allow. Photonic states in particular bring the added advantages of weak environmental coupling and data transmission near the speed of light, allowing for simpler control and lower system design complexity. In this dissertation, numerous novel, scalable designs for practical high-dimensional linear-optical QIP systems are presented. First, a correlated photon imaging scheme using orbital angular momentum (OAM) states to detect rotational symmetries in objects using measurements, as well as building images out of those interactions is reported. Then, a statistical detection method using chains of OAM superpositions distributed according to the Fibonacci sequence is established and expanded upon. It is shown that the approach gives rise to schemes for sorting, detecting, and generating the recursively defined high-dimensional states on which some quantum cryptographic protocols depend. Finally, an ongoing study based on a generalization of the standard optical multiport for applications in quantum computation and simulation is reported upon. The architecture allows photons to reverse momentum inside the device. This in turn enables realistic implementation of controllable linear-optical scattering vertices for

An investigation on a two-dimensional problem of Mode-I crack in a thermoelastic medium

Science.gov (United States)

Kant, Shashi; Gupta, Manushi; Shivay, Om Namha; Mukhopadhyay, Santwana

2018-04-01

In this work, we consider a two-dimensional dynamical problem of an infinite space with finite linear Mode-I crack and employ a recently proposed heat conduction model: an exact heat conduction with a single delay term. The thermoelastic medium is taken to be homogeneous and isotropic. However, the boundary of the crack is subjected to a prescribed temperature and stress distributions. The Fourier and Laplace transform techniques are used to solve the problem. Mathematical modeling of the present problem reduces the solution of the problem into the solution of a system of four dual integral equations. The solution of these equations is equivalent to the solution of the Fredholm's integral equation of the first kind which has been solved by using the regularization method. Inverse Laplace transform is carried out by using the Bellman method, and we obtain the numerical solution for all the physical field variables in the physical domain. Results are shown graphically, and we highlight the effects of the presence of crack in the behavior of thermoelastic interactions inside the medium in the present context, and its results are compared with the results of the thermoelasticity of type-III.

A survey on coordinate metrology using dimensional X-ray CT

International Nuclear Information System (INIS)

Matsuzaki, Kazuya

2016-01-01

X-ray computed tomography (X-ray CT) has been occupying indispensable position in geometrical and dimensional measurements in industry, which is capable of measuring both external and internal dimensions of industrial products. Since dimensional X-ray CT has problems about ensuring traceability and estimating uncertainty, requirement of developing measurement standard for dimensional X-ray CT is increasing. Some of national metrology institutes (NMIs) including NMIJ have been working on developing measurement standard. In this report, the background of coordinate metrology using dimensional X-ray CT is reviewed. Then, measurement error sources are discussed. Finally, the plan to develop high accuracy dimensional X-ray CT is presented. (author)

Similarity measurement method of high-dimensional data based on normalized net lattice subspace

Institute of Scientific and Technical Information of China (English)

Li Wenfa; Wang Gongming; Li Ke; Huang Su

2017-01-01

The performance of conventional similarity measurement methods is affected seriously by the curse of dimensionality of high-dimensional data.The reason is that data difference between sparse and noisy dimensionalities occupies a large proportion of the similarity, leading to the dissimilarities between any results.A similarity measurement method of high-dimensional data based on normalized net lattice subspace is proposed.The data range of each dimension is divided into several intervals, and the components in different dimensions are mapped onto the corresponding interval.Only the component in the same or adjacent interval is used to calculate the similarity.To validate this meth-od, three data types are used, and seven common similarity measurement methods are compared. The experimental result indicates that the relative difference of the method is increasing with the di-mensionality and is approximately two or three orders of magnitude higher than the conventional method.In addition, the similarity range of this method in different dimensions is [0, 1], which is fit for similarity analysis after dimensionality reduction.

Generating Lie Point Symmetry Groups of (2+1)-Dimensional Broer-Kaup Equation via a Simple Direct Method

International Nuclear Information System (INIS)

Ma Hongcai

2005-01-01

Using the (2+1)-dimensional Broer-Kaup equation as an simple example, a new direct method is developed to find symmetry groups and symmetry algebras and then exact solutions of nonlinear mathematical physical equations.

A model problem for restricted-data gamma ray emission tomography of highly active nuclear waste

International Nuclear Information System (INIS)

Cattle, Brian A.

2007-01-01

This paper develops the work of Cattle et al. [Cattle, B.A., Fellerman, A.S., West, R.M., 2004. On the detection of solid deposits using gamma ray emission tomography with limited data. Measurement Science and Technology 15, 1429-1439] by considering a generalization of the model employed therein. The focus of the work is the gamma ray tomographic analysis of high-level waste processing. The work in this paper considers a two-dimensional model for the measurement of gamma ray photon flux, as opposed to the previous one-dimensional analysis via the integrated Beer-Lambert law. The mathematical inverse problem that arises in determining physical quantities from the photon count measurements is tackled using Bayesian statistical methods that are implemented computationally using a Markov chain Monte Carlo (MCMC) approach. In a further new development, the effect of the degree of collimation of the detector on the reliability of the solutions is also considered

Determinable solutions for one-dimensional quantum potentials: scattering, quasi-bound and bound-state problems

International Nuclear Information System (INIS)

Lee, Hwasung; Lee, Y J

2007-01-01

We derive analytic expressions of the recursive solutions to Schroedinger's equation by means of a cutoff-potential technique for one-dimensional piecewise-constant potentials. These solutions provide a method for accurately determining the transmission probabilities as well as the wavefunction in both classically accessible regions and inaccessible regions for any barrier potentials. It is also shown that the energy eigenvalues and the wavefunctions of bound states can be obtained for potential-well structures by exploiting this method. Calculational results of illustrative examples are shown in order to verify this method for treating barrier and potential-well problems

High dimensional model representation method for fuzzy structural dynamics

Science.gov (United States)

Adhikari, S.; Chowdhury, R.; Friswell, M. I.

2011-03-01

Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.

The Role of Content Knowledge in Ill-Structured Problem Solving for High School Physics Students

Science.gov (United States)

Milbourne, Jeff; Wiebe, Eric

2018-02-01

While Physics Education Research has a rich tradition of problem-solving scholarship, most of the work has focused on more traditional, well-defined problems. Less work has been done with ill-structured problems, problems that are better aligned with the engineering and design-based scenarios promoted by the Next Generation Science Standards. This study explored the relationship between physics content knowledge and ill-structured problem solving for two groups of high school students with different levels of content knowledge. Both groups of students completed an ill-structured problem set, using a talk-aloud procedure to narrate their thought process as they worked. Analysis of the data focused on identifying students' solution pathways, as well as the obstacles that prevented them from reaching "reasonable" solutions. Students with more content knowledge were more successful reaching reasonable solutions for each of the problems, experiencing fewer obstacles. These students also employed a greater variety of solution pathways than those with less content knowledge. Results suggest that a student's solution pathway choice may depend on how she perceives the problem.

Interface between path and orbital angular momentum entanglement for high-dimensional photonic quantum information.

Science.gov (United States)

Fickler, Robert; Lapkiewicz, Radek; Huber, Marcus; Lavery, Martin P J; Padgett, Miles J; Zeilinger, Anton

2014-07-30

Photonics has become a mature field of quantum information science, where integrated optical circuits offer a way to scale the complexity of the set-up as well as the dimensionality of the quantum state. On photonic chips, paths are the natural way to encode information. To distribute those high-dimensional quantum states over large distances, transverse spatial modes, like orbital angular momentum possessing Laguerre Gauss modes, are favourable as flying information carriers. Here we demonstrate a quantum interface between these two vibrant photonic fields. We create three-dimensional path entanglement between two photons in a nonlinear crystal and use a mode sorter as the quantum interface to transfer the entanglement to the orbital angular momentum degree of freedom. Thus our results show a flexible way to create high-dimensional spatial mode entanglement. Moreover, they pave the way to implement broad complex quantum networks where high-dimensionally entangled states could be distributed over distant photonic chips.

Using the Solving Problems Together Psychoeducational Group Counseling Model as an Intervention for Negative Peer Pressure

Science.gov (United States)

Hall, Kimberly R.; Rushing, Jeri Lynn; Khurshid, Ayesha

2011-01-01

Problem-focused interventions are considered to be one of the most effective group counseling strategies with adolescents. This article describes a problem-focused group counseling model, Solving Problems Together (SPT), that focuses on working with students who struggle with negative peer pressure. Adapted from the teaching philosophy of…

A block-iterative nodal integral method for forced convection problems

International Nuclear Information System (INIS)

Decker, W.J.; Dorning, J.J.

1992-01-01

A new efficient iterative nodal integral method for the time-dependent two- and three-dimensional incompressible Navier-Stokes equations has been developed. Using the approach introduced by Azmy and Droning to develop nodal mehtods with high accuracy on coarse spatial grids for two-dimensional steady-state problems and extended to coarse two-dimensional space-time grids by Wilson et al. for thermal convection problems, we have developed a new iterative nodal integral method for the time-dependent Navier-Stokes equations for mechanically forced convection. A new, extremely efficient block iterative scheme is employed to invert the Jacobian within each of the Newton-Raphson iterations used to solve the final nonlinear discrete-variable equations. By taking advantage of the special structure of the Jacobian, this scheme greatly reduces memory requirements. The accuracy of the overall method is illustrated by appliying it to the time-dependent version of the classic two-dimensional driven cavity problem of computational fluid dynamics

On nonlinear equations associated with Lie algebras of diffeomorphism groups of two-dimensional manifolds

International Nuclear Information System (INIS)

Kashaev, R.M.; Savel'ev, M.V.; Savel'eva, S.A.

1990-01-01

Nonlinear equations associated through a zero curvature type representation with Lie algebras S 0 Diff T 2 and of infinitesimal diffeomorphisms of (S 1 ) 2 , and also with a new infinite-dimensional Lie algebras. In particular, the general solution (in the sense of the Goursat problem) of the heavently equation which describes self-dual Einstein spaces with one rotational Killing symmetry is discussed, as well as the solutions to a generalized equation. The paper is supplied with Appendix containing the definition of the continuum graded Lie algebras and the general construction of the nonlinear equations associated with them. 11 refs

Saving Face: Managing Rapport in a Problem-Based Learning Group

Science.gov (United States)

Robinson, Leslie; Harris, Ann; Burton, Rob

2015-01-01

This qualitative study investigated the complex social aspects of communication required for students to participate effectively in Problem-Based Learning and explored how these dynamics are managed. The longitudinal study of a group of first-year undergraduates examined interactions using Rapport Management as a framework to analyse communication…

Reply to "Comment on 'Calculations for the one-dimensional soft Coulomb problem and the hard Coulomb limit' ".

Science.gov (United States)

Gebremedhin, Daniel H; Weatherford, Charles A

2015-02-01

This is a response to the comment we received on our recent paper "Calculations for the one-dimensional soft Coulomb problem and the hard Coulomb limit." In that paper, we introduced a computational algorithm that is appropriate for solving stiff initial value problems, and which we applied to the one-dimensional time-independent Schrödinger equation with a soft Coulomb potential. We solved for the eigenpairs using a shooting method and hence turned it into an initial value problem. In particular, we examined the behavior of the eigenpairs as the softening parameter approached zero (hard Coulomb limit). The commenters question the existence of the ground state of the hard Coulomb potential, which we inferred by extrapolation of the softening parameter to zero. A key distinction between the commenters' approach and ours is that they consider only the half-line while we considered the entire x axis. Based on mathematical considerations, the commenters consider only a vanishing solution function at the origin, and they question our conclusion that the ground state of the hard Coulomb potential exists. The ground state we inferred resembles a δ(x), and hence it cannot even be addressed based on their argument. For the excited states, there is agreement with the fact that the particle is always excluded from the origin. Our discussion with regard to the symmetry of the excited states is an extrapolation of the soft Coulomb case and is further explained herein.

Elucidating high-dimensional cancer hallmark annotation via enriched ontology.

Science.gov (United States)

Yan, Shankai; Wong, Ka-Chun

2017-09-01

Cancer hallmark annotation is a promising technique that could discover novel knowledge about cancer from the biomedical literature. The automated annotation of cancer hallmarks could reveal relevant cancer transformation processes in the literature or extract the articles that correspond to the cancer hallmark of interest. It acts as a complementary approach that can retrieve knowledge from massive text information, advancing numerous focused studies in cancer research. Nonetheless, the high-dimensional nature of cancer hallmark annotation imposes a unique challenge. To address the curse of dimensionality, we compared multiple cancer hallmark annotation methods on 1580 PubMed abstracts. Based on the insights, a novel approach, UDT-RF, which makes use of ontological features is proposed. It expands the feature space via the Medical Subject Headings (MeSH) ontology graph and utilizes novel feature selections for elucidating the high-dimensional cancer hallmark annotation space. To demonstrate its effectiveness, state-of-the-art methods are compared and evaluated by a multitude of performance metrics, revealing the full performance spectrum on the full set of cancer hallmarks. Several case studies are conducted, demonstrating how the proposed approach could reveal novel insights into cancers. https://github.com/cskyan/chmannot. Copyright © 2017 Elsevier Inc. All rights reserved.

Multi-Scale Factor Analysis of High-Dimensional Brain Signals

KAUST Repository

Ting, Chee-Ming; Ombao, Hernando; Salleh, Sh-Hussain

2017-01-01

In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive

A two-dimensional, semi-analytic expansion method for nodal calculations

International Nuclear Information System (INIS)

Palmtag, S.P.

1995-08-01

Most modern nodal methods used today are based upon the transverse integration procedure in which the multi-dimensional flux shape is integrated over the transverse directions in order to produce a set of coupled one-dimensional flux shapes. The one-dimensional flux shapes are then solved either analytically or by representing the flux shape by a finite polynomial expansion. While these methods have been verified for most light-water reactor applications, they have been found to have difficulty predicting the large thermal flux gradients near the interfaces of highly-enriched MOX fuel assemblies. A new method is presented here in which the neutron flux is represented by a non-seperable, two-dimensional, semi-analytic flux expansion. The main features of this method are (1) the leakage terms from the node are modeled explicitly and therefore, the transverse integration procedure is not used, (2) the corner point flux values for each node are directly edited from the solution method, and a corner-point interpolation is not needed in the flux reconstruction, (3) the thermal flux expansion contains hyperbolic terms representing analytic solutions to the thermal flux diffusion equation, and (4) the thermal flux expansion contains a thermal to fast flux ratio term which reduces the number of polynomial expansion functions needed to represent the thermal flux. This new nodal method has been incorporated into the computer code COLOR2G and has been used to solve a two-dimensional, two-group colorset problem containing uranium and highly-enriched MOX fuel assemblies. The results from this calculation are compared to the results found using a code based on the traditional transverse integration procedure

Simulation and Analysis of Converging Shock Wave Test Problems

Energy Technology Data Exchange (ETDEWEB)

Ramsey, Scott D. [Los Alamos National Laboratory; Shashkov, Mikhail J. [Los Alamos National Laboratory

2012-06-21

Results and analysis pertaining to the simulation of the Guderley converging shock wave test problem (and associated code verification hydrodynamics test problems involving converging shock waves) in the LANL ASC radiation-hydrodynamics code xRAGE are presented. One-dimensional (1D) spherical and two-dimensional (2D) axi-symmetric geometric setups are utilized and evaluated in this study, as is an instantiation of the xRAGE adaptive mesh refinement capability. For the 2D simulations, a 'Surrogate Guderley' test problem is developed and used to obviate subtleties inherent to the true Guderley solution's initialization on a square grid, while still maintaining a high degree of fidelity to the original problem, and minimally straining the general credibility of associated analysis and conclusions.

Meeting the expectations of chronic tinnitus patients: comparison of a structured group therapy program for tinnitus management with a problem-solving group.

Science.gov (United States)

Wise, K; Rief, W; Goebel, G

1998-06-01

Two different group treatments were evaluated in 144 in-patients suffering from impairment due to chronic tinnitus. A tinnitus management therapy (TMT) was developed using principles of cognitive-behavioral therapy and compared with problem solving group therapy. Self-ratings were used to evaluate the help patients found in dealing with life problems and tinnitus as well as the degree to which they felt they were being properly treated and taken seriously. Patients showed significantly more satisfaction with the TMT group and evaluated the help they found in coping with tinnitus and life problems significantly higher. Thus, in the light of unsatisfactory medical solutions and the poor acceptance of some psychological treatments for tinnitus, TMT appears to be an acceptable and helpful treatment program.

Perceived body weight, eating and exercise problems of different groups of women.

Science.gov (United States)

Coker, Elise; Telfer, James; Abraham, Suzanne

2012-10-01

To compare prevalence of problems with body weight, eating and exercise (past or present) of female psychiatric inpatients with routine care, gynaecological and obstetric female outpatients, and eating disorder inpatients. One thousand and thirty-eight females aged 18-55 years from routine care (n=99), gynaecological (n=263) and obstetric (n=271) outpatient clinics, and eating disorder (n=223) and general psychiatric units (n=182) participated. Participants self-reported past or current problems with weight, eating and exercise using a short survey. A sub-sample of women completed the Eating and Exercise Examination (EEE) which includes the Quality of Life for Eating Disorders (QOL ED). The prevalence of self-reported problems controlling weight (52%), disordered eating and eating disorders (43%) for the psychiatric patients was significantly greater than for the routine care and gynaecological and obstetrics outpatients. The psychiatric group had a significantly higher mean body mass index (BMI) of 27.3 kg/m(2) (standard deviation (SD)=6.7) and prevalence of self-reported obesity (28%) than the other groups. Treatment of women with psychiatric problems should include assessment and concurrent attention to body weight, eating disorder and exercise problems in association with appropriate medical, psychiatric, psychological and medication treatment of their presenting disorder.

Epidemiology of drinking, alcohol use disorders, and related problems in US ethnic minority groups.

Science.gov (United States)

Caetano, Raul; Vaeth, Patrice A C; Chartier, Karen G; Mills, Britain A

2014-01-01

This chapter reviews selected epidemiologic studies on drinking and associated problems among US ethnic minorities. Ethnic minorities and the White majority group exhibit important differences in alcohol use and related problems, including alcohol use disorders. Studies show a higher rate of binge drinking, drinking above guidelines, alcohol abuse, and dependence for major ethnic and racial groups, notably, Blacks, Hispanics, and American Indians/Alaskan Natives. Other problems with a higher prevalence in certain minority groups are, for example, cancer (Blacks), cirrhosis (Hispanics), fetal alcohol syndrome (Blacks and American Indians/Alaskan Natives), drinking and driving (Hispanics, American Indians/Alaskan Natives). There are also considerable differences in rates of drinking and problems within certain ethnic groups such as Hispanics, Asian Americans, and American Indians/Alaskan Natives. For instance, among Hispanics, Puerto Ricans and Mexican Americans drink more and have higher rates of disorders such as alcohol abuse and dependence than Cuban Americans. Disparities also affect the trajectory of heavy drinking and the course of alcohol dependence among minorities. Theoretic accounts of these disparities generally attribute them to the historic experience of discrimination and to minority socioeconomic disadvantages at individual and environmental levels. © 2014 Elsevier B.V. All rights reserved.

One-way functions based on the discrete logarithm problem in the groups meeting conditions C(3-T (6

Directory of Open Access Journals (Sweden)

N. V. Bezverkhniy

2014-01-01

Full Text Available In this work we are consider a possibility to create schemes of open key distribution in the groups meeting conditions C(3-T(6. Our constructions use the following algorithms.1. The algorithm that solves the membership problem for cyclic subgroups, also known as the discrete logarithm problem.2. The algorithm that solves the word problem in this class of groups.Our approach is based on the geometric methods of combinatorial group theory (the method of diagrams in groups.In a cryptographic scheme based on the open key distribution one-way functions are used, i.e. functions direct calculation of which must be much easier than that of the inverse one. Our task was to construct a one-way function using groups with small cancelation conditions C(3-T(6 and to compare the calculation complexity of this function with the calculation complexity of its inverse.P.W. Shor has shown in the paper that there exists a polynomial algorithm that can be implemented in a quantum computer to solve the discrete logarithm problem in the groups of units of finite fields and the rings of congruences mod n. This stimulated a series of investigations trying to find alternative complicated mathematical problems that can be used for construction of new asymmetric cryptosystems. For example, open key distribution systems based on the conjugacy problem in matrix groups and the braid groups were proposed.In the other papers the constructions used the discrete logarithm problem in the groups of inner automorphisms of semi-direct products of SL(2,Z and Zp and GL(2,Zp and Zp. groups. The paper of E. Sakalauskas, P. Tvarijonas, A. Raulinaitis proposed a scheme that uses a composition of two problems of group theory, namely the conjugacy problem and the discrete logarithm problem.Our results show that the scheme that we propose is of polynomial complexity. Therefore its security is not sufficient for further applications in communications. However the security can be improved

Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs

Energy Technology Data Exchange (ETDEWEB)

Liao, Qifeng, E-mail: liaoqf@shanghaitech.edu.cn [School of Information Science and Technology, ShanghaiTech University, Shanghai 200031 (China); Lin, Guang, E-mail: guanglin@purdue.edu [Department of Mathematics & School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907 (United States)

2016-07-15

In this paper we present a reduced basis ANOVA approach for partial deferential equations (PDEs) with random inputs. The ANOVA method combined with stochastic collocation methods provides model reduction in high-dimensional parameter space through decomposing high-dimensional inputs into unions of low-dimensional inputs. In this work, to further reduce the computational cost, we investigate spatial low-rank structures in the ANOVA-collocation method, and develop efficient spatial model reduction techniques using hierarchically generated reduced bases. We present a general mathematical framework of the methodology, validate its accuracy and demonstrate its efficiency with numerical experiments.

Smooth controllability of infinite-dimensional quantum-mechanical systems

International Nuclear Information System (INIS)

Wu, Re-Bing; Tarn, Tzyh-Jong; Li, Chun-Wen

2006-01-01

Manipulation of infinite-dimensional quantum systems is important to controlling complex quantum dynamics with many practical physical and chemical backgrounds. In this paper, a general investigation is casted to the controllability problem of quantum systems evolving on infinite-dimensional manifolds. Recognizing that such problems are related with infinite-dimensional controllability algebras, we introduce an algebraic mathematical framework to describe quantum control systems possessing such controllability algebras. Then we present the concept of smooth controllability on infinite-dimensional manifolds, and draw the main result on approximate strong smooth controllability. This is a nontrivial extension of the existing controllability results based on the analysis over finite-dimensional vector spaces to analysis over infinite-dimensional manifolds. It also opens up many interesting problems for future studies

Renormalization group critical frontier of the three-dimensional bond-dilute Ising ferromagnet

International Nuclear Information System (INIS)

Chao, N.-C.; Schwaccheim, G.; Tsallis, C.

1981-01-01

The critical frontier (as well as the thermal type critical exponents) associated to the quenched bond-dilute spin - 1/2 Ising ferromagnet in the simple cubic lattice is approximately calculated within a real space renormalization group framework in two different versions. Both lead to qualitatively satisfactory critical frontiers, although one of them provides an unphysical fixed point (which seem to be related to the three-dimensionality of the system) besides the expected pure ones; its effects tend to disappear for increasingly large clusters. Through an extrapolation procedure the (unknown) critical frontier is approximately located. (Author) [pt

Junior High School Students’ Perception about Simple Environmental Problem as an Impact of Problem based Learning

Science.gov (United States)

Tapilouw, M. C.; Firman, H.; Redjeki, S.; Chandra, D. T.

2017-09-01

Environmental problem is a real problem that occur in student’s daily life. Junior high school students’ perception about environmental problem is interesting to be investigated. The major aim of this study is to explore junior high school students’ perception about environmental problems around them and ways to solve the problem. The subject of this study is 69 Junior High School Students from two Junior High School in Bandung. This study use two open ended question. The core of first question is environmental problem around them (near school or house). The core of second question is the way to prevent or to solve the problem. These two question are as an impact of problem based learning in science learning. There are two major findings in this study. The first finding, based on most students’ perception, plastic waste cause an environmental problem. The second finding, environmental awareness can be a solution to prevent environmental pollution. The third finding, most student can classify environmental pollution into land, water and air pollution. We can conclude that Junior High School Students see the environmental problem as a phenomenon and teacher can explore environmental problem to guide the way of preventing and resolving environmental problem.

GPU Implementation of High Rayleigh Number Three-Dimensional Mantle Convection

Science.gov (United States)

Sanchez, D. A.; Yuen, D. A.; Wright, G. B.; Barnett, G. A.

2010-12-01

Although we have entered the age of petascale computing, many factors are still prohibiting high-performance computing (HPC) from infiltrating all suitable scientific disciplines. For this reason and others, application of GPU to HPC is gaining traction in the scientific world. With its low price point, high performance potential, and competitive scalability, GPU has been an option well worth considering for the last few years. Moreover with the advent of NVIDIA's Fermi architecture, which brings ECC memory, better double-precision performance, and more RAM to GPU, there is a strong message of corporate support for GPU in HPC. However many doubts linger concerning the practicality of using GPU for scientific computing. In particular, GPU has a reputation for being difficult to program and suitable for only a small subset of problems. Although inroads have been made in addressing these concerns, for many scientists GPU still has hurdles to clear before becoming an acceptable choice. We explore the applicability of GPU to geophysics by implementing a three-dimensional, second-order finite-difference model of Rayleigh-Benard thermal convection on an NVIDIA GPU using C for CUDA. Our code reaches sufficient resolution, on the order of 500x500x250 evenly-spaced finite-difference gridpoints, on a single GPU. We make extensive use of highly optimized CUBLAS routines, allowing us to achieve performance on the order of O( 0.1 ) µs per timestep*gridpoint at this resolution. This performance has allowed us to study high Rayleigh number simulations, on the order of 2x10^7, on a single GPU.

A hybridized K-means clustering approach for high dimensional ...

African Journals Online (AJOL)

International Journal of Engineering, Science and Technology ... Due to incredible growth of high dimensional dataset, conventional data base querying methods are inadequate to extract useful information, so researchers nowadays ... Recently cluster analysis is a popularly used data analysis method in number of areas.

Two-dimensional wave propagation in layered periodic media

KAUST Repository

Quezada de Luna, Manuel